Scientific Papers Series A. Agronomy

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In this area, priority must be to place soybean crops on irrigated land or on areas with groundwater supply (Roman et al., 2011). Table 1. Suitability marks of agricultural land for soybean crop in Dobrogea Conditions Tulcea Constanta Non-irrigated crop 42 42 Irrigated crop 87 86 Evaluation marks for soybean under natural conditions are poor: 41 to Tulcea County (and 42 for Constanta County, Table 1), while a series of measures to enhance the productive potential of soils, especially investment in irrigation, mark of evaluation is doubled. Evolution soybean growing in Tulcea County. Considering the benefits of soybean crop - many uses of the harvest and suitability as previous crop in crop rotation -, soybean cultivated area has registered significant growth until 1989 (Enciu et al., 1982). In this respect, prior to 1990, soybean covered in Tulcea County tens of thousands ha, soybean crops being one of the beneficiaries of irrigation systems extending over nearly half of the arable land of the county. Table 2. Evolution of soybean crop growing in Tulcea County in the years 2000-2006 Area Total production Average yields Year (ha) (tone) (kg/ha) 2000 3,950 2,503 633 2001 1,878 2,723 1,450 2002 1,658 3,843 2,045 2003 4,233 11,230 2,653 2004 5,021 10,159 2,023 2005 3,938 8,736 2,218 2006 5,229 9,748 1,864 2007 3,466 2,710 782 Media 3,671 6,456 1,708 In the years 1990-2000 there was a sharp reduction in soybean areas due to reduced activity of the livestock sector, but also to dramatic decrease in irrigated area (Table 2). For example, in 1999 soybean occupies only 7,241 ha, and the average production was of 1,472 kg/ha, leading to a total production of 10,658 tons. In the years that followed, areas planted annually with soybeans ranged from 1,878 ha in 2001 and 1,658 ha in 2002, to 5,021 ha in 2004 and 5,229 ha in 2006. The Table 3 show that average yields fluctuate greatly from year to year depending on rainfall, 311 and the opportunity to intervene through irrigation in some areas (e.g. in 2003) (Chelu, 2008; Statistical Yearbook, 2013). Soybean growing farms. Analysis performed in Tulcea County illustrated that there was a large fluctuation from year to year in terms of acreage in soybean and their distribution on individual farms. Thus, in 2000, 3,950 ha were cultivated with soybean, which contributed 13 farms with areas between 10 and 1,381 ha. The higher surface with soybean detaches SC Agrodelta Sireasa (1,381 ha) and SCA Vacareni (870 ha) (Table 3). The average yields were low, with 1,000 kg/ha or more registering only 3 farms. The following year (2001), total soybean area decreased to 1,878 ha; the 12 farms growing soybean were sown less that 200 ha, except SCA Vacareni (844 ha). The average yields were higher, as follows: SC Victoria Trading Ltd (2,100 kg/ha), SC Agrodelta Sireasa (2,000 kg/ha) and SCA Vacareni (1,919 kg/ha). A series of years, the expansion of GM soybean varieties boosted soybean growing. In 2002, the number of growing farms increased to 20, but the cultivated area decreased to 1,658 ha; areas planted in a farm ranged from 5 ha up to 508 ha (SC Acvila Macin Ltd). The county average yield this year was 2,045 kg/ha, and few farms harvested over 3,000 kg/ha, including SC Lombardi Agro Ltd, SC Acvila Macin Ltd, SC Soia Agro Ltd (Table 4). In 2003, the number of soybean growing farms increased to 43, but the areas per farm were very small in most of them. The most important areas are distinguished primarily SC Acvila Macin Ltd (484 ha) and SC Agrodelta Sireasa (482 ha), but SC Lombardi Agro Ltd, SC Adam Agrorent Ltd and SC Euroavipo Ltd, too (over 200 ha each). Year 2005 was characterized by lower soybean areas (1,950 ha) and 25 growing farms, none with more than 200 ha sown with soybean. More than 100 ha were sown few farms, including SC Acvila Macin Ltd and SC Lombardi Agro Ltd. The average yields achieved were good, 9 farms harvesting over 3,000 kg/ha, including SC Soia Agro Ltd (4,009 kg/ha) and SC Adam Agrorent Ltd (3,664 kg/ha).
