ارزیابی کارایی شاخص‌های waasb، waasby و مدل اثرهای مختلط خطی (lmm) برای شناسایی ژنوتیپ‌های عدس پر محصول سازگار با مناطق دیم

ادغام دو روش ارزیابی پایداری بهترین پیش بینی‎های نااریب خطی (blup) و اثرات اصلی جمع پذیر و برهمکنش‎های ضرب پذیر (ammi) در آزمایش‎های ناحیه‎ای بر پایه شاخص پایداری میانگین وزنی نمرات مطلق (waasb)، به ارزیابی بهتر ژنوتیپ‎های گیاهی و دستیابی به نتایج دقیق‎تر کمک می‎کند. در پژوهش حاضر پایداری 18 ژنوتیپ پیشرفته عدس، در سه منطقه خرم‌آباد (لرستان)، زنجیره (ایلام) و سرارود (کرمانشاه) طی سه سال زراعی (1389-92) در قالب طرح بلوک‎های کامل تصادفی با سه تکرار مورد ارزیابی قرار گرفت. با توجه به معنی‌دار بودن برهمکنش ژنوتیپ در محیط بر پایه نتیجه آزمون درست نمایی نسبی (lrt)، امکان تجزیه داده‌ها به روش blup وجود داشت. بر این اساس بالاترین عملکرد دانه پیش‌بینی‌شده با روش blup مربوط به ژنوتیپ 2 و پس از آن ژنوتیپ‎های 4، 19، 5 و 1 بودند که عملکرد دانه پیش‌بینی‌شده بیشتر از میانگین کل داشتند. به‌منظور فراهم کردن امکان گزینش هم‌زمان بر اساس عملکرد و پایداری، با تلفیق دو شاخص عملکرد دانه و پایداریwaasb، شاخص waasby به دست آمد. با در نظر گرفتن سهم 50 درصد برای هر یک از دو جزء عملکرد و پایداری، 14 ژنوتیپ دارای waasby بالاتر از میانگین بودند. مقدار waasby به‌ویژه در مورد ژنوتیپ‎های 19، 2، 4، 6، 1، 3 و 11 به‌طور قابل توجهی بالاتر از سایر ژنوتیپ‎ها بود و بر این اساس به‌عنوان بهترین ژنوتیپ‎ها شناسایی شدند. در مجموع با توجه به استفاده از مدل مختلط و همچنین تمام مولفه ها در محاسبه شاخص waasby، به نظر می‎رسد که این شاخص برتر از سایر شاخص‎ها باشد.

evaluation of the efficiency of waasb, waasby indices and and linear mixed effects model (lmm) for identifying high- yielding lentil genotypes adapted to rainfed regions

introduction: lentil is one of the legumes due to its protein percentage and high nutritional value, and it can be cultivated in the fall in rainy conditions. due to the different reactions of crop genotypes in different environments, the evaluation of the genotype × environment interaction in the process of introducing new cultivars is fundamentally important. the development of high yielding cultivars with wide adaptability is the ultimate aim of plant breeders. however, attaining this goal is made more complicated by genotype-environment interactions. the genotype by environment interaction is a major problem in the study of quantitative traits because it complicates the interpretation of genetic experiments and makes predictions difficult, also it reduces grain yield stability in different environments. multi-environment trials are often analyzed to assess the yield stability of genotypes. combining features of the best linear unbiased predictions (blup) and additive main effects and multiplicative interaction (ammi) throught “ weighted average of absolute scores of best linear unbiased predictions ” (waasb) index in multi- environment experiments may lead to more precise evaluation of genotypes and assessment of genotype × environment interaction. this statistical models has been widely used to explain complicate g×e interaction, to enhance selection efficiency and to ensure genetic gain from selection. the objective of this study was to investigate the response of the lines in studied locations and to identify lines adapted to the test environments. the objective of this study was to investigate the response of the lines in studied locations and to identify lines adapted to the test environments.materials and methods: in the present study, the seed yield stability of 18 advanced lentil genotypes was evaluated in a multi-environment trials in three locations including; khoramabad, ilam and kermanshah, iran in 2010-2013 cropping seasons. the experimental design was s randomized complete block design with three replications. statistical analyzes were performed using multi-environment trials analysis. in order to evaluate genotype × environment interaction, ammi and blup methods were combined by introducing waasb and waasby indicators and the yield stability was evaluated by drawing various graphs.results and discussion: considering the significant g×e interaction based on the results of the relative likelihood test (lrt), it was possible to perform blup analysis on the data. the results of the mosaic diagram showed that the contribution of genotype and genotype × environment interaction were 15.45% and 84.55% of the total variation, respectively. the highest predicted seed yield by blup method belonged to genotype no. 2 followed by genotypes no. 4, 19, 5 and 1 which had higher than average predicted seed yield. to enable simultaneous selection based on both seed yield and yield stability, by combining seed yield (y) and waasb, a new index “waasby” was created. considering 50% contribution of each of the two components of seed yield and yield stability, fourteen genotypes showed above average waasby. genoypes no. 19, 2, 4,6, 1, 3 and 13 had considerably higher waasby when compared with other genotypes and was identified. control gachsaran cultivar (genotype 20) had lower than average waasbyconclusion: in conclusion, considering waasby index, genotypes 2, 4, 6, 1, 3 and 11 were identified as genotypes with high seed yield and yield stability, and can be considered for being released as new lentil cultivars.in general, usin mixed model as well as all the components in calculation the waasby index, it can be concluded that this index is superior to other indices.