شناسایی صفات مؤثر بر عملکرد ریشه چغندرقند (Beta vulgaris L.) تحت شرایط آلودگی طبیعی ریزوکتونیایی

محورهای موضوعی : توليد محصولات زراعي

حیدر عزیزی ¹

1 - مرکز تحقیقات کشاورزی

تاریخ دریافت : 1397/04/24 تاریخ پذیرش : 1398/02/25 تاریخ انتشار : 1400/03/08

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

چکیده انگلیسی:

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.

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