شناسایی صفات مؤثر بر عملکرد ریشه چغندرقند (Beta vulgaris L.) تحت شرایط آلودگی طبیعی ریزوکتونیایی
محورهای موضوعی : توليد محصولات زراعي
حیدر عزیزی
1
(مرکز تحقیقات کشاورزی)
کلید واژه: تجزیه علیّت, چغندرقند, رگرسیون گام به گام, همبستگی.,
چکیده مقاله :
به منظور شناسایی صفات مؤثر بر عملکرد ریشه و تعیین روابط علت و معلولی بین آن¬ها، تعداد 20 رقم مختلف چغندرقند در قالب طرح بلوک¬های کامل تصادفی با چهار تکرار به لحاظ 11 صفت مهم کمّی و کیفی شامل عملکرد ریشه، عملکرد قند ناخالص، عملکرد قند خالص، درصد قند ناخالص، درصد قند خالص، ضریب استحصال شکر، α-آمینو نیتروژن، سدیم، پتاسیم، ضریب قلیاییت و درصد قند ملاس مورد ارزیابی قرار گرفت. نتایج حاصل از تجزیه واریانس نشان داد که اختلاف بین ارقام مورد بررسی از نظر صفت مقدار نیتروژن مضره ریشه در سطح احتمال پنج درصد و برای سایر صفات، در سطح احتمال یک درصد معنی¬دار بود. ضرایب تنوع فنوتیپی و ژنوتیپی برای اکثر صفات بالا بود که بیانگر وجود تنوع نسبتاً بالا در ارقام مورد مطالعه برای صفات ارزیابی شده می¬باشد. ضرایب همبستگی بین صفات نشان داد که بیشترین همبستگی منفی و معنی¬دار به ترتیب در بین صفت عملکرد ریشه با صفات درصد قند ناخالص (62/0-)، درصد قند خالص (53/0-)، ضریب قلیاییت (52/0-)، مقدار پتاسیم (49/0)، سدیم ریشه (45/0-) و همچنین میزان قند ملاس (49/0-) و با صفات عملکرد قند ناخالص (95/0)، عملکرد قند خالص (90/0) و ضریب استحصال شکر (58/0) همبستگی مثبت و معنی¬داری وجود دارد. در تجزیه رگرسیون چندگانه به روش گام به گام، صفات درصد قند خالص و ناخالص، میزان نیتروژن مضره و ضریب قلیاییت به ترتیب وارد مدل شدند که 82 درصد از تغییرات عملکرد ریشه را توجیه کردند. بر اساس نتایج تجزیه علیّت، صفات میزان نیتروژن مضره (35/0) و درصد قند خالص (31/0-) به ترتیب بیشترین اثر مستقیم را با عملکرد ریشه داشتند، بنابراین گزینش بر اساس صفات مذکور می¬تواند ما را در دستیابی به ژنوتیپ¬های با عملکرد بالا یاری دهد
In order to identify the effective traits on root yield and also determine the cause and effect of the relationship between them, 20 different sugar beet cultivars in a RCB design with four replications for 11 important quantitative and qualitative traits including root yield, sugar yield, sugar content, white sugar content, extraction coefficient of sugar, a-amino nitrogen, sodium, potassium, alkalinity and molasses sugar were evaluated. The results of analysis of variance showed that the difference between studied cultivars for amino nitrogen (a-N) all traits were significant at the 0.05 probability level and for other traits was important at the 0.01 probability level. Phenotypic and genotypic coefficients of variation for most traits were high, indicating relatively high variability in studied cultivars for evaluated traits. Correlation coefficients between traits showed that there was the most negative and significant correlation between root yield trait with sugar content (-0.62), whit sugar content (-0.53), alkalinity coefficient (-0.52), potassium (-049), sodium (-0.45) and also molasses sugar content (-049) traits, and the most positive and significant correlation with sugar yield (0.95) and extraction coefficient of sugar (0.58) traits, respectively. In multiple regression analysis by stepwise method, sugar content, amino nitrogen and alkalinity coefficient traits were entered into model, respectively, that explained 82 percent of root yield variations. Based on path analysis results, amino nitrogen (0.35) and white sugar content (-0.31) traits had the most and positive direct effect with root yield and thus , selection based on the mentioned traits can help us achieve high-yielding genotypes.
Amal G.A., S. Orabi, and A.M. Gomaa . 2010. Bio-organic farming of grain sorghum and its effect on growth, physiological and yield parameters and antioxidant enzymes activity. Research Journal of Agriculture and Biological Sciences, 6: 270-279.
Amirabadi, M., M.R. Ardakani, F. Rejali and M. Borj. 2010. Effects of Azotobacter chroococcum and Mycorrhizal Fungus along with different levels of phosphorus on qualitative and morphological characteristics of forage Maize (KSC 704). Iranian J. of Soil and Water Res.41(1). 49-56.
