Journal of Applied Science Studies - Ozean Publications

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Journal of Applied Science Studies - Ozean Publications

Volume 3, Issue 1

March 2010

Spectra out of Oxygen and Ozone in Dielectric Barrier

Discharge.

M. A. HASSOUBA and N. DAWOOD

Extension Mechanisms Influencing The Adoption Of Sprinkler

Irrigation System In Iran

SEYED JAMAL F.HOSSEINI, YOSRA KHORSAND and SHABALDEEN

SHOKRI

Geoelectric Assessment Of Groundwater Prospect And

Vulnerability Of Overburden Aquifers At Idanre, Southwestern

Nigeria

OMOSUYI, G.O.

Comparative vegetative and foliar epidermal features of three

Paspalum L. species in Edostate, Nigeria.

E.A OGIE-ODIA, A.I MOKWENYE, O. KEKERE and O. TIMOTHY

Digital Moulding of the Solicitations within the Dielectric of

the Transformers and the Evaluation of Life Cycle of the

Insulation Systems

MARIUS-CONSTANTIN POPESCU and CRISTINEL POPESCU

A disconnect congestion detection from TCP to improve the

robustness

ISSA KAMAR and SEIFEDDINE KADRY

Analysis Of Microwave Signal Reception Using Finite

Difference Implementation. (A Case Study Of Akure – Owo

Digital Microwave Link In South Western Nigeria)

OTASOWIE P.O and UBEKU E.U.

Estimation of C factor for soil erosion modeling using NDVI in

Buyukcekmece watershed

AHMET KARABURUN

Journal of

Applied Science

Physiological properties studies on essential oil of Jasminum

grandiflorum L. as affected by some vitamins

RAWIA.A.EID, LOBNA, S. TAHA and SOAD , M.M. IBRAHIM

Effect of zinc and / or iron foliar application on growth and

essential oil of sweet basil (Ocimum basilicum L.) under salt

stress

H.A.H. SAID-AL AHL and ABEER A. MAHMOUD

Growth and yield of Foeniculum vulgare var.azoricum as

influenced by some vitamins and amino acids

S.F. HENDAWY and AZZA A.EZZ EL-DIN

Effect of water stress and potassium humate on the

productivity of oregano plant using saline and fresh water

irrigation

H.A.H. SAID-AL AHL and M.S. HUSSEIN

Influence of Foliar Application of Pepton on Growth, Flowering

and Chemical Composition of Helichrysum bracteatum Plants

under Different Irrigation Intervals.

SOAD , M.M. IBRAHIM, LOBNA, S. TAHA and M.M. FARAHAT

Permeability and Porosity Prediction from Wireline logs Using

Neuro-Fuzzy Technique

WAFAA EL-SHAHAT AFIFY and ALAA H. IBRAHIM HASSAN

Response of vegetative growth and chemical constituents of

Schefflera arboricola L. plant to foliar application of inorganic

fertilizer (grow-more) and ammonium nitrate at Nubaria.

MONA, H. MAHGOUB, EL-QUESNI, FATMA E.M. and MAGDA,M.

KANDIL

Statistical Modelling For Outlier Factors

Ahmet KAYA


OZEAN JOURNAL of

APPLIED SCIENCE

A PEER REVIEVED INTERNATIONAL JOURNAL

----------------------------------------------------------------------------------------------------------------------------------------------

Volume 3, Issue 1, March 2010

ONLINE ISSN 1943-2542 PRINTED ISSN: 1943-2429

----------------------------------------------------------------------------------------------------------------------------------------------

Gerald S. Greenberg, Ohio State University, USA

Hakki Yazici, Afyon Kocatepe University, Turkey

Hayati Akyol, Gazi University, Turkey

Hayati Doganay, Ataturk University, Turkey

Laurie Katz, Ohio State University, USA

Lisandra Pedraza, University of Puerto Rico in

Rio Piedras, Puerto Rico

Lutfi Ozav, Usak University, Turkey

Managing Editor

Ali Ozel, Dumlupinar University

Publication Coordinator

Taskin Inan, Dumlupinar University

Editorial Board

Mihai Maxim, Bucharest University, Romania

Ibrahim Atalay, Dokuz Eylul University, Turkey

Ibrahim S. Rahim, National Research Center, Egypt

Janet Rivera, NOVA University, USA

Ramazan Ozey, Marmara University, Turkey

Samara Madrid, Northern Illinois University, USA

Samia Abdel Aziz-Ahmed Sayed, National Research

Center, Egypt

Web: http://www.ozelacademy.com E-mail: editorejes@gmail.com

Copyright © 2008 Ozean Publication, 2141 Baneberry Ct. 43235, Columbus, Ohio, USA


Journal of Applied Sciences 3(1), 2010

OZEAN JOURNAL of

APPLIED SCIENCE

A PEER REVIEVED INTERNATIONAL JOURNAL

---------------------------------------------------------------------------------------------------------------------------------

Volume 3, Issue 1, March 2010

ONLINE ISSN 1943-2542 PRINTED ISSN: 1943-2429

---------------------------------------------------------------------------------------------------------------------------------

Spectra out of Oxygen and Ozone in Dielectric Barrier Discharge.

M. A. HASSOUBA and N. DAWOOD

Extension Mechanisms Influencing The Adoption Of Sprinkler Irrigation System In Iran

SEYED JAMAL F.HOSSEINI, YOSRA KHORSAND and SHABALDEEN SHOKRI

Geoelectric Assessment Of Groundwater Prospect And Vulnerability Of Overburden Aquifers At

Idanre, Southwestern Nigeria

OMOSUYI, G.O.

Comparative vegetative and foliar epidermal features of three Paspalum L. species in Edostate,

Nigeria.

E.A OGIE-ODIA, A.I MOKWENYE, O. KEKERE and O. TIMOTHY

Digital Moulding of the Solicitations within the Dielectric of the Transformers and the Evaluation of

Life Cycle of the Insulation Systems

MARIUS-CONSTANTIN POPESCU and CRISTINEL POPESCU

A disconnect congestion detection from TCP to improve the robustness

ISSA KAMAR and SEIFEDDINE KADRY

Analysis Of Microwave Signal Reception Using Finite Difference Implementation. (A Case Study Of

Akure – Owo Digital Microwave Link In South Western Nigeria)

OTASOWIE P.O and UBEKU E.U.

Estimation of C factor for soil erosion modeling using NDVI in Buyukcekmece watershed

AHMET KARABURUN

Physiological properties studies on essential oil of Jasminum grandiflorum L. as affected by some

vitamins

RAWIA.A.EID, LOBNA, S. TAHA and SOAD , M.M. IBRAHIM

Effect of zinc and / or iron foliar application on growth and essential oil of sweet basil (Ocimum

basilicum L.) under salt stress

H.A.H. SAID-AL AHL and ABEER A. MAHMOUD

Growth and yield of Foeniculum vulgare var.azoricum as influenced by some vitamins and amino

acids

S.F. HENDAWY and AZZA A.EZZ EL-DIN


Journal of Applied Sciences 3(1), 2010

Effect of water stress and potassium humate on the productivity of oregano plant using saline and

fresh water irrigation

H.A.H. SAID-AL AHL and M.S. HUSSEIN

Influence of Foliar Application of Pepton on Growth, Flowering and Chemical Composition of

Helichrysum bracteatum Plants under Different Irrigation Intervals.

SOAD , M.M. IBRAHIM, LOBNA, S. TAHA and M.M. FARAHAT

Permeability and Porosity Prediction from Wireline logs Using Neuro-Fuzzy Technique

WAFAA EL-SHAHAT AFIFY and ALAA H. IBRAHIM HASSAN

Response of vegetative growth and chemical constituents of Schefflera arboricola L. plant to foliar

application of inorganic fertilizer (grow-more) and ammonium nitrate at Nubaria.

MONA, H. MAHGOUB, EL-QUESNI, FATMA E.M. and MAGDA,M. KANDIL

Statistical Modelling For Outlier Factors

Ahmet Kaya

Web: http://www.ozelacademy.com E-mail: editorejes@gmail.com

Copyright © 2008 Ozean Publication, 2141 Baneberry Ct. 43235, Columbus, Ohio, USA

A peer revieved international journal

ONLINE ISSN 1943-2542 PRINTED ISSN: 1943-2429

http://ozelacademy.com/ojas.htm


Journal of Applied Sciences 3(1), 2010


Ozean Journal of Applied Sciences 3(1), 2010

Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Spectra out of Oxygen and Ozone

in Dielectric Barrier Discharge.

M. A. Hassouba* and N. Dawood

Applied Physics Dept., Faculty of Applied Sciences, Taibah Univ., KSA.

*E-mail address for correspondence: hassouba@yahoo.com

________________________________________________________________________________________

Abstract: Dielectric-barrier discharges (DBD) are very attractive for industrial applications because they can

provide nonequilibrium plasma conditions at about atmospheric pressure. DBD is an excellent source of ideal

energetic electrons with 1–10 eV and high density. Its unique advantageous is to generate low excited atomic

and molecular species, free radicals and excimers with several electron volt energy.Spectra out of ozone

synthesis system, in dielectric barrier discharge (DBD) using oxygen gas, have been detected in the range of 300

to 400 nm. The dependence of spectral intensity on the discharge voltage and the oxygen pressure has been

studied. The half-width of the detected lines was found to be within 20 A o approximately. Spectroscopic

technique is a well-known technique for the measurement of the mean electron temperature in the gas discharge.

The electron temperature within the microdischarge has been estimated by using the relative intensity of the line

to line ratio technique of the identified spectral lines. An average mean electron temperature of 3.6 eV was

obtained and it has been found to be insensitive to the gas pressure variation.

Key Words:- Dielectric Barrier Discharge, Ozone Spectra, Electron Temperature

measurements ,Plasma Spectroscopic Models.

__________________________________________________________________________________________

INTRODUCTION

Dielectric-barrier discharges (silent discharges) combine the ease of atmospheric pressure operation with

nonequilibrium plasma conditions suited for many plasma chemical processes. In most gases at this pressure the

discharge consists of a large number of randomly distributed short-lived microdischarges.. Traditionally mainly

used for industrial ozone production, dielectric-barrier discharges have found additional large volume

applications in surface treatment, high-power CO2 lasers, excimer ultraviolet lamps, pollution control and, most

recently, also in large-area flat plasma display panels. Future applications may include their use in greenhouse

gas control technologies [1].

Many articles [1-7] have been published about the optical emission from DBDs by using other gases such as Xe,

Cl, Ar, He. The dielectric barrier discharges (silent discharge) offer the possibility of building large area and

high intensity UV-sources, for industrial processing.

Burm [8] investigate two plasma sources, an air plasma torch and a nitrogen dielectric barrier discharge. Optical

emission spectroscopy is used to determine the heavy particles and the vibration (electron) temperatures for the

two plasma sources. The two temperatures are measured to obtain an estimation of the deviation from local

thermal equilibrium and to compare the two source configurations which are used for surface treatment.

The present work is originally directed toward the design of a cheap and simple DBD ozonizer [9]. The spectra

out from this system have been detected and the electron temperature of the discharge is determined using the

spectroscopic method.

1


The experiment setup consists of two parts

1- Discharge Cell

Ozean Journal of Applied Sciences 3(1), 2010

EXPERIMENTAL SETUP

In the present work, the cell of the discharge consists of coaxial electrodes. The inner electrode has been made of

brass rod with radii 0.5 cm. The outer electrode is made of graphite coated on the outer wall of a Silica glass

tube, which has been used as a dielectric material and as a window for the study output radiation of the system.

The gap space between the inner electrode and the inner wall of glass tube was 0.175 cm. The length of the

reactor region was 30 cm and the pressure of gas could be controlled by the needle valves, which enable

controlling the flow rate in the system. The pressure inside the discharge tube was measured by using manometer

and gauge model P200-H (RS-497-606) which enables the pressure to be measured in the range from 1 to 2.25

bars within 1 mbar experimental error. The flow rate of oxygen (98.7% purity) has been measured by using a

flow meter (Cole Parmer). Figure (1) shows the present DBD system.

The electric circuit of the discharge is also shown in Fig. (1) which consists of AC power supply (0�220 V , 50

Hz) connected to a high voltage transformer with a variable output, 0�20 kV. In order to measure the applied

potential across the discharge cell, a potential divider has been built, which consists of two resistors in the ratio

of (1/450) connected in parallel with the discharge cell. Only the potential difference across the lower part of the

divider is measured, and then the actual applied potential across the cell can be estimated.

2- The Spectroscopic Setup

Figure (2) shows the present spectroscopic setup, which is controlled by PC computer. The spectroscopic

devices of type Oriel, consists of mono-chromator 25 cm path length and has a diffraction grating of 1200

mm. The relative intensity of lines has been measured by using photo-multiplier (PMT) capable of measuring the

spectra in the range of 185–650 nm. PMT connect to readout system for reading the intensity of light, the readout

capable of current amplification up to 10 9 A. PC computer with interface and stepper motor driver has been used

to control in the motion of the grating, so that it enables to variation of the wavelength one angstrom by step.

1- Spectra of Oxygen in Silent Discharge

RESULTS AND DISCUSSION

The only detectable spectra have been found in the region from 300 to 400 nm. The absorption cross section of

ozone is known to be high in two ranges; Hartly band; 160 - 320 nm and Chappuis band; 420-730 nm [10].

Therefore, no spectra emission could be seen or measured in these two ranges.

Typical spectrums of DBD at different pressure and discharge voltages are shown in Figs. (3-a, b and c).

It is noticed that, the emitted lines could not be detected until the applied potential reached the onset potential

where the ozone starts to build up, which depends on the working gas pressure p, inner electrode distance d and

the type of the dielectric material and its thickness T.

e= e/d =

constant * V/p), where q is the electron charge, V is the applied voltage, d is the gap space distance between the

e is the mean free path of the electrons.

Figure (4) shows a typical graph for the present relation between (VB) and (p*d) in oxygen (right hand side of the

Paschen Curve) under the given conditions where VB is increasing linearly with (p*d). Also as a ozone

composition is a chemical reaction it is therefore the current is the main parameter which controls the number of

ozone reactions that take place in this system. Figure (5) shows the relation between the voltage and the current

flowing in the system at different gas pressures.

2


Ozean Journal of Applied Sciences 3(1), 2010

When the pressure is kept constant the mean free path is constant but if the applied voltage is increased, the

number of electrons capable on excitation and ionization increases. Therefore, it is expected in this case that the

intensity of the emitted lines will increase with the applied potential, [at p=1.25 bar]. Also, when the pressure

increases the collision frequency increases, therefore the intensity of the emitted lines increases.

It can be noticed that the half width of any of these lines is less than 2 nm, which could be, used more or less as a

monochromatic radiation [10]. Such radiation could be easily generated on a large scale for the purpose of

industrial applications [11].

2- Mean Electron Temperature.

Spectroscopic technique is a well-known technique for the measurement of the mean electron temperature in the

gas discharge.

In the present work not all the radiation lines has been identified, although pure oxygen of 98.7% purity has

been used and unfortunately only few lines of them has been identified and were therefore used for the deriving

of the electron temperature.

The line to line relative intensity ratio technique (for the same ionization stage) is used to determine the

mean electron temperature, Te, in silent discharge, according to the following equation [11]:-

Where: -

K is the Boltzmann`s constant, Te is the mean electron temperature, I, I’ are the relative intensity of the two

given lines, �, � ` are the wavelengths of two lines, g, g ` are the statistical weight of two lines, f, f ` are the

oscillator strength of two lines, E` is the excitation energy for the higher ionization stage and E is the excitation

energy for the lower ionization stage. The lines identified are of the wavelengths tabulated in Table (1), together

with their values of the above parameters [11]. The intensities of the identified lines were taken from the

measured discharge spectra in Fig. (3).

Wavelength (�)

A o

'

(E � E)

KTe


3 ' '

I�

g f

ln( )

' 3

I � gf

Table (1) The parameters of the selected lines used in the calculation.

Excitation

Energy (E)

Oscillator

Strength (f)

3

Statistical

Weight (g)

Product of

(f) x (g)

3709.5 45.07 eV 0.0747 1 0.0747

3754.7 36.29 eV 0.277 5 1.385

3911.96 28.71 eV 0.0326 4 0.130

3945 26.45 eV 0.113 4 0.452

In order to derive the mean electron temperature from the above equation two couples of lines have to be chosen

so that their wavelengths are very near to each other, and from the same stage of ionization.

The parameters of these couples of lines were substituted in the equation and hence the mean electron

temperature was calculated and has been tabulated below.

The results for the couple of lines of wavelengths 391.19 nm and 394.5 nm emitted from O + are shown in Table

(2). Also, the results of the couple of lines of wavelengths 370.95 nm and 375.47 nm, which emitted from O ++

are shown in Table (2).


Pressure

(bar)

Ozean Journal of Applied Sciences 3(1), 2010

Table (2) Shows the results for the couple of lines of wavelengths 391.19 nm

and 394.5 nm emitted from O + at different conditions.

Lines 391.19 nm and 394.5 nm Lines 370.9 nm and 375.47 nm

V (dis.)

18 kV

Electron

Temp.(Te)

V(dis.)

13.5 kV

Electron

Temp.(Te)

4

V (dis.)

18 kV

Electron

Temp. (Te)

V(dis.)

13.5 kV

Electron

Temp. (Te)

1.005 3.77 eV 3.6 eV 3.8 eV 3.4 eV

1.25 3.6 eV 3.7 eV 3.6 eV 3.2 eV

1.5 3.7 eV 3.7 eV 3.8 eV 3.4 eV

1.75 3.77 eV 3.8 eV 3.85 eV 3.4 eV

The mean electron temperature has been drawn as a function of gas pressure and applied voltage and is shown in

Fig. (6-a, b).

It can be noticed from Fig. (6-a, b) that the mean electron temperature in the dielectric barrier discharge is nearly

constant at a mean electron temperature is 3.6 eV and does not depend on the gas pressure.

CONCLUSION

The silent discharge is a non-equilibrium discharge which can be operated up to pressures of several bars. It is

industrially used on a large scale for the generation of ozone from air or oxygen. Ozone generators have a typical

power consumption ranging from some kilowatts to several megawatts. The main characteristic of the silent

discharge is that narrow discharge gaps of a few millimeter spacing are used and that at least one of the

electrodes is covered by an insulating layer. For this reason the silent discharge is also referred to as the

"dielectric-barrier discharge" (DBD).

The present work is originally directed toward the design of a cheap and simple DBD ozonizer.

It is noticed that, the emitted lines could not be detected until the applied potential reached the onset potential

where the ozone starts to build up, which depends on the working gas pressure p, inner electrode distance d and

the type of the dielectric material and its thickness T

Spectroscopic technique is a well-known technique for the measurement of the mean electron temperature in the

gas discharge.

It is concluded that, that the mean electron temperature in the dielectric barrier discharge is nearly constant at a

mean electron temperature is 3.6 eV and does not depend on the gas pressure.


Ozean Journal of Applied Sciences 3(1), 2010

FIGURES

Figure (1) shows the discharge Cell.

PC Computer Steeper Motor

P.S. for PMT

A/D Converter Readout Amp.

Figure (2) shows the spectroscopic setup.

5

PMT

Mono- Plasma

chromator Source


Intensity (Arb. Unit)

Silica

p=1.25 bar

V(dis.)=13.5 KV

300 320 340 360 380 400

Wavelength (nm)

Intensity (Arb. Unit)

Ozean Journal of Applied Sciences 3(1), 2010

3

2

2

1

1

CB

BA

0

300 320 340 360 380

Wavelength (nm)

400

6

B

Silica

p.=1.75 bar

V(dis)=18 kV

Figure (3-A, B and C) show the spectra of the discharge at different conditions and at T =0.15 cm, d

= 0.175 cm and L = 30 cm.


Ozean Journal of Applied Sciences 3(1), 2010

Figure (4) shows the relation between V (breakdown) and (pressure*gap space).

Figure (5) shows the relation between I(dis.) and V(dis.) at d=0.175 cm, L=30 cm and

T=0.15 cm

7


Ele.Temp.(eV)

Ele.Temp.(eV)

5

4

3

2

1

0

Ozean Journal of Applied Sciences 3(1), 2010

O(++)

3709.5 A

& 3754.7 A

0.75 1.00 1.25 1.50 1.75 2.00

Pressure (bar)

5

4

3

2

1 O(+)

3911.96

0

& 3954.7 A

0.75 1.00 1.25 1.50 1.75 2.00

Pressure (bar)

Figure-(6-A, B) show the Figure relation between (7-a, the b) electron show the temperature relation and between the pressure the at + electron 13.5 and temperature 18.0 KV an

at 13.5 and 18.0 KV

8

BA

AB


Ozean Journal of Applied Sciences 3(1), 2010

REFERENCES

A.A.Garamoon, F.F.Elakshar and A.M.Nossair, (1999), GEC 52 nd , Virginia, USA, 324.

A.Baulch, (1980), J. Phys. Chem. Ref. Data, 9, 296.

H.R.Griem, (1964), Plasma Spectroscopy , McGraw-Hill, New York., p.382..

Haile Lei, Yongjian Tang, Jun Li, and Jiangshan Luo, (2007), Appl. Phys. Lett. 91, 113119.

K.G. Kostov; R. Y. Honda; L.M.S. Alves and M.E. Kayama Braz, (2009), J. Phys., 39, 2.

K.T.A. Burm, (2005), Contrib. Plasma Phys., 45, 54.

M.P.Milden, (2001), J. of Phys. D: Appl. Phys. 34, L1.

Takaaki Tomai, Tsuyohito Ito and Kazuo Terashima, (2006), Thin Solid Films, 507 , 409.

U.Kogelschatz, (1997), J. de Physique IV, 7, C4-47 to C4-66.

U.Kogelschatz, (1997), ICPIG XXIII, Toulouse, France, 1.

Ulrich Kogelschatz², Baldur Eliasson and Walter Egli, (1999), Pure Appl. Chem., 71, 1819.

Young Sun Mok, (2005), XXVIIth ICPIG, Eindhoven, the Netherlands, 18-22 July, PP. 18.

9


Ozean Journal of Applied Sciences 3(1), 2010

Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Extension mechanisms influencing the adoption of sprinkler irrigation system in Iran

Seyed Jamal F.Hosseini*, Yosra Khorsand** and Shabaldeen Shokri***

*Islamic Azad University, Science and Research Branch Tehran, Iran

**Islamic Azad University, Birjand branch Birjand, Iran

***Department of Agricultural development Islamic Azad University, Science and Research Branch

Tehran, Iran

*Email address for correspondence: jamalfhosseini@yahoo.com

__________________________________________________________________________________________

Abstract: Horticultural producers were surveyed in order to explore their perception about the role of extension

mechanisms in adopting the sprinkler irrigation system in Iran. The methodology used in this study involved a

combination of descriptive and quantitative research. The total population for this study was 150 gardeners who

adopted the sprinkler irrigation system in Chenaran Township in Khorasan Razavi Province. Based on the

results of the mean score, respondents indicated that visiting extension agents in the service centers was the

most effective individual extension method main in helping them to adopt the sprinkler irrigation systems. It was

also reported from the findings of the study 45% of the variance in the perception of gardeners about the role of

extension mechanisms in adopting the sprinkler irrigation systems could be explained by visiting extension

agents in service centers, extension classes, visiting extension agents in the field and visiting sample farm.

Kewords: Extension Mechanisms, Sprinkler Irrigation System, Iran, Gardener.

__________________________________________________________________________________________

INTRODUCTION

World Bank predicted that by the year 2035, three billion people will live in the tough conditions because of

water shortage (World Bank, 2009). According to the Human Development Report, by the year 2080 climate

change would affect the life of many people throughout the world and more than 1.8 billion people would face

water shortages (UNDP, 2007, p.30).

Today, there are several major issues in connection with the water sector in developing and developed countries

which include: water cycle, quality of life, equality of water, sustainability and human rights (Sohail and Cavill,

2006). In Iran, the policy of government has been to increase agricultural production for various reasons, such as

price stability, improved per capita income and increased need for non-oil foreign exchange resources and this

trend has become an unavoidable reality for agricultural sector. Increasing agricultural production has resulted

in consumption of more water and there is no other way to change the amount of water used which is the

equivalent of 130 billion cubic meters a year unless to use water more efficiently and to adopt new methods of

irrigation.

Consumption of water by agriculture sector in Iran has always been an issue of concerns which caused by high

water losses in farm fields, farms inappropriate shape and size, lack of knowledge of farmers about making

optimum use of water, rapid destruction of water infrastructure, loss in quality of irrigation networks,

inappropriate methods of irrigation, irrigation efficiency and loss of water in irrigation systems (Keshavarz,

2000).

Omani et al (2009) citing Keshavarz, Heydari, and Ashrafi (2003) pointed out that the overall irrigation

efficiency in Iran ranges from 33 to 37%, which is lower than the average for both developing countries (45%)

and developed countries (60%).

11


Ozean Journal of Applied Sciences 3(1), 2010

Unfortunately, inefficient use of water in the past decades has nearly reduced more than 40 meter in

underground water level (Unit, 2005). Currently, the total water consumption is approximately 88.5 bm3, out of

which more than 93% is used in agriculture, while less than 7% is allocated to urban and industrial

consumption. Under the present situation 82.5 bm3 of water is utilized for irrigation on 7.5 million hectares of

land under irrigated agriculture (Ommani & Noorivandi, 2003).

In order to combat this problem, there is need for new technologies and methods to manage water more

efficiently especially in agricultural sector (Karami, Rezaei-Moghaddam, and Ebrahimi., 2006). On one hand a

more comprehensive water management is needed to achieve sustainable development and participatory

mechanism could accelerate this process (Guterstan, 2008). On the other hand the principle of sustainable

development is an essential imperative for the water industry which should be seen as an opportunity not a

limitation (Asheley et al. 2003).

Khorasan Razavi province is among regions in Iran with low rainfall. The amount of evaporation and

transpiration of rainfall in this province is very significant which is 2 to 3 times higher than the average in

country. According to the latest statistics, total volume of water consumption from surface water and

groundwater is 9261.8 million cubic meters and more than 8445 million cubic meters of this amount used in

agricultural sector.

The traditional methods of water management have many problems and the best option currently to use for

irrigating farms is sprinkler irrigation systems. The results of Study show that implementation of this irrigation

method resulted in decreasing rate of water consumption from 12,000 cubic meters in hectare to 6,200 cubic

meters (Vojdani, 2006). Despite, financial facilities which are allocated each year for farmers, the participation

of farmers has not reached to a satisfactory level.

Agricultural extension by its nature has an important role in promoting the adoption of new technologies and

innovations. Extension organizations have a key role in brokering between providers of technologies and

farmers. However, adopting is rarely instantaneous; the technology has to be taught and learned, adapted to

experience, and integrated into production. As is often the case with technological innovation, potential and

expectations can outpace reality (Bonati and Gelb, 2005).

Omani et al (2009) citing Evenson (1997) pointed out to this fact that agricultural extension and education as

achieving its highest economic impact and sustainability in agriculture by providing information to increase

farmers awareness, knowledge, adoption and productivity.

Therefore, understanding the extension mechanisms which would speed up the development and adoption of the

sprinkler irrigation system in the township of Chenaran in Khorasan Razavi Province was investigated in this

research.

MATERIAL AND METHODS

The methodology used in this study involved a combination of descriptive and quantitative research and

included the use of correlation, regression and descriptive analysis as data processing methods. The total

population for this study was 150 gardeners who adopted the sprinkler irrigation system. Data were collected by

using questionnaire and through interview schedules.

A series of in-depth interviews were conducted with some senior experts in the Department of Agriculture and

Power in the Khorasan Razavi Province to develop the questionnaire. The questionnaire included both openended

and fixed-choice questions. The open-ended questions were used to gather information not covered by the

fixed-choice questions and to encourage participants to provide feedback.

Content and face validity were established by a panel of experts consisting of faculty members at Islamic Azad

University, Science and Research Branch and some experts in the Departments of Agriculture and Power. A

pilot study was conducted with 25 specialists who had not been interviewed before the earlier exercise of

determining the reliability of the questionnaire for the study. Computed Cronbach’s Alpha score was 85.0%,

which indicated reliability of the questionnaire.

Independent variables in the study included extension mechanisms and personal characteristics of respondents.

The dependent variable in this research study were the adoption of the sprinkler irrigation system by gardeners...

For measurement of correlation between the independent variables and the dependent variable correlation

coefficients have been utilized and include spearman test of independence.

12


Ozean Journal of Applied Sciences 3(1), 2010

RESULTS

Table 1 summarizes the demographic profile and descriptive statistics of respondents. The results of descriptive

statistics indicated that average age of respondents was 46 years old and majority of respondents did not have

high school diploma. The study shows that average work experience was 19 years and the main occupation of

respondents was farming and gardening. Approximately 43 percent of respondents owned their lands and the

remainder either had a collective ownership or rented the land.

Respondents were asked to respond the question about role of water shortages in implementing sprinkler

irrigation system. As a result, 71 percent of respondents indicated that agricultural water shortage was the main

factor in the implementation of the irrigation system.

The perception of respondents about the sources which help them to acquire information about sprinkler

irrigation systems was displayed in Table 2. The highest mean refers to extension agents (mean=3.58) and the

lowest mean refers to experiment stations (mean=1.59).

The results of perception of respondents about the role of communication channels which would influence the

adoption of sprinkler irrigation systems by gardeners were displayed in Table 2. The results indicated that the

highest mean number refers to extension agents (mean=4.11) and the lowest mean number refers to relatives

(mean=1.67).

The respondents’ perception about the role of extension mechanisms in adopting the sprinkler irrigation systems

was displayed in Table 4. As can be seen from this table, the highest mean refers to visit by extension agents in

agricultural service centers (mean=3.18) and the lowest mean refers to extension workshops (mean=2.57).

Spearman coefficient was employed for measurement of relationships between perceptions of gardeners about

the role of extension mechanisms in adopting the sprinkler irrigation system as dependent variable. Table 5

displays the results which show that there was relationship between perception of respondents about the age,

visiting extension agents in the service centers, extension classes, visiting the sample farm and visiting extension

agents in the field and adopting the sprinkler irrigation system.

Table 6 shows the result for regression analysis by stepwise method. Independent variables that were

significantly related to perception of respondents about role of extension mechanisms in adopting the sprinkler

irrigation system were entered. The result indicates that 45% of the variance in the perception of gardeners

about the role of extension mechanisms in adopting the sprinkler irrigation systems could be explained by

visiting extension agents in service centers, extension classes, visiting extension agents in the field and visiting

sample farm.

CONCLUSION

The perception of gardeners about the role of extension mechanisms in adopting sprinkler irrigation system was

discussed in this article. As the regression analysis showed visiting sample farms, visiting extension agents in

the service centers and field and extension classes caused 45% of variance on the perception of respondents

regarding the role of extension mechanisms in adopting sprinkler irrigation systems. This result is consistent

with Okunade (2007) conclusion in which skill is better acquired through group contact methods. These

methods have the nature of practical demonstration which will help the clientele from desire stage through

conviction and probably into taking action. The individual contact method is considered to be important tool to

help farmers to adopt a new technology. This may be as a result of the nature of the methods of giving

information and deeper understanding of the innovation concerned.

Based on the results of the study by Chizari, etal. (1998) the majority of extension agents believed the result

demonstration were the most effective method for teaching their clientele. Result demonstrations are the

processes of showing farmers the impact of using a particular practice. The second most effective method

identified by extension agents was method demonstration. Method demonstrations typically occur after result

demonstrations.

Based on the results of the mean score, respondents indicated that visiting extension agents in the service centers

was the most effective individual extension method main in helping them to adopt the sprinkler irrigation

systems. The results demonstrated that respondents preferred individual teaching methods compared with group

13


Ozean Journal of Applied Sciences 3(1), 2010

and mass methods. Although all agents use a variety of teaching methods, agricultural agents generally tend to

use more individual methods than the other agents. Farm visits and on-farm demonstrations model the early

farm demonstration method of providing research-based recommendations to the local producer.

IMPLICATIONS

The perception of gardeners about the extension mechanisms in adopting the sprinkler irrigation system was

discussed in this article. The results demonstrated that visiting sample farms and face to face meetings with

extension agents in service center and farms are the most important mechanisms in helping gardeners in

adopting sprinkler irrigation systems. Successful adoption of this technology in Iran will depend on the

appropriate government support and the authorities should develop policies that would overcome the challenges

in adopting this method of irrigation.

In Iran like some of the developing countries, there is not a clear understanding about role of the new methods

of irrigation in sustainable water management in agriculture sector and policy makers have difficulty in

prioritizing the policies and strategies. In this regard, public involvement will enhance and accelerate the

adoption process.

REFERENCES

Ashley, R., Blackwood, D., Butler, D., Davies, J., Jowitt, P., & Smith, H. (2003). Sustainable decision making

for UK water industry. Engineering Sustainability, 1, 41-49.

Bonati, G., and Gelb, E. (2005) 'Evaluating internet for extension in agriculture.' In: gelb, B. And Offer, A.

(ed.), ICT in Agriculture: Perspectives of Technological Innovation, Paris: European Federation for

Information Technologies in Agriculture, Food and the Environment.

Chizari, M., Karbasioun, M., and Lindner, J.R. (1998). Obstacles facing extension agents in the development

and delivery of extension educational programs for adult farmers in the Province of Esfahan, Iran.

Journal of Agricultural Education, 1, 48-54.

Evenson, R. (1997). The economic contributions of agricultural extension to agricultural and rural development.

In Food and Agriculture Organization of the United Nations (eds.) Improving agricultural extension.

FAO. Rom. pp. 27–36.

Guterstam, B. (2008). Toward Sustainable Water Resource Management in Central Asia. [on-line]

Available:www.water.tkk.fi/English/wr/research/global/material/CA_chapters/02-CA_Waters-

Guterstam.pdf

Karami, E., Rezaei-Moghaddam, K., & Ebrahimi, H. (2006). Predicting sprinkler irrigation adoption:

Comparison of models. Journal of Science and Technology of Agricultural and Natural Resources, 1,

90–104.

Keshavarz, A. (2000). Recommendation on policies and programs about water and irrigation in Iran. Tehran:

Agricultural Extension Organization.

Keshavarz, A., Heydari, N., and Ashrafi, S. (2003). Management of agricultural water consumption, drought,

and supply of water for future demands. pp. 42–48. In: Proceedings of the Seventh International

Conference on the Development of Dryland, September 14–17, 2003, Tehran, Iran.

Okunade, E.O. (2007). Effectiveness of extension teaching methods in acquiring knowledge, skills and attitude

by women farmers in Osun State. Journal of Applied Science Research, 4, 282-286.

Ommani, A. R., Chizari, M., Salmanzadeh, C., & Hosaini, J. (2009). Predicting Adoption Behavior of Farmers

Regarding On-Farm Sustainable Water Resources Management (SWRM): Comparison of Models.

Journal of Sustainable Agriculture, 5, 595- 616.

Ommani, A.R., & Noorivandi, A. (2003). Water as food security resource (Crises and Strategies). Jihad Monthly

Scientific, Social and Economic Magazine, 255, 58–66.

14


Ozean Journal of Applied Sciences 3(1), 2010

Sohail, M., and Cavill, S. (2006). Ethics: making it the heart of water supply. Civil Engineering, 5, 11-15.

UNDP. (2007). Human Development Report 2007/2008. [on-line] Available: Http://hrd.undp.org

Vojdani, M. (2006). Assessing factors influencing the adoption of irrigation technologies by farmers in

Township of Bahar. Master Thesis in Agricultural Extension and Education, Tehran, Iran.

World Bank. (2009). Water Resource Management. [on-line] Available :

http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTWAT/0,,contentMDK:21630583~men

uPK:4602445~pagePK:148956~piPK:216618~theSitePK:4602123,00.html

Main Occupation Farming and Gardening (44%) Gardening (24.0%)

Age (year) Mean=46

Work Experience (Year) Mean=19

Educational level Secondary School (75%) Diploma (25%)

Amount of land owned (Hectares) Mean= 10.5

Table 1. Personal Characteristics of Respondents.

Sources Mean and Standard Deviation

15

Mean SD

Extension Agents 3.58 0.959

Rural Cooperatives 2.77 0.886

Agricultural Magazines 2.55 1.347

Agricultural Input suppliers 2.43 0.890

Local Leaders 2.31 1.056

Neighbors 2.13 0.824

Rural Service Centers 2.09 0.928

Relatives 1.67 0.864

Experiment Stations 1.59 1.783

Table 2. Means of respondents’ views about the sources which help them to acquire information about sprinkler

irrigation system (1=Too little; 5=Too much).


Ozean Journal of Applied Sciences 3(1), 2010

Communication Channels Mean and Standard Deviation

Extension Agents 3.80

Television 3.58

Visit the sample farm 3.09

16

Mean SD

1.069

0.959

0.963

Rural organizations 2.77 0.886

Printing Materials 2.63 1.178

Private Sector 2.41 0.881

Local Leaders 2.31 1.563

Radio 2.18 1.063

Neighbors 2.13 0.824

Researchers 2.08 0.900

Relatives 1.67

0.864

Table 3. Means of respondents’ views about the role communication channels which influence the adoption of

sprinkler irrigation systems by gardeners (1=strongly disagree; 5=strongly agree).

ٍ Extension Mechanisms Mean and Standard Deviation

Visiting extension agents in service centers 3.18

Extension Classes 3.17

Visit the sample farm 2.96

Mean SD

1.032

1.042

1.021

Extension films 2.81 1.024

Visiting extension agents in the field 2.78 1.041

Workshops 2.57 1.057

Table 4. Means of respondents’ views about the role of extension mechanisms in adopting sprinkler irrigation

systems by gardeners (1=strongly disagree; 5=strongly agree).

Independent variables Dependent variable Gardeners

r Sig.

Age Adoption of Sprinkler Irrigation System 0.535 0.000**

Workshop Adoption of Sprinkler Irrigation System 0.050 0.550

Visiting Extension Agents in service centers Adoption of Sprinkler Irrigation System 0.329 0.021*

Working Experience Adoption of Sprinkler Irrigation System 0.519 0.000**

Extension Classes Adoption of Sprinkler Irrigation System 0.315 0.025*

Visiting the Sample Farm Adoption of Sprinkler Irrigation System 0.327 0.020*

Extension films Adoption of Sprinkler Irrigation System 0.094 0.562

Visiting extension agents in the field Adoption of Sprinkler Irrigation System 0.306 0.031*

**p


Ozean Journal of Applied Sciences 3(1), 2010

B Beta T Sig.

Constant 0.402 ------- 0.792 0.434

Visiting extension agents in service

centers

0.414 0.386 4.327 0.000

Extension classes 0.226 0.284 3.086 0.004

Visiting extension agents in field 0.197 0.240 2.963 0.005

Visiting the sample farm 0.210 0.292 2.750 0.010

R 2 =0.45

Table 6. Multivariate Regression Analysis (adopting the sprinkler irrigation system as dependent variable).

17


Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Ozean Journal of Applied Sciences 3(1), 2010

GEOELECTRIC ASSESSMENT OF GROUNDWATER PROSPECT AND

VULNERABILITY OF OVERBURDEN AQUIFERS AT IDANRE, SOUTHWESTERN

NIGERIA

OMOSUYI, G.O.

Department of Applied Geophysics, Federal University of Technology,

P.M.B. 704, Akure, Nigeria

E-mail address for correspondence : droluomosuyi@yahoo.com

___________________________________________________________________________________________

Abstract: Idanre and environs, southwestern Nigeria, is characterized by extensive outcrops of crystalline

basement rocks, largely of granite gneiss petrology. Inadequate municipal water supply, coupled with

hydrogeologically difficult nature of the terrain, individuals and corporate bodies indiscriminately sink tube wells

and boreholes within the unconsolidated overburden materials, with glaring lack of concerns for the vulnerability

status of aquifers, and possible environmental risk. Sixty five (65) Schlumberger depth sounding data from the

area were interpreted in order to assess the groundwater prospect, focused on the thickness of the unconsolidated

materials overlying the crystalline bedrock. The resistivity parameter of the geoelectric topmost layer across the

area was also used to assess the vulnerability of the underlying aquifers to near-surface contaminants. The

thickness of the unconsolidated overburden varies from 0.5m to 15.8m, where about 81.5% falls within the 1-5.9m

brackets. This shows that unconsolidated materials are generally not significantly thick and hence of apparently

low groundwater prospect. The topmost geoelectric layer has resistivity mostly within the range of 1-100 Ohm-m

(77%) across the area. Resistivity values within these brackets tend to indicate silt or clay sequence, which can

constitute effective protective geologic barriers for the underlying aquifers. This suggests that aquifers within the

unconsolidated overburden at Idanre are mostly capped by impervious/semi-pervious materials, geologically

protecting the underlying aquifers from near-surface contaminants.

___________________________________________________________________________________________

INTRODUCTION

Groundwater has become immensely important for human water supply in urban and rural areas in developed and

developing nations alike. Despite its importance, there is gross inadequate supply of water at Idanre, the study

area.

Idanre lies within the Precambrian basement complex terrain of southwestern Nigeria (Rahaman, 1988).The

crystalline basement rocks are extensively exposed in the area (Ocan, 1991). In basement terrains, groundwater is

generally believed to occur within the overlying unconsolidated material derived from the in-situ weathering of

rocks, and the fractured/faulted bedrock (Clark, 1985; Jones, 1985; Acworth, 1987; Bala and Ike, 2001). Since the

intrinsic resistivity of the unconsolidated overburden and that of the crystalline basement differs by orders of

magnitude, geoelectric methods are suitable to map the thickness and extent of the overburden (1975; Koefoed,

19


1989; Parasnis, 1997). The electrical resistivity depth sounding is useful in locating areas of maximum aquifer

thickness and serves as a good predictive tool for estimation of borehole depth.

Aquifers in basement complex terrains often occur at shallow depths, thus exposing the water within to

environmental risks, that is, vulnerable to surface or near-surface contaminants. A recent study (Omosehin, 2009)

reveals that the people around Idanre abstracts water from the unconsolidated materials overlying the crystalline

basement through uncontrolled sinking of tube wells, with glaring lack of concern for aquifer vulnerability to

near-surface contaminants and quality status of the groundwater.

This work, in addition to assessing the groundwater prospect of the unconsolidated materials in the area, the

geoelecrtic parameters of the near-surface materials overlying the aquifers were also used to assess the

vulnerability of the near-surface aquifers to near-surface contaminants. The work is anticipated to upgrade our

knowledge on groundwater potential of the unconsolidated material in the area, and the vulnerability of the

aquifers within.

Geologic setting

Idanre area is underlain by the Precambrian basement complex of southwestern Nigeria (Ajibade and Fitches,

1988), where six major petrologic units has been identified and described by Rahaman (1988). The study area is

underlain by three of these six major petrologic units: the migmatite gneisses, members of the older granite suite

and charnockitic rocks (Ocan, 1991). Most of the outcrops observed in Idanre are melanocratics, therefore

possibly rich in biotite and/or hornblende. Field observation shows that granite rocks constitute extensive outcrops

in the entire area (Fig 1). Granite gneisses outcrops either occur alone or in association with other components.

Minerallogically, the granite gneiss around Idanre are composed of alkaline feldspar, quartz, plagioclase and

biotite (Ocan, 1991).

Materials and Methods of study

The vertical electrical soundings (VES) were conducted using the Schlumberger electrode array (Zhody et al.,

1974). The Ohmega Resistivity Meter was used for resistance measurement. The geoelectric survey comprised of

sixty five (65) depth soundings (Fig 2), with maximum current electrode spacing (AB) ranging from 130m to

200m (AB/2 = 65 - 100). The field curves were interpreted through partial curve matching (Koefoed, 1979),

engaging master curves and auxiliary point charts (Orellana and Mooney, 1966).

20


5 00' E

7 15' N

7 15' N

River Osun

River Apurare

River Owena

5 00' E

Owena

60

50

Ago - Moferere

Gberiwojo

Ago - Ireti

Aponmu Akore

Odoko Bekun Odoji

ALADE

IDANRE

Odo - Isa

Odo - Isa

21

Apefon

Igbo - Olokun

Igbo - Epo - Aiyemofewa

Omiwonja

Ajegunle - Arun

Iwanja - Moferere

Igbo - Epo

Igbo - Epo - Owomofewa

300 m

0

River Aponmu

River Esun

A

50

40

River Iwari

River Imoja

Porphyritic Granites

Massive charnockite

Granitic charnockite

Migmatite

Strike and dip of Foliation

Major fault

Idanrore

Tejugbala

Ajegunle - Iwonja

B

1 0 1 2 3 4 5 Km

0 2000 4000 6000 8000 10000 12000

LEGEND

ALADE River Arun

20

A

Cross Section Across Direction A - B

River Ogburugburu

Opa - Idanre

Kajola - Asoko

River Owena

Oposinle

River Otan

AKURE

Orientation Of feldspar in granite

Roads

Footpaths

Village

Fig. 1: Simplified Geological Map around Idanre (Ocan, 1991).

50

60

River

40

20

40

Italepo - Odo

Ododin Ipinlerere

B

30

30

Oda

Oke - Alafia

5 15' E

5 15' E

7 15' N

7 00' N


The manually derived geoelectric parameters were subjected to an inversion (Vander Velpen, 1988), which

successfully reduced the interpretation error to acceptable levels (Barker, 1989).

