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Table 1. Results of the analysis of the soil of study field. Depth Saturation percentage EC (ds.m -1 ) pH Neutralizable material (%) Organic C (%) Total N (%) Absorbable P (ppm) Absorbable K (ppm) Amoghein et al. 2495 Soil texture Clay Silt Sand Soil type 0-30 48 2.66 7.8 4.8 0.97 0.103 4.8 4601 28 41 31 Loam-clay 30-60 45 2.4 8.2 7 0.48 0.056 2 290 24 36 40 Clay significant on the number of heads per plant, the number of seeds per head, 1000-seed weight, harvest index, and seed and oil yield. In the study of Ranjbar et al. (2004), optimum seeding rate (row spacing and on-row plant spacing) influenced yield and yield components through changing density and environmental resources. Majd et al. (2003) stated that seed yield per unit area and per plant, yield components, the number of seeds per plant and kernel percentage were influenced by plant density. Means comparison for different studied traits at different plant densities showed that as plant density was decreased, the number of heads per plant, 1000-seed weight, the number of seeds per plant, kernel percentage and seed yield per plant were increased, but the number of seeds per head and yield per unit area were significantly decreased. In this study, safflower is considered as one of the resistant drought plants and it has excessive drug use and spice. Also, the Ardabil region in Iran has the highest talent to cultivate various medicinal plants. So, the objective of the current study was to examine the effect of plant density on phenology and oil yield of safflower herb under irrigated and rainfed systems in Ardabil, Iran. MATERIALS AND METHODS The current study was carried out in Agriculture Research Station of Islamic Azad University, Ardabil Branch, Ardabil, Iran (Alt. 1350 m., Long. 48°20´ E, Lat. 38°05´ N) in 2010. All the executive and laboratory operations were conducted in Department of Agronomy, University of Mohagheghe Ardabili, Ardabil, Iran. In order to determine physical and chemical characteristics of the soil of the study field, it was sampled before field preparation from the depths of 0 to 30 and 30 to 60 cm. Then, the samples were analyzed in Water and Soil Laboratory of Islamic Azad University, Ardabil Branch, whose results are given in Table 1. Sina was the cultivar of autumn safflower which was used in this study. It was procured from Agriculture Research Center of Zanjan, Iran. Imported from ICARDA in 1997, Cv. Sina (line PI-537598) was first examined in Rainfed Agriculture Research Institute of Iran. It was one of the superior genotypes and was studied in terms of its local adaptability. Its evaluation in the fields of Kermanshah, Lorestan, Northern Khorasan and Ilam, all in Iran, showed that it performed considerably better than control cultivar (Namely, Zaraghan 279). Safflower cv. Sina is early-maturing with intermediate growth type, resistant to drought stress, thorny with yellow/orange flowers with mean height of 103.5 cm and 1000-seed weight of 34.7 g. The study was a factorial experiment based on a randomized complete block design with four replications. The factors included plant density and planting system (irrigated and rainfed). Each block consisted of 8 treatments or plots with the dimensions of 4×2.1 m 2 with 7 rows with row spacing of 30 cm and inter-plant spacing of 8, 6, 5 and 4 cm used for making the densities of 60, 50, 40 and 30 plants.m -2 . The planting system was created with and without irrigation. The study field had been under the cultivation of potato in the previous year. For the field preparation, the field was first plowed in autumn and was added with 100 kg ammonium phosphate per hectare. Then, it was leveled. After testing the germination percentage of the seeds, they were planted with the on-row spacing of 8, 6, 5 and 4 cm at the depth of 4 cm on April 9, 2010. At the same day, the first irrigation was carried out. The measured traits included days to 50% emergence, 50% rosette, 50% branch-bearing, 50% boll-bearing, flowering initiation, 50% flowering and flowering termination in order to make phenological studies possible. To measure seed and oil yield, the upper and lower 0.5 m of the harvested plants were removed and the rest was used for this measurement. After harvesting, the plants were dried in open air. Then, their seeds were separated and weighed. Next, seed weight per unit area and per hectare was measured. Afterwards, the oil percentage of the seed samples (32 samples) was determined by Soxhlet method, and finally, oil yield was measured by the following formula: Oil yield = oil percentage × weight of dried seed sample Statistical analysis To analyze the variance of the data, software MS-TATC and SAS were used and the means were compared by Duncan Test. Regression analysis was used to study the relations between different harvest stages and studied traits as well as to interpret the observed variation during seeds maturing, and the graphs were drawn by software MS-Excel. At the end, the coefficient of the correlations between the studied traits was measured. RESULTS AND DISCUSSION Days to 50% emergence The results of analysis of variance of phenological traits are shown in Table 2. As shown, the simple effect of plant density was significant at 5% probability level with respect to 50% germination. The means comparison for this trait (Table 3) at the lowest density (30 plants.m -2 ) showed the highest number of days to 50% emergence, while the simple effect of the density of 60 plants.m -2 had the lowest number of days after emergence. In the study of Rahman et al. (2005), the plant density did not affect germination. In addition, drought stress had no effect on
