ارزیابی واکنش عملکرد و اجزای عملکرد ژنوتیپ‌های امیدبخش مقاوم به تنش خشکی لوبیا قرمز (phaseolus vulgaris l.)

جهت تشخیص میزان تاثیر عوامل ژنتیکی و یا محیطی بر روی یک صفت، ژنوتیپ‌های مختلف بایستی در محیط‌های متعدد مطالعه شوند. این عمل از لحاظ تعیین استراتژی اصلاحی مناسب برای آزادسازی ارقام سازگار به محیط‌های هدف با شرایط محیطی خاص دارای اهمیت می‌باشد. با توجه به شرایط اقلیمی مناطق مختلف، این تحقیق در چهار منطقه عمده کشت لوبیا در کشور به‌منظور بررسی عملکرد و اجزای عملکردی لوبیا قرمز (phaseolus vulgaris l.) با استفاده از 14 ژنوتیپ لوبیا به همراه ارقام شاهد یاقوت، افق و دادفر در قالب طرح بلوک‌های کامل تصادفی با سه تکرار در چهار ایستگاه تحقیقاتی خمین، بروجرد، شهرکرد و زنجان به‌مدت دو سال زراعی (1398-1399) انجام گرفت. نتایج نشان داد که بین مکان‌ها، سال‌ها و ژنوتیپ‌های مورد بررسی از نظر تمامی صفات، اختلاف معنی‌داری در سطح احتمال یک درصد وجود دارد. معنی‌دار بودن اثر متقابل ژنوتیپ × مکان برای تمامی صفات، نیاز به تجزیه واریانس جداگانه در هر مکان مورد بررسی را ضروری ساخت. براساس تعداد روز تا رسیدن رقم افق و ژنوتیپ‌های g9، g16 و تا حدودی g4 و براساس عملکرد و اجزای آن ژنوتیپ g12‌ و ارقام یاقوت و دادفر (به‌ترتیب با میانگین عملکردهای 3288، 3135.95 و 3110.58 کیلوگرم در هکتار) به‌عنوان ژنوتیپ‌های مطلوب برای تمامی مناطق معرفی شدند. تجزیه همبستگی نشان داد که بین عملکرد دانه با صفات تعداد غلاف در بوته، تعداد دانه در غلاف و تعداد دانه در بوته همبستگی مثبت ولی غیرمعنی‌دار وجود دارد. تجزیه رگرسیون نشان داد که صفات تعداد دانه در غلاف، روز تا رسیدگی، تعداد غلاف در بوته و وزن 100 دانه به‌عنوان صفات موثر وارد مدل رگرسیونی می‌شوند و از بین این صفات نیز روز تا رسیدگی با ضریب منفی و تعداد غلاف در بوته با ضریب مثبت در عملکرد دانه موثرتر بودند. در نهایت، می‌توان این‌گونه نتیجه گرفت که غیر از عملکرد دانه، اجزاء عملکرد شامل تعداد غلاف در بوته، تعداد دانه در بوته، و وزن 100 دانه نیز در گزینش ژنوتیپ‌های برتر می‌توانند موثر باشند، لذا انتخاب غیرمستقیم از طریق این صفات می‌تواند در جهت افزایش عملکرد دانه موثر باشد.

evaluation of yield response and yield components of promising red bean (phaseolus vulgaris l.) genotypes resistant to drought stress

introduction considering the limitation of arable land, the most effective factor in increasing the production of beans is to conduct research in the field of agronomic and breeding in order to increase the yield per unit area. in order to determine the effect of genetic or environmental factors on a trait, different genotypes should be studied in multiple environments. the varying responses of genotypes in different environments, coupled with the interaction effects of genotype in the environment, render the selection of genotypes from one environment to another challenging. therefore, examining genotypes in diverse environments holds significant importance in determining the appropriate breeding strategy for the release of adapted cultivars to the target environments. considering the role of genetic diversity in the advancement of breeding programs, the study of morphological and phenological characteristics that determine yield is a suitable method to achieve selection criteria for improving yield and improving and introducing compatible and high-yielding cultivars. seed yield is a complex trait that is controlled by a large number of genes, and selection based on yield alone is often not successful. for this reason, one of the ways to identify high-yielding genotypes is to study traits that have a significant relationship with seed yield, so that by selecting or removing them, the accumulation of desirable genes in improved cultivars can be done. considering the climatic conditions of different regions of iran, this research was conducted in order to investigate the yield and yield components of red beans (phaseolus vulgaris l.) in 4 major bean growing regions in the country. materials and methods 14 red bean genotypes along with yaghout, ofogh and dadfar varieties (controls) were studied in randomized complete block design with three replications in four research stations of khomein, broujerd, shahrekord and zanjan for 2 crop years (2018-2019). at the time of harvest, each plot was harvested separately and the yield of each plot was weighed after threshing. after collecting data related to yield and its components, combined variance analysis, simple variance analysis related to each location and mean comparisons were performed. also, correlation analysis and step-by-step regression were used to investigate the relationship between yield and its components.  results and discussionthe results showed that there is a significant statistical difference between the studied locations, years and genotypes in terms of all traits at the probability level of 1%. the significance of genotype × location interaction for all traits made it necessary to analyze the variance separately in each investigated location. the significance of double interactions indicates the relative instability of the traits of different genotypes in different times and places. the highest seed yield was observed at khomein station in g12, yaghot and g4 genotypes, borujerd in g14 and g13 genotypes, zanjan in yaghot and g12 genotypes and shahrekord in g12 and g16 genotypes. based on the days to maturity the ofogh variety, g9, g16 and to some extent g4 genotypes, and based on its yield and yield components, the g12 genotype and yaghuot and dadfar varieties were introduced as desirable genotypes. correlation analysis showed that there is a positive but non-significant correlation between seed yield and number of pods per plant, number of seeds per pod and number of seeds per plant. regression analysis showed that the traits of number of seeds per pod, days to maturity, number of pods per plant and 100 grain weight are included in the regression model as effective traits and among these traits, days to maturity with a negative coefficient and the number of pods per plant with a positive coefficient were more effective in seed yield. conclusions this study showed that according to the yield and its components in red beans, it is better to introduce a specific variety for each region. based on the number of days to maturity, ofogh (check) and g9, g16, and to some extent g4 genotypes, and based on its yield and components, genotypes g12 and g5 can be reported as favorable genotypes. besides the seed yield, the yield components including the number of pods per plant, the number of seeds per plant, and the 100 grain weight also played a role in selecting better lines; therefore, indirect selection through the selection of these traits can be effective in increasing seed yield. finally, it can be concluded that apart from seed yield, yield components including the number of pods per plant, the number of seeds per plant, and the weight of 100 seeds can also be effective in selecting superior genotypes; therefore, indirect selection through these traits can be effective in increasing grain yield