The electrical resistivity contrasts existing between lithological sequences in the subsurface (Dodds and Ivic, 1998;

Lashkaripour, 2003) were used in the delineation of geoelectric layers, identification of aquiferous materials

(Deming, 2002) and assessment of groundwater prospect of the area. Also, the resistivity parameter of the

uppermost geoelectric layer (topsoil) was used to evaluate, in quantitative terms, its permeability to surface/nearsurface

contaminants, and hence the vulnerability of the underlying aquifers, as demonstrated in Draskovits et al.

(1995).

7 06' 27.4''

7 06' 22.3'' 5 06' 15.0''

v54

o

T

A

e

r u

k

v53

v51

v52

v1

v3

v2

v7

v4

o

r v6 v5

l v8

v11 v12

a

d

v9

v10

v13

v37

v14

v33 v36 v19 v18

v15

v35

v32

v17

v16

v27

v26 v31 v34

v25 v30

v20

v23 v21

v28 v24

v29

v22

v38

v42

v41

v39

v40

v43 v44 v45 v46 v47

m

m

o

C

v49 v48

v50

e r c i a

T o A p e f o n

T o A b a B a b u b u

Scale

0 1000 2000

Fig. 2: Layout Map of Idanre showing VES positions (Inset: Map of Nigeria).

m

v59

22

v57

v58

v56

v60 v61 v62 v63

v65

v64

v55

T o

l

S c

h

l a

i c

n

T e c

h .

T o A p e t a n

5 08' 22.3''

Study Area

N

NIGERIA

v

LEGEND

Road / Major Street

Minor Street

VES Location

River

Scale

0 300 Km


RESULTS AND DISCUSSIONS

The Schlumberger depth soundings produced a short range of sounding curves: three-layer case of type A (41.5%),

H type (24.6%), and four-layer curves of type KH (15.4%) were mostly recorded. Typical curves are shown in Fig

3. Field curves often mirror-image (geoelectrically) the nature of the successive lithologic sequence in a place and

hence can be used, in qualitative sense, to assess the groundwater prospect of an area (Worthington, 1977). Type

H and KH curves are often associated with groundwater possibilities while type A may typify a rapid resistivity

progression, indicative of shallow, resistive bedrock.

Aquifer Delineation: Electrical resistivity contrasts exists across interfaces of lithologic units in the subsurface.

These contrasts are often adequate to delineate discrete geoelectric layers and identify aquiferous or nonaquiferous

layers (Schwarz, 1988). The geoelectric parameters of the aquifer units were determined from the

interpretation of the sounding curves. Resistivity of earth materials is strongly affected by water saturation and

water quality (Lucius et al., 2001). The resistivity parameter of a geoelectric layer is an important factor to

adjudge an aquifer or otherwise.

Cross sections of interpreted resistivity data from the area (Fig 4) show three to four geoelectric layers: the topsoil,

the lateritic or weathered layer, and the fractured/fresh bedrock. In the topsoil, resistivity values range from 20 to

260 Ohm-m, with layer thickness varying between 0.5 and 2.1m. The lateritic or weathered layer has resistivity in

the range of 35 to 600 Ohm-m, with most of the values (67%) less than 150 Ohm-m. Layer thickness ranges from

0.8 to 7.8m. In few areas however, the thickness gets up to over 20m, but about 85% of layer thickness obtained is

less than 6m. The presumed decomposed portion of the bedrock has resistivity in the range of 69 to 874 Ohm-m,

while the thickness ranges from 3.2 to 24m.

NORTH

DEPTH (m)

-1

-3

-5

-7

-9

-11

-13

-15

-17

(a)

VES 54

61

150Ohm-m

8121

Depth (m)

4

2

33

Scale

0

0 400

Distance (m)

VES 3

VES 11 VES 38

VES 8 VES 42

99

31

54694

22

197

2522

114

23

299

103

5683

59

27

599

73

54 Ohm-m

1199

LEGEND

VES 25 VES 29

79

26

9233

Topsoil

67

109

24

1175 Ohm-m

590

7251

Weathered layer

Fractured basement

Fresh basement

SOUTH


DEPTH (m)

WEST

0

-2

-4

-6

-8

-10

-12

-14

VES 43

88

VES 44

83 Ohm-m

8868

(b)

66

159

26840

Depth (m)

VES 45 VES 27 VES 26 VES 31

4

2

64

79

8284

Scale

0

0 300 600

Distance (m)

22

119

23

12742

24

60

38

351

1206

13

891

Fig 4(a) & (b): Cross Sections of Interpreted Resistivity data from Idanre.

Assessment of Groundwater Prospect

VES 34

26

3172 Ohm-m

221

1553

LEGEND

Topsoil

Weathered layer

Fractured basement

Fresh basement

VES 17

No acceptable framework has yet emerged, as to where exactly is the major focus for groundwater resources in a

typical crystalline basement terrain. Acworth (1987) reported successful completion of boreholes in shallow

weathered zones in a typical basement terrain. Fracture-zone aquifers in crystalline rocks are also believed to be

important sources of water for rural communities (Meju et al., 1999). Lenkey et al (2005) however believes that

the thickest layer above the basement constitute the main water-bearing layer.

The approach of Lenkey et al (2005) has been adapted for this study. Fig 5 is a contour map while figure 6 is the

numerical value distribution, showing the thickness of unconsolidated materials overlying the crystalline

basement in Idanre; the thickness ranges from 0.5m to 15.8m, with an average of 4.5m. Fig 5 shows that

overburden thickness of 1-5.9m in the area constitutes about 81.5%, thus suggesting that the water-bearing

horizon (Lenkey et al., 2005) across the area is generally not significantly thick.

Assessment of Aquifer Vulnerability

Due to shallow depth of occurrence, aquifers in crystalline basement terrains are often exposed to environmental

risks. An effective groundwater protection is given by protective geologic barriers with sufficient thickness

(Mundel et al., 2003) and low hydraulic conductivity. Laterite, silt or clay often constitutes protective geologic

barriers. When found above an aquifer they constitute its cover (Lenkey et al., 2005).

The resistivity parameters of the uppermost geoelectric layer in the study area have been used to assess the

vulnerability of the underlying aquifers. Fig 7 is a contour map of resistivity of the first layer while figure 8 shows

the numerical resistivity distribution across the first layer in the area.

35

56

12480

EAST


7 06' 27.4''

7 06' 22.3''

Frequency

v53

v54

v51

v52

v1

v3

v2

v7

v4

v8 v6 v5

v11v12 v9

v42

v10

v37

v13

v14

v15

v33 v36

v19v18

v35

v32

v17

v16

v27

v26 v31

v34

v25 v30

v20

v23 v21

v28 v24

v29

v22

v38

v49 v48

v50

v41

v39

v43 v46

v44v45

v47

v40

To Aba Babubu

5 06' 15.0''

To Akure

Commercial road

Scale

To Apefon

0 1000 2000 m

25

v65

v59

v58

v57

v64

v60v61v63

v62

v56

v55

To Technical Schl.

To Apetan

N

5 08' 22.3''

Fig. 5: Map of thickness of unconsolidated material overlying the Basement at Idanre.

30

25

20

15

10

5

0

1 - 2.9 3 - 5.9 6 - 8.9 9 - 11.9 12 - 14.9 15 -17.9

Overburden Thickness (m)

Fig 6: Distribution of thickness of unconsolidated material at Idanre.

v

Series1

22 m

19

16

13

10

7

4

1

LEGEND

Road / Major Street

Minor Street

VES Location


7 06' 27.4''

7 06' 22.3''

Frequency

v53

v54

v51

v52

v1

v3

v2

v7

v4

v8 v6 v5

v11v12 v9

v42

v10

v37

v13

v14

v15

v33 v36

v19v18

v35

v32

v17

v16

v27

v26 v31

v34

v25 v30

v20

v23 v21

v28 v24

v29

v22

v38

v49 v48

v50

v41

v39

v43 v46

v44v45

v47

v40

To Aba Babubu

5 06' 15.0''

60

50

40

30

20

10

0

To Akure

Commercial road

Scale

To Apefon

0 1000 2000

26

m

v65

v59

v58

v57

v64

v60v61v63

v62

v56

v55

To Technical Schl.

To Apetan

N

5 08' 22.3''

Fig. 7: Contour Map of Resistivity Distribution in the First Layer at Idanre.

1-100 101-200 201-300 301-400 401-500 501-600 601-700 701-800 801-900 901-

1000

Resistivity (Ohm-m)

Fig 8: Distribution of resistivity in the topmost geoelectric layer at Idanre

Series1

v

800 Ohm-m

750

700

650

600

550

500

450

400

350

300

250

200

150

100

50

0

LEGEND

Road / Major Street

Minor Street

VES Location


About 77% of the resistivity values of the topmost geoelectric layer fall within 1-100 Ohm-m range. In Nigerian

geological circumstances, this suggests considerable clayey or silt sequences (aquitard), with effective capacity to

constitute impervious/semi-impervious barriers.

CONCLUSIONS AND RECOMMENDATIONS

Due to rugged geologic terrain, the unconsolidated materials overlying the crystalline basement rocks around

Idanre constitute the major water-bearing horizon from which the inhabitants abstract water for domestic needs.

Geoelectric depth sounding around the area reveals that the thickness of the unconsolidated materials varies from

0.5m to 15.8m, where values within 1-5.9m brackets constitute about 81.5%. This indicates that the

unconsolidated material in the area is not significantly thick, thus suggesting that the groundwater potential is

apparently low.

About 77% of the resistivity values of the topmost geoelectric layer in the area fall within the range of 1-100

Ohm-m. Values of resistivity within this brackets suggest aquitard (silt or clay), which constitute effective,

impervious geologic barriers to infiltrating near-surface contaminants. Aquifers within the unconsolidated

materials at Idanre are therefore mostly capped by impervious/semi-pervious geologic materials, suggesting that

they are mostly non-vulnerable to near-surface contaminants.

Since decomposed bedrock in the crystalline basement terrain can house significant quantity of groundwater,

groundwater developers in the area may explore the bedrock for bedrock aquifers, to complement the aquifers

within the unconsolidated overburden.

ACKNOWLEDGEMENT

Messrs T. Omosehin, E. Faleye and M. Bawallah assisted in the data acquisition while Messrs O.Adegoke and A.

I. Adeyemo helped in preparing the figures. The author gratefully acknowledged these assistances.

REFERENCES

Acworth, R.I. (1987). The development of crystalline basement aquifers in a tropical environment. Q. J. Eng. Geol.

London. Vol. 20, pp. 265-272

Ajibade, A.C. and Fitches, W.R. (1988). The Nigerian Precambrian and the Pan- African Orogeny. In:

Precambrian Geology of Nigeria. A publication of the Geological Survey of Nigeria. Pp 329.

Barker, R.D. (1989). Depth of investigation of collinear symmentrical four-electrode arrays. Geophysics 54, 1031-

1037

Bala, A. E. and Ike, E. C. (2001). The Aquifer of the Crystalline Basement Rocks in Gusau Area, North-Western

Nigeria. Journal of Mining and Geology, Vol. 37, No. 2, pp. 177 – 184.

Clark, L. (1985). Groundwater abstraction from Basement Complex areas of Africa. Q. J. Eng. Geol. London. Vol.

18, pp 25-32.

Deming, D. (2002). Intrduction to Hydrogeology. McGraw Hill Company. Pp 468.

Dodds, A.R. and Ivic, D. (1988). Integrated geophysical methods used for groundwater studies in the Murray

Basin, South Australia. In Geotechnical and Environmental Studies Geophysics, Vol II: Soc. Explor

Geophys.,Tulsa, pp 303-310.

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Draskovits, P, Maayar, B and Pattantyus-A, M. (1995). Geophysical methods in groundwater prospecting and

environmental protection. Fisica de la Tierra, no 7, 53-86.

Lones, M.J. (1985). The weathered zone aquifers of the basement complex areas of Africa. Q. J. Eng. Geol.

London. Vol. 18, pp 35-46.

Koefeod, O. (1979). Geosounding Principles, 1. Resistivity sounding measurements. Elsevier Scientific

Publishing Comp., Amsterdam, pp 275.

Lenkey, L., Hamori, Z and Mihalffy, P. (2005). Investigating the hydrogeology of a water-supply area using

direct-current vertical electrical soundings. Geophy, Vol.70. no. 4, H1-H19

Lashkarripour, G.R. (2003). An investigation of groundwater condition by geoelectrical resistivity method: A case

study in Korin aquifer, southeast Iran. Journal of Spatial Hydrology, Vol.3, No. 1, pp1-5.

Lucius, J.E., Bisdort, R. J. and Abraham, J. (2001). Results of electrical survey near Red River, New Mexico.

USGS Open-File Report 01-331, pp24.

Meju, M.A., Fontes, S.L., Oliveira, M.F.B., Lima, J.P.R., Ulugerger, E.U. and Carrasquilla, A.A. (1999). Regional

aquifer mapping using combined VES-TEM-AMT?EMAP methods in the semiarid eastern margin of

Parnaiba Basin, Brazil. Geophysics, Vol. 64, No. 2. P. 337-356.

Mundel, J.A., Lother, L., Oliver, E.M. and Allen-Long, S. (2003). Aquifer vulnerability analysis for Water

Resources Protection. Indiana Department of Environmental Management (IDEM), ‘Source Water

Assessment Plan’, pp 25.

Ocan, T. (1990). Petrogenesis of the rock units of Idanre, southwestern Nigeria. Unpublished Ph.D thesis,

Obafemi Awolowo University, Ile Ife, Nigeria, pp 194.

Omosehin, T.B. (2008). Geoelectric delineation of aquifers and assessment of their vulnerability in Idanre,

Southwestern Nigeria. Unpublished M. Tech. thesis, Federal University of Tech., Akure, Nigeria. Pp 83.

Orellana, E. and Mooney, H.M. (1966). Master tables and curves for vertical electrical

sounding over layered structures. Inteciencis, Madrib, 34pp.

Parasnis, D.S. (1979). Principles of Applied Geophysics. Chapman and Hill, London. Pp 98 130.

Rahaman, M.A. (1988). Recent advances in the study of the Basement complex of Nigeria. Precambrian Geology

of Nigeria. A Publication of Geological Survey of Nigeria. Pp. 11-41.

Schwarz, S.D. (1988). Application of Geophysical Methods to Groundwater Exploration in the Tolt River Basin,

Washington State. In Geotechnical and Environmental Geophysics. Vol 1. Soc. Explor. Geophs, Tulsa,

pp 213-217.

Vander Velpen, B. P. A. (1988). Resist Version 1.0, M.Sc. Research Project, ITC. Delft, Netherlands.

Worthington, P. R. (1977). Geophysical investigations of groundwater resources in the Kalahari Basin.

Geophysics, Vol. 42, No 4, pp.838-849.

Zohdy, A. A. R., Eaton, G. P., and Mabey, D. R. (1974). Application of surface geophysics to groundwater

investigations: Techniques of water resources investigations of U.S. Geol. Survey: Book 2, Chapter DI,

U.S. Government Printing Office, Washington, pp.66.

28


Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Ozean Journal of Applied Sciences 3(1), 2010

Comparative vegetative and foliar epidermal features of three Paspalum L. species in

Edostate, Nigeria.

E.A Ogie-Odia*, A.I Mokwenye*, O. Kekere ** and O. Timothy ***

*Department of Botany, Ambrose Alli University, Ekpoma , Edo State.

** Department of Plant Science and Biotechnology, Adekunle Ajasin University, Akungba Akoko, Ondo State.

*** Department of Environmental Science, Western Delta University, Oghara, Delta State.

*Email address for correspondence: effexing@yahoo.com

___________________________________________________________________________________________

Abstract: Investigations into the vegetative morphology and epidermal features of three species of the genus

Paspalum L. (P. conjugatum Berg, P. scrobiculatum L. and P. vaginatum Sw.) was carried out. Pictorial

illustrations are presented. For the vegetative features, it was observed that there is variability of hairs on both the

margins of the lamina and leaf sheath of P. scrobiculatum. In the epidermal studies, macro-hairs were observed on

the margins of the lamina of two out of the three taxa; prickles were observed on the intercoastal zone of two out of

the three taxa; papillae was observed in the intercoastal zone of one of the three taxa; micro-hairs were observed in

two out of the three taxa. It was observed that the shape of the subsidiary cells of P. conjugatum varied from low

dome to triangular in the adaxial surface and mainly triangular shaped in the abaxial surface. P.scrobiculatum had

mainly triangular shaped subsidiary cells, while that of was low dome shaped in the adaxial surface and triangular

shaped in the abaxial surface. On the basis of the variations that exist in its morphological and epidermal features, a

taxonomic key has been produced for identification and separation of the various taxa.

Keywords: Vegetative, leaf epidermal, genus, Paspalum, Poaceae, systematic.

___________________________________________________________________________________________

INTRODUCTION

Poaceae which is the grass family includes approximately 10,000 species classified into 600 to 700 genera (Clayton

and Renvoize, 1986). The grasses are included with lilies, Orchids, Pineapples and Palms in the group known as

monocotyledons which includes all flowering plants with a single seed leaf (Kellogg, 2001). The members of this

group are present in all the conceivable habitats, suitable for growth of plant communities (Mitra and Mukherjee,

2005). The grass family Poaceae, is noted for its wide diversity and complexity and so has posed many problems to

the taxonomists using the traditional methods based on gross morphology (Strivastava, 1978).

Before the later part of the 19 th century, taxonomists were confined to the use of the features of reproductive organs

as floral characters were considered to provide the most valuable characters to taxonomic affinities (Nwokeocha,

1996). Of all the non-reproductive organs, the leaf is the most widely used in plant taxonomy (Stace, 1984).

Strivastava (1978) described the leaf epidermis as the second most important character after cytology for solving

taxonomic problems.

29


Ozean Journal of Applied Sciences 3(1), 2010

Paspalum L. is a member of the tribe Paniceae R. Br. Within the Paniceae, Paspalum is one of the most complex

genera containing over 400 species that are largely endemic to the tropics and subtropics of the world (Clayton and

Renvoize, 1986). The centre of diversity of this genus is South America (Fernandes et al, 1968). In Nigeria, Lowe

(1989) reported that the genus is represented by five species which are mostly straggling plants grown in damp open

places. The reported species are P. vaginatum, P. conjugatum, P. notatum, P. scrobiculatum and P. auriculatum.

The economic values of these species are many. For example, P. vaginatum provides for dune stabilization and

waterflow fodder under saline and fresh water environments respectively and can also be cultivated as a turfgrass for

soil stabilization. On the other hand, P. scrobiculatum has been domesticated as a cereal grain in Asia (Jarret et al.,

1998). The use of morphological and leaf epidermal features has been found to be of immense interest in taxonomy.

An excellent review of the application of morphological features in systematic studies is shown in the works of

Olowokudejo 1990, Mensah and Gill (1997), Edeoga and Ikem 2001, Gill and Mensah (2001) and Kharazian

(2007).The use of leaf epidermal features in systematics has become popular and distinctive and has been used as a

great taxonomic tool at the levels of family, genus and species.

This study is to give the morphological description of the three Paspalum species and also to compare/determine the

intraspecific relationship and patterns of variation associated with the epidermal features/characteristics among the

taxa studied.

METHODOLOGY

Fresh and matured leaves of Paspalum scrobiculum L. and Paspalum conjugatum Berg. were collected from

Beverly-Hills area, off Benin-Auchi express road, Ekpoma, while Paspalum vaginatum Sw. was collected close to

the bank of the Ikpoba river in Benin-city, Edo State. They were first boiled in water to restore to their normal

shape. The tissue above the epidermis was gradually scraped away with a safety razor blade and during this

operation the leaf was continuously irrigated with commercial Jik. The epidermal peels were then washed in water,

stained with 1% safranin solution in 50% alcohol and temporary mounts (under low and high power) viewed under

the microscope. Photo micrographs of the epidermal features were taken from the slides using a Light microscope

fitted with a Cannon digital camera (5.0 mega pixels). The terminologies for the epidermal morphology are that of

Metcalfe (1960) and Van Cottem (1973).

RESULTS

The morphological (vegetative) features of the three Paspalum species investigated are summarized in Table 1. The

descriptions of the leaf epidermal studies are presented in Tables 2; the epidermal and morphological Keys are also

presented while the epidermal slides are illustrated in Plates 1, 2 and 3. The vegetative results of the three taxa

studied showed that the habit of the three Paspalum species are perrenial herbs with P. scrobiculatum being a turfed

perennial herb. The heights are about the same (60cm) with P. scrobiculatum growing up to 100cm and while of the

habit and height of is perennial herb and respectively. Similarly the leaf shapes shows that they are all linear

although P. conjugatum is linear lanceolate while the the inflorescence is raceme for P. conjugatum and P.

vaginatum (terminal) and P. scobiculatum is digitate. The stem types varies with P. conjugatum having prostrate

stoloniferous stems, P. scrobiculatum with erect or decumbent stem and P. vaginatum with creeping stoloniferous

stem . Equally, all the spikelets in the three species have two rows with P. scrobiculatum and P. vaginatum being

hairless while P. conjugatum has hairs.

30


Ozean Journal of Applied Sciences 3(1), 2010

Table 1: Vegetative characters of the three Paspalum species studied

Characters Paspalum conjugatum Paspalum scrobiculatum Paspalum vaginatum

Habit Perennial herb Turfed perennial herb Perennial herb

Height 60cm 60-100cm 60cm

Stem type Prostrate stolon Erect or decumbent Creeping stolon

Leaf shape Linear or lanceolate Linear Linear

Leaf texture Smooth with hairy margins Soft with rough margins and

sometimes hairy

31

Smooth and hairless

Inflorescence Raceme Digitate Terminal raceme

Spikelet Two rows and hairy Two rows and hairless Two rows and hairless

Ligules Toothed Distinct and short Dense

Table 2: Summary of leaf epidermal features

Species Surface MIC MAH PRK PAP SSc OPB Distribution

of stomata

Paspalum conjugatum

Berg.

Paspalum

scrobiculatum L.

Paspalum vaginatum

Sw.

AD C

IC

AB C

IC

AD C

IC

AB C

IC

AD C

IC

AB C

IC

-

b

-

B

-

b

-

B

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

+

-

+

-

+

-

+

-

-

-

-

-

-

-

-

-

-

-

-

-

+

-

-

LD, T

T

T

T

LD

T

Db, S

-

S, Cr

-

Db, Cr

-

Db, Cr

-

HES

-

Db, Cr

-

AMP

AMP

AMP


Legends for Plates and Table 2

Ozean Journal of Applied Sciences 3(1), 2010

AB = Abaxial surface SHC = Short cell

AD = Adaxial surface C = Coastal zone

OPB = Opaline body LD = Low dome shaped

IC = Intercoastal zone S = Saddle shaped

MIC = Micro-hair Cr = Cross shaped

b = Bi-cellular Db = Dumb bell shaped

MAH = Macro-hair Amp = Amphistomatic

PRK = Prickle HES = Horizontally elongated surface

PAP = Papillae SSc = Subsidiary cell

LNC = Long cell T = Triangular

+ = Present - = Absent

Paspalum conjugatum Berg.

Leaf blade up to 9.5cm long and 6.1mm broad, with prickles and macro-hairs present on leaf margins.

a. Adaxial surface: Clearly separated into coastal and intercoastal zone.

Solitary short cells are present in the intercoastal zone. Long cell vary from slightly to straight anticlinal walls.

Prickles present in the intercoastal zone. Bi-cellular micro-hairs with distal cell having tapering apices present in the

intercoastal zone. Papillae and micro-hair were absent in the coastal and intercoastal zones. Subsidiary cells of the

stomata vary from low-dome to triangular shape. Opaline bodies of the coastal zone vary from dumbbell to rounded

or saddle shaped

b. Abaxial surface: Clearly separated into coastal and intercoastal zone

Long cells rectangular shaped with some tending to be square shaped with sinuous anticlinal walls. Long cells

observed in the coastal zone. Bi-cellular micro-hairs present in the coastal zone, distal cells with tapering apices.

Prickles present in the intercoastal zone. Macro-hairs and papillae absent, subsidiary cells of stomata are triangular

shaped. Opaline bodies mostly saddle shaped, occasionally cross shaped in the coastal zone

32


Plate 1a Adaxial surface of P. conjugatum

Plate 1b Abaxial surface of P. conjugatum

Paspalum scrobiculatum L.

Ozean Journal of Applied Sciences 3(1), 2010

Leaf blade up to 16cm long and 0.9mm broad with prickles and macro-hairs present on margins.

a. Adaxial surface: Clearly distinguished into coastal and intercoastal zone.

Long cell are rectangular shaped with some tending to be square with sinuous walls. Solitary short cells present in

the intercoastal zone. Long cells present in the coastal regions. Bi-cellular micro-hairs present in the intercoastal

zone, with distal cells having tapering apices. Prickles with hook shape present in the intercoastal zone. Papillae and

33

C

C

IC

PRK

IC

MIC

SSc

LNC

LNC

MIC

SSc


Ozean Journal of Applied Sciences 3(1), 2010

micro-hairs absent and stomata present with triangular shaped subsidiary cells. Opaline bodies of the coastal zone

are mainly cross and dumb bell shaped.

b. Abaxial surface: Coastal and intercoastal zone clearly distinct.

Long cells rectangular shaped with sinuous anticlinal walls. Long cells present in the coastal zone. Solitary short

cells present in the intercoastal zone. Hook shaped prickles present in the intercoastal zone. Papillae and macro-hair

absent, bi-cellular micro-hairs present in the intercoastal region and stomata with triangular shaped subsidiary cells.

Opaline bodies vary from cross to dumb bell shaped in the coastal zone.

Plate 2a Adaxial surface of P. scrobiculatum

Plate 2b Abaxial surface of P. scrobiculatum

Paspalum vaginatum Sw.

34

C

C

SSc

IC

MIC

IC

SSc

LNC

LNC

MIC


Ozean Journal of Applied Sciences 3(1), 2010

Leaf blade up to 6cm long and 2.5mm broad with prickles and macro-hairs present on margins.

a. Adaxial surface: Clearly seperated into coastal and intercoastal zone.

Long cell are rectangular shaped with some tending to be square with slightly sinuous to straight anticlinal walls.

Short cells is absent in the intercoastal zone. Macro-hairs and micro-hairs absent, papillae tend to overarch with

stomata in the intercoastal zone. Subsidiary cells of the stomata were low-dome shaped. Opaline bodies in the

coastal regions are horizontally elongated.

b. Abaxial surface: Clearly distinguished into coastal and intercoastal zone.

Long cells are rectangular shaped with sinuous anticlinal walls in the intercoastal zone. Long cells present in the

coastal zone. Short cells are paired, occasionally solitary in the intercoastal zone. Prickles, micro-hairs and macrohairs

are absent. Subsidiary cells of stomata are triangular shaped.

Opaline bodies vary from dumb bell to cross shaped in the coastal zone.

Plate 3a Adaxial surface of P. vaginatum

35

C

IC

PAP

SSc

LNC


Plate 3b Abaxial surface of P. vaginatum

Ozean Journal of Applied Sciences 3(1), 2010

Key to the three species of Paspalum studies based on their epidermal features

1. Prickles present on both surfaces………………………………………………2

1. Prickles absent on both surfaces……………………………………………….4

2. Macro-hairs variable on the leaf margins………………………..scrobiculatum

2. Macro-hairs constant on the leaf margins…………………….........conjugatum

3. Papillae present on adaxial surfaces…………………………………………...4

3. Papillae absent on both surfaces……………………………………………….2

4. Micro-hairs present on both surfaces…………………………………………..2

4. Micro-hairs absent on both surfaces………………………………....vaginatum

Key to the three species studies based on their morphological features

Inflorescence: Consisting of 2 long slender raceme between 8-15cm that has greenish yellow

spikelets which are almost circular lying flat with hairy fringe on their margin……..P. conjugatum

Inflorescence: Consisting of 2-10 racemes, each with two rows of overlapping swollen circular

spikelets…...................................................................................................................P. scrobiculatum

Leaves: Borne in two distinct ranks on either side of the culm

Inflorescence: Consisting of 1-3 racemes, sometimes a pair of terminal racemes with 2 rows of overlapping ovate

spikelets …………………………………………………..……..P. vaginatum

DISCUSSION

36

C

IC

SSc

OPB

SHC

LNC


Ozean Journal of Applied Sciences 3(1), 2010

The morphological (vegetative) features observed showed that there were little or slight differences in the features of

the three species of Paspalum studied and this suggests their differences in species level as they exhibited different

characters though some of the characters were quite identical.

Some differences in type of stem and the inflorescence and spikelets (Table 1) were observed, although the heights

were almost the same in the three species except for P.scrobiculatum which grows up to 100cm. The analysis of the

morphological structure of the three studied species has revealed characteristics, which correspond to those

mentioned by Lowe (1989) and Akobundu and Agwayaka (1998). The epidermal cells are arranged in horizontal

files. Leaf epidermis of the genus Paspalum is clearly distinguished into coastal and intercoastal zones. The coastal

zones are generally narrower while the intercoastal zones are broader. Studies carried out by Sharma and Salam

(1984); Sharma and Mittal (1986) have reported similar observations in other genera and tribes of Poaceae. The

epidermal cells possess sinuous, slightly to straight anticlinal walls. Metcalfe (1960) reported similar undulations in

various genera and tribes of Poaceae. Explanations have been given for the wavy nature of the anticlinal walls of the

epidermal cells. One of the explanations for this phenomenon relates the undulations to the development of stress

during the differentiation of the leaf (Avery, 1933). Another concept is that the waviness is caused by the method of

hardening of the differentiating cuticle (Watson, 1942). Furthermore, Linsbauer (1930) and Watson (1942) stated

that the waviness is also affected by environmental conditions prevailing during leaf development. Prickles with

hook shape have been observed in the adaxial and abaxial surfaces of P. conjugatum and P. scrobiculatum. Prickles

with angular spines were restricted to the margins of leaf lamina of the three species., various shapes of prickles in

tribes of Poaceae have been described by Sharma and Mittal (1986) Sharma and Salam (1984). Font Quer (1975)

defines papillae as the simplest of trichomes, characterized by wall projection followed by the protoplast of

epidermal cells. According to Ellis (1979), Poaceae papillae occur in long and short cells, especially in intercostal

zones, in numbers that may vary from one to many per cell. Papillae are absent in most of the three species studied

except on the adaxial surface of P. vaginatum where it was found to be present. Thus, the absence of papillae in this

last mentioned species can be interpreted as a taxonomic indicator. Micro-hairs observed are mainly bi-cellular with

tapering apices in the intercoastal zones of both the adaxial and abaxial surfaces of P. conjugatum and P.

scrobiculatum. Metcalfe (1960) have described bi-cellular hairs in a number of grass species. Macro-hairs were

absent in the coastal and intercoastal zones of the three species but were present on the margins of P. conjugatum. In

P. scrobiculatum, it varied (i.e it was present in some and absent in the others). The reason for this could be

probably due to the presence or absence of hairs on the leaf margins of the grass or other factors could be

responsible. The stomata are restricted to the intercoastal zones on both adaxial and abaxial surfaces. According to

Ellis (1979), the Poaceae stomata generally occur in well-defined bands in intercostal zones, and they may be

classified according to the shape of subsidiary cells. Subsidiary cells of the stomata varied from triangular to low

dome shape in the adaxial surface of P. conjugatum while it was the same in the abaxial surfaces of the remaining

two species. Mensah and Gill (1997) have reported similar observations in other genera and tribes of Poaceae like

Sporoboleae. Opaline bodies which are depositions of silica materials were mainly dumbbell, cross, saddle and

horizontally elongated in shape. The importance of opaline bodies as a systematic tool in grasses has been

overemphasized by many researchers including Metcalfe (1960).

Grasses are currently identified based on their floral characters, but a problem encountered with the system of

identification is that grasses do not flower for a greater part of their life cycle. Hence, a biosystematic approach

could be used in tackling this problem through gathering of data from various studies such as cytology, palynology,

epidemiology etc. The study of different epidermal characters such as macro-hairs, prickles, papillae, micro-hairs,

distribution of stomata, nature of long cells, subsidiary cells, opaline bodies and surface views of the leaf helps us

classify and identify grasses into their various tribes and genus and thus adds to our knowledge on the

biosystematics of grass species. It will also be beneficial as a research tool to cytologist, weed scientist and research

workers.

REFERENCES

Akonbondu O.I and Agwaraka W. C (1998) A handbook of West African weeds, IITA, Ibadan 564p

Avery G. S Jr (1933). Structure and development of the Tobacco leaf. Amer. Jour. Bot. 20: 565-592

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Clayton W. D and Renvoize, S. A (1986). Genera Graminae: grasses of the world. Royal Bot. Gard. Kew, London.

Kew Bulletin. Additional series XIII

Edeoga H.O and Ikem C.L (2001). Comparative Morphology of the leaf epidermis in three species of Boehavia L.

Nyctagininaceae. J.Pl. Anat Morph. 1:14-21.

Ellis R. P. (1979). A procedure for standardizing comparative leaf anatomy in the Poaceae II: the epidermis as seen

in surface view. Bothalia .12 (4): 641-671.

Font Quer P. (1975). Diccionario de Botanica. Labor., 1244p.

Gill L. S. and Mensah J. K. (2001). Epidermal and leaf anatomical studies of the tribe Eragrostideae (Poaceae) from

West Africa: J. Plant Anat. Morph. 25: 41 – 58.

Jarret R. L., Lui, Z. W and Webster R. W (1998). Genetic diversity among Paspalum spp. as determined by RPLPs.

Euphytica 104: 119-125

Kellogg E. A (2001). Evolutionary history of the grasses. Plant Physiol. 125: 1198-1205

Kharazian N. (2007). The Taxonomy and variation of leaf anatomcial characters in the genus Aegilops L. (Poaceae)

in Iran Turk J. Bot. 31: 1 – 9.

Linsbauer K. (1930). Die Epidermis. In: K. Linsbauer Handbuch der Pflanzenanatomie Band 4 Lief: 27.

Lowe J. (1989). The Flora of Nigeria grasses. Ibadan University Press, Ibadan. 326p.

Mensah J.K. and Gill L. S (1997).Cuticular and leaf blade anatomical studies of the tribe Sporoboleae (Poaceae)

from West Africa. J.Plant.Anat.Morph.7: 72-81.

Metcalfe C. R, (1960).Anatomy of the Monocotyledons I. Gramineae Clarendon Press Oxford. 731p.

Mitra S and Mukherjee S.K (2005). Ethnobotanical usages of grasses by the tribals of West Dinajpur district, West

Bengal. Indian J. Tradit. Knowledge 4(4): 396-402.

Nwokeocha,C. C, (1996). Foliar epidermal studies in Oryza punctata. Nig. J. Bot 9: 49 -58.

Olowokudejo J.D ( 1990). Comparative Morphology of leaf epidermis in the genus Annona (Annonaceae) in West

Africa. Phytomorphol 40: 407-422.

Sharma M. L. and Mittal H. R. (1986). Leaf epidermal studies in Gramineae V. Genus Eragrostic P. Beauv. Res.

Bull. Pangab Univ. 37: 29 – 35.

Sharma M. L. and Salam A. (1984). Biosystematic survey of the Dactyloctenium aegyptium complex (Gramineae)

in Punjab plains II Leaf epidermis Res. Bull. Pangab Univ. 35: 7 – 11.

Stace C. A. (1984). The taxonomic importance of the leaf surface, current concept in plant. Taxonomy systematic

association. Special vol. 25, Academic press, London and Orlando pp 628 – 642.

Strivastava A. K. (1978). Study of leaf epidermis in the genus (Gramineae). Journal of Indian Botanical society 37:

155 – 160.

Van Cottem W. R. J. (1973). Stomata types and systematic. In : The phylogeny and classifications of the Ferns (Ed).

by A. C. Jermy. Academic press, London pp 301 – 405.

Watson R. W (1942). The effect of cuticular hardening on the form of epidermal cells. New Phytol. 42: 223-229

38


Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Digital Moulding of the Solicitations within the Dielectric of

the Transformers and the Evaluation of

Life Cycle of the Insulation Systems

MARIUS-CONSTANTIN POPESCU* and CRISTINEL POPESCU

Faculty of Electromechanical and Environmental Engineering, University of Craiova,

B-dul Decebal, nr.107, 200440-Craiova, Dolj, ROMÂNIA

*E-mail address for correspondence: mrpopescu@em.ucv.ro

_________________________________________________________________________________________

Abstract: This papers analyses the evaluation methods of the wear of transformers that occurs on their charging

with alternating load, taking into consideration mainly the thermal ageing of electroinsulation material,

especially of those of A class.

Key-Words: wear of transformer, thermal parameters.

_________________________________________________________________________________________

INTRODUCTION

In regular service conditions, the transformer is subject to added solicitations which influence the long-term

response of the transformer. Among the elements of the transformer, the insulation, which this chapter deals

with, is stressed in different conditions in use from those of the lab. In regular service conditions the insulation of

the transformers is under nominal voltage of the electric network, reaching the crest working voltage at the most.

In lab conditions, the insulation of the transformers is subject to the action of proof stress which has the value,

form and time period appropriate for the concepts and actual conditions of coordination of the insulation, applied

in transformer plants and distribution stations. As a result, the testing of the insulation of the transformers in lab

must guarantee the safe running of the transformers under most unfavorable conditions. The insulation of the

electrical power transformers is subject to different kinds of stress, both in real and in lab conditions. In standard

conditions, electrical (of nominal voltage and of overvoltage), mechanical (due to the short-circuit stresses),

chemical (due to deposits or chemical agents) and thermal (due to changes in temperature and in the atmosphere)

stresses are applied on the insulation. Due to these stresses, in the course of utilization, the properties of the

electroinsulation materials deteriorate, bringing about the ageing of these materials. On the whole, the ageing

process of the insulating materials is a complex process because of the multitude of different kinds of factors

which influence it. Among these stresses, those which influence the most the insulation are those due to internal

overvoltage, caused by the changes in the parameters of the electroenergetic system, and to external overvoltage

(atmospherical), caused by lightning, the temperature of the oil/paper insulation complex from the transformer

respectively. After the changes in the physical properties of the electroinsulation materials, changes occurred in

use, the marking of the state of an insulation can not be carried out taking into consideration a single property

due to the fact that the changes are the result of the action of a large number of external actions, the

combinations of which are random, their accurate reproduction being impossible. It is difficult to study the

transformers while they are working, because it would take a long time, namely decades. Shortening the length

of the trials could be carried out by introducing accelerated ageing procedures, but these methods do not

guarantee results that can be applied in real conditions. Therefore, the trial conditions must be created in a way

that they are as similar as possible to the real ones and in accordance to the purpose for which the results are

used later on. For this reason, the functional trials carried out on mock-ups are of great scientific value.

39


1.External stresses of the insulation of the electrical power transformers

In the case of the external stresses, the potential pulse that applies stresses on the insulation can be:

- full-wave impulse - of long standing, after which high voltage oscillations develop in the windings hence

resulting stresses both among the spires and between the winding and the earth point.

- chopped-wave impulse – the amplitude of which is not so great, but due to scarp cutting, it can bring about

voltage gradients that are dangerous to the insulation on entrance or at the neutral point of the transformer.

- steep-wave impulse – has great amplitude but it lasts little and as a consequence it produces the most stresses.

These can apply stress on the insulation at the table and the insulation among the entrance spires of the winding.

In lab conditions, the transformer is subject to a minute sinusoidal proof voltage, namely a proof voltage of

impulse. Each of the proof voltages is referred to maximum overvoltage in use, equating the overvoltage in use

to lab conditions.

The proof voltage of the internal insulation with full-wave is stated by the relation:

[Uinc]up=Kt[Ugp]up+0,5UN (1)

where: Kt is coefficient with the value 1.15 for the 6 -35 kV transformers and 1.10 for the 110 and 220 kV

transformers; UN is nominal voltage of the winding of the transformer.

The proof voltage of the internal insulation with the chopped-wave impulse is stated by the relation:

[Uinc]ut=1.15*1.25[Ugp]up (2)

where 1.15 takes into account the cumulative effect, and 1.25 takes into account the increase of voltage at the lug

of the transformer in relation with the lightning arrester.

The minute sinusoidal proof voltage is stated by the relation:

�U �

inc �

Ua�


� � K

si

c

where: βsi is equation coefficient of the Usi internal overvoltages in use with the Uα minute proof voltages in lab;

Kc ≈0.9 is the coefficient that takes into account the cumulative effect of repeated stresses in exploitation.

2. Factors that determine the state of the insulation

The insulation of the transformers is influenced by the following factors [1, 2, 4, 5]:

The alien substances in the internal insulation are: moisture left in the insulation after an inappropriate drying

procedure; residues of the coating varnish solvent that have not been removed when the windings were dried;

blisters or gaseous inclusions left in the insulation after the filling of the transformer with oil; dirt resulted from

an inappropriate operating process. The contamination of the external insulation, the thermal operating

conditions and the altitude at which the transformer works. Damping the insulation causes: an increase in

dielectric losses and a decrease in dielectric rigidity. The presence in oil of water in the form of emulsion (in

dispersed state) leads to a rapid decrease of rupturing voltage of the oil. The water molecularly dissolved in oil

does not influence the dielectric rigidity and losses. But in the presence of alien fields in the oil-water

molecularly dissolved changes into dispersed state leading to the decrease of dielectric rigidity. Variations in

temperature also cause changes in rupturing voltage. Thus, when the temperature increases from 20�C to 60�C,

at a frequency of 50 Hz, an important increase in rupturing voltage takes place. The electrical insulating oil,

commercially pure, contains an amount of moisture, dissolved gases and solid impurities (waste and grains).

When the temperature increases the dilution of water increases and the waters turns from the state of emulsion

into the state of dilution leading to the decrease of dielectric rigidity. The effect that the temperature variations

40

(3)


have on the insulation of the transformers in a long time cause an ageing of the insulation, which loses its

mechanical properties (it becomes fragile). The impurities and the dirt from the atmosphere reduce the value of

the rupturing voltage of the external insulation of the transformers, even under working stress. Gaseous

inclusions or blisters lead to partial discharges and thus to the decomposition of the structural insulation, having

negative effects on the dielectric rigidity as it decreases. Low atmospheric pressure in mountainous regions cause

the decrease of the voltage of the external insulation because of the decrease of the relative density of the air.

The quality of the impregnation process and especially the polymerization degree of the varnish highly influence

the condition of the insulation of the transformers, incomplete polymerization causing an increase in dielectric

losses, the decrease of the dielectric rigidity, the oxidation and ageing of the electrical insulating oil.

3. The testing of the insulation of transformers

The testing with direct voltage have as purpose the finding out of the dampness of the insulation of transformers,

if there are or not deficiencies able to cause partial discharges (gaseous inclusions, deficient junctions), if

changes in the response of the dielectric occur by applying stress for a long period of time. Based on the

variations from the initial state of the insulation, variations caused by the influence of dampness, of the ageing of

the insulation of the transformers or of an overcharge, it can be decided if the occurring deficiencies can be

remedied or if the transformer must be submitted to a general overhaul. Furthermore, the main tests on the

electrical power transformers are presented [4], [7], [10], [12], [14], [15], [16].

The measurement of the insulation resistance. The insulation resistance, through the absorption coefficient

R60/R15 allows the estimation of the degree of moistness of the insulation of transformers. For a dry enough

transformer the absorption coefficient must relate to the following: R60/R15≥1,5. When applying direct voltage,

in time, an alternative current is established through the dielectric which decreases and then settles at a value.

Initially the current has a high value and thus the insulation resistance has a high value due to the polarization

current and to the charging current. Compared to a dry dielectric, at a damp dielectric, to the polarization current,

displacement current, an orientation component is added and as a consequence the line current rises. The

insulation resistance of a dielectric is given by the relation between the applied direct voltage and the resulted

full current. The value of the insulation resistance is influenced by the following factors: the value of the direct

voltage which is applied, the length of applying the voltage, the electrostatic charge, the temperature of the

insulation and the dampness degree of the insulation. The state of the insulation of the transformer is determined

through the diagram I=f(U) by means of the position of the break which appears in the curve at a certain value of

the voltage. The higher the voltage at which the break appears and the gentler the transfer from a slope to another

is, the better the state of the insulation is. If the break appears below the value 2 * U max,

the insulation is

considered to be weakened and the transformer must be overhauled. If the current suddenly increases the

insulation is disrupted and the tests must be stopped. The state of the insulation of the transformer can also be

determined through the variation of the insulation resistance and of the current depending on the applied voltage.

After a while the insulation resistance, namely the through the insulation reach a set value. If the stabilization

takes place in a short period of time and also at a low value, it means that the conductance component IS is high

compared to the polarization component Ip and consequently the insulation is damp. On the other hand, the low

values of the insulation resistance due to the high content of water in the insulation do not mean that the

transformer is aged or permanently deteriorated. The insulation resistance is not standardized. It is to be

compared with the values of the measurements at the same temperature. If the previous measurements have been

carried out at different temperatures then their values are reduced to the temperature of the latest measurement.

The insulation resistance varies in inverse ratio to the temperature. As the measurements can not be carried out

all the time at the same temperature, recomputed values are used, recomputed through recomputation values of

the insulation resistance depending on the temperature. For each transformer two measurements are carried out

at temperatures between 20�C and 75�C. The relation to the same temperature is performed by the multiplication

or the division of the values of the insulation resistance with its variation coefficient by the temperature

difference K1 following the values presented in Table 1.