2496 J. Med. Plants Res. Table 2. Summary of analysis of variance for some studied traits at final harvest. Sources of variation df 50% emergence Mean of squares 50% rosette 50% branch-bearing 50% boll-bearing Replication 3 6.00 ns 8.28 ns 6.36* 0.75 ns Planting system (S) 1 2.00 ns 5.28 ns 30.03** 18.00* Plant density (D) 3 8.66* 3.28 ns 26.94** 4.50 ns Interaction S × D 3 3.33 ns 4.28 ns 6.86* 4.50 ns Error 21 2.57 11.85 2.38 2.89 Coefficient of variations (%) 8.11 9.20 2.45 2.31 ns, * and ** show non-significance and significance at 5 and 1% probability level, respectively. Table 3. Means comparison for the main studied effects on some traits at final harvest based on Duncan Test at 5% probability level. Treatment Planting system Irrigated Rainfed Plant density 30 plants.m -2 40 plants.m -2 50 plants.m -2 60 plants.m -2 50% emergence (days after planting) 19.51 a 20.00 a 21.00 a 20.00 ab 19.50 ab 18.50 a Means with the same letter(s) showed no significant differences. seed germination or vigor of corn and sorghum (Ghassemi-Golezani et al., 1997). Francaneto (1993) showed that drought stress can reduce the germination of soybean seeds and that irrigation can be used to counteract this effect. Days to 50% rosette The results of analysis of variance (Table 2) showed no statistically significant differences in the number of days to 50% rosette between planting system and plant density per m 2 as well as the interactions between them. Means comparison for this trait (Table 3) confirmed this result. Among the interactions between planting system and plant density (Figure 1), no statistically significant differences were observed in this trait. Nonetheless, rainfed system had lower number of days to 50% rosette than irrigated system. So, it can be concluded that as the density was increased from 30 to 60 plants.m -2 , the number of days to 50% emergence and 50% rosette decreased. Days to 50% branch-bearing According to the results of analysis of variance (Table 2), 50% rosette (days after planting) 37.00 a 37.81 a 37.62 a 38.00 a 36.50 a 37.50 a 50% branch-bearing (days after planting) 61.93 b 63.87 a 60.50 c 62.50 b 64.62 a 64.00 ab 50% boll-bearing (days after planting) 74.25 a 72.75 b 73.12 a 73.12 a 73.12 a 74.62 a the simple effect of planting system and plant density resulted in statistically significant differences in the number of days to 50% branch-bearing at 1% probability level. Moreover, the interaction between planting system and plant density was significant at 5% probability level. Means comparison (Table 3) indicated that 50% branchbearing was realized earlier under irrigated system than under rainfed system and that the densities of 50 and 60 plants.m -2 had the highest number of days to 50% branch-bearing and the density of 30 plants.m -2 had the lowest one. The density of 40 plants.m -2 had the highest number of days to 50% branch-bearing and was ranked in the same group with the density of 60 plants.m -2 . Among the interactions (Figure 2), the densities of 60 and 50 plants.m -2 under rainfed system had the highest number of days to 50% branch-bearing and were ranked in the most superior group. The density 30 plants.m -2 under both planting systems and the density of 40 plants.m -2 under irrigated system had the lowest number of days to 50% branch-bearing; and the density of 50 plants.m -2 under irrigated system had the highest number of days to 50% branch-bearing and was ranked in the same group with the density of 40 plants.m -2 under rainfed system. Yasari et al. (2005) revealed that the duration of
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Journal of Medicinal Plants Researc
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Editors Prof. Akah Peter Achunike E
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Electronic submission of manuscript
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Fees and Charges: Authors are requi
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Table of Contents: Volume 6 Number
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Figure 1. Chuanxiong Rhizoma (http:
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Table 1. Identification of main pea
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Table 3. Pharmacokinetic parameters
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active component study, many invest
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and 1185 kg ha -1 in the first site
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Table 1. Recommendation for use fer
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Sadanandan AK, Hamza S (1996c). Stu
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and it has been traced to South Ame
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Table 3. Results of phytochemical a
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(a) (b) (c) Figure 1. (a) Normal ce
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emedies in the south of Brazil. J.