Anbessa, Y. and P. Juskiw. 2014. Fertilizer rate and cultivar interaction effect on nitrogen recovery, utilization efficiency, and agronomic performance of spring Barly. Int. Scholary Res. Network Agron. P: 8.
Bhaskara Rao, K.V. and P.B.N. Charyulu. 2005. Evaluation of effect of inoculation of Azospirillum on the yield of Setaria italic L. African J. of Biotech. 4: 989- 995.
Bruns, H.A. and H.K. Abbas. 2005. Ultra high plant population and N fertility effect of corn in the Mississippi vally. Agron. J. 97: 1136-1140.
Darzi, M.T., A. Ghalavand, F. Rejali, and F. Sefidkan. 2007. Effects of Biofertilizers Application on yield and yield components in Fennel (Foeniculum vulgare Mill.). 22( 34) 276-292.
Emam, Y. and M.J. Seghateleslami. 2005. Crop yield, physiology and processes. Shiraz Uni. Press. 593.(In Persian)
Hashemi Dezfuli, S., S. Alemi, and K. Syadat. 2008. Effects of sowing date on yield potantial of two sweet corn cultivar in Khozestan condition. Iran Agricultural J: 32: 681-689.
Izadi, M. H. and Y. Emam. 2010. Effect of planting pattern, plant density and nitrogen levels on grain yield and yield components of maize cv. SC704. Iranian J. of Crop Sci. 12 (3) 239-251. (In Persian))
Larson, J.E., D.F. Warren and K. Langton. 2008. Effect of Fe and Al and humic acid on phosphorous fiction by organic soil. soil sci. Am. Proc., 23: 438 – 440.
Marashi, K. Sh. Zaker Nejad, S. Lak and A. Siadat. 2007. Assessment of planting patterns and plant density on yield and yield components of corn(zea mays S.C. 704) under Ahvaz climatic conditions. Sci. J. Agric. 3: 63-70. (In Persian)
Nasrollah Zadeh Asl, A., F. Jalili and E. Valizadegan. 2015. The impact of nitrogen(nitroxin) and phosphorus biofertilizers on the yield and percentage of sesame oil. J. of Res. In Crop Sci. 6(24). 97- 112. (In Persian)
Niknam, N. and H. Faraji. 2014. Effect of plant density and nitrogen on yield and yield ncomponents of maize Var. 704. Agron. J.(Pajouesh and sazandegi). 102: 56-60.
Nieto, K.F. and W. T. Frankenberger. 1991. Influence of adenine, isopenthyle alchol and Azotobacter chroococcum on the vegetative of zea mays. plant and soil. 135:213- 219.
Nourmohammadi , Gh., S. A. Syadat, and A. Kashani. 2001. A kernel of wheat. Shahid Chamran Uni. of Ahvaz. Press.
Rangarajan, A., B. Ingall, M. Orfanedes and D. Wolf. 2002. In row spacing and cultivar affects ear yield and quality of early-planted sweet corn. Hort.
Saberi, A., D. Mazaheri and H. Sharif. 2006. The effects of sowing density and sowing pattern on yield, yield ncomponents and some agronomic charactristics of corn (zea mays), H.T.W.C. 647 cultivar. 13(1): 49- 57.
Saeed-negad, A., and P. Rezvani. 2010. Evaluation of biological and chemical fertilizers effect on morphological characteristics, yield and yield components of cumin herbal plant. J. of Hort. Sci. 1: 38-44. (In Persian)
Salardini, E. 1992. Agricultural fertilizer. Tehran Uni. Press.
Singh, V.P. and A. Arora. 2001. Interaspecific variation in N uptake and N utilization efficiency in wheat. Crop Sci. 180: 1860-1869.
Sharifi, M., m. Mirzakhani ans N. Sajedi. 2011. Nitroxin the effect of nitrogen and manure on yield, nitrogen efficiency trats and some sweet corn. New Findingsin Agri. 6(2): 15-24.
Subedi, K.D. and B.L. Ma and D. L. Smith. 2006. Response of a leafly and nonleafly Maize hybrid to population densities and fertilizer nitrogen levels. Crop Sci. 46: 1860- 1869.
Tale, S. and M., Mojaddam. 2017. Evlauation of application methods of nitroxin and nitrogen on yield and some physiological traits of maize (Zea mays L. cv SC 704). J. of Iranian Plant Ecophysiological Rec. 12(45): 95-106. (In Persian)
Torbatinejad, M.N., M.R. Chaichi, and S. Sharifi. 2002. Efferct of nitrogen level on yield and yield components of three forage sorghum cultivar in Gorgan. 9(2): 205-220.
Ziaian, E., M. Lotfallahi, and M.J. Malakooti. 1991. The role of consumption management has been optimized to increase yield and improve the quality of corn . Agricultural Res. Training and Promotion Organ.12- 14.