Δt

( 0 C)

Table 1. The values of the coefficient of variation K1

1 2 3 4 5 10 15 20 25 30 35 40 45 50

Val K1 1.05 1.07 1.12 1.16 1.23 1.4 1.74 2.23 2.65 3.35 4.05 5.15 6,1 7.5

41


The insulation resistance must not drop below 70% of the initial value of the insulation resistance. When

measuring, the following are taken into consideration:

- For the new transformers, when putting it to service, the R60 value must not be below 70% of the its value set in

the factory;

- For the transformers in use, R60 must not drop below the values shown in Table 2.

Un (kV)

Table 2. R60 values for different values of the nominal voltage.

R60

20 0 C 50 0 C

≤ 60 300 90

110 – 220 600 180

400 1000 300

In time, the insulation resistance of the transformer rises up to practically a set value. The variation of the

insulation resistance in relation with the time represents the absorption curve. The measurement of the insulation

resistance is carried out after 15, 60s respectively. The absorption coefficient R60/R15 tends to the value 1if the

insulation has a great content of dampness. The absorption coefficient provides information on the variation of

the insulation resistance in time, which is why the state of the insulation resistance is judged by absorption

curves and polarization curves. The absorption coefficient is used as one of the criteria to establish the dampness

of the curves, the shape of the absorption curve depending on the degree of dampness of the dielectric and its

build. The absorption curve shows the variation of the insulation resistance in time and of the current through the

insulation. The measurements are carried out in the specified thermal and dampness conditions, in fair weather,

at a relative dampness of the environment, of 80% at the most, taking into consideration the following

observations:

- When it starts working the Kabs value must not be over 5% below the value set in the factory;

- For the transformers in use the Kabs value is not standardized;

- The value of the absorption coefficient at 20�C is considered normal if: Kabs≥1,2 for power transformers with

U≤110kV; Kabs≥1,3 for power transformers with U≤110kV.

The dissipation factor. The tgδ dissipation factor is also a criterion for evaluating the state of the insulation. The

increase of the tgδ value is determined by the chemical degradation of the oil, its getting wet, the ageing of the

solid insulation affected by dampness, oxigen or by temperature. The measuring of tgδ is compulsory for all

transformers of over 110kV voltage and powers of over 10 MVA inclusive, respecting the following

observations:

- When putting into service tgδ the measuring must be carried out at the temperature recommended in the manual

provided by the factory (±5 0 C), not below 10 0 C .

- The values measured at the putting into function are compared to the values measured in the factory. The

values in use must be kept between the limits provided in the Table 3.

Table 3. Normal values for tgδ.

Un (kV) 20 0 C 50 0 C


In use, the values obtained for tgδ at one of the two reference temperatures is compared to the values measured

previously (in the factory, at putting into service). In the case of new transformers, the tgδ value must not

increase over the value set in factory with over 30%. If the previous measurement has been carried out at a

different temperature from the one of the latest measurement, it will relate to the temperature of the latest

measurement by division or multiplication by the coefficient of variation K2, depending on the difference of

temperature Δt ( 0 C).

Δt

( 0 C)

Table 4. The values of the coefficient K2

1 2 3 4 5 10 15 20 25 30 35 40 45 50 55 60

Val K2 1.04 1.07 1.10 1.11 1.16 1.26 1.52 1.65 2 2.4 2.55 3 3.4 4 4.5 5.4

For all transformers, the real values of the reporting coefficient is determined from the diagram obtained from

measuring the tgδ at the temperature of 50±5 0 C, after which the tgδ=f(t) line is used when the temperature has

dropped to 20±5 0 C. For measuring we employ a measuring bridge for MD – 16 capacity assembled after a

Scherine assemblage.

The measuring of the ohmic resistance of the curves. The purpose of the measuring of the ohmic resistance of

the curves is: to determine the real resistance of the curves; to check the welds or junctions from the conductors

of the windings; to track down the possible interruptions; to make evident the dead short circuits among the

spires or other deficiencies which are reflected in the value of the resistance. The measuring is carried out in

direct current at a value that exceeds with 20% the value of the non-load current, but it is not to exceed 0,1In.

While the ohmic measurements are carried out, the winding temperature is put down. The measured resistance is

related to another temperature by means of the relation:

T � t

R * 2

t � R

2 t1

T � t1

T = 235 both for the copper windings and for the aluminum windings.

Taking these into consideration, some special measurements have been carried out on some electrical power

transformers from Romania. The gathered data, recorded in the task report, have been synthesized in a tabular

and graphic form. Analyzing the result of the measurements, conclusions regarding the behaviour of the

transformers in use could be drawn. Fig’s 1 and 2 show the results of the measurements carried out on electrical

power transformers considered to be matters of study. The study has been completed for the main sizes that

characterize the behavior of the transformers, from 1998 to 2008. For each size the measured value has been

compared to the normalized value and to the value EPC set in the factory. From the obtained data and the

graphical representations it can be determined that only in the case of the transformer T11 (from a Station in

Romania) a negative variation can be observed both of the insulation resistance and of the tangent delta,

especially between 2004 and 2005. As a consequence, the increase of the insulation over the EPC values calls for

a further close surveillance of the insulation. The rest of the transformers can be considered suitable to be in

service.

Table 5. The result of the measurements TS – earth point performed on the T9 power transformer.

EPC

Tg la EPC 38 C

Tg EPC trans la 20C

R 15 EPC la 38 1200 TS-TI Trafo 11

R 15 EPCla 20 2472

R 60 EPCla 38 2400 Vn 20 C= 600 Mohm Vn 50 C=180 Mohm

R 60 EPCla 20 4944 Vn 20 C= 2,5% Vn 50 C= 7 %

R1-rez EPCla 38 1,373 An EPC-1986

t1-EPC 38 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Tg mas trans la 20 C 0,23 0,25 0,29 0,28 0,32 0,24 0,28 0,25 0,25 0,23 0,30

Tg masurata 0,35 0,38 0,4 0,42 0,45 0,4 0,42 0,4 0,38 0,4 0,42

%R60mas din R60EPC la 20gr 60 65 51 49 54 60 49 50 41 56 54

R60 transpus la 20 2980 3220 2527 2429 2652 2966 2429 2448 2024 2768 2652

R 60 masurata 1560 1750 1560 1320 1560 1440 1320 1230 1100 1230 1560

Roh plot 1-mas 1,332 1,326 1,312 1,325 1,313 1,345 1,326 1,338 1,325 1,353 1,316

t2-calc la mas 38,0 36,5 35,4 32,9 35,3 33,1 38,9 35,4 37,6 35,3 40,4 33,6

Delta t

kiz

18,0

2,06

16,5

1,91

15,4

1,84

12,9

1,62

15,3

43 1,84

13,1

1,7

18,9

2,06

15,4

1,84

17,6

1,99

15,3

1,84

20,4

2,25

13,6

1,7

k tg 1,65 1,55 1,51 1,38 1,51 1,42 1,65 1,51 1,6 1,51 1,75 1,42

R15 transpus la 20 2197 1748 1426 1838 1105 1813 1041 1325 1593 1766 1586

R15 masurat 1150 950 880 999 650 880 566 666 866 785 933

Kabs 1,36 1,84 1,77 1,32 2,40 1,64 2,33 1,85 1,27 1,57 1,67

(4)


Fig. 1. The variation of the insulation resistance of the T9 power transformer.

Table 6. The TS – TI measurement results performed on the T 11 power transformer.

EPC

Tg la EPC 38 C 0,49

Tg EPC trans la 20C 0,30

R 15 EPC la 38 2680 TS-masa Trafo 9 st Mare - 199999

R 15 EPCla 20 5521

R 60 EPCla 38 4930 Vn 20 C= 600 Mohm Vn 50 C=180 Mohm

R 60 EPCla 20 10156 Vn 20 C= 2,5% Vn 50 C= 7 %

R1-rez EPCla 38 1,353 An EPC-1986

t1-EPC 38 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Tg mas trans la 20 C 0,29 0,25 0,25 0,26 0,30 0,30 0,32 0,28 0,32 0,29 0,32 0,31

Tg masurata 0,45 0,38 0,35 0,4 0,43 0,5 0,48 0,45 0,48 0,5 0,45 0,45

%R60mas din R60EPC la 20gr 33 31 27 27 26 27 26 29 29 32 32 31

R60 transpus la 20 3343 3110 2722 2760 2635 2719 2668 2985 2944 3263 3230 3186

R 60 masurata 1750 1690 1680 1500 1550 1320 1450 1500 1600 1450 1900 1800

Roh plot 1-mas 1,332 1,326 1,312 1,325 1,313 1,345 1,326 1,338 1,325 1,353 1,316 1,322

t2-calc la mas 38,0 36,5 35,4 32,9 35,3 33,1 38,9 35,4 37,6 35,3 40,4 33,6 34,7

Delta t 18,0 16,5 15,4 12,9 15,3 13,1 18,9 15,4 17,6 15,3 20,4 13,6 14,71377

kiz 2,06 1,91 1,84 1,62 1,84 1,7 2,06 1,84 1,99 1,84 2,25 1,7 1,77

k tg 1,65 1,55 1,51 1,38 1,51 1,42 1,65 1,51 1,6 1,51 1,75 1,42 1,46

R15 transpus la 20 3362 3533 1944 2429 1870 3296 3165 3343 2263 2768 2584 2620

R15 masurat 1760 1920 1200 1320 1100 1600 1720 1680 1230 1230 1520 1480

Kabs 0,99 0,88 1,40 1,14 1,41 0,83 0,84 0,89 1,30 1,18 1,25 0,00

Fig. 2. The variation of the dissipation factor of the T9 power transformer.

Fig. 3. The variation of the insulation resistance of the T 11 power transformer.

44


Fig. 4. The variation of tangent delta of the T11 power transformer.

Table 7. The results of the TI – earth point measurements performed on the T11 power transformer.

EPC

Tg la EPC 38 C 0,25

Trafo 11

Tg EPC trans la 20C 0,15

R 15 EPC la 38 1000 TI-masa

R 15 EPCla 20 2060

R 60 EPCla 38 2200

Vn 20 C= 600 Mohm Vn 50 C=180 Mohm

R 60 EPCla 20 4532

Vn 20 C= 2,5% Vn 50 C= 7 %

R1-rez EPCla 38 1,373 An EPC-1986

t1-EPC 44 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Tg mas trans la 20 C 0,21 0,24 0,30 0,34 0,44 0,44 0,33 0,21 0,29 0,31 0,37

Tg masurata 0,33 0,36 0,42 0,52 0,62 0,72 0,5 0,33 0,44 0,55 0,52

%R60mas din R60EPC la 20gr 70 63 58 67 64 78 71 76 69 79 65

R60 transpus la 20 3171 2852 2608 3036 2890 3543 3220 3423 3128 3600 2924

R 60 masurata 1660 1550 1610 1650 1700 1720 1750 1720 1700 1600 1720

Roh plot 1-mas 1,332 1,326 1,312 1,325 1,313 1,345 1,326 1,338 1,325 1,353 1,316

t2-calc la mas 38,0 36,5 35,4 32,9 35,3 33,1 38,9 35,4 37,6 35,3 40,4 33,6

Delta t 18,0 16,5 15,4 12,9 15,3 13,1 18,9 15,4 17,6 15,3 20,4 13,6

kiz 2,06 1,91 1,84 1,62 1,84 1,7 2,06 1,84 1,99 1,84 2,25 1,7

k tg 1,65 1,55 1,51 1,38 1,51 1,42 1,65 1,51 1,6 1,51 1,75 1,42

R15 transpus la 20 1815 1693 2138 1582 1105 3193 2453 3483 1380 1575 1326

R15 masurat 950 920 1320 860 650 1550 1333 1750 750 700 780

Kabs 1,75 1,68 1,22 1,92 2,62 1,11 1,31 0,98 2,27 2,29 2,21

Fig. 5. The variation of the insulation resistance of the T11 power transformer.

45


Fig. 6. The variation of the dissipation factor of the T11 power transformer.

4.Thermal ageing of the electroinsulation materials

The lifetime of a transformer is influenced by a series of factors which determine the changes in physical

properties, properties of a mechanical, electrical, thermal or chemical nature.

- Alien substances in the internal insulation: moisture left in the insulation after an inappropriate drying

procedure; residues of the coating varnish solvent that have not been removed when the windings were dried;

blisters or gaseous inclusions left in the insulation after the filling of the transformer with oil; dirt resulted from

an inappropriate operating process. The damping of the insulation brings about an increase of the dielectric

losses as well as a decrease of the dielectric rigidity.

- The contamination of the external insulation, the thermal operating conditions and the altitude at which the

transformer works.

The ageing of the transformers occurs due to the alterations of the physical properties, ageing that brings about

the reduction of their lifetime. The way in which the external factors influence the transformers' lifetime is hard

to study as such a study includes some proof tests that take a great deal of time, that is decades. This is why the

study time must be reduced by reducing the period of testing and by settling the conditions of the testings. For

this purpose functional testings on models are employed. Consequently, mathematical laws have been

established to mirror as much as possible the ageing process of the transformers.

Concerning the electrical equipment, the most sensitive component is the insulation, the lifetime of which

actually determines the lifetime of the equipment. Concerning electrical transformers and static devices

generally, the ageing of the insulation is essential. For the lifetime, laws have been defined experimentally to

state the lifetime of the insulation. For example the Montsinger’s law in which the lifetime is expressed in

degrees Celsius, while in Bűssing’s law the lifetime is expressed in degrees Kelvin.

���

D � �*

e , (5)

V. M. Montsinger’s relation, valid for temperatures between 90� C and 110� C, namely

B

T

D � A*

e , (6)

W. Bűssing’s relation, valid for a large range of temperatures and for a great number of materials of different

classes, here: D - the lifetime of electroinsulant materials; θ, T – the temperature of the electroinsulant material

expressed in degrees Celsius, in degrees Kelvin respectively; α, β, A, B – constant specific to the electroinsulant

material.

The ageing method is based on Arhhenius’s equation, which expresses the degradation rate of an electroinsulant

material:

46


�E


� � A*

e KT

, (7)

Arhhenius’s relation, where: A is constant specific to the material; ΔE is activation energy; K is Boltzman’s

constant; T is the temperature of the electroinsulant material expressed in degrees Kelvin.

The law expressed by the relation (5) was established by V.M. Montsinger and it was proved to be valid for A

class electroinsulant materials, but for a relatively limited range of temperature, 90�C...110�C. The law given by

the relation (6) was demonstrated for the first time by W. Bűssing through the kinetic theory of chemical

reactions and it proved to be valid for a great deal of electroinsulant materials of different classes and for a wide

range of temperatures. The lifetime laws of electroinsulant materials take into account not only the temperature

as decisive factor, but also the other factors. The other factors are taken into account when choosing the

constants A and B, and α and β. The values of these constants are chosen in keeping with functional trials of

accelerated ageing. The factors which determine the ageing of the transformers determine their lifetime, deriving

from the lifetime equation of transformers. Thus, the ageing of transformers is marked by:

- The relative factor of thermal ageing, also named relative factor of thermal wear

- Relative thermal ageing, also named relative thermal wear.

The relative factor of thermal ageing is defined by:

� B B �

� � �

�TN

T � � � e

(8)

where: T is the absolute temperature expressed in degrees Kelvin; TN is the absolute temperature at which a

normal lifetime if obtained; B is a constant characteristic to the material.

Considering that the temperature varies in relation to time, the relative ageing factor will be, too, time function as

follows:

�(

t) � e

� B B

� �

�TN

T

The relative ageing factor p(t) marks the degradation rate of the insulating material and, thus, the extent of heat

density of the electroinsulant material. Relative thermal ageing is given by the average value of the relative

ageing factor in a certain period of time, namely:

Replacing the expression for p(t), we obtain:

1 �t

u(

t)


�t

0

47


� � � t �

��(

t)

dt

1

u(

t)

� � e

�t

� B B �

�t � � �

�TN

T ( t)


The two obtained expressions mark the thermal ageing of the electroinsulant material for a single time interval

taken into consideration. If there are several time intervals taken into consideration, the expression of relative

thermal ageing becomes:

0

(9)

(10)

(11)


n

�ui�ti

u(

t)

� i�1

n

(12)

� �ti

i�1

Considering the same range of validity for the relations (5) and (6) written for the temperatures θ şi θN, and T şi

TN, by equaling the following results:

where the following can be written:

and:

e

��

( � ��

)

� �

e

N � e

��(

�N

��)

48

B B


TN

T

1 �t

����

��


N ( t)

u


� e dt

�t

0

The two relations allow the evaluation of the ageing and wear degree of the insulation of electrical transformer.

Where transformers are concerned, temperature is the main factor that influences their behavior, affecting

especially the oil/paper insulation. In this case, dampness is another influencing factor, besides temperature. The

ageing state marked by the thermal ageing factor p, the relative thermal ageing u, respectively, does not allow a

different marking of the insulation considering temperature as main influencing factor. And that is because the

degradation rate of the insulation is influenced by dampness at any temperature, and the ageing p factor may be

considered as a ratio between two degradation rates, one of which the working temperature θ is expressed in

degrees Celsius, namely T expressed in degrees Kelvin, the other at standard temperature θN, TN respectively, the

relative ageing u being the average value of the ageing factor p in a certain period of time. thus, it may be

considered that, if the change in the dampness degree influences in the same way the degradation rate of the

oil/paper insulation, the ageing factor p can be regarded non dependent on dampness. The main component of

the ageing factor p is temperature, but at the same time, through the material constants α and β (actually θ şi β),

A and B respectively (actually TN and B), it depends on the other chemical, mechanical or electrical factors that

influence the ageing process of the oil/paper insulation from of the transformers.

5.Thermal wear of the transformers

In most cases the thermal wear of transformers in oil is determined by the wear of the paper impregnated with oil

insulation. It is usually exposed to the highest of temperatures of the transformer close to the curves. The starting

points of analyzing the wear of the transformer are two distinct cases: the temperature of the transformer varies

distortionless with time and the temperature varies exponentially with time. Each of the cases can be treated as

having as basis either Molntsinger’s law (5) or Bűssing’s law (6) [6], [9], [11], [14].

6.1. The case of distortionless variation of temperature in relation with time

The case in which the ageing of the transformer is reflected by Montsinger’s law (5). Taking into consideration

at the initial moment t=0, θ=θi, after a time t=tf the temperature θ=θf respectively, the distortion less variation of

the temperature can be written in relation with time, in degrees Celsius, after an expression as follows:

t

� ( t) � �i

� ��

�t

,

��

� �

f � �i

(13)

(14)

(15)

(16)


where: θi is the temperature at the beginning of the time period taken into consideration, expressed in degrees

Celsius; θf is the temperature at the end of the time period taken into consideration, expressed in degrees Celsius;

Δt is the period of time during which the temperature increases from θi to θf.; t is time as current variable.

The case in which the lifetime law of the transformer is expressed by the relation (6) given by Bűssing. In this

case, the temperature variation in relation with time is expressed in degrees Kelvin after an expression as the

following:

T( t)

� Ti

� �T

t

�t

There are the following relations between the two temperatures:

,

49

T T � � �

f i T

(17)

Ti=273+ θi; Tf=273+ θf, (18)

namely ΔT=Δθ (19)

The thermal ageing factor p as well as the relative thermal ageing u by means of their parameters link the relative

sizes that lead to the ageing of the materials and based on the variation of these factors in time the curves that

will characterise the ageing of the electroinsulant materials will be able to be marked off. This paper deals with

the evaluation of the relative thermal wear based on the Montsinger’s law employing the relation (5).

Thus, considering the distortionless variation of temperature the relation becomes:

By integrating the expression u(t), we bwill obtain:

� � t ��

�t ����N

���i

���*


1


t

u t � e � � � �

( ) � *

�dt

�t

0

1 � ��

u � * e

���

��

��N ��

f � ��


�� ��

e N i �� ��

The expression (21) allows us to determine by computing the relative thermal wear, applicable both for a cooling

process and in the case of one cooling process.

6.2 The case of exponential variation of temperature in relation with time

The exponential variation of temperature is deducted using the heating equation considering the parameter

constant Tt only in input condition with P=constant. When I= constant, Tt depends on I, and when U=constant it

depends on U and t. In these conditions we will continue to consider the hypothesis that P=constant and/or

I=constant.

In the case of exponential variation of temperature, temperatures θ and T become:

respectively:

t


T

� �t� � �

t

r � ��*

e

(20)

(21)

(22)


T

�t� � T � �T

* e

r

where: θr, Tr – stand for stationary regime temperatures expressed in degrees Celsius, and degrees Kelvin

respectively; Δθ, ΔT – stand for the difference between the stationary regime temperature and the temperature at

the beginning of the thermal process expressed in degrees Celsius, and degrees Kelvin respectively; Tt is time

constant with wich the temperature variation process takes place[s], having the following relation between the

temperatures:

50

t T

t


(23)

Tr=273+ θr; Δθ=ΔT (24)

The temperature differences Δθ, ΔT are of different symbols, according to the process, whether it is of cooling or

of heating. If we take into consideration the thermal wear based on Montsinger’s relation, the following results:

�t

1

u � � e

�t

0

� � t ��

� � � ��

����

���

���

T

N

��

� �

r * e t

��

� �


� �

��


Placing the independent of time factors before the integral, the following results:

��

u �

�� � � � �t

N r


�t

0

e

t


����*

e

Tt

Consequently, the wear variation u can be figured for different values of the material constat β and certain values

of the time value Tt.

In order to simplify the display, relative values can be thus used:

� � ��

*

;

With the above, the expression of thermal wear becomes:

e

u �

* t

t �

Tt


�� *

��

*




r N

� �t *

���

* �

*

e

t

* � e

�t

0

;

dt

dt

* dt

dt �

Tt

The value of the integral in the expression of the thermal wear depends on the parameters Δθ * and Δt * which

have a symbol for a cooling process and a different one for a heating process. Thus, in the case of the heating

process Δθ * is positive, and in the case of the cooling process Δθ * is negative. Consequently, the evaluation of

the thermal wear must be dealt with differently.

dt

*

(25)

(26)

(27)

(28)


6.2.1 The case of thermal heating process

In the case of the thermal heating process, Δθ * being positive, the following form of expressing the heating

integral Ii appears to be more convenient, employing the relation (28):

�t *

�e�

�ln ��

*

�t

*



� � � *

Ii

� e

dt

0

If lnΔθ * -t * is noted with x, dx=-dt * results, the expression of the integral Ii becoming:

The function

I

51

(29)

ln ��

*

�e

x

i � � e dx

ln ��

*

��t

*

(30)

y � e

is shown in the Fig. 7a the shaded area represents the value of the integral in the relation (10).

�e

a) b)

Fig. 7. The variation of function: a) y=f(x); b) f(x).

The value of the integral can be expressed as a difference between two values of the function f(x):

Considering the limits of integration:

x

� 0 x

f ( x)

x

* *

x ln�� � �t

the integral Ii can be expressed at heating as it follows:

� ,

� e

�e

x

dx

*

0 � ln�

x

(31)

(32)

(33)


� � � � *

* *

ln�� � �t

� ln��

Ii � f

f

(34)

The graphical representation of f(x) in relation to x is shown in Fig. 7b where the way of obtaining the integral Ii

is also explained. The graphical representation requires the setting of the limits of integration x0 and xi of the

heating integral Ii. The limit of integration x0 is chosen in a way that it accomplishes the condition lnΔθ *


where:

Ir � g

x

x

e �e 1�

�(

x)

� � �

x

0

53

dx

*

* * * *

�ln�� ��

���

g�ln��

��

��

t � � �t

� �t

a) b)

Fig. 8. The variation of the function y= e .

The graphical representation of the function � (x)

is shown in the Fig. 8b, illustration followed by the

explanation of how the integral Ir is obtained. The random limit of integration x0, similar to the case of the

heating process, depends on the sought accuracy in obtaining the value of the integral Ir. If a 1% error is

accepted, it can be considered that at cooling the curve y is identical with an asymptote to which it tends

(ordinate asymptote 1) when y reaches the value 1.01. The corresponding abscissa is a result of e �1,

01 as

being x0= - 4.6. Thus, for x


values of the constants β şi B. Fig. 9 [9] shows: curve 1 with dotted line – relation (14), corresponding to the “8

degree Celsius rule”, with β=0.08664 0 C -1 ; curve 2 with dotted line - relation (14), corresponding to the “6

degree rule”, with β=0.11552 0 C -1 ; curve 1 with solid line – relation (8), with B=11500 0 K; curve 2 with solid

line – relation (8), with B=14573 0 K; curve 3 with solid line – relation (8), with B=17184 0 K.

For all the cases the following were considered : θN=95 0 C, and TN=368 0 K, resulting ρ=1.

θN and TN represent the temperature at which the degradation rate of the electroinsulant material is considered to

be normal. These constants have been set starting from the hypothesis that the highest temperature admisible

must allow a 25000 hour working time of the transformer, that is at a temperature of 95�C about 30 years of

working time. Thus, taking into consideration the lifetime laws and all the above mentioned, θN is considered to

be ranging between 95 0 şi până la 98 0 C. Even 110�C is acceptable. The highest temperature admisible

determines the aspect of the curves that characterise the thermal wear of the transformers [11], [13]. Regarding

the transformers with oil its limit is 115�C

Fig. 9. The variation curves of the thermal ageing relative factor ρ in relation to the temperature.

Sometimes in cases of overvoltage conditions, this peak temperature can increase, without having negative

effects on the way the transformer works though. Experiments have revealed that in cases of overvoltage the oil

can reach 115�C, while the curves can reach even 200�C. This does not break the transformer if it lasts between

one and four hours, but it influences its ageing process. In case of shortcircuits the temperature limit of 250�C is

considered, in the hottest spot of the transformer.

6.2.3 The heating process case

The numerical computation of the function f(x) defined by the relation (31) allows the evaluation of the thermal

ageing of the transformer in case of a heating process, the limits of integration x0 and xi being set according to

the above.

Thus, the limit of integration x0 is obtained from the condition:

where lnΔθ*max is the peak value of Δθ* that can appear in use.

X0>lnΔθ*max (42)

The starting point is the hypothesis that the peak temperature of stationary regime that can appear in use is

Δrlim=200 0 C. In this case, the initial temperature can be lower than that which determines a minimum thermal

wear relative factor ρmin which must be taken into account. Therefore, when computing the function f(x) that

minimum value of Δθ is taken into account, value which at θr=200 0 C determines a temperature of which a

relative wear factor ρmin complies with. For higher values of Δθ, we will consider ρ=0 and so f(x), too. Taking all

these into consideration Δθ*max will be obtained from the condition:

54


� �� ���

���

��

� N r

then considering ρmin=0.1 and θr=200 0 C the following results:

e

55

max � �

min

(43)

Δθ*max=β(200-θN)+2.3 (44)

Taking into account the relation (43) in order to obtain the highest value of Δθ*max the lowest value possible

must be considered for θN and the highest for β. On the observations carried out previously we can consider the

extreme values θN=95 0 C, and β=0.126 0 C -1 . We thus obtain:

From the relations (41) and (44) the following results:

Δθ*max=0.126*(200-95)+2.3=15.53 (45)

X0=ln 15.53=2.75 (46)

When x has values over 2.75, we consider f(x)=0. The lower value of the variable x that is taken into

consideration is the one defined by the relation (31), namely xi= - 4.6. Fig. 10 [8] presents the variation curves

for f(x), and Δθ respectively, for different values of the constant β.

Fig. 10. The variation of the function f(x) and of temperature for different values of the material constant β.

When using the curve f(x) the wear corresponding to the wear factors below 0.1 is neglected only in the critical

case θr=θrlim. At other values of θr by using the curve f(x) the neglect of the wear appears in the case of wear

factors below a critical case of ρ than 0.1. This critical case can be determined with the relation:


considering x0=2.75.

56

x

�� ���

�e

0 ��

��

N r

� lim � e

(47)

As established, the constant ρlim depends on the parameters β, θr, θN, but it must always be ρlim≤0,1.

6.2.4 The cooling process case

The numerical computation of the function φ(x) defined by the relation (39) allows the evaluation of the thermal

ageing of the transformer in case of a cooling process, the limits of integration x0 and xi being set according to

the above. Thus, the value of the minimum limit is x0= - 4.6. The upper limit of integration results from the

condition:

xS

�� � �

� ln �

* max

considering –Δθ*max as the peak value for -Δθ* that can appear in use.

As shown previously, we take the hypothesis that the cooling temperature can not be higher than 140�C as

starting point. Exaggeratedly considering that the cooling takes place towards 0�C, the following results –

Δθ*max=140 0 C. The peak value of -Δθ* complies with the peak value of β=0.126 0 C -1 . Consequently we obtain:

(48)

xS=ln(0.126*140)=2.87 (49)

With the limits x0 şi xs thus delimited in the Fig. 11 the variation of the function φ(x) has been featured together

with that of Δθ with the help of which the evaluation of the ageing factor of the insulation of the transformer can

be carried out. The function φ(x) becomes equal with zero when x=-4.6. Because when x=-4.5, φ(x)=0.001

results, employing the curve in Fig. 11 [9] we will consider φ(x)=0 la x≤-4.5.

Fig. 11. The variation of the function φ(x) and of size Δθ for different material constants β.


6.3. Computing examples

As stated previously, the lifetime as well as the wear factor determines the state of ageing of the transformers.

For example, by using the Mathcad medium, the cases of some transformers from a transformer station from

Romania has been taken into consideration.

1) In the case of the first transformer, to compute the wear the following initial data have been used: the initial

temperature θi=78 0 C, the temperature is considered to vary exponentially with time, the stationary regime value

is θr=110 0 C, the time period of the thermal process is considered to be 2.25 hours, the time constant of the

thermal process is considered to be 1.5 hours. θN=95 0 C şi β=0.086643 0 C -1 are accepted, considering the “8

degree Celsius rule”. The stationary regime temperature being higher than the initial temperature, and so a

heating process takes place for which Δθ=110-78=32 0 C and as a consequence the f(x) curve will be used to

determine the values x1 and f(x1). Therefore, on the basis of the diagram in Fig. 10 for β=0.086643 0 C -1 , the

following values will be obtained: x1=1.02, f(1.02)=0.01745. Using relative values we obtain:

For the limit x2 the following is obtained x2=x1-Δt * =1.02-1.5=-0.48 with which f(-0.48)=0.4376 complies.

Consequently, considering the relations 28 and 33, the thermal wear will be:

e

u �

0.

086643

1.

5

�110�95� �0. 4376 � 0.

01745�

�1.

03

As the wear u is over unity, the thermal wear for the considered time period is lower than the normal wear. From

the Fig. 10, it can be established that, at the end of the time period, as x2=-0,48 complies with Δθ=7 0 C, the final

temperature will be θf=110-7=103 0 C.

2) In the case of the second transformer, the initial data are the following: the initial temperature θi=120 0 C, the

temperature varies exponentially with the time, the stationary regime temperature is θr=85 0 C, the period of time

for the thermal process is 4 hours, the time constant of the thermal process is 2 hours. θN=98 0 C şi β=0.11552 0 C -

1 0

are accepted, taking into consideration the six degrees rule. From the initial data, Δθ=85-120=-35 C, resulting

that we are dealing with a cooling process, the function φ(x) will be employed. From the diagram φ(x), for the

value β=0.11552 0 C -1 , the following results: –Δθ=35 0 * 4

C, x1=1.40, φ(1,40)=18.42; in relative values: �t � � 2 .

At x2=x1-Δt * =1.40-2=-0.60, in Fig. 11, we can establish φ (-0.60)=0.62. The thermal wear, computed on the

basis of the relations (28) and (41), will be:

0,

11552

e

u �

�85�98� 18,

42 � 0,

62 � 2

2

� � � 2,

21

Furthermore, with the help of the graphical representations in Fig. 11 the temperature at the end of the 4 hour

period can be established. Thus, from the diagram of the function φ (x), for x2=-0.6 –Δθ=5 0 C will result and so

the final temperature will be: θf=85+5=90 0 C.

3) The general case in which the variation range of the constant β can be considered with the following initial

data: the initial temperature θi=75 0 C, the temperature varies exponentially with time, the stationary regime

temperature is θr=110 0 C and θN=95 0 C. The graphical representation of the function f(x) by reproducing the

coordinates, is presented in Fig. 12.

57

.

�t

*


2,

25

1,

5

2


1,

5

.


Fig. 12. The variation of the function f(x).

The variation of the thermal wear with the variable parameter with the help of the Mathcad program is shown in

Fig. 13.

Fig. 13. The variation of the thermal wear with the material constant β.

Considering the same initial data we can observe the variation of the thermal wear with the temperature in Fig.

14.

58


Fig. 14. The variation of thermal wear with temperature.

CONCLUSIONS

As a result of the studies carried out, it can be stated that a number of the transformers from different transformer

stations are improperly employed, that is under their real potential. An estimation of the wear of the transformers

and of their ageing degree can be carried out considering the lifetime law by taking into consideration certain

grounds and specific particularities:

- the transformers are subject to different stresses, among which the thermal stress can be considered to be the

most significant;

- transformers can be considered to have a certain typical thermal behaviour;

- the evaluation of the behaviour is carried out by applying the lifetime law with certain values of the constants

that interfere with the law, most often making use of the rule of ”n” degrees. The most eloquent results have

been obtained by using the “8 degree Celsius rule”;

- certain load curves, of special shapes, are allowable.

The thermal behaviour of transformers can be understood by means of mathematical relations, simulated through

mathematical computation programme, such as the Mathcad programme. The results of the mathematical

simulation can be visualised using curves and tables in which a particularization of the calculus is needed having

in view: the behaviour of the transformers from a thermal point of view, the charging conditions of the

transformer, the characteristics of the insulation and the evaluation method of the thermal ageing of the

insulation.

REFERENCES

Ilie F., Bulucea C.A., Popescu M.C.,(2009), Simulations of Oil-filled Transformer Loss-of-Life Models,

Proceedings of the 11 th International Conference on Mathematical Methods and Computational

Techniques in Electrical Engineering (MMACTEE'09), Published by WSEAS Press, pp.195-202,

Vouliagmeni Beach, Greece.

Mastorakis N., Bulucea C.A., Manolea Gh., Popescu M.C., Perescu-Popescu L., (2009) Model for Predictive

Control of Temperature in Oil-filled Transformers, Proceedings of the 11 th WSEAS International

Conference on Automatic Control, Modelling and Simulation, pp.157-165, Istanbul, Turkey, May.

Mastorakis N., Bulucea C.A., Popescu M.C., Manolea Gh., Perescu L., (2009) , Electromagnetic and Thermal

Model Parameters of Oil-Filled Transformers, WSEAS Transactions on Circuits and Systems, Issue 6,

Vol.8, pp.475-486, Available: http://www.worldses.org/journals/circuits/circuits-2009.htm

59


Mastorakis, N.. Bulucea, C.A., Popescu M.C., (2009) Transformer Electromagnetic and Thermal Models,

Proceedings of the 9 th WSEAS International Conference on Power Systems (PS`09): Advances in

Power Systems, pp.108-117, Budapest, Hungary.

Popescu M.C., Bulucea C.A., Perescu L., (2009) Improved Transformer Thermal Models, WSEAS Transactions

on Heat and Mass Transfer, Issue 4, Vol.4, pp. 87-97, October.

Available:http://www.worldses.org/journals/hmt/heat-2009.htm

Popescu M.C., Manolea Gh., Bulucea C.A., Boteanu N., Perescu-Popescu L., Muntean I.O., (2009) Transformer

Model Extension for Variation of Additional Losses with Frequency, Proceedings of the 11 th WSEAS

International Conference on Automatic Control, Modelling and Simulation, pp.166-171, Istanbul,

Turkey.

Popescu M.C., Manolea Gh., Perescu L., (2009), Parameters Modelling of Transformer, WSEAS Transactions

on Circuits and Systems, pp.661-675, Issue 8, Vol.8.

Available:http://www.worldses.org/journals/circuits/circuits-2009.htm

Popescu M.C., Mastorakis N., Bulucea C.A., Manolea Gh., Perescu L., (2009), Non-Linear Thermal Model for

Transformers Study, WSEAS Transactions on Circuits and Systems, Issue 6, Vol.8, pp.487-497.

Available: http://www.worldses.org/journals/circuits/circuits-2009.htm

Popescu M.C., Mastorakis N., Bulucea C.A., Popescu-Perescu L., (2009) Modelling of Oil-filled Transformer,

International Journal of Mathematical Models and Methods in Applied Sciences, Issue 4, Vol.3, pp.346-

355. Available: http://www.naun.org/journals/m3as/19-166.pdf

Popescu M.C., Mastorakis N., Manolea Gh., (2009), Thermal Model Parameters Transformers, WSEAS

Transactions on Power Systems, Issue 6, Vol.4, pp.199- 209,

June.Available:http://www.worldses.org/journals/power/power-2009.htm

Popescu M.C., Mastorakis N., Popescu-Perescu L., (2008) Electromagnetic and Thermal Model Parameters,

International Journal of Energy, Issue 4, Vol.2, pp.51-65.

Available: http://www.naun.org/journals/energy/19-141.pdf

Popescu M.C., Mastorakis N.. Popescu-Perescu L., (2009), New Aspects Providing Transformer Models,

International Journal of Systems Applications, Engineering & Development, Issue 2, Vol.3, pp.53- 63.

Available: http://www.universitypress.org.uk/journals/saed/19-165.pdf

Popescu M.C., Popescu C., (2009), Functional Parameters Modelling of Transformer, Journal of Mechanical

Engieenering Research, pp.001-037.

Available: http://www.academicjournals.org/JMER/contents/2009cont/Nov.htm.

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Engineering Research, pp.001-022.

Available: http://www.academicjournals.org/JEEER/contents/2009cont/Nov.htm

Popescu, M.C., Manolea, Gh., Bulucea, C.A., Perescu-Popescu, L., Drighiciu, M.A., (2009), Modelling of

Ambient Temperature Profiles in Transformer, Proceedings of the 13 th WSEAS International

Conference on Circuits, (part of the 13 th WSEAS CSCC Multiconference), pp.128-137, Rodos, Greece.

Stoenescu E., Popescu M.C., Bulucea C.A., Assessment of Improved Transformer Thermal Models, (2009),

Proceedings of the Applied Computing Conference (ACC'09), Published by WSEAS Press, pp.189-195,

Vouliagmeni Beach, Greece.

60


Ozean Journal of Applied Sciences 3(1), 2010

A disconnect congestion detection from

TCP to improve the robustness

Issa Kamar and Seifeddine Kadry

AUL university, Beirut, Lebanon

Lebanese University - Faculty of Science, Lebanon

E-mail: seifdine.kadry@aul.edu.lb, Issa.kamar@aul.edu.lb

Abstract – The Transmission Control Protocol (TCP) is the most popular transport layer protocol for the internet.

Congestion Control is used to increase the congestion window size if there is additional bandwidth on the network, and

decrease the congestion window size when there is congestion.This paper uses a classic TCP which we called Robust

TCP with an accurate algorithm of congestion detection in order to improve the performance of TCP. Our TCP Robust

only reacts when it receives an ECN (Explicit Congestion Notification) mark. The evaluation result shows a good

performance in the terms of drop ratio and throughput.

Keywords: Congestion Control, TCP, ECN, Implicit Congestion Notification.

________________________________________________________________________________________________

I. INTRODUCTION

TCP is a connection-oriented, end-to-end reliable protocol designed to fit into a layered hierarchy of protocols which

support multi-network applications. Congestion events in communication networks cause packet losses, and it's well

known that these losses occur in burst.TCP congestion control involves two tasks:

1. Detect congestion

2. Limit Transmission rate

To achieve good performance and obtain a Robust TCP, it is necessary and important to control network congestion, by

limiting the sending rate and regulating the size of congestion window (Cwnd) after the detection of congestion.TCP

congestion control operates in a closed loop that infers network conditions and reacts accordingly by means of losses. A

negative return is due to a loss of a segment which can be translated by decreasing the flow from the source through a

reduction in the size of window control.

TCP considers loss of a segment as a congestion in the network, the detection of this loss can be done in several ways:

Timeout, Three Duplicate ACKs (Fast retransmit) and by receiving a partial ACK.

The state is:

Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

61


� If Packet Loss or congestion event =>TCP decreases Cwnd.

� All is well and no congestion in the network, i.e., TCP increases Cwnd.

At all cases, loss indication should be done with accuracy because it may lead to false indications like: Spurious

retransmission.

Spurious timeout occurs when a non lost packet is retransmitted due to a sudden RTT (Round Trip Time) increase (hand

over, high delay, variability, rerouting . .) which implies to an expiration of the retransmission timer set with a previous

and thus outdated RTT value.

This effect is known to be the root cause of spurious retransmission.

The function of the congestion control is an essential element to the stability of the internet.

Indeed, TCP congestion control reduces the flow when it detects a loss in the network. Therefore, it is important to be

accurate in the loss detection to improve the performance of TCP.

A congestion event (or loss event) corresponds to one or several losses (or in the context of ECN: at least one

acknowledgment path with an ECN-echo) occurring in one TCP window during one current RTT period, it means that a

congestion event begins when the first loss occurs and finishes one RTT later.

In this paper, we propose a congestion detection algorithm that is realized independently of the TCP code. To improve

the TCP by reducing the Cwnd, we aim to illustrate the feasibility of the concept by demonstrating that we can both

obtain similar performances and also improve the accuracy of the detection outside the TCP stack.

We implement the Implicit Congestion Notification (ICN) algorithm to better understand and investigate the problem of

congestion events estimation.

This paper is organized as follows: section 2 presents related works, section 3 shows the architecture of the congestion

detection, section 4 presents the detailed discussion for the Robust TCP with ICN congestion detection algorithm, and

section 5 presents an evaluation of the TCP Robust using simulations.

Finally, section 6 concludes this article and presents some perspectives.

II. RELATED WORKS:

Over the past few years, several solutions have been proposed to improve the performance of TCP. In [5] proposed

TCP-DCR modifications to TCP's congestion control mechanism to make it more robust to non-congestion events, this

is implemented by using the delay "tau" based on a timer.

Our mechanism is different; it relies on the accurate congestion detection algorithm (ICN) and uses the timestamp option

to detect spurious timeout which can more improve the reliability of the algorithm and leads to a real Robust TCP.

In Forward RTO-Recovery (F-RTO): the F-RTO algorithm of the TCP sender monitors the incoming

acknowledgments to determine whether the timeout was spurious.

TCP suffers from the inaccuracy of the congestion detection in the other TCP agents, for this reason we design an

accurate mechanism of congestion detection (ICN) that interacts with TCP robust.

Our study must prove the functionality of our TCP with ICN is better than other versions of TCP. For this point we have

to show that the mechanism of congestion detection for some TCP variants (New-Reno, Sack) doesn’t detect well when

there is congestion and doesn't not work well more than TCP Robust with ICN.

In [5], the idea or the solution proposed for the detection of congestion is the delay of the time to infer congestion by T,

and this value should be large to recover from non-congestion event, and should be small to avoid expensive RTO.

Our approach is different by using a classic TCP that responds only to an accurate algorithm of congestion detection.

62


III. STAND-ALONE TCP CONGESTION EVENTS ALGORITHMS

In this section we present the architecture of decorrelating congestion Detection from the Transport Layer (figure 1).The

main goal of this architecture is to simplify the task of kernel developers as well as improve TCP performances. This

scheme opens the door to another way to react to congestion by enabling ECN emulation at end-host. In this case ICN

emulates ECN marking to imply a congestion window reduction.

Figure. 1. Decorrelating Congestion Detecting from the Transport Layer

IV. ROBUST TCP ALGORITHM:

Our proposed algorithm which we called Robust TCP is to make the congestion detection reliable and to distinguish the

causes of losses in order to improve the flow control.

The main idea is to determine CE (i.e. the congestion detection) which impact on the TCP flow performance by

monitoring the TCP flow itself.

The principle is to obtain a detection system at the edge of a network or at the sender side which analyses the TCP

behavior through the observation of both data packets and acknowledgments paths.

So, the scenario is to make a new version of TCP (Robust TCP) without detection of congestion. Robust TCP doesn't

reacts (reducing of Cwnd) whenever it doesn't receive a notification ECN. Robust TCP must interact with ICN algorithm

through ECN. Once we have congestion indication and the congestion event is validated, in this case it must notify the

TCP we are exploring the functionality of Robust TCP and the ICN algorithm with the interaction between each other.

Robust TCP maintains all the functions of TCP Reno (slow start, Congestion avoidance, Fast retransmit and Fast

recovery) and modified by adding error control and limited transmit (like in New-Reno TCP) to avoid unnecessary

timeouts.

Robust TCP is a classic version of TCP but very sensitive to packet loss. It contains the major congestion control

phases:

1. Slow start and congestion avoidance (increase Window size).

2. Fast retransmit (Detection of congestion).

3. Fast recovery.

1. Slow start:

63


� When ACK received: cwnd++ which means for every ACK received, the sender sends two more segments.

� Exponential increase in the window (Every RTT: cwnd = 2*cwnd)

� Threshold (sstrhesh) controls the change to congestion avoidance.

2. Congestion avoidance

� When ACK received: cwnd+ = 1/cwnd.

� Linear increment of cwnd (every RTT: cwnd++) slow start is exists until cwnd is smaller or equal to ssthresh.

Later congestion avoidance takes over.

3. Fast retransmit:

TCP generates duplicate ACK when out-of-order segments are received. In this case Fast retransmit uses "duplicate

ACK" to trigger retransmission packets, so the sender does not wait until timeout for retransmission, sender retransmits

the missing packet after receiving 3

DUPACK.