Table 3. The most important soybean growers in Tulcea County (2001-2006) Succesion of soybean growing farms in accordance to Year sown area 1 2 3 4 5 2001 SC Vacareni 844 ha SC Euroavipo SRL 204 ha SCA Acvila Greci 2002 Macin SRL 178 ha 508 ha SC Acvila 2003 Macin SRL 484 ha SC Agrodelta Sireasa 482 ha SC Aldo SC Comert Impex 2004 Cerale SRL SRL 550 ha 343 ha SC Transion- 2005 Trading SRL 192 ha SC Agro Eco 2006 Sanitas SRL 610 ha SC AMP Tornea SRL 170 ha SC Miti- Geo SRL 313 ha SCA Macin 193 ha SC Agrodelta Jijila Sireasa 140 ha 156 ha SC Euroavipo SRL 280 ha SC Acvila Macin SRL 235 ha SC Acvila Macin SRL 155 ha SC Acvila Macin SRL 300 ha SC Agroin- SC Spicoza dustriala SRL Murighiol 90 ha 148 ha SC Adam Agrorent SRL 265 ha SC Agroschinau SRL 135 ha SC Lombardi Agro SRL 214 ha SC Cold SC Riambo Prod Com SRL SRL 229 ha 210 ha SC Lombardi Agro SRL 140 ha SC Spicoza SRL 247 ha SC Agrodar SRL 120 ha SC Agrocom Soimul SRL 230 ha In 2004, the area planted with soybeans was 3,752 ha and growing farms number was 34, with a large dispersion surfaces, from only 7 ha to 550 ha in SC Commerce Cereals Ltd and 343 ha in SC Aldo Impex Ltd, plus a few farms over 200 ha sown with soybeans, including SC Acvila Macin Ltd. In that year, resulted better productions, SC Spicoza Ltd and SC Acvila Macin Ltd harvesting just over 4,000 kg/ha. In 2006, the area planted with soybeans increased to 3,434 ha, dispersed in 34 farms, each with areas between 2 ha and 313 ha. More than 300 ha of soybean were sown in SC Agro Eco Sanitas Ltd (610 ha), SC Miti-Geo Ltd (313 ha) and SC Acvila Macin Ltd (300 ha). This year can be considered as very favorable for soybeans, if they consider yields over 4,000 kg/ha achieved by SC Soia Agro Ltd (5,950 kg/ha), SC Airem Ltd (5,190 kg/ha), SC Mancov Ltd (5,000 kg/ha) and SC Acvila Macin Ltd (4,216 kg/ha). Aspects in soybean seeds productions in Tulcea County. The study-survey concluded that some of the soybean seeds for the establishment of soybean crops in Tulcea County are produced in seeds crops located only in conditions of irrigation. Most of the biological material (seeds) comes from neighboring counties (Constanta, Braila), or from companies that sell seeds material. Table 4. Farms in Tulcea County with higher soybean yields (2001-2006) Succesion of soybean growing farms in accordance to Year average yields 1 2 3 4 5 SC SC Victoria Agro- Trading delta 2001 SRL Sireasa 2100 kg/ha 2000 kg/ha SC Acvila 2002 Grindu Macin 3400 kg/ha SRL 3289 kg/ha SC Acvila 2003 Grindu Macin 4114 kg/ha SRL 3523 kg/ha SC Acvila SC Spicoza Macin 2004SRL SRL 4560 kg/ha 4230 kg/ha SC Soia 2005Agro SRL 4009 kg/ha SC SC Soia Airem 2006Agro SRL SRL 5950 kg/ha 5190 kg/ha SCA Vacareni 1919 kg/ha SCA Lombardi Agro SRL 3000 kg/ha SC Adam Agrorent SRL 2800 kg/ha SC Agrodar SRL 3814 kg/ha SC Agrodunarea SC Adam Agrorent SRL SRL 3664 kg/ha 3750 kg/ha SC Mancov SRL 5000 kg/ha SCA Macin 1326 kg/ha SC Soia Agro SRL 3000 kg/ha SCA Lombardi Agro SRL 1321 kg/ha SC Agrodelta Sireasa 3000 kg/ha SC Teodema SC Soia Serv Agro SRL Com 2798 SRL kg/ha 2800 kg/ha SC Lord SRL 3600 kg/ha SC Lord SRL 3618 kg/ha SC Acvila Macin SRL 4216 kg/ha SC Inextenso SRL 3500 kg/ha SC Agrodar SRL 3500 kg/ha SC Lombardi Agro SRL 3974 kg/ha Between 2001 and 2006, farmers included in the assortment GM soybean varieties (S0994RR, S1484RR, S2254RR, PR92B05RR, PR92B71RR, AG0801RR). Among the varieties listed in Official Catalogue of Varieties, in Tulcea County were grown mainly Danubiana, Columna and Triumf. In the analyzed period soybean seeds crops totaled between 35 ha (in 2005) and 370 ha (in 2000). Varieties for which seed were produced were Danubiana, Columna, Triumf (of current range), Avila, Condor, Dekabig, Orlando (which were removed from the national assortment). Among farms producing 312
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SCIENTIFIC PAPERS SERIES A. AGRONOM
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University of Agronomic Sciences an
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SUMMARY SOIL SCIENCES Variation of
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A survey study on determination of
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Effects of different nitrogen forms
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Determine the effect of some cultiv
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SOIL SCIENCES
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K + /Na + ratio that ultimately pre
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ZINC POLLUTION OF SOILS LOCATED INT
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as the result of the plant protecti
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OBTAINING OF HUMATE-BASED LIQUID FE
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an 11.6% mass loss and a 145.5 J/g
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mijloc important de fertilizare ech
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collected on 13/09/2012 at the dept
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Table 3. The Influence of mineral f
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CONCLUSIONS The Hybrid rapeseedseed
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Scientific Papers. Series A. Agrono
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CONCLUSIONS The results have shown
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organic carbon was determined thoug
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THE INFLUENCE OF SOIL TILLING SYSTE
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emerging plant, we recommend using
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at the cellular level of Ni (Bou et
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concentrations in agricultural soil
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Surfaces at the bottom shows higher
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substantial balance that means maxi
