مقایسه شاخص‌های انتخاب در هیبریدهای ذرت علوفه‌ای (.zea mays l) تحت شرایط تنش و بدون تنش شوری

عملکرد صفت پیچیده‌ای است که وراثت‌پذیری پایینی دارد به همین دلیل گزینش بر اساس شاخص انتخاب یکی از روش‌های موثر جهت گزینش غیرمستقیم برای بهبود عملکرد است. به‌منظور بررسی شاخص‌های انتخاب برای بهبود عملکرد ذرت، آزمایشی با 14 هیبرید سینگل‌کراس ذرت علوفه‌ای (شامل 12 هیبرید امیدبخش و 2 رقم هیبرید سینگل‌کراس تجاری 704 و 715 به‌عنوان شاهد) در قالب طرح بلوک‌های کامل تصادفی با 4 تکرار در دو شرایط شور و غیر شور و در ایستگاه‌های تحقیقات کشاورزی طرق مشهد و عباس‌آباد تنگلشور در سال 1396 اجرا گردید. نتایج تجزیه واریانس آماری مرکب حاکی از وجود تفاوت بسیار معنی‌دار بین دو محیط شور و غیر شور به لحاظ اغلب صفات موردبررسی بود (p≤0.01). از رگرسیون گام‌به‌گام برای کاهش داده‌های اندازه‌گیری شده و محاسبه شاخص‌های انتخاب استفاده شد. صفات عملکرد علوفه‌تر، عملکرد علوفه خشک، تعداد کل برگ، تعداد بلال، ارتفاع بوته و تعداد روز تا گرده‌افشانی از مدل رگرسیونی انتخاب شدند. بر اساس این نتایج، در شرایط بدون تنش جمعاً 77.84 درصد و در شرایط تنش شوری 76.90 درصد از تغییرات مربوط به عملکرد را توجیه و در محاسبه شاخص‌های گزینش مورداستفاده قرار گرفتند. کارایی نسبی گزینش و بهره مورد انتظار در شاخص‌های بهینه نسبت به پسکبیکر بیشتر بود. بیشترین مقدار کارایی نسبی گزینش در شرایط بدون تنش در شاخص شماره 5 (هیبریدهای شماره 3، 5، 2، 8 و 6) و در شرایط تنش شوری در شاخص شماره 4 (هیبریدهای شماره 13، 3، 4، 10 و 8) برآورد شد. به‌علاوه در هر دو شرایط بدون تنش و تنش شوری ژنوتیپ شماره 2 توسط بیشتر شاخص‌های گزینشی موردمطالعه به‌عنوان برترین ژنوتیپ گزینش شد.

Comparison of selection indices in forage maize (Zea mays L.) hybrids in normal and salt stress conditions

IntroductionTo improve a complex character such as grain yield with low heritability, indirect selection through other characters and selection index based on different effective traits were used. Grain yield has quantitative heritance and can be affected by environment severely; therefore selection for genetic improvement only based on yield may have low efficiency. But selection based on proper index can be one of the most effective methods for indirect selection of yield and yield components simultaneously.Materials and methodsIn order to determine selection index for improvement of maize yield, 14 single cross maize hybrids (including 12 promising maize hybrids and KSC704 and KSC705 cultivars as control cultivars) were planted in two separate experiments (Saline stress and normal condition) based on randomized complete block design (RCBD) with four replication in Khorasan Razavi agricultural and natural resources research and education center (TOROQ Station and Abbas Abad Station), Mashhad Iran on 20172018. In this study silage yield, Dry Forage yield, number of total leaves, Ear Diameter, Ear Length, Ear Height, Kernel depth, anthesis silking interval (ASI) and Plant Height appearance was measured randomly from 10 sample. Then some of morphological and phonological traits, yield and yield components were recorded.Results and discussionThe results of ANOVA showed significant differences between hybrids for many of measured traits in both conditions (P≤0.01). Thus, selection will be effective due to existence of enough variation. The results of correlation, multiple regression and principle component analysis were used for identification of traits that are more effective on grain yield. Selection indices were calculated based on results of stepwise regression considering to phenotype, genotypic and economic values. Based on stepwise regression results in normal condition, Plant Height, Number of Ear, Dry Forage Yield, Days to anthesis, Number of Leaves totally could explain 77.84 percent of gain yield variation, then these traits were used to calculate selection index. In Saline stress condition, Number of Ear, Ear Length, Days to anthesis, Number of Leaves, Plant height could explain 76.90 percent of grain yield variation that these traits were used to calculate of selection index. SmithHazel and PeskBaker selection indexes for dry silage yield performance, leaf total number, number of cob, plants length and days to pollination in nonstressed condition and number of cob, days to pollination, leaf total number and plants length were calculated under stressed situation. Moreover, relative efficiency of selection and expected gain of selection index using the Smith – Hazel index was higher than the Pesk – Baker index. The highest relative efficiency of selection under nonstressed condition was measured in index number 5 (Smith – Hazel 5) while in saline stressed condition it was achieved in index number 4 (Smith Hazel 4).ConclusionIn summary, by adjusting phenotype values in mentioned traits in index equivalent, the amount of each index was determined. Finally Based on grain yield and selection indices, 20 percent of the best genotypes were selected by each selection indices. The highest selection indices were obtained for the hybrids 1, 5, 2, 8 and 6 in normal condition and hybrids 13, 3, 4, 10 and 8 in saline condition.