4. Fast recovery:

TCP retransmits the missing packet that was signaled by three duplicate ACKs and waits for an acknowledgment of the

entire transmit window before returning to congestion avoidance. If there is no acknowledgment, TCP Robust

experiences a timeout and enters the

Slow-start state.

TCP recovers much faster from fast retransmit than from timeout. When congestion window is small, the sender may not

receive enough dupacks to trigger fast retransmit and has to wait for timer to expire but under

Limited transmit, sender will transmit a new segment after receiving 1 or 2 DUPACKs if allowed by receivers advertised

window to generate more dupacks.

Robust TCP is poor in performance without detection of congestion and worse than other TCP like TCP New-Reno and

Sack. It reacts only on the receiving of ECN notification.

Once it doesn't receive a notification that means there is no congestion control on TCP and the window keep increasing,

but in case of receiving ECN that will indicate the occurrence of congestion indication notified by ICN, than Robust TCP

reacts by limiting its sending rate and takes the full meaning of its name.

IV.1 ICN WITH TIMESTAMP

ICN (implicit congestion notification) is an algorithm for congestion detection implemented outside the TCP stack to

analyze TCP flow and to better understand the problem of congestion events and than to conclude if the congestion

occurs in the network or no and it is also more accurate in congestion detection than TCP.

The main goal of ICN is to determine the losses (i.e. the congestion detection) which impact on the TCP flow

performance by observing the flow itself which mean by looking at the losses occurring over an RTT period given.

ICN is a generic algorithm that doesn't depend on the TCP version used which implements a congestion control where a

negative feedback means a loss. It is important to note that ICN doesn't manage the error control which remains under

the responsibility of TCP

Starting from the observation of the data segments and the acknowledgments, we identify each TCP connection with a

state machine. This state machine indentifies the control congestion phase and classifies retransmission as spurious or

not.TCP congestion control reacts following binary notification feedbacks allowing assessing whether the network is

congested or not.

ICN algorithm consists of two states:

1. Normal state: which characterizes TCP connection without losses, in this state no congestion occurs and the sender

receive the ACK normally.

64


2. Congestion state: This state starts from the loss of the first window data segment. When a loss occurs ICN enters in

this state and waits to the congestion event to be validated to notify Robust TCP about this loss. When the top of the

window is acknowledged, ICN enters in the normal state.

To improve the performance of the congestion detection algorithm and especially against spurious timeout we added the

timestamp option, in order once the congestion happens ICN enter in this state and append a timestamp to let the sender

to compute the RTT estimate based on returned timestamp in ACK.

Time stamps used in this state to measure the round trip time (RTT) of a given TCP segment and including retransmitted

segment, this option also can help to eliminate the retransmission ambiguity ( due to false indication) and identifies when

retransmission is spurious or not.

Spurious Timeout are inevitable and not rare in data networks, for this reason and once the congestion event occurs, ICN

enter in the congestion event state, timestamp is added for each data segment. Timestamp can be considered as an

acknowledging mechanism in the time domain.

In the figure (2) shown below we will present the flowchart of TCP Robust with ICN mechanism:

IV.2 Robust TCP and ICN interaction

Figure 2: Robust TCP with ICN detection algorithm

ICN is an accurate congestion detection algorithm where after detecting a loss event in the congestion state, the

congestion event (CE) must be validated.

The validation of CE should lead to a congestion indication which is the principle responsible to inform the Robust TCP

about the congestion. The confirmation method due to a congestion indication is ECN (Explicit congestion notification),

which is the main fag in the ACK to notify the loss to the source TCP. Once the source is signaled by ECN notification it

reacts by reducing its window (Cwnd) and this time Robust TCP takes the full meaning of its name.

After reducing its window, we can notice very well the decreasing of the number of dropped packets (d) in the network

due to using of ICN congestion detector and our TCP becomes better in performance than others like

TCP New-Reno and Sack.

65


V. VALIDATIONS AND EVALUATIONS

In this section we evaluate the performance of Robust TCP with ICN algorithm. The main idea is to build an algorithm of

congestion detection outside the TCP stack that is responsible to detect the loss and notify it to Robust TCP.

The architecture of our tools is shown in the figure (3), which is mainly composed from the following components:

1. Network topology.

2. Traffic model.

3. Performance evaluation metrics.

After the simulation is done, a set of result statistics and graphs are generated.

V .1 Network topology

Figure 3: Architecture of our tools

To study our TCP and ICN behavior we built our Network and application model shown in figure (4), in which source

nodes and sink nodes connect to router 1 or router 2. The bandwidth between the two routers is much lower than the

other links, which causes the link between the routers to be a bottleneck. (Traffic can be either uni-directional or

bidirectional).

V.2 Traffic Model

Figure 4: Network topology

The tool attempts to apply the typical traffic settings. In our application include the FTP traffic that uses infinite, nonstop

file transmission, which begins at a random time and runs on the top of TCP. Implementation details and a

comparative analysis of TCP Tahoe, Reno, New-Reno, SACK and Vegas choices of TCP variant are decided by users.

V.3 Performance evaluation metrics

The metrics used in our simulations are Throughput and Drop ratio. Throughput is the total elapsed flow since the

beginning of simulation time. Throughput may also includes retransmitted traffic (repeated packets).Drop ratio is the

total rate of packet loss during the simulation time. To obtain network statistics, we measure also the drop ratio metric

that result in the failure of the receiver to decode the packet and simulation time is 100 seconds.

66


Robust TCP is poor in performance as a standalone TCP but after adding the ICN it becomes much better (see figure 5)

and accurate than TCP New-Reno as show in the figure (6). To evaluate our scenario, we compare TCP Robust with

other TCP variants (TCP New-Reno) by using different metrics that will show us clearly the improvement of our TCP

version compared to others. (Figure 6 and 7).

Figure 5: Comparison between TCP Robust before and after adding ICN algorithm.

The main difference between Robust and New-Reno TCP occurs in the reaction of each protocol. In the TCP New-Reno

the reaction will be whenever an error or congestion occurs on the network by slowdown the transmission without being

accurate if there is a congestion or not. In addition of that the main problem of New-Reno TCP that it suffers from the

fact that it takes one RTT to detect each packet loss. When the ACK for the first retransmitted segment is received only

then we can deduce which other segment was lost. This problem of inaccuracy in TCP New-Reno is solved by the ICN

algorithm that the ICN receive the packet and check the presence of congestion by using the normal and congestion

phase and by adding the timestamp option which can be make sure of the presence of congestion or no. The deduction of

congestion in TCP Robust is different from New-Reno, it will be deduced after signaling ECN from ICN to TCP robust,

and then the TCP reacts by decreasing the transmission. This accuracy in detection of congestion can be up to 24 % as

difference between the two protocols (Figure 6) before reaction of each one and starting slowdown retransmission.

Due the fast reaction of TCP robust, the transmission of TCP become less than in TCP New-Reno which means that the

throughput in the TCP robust must be less than in New-Reno, this is clear and deduced in the figure 7.

Figure 6: Comparison between TCP Robust and TCP New-Reno

67


In figure (6) represents that the drop ratio is less in Robust than in New-Reno due that TCP reacts only when receiving

ECN which make its reaction faster.

Figure 7: Comparison between TCP Robust and TCP New-Reno

In figure (7) Robust TCP algorithm reaction is faster than the Reaction of New-Reno, thus Throughput in New-Reno is

higher than when using Robust TCP. Congestion detection used by ICN algorithm is more accurate when using the

timestamp option for detecting a spurious timeout which improve more the performance of TCP.

The main difference between spurious timeout algorithms relies on the method how to detect spurious timeout by solving

the retransmission ambiguity in many circumstances. After clarifying this ambiguity TCP can tell whether the data is there

is spurious timeout has happened or not. DSACK, F-RTO and Robust TCP can see the problem of spurious timeout in

different aspects.

DSACK, an extension of TCP SACK, works it out in the sequence space. It requires the TCP receiver explicitly

acknowledging duplicate segments with duplicate SACK options. F-RTO algorithm is used for detecting spurious

retransmission timeouts with TCP. It is a TCP sender-only algorithm that does not require any TCP options to operate-

RTO delays the decision of loss recovery and waits further two ACK. If the first arrived ACK forwards the sender's

transmitting window, TCP concludes a spurious timeout and resume transmitting new data.

Our approach is different than other TCP by using an algorithm of congestion detection outside the TCP code, where it

can detect congestion and spurious timeout by using the timestamp option at the occurrence of loss or congestion event.

The main advantage of ICN with timestamp algorithm is that it can work with spurious timeouts and the others loss

events by detecting the congestion in the network immediately and then directly will be notified to Robust TCP in order

that TCP after this action will reduce its window, which can improve very well the performance of our TCP.

VI. CONCLUSION AND FUTURE WORK

This paper has proposed a new algorithm, which is implemented as a stand alone component and not inside a TCP stack.

This algorithm that interacts with a classic version of TCP is able to detect congestion and notify directly the loss to the

Robust TCP through the congestion notification (ECN) in order to reduce its window which leads to a Robust TCP

compared to other variants like New-Reno and SACK TCP. In our work we demonstrate that congestion event detection

can be realized independently of the TCP code in sake of better detecting congestion occurring in the network.

Following this work and the results obtained so far, we are currently planning to develop more the detection of

congestion by using the delay-based in the congestion detection algorithm (ICN) and the effect of fast reaction of TCP

robust in the Network.

68


REFERENCES

A Comparative Analysis of TCP Tahoe, Reno, New- Reno, SACK and Vegas.

Bhandarkar, S. and Reddy, A.L.N. (2004), Networking, May TCP-Dcr: Making TCP Robust to Non-Congestion Events.

K. Ramakrishnan, S. Floyd, and D. Black, (2001), The addition to explicit congestion notification (ECN) to ip. Request

for comments 3168,IETF.

P. Anelli and F. Harivelo, E. lochin. On TCP congestion events detection.

P.sarolahti and M. kojo. (2005), Forward rto-recovery (f-tro): An algorithm for detecting spurious retransmission

timeouts with tcp and the stream control transmission protocol (sctp).rfc 4138,IETF.

Reiner Ludwig and Randy H..Katz, (2000), The Eifel algorithm: making TCP robust against spurious retransmissions.

SIGCOMM Comput. Common. Rev., 30(1):30-36.

RFC 3649, (2003), High Speed TCP for Large Congestion Windows, S. Floyd.

RFC 793, (1981), Transmission Control Protocol, September .

S. Floyd, (2003), ICSI. RFC 3649 - High Speed TCP for Large Congestion Windows.

69


Ozean Journal of Applied Sciences 3(1), 2010

Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

ANALYSIS OF MICROWAVE SIGNAL RECEPTION USING FINITE DIFFERENCE

IMPLEMENTATION. (A CASE STUDY OF AKURE – OWO DIGITAL MICROWAVE

LINK IN SOUTH WESTERN NIGERIA)

OTASOWIE P.O* and UBEKU E.U.

Dept of Electrical /Electronic Engineering University of Benin, Benin City Nigeria.

*E-mail address for correspondence : potasowie@yahoo.com

______________________________________________________________________________________________

Abstract: In this work, the finite difference method have been used to model microwave signal propagation. The data

used for this analysis were gathered between January and December 2006 in Akure – Owo digital microwave line of

sight link in southwestern Nigeria.The data collected were analyzed using finite difference method and writing a

program in MATLAB 7.0 software program to obtain a model equation for the line of sight link. The results of the

work shows that the months of August, September, July and January have the poorest signal reception while the

months of February, march and April have the best signal reception in the link.The results of the predicted model

were validated by measured data and the results obtained showed that the developed model can be used to accurately

predict the link degradation parameters.

Keywords: Microwave link, finite difference method, average signal level, signal reception.

_____________________________________________________________________________________________

Justification for the work

INTRODUCTION

Microwave signal transmission and reception in Nigeria especially for telephone services is very poor basically

because of non-availability of data for planning and design of microwave links. There is a need for the build up of

such a database in Nigeria [1]

Microwave signal propagation

Microwave radio relay is a technology for transmitting digital and analog signals such as long – distance telephone

calls and the relay of television programs between two locations on a line of sight radio path [ 2, 3 ]

In a microwave radio relay, a line of sight link is required, therefore obstacles, the curvature of the earth, the

geography of the area are important issues to consider when planning radio links.

Microwave propagation hardly occur under ideal conditions, for most communication links, the analysis must be

modified to account for the presence of the earth, the ionosphere and atmosphere precipitates such as fog, raindrops,

snow and hail, for stations on the ground transmitting through the lower atmosphere is complicated by uncontrolled

variables associated with climate weather and path terrain. Signals are said to undergo fading which refers to the fact

71


Ozean Journal of Applied Sciences 3(1), 2010

that time – varying atmospheric processes influence the mechanisms of reflection, refraction and diffraction separately

or in combination, so as to cause signal losses at a receiving antenna [3 ].

Once a microwave signal is radiated by the antenna, it will propagate through space and will ultimately reach the

receiving antenna. As would be expected the energy level of the signal decreases rapidly as the distance from the

transmitting antenna is increased further.

Mathematical Modeling

The finite difference method is a full wave method of parabolic equation that directly solve a wave equation

numerically subject to a number of assumptions and simplifications. The finite difference method is based on

discretisation of the wave equation through the introduction of a rectangular gird and the evaluation of the various

derivative terms using centered finite differences [ 4,5,6,7,8 ].

The derivation of the parabolic equation normally start by reducing Maxwell’s equations to the Helmholtz equation.

However in this instance if we assume the presence of an atmosphere described by a complex refractive index:

n( r)

� �( r)

� �r

( r)

� j�

( r)

�� …………….(1.0)

0

which is a continuously varying function of position. Provided that � �ln n ��1,

the scalar Helmholtz equation

describes accurately each of the Cartesian components of the electric and magnetic fields.[,6,7]

2 2 2

� � � k n � � 0 ………………………(1.1)

0

The wave number in vacuo is now given by k 0 � 2� / �0

. Considering a two dimensional propagation problem

along the great circle path and making the approximation that the earth is flat over a short length for simplicity,

Equation 1.1 can be expanded in Carteisian co-ordinates as:

2 2

� � � �

� � k

2 2

�x

�z

2

0

2

n � � 0

……………….(1.2)

We now introduce the assumption that an a priori preferred direction of propagation exists and identify this with the

x axis. It is, therefore, reasonable that we can write the following form for the solution: [6,7]

( , ) ( , ) exp( 0 ) x jk z x u z x �

� � ………….(1.3)

where the reduced wave amplitude u( x,

z)

can now be assumed to vary slowly along the x direction on the scale of

a free-space wavelength, � . Substituting Equation 1.3 into 1.2 and discarding the common factor exp( 0 ) x jk � after

performing the differentiations yields the following equation for the reduced wave amplitude:

2

� u

� 2 jk 2

�x

0

2

�u

� u

� � k 2

�x

�z

2

0

( n

2

�1)

u � 0

……. (1.4)

Equation 1.4 describes waves propagating both along the positive and negative x directions. By analogy with the

one-dimensional wave equation

2

2

� w 1.

� w � � 1 � ��

� 1 � �

� � 0 �

� 0

2 2 2 � � ��

� �w

�x

c �t

� �x

c �t

��

�x

c �t


which has linearly independent solutions given as:

w � f ( x � ct)

and w � g(

x � ct)

……………………………. (1.5b)

72

0

……………… (1.5a)


Ozean Journal of Applied Sciences 3(1), 2010

These can be identified as forward and backward traveling waves corresponding to the two

differential operators in Equation 1.5a. If we factorise Equation 1.4 into forward and backward traveling wave

operators; then we have

…………………….(1.6)





� jk

� �x


� �

� jk



�x

0

0



jk

jk

0

0

1�

( n

1�

( n

2

2

1 �

�1)

� 2

k �z

1 �

�1)

� 2

k �z

73

0

0

2

2

2







�u

� 0



If you discard the backward traveling wave for consistency with Equation 1.3, then finally, we have,


� �

� jk



�x

0


jk

0

2

2 1 �

�n �1�

� �u

� 0

1� 2 2

k0

�z




……(1.7)

It is to be understood that the differential operator under the square root sign in Equation 1.7 can only be interpreted in

a formal sense. Its numerical evaluation can only be achieved by replacing the square root by a power series, or

rational fractions of operators.

Thus, we rewrite Equation 1.4 as:

�u


� jk �

�x



2

2 1 � �

1 � �n �1�

� �u

� jk �1 � 1�

Q(

x,

z)

�u ………….. (1.8)

2 2

k0

�z



0 1 �

0

The differential operator Q (x, z) must give a significantly smaller answer than the unity operator when operated on

u (x,z), since by assumption, the oscillatory variation of i (x,z) is predominantly along the x direction, perpendicular to

the z axis. Therefore, the z derivative on a scale of a wavelength (1/k0) is much smaller than the unity operator. For

the atmosphere, we also know that n (x,z) � 1, giving: [7]

Q( x,

z)

u(

x,

z)

�� u(

x,

z)

or formally ��1

Q ………………………. (1.9)

The simplest approximation for the square root term is given by the first two terms in its Taylor expansion, namely,

1 Q( x,

z)

� 1�

Q(

x,

z)

/ 2

� ……………….. (1.10)

which finally yields the narrow-angle parabolic equation:

�u


�x

2 jk

2 � � u


� � k 2

� �z

1 2

0

2

0


�n �1�u




………………(1.11)

Parabolic Equation – Finite difference Implementation

This method is based on a more direct discretisaton of Equation 1.11, through the introduction of a rectangular grid

and the evaluation of the various derivative terms using centered finite differences. The various terms appearing in

Equation 1.11 are evaluated at the centre point through their finite difference discrete approximations to yield; [7,8]


Ozean Journal of Applied Sciences 3(1), 2010

n n

u um

um

n

x

k


�1

� 1

( � ) �

…..…………………..(1.12)

� 2

METHODOLOGY

The line of sight microwave link used in this research work is situated between Akure located at latitude 071509.30N,

longitude 0051142.60E (transmitting end) and Owo located at latitude 071220.00N longitude 0053402.00E (receiving

end) over a path length of 41.42km. The Akure – Owo microwave link is owned and managed by NITEL – Nigeria

Telecommunication Ltd. The microwave signal data were gathered between January and December 2006. The

measurement was done with a data acquisition software PROCOMM PLUS 3.0 software program at the receiving

end twice a week over a 24- hour period. This software was installed in a computer system (laptop) type 3050 Acer

Aspire. The Laptop computer system was then connected to the NITEL equipment at Owo. The PROCOMM PLUS

3.0 software detects and captures the received signal values in the link. The system characteristics of the Akure –

Owo digital microwave link is given in Table 1.0.

Table 1.0 System characteristics of the Akure – Owo digital microwave link[9]

Characteristics Akure Owo

Elevation (M) 348 320

Latitude 071509.30N 071220.00N

Longitude 0051142.60E 0053402.00E

Antenna model VHP4 – VHP 4 –

71W

71W

Antenna Height 90.00 90.00

(M)

Antenna Gain

(dbi)

Frequency (MHz) - 7500

Polarization - Vertical

Path length (km) - 41.42

Radio Equipment model - MSM/H7 16E QPS

Transmitted power (dBm) - 25.00 to 28.00

Main received signal (dBm) - 45.03

Received Threshold level (dBm) - 85.50

36.60 36.60

RESULTS AND DISCUSSION

The recorded microwave signal data for the period (January to December 2006) were computed into monthly

averages as shown in Table 2.0

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Ozean Journal of Applied Sciences 3(1), 2010

Table 2.0 Akure – Owo Digital Microwave link, Year 2006 Average monthly data

Month Received Signal Level (dBm)

January - 47.0

February - 36.0

March - 37.0

April - 36.0

May - 39.0

June - 39.0

July - 48.0

August - 50.0

September - 50.0

October - 46.0

November - 40.0

December - 47.0

(i) Variation of Average Signal level with months for Year 2006

The analysis of the results shows that the months of February, March and April have the best signal reception while

the months of August, September and July have the poorest signal reception.

(ii) Analysis of Daily signal reception using the Finite difference model

The figure 1.0 shows the plot of the finite difference implementation of daily received signal level with distance.

Predicted Received Signal Level for Year 2006

The model equation is

Y = 9x10 -32 x 8 -1.4x10 -26 x 7 + 8.8 x 10 -22

- 2.9 x 10 -17 x 5 + 5.4 x 10 -13

Figure 1.0: Daily microwave received signal level with distance

4

x – 5.5 x10 19

6

x

3

x

+ 2.8 x 10 -5 x 2 – 1.0x10 -5 x + 13 ………. (1.13)

If x (dBm) = Received signal level measured in equation (1.13) then Y (dBm) = predicted values.

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Ozean Journal of Applied Sciences 3(1), 2010

For example, on Mondays 15 th February 2006, the signal transmitted was 28dbm while the signal received was -

35dBm. This corresponds to the model deduced as shown in equation 1.13 that if x = 28dbm then y = -35dBm.

CONCLUSION

In this work microwave signal received level were measured on a monthly basis and the finite difference method was

used to develop a model that can predict microwave signal received level on a daily basis.

The result of the research work shows that the months of August, September, July and January have poor signal

reception while the months of February, march and April have good signal reception.

The model equation developed using the finite difference method is reasonably accurate.

REFERENCES

Akleman, F; Sevgi, L (2008) “A novel finite difference time – Domain wave propagation IEE transaction on

Antennas and propagation Vol 48 No 3.

Barclay, L. (2003) “Propagation of Radio waves “IEE London 2 nd Edition pp 169-177.

Bogucci, J; Wielowreyska, E. (2004) “Propagation reliability of line – of – sight radio systems” 17 th International

Symposium and Exhibition on Electromagnetic Compatibility Wroclaw.

Isaakidis, S.A; xenos, T.D. (2004) “Progress in Electromagnetic Research” Aristotle university of Thessaloniki

Greece.

Landstorfer, F.M. (1999) “wave propagation models for planning of mobile communication Networks” Proceedings

of the 29 th European Microwave Conference (EUMC) Vol 1

Matzler, C (2004) “Parabolic Equations for wave propagation and the advanced atmospheric effects prediction

systems” (AREPS) Literar seminar

Nigeria Telecommunication Ltd Journal (1992) Vol 2

Otasowie, P.O; Edeko, F.O. (2008) “An investigation of microwave link degradation due to Atmospheric Conditions”

(A case study of Akure – Owo Digital microwave link) Journal of Advances in materials research and

Systems Technologies II. Trans Tech publications Ltd Zurich Switzerland vol. 62 pp 159-165.

www. Answers.com (2007) “Microwave Radio Relay 15 th February 2007.

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Ozean Journal of Applied Sciences 3(1), 2010

Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Estimation of C factor for soil erosion modeling using NDVI in Buyukcekmece

watershed

Ahmet Karaburun

Fatih University,

Department of Geography,

Buyukcekmece, Istanbul, 34500, Turkey

E-mail address for correspondence: akaraburun@fatih.edu.tr

__________________________________________________________________________________________

Abstract: In order to take measures in controlling soil erosion it is required to estimate soil loss over area of

interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss

Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). The accuracy of these models depends on

parameters that are used in equations. One of the most important parameters in equations used in both of

models is C factor that represents effects of vegetation and other land covers. Estimating land cover by

interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator

that shows vegetation cover. The aim of this study is estimate C factor values for Buyukcekmece watershed using

NDVI derived from 2007 Landsat 5 TM Image. The final C factor map was generated using the regression

equation in Spatial Analyst tool of ArcGIS 9.3 software. It is found that north part of watershed has higher C

factor values and almost 60% of watershed area has C factor classes between 0.2 and 0.4

Keywords: Erosion, RUSLE, USLE, C factor, Landsat, NDVI,

___________________________________________________________________________

INTRODUCTION

Sediment yield studies play key role for various soil and water conservation planning processes including

reservoir sedimentation analysis, studies on river morphology changes and river bed siltation, and agricultural

project planning. Erosion process result in soil loss from a watershed and it is difficult to estimate soil loss as it

arises from a complex interaction of various hydro-geological processes (Singh et al., 2008). Estimating the soil

loss risk and its spatial distribution are the one of the key factors for successful erosion assessment. Thus it can

be possible to develop and implement policies to reduce the effect of soil loss under varied geographical

conditions (Colombo et al., 2005). The accuracy of estimating soil risk depends on model and its factors.

Researchers have developed many predictive models that estimate soil loss and identify areas where

conservation measures will have the greatest impact on reducing soil loss for soil erosion assessments (Angima

et al., 2003).

Those models can be classified into three main categories as empirical, conceptual and physical based models

(Merrit et al.,2003). USLE and its modifications are the examples of empirical models and ANSWER,

CREAMS, and MODANSW are the samples of conceptual models. Examples for the first two groups comprise

the empirical USLE and its modifications, and some of the more comprehensive models like ANSWERS,

CREAMS, and MODANSW. ANSWERS and CREAMS are basically conceptual and eventbased. European Soil

Erosion Models, EUROSEM/KINEROS, EUROSEM/MIKE SHE and SHESED-UK are the physically-based

models that have been developed at catchment or small subbasin scales (Fistikoglu and Harmancioglu, 2002).

Universal Soil Loss Equation (USLE) was designed to predict longtime average soil losses in runoff from

specific field areas in specified cropping and management systems. The USLE (Wischmeier and Smith, 1978)

estimates the average annual soil loss from:

A = R.K.LS.C.P

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Ozean Journal of Applied Sciences 3(1), 2010

where A is the estimated soil loss per year R is the runoff factor, K is the soil erodibility factor, LS is the slope

length and steepness factor, C is the cover and management factor and P is the support practice factor

(Wischmeier and Smith, 1978). The R factor expresses the erosivity occurring from rainfall and runoff at a

particular location. An increase in the intensity and amount of rainfall results in an increase in the value of R.

The K factor expresses inherent erodibility of the soil or surface material. The value of "K" is defined as a

function of the particle-size distribution, organic-matter content, structure, and permeability of the soil or surface

material. The LS factor expresses the effect of topography, specifically hillslope length and steepness, on soil

erosion. An increase in hillslope length and steepness results in an increase in the LS factor. The C covermanagement

factor is used to express the effect of plants and soil cover. Plants can reduce the runoff velocity

and protect surface pores. The C-factor measures the combined effect of all interrelated cover and management

variables, and it is the factor that is most readily changed by human activities. The P factor is the support

practice factor. It expresses the effects of supporting conservation practices, such as contouring, buffer strips of

close-growing vegetation, and terracing on soil loss at a particular site. A good conservation practice will result

in reduced runoff volume, velocity and less soil erosion. The USLE concept has more recently been modified

and adapted by a large number of researchers by including additional data and incorporating research results.

Revised Universal Soil Loss Equation (RUSLE) was developed by integrating several recent techniques and

additional data that improves the accuracy of factors of USLE model (Renard and Freimund, 1994; Renard et al.

1997; Yoder and Lown, 1995). Thus RUSLE was extended to include forest, rangelands and disturbed areas

compared to USLE. The Revised Soil Loss Equation (RUSLE) followed the same formula as the USLE, but it

has a subfactor for evaluating the cover-management factor, a new equation for slope length and steepness, and

new conservation practice values. It is also applicable to non-agricultural conditions such as construction sites.

The RUSLE model is widely used as a predictive model for estimating soil erosion potential and effects of

different management practices for over 40 years (Renard et al., 1997).

One of the most important parameters in USLE and RUSLE equations is the cover management factor (C) that

represents effects of vegetation and other land covers. The C factor reflects the effect of cropping and

management practices on the soil erosion rate. The C factor indicates how conservation plans will affect the

average annual soil loss and how that soil-loss potential will be distributed in time during construction activities,

crop rotations, or other management schemes (Van der Knijff et al., 2000). Vegetation cover protects the soil by

dissipating the raindrop energy before reaching the soil surface. As such, soil erosion can be effectively limited

with proper management of vegetation, plant residue, and tillage (Lee, 2004). In both of USLE and RUSLE, the

C factor is computed using empirical equations that contain field measurements of ground cover. (Wischmeier

and Smith, 1978; Renard et al., 1997). Since the satellite image data provide up to date information on land

cover, the use of satellite images in the preparation of land cover maps is widely applied in natural resource

surveys (Deng et al., 2008; Serra et al.,2008; Yuan,2008).

The traditional method for spatial estimation of C factor is assigning values to land cover classes using classified

remotely sensed images of study areas. At the end of supervised or unsupervised classification, land cover

classes are derived from image for study area and then C factors that are obtained from USLE/RUSLE guide

tables or computed using field observation for each land cover classes are assigned to each pixel in land cover

class (Karaburun, 2009; Efe et al., 2008; Morgan, 1995; Folly et al., 1996; Juergens and Fander, 1993). Since all

pixels in a vegetation class have the same C factor value, those pixels can not represent variation of this

vegetation class over the study area (Wang et al., 2002). Researchers developed many methods to estimate C

factor using NDVI for soil loss assessment with USLE/RUSLE (De Jong 1994; De Jong et al., 1999; De Jong

and Riezebos, 1997; Wang et al., 2002; Lin et al. 2002). These methods employ regression model to make

correlation analysis between C factor values measured in field or obtained from guide tables and NDVI values

derived from remotely sensed images. The unknown C factor values of land cover classes can be estimated using

equation obtained from linear regression analyses. The aim of this study is to estimate C factor values of land

cover classes using NDVI values by regression analysis for erosion modeling in Buyukcekmece Watershed.

Study Area

Buyukcekmece watershed is located in the west of Istanbul and adjacent to the Marmara Sea (Fig.1) and it

contains most important water sources and a dam provides drinking water for Istanbul. The Buyukcekmece

watershed is one of the largest watersheds in Istanbul having an area of about 63000 ha and located 50

kilometers west of the center of Istanbul. Agriculture is one of the most dominant land use patterns in

Buyukcekmece watershed, occupying about 42000 hectares of land which makes around 67 % of the total

surface of watershed. Forest area of watershed is located in the west side and covers about 8000 hectares. The

upper side of watershed is forest and receives annual average rainfall about 750 mm with annual average

temperature 17 0 C. The climate of watershed is influenced by Mediterranean climate and Black Sea climate.

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Fig.1 Study area

Normalized Difference Vegetation Index (NDVI)

Ozean Journal of Applied Sciences 3(1), 2010

METHODOLOGY

Remote sensing techniques are employed for monitoring and mapping condition of ecosystems of any part of

earth. Vegetation cover is the one of most important biophysical indicator to soil erosion. Vegetation cover can

be estimated using vegetation indices derived from satellite images. Vegetation indices allow us to delineate the

distribution of vegetation and soil based on the characteristic reflectance patterns of green vegetation. The

Normalized Difference Vegetation Index (NDVI), one of the vegetation indices, measures the amount of green

vegetation. The spectral reflectance difference between Near Infrared (NIR) and red is used to calculate NDVI.

The formula can be expressed as (Jensen, 2000);

NDVI = (NIR – red) / (NIR + red)

The NDVI has been used widely in remote sensing studies since its development (Jensen, 2005). NDVI values

range from -1.0 to 1.0, where higher values are for green vegetation and low values for other common surface

materials. Bare soil is represented with NDVI values which are closest to 0 and water bodies are represented

with negative NDVI values (Lillesand et al., 2004: Jasinski, 1990; Sader and Winne, 1992). More than 20

vegetation indices have been proposed and used at present. Since NDVI provides useful information for

detecting and interpreting vegetation land cover it has been widely used in remote sensing studies (Gao, 1996:

Myneni and Asrar, 1994; Sesnie et al., 2008).

A time-series of NDVI were derived from Landsat 5 TM images acquired on April, May, June and August 2007.

An average NDVI of watershed area was calculated using those NDVI images (Fig.2).

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C Factor Estimation

Ozean Journal of Applied Sciences 3(1), 2010

Fig.2 Average NDVI map of Buyukcekmece watershed

Soil loss is very sensitive to vegetation cover with slope steepness and length factor (Renard and Ferreira 1993;

Benkobi et al., 1994; Biesemans et al., 2000). Vegetation cover protects the soil by dissipating the raindrop

energy before reaching soil surface. The value of C depends on vegetation type, stage of growth and cover

percentage (Gitas et al., 2009). The C factor values vary between 0 and 1 based on types of land covers. Since

NDVI values have correlation with C factor (De Jong, 1994; Tweddales et al., 2000; De Jong et al., 1999; De

Jong and Riezebos, 1997). Many researchers used regression analysis to estimate C factor values for land cover

classes in erosion assessment (Lin et al., 2002; 2006; Symeonakis and Drake, 2004; Van der Knijff et al., 2002).

The goal of regression analysis is to estimate the unknown values of dependent variable based upon values of an

independent variable using a mathematical model. The linear or non-linear regression equations are constructed

using correlation analysis between NDVI values obtained from remotely sensed image and corresponding C

factor values obtained from USLE/RUSLE guide tables or computed using field observation.

Fig.3 Workflow of C factor estimating using NDVI

The study assumes that there exists a linear correlation between NDVI and C factor and uses bare soil and forest

NDVI values as reference values (Fig.3). Sample NDVI values were collected for bare soil and forest land cover

classes from average NDVI image. Since C factor values range from 0 for well-protected soil to 1 for bare soil

(Pierce et al.,1986; Vicenta et al., 2007) the C factor values for bare soil and forest land cover were set to 1 and

0, respectively in the regression analysis. Fig.4 shows the graph of the regression equation. The line in Fig.4 is

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Ozean Journal of Applied Sciences 3(1), 2010

the regression line that describes relationship between C and NDVI values and R shows the correlation

coefficient of regression analysis.

The regression equation was found as;

C factor = 1.02 – 1.21 * NDVI

The final C factor map was generated using the regression equation in Spatial Analyst tool of ArcGIS 9.3

software. The graphs of regression analysis and C factor are given in Fig. 4 and Fig.5 respectively.

RESULTS

As can be seen from Table 1, Buyukcekmece experienced lowest mean NDVI values in August. Since watershed

consists of agricultural areas the mean NDVI values of April, May and June are close to each other. Mean NVDI

values of August are lowest because there is no vegetation on agricultural areas.

Table 1 NDVI values of Landsat images

Image Date Max NDVI Min NDVI Mean NDVI

April 2007 1 -1 0,395

May 2007 1 -1 0,40

June 2007 1 -1 0,31

August 2007 0,66 -0,43 0,09

Fig.4 Linear regression of NDVI and C factor values

As seen from Fig.5 the north part of watershed is represented by 0-0.1 C factor class since it is occupied by

forest. Water bodies like Buyukcekmece Lake are represented by 0.9-1.0 C factor class. The agricultural areas of

watershed are represented by C factor classes from 0.2 to 0.4

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Ozean Journal of Applied Sciences 3(1), 2010

Fig.5 C factor map of Buyukcekmece Watershed

The estimated C factor values through regression equation were divided into ten categorical classes and those

classes vary between 0-0.1 and 1.0. The pixel numbers of those classes are shown in Fig.6. Since agricultural

areas cover almost 60% of watershed area the C factor classes 0.2-0.3 and 0.3-0.4 contain the highest pixel

number respectively. As shown in Fig.6, 0.2-0.3 class has about 28% of total pixels while 0.3-0.4 has about 15%

of total pixels. The 0.9-1.0 class has the lowest pixel number.

Fig.6 Pixel distribution of the C factor map based on NDVI

CONCLUSION

An attempt has been made to estimate C factor values of land cover classes using NDVI values for modeling soil

erosion using ArcGIS 9.3 software. A regression analysis was performed between NDVI and C factor using an

assumption. C factor values were assigned to pixels of NDVI image through regression equation. Based on an

assumption, the C factor map of Buyukcekmece watershed was produced to use in soil erosion methods such as

USLE and RUSLE based on an assumption that NDVI and C factor values are correlated with each other. The

results revealed that large parts of areas were assigned to C factor classes that vary between 0.2 and 0.4.

It should be noted that C factor values can be precisely estimated using empirical equations that contain field

measurements of land cover classes. However, this study shows that NDVI based regression method offers an

optimal method to estimate C factor values of land cover classes of large areas in a short time.

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Ozean Journal of Applied Sciences 3(1), 2010

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Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Physiological properties studies on essential oil of Jasminum grandiflorum L. as

affected by some vitamins

Rawia.A.Eid, Lobna, S. Taha*, and Soad , M.M. Ibrahim

Department of Ornamental Plants and Woody Trees,

National Research Centre, Dokki, Cairo, Egypt

*E-mail address for correspondence: lobnasalah82@yahoo.com

____________________________________________________________________________________

Abstract : A field experiment was conducted out during 2008 and 2009 seasons at Gezayh village, Imbaba

district, Giza Governorate, Egypt. The aim of this work is to study the effect of foliar application of various

concentrations (50, 100 and 150 ppm) of ascorbic acid, Thiamin and α –tocopherol separately or

collectively on some flower characters (flower yield and weight of flowers), oil pattern (essential oil

concrete percent, yield and some constituents of oil), physiochemical properties of oil and some chemical

composition of Jasminum grandiflorum L. Promoting results were obtained with foliar application of all

treatments, especially those of Ascorbic acid + Thiamin + α –tocopherol at 100 ppm of each or α –

tscopherol at 150 ppm alone on flower yield, weight of flowers, oil concrete percent and oil yield as well

as chemical constituents (soluble, non-soluble sugars and carbohydrates). Gas liquid chromatography of

the oil of control plants and those which showed increase in the oil percent revealed that the major

components, i.e. Benzyl Benzoate, benzyl acetate, eugenol, trans-methyl jasmonate and cis jasmone

pronouncedly increased depending on the applied vitamin (ascorbic acid, Thiamin and α –tocopherol)

which also showed a stimulatory effect on physiochemical properties of oil such as refractive index,

specific gravity, ester number and acid number as good conductor of oil quality.

Keywords: Ascorbic acid, Thiamin , α –tocopherol, jasmin

_____________________________________________________________________________________

INTRODUCTION

Jasmine (Jasminum grandiflorum L.) is an ornamental plant of Oleacae. It is semi-evergreen to deciduous

shrub reaching a length of 8 meters, often with pendulous branches. The leaves are odd-pinnate wit 7 to 9

leaflets and used medicinally in skin diseases, odontalgia, otalgia, wounds, etc. (Kulkarmi and Ansari,

2004; Sharma et al., 2005).

The flowers are white with faint, pinkish streaks, delightfully fragment, and borne in lax, terminal

inflorescences. These flowers are not only essential to the perfumery industry but also have been highly

appreciated by orientals since time immemorial. The pretty jasmine flower originated in the lower valleys

of the Himalayas of northern India (Braja et al ., 1990). The shrub is widely cultivated in the plains and

on the hills specially in Kashmir, Afghanistan, Persia, France, China, Japan and Egypt (Frank and Amelio,

1999).

Jasmine oil has great value for treating sever depression, respiratory tract, for muscle pain and for toning

the skin. This oil is expensive. It takes approximately 800 kilos of petals or 10000 flowers, to make 1 kilo

of concrete jasmine. Egypt is the main producer of jasmine oil.

Plants have a small molecule antioxidants (e.g. ascorbic acid, vitamin C), glutathion and tocopherol

(vitamin E) that they have signaling roles in plant development. In general, the energy metabolism

pathway could be affected by one or another of these substances (Robinson, 1973; Pallanca and

Smirnoff, 2000).

Ascorbate is the most abundant antioxidant in plants but little was known about its biosynthesis.

Smirrnoff et al., (2001) proposed a biosynthetic pathway and identified novel some enzymes. They also

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Ozean Journal of Applied Sciences 3(1), 2010

reported that ascorbate is synthesized from L-galactose via GDP-mannose and GDP-L-galactose. El-

Kobisy et a.,l (2005) stated that Ascorbic acid is synthesized in the higher plants and affects plant growth

and development, it is product of D-glucose metabolism which affects some nutritional cycles activity in

higher plants and play an important role in the electron transport system. Ascorbic acid (vitamin C) is

known as a growth regulating factor which influences many biological processes, Price (1966). Robinson

(1973) reported that Ascorbic acid acts as co-enzymatic reactions by which carbohydrates; proteins are

metabolized and involved in photosynthesis and respiration processes.

Ascorbic acid is an important antioxidant, which reacts not only with H2O2 but also with O2, OH and lipid

hydroperoxidase (CSIR, 1992; Jacobs et al., 2000). A high level of endogenous ascorbate is essential

effectively to maintain the antioxidant system that protects plants from oxidative damage (Cheruth, 2009).

Tarraf et al., (1999) on lemongrass (Cympapogom citrates L.) and Farahat et al (2007) on Cupressus

semperviren L. reported that foliar application of ascorbic acid caused pronounced increases in vegetative

growth and chemical constituents as well as essential oil percent, oil yield per plant.

Thiamin (vitamin B1) is a necessary ingredient for the biosynthesis of the coenzyme Thiamin

pyrophosphate, so it plays an important role in carbohydrate metabolism. It is an essential nutrient for both

plants and animals.

In plants, it is synthesized in the leaves and is transported to the roots where it controls growth. Thiamin is

an important cofactor for the translocation reactions of the pentose phosphate cycle, which provides

pentose phosphate for nucleotide synthsis and for the reduced NADP required for various synthetic

pathways (Kawasaki, 1992). Youssef and Talaat (2003) reported that pronounced increases in vegetative

growth and chemical constituents of rosemary plants by foliar application of thiamine.

Alpha-tocopherol (vitamin E) is low molecular weight lipophilic antioxidant which mainly protect

membrane from oxidative damage (Asada, 1999). Zhang et al., (2000) reported a positive correlation

between α-tocopherol and shoot or root growth in two grass species grown under drought. Tocopherols

were proposed to function in relation to their antioxidant properties being prominent in protection of

polysaturated fatty acids from lipid peroxidation (Bosch, 1995). Recently, tocopherol had an antioxigenic

property when added to green lubricating oil as rapeseed oil (Xiao et al., 2008).

The aim of the present study was to reveal the best level to apply of ascorbic, thiamin and α-tocopherol

which could improve the flower characters, chemical constituents and essential oil production of Jasminum

grandiflorum L.

Materials and methods

A field experiments were conducted out at Gezayh village, Imbaba district, Giza Governorate, Egypt during

two successive seasons of 2008 and 2009. The aim objective of this study was to investigate the effect of

foliar application of ascorbic acid, Thiamin and α –tocopherol on yield of flowers, oil pattern and chemical

constituents of Jasminum grandiflorum L. cv. The investigated soil characterized by coarse sand 54%,

fine sand 1%, silt 23 %, clay 22%, pH 7.5, EC 3.79 dSm -1 , and (N 35.3, P 22.6 and K 5.6 mg/100 g soil).

Thirty three years old trees of jasmine were planted 2X2 m apart (1000 tree /fed). The experimental area

was irrigated by flood irrigation system.

Trees were sprayed twice with freshly prepared solutions of ascorbic acid, thiaminand α-tocopherol each at

50, 100 and 150 ppm, and combination of the different concentrations of the three factors had been also

carried out, in addition to the untreated plants (control) which were sprayed with tap water. Foliar

application of ascorbic acid, thiamine and α-tocopherol carried out two times of 30 days intervals, starting

at one month after March at both seasons.

During the flowering period of each season, the following data were recorded: flowers yield/tree (kg) and

weight of 100 flowers (g). Jasmine concrete was extracted from the flowers using a solvent extraction

system of N-hexane according to Guenther (1961).

Flowers are placed in vessel and covered with the solvent such as hexan, it gently heated electrically while

the solvent extracts the fragments molecules of the plant. The fragment chemicals are transferred to the

alcohol which is removed by low heat distillation. The essential oil was dried over anhydrous sodium

sulfate and stored at 4-6 o C. The essential oil was subjected to Gc/Ms analysis and its components were

identified by matching their relative retention times in conjunction of discriminating Ms ions against a

computer library file of large number of data obtained under identical experimental conditions (Adams,

1995). Gc/Ms Analysis was carried out on finningan Mat SSQ 7000 mass sepctometer directly coupted to

a varion 3400 gas chromatography equipped with DB-5 (0.25 mm i.d. dX30m, 0.25 coating thickness,

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Ozean Journal of Applied Sciences 3(1), 2010

fused silica capillary column using helium as the carrier gas at flow rate of 1.017 ml/min injector

temperature, 220 o C transfer/line, 250 o C oven temperature programmed, 60 to 250 o C at 3 o C/min.

Some jasmine oil characters i.e. refractive index at 20 o C, specific gravity at 15 o C, acid number and ester

number were determined according to Guenther (1961). Also, total carbohydrates and soluble and non

soluble sugars % in the flowers were estimated according to Herbert et al (1971). The recorded data

(means of the two growing seasons) were statistically analyzed using the completely randomized design in

factorial arrangement according to the procedure of Snedecor and Cochran (1980), where the means of

the studied treatments were compared using LSD test at 0.05 of probability.

Flower characters

RESULTS AND DISCUSSION

Data presented in Table (1) reveled that all treatments of ascorbic acid, thiamine and α-tocopherol

separately or collectively significantly increased flower yield/tree and weight of flowers (100 flowers (gm))

of Jasminum grandiflorum L. trees compared with untreated plants. The highest increases in flower yield

and fresh weight of flowers were observed in plants treated with Asc. 100 ppm + thiamin 100 ppm + αtocopherol

100 ppm followed by α-tocopherol 150 ppm. The increments were 76.68 and 75.21 %, for

flower yield than the corresponding values of control plants, the fresh weight of f lowers increased by 56.69

and 53.42 % than the corresponding values of the control plants. Similar results were obtained by El-

Quesni et al (2009) who revealed that foliar application of Ascorbic acid and α-tocopherol on Hibiscus rosa

, Sineses L. plants significantly increased number of flower/plant and fresh weight of flowers gm/plant

compared with untreated plants. The stimulatory effects of ascorbic acid may be attributed to its role in the

regulation of cell division, differentiation and enhancement of leaf expansion (Noctor and Foyer, 1998).