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Table 4. Aggregate composition and
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1. The initial parameters of ordina
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Table 8. Modification of the featur
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Abstract Scientific Papers. Series
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the linear correlation coefficient
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CONCLUSIONS For soil polluted with
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50 and 100 mg/kg and appreciated th
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Figure 4. Copper content in soil Fi
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samples collected in northern of fa
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MATERIALS AND METHODS Study areas T
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influenced by heavy metals contamin
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Pankhurst C.E., 1997. Biodeversity
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horizons, color, texture, structure
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From a chemical reaction these soil
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- Organic matter by Tiurin; - pH (H
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RESULTS AND DISCUSSIONS Invertebrat
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of moisture in arable layers, incre
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experimentation. The increase of mo
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THE TRANSITION PERIOD TO THE MARKET
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Activity data Activity data comes f
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Figure 2. The decrease of cultivate
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of nitrous oxide. In: Revised 1996
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Laboratory results have been interp
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The air-mass interferes with the ov
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Under these conditions, Moldavian r
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decreased to near wilting coefficie
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CONCLUSIONS Severe drought that aff
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(temperature and soil moisture, air
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primary cultures analyzed, hybrids
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weeding crops during the growing se
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improper drainage and irrigation (G
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Figure 4. Scores plot of the soil s
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Table 1. Cluster analysis of the st
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DIFFERENTIATION OF FERTILIZATION RA
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Figure 2. Situation and location of
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Statistical data processing For the
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Phosphorus and potassium fertilizer
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30 m. Regarding the formation and d
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considerably less. These facts are
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Table 2. Hydraulic dimensioning Par
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SPATIAL VARIATION OF PHYSICAL CLAY
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Figure 2. Situation and location of
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esistant to high clay content in th
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CONCLUSIONS Described regularities
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ecome widespread and in order to ea
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Table 3. Results of the analysis of
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COMPARISON OF SYSTEMS FOR TAXONOMY
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RESULTS AND DISCUSSIONS Soil types
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underdeveloped cinnamon forest soil
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Figure 8. Content of skeletal fract
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MODEL FOR INVESTIGATION, AMELIORATI
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RESULTS AND DISCUSSIONS Characteris
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terrain is in the composition of a
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Such characteristics require the ne
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Australia) with high resolution nit
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some important medicinal plants of
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RFV = [120 / NDF] × [88.9 - (0.779
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average at Viani - Brila County). A
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Figure 1. Dry above-ground biomass
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County) and 30.29% (CERA 270 hybrid
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phenological stages were found to h
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STUDIES REGARDING THE INFLUENCE OF
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ainfall were able to have a negativ
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Figure 7. Thermo-hydric stress fact
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In Romania is grown a large assortm
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Mainly vitamin C, E and polyphenols
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soluble compounds with antioxidant