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known fatty acids and terpenoids we
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Table 1. Renal function tests of ra
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Al-Radahe et al. 2271 Figure 3.nnnn
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namely disruption of the vascular e
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Zayachkivska OS, Konturek SJ, Drozd
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β-carotene were purchased from Sig
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Figure 1. Effect of ethanol concent
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Table 3. Climatic and soil factors
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content of polysaccharides. Phospha
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Serge et al. 2285 Table 1. Relative
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Percentage inhibition % of inhibiti
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Table 1. Result of phytochemical sc
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Table 3. Result of thin layer chrom
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Table 2. MIC of a compound 1 from c
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Zirihi et al. 2301 Figure 2. Termin
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Figure 5. T. catappa Linn. (Combret
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Figure 8. A. fumigatus: Aspect of c
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Figure 12. Sensitivity of A. fumiga
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Noormi et al. 2311 Table 1. Callus
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Table 2. Contd. NoC=No callus. 4.0
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Figure 2. Contd. at 2.0 mg/L yellow
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Table 1. Biochemical parameters in
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Figure 3. Bcl-xL reactions in inter
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ACKNOWLEDGMENTS The authors would l
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Figure 1. The first page of the boo
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Figure 3. The most widely included
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Figure 4. Lithographic print “St.
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Table 1. List of plants included in
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Table 1. Contd. Nedelcheva 2333 Cin
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Table 1. Contd. Nedelcheva 2335 Rhe
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14 7 1 15 1 35 17 16 Imported plant
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Academy of Science Publishing House
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et al., 1996; van Wyk and Gericke,
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DPPH inhibition (%) DPPH % inhibiti
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% Mortality Concentration (µg/ml)
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information on plants used for the
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Table 1. Levels of independent vari
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Arbutin (mg/g) Co-solvent Figure 1.
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Arbutin (mg/g) Extraction pressure
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Table 3. Arbuitn content of Asian p
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Arbutin (mg/g) Extraction pressure
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Arbutin (mg/g) Extraction temperatu
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Table 1. Chemical composition of es
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Darjazi 2369 Table 2. Statistical a
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Table 3. Correlation matrix (number
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Table 1. Precision test. extraction
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Figure 2. Effect of different alcoh
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Table 6. Results of ANOVA. Nie et a
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Table 2. Plant data and MIC values
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exhibiting the polar extracts of P.
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Table 3. Contd. AcOEt ++ ++ ++ - Me
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Figure 1. Map of Ladakh region of I
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Warghat et al. 2391 Table 3. Summar
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Table 5. Inter-Population genetic i
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Excoffier L, Smouse PE, Quattro JM
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ice residue is an ideal raw materia
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DPPH• scavenging ratio(%) OD valu
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scavenging effect on free radical a
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our new CL system. Fenton reaction
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1 2 Time (s) Figure 2. Kinetic curv
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Wong et al., 2006). It can be seen
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Pan YM, Liang Y, Wang HS, Liang M (
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2422 J. Med. Plants Res. close cano
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2424 J. Med. Plants Res. Table 1. M
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2434 J. Med. Plants Res. Table 6. T
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2436 J. Med. Plants Res. budget dur
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2442 J. Med. Plants Res. Stability
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