The effect of thiamin was showed by Kawasaki (1992) who reported that thiamin (vitamin B1) is an

essential nutrient for plant growth. It is synthesized in the leaves and is translocated to the roots where it

controls growth. In addition, α-tocopherol interacts with the polyunsaturated acyl groups of lipids, stabilize

membranes, protect chloroplast from photooxidation and help to provide an optimal environment for

photosynthetic machinery (Jaleel et a.l, 2006 and Jaleel et al., 2007).

Essential oil concrete percent and oil yield

Data given in Table (1) show that the foliar application of Ascorbic acid , thiamin, α-tocopherol or the

combination of them significantly increased both jasmine concrete essential oil percent and oil yield as

gm/tree compared to control plants. The highest increment was obtained with treatments of Ascorbic acic

100 ppm + thiamin 100 ppm + α-tocopherol 100 ppm or α-tocopherol 150 ppm alone. It could be deduced

from the present results that both concrete essential oil percent and oil yield (g/tree) responded to foliar

application of vitamins. In support, Hasnaa et al (2009) on Pelargonium graveolens L. indicated that αtocopherol

treatments at 50 and 100 mg/l significantly increased concrete essential oil percent and yield.

This might be due to Alfa-tocopherol could cause a pronounced enhancement of both synthesis and

accumulation of oil. Also, Gamal El-Din (2005) on sunflower plants, reported that ascorbic acid

significantly increased oil percentage of seeds.

Essential oil constituents

Data represented in Table 2 indicates that oil of treated and control plant mainly consisted from benzyl

benzaoat as major constituent (20.1-26.6 %), followed by benzyl acetate (4.8-7.7%) , benzyl alcohol (1.3-

2.7%), eugenol (2.0-4.0%), trans-methyl Jasmonate (5.0-7.8%), cis jasmone (2.3-7.1%) and jasmine lactone

(3.1-8.5%). On the other hand, Gas liquid chromatography showed that oil consists of other constituents

such as n-acetyl and methyl anthranilate. Benzyl benzoate content was pronouncedly increased at

treatment (150 ppm) of Ascorbic acid, thiamin or α-tocopherol. The highest increment was obtained with

their combination treatment at concentration of 100 or 150 ppm. Similar trend was found in case of benzyl

acetate, benzyl alcohol, eugenol, trans-methyl jasmonate and cis jasmone contents. However, treatment of

Ascorbic acid 100+ Thiamin 100 ppm + α-tocopherol 100 ppm gave the highest content of n-acetyl.

Highest content of methyl anthranilate was obtained with α-tocopherol (100 ppm). These results were in

agreement with those obtained by Youssef and Iman (2003) on Rosmarinus officinals L. who found that oil

composition responded greatly to foliar spray of the vitamins nicotineamide, ascorbic and thiamin at

different rates of application. Hasnaa et al., (2009) reported that Gas-liquid chromatography of the oil of

Pelargonium graveolens L. revealed that the major components, i.e. citronellol and linalool pronouncedly

89


Ozean Journal of Applied Sciences 3(1), 2010

increased depending on the applied stigmasterol or α-tocopherol. Therefore, one can conclude the positive

response of jasmin oil constituents depended on the level of applied ascorbic acid, thiamin and αtocopherol.

Essential oil physiochemical properties

Results in Table 3 showed that refractive index of jasmine oil at 20 o C under treatments (ascorbic acid,

thiamin, α-tocopherol and their combination) ranged from 1.41 to 1.50 in comparison with 1.3 in the

control treatment. α-tocopherol (100 or 150 ppm) or Ascorbic acid + thiamin + α-tocopherol (50, 100 or

150 ppm) resulted in the highest refractive index value of jasmine oil. Refractive index of oil increases

with increase in the number of double bonds (iodine value). In general, the refractive indices of oils relate

to the degree of unsaturation in a linear way (Rudan-Tasic & Klofutar, 1999). Also, the specific gravity is

a good indicative of purity of oil and depends on the number of double bonds. At any given temperature,

specific gravity increases as the mean molecular weight decreases with increase in degree of unsaturation

(higher iodine value). In our study, we can notice that specific gravity of oil under treatments ranged from

0.93 to 0.99 in comparison with 0.82 in the control treatment (Table 4).

Results showed that the ester no. of jasmine oil were 50.0 to 55.8 with tested treatments, compared with

48.2 in the control. The acid no. of jasmine oil was 40.3 to 50.8 with various treatments, compared with

45.3 in the control. The acid value is an indirect measure of free fatty acid contents present in oil. Hence it

is not desirable, because they render unpleasant odor and deteriorate the quality of the product (Muhammad

et al., 1999). However, the fragrance of jasmine is characterized by "jasmonoid" compounds, whose

biosynthesis from unsaturated fatty acids. Under study, the results in Table 4, indicates that both Ascorbic

acid and thiamin at 50, 100 and 150 ppm reduced the acid number than that of control treatment. In

support, Ismail et al, 2007 indicated that refractive index of jasmine oil at 20 o C is 1.04, specific gravity of

oil at 15 o C is 0.4113, ester no. is 46.34 and the Acid no. of jasmine oil is 43.03 in untreated plants.

Chemical constituents

Data presented in Table 4 show that all treatments of Ascorbic acid, thiamin and α-tocopherol separately or

collectively significantly increased soluble sugars, nonsoluble sugars and total carbohydrate %. The

highest increment was observed in case of treatment Ascorbic acid + thiamin + α-tocopherol each at 100

ppm followed by α-tocopherol 150 ppm. The increments were 54.6 and 52.11 % for soluble sugars, 73.29

and 69.59 % for nonsoluble sugars and 48.84 and 40.78 % for total carbohydrates than the corresponding

values of the control plants., these results could be explained by the findings obtained by Price (1966) who

reported that ascorbic acid increased nucleic acid content, especially RNA and protein content of wheat

grains. It also influenced by synthesis of enzymes, and proteins, in addition, it acts as co-enzyme in

metabolic changes (Reda et al., 1977; Fadl et al, 1978 and Abdel-Halim, 1995). These results are also in

agreement with those obtained by Kawasaki (1992) who reported that thiamine (vitamine B1) is a

necessary ingredient for the biosynthesis of the co-enzyme thiamin pyrophosphate , in this latter form it

plays an important role in carbohydrate metabolism. El-Bassiouny et al., (2005) reported that foliar spray

with α-tocopherol on faba bean plant induced increments in yield components. Also , El-Quesni et al.,

(2009) indicated that foliar application of Asc. acid and α-tocopherol separately to hibiscus plants

significantly increased total soluble sugars through flowering stage.

90


Ozean Journal of Applied Sciences 3(1), 2010

Table 1: Flower characters, oil percent and oil yield (g/tree) of Jasminum grandiflorum L. plants as

affected by Ascorbic acid, thiamin and α-tocopherol. (Average of the two seasons)

Treatments

Conc.

ppm

Flower yield

kg/tree

91

Weight of 100

flowers (gm)

Concrete

(%)

Oil yield

(g/tree)

Control 0.87 6.8 0.13 1.13

Ascorbic acid 50 1.74 8.70 0.20 3.48

100 2.89 11.90 0.25 7.23

150 3.15 13.40 0.29 9.14

Thiamin 50 1.05 8.3 0.18 2.29

100 1.85 9.0 0.23 4.26

150 2.34 10.5 0.19 4.45

α-tocopherol 50 2.11 10.3 0.22 4.64

Ascorbic acid 50 + Thiamin 50 +

α-tocopherol 50 ppm

Ascorbic acid 100 + Thiamin 100 +

α-tocopherol 100 ppm

Ascorbic acid 150 + Thiamin 150 +

α-tocopherol 150 ppm

100 3.00 12.0 0.28 8.40

150 3.51 14.6 0.32 11.23

3.11 13.6 0.26 8.09

3.73 15.7 0.34 12.68

2.15 14.2 0.32 6.88

LSD 5% 0.31 0.25 0.01 0.05


Ozean Journal of Applied Sciences 3(1), 2010

Table 2: Major constituents of essential oil from Jasminum grandiflorum L. as affected by Ascorbic acid, thiamin and α-tocopherol.

Order Retention

time

1 0.532

(Average of the two seasons)

Treatments

Constituents

Benzyl

Benzoat&Photol

Control

Ascorbic acid Thiamin α-tocopherol

92

ppm

Asorbic acid+Thiamin +

α-tocopherol

50 100 150 50 100 150 50 100 150 50 100 150

20.1 21.2 21.5 23.0 21.5 21.5 23.0 21.5 21.8 23.4 22.5 26.5 26.6

2 0.729 Benzyl Acetate 4.8 5.2 5.9 6.8 5.0 5.8 6.8 5.8 6.4 6.8 6.8 7.5 7.7

3 0.838 Benzyl Alcohol 1.3 1.7 2.1 2.2 1.8 2.1 2.5 1.5 2.1 2.4 1.9 2.7 2.6

4 0.919 Eugenol 2.0 2.1 2.5 2.9 2.0 3.3 2.7 2.2 2.5 3.1 2.5 3.8 4.0

5 1.234

Trans-methyl

Jasmonates

5.0 5.8 6.5 7.1 5.8 6.8 7.0 5.7 6.6 7.6 5.9 7.8 7.6

6 1.641 Cis Jasmone 2.3 2.5 3.3 6.2 1.8 3.7 5.8 2.4 3.4 6.5 2.0 7.0 7.1

7 1.845 Jasmine Lactone 3.1 5.5 6.2 7.4 4.3 5.7 4.5 6.5 7.4 8.5 7.0 7.9 7.5

8 1.941 n-acetyl 0.81 1.0 1.5 1.8 1.1 1.3 1.6 1.4 1.8 2.2 2.2 2.5 1.9

9 1.958

Methyl

anthranilate

1.2 1.7 1.9 2.1 1.3 1.6 1.3 2.6 3.2 3.6 2.8 3.1 3.0


Ozean Journal of Applied Sciences 3(1), 2010

Table 3: Physiological properties of essential oil from Jasminum grandiflorum L. as affected by Ascorbic acid, thiamin and α-tocopherol.

Properties

(Average of the two seasons)

Treatments

Control

Ascorbic acid Thiamin α-tocopherol

93

ppm

Asc.+Thiamin+

α-tocopherol

50 100 150 50 100 150 50 100 150 50 100 150

Refractive index 20 o C 1.31 1.43 1.43 1.43 1.41 1.41 1.42 1.43 1.48 1.49 1.49 1.50 1.50 0.02

Specific gravity 0.82 0.94 0.94 0.94 0.93 0.94 0.94 0.96 0.97 0.97 0.99 0.99 0.99 0.02

Ester number 48.2 50.0 51.3 51.9 50.0 51.2 51.8 50.1 55.2 55.7 55.2 55.6 55.8 0.12

Acid number 45.3 44.2 44.5 44.8 40.7 40.9 40.3 49.2 50.1 50.7 50.2 50.8 50.5 0.022

LSD

5%


Ozean Journal of Applied Sciences 3(1), 2010

Table 4: Chemical constituents of Jasminum grandiflorum L.flowers (%) as affected by Ascorbic acid,

thiamin and α-tocopherol. (Average of the two seasons)

Treatments

Conc.

ppm

94

Soluble

sugars

Non-soluble

sugars

Total

carbohydrate

Control 10.2 2.11 13.2

Ascorbic acid 50 15.2 2.81 19.8

100 16.7 3.57 20.4

150 17.9 4.11 21.5

Thiamin 50 13.3 2.73 17.3

100 13.2 3.84 18.4

150 11.4 3.65 16.2

α-tocopherol 50 17.3 3.41 20.4

Ascorbic acid 50 + Thiamin 50 +

α-tocopherol 50 ppm

Ascorbic acid 100 + Thiamin 100 +

α-tocopherol 100 ppm

Ascorbic acid 150 + Thiamin 150 +

α-tocopherol 150 ppm

100 19.5 5.81 22.2

150 21.3 6.94 22.8

20.4 6.7 22.6

22.5 7.9 25.8

21.0 5.8 24.3

LSD 5% 1.82 0.23 0.13


Ozean Journal of Applied Sciences 3(1), 2010

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ISSN 1943-2429

© 2010 Ozean Publication

Ozean Journal of Applied Sciences 3(1), 2010

Effect of zinc and / or iron foliar application on growth and essential oil of sweet

basil (Ocimum basilicum L.) under salt stress

H.A.H. Said-Al Ahl* and Abeer A. Mahmoud **

* Department of Cultivation and Production of Medicinal and Aromatic Plants, National Research

Centre, Dokki, Giza, Egypt.

** Department of Botany (Plant Physiology Section), Faculty of Agriculture, Cairo University.

*Corresponding Author: saidalahl@yahoo.com

___________________________________________________________________________________

Abstract: The effect of salinity and Fe and/or Zn application on the vegetative growth, dry matter yield

and essential oil production and its constituents were studied at the farm station of the National

Research Centre, at Shalakan, Kalubia Governorate, Egypt on sweet basil (Ocimum basilicum L.)

during 2006 and 2007 seasons. The highest plant height, number of branches, fresh and dry matter

yield as well as essential oil yield was recorded in normal soil which decreased with the increase in the

salinity. Increasing the soil salinity increased essential oil %. The addition of micronutrients had an

active effect comparing with control, highest plant height and number of branches being with iron

application and zinc gave the highest value of fresh weight, whereas a mixture of iron + zinc gave the

highest values of dry matter and essential oil yield under normal soil condition. In contrast application

a mixture of iron + zinc gave the highest essential oil % under soil salinity condition. Concerning

essential oil constituents, linalool and methylchavicol were the major compounds. The concentration of

linalool and methylchavicol decreased with saline soil treatment. Addition of micronutrients decreased

linalool in normal soil; on the contrary there was an increase in linalool content by using soil salinity

treatment. Highest linalool content (52.14%) was recorded in saline soil with spraying mixture of

zinc+iron. Spraying plants with zinc and /or zinc+ iron increased the content of methylchavicol in

normal soil, and it's content (44.01%) was the highest in normal soil with zinc spraying. All the

spraying treatments except mixture of zinc+iron increased the content of methylchavicol in saline soil.

The highest decrease in linalool (25.687%) and methylchavicol (20.34%) was caused with zinc+iron in

normal and saline soils, respectively.

Key words: sweet basil, Ocimum basilicum L., foliar application, iron, zinc, salt stress, essential oil

________________________________________________________________________________

INTRODUCTION

The Ocimum genus, belonging to the Lamiaceae family, includes herbs and shrubs distributed in

tropical and subtropical regions of Asia, Africa and the Americas. The most important species of

Ocimum genus is O. basilicum L.; this species, usually named common basil or sweet basil, is

considered economically useful because of their basic natural characteristics as essential oil

producers (Lawrence, 1993). Sweet basil is a popular culinary herb used in food and oral care

products (La-Chowicz et al., 1996; Machale et al., 1997). The essential oil of the plant is also used as

perfumery. Also, basil is well known as a plant of a folk medicinal used as carminative, galactogogue,

stomachic and antispasmodic tonic and vermifugem, also, basil tea taken hot is good for treating

nausea, flatulance and dysentery (Ozcan and Chalchat, 2002; Sajjadi, 2006). Basil is used in pharmacy for

diuretic and stimulating properties, in perfumes and cosmetics for its smell; in fact, it is a part of many

fragrance compositions (Bariaux et al., 1992; Khatri et al., 1995). Antiviral and antimicrobial activities

of this plant have also been reported (Chiang et al., 2005). Available literature data indicates that

there is a great deal of diversity in growth characteristics and the composition of essential oil of the

genus Ocimum. Such observations have been attributed to the abundant cross-pollination that

occurs within this genus resulting in considerable degrees of variation in the genotypes

(Lawrence, 1988). The difference in the essential oil compositions in O. basilicum cultivated in

different geographical localities led to the classification of basil into chemotypes on the basis of the

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Ozean Journal of Applied Sciences 3(1), 2010

prevalent chemical components (Lawrence, 1992) or components having composition greater than

20 percent (Grayer et al., 1996). There are usually considerable variations in the contents of the

major components within this species. In a study of essential oils of different geographical origins,

(Lawrence, 1988) found that the main constituents of the essential oil of basil are produced by two

different biochemical pathways, the phenylpropanoids (methyl chavicol, eugenol, methyleugenol and

methyl cinnamate) by the shikimic acid pathway, and the terpenes (linalool and geraniol) by the

mevalonic acid pathway. Other latter studies on the basils from other geographical regions have

added new chemotypes to that list based on the established classification scheme (Grayer,

1996; Lawrence, 1992).

Salinity is one of the major factors that affect plant growth; it is a serious problem in many areas of

world's causing considerable loss in agricultural production (Bray et al., 2000; Shao et al., 2008; Wu et

al., 2007). Soil salinity resulting from natural processes or from crop irrigation with saline water,

occurs in many arid and semi-arid regions of the world (Lauchli and Epstein, 1990). The deleterious

effects of salinity on plant growth are associated with (1) low osmotic potential of soil solution (water

stress), (2) nutritional imbalance, (3) specific ion effect (salt stress), or (4) a combination of these

factors (Yildirim and Taylor, 2005). Saline soil are generally dominated by sodium ions, with the

dominant anions being chloride and sulphate, they have a high sodium absorption rate with a high pH

and electrical conductivities (>4 dsm -1 ) (Flowers and Flowers, 2005).

In saline soils, the solubility of micronutrients is particularly low, and plants grown on such soil often

suffer from deficiencies in these elements. Soil salinity may reduce micronutrients uptake due to

stronger competition by salt cations at the root surface (Marschner and Romheld, 1994; Page et al.,

1990). Soluble ferrous fe tended to become oxidized to ferric oxide which was insoluble as well as the

limitation of iron uptake by root cell cytosol (Nikolic and Kastori, 2000) and inhibit iron transport to

shoots and its transfer from apoplasm to cytoplasm in shoot tissues (Nikolic and Romheld, 2002). Zinc

is necessary for root cell membrane integrity (Welch et al., 1982). As suggested by Parker et al. (1992),

root cell membrane permeability is increased under zinc deficiency which might be related to the

functions of zinc in cell membranes. From this point of view, external zinc concentrations could

mitigate the adverse effect of NaCL by inhibiting Na and /or Cl uptake or translocation. Alpaslan et al.

(1999) concluded that in the salt affected areas, zinc application could alleviate possible Na and Cl

injury in plants. Foliar spraying under these conditions could be much more efficient than any

application of nutrients to the soil (Horesh and Levy, 1981).

Iron (Fe) is a cofactor for approximately 140 enzymes that catalyze unique biochemical reactions

(Brittenham, 1994). Hence, iron fills many essential roles in plant growth and development, including

chlorophyll synthesis, thylakoid synthesis and chloroplast development (Miller et al., 1995). Iron is

required at several steps in the biosynthetic pathways. Zinc (Zn ) is an essential element for plant that

act as a metal component of various enzymes or as a functional structural or regulatory cofactor and for

protein synthesis, photosynthesis, the synthesis of auxin, cell division, the maintance of membrane

structure and function, and sexual fertilization (Marschner, 1995).

Moreover, little is known about salinity interaction with iron and zinc deprivation, the present study

aimed to decrease salinity stress is a main issue in this study to ensure increasing production. Also, the

present study describes the composition of the essential oils of sweet basil cultivated in Egypt.

MATERIALS AND METHODS

A field experiment was conducted at the farm station of the National Research Centre, at Shalakan,

Kalubia Governorate, Egypt during the two successive seasons of 2006 and 2007. The physical and

chemical properties of the soil sample were determined according to Jackson, 1973, Table 1.

Seeds of Ocimum basilicum L. were provided by the Medicinal and Aromatic Plants Division,

Horticultural Research Institute, Agricultural Research Center, Ministry of Agriculture, Egypt. The

seeds of basil were sown in the nursery on 1 st March of both seasons. After 45 days from seed sowing,

uniform seedlings were transplanted into plots 3x3.5m. on rows, with 60cm a part and 20 cm between

the seedlings. The experimental layout was split plot design in a complete randomized block design

with three replications. The main plots were devoted to the two levels of soil salinity (normal soil and

saline soil), while the sub ones were assigned for three sources of second factor (Fe, Zn, and a mixture

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Ozean Journal of Applied Sciences 3(1), 2010

of Fe + Zn). The experimental treatments consisted of 8 treatments, which represented all combinations

between soil salinity conditions (normal soil, S1 = 0.73 ppm and saline soil, S2 = 4.95 ppm) and foliar

application treatments (F0= control, F1= 250 ppm iron as a foliar spray of the chelated Fe-EDTA (Fe

8.5%), F2= 250 ppm Zn-EDTA (Zn16%) and F3= 250 ppm mixture of zinc and iron) were sprayed at

interval times of 45, 60, 120 and 150 days from transplanting.

Growth characters and chemical constituent's determinations were carried out at the first and second

cuts after 90 and 180 days from transplanting, respectively before flowering. The following data were

recorded. Plant height (cm), number of branches / plant, fresh and dry weights of herb (g / plant or ton /

feddan). The essential oil percentage was determined in the air dried herb using a modified Clevenger

apparatus according to Guenther (1961). Essential oil percentage was determined and expressed as (%),

while essential oil yield per plant was expressed as ml plant -1 . The essential oils of each treatment at

the first and second cuts were collected and dehydrated over anhydrous sodium sulphate and kept in a

refrigerator until GLC analysis. The GLC analysis of the essential oil samples was carried out in the

second season using gas chromatography instrument stands at the Central Laboratory of the National

Research Center with the following specifications. Instrument: Hewlett Packard 6890 series, Column:

HP (Carbwax 20M) 25m length × 0.32mm I.D, Film thickness: 0.3Mm, Sample size: 1µl, oven

temperature: 60-190 °C, Program: 60 °C/2min, 8 °C/min, 190 °C/25min. Injection port temperature:

240 °C, Detector temperature (FID): 280 °C, Carrier gas: nitrogen, Flow rate: N2 30 ml/min; H2 30

ml/min; air 300 ml/min. Main compounds of the essential oils were identified by matching their

retention times with those of the authentic samples injected under the same conditions. The relative

percentage of each compound was calculated from the area of the peak corresponding to each

compound.

Data were exposed to the proper statistical analysis of variance according to LeClerg et al. (1966) as

well as Snedecor and Cochran (1990). The means represented in the study following by the same

alphabetical letters were not significantly different at the probability level of 0.05, Least Significant

differences (L.S.D) were used compare between means according to Waller and Duncan (1969) at

probability 5%.

A. Growth characters and yield

Effect of soil salinity

RESULTS AND DISCUSSIONS

Tables (2-5) show the effect of soil salinity on plant height, number of branches, fresh and dry weights

of herb (g/plant or ton/fed.) of the basil plants. These growth characters decreased significantly with

soil salinity conditions in both cuts during two seasons. The inhibitory effect of salinity was also found

by (Abd El-Hady, 2007; Abd El-Wahab, 2006; Baghalian et al., 2008; Belaqziz et al., 2009; Ozturk et

al., 2004; Razmjoo et al., 2008; Shalan et al., 2006; Turhan and Eris, 2007). Saline conditions reduce

the ability of plants to absorb water causing rapid reductions in growth rate, and induce many

metabolic changes (Epstein, 1980). Also, salt stress with osmotic, nutritional and toxic effects prevents

growth in many plant species (Cheeseman, 1988; Hasegawa et al., 1986). Therefore, the reduction in

growth was explained by lower osmotic potential in the soil, which leads to decreased water uptake,

reduced transpiration, and closure of stomata, which is associated with the reduced growth (Ben-Asher

et al., 2006; Levitt, 1980). In general, the mechanisms of salinity effect on plant growth were reported

by Meiri and Shalhavet (1973) who attributed the effect of salinity to the following points: (a) the

distribution of salts within the plant cells may result in turgor reduction and growth retardations. Also,

salinity affects root and stomatal resistance to water flow, (b) the balance between root and shoot

hormones changes considerably under saline conditions, (c) salinity changes the structure of the

chloroplasts and mitochondria and such changes may interfere with normal metabolism and growth, (d)

salinity increases respiration and reduces photosynthesis products available for growth.

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Effect of micronutrients

Ozean Journal of Applied Sciences 3(1), 2010

Basil plants sprayed with zinc and/or iron under normal and saline soils conditions were superior if

compared without sprayed plants (tables, 2-5). Results also indicated that treated plants with iron were

much superior in plant height and number of branches compared with other treatments. However,

plants treated by zinc were produced fresh and dry weights of herb (g/plant or ton/fed.) greater than

those other treatments. While, plants treated with mixture of zinc and iron gave the heaviest dry weight

in the first cut, but treated plants with zinc or iron were produced dry weights of herb greater than those

of other treatments in the second cut during first and second seasons, respectively. The stimulatory

effect of zinc and/or iron were recorded by (Aziz and El- Sherbeny, 2004; Pande et al., 2007; Said-Al

Ahl, 2005; Said-Al Ahl and Omer, 2009).

The stimulation effects of applying zinc and iron on vegetative growth may be attributed to the well

known functions of zinc and iron in plant life, as described in the Introduction. Moreover, zinc is a

component of carbonic anhydrase, as well as several dehydrogenases and auxin production which in

turn enhanced the elongation processes, besides the function of zinc in CO2 assimilation. Consequently,

the fresh and dry weights of herb could be increased (Marschner, 1995). However, iron deficiency

inhibited leaf growth, cell number, size and cell division, as well as chlorophyll, protein, starch and

sugar content. Thus, the fresh and dry weights of herb could be decreased. Iron is necessary for the

biosynthesis of chlorophyll and cytochrome, besides the function of iron in the metabolism of

chloroplast RNA, leading to increase in the biosyntheses materials (produced and accumulated),

consequently, the growth was enhanced (Marschner, 1995).

Effect of interaction

The interaction between normal soil and saline soil conditions with zinc and/or iron application

resulted in a significant increment of plant height and number of branches in the two cuts for both

seasons (Tables, 2-5). Fresh weight of herb (g/plant or ton/fed.) was significantly increased in the

second cut and non significant in the first cut in both seasons, but dry weight of herb (g/plant or

ton/fed.) increased significantly in both cuts, except, this increment was insignificant in the second cut

at first season. The maximum plant height and number of branches mean values were recorded from

the combination of iron spraying and non soil salinity in all cuttings of both seasons. The highest fresh

and dry weights of herb (g/plant or ton/fed.) resulted from zinc spraying and non soil salinity, or

mixture (zinc and iron) spraying and non soil salinity, respectively in all cuttings of both seasons.

While, the minimum growth characters values were resulted from the soil salinity condition without

any treatment.

B. Essential oil production

Effect of soil salinity

Tables (4, 5) explain that soil salinity conditions significant increased essential oil %. The increase in

essential oil % due to salinity conditions was found by (Al-Amier and Craker, 2007; Baghalian et al.,

2008; Baher et al., 2002; Hendawy and Khalid, 2005; Prasad et al., 2006; Tabatabale and Zari, 2007).

In contrast, essential oil yield was significant decreased at the first and second cuts of both seasons.

The results were similar in both the two seasons. Similar results were found by (Abd El-Wahab, 2006;

Baghalian et al., 2008; Ozturk et al., 2004; Razmjoo et al., 2008). The reduction of essential oil yield

by salinity due to a decrease in growth characters.

The stimulation of essential oil production under salinity could be due to a higher oil gland density and

an increase in the absolute number of glands produced prior to leaf emergence (Charles et al., 1990).

Salt stress may also affect the essential oil accumulation indirectly through its effects on either net

assimilation or the partitioning of assimilate among growth and differentiation processes (Charles et

al., 1990).

Penka (1978) showed that the formation and accumulation of essential oil in plants was explained as

due to the action of environmental factors. It might be claimed that the formation and accumulation of

essential oil was directly dependent on perfect growth and development of the plants producing oils.

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Ozean Journal of Applied Sciences 3(1), 2010

The decrease in oil production might be due to the decrease in plant anabolism. Morales et al. (1993)

suggested that, an increase in oil content in some of the salt stressed plants might be attributed to

decline the primary metabolites due to the effects of salinity, causing intermediary products to become

available for secondary metabolites synthesis.

Effect of micronutrients

Data in Tables (4, 5) indicate that the essential oil (% or yield) of basil sprayed with zinc + iron was

higher than the other treatments, followed by plants treated with zinc, and then plants treated with iron,

whereas plants untreated (control) was lower in this respect in the two cuts during the two seasons. The

increase in essential oil due to zinc and /or iron was also found by (El-Sawi and Mohamed, 2002;

Maurya, 1990; Pande et al., 2007; Said-Al Ahl, 2005; Said-Al Ahl and Omer 2009; Subrahmanyam et

al., 1992). From previous studies, biosynthesis of secondary metabolites is not only controlled

genetically but it also is affected strongly by environmental influences (Naghdi Badi et al., 2004). In

line with the foregoing, environmental variables affect essential oil, Marschner (1995) found that iron

has important functions in plant metabolism, such as activating catalase enzymes associated with

superoxide dismutase, as well as in photorespiration and the glycolate pathway. Also, in iron-deficient

plants, the activities of some enzymes are impaired and may often be responsible for gross changes in

metabolic processes. Moreover, zinc is an essential micronutrient that acts either as a metal component

of various enzymes or as a functional, structural, or regulatory cofactor associated with saccharide

metabolism, photosynthesis, and protein synthesis (Marschner, 1995). Carbon dioxide and glucose are

precursors of monoterpene biosynthesis. Saccarides are also a source of energy and reducing power for

terpenoid synthesis. As zinc is involved in photosynthesis and saccaride metabolism, and as CO2 and

glucose is the most likely sources of carbon utilized in terpene biosynthesis, the role of zinc in

influencing essential oil accumulation seems particularly important (Srivastava et al., 1997).

Effect of interaction

From data in Tables (4, 5), it can be concluded that the interaction treatments between foliar spray with

micronutrients (Zn, Fe and mixture of Zn + Fe) and soil salinity significantly increased essential oil %

and essential oil yield in both cuts during two seasons, except essential oil % at first cut was increased

insignificantly of both seasons if comparing with none and soil salinity conditions. The highest value of

essential oil % was obtained by spraying with zinc + iron under soil salinity conditions. Whereas,

plants sprayed with zinc + iron under none soil salinity gave the highest value of essential oil yield in

both cuts during two seasons.

C. Chemical composition of essential oils

Table (6) show the data belonging to qualitative and quantitative constituents of essential oils distilled

from the basil herb before flowering stage collected from the first and second cuts during the season of

2007. The essential oil composition of 8 treatments, along with the quantitative data is listed in Table 6.

Twenty-four compounds were identified. Comparison of the analytical data of the oils revealed marked

differences in qualitative and quantitative composition. Considering the main components, of the all

treatments were characterized by high contents of linalool (38.28-52.14%) and methylchavicol (20.34-

27.67%), and moderate amounts of 1,8-cineol (6.04-9.22%), germacrene D (2.32-4.38%), and very

variable amounts of cis-bisabolene (0.00-2.53%), geraniol (0.59-2.02%), nerol (0.89-1.78%), cadinol

(0.00-1.75%) and 1,4 terpineol (0.66-1.70%), and a lower amounts of α-thujene, β-pinene, α-pinene,

camphene, sabinene, myrcene, ocimene, limonene, selinene, nerolidole, cadinene, caryophyllene,

eugenol, camphor and α-terpinene considered as traces.

The results in table (6) show that iron treatment gave the highest content of (methylchavicol,

germacrene D, α-pinene and α-thujene); zinc treatment gave the highest content of (1, 8-cineol, βpinene,

camphor, nerolidole and camphene) as well as iron + zinc treatment gave the highest content of

(linalool, sabinene, nerol, eugenol, selinene and cadinole). However, control treatment gave the same

result of (limonene, α-terpinene, 1,4 terpineol, caryophyllene, cis-bisabolene, cadinene and ocimene)

under the soil salinity conditions.

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Ozean Journal of Applied Sciences 3(1), 2010

According to major compounds it was obviously cleared that soil salinity treatment decreased both of

linalool and methylchavicol compared to that of control Also, linalool was decreased with spraying

treatments comparing to that of control, while there was an increase in methylchavicol by using zinc

and mixture of zinc + iron whereas iron treatment had the lowest in this regard comparing to that of

control in normal soil. However, under saline soil condition, the results indicate that linalool was

increased with spraying treatments comparing to that of control and mixture of iron + zinc followed by

zinc and then iron gave the highest content of linalool. Whereas, methyl chavicol was increased with

spraying of iron and zinc, but decreased by iron + zinc comparing to that of control and iron followed

by zinc and then control treatment gave the highest content of methylchavicol. The highest content of

linalool was obtained by using zinc + iron under saline soil compared to the other interaction ones and

the lowest value in this respect obtained in normal soil from the same treatment. However, zinc

treatment gave the highest content of methylchavicol in normal soil but, under soil salinity, zinc+iron

treatment gave the lowest value in this respect in all cases.

The present study was in accordance by EL-Keltawi and Croteau (1987) on spearmint and marjoram

who indicated that irrigation of both plants with saline solution consisting of calcium chloride and

sodium chloride reduced essential oil. They added that under salinity in spearmint the content of

limonene was increased and carvone was concomitantly decreased relative to controls irrigated with

water only. In case of marjoram, salt stress led to increase the content of sabinene which was

accompanied by a decrease in the content of sabinene hydrate. Hendawy and Khalid (2005) on salvia

officinalis reprted that treatment of 2500 ppm soil salinity increased α–thujone, camphor and 1,8-

cineol but it decreased the component of β–thujone compared with the control treatment.

Said-Al Ahl and Omer (2009) indicated that linalool was increased in the herb and seeds of coriander,

but dodecenal of herb was decreased with treatment of zinc and mixture of zinc + iron compared to

control. Also, Said-Al Ahl et al. (2010) indicated that soil salinity treatments at 1500 and 4500 ppm

levels increased the content of linalool and on the contrary there was decreased in eugenol content by

using 1500 and 4500 ppm of soil salinity in the Ocimum basilicum var. purpurascens.

The essential oil of basil in this study belonging to linalool and methylchavicol chemotype,

characterized by the simultaneous presence of linalool and methylchavicol, can be ascribed to those

plants in which essential oil constituents are produced by two different biosynthetic pathways. In fact,

methylchavicol has a common biosynthesis originating from the precursor (L-phenylalanine and

cinnamic acid), whereas linalool follows another biogenetic pathway from mevalonic acid via geranyl

pyrophosphate (Nikanen, 1989). It is known that climatic conditions and water available in the soil can

change the vegetal secondary metabolism and, consequently ,alter the composition of essential oils,

throughout the seasons of the year. Chemical variations in essential oils were associated with seasons

for Ocimum selloi (Moraes et al., 2002) and with time of day for Ocimum gratissimum (Vasconcelos

Silva et al., 1999(.

.

Table 1. The physical and chemical properties of the experimental soil.

Physical and chemical properties Normal soil Saline soil

Sand (%) 46.8 49.6

Silt (%) 28.2 26

Clay (%) 25.0 24.4

Soil texture Sandy loam Sandy loam

pH 8.12 8.45

E.C (m. mohs/cm) 0.73 4.95

Organic matter (%) 0.95 0.40

N (mg kg -1 ) 0.09 0.05

P (mg kg -1 ) 20.0 0.45

K (mg kg -1 ) 208.0 2.04

Zn (ppm) 1.2 0.65

Iron (ppm) 20.0 1.32

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Ozean Journal of Applied Sciences 3(1), 2010

Table 2. Effect of soil salinity, foliar spray with micronutruients and their interactions on plant height, branches number and herb fresh weight of Ocimum

basilicumL. plants at first cut in 2006 and 2007 seasons.

Treatments

Plant height (cm) Branches number plant -1 Fresh weight g plant -1

Season 1 Season 2 Season 1 Season 2 Season 1 Season 2

S1 55.43 a ± 7.831 55.61 a ± 7.972 11.91 a ± 2.188 11.24 a ± 1.898 110.44 a ± 9.481 110.24 a ± 10.077

S2 36.27 b ± 3.939 37.11 b ± 5.451 7.18 b ± 1.395 7.68 b ± 1.589 54.43 b ± 6.849 53.25 b ± 5.940

LSD at � 0.05 5.1220 0.6758 2.2470 1.0230 6.0970 7.8010

F0 38.24 d ± 6.538 37.45 d ± 7.113 7.68 c ± 2.891 7.23 c ± 2.285 71.25 b ± 28.708 69.83 b ± 28.388

F1 52.69 a ± 12.539 53.69 a ± 10.499 11.10 a ± 3.705 11.17 a ± 2.792 85.27 a ± 29.959 84.00 a ± 30.361

F2 44.15 c ± 11.738 44.04 c ± 11.247 9.29 b ± 1.385 9.46 b ± 0.499 88.43 a ± 33.338 87.52 a ± 33.179

F3 48.32 b ± 11.649 50.25 b ± 12.007 10.10 ab ± 3.188 9.99 b ± 2.357 84.80 a ± 31.976 85.63 a ± 33.696

LSD at � 0.05 1.8820 2.0190 1.0550 0.5440 6.9310 4.5900

S1xF0 44.07 d ± 2.001 43.87 c ± 0.998 10.15 c ± 1.550 9.29 cd ± 0.543 97.17 ± 4.908 95.50 ± 5.500

S1xF1 64.09 a ± 0.460 63.17 a ± 1.607 14.40 a ± 1.058 13.70 a ± 0.265 112.33 ± 4.646 111.50 ± 5.074

S1xP2 54.73 c ± 2.194 54.22 b ± 1.338 10.18 c ± 1.154 9.89 c ± 0.271 118.60 ± 5.769 117.63 ± 5.119

S1xF3 58.83 b ± 2.021 61.17 a ± 1.607 12.90 b ± 1.258 12.07 b ± 0.902 113.67 ± 5.508 116.33 ± 3.215

S2x F0 32.42 g ± 1.040 31.03 e ± 1.380 5.20 e ± 0.346 5.17 f ± 0.153 45.33 ± 4.619 44.17 ± 2.843

S2xF1 41.29 e ± 1.728 44.20 c ± 1.814 7.80 d ± 0.721 8.63 de ± 0.404 58.20 ± 4.952 56.50 ± 3.148

S2xF2 33.56 g ± 1.822 33.87 e ± 1.963 8.40 d ± 1.039 9.04 d ± 0.063 58.27 ± 3.900 57.41 ± 2.342

S2 xF3 37.80 f ± 1.836 39.33 d ± 0.577 7.30 d ± 0.520 7.90 e ± 0.173 55.93 ± 5.100 54.93 ± 0.902

LSD at � 0.05 2.6620 2.8550 1.4920 0.7693 N.S N.S

Means with different letters within each column are significant at 0.05 level and means in the same column with the same letters are not significant. Mean

±Sd (standard deviation)

Since: S = Soil salinity, i. e. S1 = 0.73 dsm -1 , S2 =4.95 dsm -1 ; F = Foliar spray with micronutrients, i. e. F0 = control, F1 = iron 250ppm, F2 = zinc 250ppm,

F3= mixture of iron + zinc

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Table 3. Effect of soil salinity, foliar spray with micronutruients and their interactions on plant height, branches number and herb fresh weight of Ocimum

basilicum L. plants in at second cut in 2006 2007 seasons.

Treatments

Plant height (cm) Branches number plant -1 Fresh weight g plant -1

Season 1 Season 2 Season 1 Season 2 Season 1 Season 2

S1 70.53 a ± 7.733 69.46 a ± 7.137 15.41 a ± 1.874 14.79 a ± 2.192 138.78 a ± 15.292 133.63 a ± 12.583

S2 51.08 b ± 5.595 51.75 b ± 5.683 11.03 b ± 2.116 11.17 b ± 2.248 67.75 b ± 9.697 71.65 b ± 11.697

LSD at � 0.05 3.3340 1.9350 1.3940 2.2600 5.3080 2.7990

F0 53.17 c ± 7.047 51.70 d ± 7.200 10.63 c ± 2.815 10.38 b ± 2.681 84.81 c ± 35.643 84.58 d ± 32.444

F1 69.32 a ± 10.901 68.02 a ± 8.634 14.44 a ± 3.247 14.18 a ± 2.717 106.50 b ± 35.681 107.30 b ± 30.040

F2 59.01 b ± 12.088 60.36 c ± 10.843 13.95 ab ± 0.580 13.48 a ± 0.949 116.50 a ± 45.873 114.67 a ± 34.373

F3 61.70 b ± 13.336 62.35 b ± 12.282 13.84 b ± 3.299 13.88 a ± 3.279 105.25 b ± 38.621 104.00 c ± 39.100

LSD at � 0.05 2.9820 1.2510 0.5352 0.9621 1.9870 2.6340

S1xF0 59.47 c ± 1.295 58.23 e ± 0.979 13.20 c ± 0.200 12.70 bc ± 1.082 117.29 c ± 2.350 114.17 d ± 1.443

S1xF1 79.01 a ± 2.968 75.87 a ± 0.594 17.39 a ± 0.344 16.50 a ± 1.323 139.00 b ± 1.000 134.67 c ± 2.517

S1xP2 69.89 b ± 1.723 70.22 c ± 1.235 14.23 b ± 0.521 13.09 bc ± 1.299 158.33 a ± 2.887 146.00 a ± 2.000

S1xF3 73.73 b ± 2.802 73.53 b ± 0.924 16.81 a ± 0.812 16.87 a ± 0.231 140.50 b ± 0.500 139.67 b ± 2.082

S2x F0 46.87 d ± 1.848 45.17 g ± 0.764 8.07 e ± 0.115 8.05 e ± 0.777 52.33 f ± 2.517 55.00 g ± 2.000

S2xF1 59.63 c ± 2.570 60.17 d ± 1.041 11.50 d ± 0.500 11.87 cd ± 0.777 74.00 d ± 3.606 79.93 e ± 1.675

S2xF2 48.13 d ± 2.721 50.50 f ± 0.866 13.67 bc ± 0.577 13.87 b ± 0.325 74.67 d ± 1.528 83.33 e ± 2.082

S2 xF3 49.67 d ± 1.528 51.17 f ± 1.041 10.87 d ± 0.231 10.90 d ± 0.361 70.00 e ± 1.000 68.33 f ± 1.155

LSD at � 0.05 4.2170 1.7690 0.7569 1.3610 2.8090 3.7260

Means with different letters within each column are significant at 0.05 level and means in the same column with the same letters are not significant. Mean ±Sd

(standard deviation)

Since: S = Soil salinity, i. e. S1 = 0.73 dsm -1 , S2 =4.95 dsm -1 ; F = Foliar spray with micronutrients, i. e. F0 = control, F1 = iron 250ppm, F2 = zinc 250ppm,

F3= mixture of iron + zinc

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Table 4. Effect of soil salinity, foliar spray with micronutruients and their interactions on plant height, branches number and herb fresh weight of Ocimum

basilicum L. plants at first cut in 2006 and 2007 seasons.

Treatments

Dry weight g plant -1 Essential oil % Essential oil yield plant -1

Season 1 Season 2 Season 1 Season 2 Season 1 Season 2

S1 30.16 a ± 5.739 26.49 a ± 3.998 0.70 b ± 0.089 0.69 b ± 0.083 0.21 a ± 0.064 0.19 a ± 0.046

S2 14.71 b ± 2.475 15.02 b ± 2.636 0.76 a ± 0.088 0.76 a ± 0.096 0.11 b ± 0.028 0.12 b ± 0.032

LSD at � 0.05 2.0730 1.1370 0.0095 0.0123 0.0145 0.0034

F0 16.63 d ± 6.445 16.30 c ± 6.123 0.60 d ± 0.043 0.59 c ± 0.033 0.10 d ± 0.033 0.10 d ± 0.033

F1 22.02 c ± 6.580 19.90 b ± 4.769 0.72 c ± 0.039 0.74 b ± 0.037 0.16 c ± 0.042 0.15 c ± 0.034

F2 24.67 b ± 9.694 22.85 a ± 6.791 0.76 b ± 0.048 0.75 b ± 0.064 0.18 b ± 0.062 0.17 b ± 0.039

F3 26.42 a ± 11.314 23.97 a ± 7.731 0.83 a ± 0.037 0.82 a ± 0.041 0.21 a ± 0.085 0.19 a ± 0.054

LSD at � 0.05 1.1730 1.2150 0.0325 0.0398 0.0080 0.0174

S1xF0 22.47 d ± 0.896 21.83 d ± 1.258 0.57 ± 0.025 0.57 ± 0.027 0.13 de ± 0.003 0.12 de ± 0.013

S1xF1 27.97 c ± 1.002 24.17 c ± 1.443 0.70 ± 0.040 0.72 ± 0.031 0.20 c ± 0.005 0.18 c ± 0.018

S1xP2 33.50 b ± 0.500 28.97 b ± 1.704 0.72 ± 0.006 0.70 ± 0.000 0.24 b ± 0.006 0.20 b ± 0.012

S1xF3 36.70 a ± 1.468 31.00 a ± 1.000 0.80 ± 0.021 0.78 ± 0.017 0.29 a ± 0.014 0.24 a ± 0.009

S2x F0 10.80 f ± 0.985 10.77 f ± 0.580 0.63 ± 0.025 0.62 ± 0.021 0.07 f ± 0.007 0.07 f ± 0.004

S2xF1 16.07 e ± 1.007 15.63 e ± 0.404 0.75 ± 0.025 0.75 ± 0.044 0.12 e ± 0.006 0.12 e ± 0.004

S2xF2 15.83 e ± 0.764 16.73 e ± 0.404 0.80 ± 0.006 0.81 ± 0.042 0.13 de ± 0.006 0.13 de ± 0.010

S2 xF3 16.13 e ± 0.709 16.93 e ± 0.058 0.85 ± 0.025 0.85 ± 0.017 0.14 d ± 0.002 0.14 d ± 0.004

LSD at � 0.05 1.6580 1.7180 1.4920 0.7693 N.S N.S

Means with different letters within each column are significant at 0.05 level and means in the same column with the same letters are not significant. Mean ±Sd

(standard deviation)

Since: S = Soil salinity, i. e. S1 = 0.73 dsm -1 , S2 =4.95 dsm -1 ; F = Foliar spray with micronutrients, i. e. F0 = control, F1 = iron 250ppm, F2 = zinc 250ppm,

F3= mixture of iron + zinc

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Table 5. Effect of soil salinity, foliar spray with micronutruients and their interactions on herb dry weight, essential oil % and essential oil yield of Ocimum

basilicum L. plants at second cut in 2006 and 2007 seasons.