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primarily the water-soluble antioxi
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has a split-split-plot design with
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Kovács B., Gyori Z., Prokisch J.,
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pays off (Mares et al., 2004; Gonz
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Table 3. Tested variants V1 Control
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about the inner value of flora. The
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MATERIALS AND METHODS Biological ma
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Figure 2. Correlation between prote
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CONCLUSIONS Production and quality
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The following presents several tech
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3. Evolution of total weed number i
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RESEARCH ON APPLICATION OF NPK FERT
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Also increase production significan
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In April 2012, the pre-sowing proce
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difference with the hoed control sa
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RESULTS AND DISCUSSIONS Data about
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Table 7. Proved difference between
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Table 1. Variance analysis experien
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Amongst the three precocity groups,
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ACKNOWLEDGEMENTS This study was car
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to present genetic sources of resis
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REFERENCES Antonova T.S., Araslanov
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Halstedii is necessary to identify
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EFFICIENCY OF UTILIZATION OF ASELEC
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to separate the effects of genotype
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INFLUENCE OF THE CLIMATIC CONDITION
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In 2012, at NARDI Fundulea, data fr
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parameter from the treated variants
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Table 6. The effectiveness of some
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Page 264 and 265: Table 1. Probability of the meteoro
Page 266 and 267: At 50% DI in EOF, only a small part
Page 268 and 269: This was probably due to the specif
Page 270 and 271: under deficit irrigation. This prov
Page 272 and 273: RESULTS AND DISCUSSIONS Intervals w
Page 274 and 275: productions from one year to anothe
Page 276 and 277: epresented by soil ecologization an
Page 278 and 279: new created ones as a basic conditi
Page 280 and 281: The highest number of kernels per e
Page 282 and 283: Table 8. Average weight of thousand
Page 284 and 285: CONCLUSIONS The drought from the ye
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Page 288 and 289: 100% in the first 6 weeks of growth
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Page 292 and 293: locules boll -1 (0.02), seeds locul
Page 294 and 295: Bhutto H., Baloch M.J., Yousaf M.,
Page 296 and 297: Table 4. GCA effects for morpho-yie
Page 298 and 299: MATERIALS AND METHODS This study wa
Page 300 and 301: vegetation of each of the swaths, i
Page 302 and 303: Sudangrass hybrids depending on the
Page 304 and 305: The parameters of biomass and dry m
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Page 308 and 309: Fertilization Forms Table 2. The me
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Page 318 and 319: Figure 6. Embryo and endosperm mark
Page 320 and 321: RESEARCHES CONCERNING THE INFLUENCE
Page 322 and 323: Table 1. The influence of seeding d
Page 324 and 325: Exagone hybrid. Thus, when sown at
Page 326 and 327: Table 9. The influence of sowing di
Page 328 and 329: MATERIALS AND METHODS In order to k
Page 330 and 331: Table 3. Genotype influence on whea
Page 332 and 333: Romanian varieties from the experim
Page 334 and 335: Abstract Scientific Papers. Series
Page 336 and 337: Table 2. Efficacy of some fungicide
Page 338 and 339: ROMANIAN WHEAT - STRATEGIC PRODUCT
Page 340 and 341: exceeded 2,000 thou ha, and maximum
Page 342 and 343: Values over 26% wet gluten were det
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Page 346 and 347: grassland. This method is commonly
Page 348 and 349: RESULTS REGARDING DROUGHT RESISTANC
Page 350 and 351: average for this period is 170.6 mm
Page 352 and 353: Hybrid FAO grupe Table 2. The main
Page 354 and 355: Abstract Scientific Papers. Series
Page 356 and 357: length has lowest values at the unt
Page 358 and 359: CHARACTERISTICS OF SECOND GENERATIO
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Table 5. Cytological characteristic
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We can see in the table that all li
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RESULTS AND DISCUSSIONS Mean compar
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Table 4. Statistical interpretation
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COMPARATIVE STUDY OF CONVENTIONAL A
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Improved sunflower hybrids for use
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differences in production to contro
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International Center for Agricultur
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Table 3. Evaluation of Genotypes fo
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Table 1. Characteristics of city sl
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Table 4. Amount of the rainfall dur