Treatments

Dry weight g plant -1 Essential oil % Essential oil yield plant -1

Season 1 Season 2 Season 1 Season 2 Season 1 Season 2

S1 40.49 a ± 3.288 39.68 a ± 3.623 0.66 b ± 0.083 0.66 b ± 0.075 0.27 a ± 0.051 0.26 a ± 0.050

S2 21.40 b ± 2.424 21.39 b ± 2.220 0.73 a ± 0.083 0.73 a ± 0.080 0.16 b ± 0.030 0.16 b ± 0.030

LSD at � 0.05 1.6190 3.1310 0.0393 0.0156 0.0231 0.0271

F0 26.75 b ± 9.464 25.94 b ± 8.688 0.58 c ± 0.044 0.58 c ± 0.041 0.15 c ± 0.048 0.15 c ± 0.041

F1 32.58 a ± 10.394 32.23 a ± 10.213 0.71 b ± 0.026 0.70 b ± 0.025 0.23 b ± 0.069 0.22 b ± 0.068

F2 32.67 a ± 10.671 32.08 a ± 10.420 0.72 b ± 0.069 0.72 b ± 0.082 0.23 ab ± 0.055 0.22 b ± 0.050

F3 31.78 a ± 11.570 31.87 a ± 10.905 0.78 a ± 0.038 0.77 a ± 0.039 0.25 a ± 0.080 0.24 a ± 0.073

LSD at � 0.05 1.7420 0.8172 0.0303 0.0281 0.0164 0.0113

S1xF0 35.33 ± 1.528 33.83 b ± 0.764 0.55 g ± 0.045 0.55 e ± 0.027 0.19 c ± 0.021 0.19 d ± 0.006

S1xF1 42.00 ± 1.000 41.50 a ± 1.500 0.69 de ± 0.030 0.69 c ± 0.023 0.29 b ± 0.018 0.29 b ± 0.019

S1xP2 42.33 ± 0.577 41.57 a ± 0.751 0.66 e ± 0.010 0.65 d ± 0.021 0.28 b ± 0.008 0.27 c ± 0.011

S1xF3 42.30 ± 1.572 41.80 a ± 0.700 0.75 bc ± 0.031 0.74 b ± 0.017 0.32 a ± 0.016 0.31 a ± 0.012

S2x F0 18.17 ± 0.764 18.04 d ± 1.066 0.61 f ± 0.006 0.62 d ± 0.015 0.11 e ± 0.005 0.11 f ± 0.007

S2xF1 23.17 ± 1.756 22.97 c ± 0.950 0.72 cd ± 0.010 0.71 bc ± 0.023 0.17 d ± 0.012 0.16 e ± 0.009

S2xF2 23.00 ± 2.000 22.60 c ± 1.039 0.78 ab ± 0.015 0.79 a ± 0.012 0.18 cd ± 0.015 0.18 de ± 0.010

S2 xF3 21.27 ± 0.643 21.93 c ± 0.902 0.81 a ± 0.006 0.81 a ± 0.012 0.17 cd ± 0.004 0.18 de ± 0.010

LSD at � 0.05 N.S 1.1560 0.0428 0.0398 0.0232 0.0159

Means with different letters within each column are significant at 0.05 level and means in the same column with the same letters are not significant. Mean ±Sd

(standard deviation)

Since: S = Soil salinity, i. e. S1 = 0.73 dsm -1 , S2 = 4.95 dsm -1 ; F = Foliar spray with micronutrients, i. e. F0 = control, F1 = iron 250ppm, F2 = zinc 250ppm,

F3= mixture of iron + zinc

106


Ozean Journal of Applied Sciences 3(1), 2010

Table 6. Effect of soil salinity and foliar spray with micronutruients on essential oil constituents of Ocimum basilicum L. plants

in 2007 seasons.

Soil salinity

Compounds Saline soil (4.95 dsm )

-1

Normal soil (0.73 dsm )

-1

F0

F1

F2

F3

F0

F1

F2

α–thujene--

--

--

--

--

0.02

0.01

α-pinene

0.42

0.19

0.32

0.40

0.29

0.40

0.01

camphene--

--

--

--

--

0.02

0.46

sabinene--

--

0.08

0.07

--

0.01

0.35

β-pinene

0.86

0.94

0.93

1.21

0.75

1.18

1.69

myrcene--

--

--

--

0.45

0.84

1.33

limonene

0.37

0.70

0.76

0.97

0.64

0.10

0.11

1 ,8-cineol 7.79

9.40

6.36

7.99

6.63

8.39

9.22

α - terpinene 1.03

0.93

0.91

0.93

0.35

0.10

0.32

ocimene--

0.42

0.36

0.36

0.48

0.12

0.41

Linalool

39.85

32.42

27.68

25.68

38.28

46.54

49.33

camphor--

--

0.27

0.06

0.02

0.22

0.29

1,4-terpineol 1.05

1.34

0.78

0.73

1.70

0.66

0.89

methylchavicol 35.64

30.84

44.01

38.52

21.48

27.67

23.66

nerol

1.00

1.89

1.29

1.11

0.89

1.22

1.09

geroniol

0.75

1.23

1.13

1.18

2.02

0.85

0.59

eugenol--

--

--

--

--

--

--

caryophyllene-- 0.44

0.24

0.37

0.18

0.12

0.01

germacrene D 2.19

3.89

1.80

2.88

2.32

4.38

4.08

cadinene--

0.09

--

0.10

0.11

--

--

cis-bisabolene 1.71

1.98

1.74

2.04

2.53

--

--

nerolidole

0.08

0.41

0.60

0.25

0.44

0.43

0.45

selinene

0.42

0.60

0.05

0.86

0.01

0.09

0.74

t-cadinol

3.25

3.91

4.02

4.76

--

1.38

1.61

Identified

compounds

96.31

91.62

93.33

90.47

91.42

99.26

93.13

F = Foliar spray with micronutrients, i. e. F0 = control, F1 = iron 250ppm, F2 = zinc 250ppm, F3 = mixture of iron + zinc

107

F3

--

--

--

0.47

0.30

0.05

0.01

6.04

0.31

0.40

52.14

0.14

0.78

20.34

1.78

1.07

0.42

--

3.63

--

--

0.30

0.91

1.75

91.35


Ozean Journal of Applied Sciences 3(1), 2010

CONCLUSIONS

It may be concluded that Ocimum basilicum (linalool and methylchavicol chemo type) is tolerant to

soil salinity, thus we may recommend its cultivation in slain soil of Egypt. Foliar spraying with iron

and /or zinc under these conditions could be much more efficient than not application of nutrients. So,

we recommended that, foliar application of iron and /or zinc to raise the salt stress tolerance of sweet

basil (Ocimum basilicum L.).

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Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Growth and yield of Foeniculum vulgare var.azoricum as influenced by some

vitamins and amino acids

S.F. Hendawy and Azza A.Ezz El-Din*

Cultivation and Production of Medicinal and Aromatic Plants Dept.

National Research Centre, Dokki, Cairo -12622, Egypt

E-mail address for correspondence :azzaamin2001@hotmail.com

___________________________________________________________________________________

Abstract :This investigation was carried out in Saft El-Laban farm, Giza during two successive

seasons of 2006/2007 and 2007/2008 to study the effect of foliar application of ascorbic acid and

thiamine in a rate of 0, 25 , 50 and 75 mgL -1 . for each as well as amino acids i.e aspartic and phenyl

alanin in a rate of 0, 100, 200 and 300 ppm for each on growth, yield and chemical composition of

fennel plants. The obtained results could be summarized as follows: ascorbic acid at 75 mgL -1 .

recorded the best value of plant height, number of branches, number of flower heads and seed weight

per plant. No significant difference was shown between aspartic acid and ascorbic acid. Phenyl alanin

at 300 ppm resulted the highest essential oil percent (2.78%) compared with control (2.00%).

Key words: Foeniculum vulgare, ascorbic acid, aspartic, phenylalanine, thiamine, essential oil

__________________________________________________________________________________

INTRODUCTION

Foeniculum vulgare (Fennel) belonging to the family Apiaceae is a perennial herb native to the

Mediterranean Region. It is widely cultivated and extensively used as a culinary spice. The plant is

aromatic and is used as a pot herb. The leaves have diuretic properties and the roots are regarded as

purgatives. Dried fruits of fennel posses a pleasant aromatic taste and used for flavouring soups, meat

dishes and sauces. The fruits are considered to be usefull in treatment of diseases of the chest, spleen

and kidney (Singh and Kale 2008).

The anti-inflammatory, analgesic and antioxidant activities of the fruits of fennel have been reported by

(Choi and Hwang 2004).

The oil of fennel regulates the peristaltic functions of the gastrointestinal tract and relevies the spasms

of intestines (Fathy et al 2002).

Amino acids are fundamental ingredients in the process of protein synthesis. Glycine and Glutamic

acids play an important role in formation of vegetative tissue and chlorophyll. They also have a

chelating effect on micronutrients through making their absorption and transportation easier for the

plant. They are precursors or activators of phytohormones and growth substances. L. Methionine is a

precursor of ethylene and growth factors such as espermine and espermidine (Singh 1999).

Gamal El-Din et al (1997) found that foliar application of ornithine and phenylalanine 50, 100 mgL -1 .

on Cymbopgon citrates led to significantly increase in vegetative growth, number of leaves and tillers

as well as fresh and dry weight of herb. El-Sherbeny and Hassan (1987) reported that phenylalanine

or tryptophan at 200 or 250 mgL -1 significantly increased growth parameters and alkaloid content of

datura plants.

Moursy et al (1988) indicated that phenylalanine or ornithine increased the fresh and dry weight of

callus explants of Datura stramonium L. Refaat and Naguib (1998) found that spraying peppermint

plant with alpha-alanine at 25 and 50 ppm increased fresh and dry weight of the plant and essential oil

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Ozean Journal of Applied Sciences 3(1), 2010

content. Harridy (1986) mentioned that the higher alkaloid percentage and yield of Catharanthus

roseus resulted from foliar application of some amino acids. Similar trend was observed by Awad

(1986), studying methionen on Hyoscyamus muticus. Talaat and Youssef (2002) found a pronounced

increase in vegetative growth of basil plant as a result of lysine and ornithine treatments.

Little information are available about the role of vitamins in regulating the biosynthesis of essential oil

in plants. Robinson (1973) reported that vitamin B complex and vitamin C act as co-enzmes in the

enzymatic reactions by which carbohydrates, fats and proteins are metabolized and involved in

photosynthesis and respiration. Taraf et al (1999) reported that foliar application of nicotine amide to

lemongrass plants significantly promoted vegetative growth as well as essential oil percent, oil yield

per plant, total carbohydrates and crude proteins.

Ascorbic acid (vitamin C) is known as a growth regulating factor which influences many biological

processes. Price (1966) reported that ascorbic acid (vit.C) increases nucleic acid content, especially

RNA. It also influenced the synthesis of enzymes, nucleic acids and protein, in addition it acts as coenzyme

in metabolic changes. Abd El-Halim (1995) reported that foliar application of ascorbic acid on

tomato plants significantly increased growth parameters (stem length, number of branches, leaves,

flowers and fruit set as well as dry weight of shoot per plant) in comparison with control plants.

Thiamine (Vitamin B1) is a necessary ingredient for biosynthesis of the coenzyme thiamine

pyrophosphate, in this latter form it plays an important role in carbohydrate metabolism. It is an

essential nutrient for both plant and animal. In plants, it is synthesized in the leaves and is transported

to the roots where it controls growth. Thiamine is an important cofactor for the transketolation reaction

of the pentose phosphate for nucleotide synthesis and for the reduced NADP required for various

synthetic pathways. It acts as co-enzyme oxidative carboxylation of � -keto acids (e.g. � ketoglutarate,

pyruvate, the � -keto analogs of the branched-chain amino acids: leucine isoleucine and

valine) Kawasaki (1992). In this concern, Reda et al (1977) reported that thiamine treatment

significantly increased the total yield of chromones as well as khellin and visnagin yield (mg plant -1 ) in

the fruits of Ammi visnaga. Ascorbic acid seemed to retard the growth of Ammi Visnaga but the yield

of different chromones in the fruits under the effect of ascorbic acid (50 and 100 mg/1) was about three

folds that of the corresponding control.

The aim of this study is to investigate the effect of some vitamins and amino acids on growth, yield and

oil composition of fennel plants.

Field experiments:

MATERIALS AND METHODS

Field experiments were carried out at Saft El-Laban farm, Giza, Egypt during two successive growing

seasons (2007 and 2008) to study foliar application of some vitamins i.e ascorbic acid and thiamine and

amino acids i.e aspartic and phenylalanine on growth, yield and chemical composition of fennel plants.

Seeds of Foeniculum vulgare var. azoricum were obtained from Sekem Group Company, Egypt.

The mechanical and chemical analysis of the soil were carried out according to the method of

Chapman and Pratt (1978), which were presented in Table (1).

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Ozean Journal of Applied Sciences 3(1), 2010

Table (1): Physical and chemical analysis of the experimental soil.

Physical properties Chemical parameters

Soil type loamy

Course sand 4.9%

Fine sand 30.7%

Silt 27.5%

Clay 27.5%

Organic matter 2.1%

115

pH

Available N

Available P2O5

Available K2O

Fe

Mn

Zn

Cu

Na

Mg

7.8

13.8 mg/100g

0.482 mg/100g

3.01 mg/100g

1.1 ppm

0.53 ppm

21 ppm

21 ppm

29 ppm

2.4 ppm

Seeds were sown directly in soil on 12 th of October 2006, and on the 2 nd of October 2007. The

experimental unit area was 4 m 2 and the treatments were arranged in completely randomized block

design with three replicates for each treatment. Each plot contained 3 rows of 60 cm apart and the

distance between plants was 30 cm. Calcium super phosphate (15.5% P2O5), at 100 kg/ feddan,

ammonium sulphate (20.5%N) at 150 kg/ feddan and potassium sulphate (48% K2O) at 100kg/feddan

were applied. Phosphorus fertilizer was added at the time of soil preparation while nitrogen fertilizer

was added at two separated side dressings, the first one on 15 th. December and the second on 15 th.

February in both seasons.

The treatments were as follows:

Treat. 1: Control (Sprayed with water)

Treat.2: Sprayed with aspartic acid at 100 ppm.

Treat.3: Sprayed with aspartic acid at 200 ppm.

Treat.4: Sprayed with aspartic acid at 300 ppm.

Treat.5: Sprayed with Phenyl alanin at 100 ppm.

Treat.6: Sprayed with Phenyl alanin at 200 ppm..

Treat.7: Sprayed with Phenyl alanin at 300 ppm.

Treat.8: Sprayed with thiamine at 25 mg/L.

Treat.9: Sprayed with thiamine at 50 mg/L.

Treat.10:Sprayed with thiamine at 75 mg/L.

Treat.11:Sprayed with ascorbic acid at 25 mg/L.

Treat.12:Sprayed with ascorbic acid at 50 mg/L.

Treat.13:Sprayed with ascorbic acid at 75 mg/L.

The plants were sprayed with vitamins or amino acids twice, the first one on 15 th December and the

second on 15 th February, early in the morning, while the control plants were sprayed with distilled

water.

Plant height (cm), plant fresh weight or (aerial parts)g plant -1 plant dry weight (aerial parts), g plant-1

flowers head number, no of branches, no. of suckers and seed weight per plant were recorded through

the two growth seasons. Essential oil percentage was determined in the fruits.


Chemical analysis:

Ozean Journal of Applied Sciences 3(1), 2010

Samples of dried seeds were subjected to water distillation for determination of their essential oil

content using clevenger's apparatus Marotti and Piccaglia (1992).

Oil samples were subjected to Gas Chromatographic Analysis to identify their oil composition adopting

the following condition:

Apparatus: Thermo Quest Trace GC 2000 Series-Finnegan

Standard material: Piano paraffines SUPELCO product.

Column: 60m x 0.32 mm SPB TM -5

Detector: FID; Operating mode Splitless; Base temp. 300 o C

Mobile phase: Nitrogen 30ml/min

Oven Program: Initial temp. 40 o C, rate of increase 3 o C/minute; Final temp. 240 o C; Hold time 10

minutes.

The results of all the parameters were statistically analysed adopted the method of (Snedecor and

Cochran 1980).

RESULTS AND DISCUSSION

Table (2&3) showed the effect of foliar application of vitamins i.e, ascorbic acid (vitamin C) and

thiamine (vitamin B1) as well as amino acids i.e, aspartic acid and phenylalanine on growth and yield

of Foeniculum vulgare var. azoricum during 2007 and 2008. The data indicate that application of

aspartic acid increased plant height (cm) up to

116


Ozean Journal of Applied Sciences 3(1), 2010

Table(2): Effect of foliar application of ascorbic acid and thiamine and amino acids, aspartic and phenylalanine on growth, yield and chemical composition

Foeniculum vulgare var. azoricum plants; First season (2007).

Treatments

Plant height

(cm)

Aerial parts

fresh weight

g plant -1

Aerial parts

dry weight

g plant -1

117

Number of

flower heads

plant -1

Number of

branches

plant -1

Number of

suckers plant -1

Seed weight

g plant -1

Control 0ppm 128.0 650.0 98.48 30.0 8.0 2.0 38.0 2.00

Aspartic

Phenylalanine

Thiamine

Ascorbic acid

100 ppm

200 ppm

300 ppm

Mean

L.S.D. (5%)

100 ppm

200 ppm

300 ppm

Mean

L.S.D. (5%)

25 mg L -1

50 mg L -1

75 mg L -1

Mean

L.S.D. (5%)

25 mg L -1

50 mg L -1

75 mg L -1

Mean

L.S.D. (5%)

158.0

173.0

178.0

169.7

5.12

145.0

155.0

158.0

152.7

4.60

167.0

185.0

184.0.

178.7

5.90

170.0

194.0

185.0

183.0

6.33

710.0

745.0

768.0

741.0

28.16

705.0

715.0

734.0

718.0

24.16

714.0

735.0

772.0

740.3

27.00

766.0

780.0

790.0

778.7

23.51

107.58

112.88

116.36

112.3

2.94

110.16

111.72

114.69

112.2

N.S.

105.00

108.09

113.53

108.9

3.10

117.85

120.00

121.54

119.8

2.80

L.S.D. (5%) for foliar appli. 6.12 21.60 2.34 2.18 0.90 0.36 2.85 0.074

38.0

42.0

48.0

42.7

2.41

35.0

39.0

42.0

38.7

2.38

35.0

42.0

48.0

41.7

2.21

38.0

45.0

50.0

44.3

2.26

10.0

12.0

12.0

11.3

0.90

12.0

14.0

15.0

13.7

1.10

10.0

12.0

13.0

11.7

0.80

11.0

13.0

15.5

13.0

1.11

3.0

3.0

5.0

3.7

0.40

3.0

4.0

4.0

3.7

N.S.

4.0

5.0

5.0

4.7

0.35

4.0

6.0

6.0

5.3

0.38

45.0

49.0

52.0

48.7

2.34

40.0

45.0

48.0

44.3

2.47

48.0

55.0

58.0

53.7

2.35

52.0

58.0

61.0

57.0

2.71

Oil%

2.20

2.32

2.45

2.3

0.090

2.43

2.51

2.58

2.5

0.092

2.44

2.48

2.53

2.5

0.075

2.48

2.55

2.67

2.6

0.070


Ozean Journal of Applied Sciences 3(1), 2010

Table(3). Effect of foliar application of ascorbic acid and thiamine and amino acids, aspartic and phenylalanine on growth, yield and chemical composition

Foeniculum vulgare var. azoricum plants; Second season (2008).

Treatments

Plant height

(cm)

Aerial parts

fresh weight

g plant -1

Aerial parts

dry weight

g plant -1

118

Number of

flower heads

plant -1

Number of

branches

plant -1

Number of

suckers plant -1

Seed weight

g plant -1

Control 0ppm 132.0 675.0 102.27 30.0 9.0 3.0 37.0 2.00

Aspartic

Phenylalanine

Thiamin

Ascorbic acid

100 ppm

200 ppm

300 ppm

Mean

L.S.D. (5%)

100 ppm

200 ppm

300 ppm

Mean

L.S.D. (5%)

25 mg L -1

50 mg L -1

75 mg L -1

Mean

L.S.D. (5%)

25 mg L -1

50 mg L -1

75 mg L -1

Mean

L.S.D. (5%)

155.0

170.0

174.0

166.3

5.05

148.0

156.0

160.0

154.7

4.63

165.0

182.0

189.0

178.7

5.82

170.0

194.0

185.0

183.0

6.12

714.0

733.0

756.0

734.3

26.00

724.0

733.0

754.0

737.0

21.32

722.0

730.0

775.0

742.3

25.14

755.0

784.0

788.0

775.7

23.51

108.18

111.06

114.55

111.3

2.88

113.13

114.53

117.81

115.2

2.56

106.18

107.35

113.97

109.2

2.94

116.15

120.62

121.23

119.3

2.14

L.S.D. (5%) for foliar appli. 6.08 22.30 2.55 2.01 0.85 0.24 2.78 0.078

36.0

43.0

48.0

42.3

2.11

36.0

41.0

45.0

40.7

2.08

37.0

44.0

49.0

43.3

2.03

38.0

48.0

52.0

46.0

2.06

10.0

13.0

14.0

12.3

0.75

13.0

14.0

15.0

14.0

0.84

13.0

14.0

14.0

13.7

0.70

12.0

15.0

15.0

14.0

0.90

3.0

5.0

5.0

4.3

N.S.

4.0

5.0

6.0

5.0

N.S.

4.0

6.0

6.0

5.3

0.25

5.0

6.0

7.0

6.0

0.22

43.0

49.0

53.0

48.3

2.28

42.0

47.0

50.0

46.3

2.40

48.0

53.0

57.0

52.7

2.25

54.0

60.0

63.0

59.0

2.65

Oil%

2.20

2.35

2.40

2.3

0.095

2.41

2.48

2.78

2.5

0.084

2.48

2.51

2.58

2.5

0.086

2.47

2.53

2.64

2.5

0.071


Ozean Journal of Applied Sciences 3(1), 2010

300 ppm, but this increment had no significant effect comparing with 200 ppm. The maximum value of

this character was obtained by applying ascorbic acid at the rate of 50 mgL -1 . This was true during both

seasons except thiamine and ascorbic acid in the second one, whereas the three applied doses were

significant up to 75 mgL -1 . Wahba et al 2002 reported that aspartic acid as foliar spray (25, 50 and 75

ppm) increased the vegetative growth, flowering parameters and yield of courms of Anthoglyza

aethiopica.

Fresh and dry weight of aerial parts significantly increased by increasing all treatments up to 300 ppm

for asp. and phenyl. and 75 mg for vit. B1 and vit. C during the 1 st . season. In the 2 nd . season, the higher

dose applied from vitamins and amino acids, the maximum fresh and dry weight more obtained. The

highest weights were recorded with spraying ascorbic acid at 75 mgL -1 . Gamal El-Din and Abd El-

Wahed (2005) stated that all amino acids treatments (ornithine, proline and phenlyalanin) significantly

increased plant height, number of branches, number of flower heads and fresh and dry weights of aerial

part of chamomile plant.

Applying ascorbic acid significantly increased number of flower heads in fennel plants up to the higher

dose. The same effect was observed when spraying aspartic acid, phenylalanine and thiamine.

Ascorbic acid is not only an important antioxidant, it also appears to link flowering time,

developmental senescence, programmed cell death and responses to pathogens (Pastori et al 2003;

Barth et al 2004 and Pavet et al 2005). Furthermore, it affects nutritional cycle's activity in higher

plants and plays an important role in the electron transport system Liu et al (1997). El-Banna et al

(2006) found stimulatory effects of vitamin C on potato. Golan-Goldhirsh et al (1995) indicated that

soybean treated with ascorbic acid increased photosynthesis process. Talaat (2003) detected that

ascorbic foliar application on sweet paper increased content of macro-nutrients (N, P and K).

Increasing aspartic acid doses significantly increased seed weight g plant -1 up to 300 ppm. Spraying

vitamin C at 75 mgL -1 . resulted in the maximum seed weight. Attoa et al (2002) found that aspartic

acid at 75 ppm increased both the fixed oil and total glucosinolate contents of Iberis amara. The

maximum oil % was achieved from 300 ppm of phenylalanine (2.78%) compared with control (2.00%).

Table (4) showed the effect of foliar application of ascorbic acid and thiamine and amino acids,

aspartic and phenylalanine on essential oil composition of Foeniculum vulgare var. azoricum. The

analysis of essential oil of fennel showed the presence of 7 componds as main constituents. The major

one was found to be anethol (trans-1- methoxy-4- (Prop-1- enly) benzene; C10H12O).

It ranged from 61.55 to 77.31%, followed by fenchone with values of 6.14 to 13.62%. Estragol

occupied the third place and recorded 4.21% to 9.54%. Braun and Franz (1999) found that anethole,

estragole, fenchone and Limonene are the major constituents of fennel essential oil. They represent

99% of herb oil and 93% of the fruits oil. Mahfouz and Sharaf El-Din (2007) reported that Anethole

was the main component in F.vulgare oil. It reached the highest value with half dose of N, P and K

(mineral fertilization 357 kg ammonium sulphate + 238 kg calcium super-phosphate +60 kg potassium

sulphate ha -1 ) and inoculation with Basillus megatherium).

119


Ozean Journal of Applied Sciences 3(1), 2010

Table(4). Effect of foliar application of ascorbic acid and thiamine and amino acids, aspartic and phenylalanine on oil composition of Foeniculum vulgare var. azoricum .

Treatments � -pinene � -pinene Myrcene Limonene Fenchone Estragol Anethol Un-Known

Total identified

compounds

Control 0 2.24 0.44 1.55 7.33 10.24 9.54 61.55 7.11 92.89

Aspartic 100 ppm 1.15 traces 2.11 6.54 9.15 8.71 62.14 10.2 89.8

200 ppm 1.36 0.16 0.06 6.65 9.13 8.82 64.21 9.61 90.39

300 ppm 1.34 0.21 0.18 7.02 9.24 7.16 65.02 9.83 90.17

Phenylalanine 100 ppm 1.44 0.33 0.16 9.14 10.38 6.23 62.34 9.98 90.02

200 ppm 1.45 0.25 0.95 7.25 12.45 6.31 68.11 3.23 96.77

300 ppm 1.48 0.24 0.38 7.93 12.36 6.01 68.42 3.76 96.24

Thiamine 25 mg L -1

50 mg L -1

75 mg L -1

1.01 0.29 0.36 6.54 10.14 6.42 64.32 9.53 90.47

1.06 0.41 0.41 6.72 11.21 6.13 65.16 9.08 90.92

1.18 0.45 0.45 6.72 10.25 6.02 66.17 8.76 91.24

Ascorbic 25 mg L -1

50 mg L -1

75 mg L -1

1.32 0.38 0.85 5.13 13.62 4.32 72.22 2.16 97.84

1.35 0.36 0.93 5.14 6.14 4.21 77.31 4.56 95.44

1.38 0.25 0.99 5.16 8.36 4.45 74.16 5.25 94.75

120


Ozean Journal of Applied Sciences 3(1), 2010

Khalil et al (2008) stated that the major components in fennel seed oil are anethole, more than 45%

and limonene, more than 12%. Abd El-Wahab and Mehasen (2009) reported that anethole content

recorded higher percentage in Indian fennel than local fennel in all sowing time (7, 15 and 21 Nov. )

and sowing locations (El-Minia, Assuit, Sohag and Qena governorates) under upper Egypt conditions.

CONCLUSION

We recommended that among all applied treatments, ascorbic acid at 75 mg L -1 resulted in the best

values of growth parameters, while phenylalanine at concentration of 300 ppm recorded the highest

essential oil percent compared with control.

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Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Ozean Journal of Applied Sciences 3(1), 2010

Effect of water stress and potassium humate on the productivity of oregano plant

using saline and fresh water irrigation

H.A.H. Said-Al Ahl* and M.S. Hussein

Department of Cultivation and Production of Medicinal and Aromatic Plants,

National Research Centre, Dokki, Giza, Egypt.

Postal code: 12622

*E-mail address for correspondence: saidalahl@yahoo.com

_________________________________________________________________________________

Abstract: To study the response of oregano (Origanum vulgare L.) plants to soil moisture regimes

using fresh and saline water irrigation and potassium humate fertilization, a pot experiment was

conducted during two successive seasons (2007/2008 and 2008/2009) under the natural conditions of

the greenhouse of the National Research Center, Dokki, Giza, Egypt. Herb fresh weight g plant -1 and

the content and yield ml plant -1 of essential oil were decreased significantly by using saline water

irrigation compared to fresh water irrigation. Herb fresh weight g plant -1 and essential oil yield ml

plant -1 of Origanum vulgare L were significantly decreased with the rise in water stress levels.

Whereas, there was significant increase in essential oil % by using lower level of available soil

moisture (30% ASM) followed by 90% ASM and then 60% ASM contained the highest values of

essential oil %. Fresh herb and essential oil production increased significantly with K-humate

application. The maximum of herb fresh and essential oil yields were obtained from plants irrigated

with 90% available soil moisture fresh water combined with k-humate fertilizer 1.5 g pot -1 . Essential

oil % recorded their maximum value from plants irrigated with 60% ASM fresh water combined with

1.5 g pot -1 K-hum ate. Totally, 20 compounds were identified in essential oils of three populations by

means of GLC. Carvacrol was the dominant compound (46.44–77.96%) for all essential oil samples,

followed by p-cymene (5.31–19.30%) and γ-terpinene (3.38–16.42%). The composition of essential oil

of oregano was affected by soil moisture regimes using fresh and saline water irrigation and potassium

humate fertilization.

Keywords: Origanum vulgare L., essential oil, potassium humate, soil moisture regime, saline

irrigation, carvacrol

_________________________________________________________________________________

INTRODUCTION

The genus Origanum belongs to the family of Lamiaceae (Labiatae) and includes many species that are

commonly found as wild plants in the Mediterranean areas (Skoula and Harborne, 2002). Because of

special compositions of essential oil the leaves of Origanum plants are widely used as a very popular

spice for food production. Origanum vulgare L. is the widest spread among all the species within the

genus which distributed all over, Europe, West and Central Asia up to Taiwan, North Africa, and

America (Goliaris et al., 2002; Ietswaart, 1980). Traditionally, leaves and flowers of oregano are used

in Lithuania mostly for their beneficial properties to cure cough, sore throats, relieve digestive

complaints, and probably stimulate the appetite (Ien et al., 2008). The volatile oil of oregano has been

used traditionally for respiratory disorders, indigestion, dental caries, rheumatoid arthritis and urinary

tract disorders (Ertas et al., 2005). The essential oil of oregano is composed of carvacrol as dominant

component, followed by p-cymene, γ- terpinene, germacrene D, and thymol (Azizi et al., 2009;

Dorman and Deans, 2004; Horne et al., 2001; Said-Al Ahl et al., 2009 a, b; Veldhuizen et al., 2007).

Recently, this spice plant has drawn more attention of consumers due to the antimicrobial, antifungal,

insecticidal and antioxidative effects of this herb on humanhealthy (Bakkali et al., 2008; Jaloszynski et

al., 2008; Kulisic et al., 2004; Lopez et al., 2007; Soylu et al., 2007).

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Ozean Journal of Applied Sciences 3(1), 2010

The commercial value of an aromatic and of a medicinal plant could be reflected by the composition of

their essential oils. The quality of oregano is determined mainly by the essential oil content and its

composition. Both parameters may vary considerably depending on genotypes and cultivation

conditions (D’antuono et al., 2000; Novak et al., 2003). In addition, the essential oil content of oregano

leaves and its components seem to be strongly influenced by environmental problems, especially

water/salt stress (Charles et al., 1990) and deficiency and inadequate mineral nutrients (Stutte, 2006).

Salinity is one of the major factors that affect plant growth; it is a serious problem in many areas of the

world causing considerable loss in agricultural production (Bray et al., 2000; Shao et al., 2008; Wu et

al., 2007). Soil salinity resulting from natural processes or from crop irrigation with saline water,

occurs in many arid and semi-arid regions of the world (Lauchli and Epstein, 1990). In Egypt, saline

water is used for irrigation in some areas. In the same time, under the arid climatic conditions

prevailing in Egypt and associated with the perennial irrigation practices, imperfect drainage system,

continuous increase of water–table level and the relatively high salinity levels of water sources

particularly in the new reclaimed land, the salinization of Egyptian soils rapidly going to be an acute

problem.

Similar to other Lamiaceae species, however, uniformity in essential oil content and composition and

consistency in growth and development are especially susceptibility to environmental stress due to

plant heterogeneity. Thus, crop yields and quality in major oregano production regions that are

frequently subject to dry periods can fluctuate (Al-Amier and Craker, 2007). The use of irrigation over

the past several years to promote crop growth has increased the salt content of the soil, frequently

forcing growers to apply 10% to 20% excess water to lower salt concentrations in the root zone (Arndt

et al., 2001; Mohamed et al., 2002; Takabayashi and Dick 1996; Takabayashi et al., 1994). Water

stress in plants from a lack of moisture or from drought induced by salt stress is associated with many

metabolic changes, including essential oil metabolites. In addition, the water supply is one of the most

determinative cultivation conditions which significantly affect the yield and essential oil content of

various spices and herb crops (Aziz et al., 2008; Mohamed et al., 2002; Singh and Ramesh, 2000;

Singh et al., 2000, 2002; Zehtab- Salmasi et al., 2001). In most cases Origanum plants must be

irrigated during the cultivation period to obtain a good yield. For example during cultivation of

Origanum dictamnus in Crete (Greece), irrigation was necessary for two harvests in 1 year (Skoula and

Kamenopoulos, 1997). Practically, the time at which the plants are irrigated is important for the

efficiency of irrigation. For example, appropriate irrigation strategies showed a great potential for

improvement of the yield of monoterpenes in field-grown spearmint and rosemary (Delfine et al.,

2005). Dunford and Vazquez (2005) reported that herb yield of Mexican oregano (Lippia Berlandieri

Schauer) increased significantly with increasing moisture and the amount of water received by the plant

did not have a significant effect on the thymol and carvacrol content of the oil.

The improvement of plant nutrition can contribute to increased resistance and production when the crop

is submitted to water stress. However, the content of essential oils and their composition are affected by

fertilization.

Humic acid (HA) is one of the major components of humus. Humates have long been used as a soil

conditioner, fertilizer and soil supplement (Albayrak and camas, 2005). Humic acid can be used as

growth regulate-hormone level improve plant growth and enhance stress tolerance (Albayrak and

Camas, 2005; Piccola et al., 1992; Tan and Nopamornbodi, 1979). Fortun et al., 1989 and Kononova,

1966 reported that humic acid improve soil structure and change physical properties of soil, promote

the chelation of many elements and make these available to plants, aid in correcting plant chlorisis,

enhancement of photosynthesis density and plant root respiration has resulted in greater plant growth

with humate application (Chen and Avid, 1990; Smidova, 1960). Increase the permeability of plant

membranes due to humate application resulted in improve growth of various groups of beneficial

microorganisms, accelerate cell division, increased root growth and all plant organs for a number of

horticultural crops and turfgrasses, as well as, the growth of some trees, Russo and Berlyn (1990),

Sanders et al. (1990) and Pioncelot (1993).

So far, there is no report on the yield and composition of the essential oil of Origanum vulgare L.

plants cultivated under this experimental condition in literature.

The aim of the present research was to investigate to evaluate oregano plants grown under osmotic

stress conditions and using organic fertilizer treatments to raise the tolerant of this plant to stress

conditions, and also to provide information on the composition of Origanum vulgare volatile oil and

its variability among osmotic stress conditions.

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Ozean Journal of Applied Sciences 3(1), 2010

MATERIALS AND METHODS

A pot trail study was carried out during the two successive seasons of 2007/2008 and 2008/2009 under

the natural conditions of the greenhouse of the National Research Center, Dokki, Giza, Egypt. The

physical and chemical analyses of the soil were determined according to Jackson, 1973. The soil

texture was sandy loam, having a physical composition as follows: 45.70% sand, 28.40% silt, 25.90%

clay and 0.85% organic matter. The results of soil chemical analysis were as follows: pH= 8.05; E.C

(dsm -1 ) = 0.81; and total nitrogen =0.09 %; available phosphorus =2.26mg/100gram; potassium= 18.85

mg/100gram; field capacity (F.C.) and wilting point (W.P.) were determined according to the pressure

membrane methods described by Black, 1965. Field capacity, permanent wilting point, available soil

moisture (A.S.M) and bulk density (B.D.), as means over the two seasons were 34.0 %, 16.0 % 18.0 %

and 1.36 g/cm 3 , respectively.

Seeds of oregano were obtained from Jellitto Standensamen Gmbh, Schwarmstedt, Germany. The

seeds were sown in the nursery on 15 th November during both seasons. The seedlings were transplanted

into pots (30 cm diameter, 50 cm depth) on the 15 th February of each season. Each pot contained three

seedlings and was placed in full sun light. Each pot was filled with 10 kg of air dried soil. The soil

related to the typic torrifluvents (based on USDA, 1996). Two levels of potassium humate (0.0 and 1.5

g pot -1 ) was applied to the soil with water irrigation application at three equal portions before each cut

in both seasons. Potassium humate which was used in this study is produced by Leili Agrochemistry

Co., LTD, China and its properties are shown in Table (1). Then after one month from transplanting,

irrigation treatments were applied to the oregano plants (90, 60 and 30% available soil moisture) equal

to 32.20., 26.80 and 21.40 soil moisture. The pots were separated into two sets, the first set irrigated

with tap water (0.40 dsm -1 ), and the second set irrigated with Nacl solution (4 dsm -1 ). Pots were

weighted daily and when soil moisture percentage reached the aforementioned points, pots were

irrigated to reach field capacity (34.0% soil moisture). The differences between the needed soil

moisture for the previous treatments and field capacity were calculated and added to the pots in the

different treatments. The experimental layout was factorial experiment in complete randomized design

(CRD) with three replications. Each replicate contained ten pots, while the pot contained three plants.

Herbal fresh weight (g plant -1 ) of each replicate was determined in the first, second and third cuts at

31 May, 31 July and 30 September, respectively before flowering stage in both seasons. Essential oil

content was determined by hydro-distillation for 3 hours by submitting fresh herb (100 g) for each

replicate at each cut in both seasons in modified Clevenger apparatus (Guenther, 1961). Essential oil

percentage of each replicate was determined and expressed as (%), while essential oil yield per plant

was expressed as ml plant -1 . The essential oils of each treatment were collected and dehydrated over

anhydrous sodium sulphate and kept in a refrigerator until gas-liquid chromatography (GLC) analyses.

The GLC analysis of the essential oil samples was carried out in the second season using a Hewlett

Packard gas chromatograph apparatus at the Central Laboratory of the National Research Center

(NRC) with the following specifications: instruments: Hewlett Packard 6890 series, column; HP

(Carbwax 20M, 25m length x 0.32mm I.D), film thickness: 0.3mm, sample size: 1µl, oven temperature:

60-190°C, Program temperature: 60°C/2min, 8°C/min, 190°C/25min, injection port

temperature:240°C, carrier gas: nitrogen, detector temperature (FID): 280°C, flow rate: N2 3ml/min.,

H2 3ml/min., air 300ml/min. Main compounds of the essential oil were identified by matching their

retention times with those of the authentic samples that were injected under the same conditions. The

relative percentage of each compound was calculated from the peak area corresponding to each

compound. Except for the constituents of the essential oils, the data of this experiment were statistically

analyzed according to Snedcor and Cochran (1981).

A.Herb fresh yield

RESULTS AND DISCUSSIONS

Effect of water stress using fresh or saline water irrigation

Data in Table (2) clear the effect of water stress and potassium humate on the productivity of oregano

plant using saline and fresh water irrigation. Under water stress, increase in available soil moisture

significantly enhanced the fresh herb yield in all cuts of both seasons. Increasing water amounts

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Ozean Journal of Applied Sciences 3(1), 2010

increased herb fresh weight. The highest mean values due to irrigation treatments were recorded with

plants that received the highest amounts of water. The pronounced effect of increased irrigation on

fresh herb yield may be attributed to the availability of sufficient moisture around the root concentrated

and thus a greater proliferation of root biomass resulting in the higher absorption of nutrients and water

leading to production of higher vegetative biomass (Singh et al., 1997). On the other hand, increasing

levels of water stress reduce growth and yield due to reduction in photosynthesis and plant biomass.

Under increasing water- stress levels photosynthesis was limited by low Co2 availability due to

reduced stomatal and mesophyll conductance. Drought stress is associated with stomatal closure and

thereby with decreased Co2 fixation. The superiority of the plants that received the highest rate of

irrigation treatments in producing the heaviest total plant fresh weight was in agreement with that of El-

Naggar et al. (2004); Moeini Alishah et al. (2006); Said-Al Ahl and Abdou (2009); Said-Al Ahl et al.

(2009 a, c) .

Data tabulated in Table (2) show that fresh weight of herb (g plant -1 ) decreased significantly with

increment of saline irrigation conditions in all cuts during both seasons. The inhibitory effect of

salinity was also found by (Abd El-Hady, 2007; Abd El-Wahab, 2006; Baghalian et al., 2008; Belaqziz

et al., 2009; Ozturk et al., 2004; Razmjool et al., 2008; Shalan et al., 2006; Turhan and Eris, 2007).

Saline conditions reduce the ability of plants to absorb water causing rapid reductions in growth rate,

and induce many metabolic changes (Epstein, 1980). Also, salt stress with osmotic, nutritional and

toxic effects prevents growth in many plant species (Cheeseman, 1988; Hasegawa et al., 1986).

Therefore, the reduction in growth was explained by lower osmotic potential in the soil, which leads to

decreased water uptake, reduced transpiration, and closure of stomata, which is associated with the

reduced growth (Ben-Asher et al., 2006; Levitt, 1980). In general, the mechanisms of salinity effect on

plant growth were reported by Meiri and Shalhavet (1973) who attributed the effect of salinity to the

following points: (a) the distribution of salts within the plant cells may result in turgor reduction and

growth retardations. Also, salinity affects root and stomatal resistance to water flow, (b) the balance

between root and shoot hormones changes considerably under saline conditions, (c) salinity changes

the structure of the chloroplasts and mitochondria and such changes may interfere with normal

metabolism and growth, (d) salinity increases respiration and reduces photosynthesis products available

for growth.

Effect of potassium humate application

Also, data reported in Table (2) showed that foliar application of humic acid caused significantly

positive trend in increasing herb fresh yield (g plant -1 ). Similar results were reported by Said-Al Ahl et

al. (2009, b) on Origanum vulgare and Zaghloul et al. (2009) on Thuja orientalis who indicated that

spraying the plants with potassium humate increased growth compared with control plants due to the

direct effect of humic acid on solubilization and transport of nutrients. These results are in accordance

with those obtained by Norman et al. (2004) on marigolds and peppers and number of fruits of

strawberries. Chen and Avaid (1990) added that humic substances have a very pronounced influence on

the growth of plant roots thought enhance root initiation which known as root stimulator. Humic acid

improve growth of plant foliage and roots where, Vaughan (1974) proposed that humic acids may

primarily increase root growth by increasing cell elongation or root cell membrane permeability,

therefore increased water uptake by increased plant roots, as well as it can produce root systems by

increasing branching and number of fine roots, as a result potentially increase nutrients uptake by

increase root surface area (Rauthan and Schnitzer, 1981).

Effect of interaction

There was a significant difference in most of interaction treatments between water or salt stress and

potassium humate application. Increment the available soil moisture using saline or fresh water

combined with potassium humate enhanced the fresh herb yield. The irrigation applied at 90%

available soil moisture using fresh water irrigation, combined with potassium humate gave the best

result of fresh herb yield in the all cuts during both seasons.

B. Essential oil production

Effect of water stress using fresh or saline water irrigation

In all cuts in both seasons, both water quantities using saline and fresh water irrigation and potassium

humate application and their interaction affected the content of essential oils in oregano (Tables 3, 4).

The mean values of essential oils due to water irrigation treatments showed that increasing water

supply from 30% to 60% available soil moisture increased essential oil percentage. Increasing water

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Ozean Journal of Applied Sciences 3(1), 2010

supply from 60% to 90% available soil moisture decreased percentage of essential oils. In other words,

the medium stress condition (60% available soil moisture treatment) accelerated the production of

essential oils, while the severe stress conditions due to water (40% available soil moisture treatment)

decreased the biosynthesis of the essential oils. On the contrary, essential oil yield increased with

increment of available soil moisture (Table 4).

Table (3) explains that salt condition significant decreased essential oil % at all cuts in both seasons.

With similar, essential oil yield also was significant decreased at all cuts of both seasons as a result of

salt stress (Table 4). The inhibitory effect of high level of salinity was also found by many investigators

(Abd El-Wahab, 2006; Baghalian et al., 2008; Ozturk et al., 2004; Razmjoo et al., 2008; Shalan et al.,

2006). The reduction of essential oil yield by salinity may be due to a decrease in growth characters

and/or essential oil %. Salt stress may also affect the essential oil accumulation indirectly through its

effects on either net assimilation or the partitioning of assimilate among growth and differentiation

processes (Charles et al., 1990).

Penka (1978) showed that the formation and accumulation of essential oil in plants was explained as

due to the action of environmental factors. It might be claimed that the formation and accumulation of

essential oil was directly dependent on perfect growth and development of the plants producing oils.

The decrease in oil production might be due to the decrease in plant anabolism.

Effect of potassium humate application

Essential oil percent and yield (ml plant -1 ) in oregano herb were significantly increased as a result of

foliar application with K-humate (Tables 3, 4). Said-Al Ahl et al. (2009, b) and Zaghloul et al. (2009)

reported that humate application lead to increase oil content in Origanum vulgare and Thuja orientalis,

respectively. From the above mentioned results, it could be concluded that foliar application of Khumate

promoted growth and possessed the best oil percentage and yield (ml plant -1 ) in oregano plant.

Effect of interaction

Generally, the maximum essential oil content was observed in the fresh herb of plants that irrigated

using fresh water at 60% ASM and sprayed with 1% K-humate in the all cuts during both seasons. In

addition, spraying oregano plants with K-humate caused an increase in the essential oil yield (Table 4).

Generally, the highest essential oil yield (ml plant -1 ) was obtained from plants irrigated using fresh

water at 90% ASM and sprayed at 1% K-humate in all cuts of both seasons. The increment of essential

oil yield may be obtained as a result of increment herb weight and/or essential oil %.

Essential oil composition of oregano

Totally, 20 constituents were identified for the oregano essential oil (Tables 5, 6). Carvacrol content

was the dominant constituent of the essential oil for all samples tested, ranging from 46.44% to

77.96%. The second major constituent was p-cymene (ranging from 5.31% to 19.30%) and the third

one was γ-terpinene (ranging from 3.38% to 16.42%). The other main constituents were α-pinene (0-

5.39%), α-terpinene (0-5.39%), α-thujene (0-5.05%), germacrene D (0-2.91%), thymol (0-2.76%),

caryophyllene (0-2.70%), terpineol-4-ol (0-1.56%) and β-pinene (0-1.19%). Other constituents such as

linalool, limonene, borneol, α-terpineol, bornyl acetate, carvacrol acetate, elemene, cadinene and

caryophyllene oxide were present in amount less the 1%.

In second cut of second season, among water and saline stress, the carvacrol percentage of essential oil

was increased by raising amount of fresh water irrigation and irrigation at 90% ASM gave a higher

value (77.96%), 60% ASM (67.17%) and 30% ASM gave a lower value (60.36%), but there was

decrease in this regard by raising amount of saline water irrigation and irrigation at 30% ASM gave a

higher content (58.02%), 90% ASM (57.79%) and 60% ASM gave a lower content (46.44%). Whereas,

p-cymene was decreased by raising amount of fresh and saline water irrigation and a higher content of

this component was resulted from irrigation at 30% ASM (15.63 and 16.94% using fresh and saline

water, respectively), 60% ASM fresh water and 90% ASM saline water (11.64 and 16.03%,

respectively) and a lower content (8.76 and 13.29%, resulted from 90% ASM fresh water and 60%

ASM saline water, respectively). Correspondingly, the percentage of γ-terpinene was decreased by

raising amount of fresh water irrigation and irrigation at 30% ASM gave a higher value (7.65%), 60%

ASM (6.61%) and 90% ASM gave a lower value (3.56%), but there was increase in this regard by

raising amount of saline water irrigation and irrigation at 90% ASM gave a higher content (12.94%),

30% ASM (11.63%) and 60% ASM gave a lower content (11.32%), Table (5). It is clear that saline

water irrigation increased the biosynthesis of p-cymene and γ-terpinene, while the apposite was true

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Ozean Journal of Applied Sciences 3(1), 2010

with carvacrol. It is well known p-cymene transforms to thymol or carvacrol and the environmental

conditions affect the rate of transformation (Aziz et al., 2008; Omer, 1999).

From Table (6) it can be observed the differences between three major constituents of essential oil of

oregano supplying with a water level of 90% available soil moisture and without / with 1.5 g K-humate

pot -1 in three cuttings, carvacrol was higher for plants irrigated with a fresh water alone in second cut

and compared to other treatments but, the plants irrigated with a saline water alone in first cut

contained a lower content. On the contrary p-cymene and γ-terpinene were the highest by using saline

water irrigation and with K-humate in first cut and the lowest content from the plants irrigated with

fresh water alone in third cut. Irrigation with 90% ASM with fresh water without potassium humate in

second cut gave the maximum value of carvacrol content (77.96%), while irrigation with 90% ASM

with fresh water without potassium humate in first cut gave the highest values for both p-cymene

(10.99%) and γ-terpinene (8.41%). Under saline water irrigation the maximum values for both pcymene

(19.30%) and γ-terpinene (16.42%) were obtained as a result of 90% ASM with potassium

humate in first cut, while 90% ASM with potassium humate in second cut gave the highest value of

carvacrol (63.17%).

Table (7) indicates that saline water irrigation decreased the mean value of carvacrol and on the

contrary there was increased in p-cymene and γ-terpinene mean values by using saline water irrigation.

Whereas, mean values of carvacrol, p-cymene and γ-terpinene were increased by application of Khumate.

Also, mean values of carvacrol, p-cymene and γ-terpinene were affected by cuttings. For

carvacrol, third cut recorded the highest mean value followed by second cut and then first cut.γterpinene

has adverse behavior, first cut resulted the highest mean value followed by second cut and

then third cut. However, the highest mean value of p-cymene resulted from second cut and third cut

recorded the lowest mean value.

Second cut was effective in raising the productivity of the essential oil yield. Table (8) show that saline

water irrigation decreased the mean value of carvacrol and on the contrary there was increased in pcymene

and γ-terpinene mean values by using saline water irrigation. Among soil moisure levels, the

carvacrol mean value of essential oil was the highest at 90% ASM and 60% ASM obtained the lowest

mean value. Also, the mean values of p-cymene and γ-terpinene were the highest for 30% ASM

followed by 60% ASM and then 90% ASM.

CONCLUSIONS

Our study showed that herbal production and essential oil content of Origanum vulgare L. can be

significantly affected by environmental and agronomical conditions including potassium humate

fertilization and soil moisture regime using fresh and saline water irrigation. Application of potassium

humate increase herb fresh yield and essential oil content of oregano herbage. Herbal fresh yield and

essential oil % and oil yield ml plant -1 were significant decreased by using a saline water irrigation

compared to fresh water. Supplying plants with a water level of 90% available soil moisture was

effective in raising the productivity of herb and yield of essential oil, but 60% available soil moisture

was effective in essential oil percentage, whereas 30% available soil moisture significantly decreased

herbal fresh yield and essential oil % and oil yield ml plant -1 .The interaction between 90% available

soil moisture of fresh water and with 1.5 g pot -1 k-hum ate gave the best results for herb and yield of

essential oil. Essential oil % recorded their maximum value from plants irrigated with 60% ASM of

fresh water combined with 1.5 g pot -1 K-humate. Whereas percentage of main compounds of essential

oil such as carvacrol, γ-terpinene and p-cymene affected by these treatments. Supplying plants with a

water level of 90% available soil moisture of fresh water alone in second cut contained the highest

value of carvacrol, but p-cymene and γ-terpinene recorded their maximum values by irrigating

Origanum vulgare with a saline water level of 90% available soil moisture and with k-humate in first

cut.

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Ozean Journal of Applied Sciences 3(1), 2010

TABLES

Table 1. Guaranteed analysis and physical data of Humic total

Guaranteed analysis

Humic acid 80%

Potassium (K2O) 10-12%

Zn, Fe, Mn, etc., 100ppm

Physical Data

Appearance Black powder

pH 9-10

Water solubility < 98%

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Ozean Journal of Applied Sciences 3(1), 2010

Table 2. Effect of water stress using saline and fresh water irrigation, K-humate fertilizer and their interaction treatments on the herb fresh weight of oregano

plants during the two seasons.

K-humate

132

First Season

Water

Herb fresh weight (g plant

and salt

stress

-1 )

Without

K-humate

First cut

K-humate Mean

Without

K-humate.

Second cut

K-humate. Mean

Without

K-humate

Third cut

K-humate Mean

S1 2.41 4.58 3.49 3.72 6.45 5.08 1.05 1.58 1.31

S2 4.18 7.77 5.97 7.50 10.07 8.78 3.13 5.02 4.08

S3 5.71 10.53 8.12 8.96 17.43 13.20 4.38 7.30 5.84

S4 1.58 2.02 1.80 2.03 2.48 2.25 0.61 0.75 0.68

S5 2.02 2.49 2-25 2.76 3.01 2.88 0.94 1.24 1.09

S6 2.72 3.21 2-96 3.59 4.42 4.00 1.83 2.02 1.92

Mean 3.10 5.10 4.76 7.31 6.03 1.99 2.98

L.S.D. at 5% K-humate =0.056

K-humate = 0.046

K-humate = 0.034

Stress = 0.098

Stress = 0.079

Stress = 0.059

Interaction =0.138

Interaction = 0.113

Interaction =0.083

S1 2.47 4.58 3.53 3.69

Second Season

6.45 5.07 1.03 5.03 3.03

S2 4.19 7.69 5.94 7.53 10.17 8.85 3.10 7.20 5.15

S3 5.70 10.75 8.23 8.88 17.28 13.08 4.44 0.58 2.51

S4 1.49 2.02 1.75 1.97 2.43 2.20 0.58 0.71 0.64

S5 2.05 2.42 2.23 2.72 3.05 2.88 0.94 1.10 1.02

S6 2.61 3.15 2.88 3.65 4.39 4.02 1.88 2.07 1.97

Mean 3.08 5.10 4.74 7.29 1.99 2.78

L.S.D. at 5% K-humate =0.050

K-humate = 0.042

K-humate = 0.039

Stress = 0.087

Stress = 0.073

Stress = 0.067

Interaction =0.123

Interaction =0.103

Interaction =0.055

S-stress; S1, S2, S3= irrigation of: 30, 60, 90% available soil moisture using fresh water; S4, S5, S6= irrigation of: 30, 60, 90% available soil moisture using

saline water


Ozean Journal of Applied Sciences 3(1), 2010

Table 3. Effect of water stress using saline and fresh water irrigation, K-humate fertilizer and their interaction treatments on the herb fresh volatile oil (%) of

oregano plants during the two seasons.

K-humate

133

First Season

Water

Volatile oil (%)

and salt

stress

Without

K-humate

First cut

K-humate Mean

Without

K-humate.

Second cut

K-humate. Mean

Without

K-humate

Third cut

K-humate Mean

S1 0.533 0.633 0.583 0.450 0.533 0.491 0.416 0.433 0.425

S2 0.650 0.750 0.700 0.533 0.633 0.583 0.500 0.583 0.541

S3 0.600 0.683 0.641 0.500 0.600 0.550 0.466 0.533 0.500

S4 0.366 0.383 0.375 0.316 0.366 0.341 0.233 0.266 0.250

S5 0.450 0.483 0.466 0.433 0.483 0.458 0.383 0.400 0.391

S6 0.433 0.466 0.450 0.433 0.466 0.450 0.350 0.383 0.366

Mean 0.505 0.566 0.444 0.513 0.391 0.433

L.S.D. at 5% K-humate = 0.0157

K-humate = 0.0143

K-humate = 0.0184

Stress = 0.0275

Stress = 0.0247

Stress = 0.0319

Interaction =N.S

Interaction = 0.0349

Interaction =0.0451

S1 0.516 0.633 0.575 0.433

Second Season

0.533 0.483 0.400 0.433 0.416

S2 0.633 0.766 0.700 0.533 0.616 0.575 0.500 0.583 0.541

S3 0.616 0.666 0.641 0.500 0.583 0.541 0.450 0.533 0.491

S4 0..383 0.416 0.400 0.300 0.383 0.341 0.250 0.316 0.283

S5 0.483 0.500 0.491 0.466 0.466 0.466 0.366 0.383 0.375

S6 0.433 0.450 0.441 0.416 0.433 0.425 0.366 0.383 0.375

Mean 0.511 0.572 0.541 0.441 0.502 0.388 0.438

L.S.D. at 5% K-humate = 0.0150

K-humate = 0.0190

K-humate = 0.0178

Stress = 0.0260

Stress = 0.0329

Stress = 0.0308

Interaction =0.0368

Interaction =0.0466

Interaction =0.0436

S-stress; S1, S2, S3= irrigation of: 30, 60, 90% available soil moisture using fresh water; S4, S5, S6= irrigation of: 30, 60, 90% available soil moisture using

saline water


Ozean Journal of Applied Sciences 3(1), 2010

Table 4. Effect of water stress using saline and fresh water irrigation, K-humate fertilizer and their interaction treatments on the volatile oil yield (ml plant -1 )

of oregano plants during the two seasons.

K-humate

134

First Season

Water

Oil yield (ml plant

and salt

stress

-1 )

Without

K-humate

First cut

K-humate Mean

Without

K-humate.

Second cut

K-humate. Mean

Without

K-humate

Third cut

K-humate Mean

S1 0.0128 0.0289 0.0209 0.0167 0.0353 0.0260 0.0044 0.0068 0.0056

S2 0.0271 0.0582 0.0427 0.0400 0.0528 0.0464 0.0153 0.0293 0.0223

S3 0.0342 0.0725 0.0534 0.0448 0.0916 0.0682 0.0204 0.0389 0.0296

S4 0.0058 0.0077 0.0068 0.0064 0.0091 0.0078 0.0014 0.0016 0.0015

S5 0.0091 0.0121 0.0106 0.0120 0.0146 0.0133 0.0036 0.0050 0.0043

S6 0.0118 0.0150 0.0134 0.0156 0.0206 0.0181 0.0064 0.0078 0.0071

Mean 0.0168 0.0324 0.0226 0.0373 0.0086 0.0149

L.S.D. at 5% K-humate = 0.00076

K-humate = 0.0048

K-humate = 0.0005

Stress = 0.00281

Stress = 0.0083

Stress = 0.0009

Interaction =0.00188

Interaction = 0.0118

Second Season

Interaction =0.0013

S1 0.0154 0.0290 0.0222 0.0160 0.0344 0.0252 0.0041 0.0065 0.0053

S2 0.0265 0.0589 0.0427 0.0387 0.0627 0.0507 0.0155 0.0294 0.0224

S3 0.0351 0.0717 0.0534 0.0444 0.1008 0.0726 0.0799 0.0384 0.0591

S4 0.0057 0.0337 0.0197 0.0059 0.0093 0.0076 0.0014 0.0023 0.0018

S5 0.0099 0.0121 0.0110 0.0127 0.0142 0.0134 0.0036 0.0046 0.0041

S6 0.0113 0.0142 0.0128 0.0152 0.0190 0.0171 0.0069 0.0079 0.0074

Mean 0.0173 0.0366 0.0270 0.0221 0.0401 0.0186 0.0148

L.S.D. at 5% K-humate = 0.0073

K-humate = 0.0012

K-humate = 0.0171

Stress = 0.0126

Stress = 0.0021

Stress = 0.0297

Interaction =0.0178

Interaction =0.0030

Interaction =0.0420

S-stress; S1, S2, S3= irrigation of: 30, 60, 90% available soil moisture using fresh water; S4, S5, S6= irrigation of: 30, 60, 90% available soil moisture using

saline water


Ozean Journal of Applied Sciences 3(1), 2010

Table 5. Essential oil composition (%) of Origanum vulgare L. plants grown under different levels of

Available soil moisture using fresh and saline water irrigation at second cut in 2009 season.

Compounds

135

Treatments

Irrigation with fresh water Irrigation with saline water

30% ASM 60% ASM 90% ASM 30% ASM 60% ASM 90% ASM

���thujene -- -- 0.33

���pinene -- 0.11 0.08

���pinene 0.56 0.61 0.11

��terpinene

0.45 0.28 0.38

P-cymene

15.63 11.64 8.76

limonene

γ- terpinene

linalool

borneol

Terpinene-4-ol

��terpineol

thymol

Bornyl acetate

carvacrol

Carvacrol acetate

elemene

0.70 0.46 0.30

7.65 6.61 3.56

0.64 0.35 0.54

0.90 0.76 0.03

0.85 0.51 0.40

0.19 0.20 0.27

1.87 1.55 0.98

0.16 0.19 0.06

60.36 67.17 77.96

0.59 0.41 0.59

0.29 0.21 0.36

�caryophyllene 0.14 0.45 0.40

germacrene D

cadinene

caryephyllene oxide

Identified compounds

0.59 1.61 0.83

0.05 0.09 0.01

-- -- 0.01

91.62 93.21 95.96

Irrigation of: 30, 60, 90% ASM– of available soil moisture

-- 5.05

-- 2.70

-- 0.75

1.62 5.39

16.94 13.29

-- 0.49

11.63 11.32

-- 0.41

-- 1.89

-- 1.56

-- --

-- 2.76

-- --

58.02 46.44

-- --

-- 0.45

1.27 2.57

1.52 1.66

-- --

-- 0.87

91.00 97.59

1.15

0.11

0.25

1.53

16.03

--

12.94

0.18

--

0.37

--

0.96

0.24

57.79

0.30

--

1.02

1.07

0.05

0.16

94.05


Compounds

���thujene

���pinene

���pinene

��terpinene

P-cymene

limonene

γ- terpinene

linalool

borneol

Terpinene-4ol

��terpineol

thymol

Ozean Journal of Applied Sciences 3(1), 2010

Table 6. Essential oil composition (%) of Origanum vulgare L. plants grown with 90% Available soil

moisture using fresh and saline water irrigation and/or k-humate application during three cuts in 2009

season.

Bornyl acetate

carvacrol

Carvacrol

acetate

elemene

�caryophyllene

germacrene D

cadinene

caryephyllene

oxide

Identified

compounds

Treatments

Irrigation with fresh water

Irrigation with saline water

Without K-humate With K-humate

Without K-humate With K-humate

Cut 1 Cut 2 Cut 3 Cut 1 Cut 2 Cut 3 Cut 1 Cut 2 Cut 3 Cut 1 Cut 2 Cut 3

0.21 0.33 0.33 0.31 0.31 1.32 1.50 1.15 1.45 0.77 0.37 1.07

0.23

0.81

0.46

10.99

0.90

8.41

0.40

0.45

0.41

0.20

1.51

0.21

66.04

0.21

0.14

0.36

0.66

0.07

--

92.67

0.08

0.11

0.38

8.76

0.30

3.56

0.54

0.03

0.40

0.27

0.98

0.06

77.96

0.59

0.36

0.40

0.83

0.01

0.01

95.96

0.18

1.04

0.58

5.31

0.53

3.38

0.24

0.23

0.52

--

0.91

0.18

77.04

0.28

0.23

0.22

2.45

0.31

0.19

94.15

0.39

0.65

0.49

9.21

0.36

7.33

0.31

0.40

0.61

0.27

1.27

0.45

67.51

0.81

0.45

0.70

0.48

--

--

91.90

0.31

--

--

10.73

--

5.33

0.36

--

0.43

0.63

1.01

0.30

74.54

0.89

0.45

0.35

0.47

0.02

--

96.13

136

1.74

0.66

0.56

5.41

--

5.00

0.63

0.39

0.68

--

1.33

0.37

71.74

0.51

0.43

0.90

2.00

0.80

0.43

94.90

1.51

1.19

1.27

13.08

--

13.56

--

--

0.71

--

1.52

--

52.41

--

--

2.70

0.79

0.73

--

91.97

0.11

0.25

1.53

16.03

--

12.94

0.18

--

0.37

--

0.96

0.24

57.79

0.30

--

1.02

1.07

0.05

0.16

94.05

0.18

0.41

--

11.95

--

11.41

--

0.12

0.40

0.08

1.03

--

60.11

0.19

--

1.15

2.91

0.30

0.11

91.50

0.88

--

1.64

19.30

--

16.42

--

--

--

--

1.61

--

54.29

--

--

1.77

--

--

--

96.68

0.40

--

0.15

17.40

--

9.58

--

--

0.65

--

1.45

--

63.17

0.65

0.11

0.75

1.60

--

0.01

96.29

0.60

0.11

0.34

12.08

0.41

10.52

0.18

0.11

0.25

0.19

1.18

0.18

61.29

0.29

0.18

1.71

2.45

0.28

0.17

93.59


Ozean Journal of Applied Sciences 3(1), 2010

Table 7. Important differences in three main compounds of Origanum vulgare L. essential oil. The

plants were grown with 90% Available soil moisture using fresh and saline water irrigation and/or k-

humate application during three cuts in 2009 season.

Compounds

137

Treatments

Water irrigation K-humate Cuttings

Mean of

Fresh

Mean of

Saline

Mean of

Without

Mean of

With

Mean of

Cut 1

Mean of

Cut 2

Mean of

Cut 3

carvacrol 72.47 58.13 65.18 65.42 60.22 63.36 67.79

P-cymene 8.40 14.37 11.02 12.35 13.14 13.23 8.68

γ- terpinene 5.50 12.40 8.87 9.03 11.43 7.85 7.57

Total 86.37 85.50 85.07 86.80 84.79 84.44 84.04

Table 8. Important differences in three main compounds of Origanum vulgare L. essential oil. The

plants were grown under different levels of Available soil moisture using fresh and saline water

irrigation at second cut in 2009 season.

Compounds

Mean of 30%

ASM

Treatments

Soil moisture Water irrigation

Mean of 60%

ASM

Mean of 90%

ASM

Mean of Fresh Mean of

Saline

carvacrol 59.19 56.80 64.87 68.49 54.08

P-cymene 16.28 12.46 12.39 12.01 15.42

γ- terpinene 9.64 8.96 8.25 5.94 11.96

Total 85.11 78.22 85.51 86.44 81.46


Ozean Journal of Applied Sciences 3(1), 2010

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Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Influence of Foliar Application of Pepton on Growth, Flowering and Chemical

Composition of Helichrysum bracteatum Plants under Different Irrigation

Intervals.

Soad , M.M. Ibrahim, Lobna, S. Taha* and M.M. Farahat

Department of Ornamental Plant and Woody Trees,

National Research Centre, Dokki, Cairo, Egypt

*E-mail address for correspondence: lonbasalah82@yahoo.com

___________________________________________________________________________________

Abstract: Two field experiments were carried out at Research and Production Station, Nubaria of

National Research Center, Egypt, during 2007 and 2008 seasons. The purpose of this study is to

investigate the influence of foliar spraying with peptone (0, 250, 500 and 1000 ppm) on growth,

flowering and chemical composition under three irrigation intervals (2, 4 and 6 days) on Helichrysum

bracteatum. Irrigation intervals treatments have a depressing effect on different growth characters

(plant height, number of branches/plant, leaf area and fresh and dry weight of leaves) by increasing

irrigation intervals. The same manner was observed and concerning flowering parameters and

chemical constituents (total soluble sugars, total soluble indoles and free amino acids). On the

contrary, three pigments content and total soluble phenols. Data also, showed that all growth

parameters and flowering parameters (number of flower/plant, flower diameter and fresh and dry

weights of flowers) were significantly promoted by increasing the concentration of pepton from 250 to

500 and 1000 ppm as well as chemical constituents. The most promising results were obtained from

plants treated with pepton 1000 ppm and irrigated every 2 days. These treatments may be

recommended for decreasing the hazard effect on growth of Helichrysum bracteatum under different

irrigation intervals.

Keywords: foliar pepton, irrigation intervals, growth parameters, chemical composition.

_________________________________________________________________________________

INTRODUCTION

Straw flower, Hardy Annual or Everlasting (Helichrysum bracteatum). Family Asteraceae is an easy

annual plant to grow with yellow, orange, pink, deep rose, red, wine, magento, purplor white blooms.

The true petals are found in the center of each flower and they are surrounded by colorful, straw like

bracts. The flowers bloom from summer to early autumn. Harvest flowers for drying before they open

fully. Seeds need light to germinate, plant in porous soil. It endemic to Austalia, growing in open

scrub and grassland areas. And using in Dried Arrangement, Border, Rock garden and Cutting Bed.

Water is the major component of the plant body. It constituents about 80 to 90 % of fresh weight of

most herbaceous plant organs and over 50 % of the fresh weight of woody parts. Water affects

markedly, either directly or indirectly, most plant physiological processes. Hence, with the exception

of some kinds of seeds, dehydration of plant tissues below some critical level is accompanied by

irreversible changes in structure and ultimately by plant death. The importance of water in living

organisms results from its unique physical and chemical properties, which also determine its functions

in plant physiology, water is a major constituent of the protoplasm, it acts as a solvent for many solid

and gaseous substances, forming a continuous liquid phase throughout the plant, it takes part in many

important physiological reactions, it maintains cell turgor, which exerts an impact on many

physiological processes. Several authors indicated the promotive effect of the high levels of wate

supply on growth parameters including, Farahat (1990) on Schinus molle, Schinus terebinthifolius and

Myoporum acuminatum, Sayed (2001) on Khaya senegalensis, Uday et al (2007), and Soad (2005) on

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Simmodsia chinensis, Azza and Sahar (2006)on Melia azedarach and Azza et al (2007) on Bauhinia

variegata.

Amino acids as organic nitrogenous compounds are the building blocks in the synthesis of proteins,

Davies (1982). Amino acids are particularly important for stimulation cell growth. They act as buffers

which help to maintain favorable pH value within the plant cell, since they contain both acid and basic

groups; they remove the ammonia from the cell. This function is associated with amide formation, so

they protect the plants from ammonia toxicity. They can serve as a source of carbon and energy, as

well as protect the plants against pathogens. Amino acids also function in the synthesis of other

organic compounds, such as protein, amines, purines and pyrimidiens, alkaloids vitamins, enzymes,

terpenoids and others, Goss (1973) and Hass (1975), stated that the biosynthesis of cinamic acids

(which are the starting materials for the synthesis of phenols) are derived from phenylalanine and

tyrosine. Tyrosine is hydroxyl phenol amino acid that is used to build neurotran smitters and

hormones. Several other authors indicated that promotive effect of amino acids on ornamental and

medicinal plants including, Mohamed and Khalil (1992) on Antirrhinum majus, Matthiola incana and

Callistephus chinensis, Hussein et al (1992) on Datura metel, Mohamed and Whaba (1993) on

Rosmarinus officinalis, Abou Dahab and Nahed (2006) on Philodendron erubescens and Nahed and

Balbaa (2007) on Saliva farinacea.

Therefore, the present investigation was planned to explore the ability of helichrysum plants of

tolerating various degrees of drought, and possible alleviating of the harmful effects by the use of

pepton.

MATERIALS AND METHODS

Two field experiments were carried out at National Research Centre (Research and Production Station,

Nubaria), during two successive seasons of 2006/2007 and 2007/2008 to investigate the effect of

irrigation and foliar application of peptone on growth, flowering and chemical constituents of

Helichrysum bracteatum plants. Helichrysum seeds were supplied from Research and Production

Station, Nubaria. The soil is sand in texture with pH 8.0 , EC 0.92 dSm -1 (at 25 o C), organic carbon

0.89 %, and nutrients (N % 0.036, P% 0.012, K% 0.016 and Fe 265 ppm).seeds were sown on the 1 st

week of September, after 45 days from sowing uniform seedlings about 8 cm height with 2 pairs of

leaves were transplanted into the open field. The experiment was set up in a split plot design with three

replicates (each replicate contained 6 plants) containing three treatments of irrigation intervals (2, 4 and

6 days) occupied the main plots and three pepton concentrations (250, 500 and 1000 ppm) in addition

to the untreated plants (control) were assigned to the subplots. The seedlings were planted in row at 50

cm, distance. Drip irrigation system was applied in the experiment using drippers (4L/h) for two hours

every two days. The plants were fertilized with 4g ammonium nitrate (33% N), 2g potassium sulphate

(48 % K2O) and 4 g calcium super phosphate (15.5 % P2O5) / plant after 15 days from transplanting.

The grown plants received the normal cultural practices during the growth seasons.

Plants were sprayed with pepton (based on the energizing power of free amino acids, produced by

A.P.C. Europe Co. Avsan Julain-Spain). Plants were sprayed twice with pepton until run-off occurred;

the first spraying was in the second week of March. One month later the second spray was performed.

At the first week of May 2006/2007 and 2007/2008, the following data were recorded: plant height

(cm), number of branches /plant, leaf area (cm 2 ) fresh and dry weights of leaves (g), number of

flowers/ plant, flower diameter (cm) and fresh and dry weight of flower (g). total soluble sugars were

determined in the methanolic extract by using the phenol-sulphoric method according to Dubois et al

(1956), photosynthetic pigments including Chlorophyll (a+b) as well as carotenoids content were

determined in fresh leaves as mg/gm fresh weight, according to the procedure achieved by Saric et al

(1976). The total indoles were determined in the methanolic extract, using P-dimethyl

aminobenzaldhyed test " Erlic's reagent" according to Larsen et al (1962). Total soluble phenols were

determined calorimetrically by using Folin Ciocalte a reagent A.O.A.C. (1985). Free amino acid

content was determined according to Rosen (1957).

The data were statistically analyzed for each season and then a combined analysis of the two seasons

was carried out according to the procedure outlined by Steel and Torrie (1980).

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Growth parameters:

RESULTS AND DISCUSSION

Data presented in Table (1) indicated that significant increasing in all growth parameters by reducing

the interval between irrigations. The highest values of plant height, number of branches/ plant, leaf

area and fresh and dry weights of leaves were obtained at the plants irrigated every 2 days, while the

lowest values occurred by irrigation at the longest intervals (6 days). Moreover, the differences

between each two successive irrigation intervals were significant. Numerically, plant height and fresh

weights of leaves were increased by (29.7 and 49.21%) and by (19.58 and 24.40 %) as a results of 2

and 4 irrigation intervals (days), respectively, in comparison with the long interval (6 days). According

to the previous results, El-Monayeri et al (1983) reported that, this may be due to the vital roles of

water supply at adequate amount for different physiological processes such as photosynthesis,

respiration, transpiration, translocation, enzyme reaction and cells turgidity occurs simultaneously.

Such reduction could be attributed to decrease in the activity of meristemic tissues responsible for

elongation. As well as the inhibition photosynthesis efficiency under efficient water condition

Siddique (1999). These results are in agreement with those obtained by Burman et al (1991) on

Azadirachta indica, Soad (2005) on Simmondsia chinensis and Azza et (2006) on Melia azedarach.

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Table (1) Some growth parameters of Helichrysum bracteatum plants as affect with irrigation intervals and foliar application of pepton (average of two seasons).

Pepton

treatments

(ppm)

Plant height (cm) Number of branhes/plant Leaf area (cm2) Fresh weight of leaves (g) Dry weight of leaves (g)

Irrigation intervals days (A)

2 4 6 Mean 2 4 6 Mean 2 4 6 Mean 2 4 6 Mean 2 4 6 Mean

Control 48.07 43.13 37.83 43.01 20.67 17.33 14.00 17.33 5.26 4.99 3.75 4.67 17.63 14.51 11.87 14.67 3.52 2.9 2.37 2.93

P1 250 57.87 54.77 43.40 52.01 25.33 22.00 21.33 22.89 6.76 6.16 4.7 5.87 19.83 17.66 13.08 16.86 3.96 3.53 2.61 3.37

P2 500 62.83 58.87 47.50 56.40 29.00 24.33 23.00 25.44 7.65 6.58 5.29 6.50 24.04 18.83 15.00 19.29 4.81 3.76 3.00 3.86

P3 1000 68.7 62.10 54.30 61.70 33.33 26.33 26.33 28.66 7.72 6.70 6.18 6.87 25.82 21.80 18.59 22.07 5.16 4.36 3.71 4.41

Mean 59.37 54.72 45.76 27.08 22.50 21.17 6.85 6.11 4.98 21.83 18.20 14.64 4.36 3.64 2.93

LSD 5%

Irrigation

A

1.66

2.29 0.13 0.86

Pepton B 1.84 1.57 0.06 0.86 0.17

Interaction

AB

NS

NS 0.11 1.49

146

0.17

0.30


Concerning the effect of peptone on saga growth, data presented in Table (1) revealed that foliar

application of peptone significantly promoted plant height, number of branches/plant, leaf area and

fresh and dry weight of leaves. Increasing peptone concentration from 250 to 500 and 1000 pm to

Helichrysum bracteatum plants significantly increased all growth parameters over control plants. The

increments effect on plant height and number of branches/plant by (20.92, 13.13 and 43.00 %) and

32.1, 46.8 and 65.54%), respectively compared with control plants. The positive effect of amino acids

on yield may be due to the vital effect of these amino acids stimulation on the growth of plant cells.

The positive effect of amino acids on growth was stated by Goss (1973) who indicated that amino acids

can serve as a source of carbon and energy when carbohydrates become defficient in the plant, amino

acids are determinate, releasing the ammonia and organic acid form which the amino acid was

originally formed. The organic acids then enter the Kreb's cycle, to be broken down to release energy

through respiration. Thon et al (1981) pointed out that amino acids provide plant cells with an

immediately available source of nitrogen, which generally can be taken by the cells more rapidly than

in organic nitrogen. The results are characteristically accompanied by Youssef et al (2004) on lemon

basil, Gamal El-Din et al (1997) on lemon grass, Talaat Youssef (2002) on basil plant, El-Fawakhry

and El-Tayeb (2003) on chrysanthemum, Refaat and Naguib (1998) on peppermint plant, Youssef et al

(2004) on datura plant and Mona and Talaat (2005) on Pelargonium graveolens plant, the found that

amino acids significantly increased vegetative growth.

The interaction between different factors (irrigation and peptone ) was almost for all vegetative growth

parameters except plant height and number of branches/plant. The highest values due to the irrigation

regime and peptone were obtained due to irrigated every 2 days and concentration 1000 ppm of foliar

spray of pepeton. The lowest sensitivity of peptone –sufficient plants to drought stress is related to the

notion that some amino acids (e.g. phenylalanine, ornithine) can affect plant growth and development

through their influence on gibberelline biosynthesis Waller and Nawachi (1978). Amino acids acting

as the building blocks of proteins can serve in number of additional functions in regulation of

metabolism, transport and storage nitrogen Bidwell (1979) and Fowden (1973).

Flowering Characters:

Data presented in table (2) show that all decreasing irrigation intervals from 6 to 2 days significantly

increased flower diameter, number of flowers/plant and fresh and dry weights of flowers. The

increments on fresh and dry weights of flowers/plant by 26.93 and 31.02% respectively for the 2 days

compared with 6 days. Our results are computable with those obtained by Ruhi Bastug et al (2006) on

gladiolus plants, Kittas et al (2004) on Rose and Banker et al (2008) on wheat and stated that the high

level of irrigation lead to the increment of flowering parameters and quality.

Data presented in table (2) show that foliar spray of sage plants with pepton at 1000 ppm resulted in the

highest values flowering parameters. The maximum and values were observed for number of

flowers/plant and fresh and dry weights of flowers/plant by 38.45, 38.51 and 38.07 %, respectively

over control plants. These results are characteristically accompanied by Karima and Abd El-Wahed

(2005) who found that using amino acids led to significant increases in number of flowers, diameters of

flower and fresh and dry weights of flowers/plant of Matricaria chamomilla L. plant. Also, Nahed

and Balbaa (2007) on Saliva fFarincea stated that application of tyrosine 100 ppm significant

promotion in all flowering parameters at flowering stage.

Regarding the interaction effects, data in Table (2) show that flowering parameters were significantly

augmented. It is also clear from the obtained data that irrigation interval 2 days combined with foliar

spray of sage plants with 1000 ppm peptone resulted in the highest pronounced effects on all flowering

parameters.

Chemical Constituents:

Pigment content

Data in Table (3) recorded that, the content of three photosynthetic pigments (Chlorophyll a, b and

carotenoids) were increased by the gradual increasing in irrigation intervals. Accordingly it can be

stated that irrigation every 6 days was the most effective irrigation treatment for promoting the

synthesis and accumulation of the three photosynthetic pigments. In harmony with these results were

those obtained by Soad (2005) and Azza et al (2007).

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The three photosynthetic pigments took similar trend in response to peptone levels. The three

concentrations used of peptone 250, 500 and 1000 ppm caused an increase in the contents of

Chlorophyll a, b and carotenoids in regard to those of untreated seedlings. Hussein et al (1992) found

that higher concentration of adenine and cytosine increased the photosynthetic pigments of datura

plants.

148


Table (2) Flowering parameters of Helichrysum bracteatum plants as affect with irrigation intervals and foliar application of pepton (average of two seasons).

Pepton

treatments

(ppm)

Number of flowers/plant Flower diameter (cm) Fresh weight of flowers (g) Dry weight of flowers (g)

Irrigation intervals days (A)

2 4 6 Mean 2 4 6 Mean 2 4 6 Mean 2 4 6 Mean

Control 11.83 11.30 8.83 10.65 3.23 3.13 2.17 2.84 27.20 25.96 20.32 24.49 8.70 7.79 6.09 7.53

P1 250 15.63 14.23 11.13 13.66 3.32 3.48 2.75 3.18 35.96 32.74 25.61 31.44 11.50 9.82 7.68 9.67

P2 500 16.60 16.00 12.50 15.03 3.76 3.56 2.87 3.40 38.18 36.54 28.75 34.49 12.21 11.06 8.63 10.63

P3 1000 20.50 16.77 14.70 17.32 4.82 3.54 2.91 3.76 47.15 38.53 33.81 39.83 14.78 11.56 10.14 12.16

Mean 16.14 14.58 11.79 3.78 3.43 2.68 37.12 33.44 27.12 11.80 10.06 8.14

LSD 5%

Irrigation

A

0.97 0.05 2.39 0.82

Pepton B 0.51 0.04 1.12 0.39

Interaction

AB

0.89 0.08 1.94 0.67

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Table (3) Chemical constituents of Helichrysum bracteatum plants as affect with irrigation intervals and foliar application of pepton (average of two seasons).

Pepton

treatments

(ppm)

Chl a (mg/g F.W.) Chl b (mg/g F.W.) Chl a+b (mg/g F.W.) Carotenoids (mg/g F.W.)

Irrigation intervals days

2 4 6 Mean 2 4 6 Mean 2 4 6 Mean 2 4 6 Mean

Control 1.629 2.062 1.921 1.871 0.335 0.667 0.394 0.465 1.964 2.729 2.315 2.336 0.849 0.972 0.972 0.931

P1 250 1.782 2.126 2.372 2.093 0.455 0.935 0.583 0.658 2.237 2.581 2.955 2.591 1.079 1.186 1.027 1.097

P2 500 2.187 2.497 2.858 2.514 0.634 0.983 0.654 0.757 2.821 3.480 3.512 3.271 1.458 1.316 1.425 1.400

P3 1000 1.851 2.444 2.750 2.348 0.524 0.976 0.614 0.705 2.375 3.420 3.364 3.053 1.269 1.634 1.286 1.396

Mean 1.862 2.282 2.475 0.487 0.890 0.561 2.349 3.053 3.037 1.164 1.277 1.178

LSD 5%

Irrigation

A

0.036 0.018 0.054 0.110

Pepton B 0.031 0.010 0.041 0.010

Interactio

n AB

0.054 0.018 0.072 0.018

150


The present data are in agreement with the findings of Hussein (2003) on Foeniculum vulgare L. plants

and Nahed and Laila (2007) on Saliva farinacea plants, they reported that foliar application of amino

acids (Tryptophan) caused an increase in photosynthetic pigments contents. The accumulation of

photosynthetic pigments as a result of these nitrogen compounds may be due to the important role of

nitrogen in the biosynthesis of Chlorophyll molecules, Meyeret et al (1968).

In this respect, interaction between irrigation intervals and pepton applications, the data revealed that

the combination of both factors on Chlorophyll a, b and carotenoids was more effective than the effect

of each factors, all the interaction of used treatments increased significantly photosynthetic pigments in

the leaves of Helichrysum bracteatum plants.

Total soluble sugars content:

Data recorded in Table (4) indicated that total soluble sugars content as affected by different irrigation

intervals treatments, followed the same manner obtained previously on photosynthetic pigments, were

gradually decreased by increasing the intervals of irrigation. These results were in accordance with

those recorded by Azza et al (2007).

Pepton at all used concentration caused an increasing in total soluble sugars content as compared with

untreated seedlings. This result could be explained by the findings obtained by Refaat and Naguib

(1998) reported that application of all amino acids (alanine, cytosine, guanine, thiamine and L-tyrosine)

increased the total carbohydrates percentage in peppermint leaves. The promotive affected of the

amino acids on the total carbohydrates content may be due to their important role on the biosynthesis of

Chlorophyll molecules which in turn affected carbohydrate content.

As far the interaction between irrigation intervals and peptone applications the higher values were

provided when adding 1000 ppm peptone and irrigation every 4 days.

Total soluble indoles:

According to the data illustrated in Table (4) the total indoles levels which were determined in leaves

of Helichrysum bracteatum plants were increased by decreasing irrigation intervals.

Concerning pepton, total indoles levels were decreased by the increase in peptone levels. The highest

values of total indoles were obtained from interaction treated plants with peptone at 1000 ppm and

irrigated every 4 days.

151


Table (4) Chemical constituents of Helichrysum bracteatum plants as affect with irrigation intervals and foliar application of pepton (average of two seasons).

Pepton treatments

(ppm)

Total soluble sugars (mg/g F.W.) Total indoles (mg/g F.W.) Total phenoles (mg/g F.W.)

Irrigation intervals days

152

Total free amino acids (mg/g

F.W.)

2 4 6 Mean 2 4 6 Mean 2 4 6 Mean 2 4 6 Mean

Control 0.948 2.245 1.338 1.510 1.225 1.117 1.292 1.211 1.165 1.354 0.908 1.142 0.971 0.685 0.714 0.790

P1 250 1.659 3.143 1.511 2.104 0.816 0.718 0.635 0.723 1.216 1.659 1.510 1.462 1.132 0.835 0.742 0.903

P2 500 1.983 3.459 1.941 2.461 1.184 0.966 0.784 0.978 1.242 1.733 1.535 1.503 1.242 1.027 0.814 1.028

P3 1000 2.045 3.580 2.865 2.830 1.246 0.482 0.813 0.847 1.364 2.506 1.594 1.821 1.375 1.091 0.910 1.125

Mean 1.659 3.107 1.914 1.118 0.821 0.881 1.247 1.813 1.387 1.180 0.910 0.795

LSD 5%

Irrigation

A

0.018 0.009 0.008 0.007

Pepton B 0.013 0.008 0.010 0.008

Interaction

AB

0.022 0.014 0.018 0.013


Total soluble phenols:

The results in Table (4) emphasized that amounts of total soluble phenols were significantly increased

by increasing irrigation intervals. These results are in accordance with those obtained by Azza et al

(2006) on Taxodium distichum. Concerning peptone, total soluble phenols levels were increased by

increasing irrigation intervals and peptone concentration the highest values were provided when adding

1000 ppm and interval 4 days.

Total free amino acids:

From the given data in Table (4) it can be concluded that decreasing irrigation intervals caused an

increase of total free amino acids content. In regard to the effect of water stress on amino acids, it has

been indicated that generally total free amino acids increased under water stress, Simpson (1981). This

trend does not apply to Myoporum since long irrigation interval caused a decrease in amino acids.

However, many investigators reported that an increase in amino acids is associated with water stress,

Farahat (1990) on Schinus molle, Schinus terebinthifolius and Myoporum acuminatum). Data

presented in table (4) show that total free amino was significantly increased as a result of foliar spray of

peptone 500 and 1000 ppm. Our results are in agreement with those obtained by Karima and Abdel-

Wahed (2005) on Chamomile plants, Gamal ElDin et al (1997) on lemon grass, Mona and Iman (2005)

on Pelargonium graveolens L. and Nahed and Balbaa (2007) on Saliva fariacea plants. They reported

that application of amino acids significantly increased total amino acids.

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Ozean Journal of Applied Sciences 3(1), 2010

Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Permeability and Porosity Prediction from Wireline logs Using Neuro-Fuzzy Technique

Wafaa El-Shahat Afify* and Alaa H. Ibrahim Hassan**

*Lecturer of Applied Geophysics, Faculty of Science, Benha University

** Senior Reservoir Geologist (Bab Team)

Abu Dhabi Company for Onshore Oil Operations

*E-mail address for correspondence: w_afify@yahoo.com

____________________________________________________________________________________

Abstract: Petroleum reservoir characterization is a process for quantitatively describing various

reservoir properties in spatial variability using all the available field data. Porosity and permeability are the

two fundamental reservoir properties which relate to the amount of fluid contained in a reservoir and its

ability to flow. These properties have a significant impact on petroleum fields operations and reservoir

management. In un-cored intervals and well of heterogeneous formation, porosity and permeability

estimation from conventional well logs has a difficult and complex problem to solve by statistical methods.