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ECOLOGICAL AGRICULTURE
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maize had a density of 5 plants/m 2
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CONCLUSIONS In terms of productivit
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amino acids, such as 4-hydroxyisole
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Table 5. Determining chlorophyll pi
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PROPOSALS ON TECHNOLOGY OF MOVING A
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These are the main technical charac
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FUNGAL BIODIVERSITY AND CLIMATE CHA
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Climate change effects and Dobrogea
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Figure 10. Pure culture of benefici
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MANAGEMENT OF BENEFICIAL MICROORGAN
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microorganisms DSMZ Braunschweig -
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Protocol of research and reporting
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“HERBAL MEDNET” AN INNOVATIVE A
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Figure 2. Value of global herbal ma
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Figure 3. The Allelopathy effect on
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AGRICULTURAL ENGINEERING AND RENEWA
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Research was also aimed at observin
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Leaf production of dry matter per h
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cooking oil and jatropha oil (Vonsh
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machines, many different fat extrac
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Table 4. The nutrient content Conte
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Figure 21. Dunaliella salina sp. ch
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for the decline is the growing numb
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Tractor power seemed the obvious wa
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Figure 4 shows that in 17 post war
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their employability, help raise the
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. Scientific Papers. Series A. Agro
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through the sprinkler irrigation. A
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Figure 5. Overlapping sprinklers wi
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CLIMATE CHANGE AND AGROMETEOROLOGIC
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Bulgaria to the use of agroclimatic
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Figure 9. Duration of the period so
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Figure 18. Evapotranspiration of wi
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RESULTS AND DISCUSSIONS After scari
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The influence of the texture on the
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Figure 6. Area of land planted with
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APPLIED BIOLOGY IN AGRICULTURAL SCI
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MATERIALS AND METHODS Researches we
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RESEARCHES REGARDING EVOLUTION OF S
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gradually reduce towards the end of
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According to that, the aspect of th
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etween classes of variation with ma
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Table 2. Average heights of Lycium
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V 1 V 2 Table 6. Average shoot leng
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Table 13. Average dry substance of
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centrifuge (7000 rev/min. during 20
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7, Streptomyces sp. 9, and Streptom
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laboratory of Biology, USAMV Buchar
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SOME NEW SPECIMENS FOR ZOOLOGICAL T
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New reptiles for our teaching colle
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Figure 1. Scatter plot of odontosty
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Table 4. Measurements of Xiphinema
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Malus pumila and P. avium are new h
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- the mean, minimum and maximum mon
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The monthly mean of the flow highli
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longer in balance with the existing
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ecording the encountered plant spec
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Mediterranean (3), Balkan (1), Cent
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Table 3. Segetal species of the Top
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of sugar/flower and the honey poten
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Territorial concentration of mellif
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CONCLUSIONS In Giurgiu County there
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farm (Awake, 1998). Rahman et al. 2
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Table 3 shows that there was a high
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RESULTS AND DISCUSSIONS x, k, r, R
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Figure 3. Us-Pressure Relations of
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