This paper suggests an intelligent technique using fuzzy logic and neural network to determine reservoir

properties from well logs. Fuzzy curve analysis based on fuzzy logic is used for selecting the best related

well logs with core porosity and permeability data. Neural network is used as a nonlinear regression

method to develop transformation between the selected well logs and core measurements. The technique is

demonstrated with an application to the well data in West July oil field, Gulf of Suez, Egypt for the

Miocene Upper Rudeis reservoirs (Asal and Hawara formations). The results show that the technique can

make more accurate and reliable reservoir properties estimation compared with conventional computing

methods. This intelligent technique can be utilized as a powerful tool for reservoir properties estimation

from well logs in oil and natural gas development projects.

____________________________________________________________________________________

INTRODUCTION

Reservoir characterization is a process of describing various reservoir characteristics using all the

available data to provide reliable reservoir models for accurate reservoir performance prediction. The

reservoir characteristics include permeability, porosity, pore and grain size distributions, facies distribution,

and depositional environment. The types of data needed for describing the characteristics are core data,

well logs, well tests, production data and seismic survey. Such information is essential to the determination

of the economic viability of a particular well or reservoir to be explored. A large number of techniques

have been introduced in order to establish an adequate interpretation model over the past fifty years.

Nevertheless, conventional derivation of a well log data analysis model normally falls into one of the two

main approaches: empirical and statistical. In the empirical approach, mathematical functions relating the

desired permeability based on several well log data inspired by theoretical concepts are used [Wyllie and

Rose, 1950, Kapadia and Menzie, 1985]. This approach has long been favored in the field and much effort

has been made to understand the underlying petroleum engineering principles. However, the unique

geophysical characteristic of each region prevents a single formula from being universally applicable.

Statistical techniques are viewed as more practical approaches [Wendt et al., 1986, and Hawkins, 1994].

The common statistical technique used is multiple regression analysis. The simplest form of regression

analysis is to find a relationship between the input logs and the petrophysical properties. The derived

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regression equations are then used for well log analysis. However, a number of initial assumptions of the

model need to be made. Assumptions must also be made as to the statistical characteristics of the log data.

Over the past decade, another technique that has emerged as an option for well log analysis is the Artificial

Neural Network (ANN). Research has shown that an ANN can provide an alternative approach to well log

analysis with improvement over the traditional methods [Osborne, 1992, Wong et al., 1995, Fung and

Wong, 1999]. Most of the ANN based well log analysis models have used the Multi-layer Neural Network

(MLNN) utilizing the backpropagation learning algorithm. Such networks are commonly known as

Backpropagation Neural Networks (BPNNs). A BPNN is suited to this application, as it resembles the

characteristics of regression analysis in statistical approaches. Fuzzy Logic (FL) that is capable to express

the underlying characteristics of a system in human understandable rules is also used. A fuzzy set allows

for the degree of membership of an item in a set to be any real number between 0 and 1. This allows human

observations, expressions and expertise to be modeled more closely. Once the fuzzy sets have been defined,

it is possible to use them in constructing rules for fuzzy expert systems and in performing fuzzy inference.

This approach seems to be suitable to well log analysis as it allows the incorporation of intelligent and

human knowledge to deal with each individual case. However, the extraction of fuzzy rules from the data

can be difficult for analysts with little experience. This could be a major drawback for use in well log

analysis. If a fuzzy rule extraction technique is made available, then fuzzy systems can still be used for well

log analysis [Wong et al., 1999 and Kuo et al., 1999]. With the emergence of intelligent techniques that

combine ANN and fuzzy together have been applied successfully in well log analysis [Huang et al., 2001,

Kadkhodaie Ilkhchi et al., 2008, Khaxar et al., 2007, Johanyák et al.2007]. These techniques used in

building the well log analysis model normally address the disadvantages encountered in ANN and fuzzy

system. This paper suggests an intelligent technique for reservoir characterization using fuzzy logic and

neural network to determine reservoir properties from well log data for the Miocene Upper Rudeis

reservoirs (Asal and Hawara formations), in West July oil field, Gulf of Suez, Egypt, Fig.1.

Back propagation neural networks (BPNN).

A neural network (NN) is an intelligent tool for solving complex problems. A BPNN is a supervised

training technique that sends the input values forward through the network then computes the difference

between calculated output and corresponding desired output from the training dataset. The error is then

propagated backward through the net and the weights are adjusted during a number of iterations, named

epochs. The training ceases when the calculated output values best approximate the desired values [Bhatt

and Helle, 2002].A flowchart of training procedure in a supervised NN is shown in Fig. 2.

Fuzzy logic (FL).

The basic theory of fuzzy sets was first introduced by Zadeh, 1965. In recent years, it has been shown that

uncertainty may be due to fuzziness (possibility) rather than probability. FL is considered to be appropriate

to deal with the nature of uncertainty in system and human errors, which were not considered in existing

reliability theories. Generally, geological data are not clear-cut and habitually are associated with

uncertainties. For example, prediction of core parameters from well log responses is difficult and is usually

associated with error [Nikravesh and Aminzadeh, 2003].FL derives useful information from this error and

applies it as a powerful parameter for increasing the accuracy of the predictions. A fuzzy inference system

(FIS) is a method to formulate inputs to an output using FL [Kadkhodaie Ilkhchi et al., 2006].

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Fig.2. A flow chart of training procedure in a supervised

neural network.

Fuzzy modeling technique can be classified into three categories, namely the linguistic (Mamdani-type), the

relational equation, and the Takagi, Sugeno and Kang (TSK). Takagi and Sugeno, 1985, is a FIS in which

output membership functions are constant or linear and are extracted by a clustering process. Each of these

clusters refers to a membership function. Each membership function generates a set of fuzzy if–then rules

for formulating inputs to outputs. A schematic diagram of FIS is shown in Fig.3.

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Neuro-fuzzy (NF) model.

Ozean Journal of Applied Sciences 3(1), 2010

Hybrid NF systems combine the advantages of fuzzy systems (which deal with explicit knowledge) with

those of NN (which deal with implicit knowledge). On the other hand, Fuzzy Logic (FL) enhances

generalization capability of a Neural Network (NN) system by providing more reliable output when

extrapolation is needed beyond the limits of the training data. A schematic diagram of information flows in

a NF system is shown in Fig.4. The architecture of the Neuro-Fuzzy classifier is slightly different from the

architecture used in function approximations [Tommi, 1994]. The two first layers have the identical

function with the approximation. Fig. 5 shows a system using the following fuzzy rules,

Rule 1: If x1 is A1 and x2 is B1, then class is 1.

Rule 2: If x1 is A2 and x2 is B2, then class is 2.

Rule 3: If x1 is A1 and x2 is B3, then class is 1.

Layer 3. Combination of firing strengths: If several fuzzy rules have the same consequence class, this layer

combines their firing strengths. Usually, the maximum connective (or operation) is used.

Layer 4. Fuzzy outputs: In this layer, the fuzzy values of the classes are available. The values describe how

well the input of the system matches to the classes.

Layer 5. Defuzzification: If the crisp classification is needed, the best-matching class for the input is chosen

as output class.

METHODS AND RESULTS

The data used for permeability and porosity determination are the open-hole wireline subsurface well log

data [gamma ray (GR), sonic (DT), density (ROHB), deep resistivity (RD), Neutron (PHIN) logs, water

saturation (SW)], and core data [core permeability and core porosity]. The work in the present research

proceeds as following;

• Removing erroneous and outliers from the raw well log data.

• Organizing data into input data sets including GR, DT, ROHB, RD, PHIN, SW and

output data sets including core permeability and core porosity.

• Normalization of input and output data sets (between the ranges 0-1) to renders the data

dimensionless and removes the effect of scaling.

• Dividing the data into: training, checking and testing data sets.

• Clustering the input and output data sets using fuzzy c-means (FCM), fuzzy k-means

(FKM) or subtractive clustering methods.

• Fuzzyfication, which involves the conversion of numeric data in real world domain to

fuzzy numbers in fuzzy domain, this takes place by building the fuzzy inference system

FIS, which involves setting the membership functions and establishment of fuzzy rules.

• Deffuzzification, which is optional, involves the conversion of the derived fuzzy

number to the numeric data in real world domain.

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Fig.3. Schematic diagram of FIS

Fig.4. Schematic diagram of information flow in a NF system

Fig.5. Neural architecture of the NF classifier.

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•Organizing data. The data for the neuro-fuzzy model come from one well SG-3105A at West July oil

field, Gulf of Suez, Egypt. The selection of this well is based on geological considerations; it contains

reasonably good core coverage of the Upper Rudeis Formation. Core-log calibration was carefully carried

out to compensate for differences in depth. Table (1), illustrates the statistics of the input and output data

sets used in NF modeling.

•Normalizing data. When processing the actual materials, due to the different dimensions of the source

rocks evaluation parameter, the volume level of actual data vary considerably. If we calculate by using the

raw data directly, the indicating role of the data which has a larger volume would become more

outstanding. While the indicator with a lower volume and a higher sensitivity will be underestimated. Thus,

we should preprocess and normalize the raw data. In this work normalizing data takes place by using the

maximum and minimum values of the data.

•Fuzzy clustering. It is necessary to classify the input and output datasets into groups using clustering

methods. In this study, a subtractive clustering method, which is a useful and effective way to FL modeling,

is used for extraction of clusters and fuzzy if–then rules. The details of subtractive clustering could be

found in Chiu [1994], Chen and Wang [1999], Jarrah and Halawani [2001].The important parameter in

subtractive clustering which controls number of clusters and fuzzy if–then rules is clustering radius. This

parameter could take values between the range of [0, 1]. Specifying a smaller cluster (say 0.1) radius will

usually yield more and smaller clusters in the data resulting in more rules. In contrast, a large cluster radius

(say 0.9) yields a few large clusters in the data resulting in few rules.

The effectiveness of a fuzzy model is related to the search for an optimal clustering radius, which is a

controlling parameter for determining the number of fuzzy if–then rules. Few rules could not cover the

entire domains, and more rules will complicate the system behavior and may lead to low performance of

the model. Regarding the permeability model, four centers result from clustering, thus the fuzzy model was

established by four fuzzy if-then rules and four membership functions for input and output data. Porosity

model, on the other hand, contains five centers (clusters), five rules and five membership functions. Figures

6 and 7 shows the subtractive clusters of permeability and porosity data.

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•Building the fuzzy inference system FIS. Fuzzy inference is the process of formulating the mapping from

a given input to an output using fuzzy logic. The mapping then provides a basis from which decisions can

be made, or patterns discerned. The process of fuzzy inference involves setting the membership functions

and establishment of fuzzy rules, [Matlab fuzzy logic user’s guide, and 2009].

1- Setting the Membership Functions (MF). A membership function (MF) is a curve that defines how each

point in the input space is mapped to a membership value (or degree of membership) between 0 and 1. The

input space is sometimes referred to as the universe of discourse, a fancy name for a simple concept. The

only condition a membership function must really satisfy is that it must vary between 0 and 1. The function

itself can be an arbitrary curve whose shape we can define as a function that suits us from the point of view

of simplicity, convenience, speed, and efficiency. There are many types of membership functions built

from several basic functions:

• Piece-wise linear functions

• The Gaussian distribution function

• The sigmoid curve

• Quadratic and cubic polynomial curves

In this study, a Gaussian distribution membership function is used to define the extracted input clusters. A

Gaussian function f (x) shows the normal distribution of data (x):

e

f ( X ) �


�(

x��

)

2 /


2�

2

Where µ and σ are the parameters of normal distribution showing the mean and standard deviation of data,

respectively. These Gaussian membership functions are constructed from mean and σ values of the clusters.

The mean represents the cluster centers and σ is derived from:

σ = (radii � (maximum data – minimum data))/sqrt. The input parameters of Gaussian membership

function for permeability and porosity are shown in tables 2A and 3A.

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In the FIS, output membership functions are linear equations constructed from inputs. For example, output

membership function number one (MF1), which is the consequent of rule no. 1, is constructed from six

petrophysical inputs as following:

Output MF1 = C1 � GR � C2

� DT � C3

� ROHB � C4

� RD � C5

� PHIN � C6

� SW � C7

In this equation, parameters C 1 , C2,

C3,

C4,

C5

and C 6 are coefficients corresponding to GR, DT,

ROHB, RD, PHIN and SW inputs, respectively. Parameter C 7 is constant in each equation. These

parameters are obtained by linear least-squares estimation. With these explanations there will be seven

parameters for each output membership function, which are shown in tables 2B and 3B for permeability

and porosity, respectively. Figures 8 and 9 represent the FIS generated Gaussian membership

functions of input data for permeability and porosity model, respectively.

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Moreover, Figure 10 A shows the FIS model generated for permeability and porosity, (Fig.10B).

2- Establishment of fuzzy rules. Fuzzy rule statements are used to formulate the conditional statements that

comprise fuzzy logic. A single fuzzy if-then rule assumes the form if x is A then y is B where A and B are

linguistic values defined by fuzzy sets on the ranges (universes of discourse) X and Y, respectively. The ifpart

of the rule “x is A” is called the antecedent or premise, while the then-part of the rule “y is B” is called

the consequent or conclusion.

The generated fuzzy if-then rules for formulating input petrophysical data to permeability are:

1. If (GR is in1mf1) and (DT is in2mf1) and (ROHB is in3mf1) and (RD is in4mf1) and (PHIN is in5mf1)

and (SW is in6mf1) then (K is out1mf1).

2. If (GR is in1mf2) and (DT is in2mf2) and (ROHB is in3mf2) and (RD is in4mf2) and (PHIN is in5mf2)

and (SW is in6mf2) then (K is out1mf2).

3. If (GR is in1mf3) and (DT is in2mf3) and (ROHB is in3mf3) and (RD is in4mf3) and (PHIN is in5mf3)

and (SW is in6mf3) then (K is out1mf3).

4. If (GR is in1mf4) and (DT is in2mf4) and (ROHB is in3mf4) and (RD is in4mf4) and (PHIN is in5mf4)

and (SW is in6mf4) then (K is out1mf4).

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The generated fuzzy if-then rules for formulating input petrophysical data to porosity are:

1. If (GR is in1mf1) and (DT is in2mf1) and (ROHB is in3mf1) and (RD is in4mf1) and (PHIN is in5mf1)

and (SW is in6mf1) then (PHI is out1mf1).

2. If (GR is in1mf2) and (DT is in2mf2) and (ROHB is in3mf2) and (RD is in4mf2) and (PHIN is in5mf2)

and (SW is in6mf2) then (PHI is out1mf2).

3. If (GR is in1mf3) and (DT is in2mf3) and (ROHB is in3mf3) and (RD is

in4mf3) and (PHIN is in5mf3) and (SW is in6mf3) then (PHI is out1mf3).

4. If (GR is in1mf4) and (DT is in2mf4) and (ROHB is in3mf4) and (RD is in4mf4) and (PHIN is in5mf4)

and (SW is in6mf4) then (PHI is out1mf4).

5. If (GR is in1mf5) and (DT is in2mf5) and (ROHB is in3mf5) and (RD is in4mf5) and (PHIN is in5mf5)

and (SW is in6mf5) then (PHI is out1mf5).

A graphical illustration showing steps to formulation of petrophysical data inputs to permeability using four

fuzzy if–then rules generated by FIS, is represented in Fig.11. The formulation of petrophysical data to

porosity using five fuzzy if-then rules generated by FIS are shown in Fig. 12. Each figure displays a

roadmap of the whole fuzzy inference process. The seven plots across the top of the figure represent the

antecedent and consequent of the first rule. Each rule is a row of plots, and each column is a variable. The

rule numbers are displayed on the left of each row.

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The structure of the NF model is now generated for permeability (Fig.13A) and porosity (Fig.13B). The

input is represented by the left-most node and the output by the right-most node. The node represents a

normalization factor for the rules.

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DISCUSSION

The NF technique is used to determine the porosity and permeability of the Upper Rudeis Formation using

the available well data, as well as core permeability and core porosity data, (Fig. 14). The Upper Rudeis

sand is the third most important reservoir in July oil field. The sand was supplied by fans draining the Red

Sea hills to the west of July field and deposited in a similar environment to the Lower Rudeis Formation,

Pivnik et al., (2003).

A total of 108 data points are used for training, 108 data points are used for checking and 60 data points are

used for testing the NF models of the permeability and porosity. The FIS is trained using the training data

set then checked and tested using checking data sets and testing data sets respectively. The testing data set

is used to check the generalization capability of the resulting fuzzy inference system. The idea behind using

a checking data set for model validation is that after a certain point in the training, the model begins over

fitting the training data set. In principle, the model error for the checking data set tends to decrease as the

training takes place up to the point that over fitting begins, and then the model error for the checking data

suddenly increases. Over fitting is accounted for by testing the FIS trained on the training data against the

checking data. Usually, these training and checking data sets are collected based on observations of the

target system and are then stored in separate files.

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Figure 15 shows the checking and the FIS output. On the other hand, Fig.16. shows testing data and FIS

output. The performance of the model is evaluated by the MSE of the data sets, as illustrated in Fig.17. and

table (4). The correlation coefficient between the measured and NF predicted K and PHI are 0.825 and

0.957, respectively. A comparison between measured and NF predicted K and PHI versus depth is shown in

Figs. 18 and 19.

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CONCLUSIONS

In this study, the NF intelligent technique is used to estimate reservoir porosity and permeability from

conventional well logs. Fuzzy curve analysis based on fuzzy logic can be used for selecting the

best related parameters with reservoir properties. The NF modeling approach presented in this paper has

been successfully applied for the prediction of petrophysical reservoir parameters. This modeling approach

has the significant advantage in that it does not require any previous assumption based on physical or

experimental considerations about the reservoir complexities to construct a reasonable and accurate model

from a set of measured data. Excellent correlation coefficients have been obtained for porosity 0.957, and

permeability 0.825, using NF models. The techniques can make more accurate and reliable reservoir

properties estimation and can be utilized a powerful tool for reservoir properties determination from well

logs in petroleum industry, and is applicable in different wells and oil fields.

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ACKNOWLEDGEMENTS

The authors would like to express their gratitude for the Gulf Of Suez Petroleum Company, (GUPCO),

Egypt for supplying the data needed for this work.

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Figure 1 - Location map of July Oil Field.

Ozean Journal of Applied Sciences 3(1), 2010

FIGURES CAPTION

Figure 2 - A flow chart of training procedure in a supervised neural network.

Figure 3 - Schematic diagram of FIS.

Figure 4 - Schematic diagram of information flow in a NF system.

Figure 5 - Neural architecture of the NF classifier.

Figure 6 - Subtractive clustering of permeability fuzzy model.

Figure 7 - Subtractive clustering of porosity fuzzy model.

Figure 8 - Generated Gaussian membership functions for permeability model input data.

Figure 9 - Generated Gaussian membership functions for porosity model input data.

Figure 10 - Diagrams showing formulation of input petrophysical data to: (A)

permeability, K and (B) porosity, PHI using fuzzy modeling.

Figure 11 – Rule viewer of FIS permeability model.

Figure 12 - Rule viewer of FIS porosity model.

Figure 13 - Structure of Neuro-Fuzzy model for permeability (A) and porosity (B).

Figure 14 - Petrophysical and core data of SG-310-5A well.

Figure 15 - Showing checking data and FIS output, permeability (A) and porosity (B).

Figure 16 - Showing testing data and FIS output, permeability (A) and porosity (B).

Figure 17 - Mean square error (MSE) obtained during training the permeability

model (A) and the porosity model (B).

Figure 18 - Predicted and core permeability.

Figure 19 - Predicted and core porosity.

TABLES CAPTION

Table1 - Statistics of input and output data sets.

Table 2 - Showing input (a) and output (b) membership functions parameters derived by

FIS for permeability.

Table 3 - Showing input (a) and output (b) membership functions parameters derived by

FIS for porosity.

Table 4 - MSE of the different datasets.

175


Ozean Journal of Applied Sciences 3(1), 2010

Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

Response of vegetative growth and chemical constituents of Schefflera

arboricola L. plant to foliar application of inorganic fertilizer (grow-more)

and ammonium nitrate at Nubaria.

Mona, H. Mahgoub *, El-Quesni, Fatma E.M., and Magda,M. Kandil

Department of Ornamental plant and Woody trees,

National Research Centre, Dokki, Cairo, Egypt

*E-mail address for correspondence: azza856@yahoo.com

________________________________________________________________________________

Abstract: A pot experiment was carried out during 2007 and 2008 seasons at Research and Production

Station, Nubaria of National Research Centre, Dokki, Cairo, Egypt to study the response of Schefflera

plants to foliar fertilizer (Grow-more at the rates of 0.0, 1.0 cm 3 /L and 2.0 cm 3 /L) and ammonium

nitrate at the rate of (0, 100 and 200 kg) and their interaction on vegetative growth expressed as plant

height, stem diameter, number of leaves, leaf area, fresh and dry weight of (leaves, roots and stem) and

chemical composition significantly affected by application of the two factors which were used in this

study.Grow-more and nitrogen fertilizer promoted all morphological characters, photosynthetic

pigments, protein %, nitrogen, phosphorus and potassium.,

Keywords: Schefflera arboricola,Grow-more,ammonium nitrate

__________________________________________________________________________________

INTRODUCTION

Schefflera arboricola L. is flowering plant in the family araliaceae, native to Tiwan and Hainan. It is

also goes by the common name "Dwarf umbrella tree". It is an evergreen shrub growing to 3-4 m

height, often trailing stems scrambing over other vegetation. The leaves are palmately compound, with

7-9 leaflets, the leaflets 9-20 cm long and 4-10 cm broad (though often smaller in cultivation). The

flowers are produced in a 20 cm pancil of small umbels, each umbel 7-10 mm diameter with 5-10

flowers.

It is commonly grown as houseplant, popular for its tolerance of neglect and poor growing condition.

Numerous cultivars have been selected for variation in leaf colour and pattern, often variegated with

creamy-white to yellow edges or centers, and dwarf forms. Scheffleras are delicate tropical plants

often used to decorate public places, such as lobbies, shopping malls and waiting rooms. Smaller

Scheffleras are better studied for homes and small offices. Uphof(1959). Inorganic fertilizers are the

elements needed in small amounts, they are often refers to as micronutrients (Kohnke 1995) these

elements are chlorine (Cl), Iron (Fe), Manganese (Mg), Boron (B), Copper (Cu), Zinc (Zn),

Molybdenum (Mo), Nickel (Ni) and Cobalt (Co) most of these elements are derived from the soil and

organic sources (Brady and Weil 2000). Micronutrients are also essential for organization and rapid

alternation of nutrition compound within plant owing to their great importance in contribution to direct

the enzymes way in metabolism Massoud et al (2005). Therefore, both granular and fluid (liquid) NPK

fertilizers are commonly used as carriers of micronutrients including micronutrients with mixed

fertilizer which is a convenient method of application and allows more uniform distribution with

conventional application equipment. Micronutrients are essential for plant growth, but are required in

much smaller amounts than those of the primary nutrients Brady and Weil (2000).

Nitrate and ammonium are the major source of inorganic nitrogen taken up by the roots of higher

plants. Most of ammonium has to be incorporated into organic compounds in the roots whereas nitrate

177


Ozean Journal of Applied Sciences 3(1), 2010

is readily mobile in the xylem and can also be stored in the vacules of roots, shoots and storage organs.

Nitrate accumulation can be considerable importance for cation-anion balance, for osmoregulation,

particularly in so-called nitrophilie species such as Chenopodium album and Urtica dioica (Smirnoff

and Stewart, 1985). Dahiya et al (2001) mentioned that further increments in nitrogen level, up to 180

ppm, adversely affected growth and dry matter yield of tuberose. While Pal and Biswas (2000) found

that the lower doses of fertilizer produced poor quality plant and yield of flower and best results were

found when tuberose were fertilized N, P and K at the level of 15, 15, 20 g/m 2 , respectively. Also

Paradhan et al (2004) noticed that combined application of N at 40 g/m 2 and K at 30 g/m 2 gave the

highest values of plant height, number of leaves /plant, leaf area, spike length and number of

flowers/spike. Mahgoub et al (2006) studied the effect of the nitrogen levels 30, 40, 50 and 60 g/m 2 as

ammonium nitrate (33.5 % N) and the level of 25, 30, 35 and 40 g/m 2 as potassium sulfate (48 % K2O).

They found that Iris bulbs showed higher values for plant height, fresh and dry weight of leaves (40 g

N + 30 g K /m 2 ) N level up to 60 g/m 2 showed stimulatory effect on chlorophyll a, b and carotenoids,

60 g N/m 2 increased carbohydrate percentage in the presence of 30 g /m 2 K, (40 g N/m 2 + 25 g K /m 2 )

recorded high values of N, P and K in Iris leaves.

The aim of this work is to study the response of Schefflera arboricola plants to foliar fertilizer of

Grow-more and nitrogen fertilizer and their interactions on growth and some chemical composition.

MATERIALS AND METHODS

The experiments was conducted at Research and Production Station of National Research Centre at

Nubaria during two successive seasons 2007 and 2008 to investigate the response of Schefflera

arboricola plant to foliar fertilizer micro nutrients and nitrogen fertilizer (ammonium nitrate 33.5 %)

on growth and some chemical composition. On the third week of February 2007 and 2008 seasons,

vegetative uniform cutting (20-24 cm length) were taken from Schefflera arboricola plant, cutting

were treated for a minute with 1000 mg/L indole butric acid before planting in pots to enhance rooting.

Rooted cuttings were planted in black plastic pots (10 cm) in diameter (one plant /pot) and grown in

shaded green house media formulated by combination of peatmoss and sandy soil (1:1, v/v). The

seedling were transplanted on 20 th April 2007 and 2008 seasons, in plastic pot (30 cm) in diameter

filled with 10 kg of peatmoss and sandy soil (1:1, v/v) arranged in a complete randomized design with

three replicates. Each replicate consists of three plants. Water requirements were relative humidity

maintained between 45-65%, allow the surface of potting media to dry slightly before irrigation. Each

pot was fertilized twice with 1.5 g nitrogen as ammonium nitrate (33.5% N) and 1.0 g potassium

sulphate (48.5 % K2O). The fertilizers were applied at 30 and 60 days after transplanting. Phosphorus

as calcium superphosphate (15.5 % P2O5) was mixed with soil before transplanting at a rate of 3.0 g/

pot. Other agricultural processes were performed according to normal practice. Plants were sprayed

with different concentration of foliar fertilizer (Gropw-more) Table (1) which produced by Ajemco

International company at the rate of (0.0, 1.0 and 2.0 cm 3 /L). Nitrogen as ammonium nitrate was

fertilized with (0, 100 and 200 kg), interaction of the two factors had been also carried out, in addition

to untreated plants (control) which were sprayed with tap water. Foliar application of Grow-more and

nitrogen was carried out two times of 30 days intervals starting at 20 July at both seasons. The

experiments were sat in completely Randomized Design (CRD) with three replicates and two factors.

The following data were recorded on 1 st week of December 2007 and 2008 season, the recorded data

were plant height (cm), stem diameter (mm), No. of leaves, leaf area (cm 2 ) of 4 and 5 base leaves, fresh

and dry weight of plant organs (gm). Photosynthetic pigments i.e. chlorophyll (a, b and carotenoids)

were determined exactly 0.1 gm of fresh leaves of schefflera plant using the Spectrophotometric

method developments by Metzzner et al (1965). Total nitrogen was determined by Chapman and Pratt

(1961), while phosphorus determination carried out Colorimtrically according to King (1951). Potassium

was determined photometrically by flam photometer method as described by Brown and Lillan (1946).

Data obtained were subjected to standard analysis of variance procedure, the values of LSD were

obtained whenever F value were significantly as 5% levels reported by Snedecor and Cochran (1980).

178


Growth characters:

Ozean Journal of Applied Sciences 3(1), 2010

RESULTS AND DISCUSSION

Data in Table (2) show that foliar application of Grow-more at the concentration of 1.0 and 2.0 cm 3 /L

on schefflera plants significantly increased all growth parameters plant height (cm), No. of leaves, fresh

and dry weight of plant organs (gm), root and stem (gm), stem diameter and leaf area (cm 2 ) than the

untreated plants, the highest values of previous characters were found when plants treated with 2.0

cm3/L of grow-more followed by 1.0 cm 3 /L. These results are agreement with El-Fouly (2001) who

noticed that the number of leaves and leaf area of sunflower plants were increased by addition of Fe,

Mn, Zn, root size was increased by addition of Fe and Mn only. Rabie et al (2002) reported that foliar

fertilizer containing N, P, K, Fe, Mn and Zn pronounced increases in dry weight, macro and

micronutrients content of sorghum plants than control plants. Negm and Zahran (2001) found that,

foliar application of micronutrients had the significant effect on increasing wheat grain and straw

yields; yield attributes (plant height, spike length and 1000 grains weight). El -Quesni et al (2009)

mentioned that using inorganic fertilizers at the concentrations of 1.0 and 2.0 cm 3 /L on syngonium

plants increased plant height, stem diameter, No. of leaves/plant, leaf area and fresh and dry weight of

roots and leaves. These results may be due to micronutrient boron which helps transport vital sugars

through plant membranes and promotes proper cell division, cell wall formation and development, also

due to zinc which promotes seed/grain formation, plant maturity, acts as enzyme activator in protein,

hormone (i.e. IAA) and RNA / DNA synthesis and metabolism. Chlorine also indirectly affects plant

growth by stomatal regulation of water loss. Molybdenum has a significant effect on pollen formation,

so fruit and grain formation are affected by molybdenum –deficient plants.

With regard to the effect of nitrogen fertilizer on schefflera plants data in Table (2) illustrated that

using nitrogen fertilizer at the rate of 100 kg gave significant increases than control plants. 200 kg

nitrogen gave the highest values in all growth parameters under study compared with control plants.

These results are in agreement with Ramesh et al (2002) they mentioned that plant height increased

with increasing the rate of nitrogen. In this respect, Paradahan et al (2004) on gladiolus c.v. red

mention that 4 g/m2 N plus K fertilizer at the rate of 30 g/m2 recorded highest value of number, fresh

and dry weight of leaves as plant height . As regarding the interaction treatments, foliar application

micronutrients and nitrogen fertilizer, the data show that significantly increased all growth characters

under study. The highest values of growth characters were obtained by grow-more 2.0 cm 3 /L

combined with ammonium nitrate at the rate of 200 kg /fed followed by grow-more 2.0 cm3/L and N at

the rate of 200 kg/fed.

Data emphasized the interaction effect were significantly affected all growth parameters i.e. plant

height (cm), number of leaves, fresh and dry weight of (leaves, root and stem) stem diameter and leaf

area of schefflera arboricola L. plants. These results may be due to increasing the nitrogen levels

which delays senescence and stimulates growth and also changes plant morphology, particularly if the

nitrogen availably is high in the rooting medium during the early growth (Levin et al, 1989; Olsthoorn

et al 1991), it presumably related to nitrogen induced changes in the phytohormone balance (Sommer

and Six 1982).

Chemical constituents:

Synthetic Pigments:

Data in Table (3) indicated that spraying schefflera plants with grow-more at the rate of 1.0 cm3/L

increasing significantly in chl. a, b and total chlorophyll and decreased in total carotenoids content

whereas 2.0 cm3/L gave the highest values in the content of plants from Chl. a, Chl. b, total

Chlorophyll and total carotenoids content. These results were agreement with those obtained by

Ratanarat et al (1990), El-Quesni et al (2009) they found that the highest values of Chl. a, Chl. b and

total carotenoids in syngonium plants increases by increasing the concentration of grow-more up to 2.0

cm3/L. These results may be due to iron, manganese, which promote chlorophyll production and

photosynthesis process, copper which helps in chlorophyll formation. With regard to the effect of

nitrogen fertilizer on schefflera plants data in Table (3) showed that the two used concentration of N

fertilizer increasing Chl. a, b and total Chlorophyll whereas total carotenoids content gave significant

increased by using 200 kg N only. These results are agreement with Mahgoub et al (2006) on Iris

179


Ozean Journal of Applied Sciences 3(1), 2010

bulbs they mentioned that maximizing the rate of N up to 60 g/m2 showed the stimulatory effect on

chlorophyll a, b and carotenoids irrespective of the K fertilizer level.

Concerning the effect of interaction on photosynthetic pigments data show that the highest significant

values was found in plant treated with 2.0 cm2/L grow-more fertilizer plus 200 kg nitrogen fertilizer

followed by 2.0 cm3/L micronutrients and 100 N , respectively. These treatments may be due to

positive effect on growth parameters.

Mineral Ions content:

Data in Table (3) found that foliar application of grow-more at the concentration of 1.0 and 2.0 cm 3 /L

and nitrogen fertilizer at the rate of 100 and 200 kg increased the total amount of nitrogen, phosphorus

and potassium ions content on schefflera plants compared with control plants. These results were

agreement with those obtained by Sharma et al (2002) they found that application of organic material

either alone or in combination with chemical fertilizers caused substantial increase in total N, available

P, K as well as increased wheat and straw yield Mahgoub et al(2006) on Iris bulbs they found that

using 40 g/m2 N plus 25 g/m 2 K recorded high values of N, P and K in Iris leaves. With regard the

effect of interaction in mineral ions content data show that significantly increased N, P and K content

of schefflera plants were obtained by grow-more 2 cm 3 /L combined with 200 kg N followed by grow

more 2 cm 3 /L.

Data in Table (3) mentioned that total protein percentage increased by (6.46 and 10.53) when plants

treated with 1.0 and 2.0 cm 2 /L grow-more respectively compared with control plants which recorded

(8.68 %). Also nitrogen fertilizer 100 and 200 kg treatments in the total protein increased by (9.68 and

10.09 %) respectively than control plants (8.90 %).

The highest recorded data in total protein percentage were (11.21, 10.69 and 10.19) obtained from 2

cm 3 /L micronutrients plus 200 kg nitrogen fertilizer followed by 2 cm 3 /L and 200 kg N respectively.

These results are in line with those obtained by Negm and Zahran (2001) they mentioned that

micronutrients increased protein grain content in wheat plants and El-Quesni et al (2009) on

syngonium plants. These increments led to positive effect of growth parameters and enhancing effect

on plant metabolism which was regarded as a better indicator for foliage plants.

Table (1) Chemical properties of micronutrients fertilizer grow-more used in this study.

Growmore

content

N2 P2O5 K2O Fe Zn Mg Ca Cu S B Mo

% 11 6 8 0.15 0.15 0.14 0.02 0.20 0.02 0.01 0.01

180


Ozean Journal of Applied Sciences 3(1), 2010

Table (2) Effect of micronutrient and nitrogen fertilizer on vegetative growth of schefflera arboricola

L. plants. (means of two seasons 2007 and 2008).

Character

Treatments

Effect of micronutrient

Plant

height

Stem

diam

eter

Control 37.61 1.21

Micro 1 cm 3 /L 33.84 1.24

Micro 2 cm 3 /L 42.97 1.46

No.o

f

leave

s

181

Leaf

area

F.W

of

root

D.W

of

root

F.W

of

leave

s

cm mm cm 2 gm

18.6

2

19.9

0

22.2

7

8.87

9.56

11.6

6

39.6

2

41.4

0

45.0

8

17.5

3

36.6

7

41.3

7

75.6

8

76.9

2

84.6

3

D.W

of

leave

s

26.6

6

26.9

3

29.8

8

F.W

of

stem

35.7

6

36.6

7

41.3

7

LSD at 5% level 1.41 0.07 1.58 1.54 1.41 2.09 3.69 1.88 2.09 1.48

Effect of nitrogen

Control 39.91 1.23

N 100 kg 39.36 1.25

N 200 kg 41.10 1.42

19.8

6

19.5

0

21.4

2

9.10

9.80

11.1

8

41.2

2

41.7

9

43.0

9

18.0

5

19.2

0

20.3

8

77.0

3

78.0

6

82.1

4

26.2

0

27.0

5

29.2

1

30.9

1

37.4

0

39.5

0

LSD at 5% level 1.41 0.07 1.58 1.54 1.40 1.70 3.69 1.88 2.09 1.48

Effect of interaction

Control 32.00 1.11

Micro 1 cm 3 /L 41.38 1.28

Micro 2 cm 3 /L 43.34 1.32

N 100 kg 40.17 1.26

N 200 kg 40.67 1.27

Micro 1 cm 3 /L + N

100 kg

Micro 1 cm 3 /L + N

200 kg

Micro 2 cm 3 /L + N

100 kg

Micro 2 cm 3 /L + N

200 kg

38.67 1.24

36.42 1.20

39.25 1.25

46.33 1.80

14.7

3

22.0

2

22.8

3

19.8

3

21.2

8

19.0

0

18.6

6

19.6

7

24.3

2

6.33

10.2

9

10.6

8

10.0

7

10.2

0

9.39

9.00

9.95

14.3

4

33.5

4

43.7

4

46.3

8

42.0

0

43.3

3

41.5

5

38.9

0

41.8

3

47.3

0

12.5

7

20.3

1

21.2

7

19.8

5

20.1

7

18.1

5

17.0

7

19.6

0

23.9

0

67.0

7

81.6

8

82.3

3

80.3

0

79.6

7

76.2

5

72.8

3

77.6

3

93.9

3

21.1

2

28.1

7

29.3

3

27.7

8

28.0

7

26.2

1

25.4

2

27.1

7

33.1

5

28.1

3

40.8

7

41.4

2

39.3

3

39.8

0

35.7

8

33.3

7

37.0

9

45.3

2

LSD at 5% level 2.44 0.11 2.73 2.66 2.44 2.94 6.39 3.01 3.61 2.56

Micro= micronutrients, F.W.=fresh weight,D.W.=dry weight , N= nitrogen

D.W

of

stem

15.0

1

16.8

5

21.1

2

16.4

1

16.7

3

19.8

9

11.0

7

18.0

0

20.1

7

16.9

8

17.0

0

16.5

4

11.0

0

16.6

7

26.5

3


Ozean Journal of Applied Sciences 3(1), 2010

Table (3) Effect of micronutrient and nitrogen fertilizer on chemical constituents of schefflera

arboricola L. plants. (means of two seasons 2007 and 2008).

Treatments

Character

Effect of micronutrient

Chlorophylls Total

Chl. a Chl. b

Chl.

a+b

182

caroten

oids

Mineral ions contents

N P K

mg/g %

Total

protein

Control 0.99 0.30 1.29 0.17 1.47 0.25 3.23 8.68

Micro 1 cm 3 /L 1.12 0.33 1.45 0.18 1.52 0.27 3.26 9.46

Micro 2 cm 3 /L 1.29 0.41 1.70 0.25 1.62 0.33 4.12 10.53

LSD at 5% level 0.08 0.08 0.09 0.09 0.03 0.02 0.33 0.39

Effect of nitrogen

Control 1.03 0.33 1.36 0.19 1.51 0.27 3.32 8.90

N 100 kg 1.18 0.34 1.50 0.19 1.52 0.27 3.42 9.68

N 200 kg 1.19 0.38 1.57 0.22 1.59 0.30 3.87 10.09

LSD at 5% level 0.08 0.02 0.09 0.02 0.03 0.02 0.33 0.39

Effect of interaction

Control 0.52 0.17 0.69 0.09 1.19 0.15 2.50 5.83

Micro 1 cm 3 /L 1.26 0.40 1.66 0.23 1.63 0.32 3.46 10.17

Micro 2 cm 3 /L 1.31 0.43 1.75 0.26 1.67 0.35 4.00 10.69

N 100 kg 1.22 0.36 1.58 0.21 1.60 0.28 3.63 10.00

N 200 kg 1.24 0.37 1.61 0.22 1.65 0.30 3.55 10.19

Micro 1 cm 3 /L + N 100 kg 1.13 0.31 1.44 0.17 1.47 0.25 3.23

Micro 1 cm 3 /L + N 200 kg 0.96 0.29 1.25 0.13 1.43

9.35

0.22 3.10 8.80

Micro 2 cm 3 /L + N 100 kg 1.18 0.37 1.50 0.18 1.48 0.26 3.39 9.69

Micro 2 cm 3 /L + N 200 kg 1.37 0.47 1.83 0.30 1.70 0.39 4.96 11.21

LSD at 5% level 0.15 0.04 0.15 0.03 0.06 0.04 0.56 0.67

Micro= micronutrients, Chl. Chlorophyll, N= nitrogen


Ozean Journal of Applied Sciences 3(1), 2010

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Ozean Journal of Applied Sciences 3(1), 2010

Ozean Journal of Applied Sciences 3(1), 2010

ISSN 1943-2429

© 2010 Ozean Publication

STATISTICAL MODELLING FOR OUTLIER FACTORS

Ahmet Kaya

Ege University, Tire Kutsan Vocational High School Computer Programming Department,

Tire-İzmir, Turkey.

e-mail address for correspondence: ahmet.kaya@ege.edu.tr

____________________________________________________________________________________

Abstract. Error in data is one of the facts that cause the parameter estimations to be subjective. If the

erroneous case is proved statistically, then these cases are called outliers. Outliers are defined as the few

observations or records which appear to be inconsistent with the rest of the group of the sample and more

effective on prediction values. Isolated outliers may also have positive impact on the results of data

analysis, data mining and estimated model. In this study, we are concerned with outliers in time series

which have two special cases, innovational outlier (IO) and additive outlier (AO). The occurence of AO

indicates that action is required, possibly to adjust the measuring instrument or mistake made by person

in observation or record. However, if IO occurs, no adjustment of the measurement operation is required.

Also in the study, a multi-factor ( 3 42

2

) modelling was done in order to fit the effects of model in data

analysis AR(1) coefficients, (0.5, 0.7, 0.9) outlier type (AO, IO), serie wideness (50, 100, 200, 500) and

criterion value sensibility (% 99 (C=3.00), % 95 (C=3.50), % 90 (C=4.00)) factors statistically by

making use of a simulation study. The results of the variance analysis on outlier factors were also

emphasized.

Key Words: ARMA, Outliers in Time Series, AO, IO, Modelling outlier factors.

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INTRODUCTION

Real data and databases may often include some erroneous parts. These situations, which damage the

characteristics of data are called “abnormal condition”, and the values, which cause these “abnormal

condition” are called outliers. The outliers, which are really independent, are the situations that cause the

parameter estimation values in modelling to be subjective, they damage the processes even though they

are set properly, and it is an obligation to destroy or to eliminate the effects. They diminish the reliability

of the results. In this case, outliers is the name given to the data or data sets, which are inharmonious with

the rest of the serie, cause the parameter estimation values to be subjective, and damage the settled

processes.

The outliers are values which seem either too large or too small as compared to rest of the observations

(Gumbel, 1960).

An outlying observation, or outlier, is one that appears to deviate markedly from other members of the

sample in which it occurs (Grubbs, 1969).

The detection of influential subsets or multiple outliers is more difficult, owing to masking and swamping

problems. Masking occurs when one outlier is not detected because of the presence of others, while

swamping occurs when a non-outlier is wrongly identified owing to the effect of some hidden outliers

(Pena and Yohai, 1995).

Data analysis is done by adapting the data to a time series model which is composed of observations.

Outliers in time series were first studied by Fox in 1972. Fox has developed a criterion to fix the outliers

which is called likelihood ratio criteria, and defined the outliers as the first and second type outliers. The

simulations made have proved that the most effective method among these is the consecutive method,

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developed by Chang(1982), Chang and Tiao(1983). Hillmer(1983) Tsay(1986), Pena(1987), Abraham

and Yatawara(1988), Bruce and Martin(1989) had some studies which contributed the theorical structure

of the consecutive method. Besides, Abraham and Yatawara(1988) have studied on lagrange multiplier

method or score based outlier tests. Pena(1987), Abraham and Chuang(1989) and Bruce and

Martin(1989) have studied about the tests depending on the elimination of the outlier values during

outlier detection and effective observations in time series (Ljung, 1993).

Isolating Outliers

The main reason for isolating outliers is associated with data quality assurance. The main exceptional

values are more likely to be incorrect. According to the definition given by Wand and Wang (1996),

unreliable data represents an unconformity between the state of the database and the state of the real

world. For a variety of database applications, the amount of erroneous data may reach to ten percent and

even more.

It is well known that outliers can seriously affect any inferences drawn if they are not treated

appropriately. Their detection and treatment, however, can lead to considerably greater computational

process. For that reason, removal of outliers effect can improve the quality of data used for statistical

inferences. Isolated outliers may also have positive impact on the results of data analysis and data mining.

Simple statistical estimates, like sample mean and standard deviation can be significantly biased by

individual outliers that are far away from the middle of the distribution.

Outlier Detection

The purpose of outlier detection is to discover the unusual data, whose behavior is very exceptional when

compared to the rest of the data set. Examining the extraordinary behavior of outliers helps to uncover the

valuable knowledge hidden behind them and to help the decision makers to make profit or improve the

service quality. Hence, mining aiming to detect outlier is an important data mining research with

numerous applications, which include credit card fraud detection, discovery of criminal activites in

electronic commerce, weather prediction, marketing, statistical applications and so on.

Detection methods are divided into two parts: univariate and multivariate methods. In univariate methods,

observations are examined individually and in multivariate methods, associations between variables in

the same dataset are taken into account.

Classical outlier detection methods are powerful when the data contain only one outlier. However