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شناسایی ژنوتیپهای جو (hordeum vulgare l.) متحمل به تنش خشکی بر اساس شاخصهای گزینشی
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نویسنده
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قویدل شاهین ,پورابوقداره علیرضا ,مصطفوی خداداد
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منبع
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تحقيقات علوم زراعي در مناطق خشك - 1402 - دوره : 5 - شماره : 3 - صفحه:671 -687
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چکیده
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تنش خشکی بهعنوان یکی از مهمترین تنشهای غیر زنده شناخته شده است و بهطور چشمگیری میزان تولید محصولات کشاورزی را کاهش میدهد. در بین غلات، جو متحملترین گیاه نسبت به تنشهای غیرزنده شناخته شده است و در گستره وسیعی از شرایط آب و هوایی کشت میشود. بهمنظور ارزیابی پاسخ به تنش خشکی آخر فصل در جو و شناسایی ژنوتیپهای متحمل به خشکی، مجموعهای متشکل از 17 ژنوتیپ امیدبخش جو به همراه رقم جلگه (بهعنوان شاهد) در دو آزمایش جداگانه بهصورت بلوکهای کامل تصادفی در دو شرایط عدم تنش و تنش خشکی با سه تکرار طی دو سال زراعی 1400-1398 در مزرعه تحقیقات غلات واقع در موسسه تحقیقات اصلاح و تهیه نهال و بذر (کرج) مورد ارزیابی قرار گرفتند. نتایج بهدست آمده از تجزیه واریانس مرکب عملکرد دانه نشان داد، بین ژنوتیپها و محیطها اختلاف معنیداری وجود داشت. بهمنظور شناسایی ژنوتیپهای پربازده و متحمل برخی از شاخصهای حساسیت و تحمل به خشکی محاسبه شد. با توجه به نتایج بهدست آمده مشخص شد شاخصهای sti، mp، gmp و hm میتوانند بهعنوان معیارهای مناسبی جهت گزینش ژنوتیپهای متحمل مورد استفاده قرار گیرند. علاوهبراین، با توجه به نتایج بهدست آمده از غربال ژنوتیپهای ارزیابیشده با استفاده از شاخصهای گزینشی mgidi، fai-blup و smith-hazel مشخص شد ژنوتیپ شماره 13 با شجره هشرجا comp.cr229//as46/pro/3/srs/4/express/5/d10*2 علاوه بر داشتن بیشترین عملکرد دانه میتواند بهعنوان متحملترین ژنوتیپ به تنش خشکی جهت ارزیابیهای بیشتر معرفی شود.
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کلیدواژه
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شاخص mgidi، ضریب همبستگی، عملکرد دانه، مدلهای چند متغیره
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آدرس
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دانشگاه آزاد اسلامی واحد کرج, گروه زراعت و اصلاح نباتات, ایران, سازمان تحقیقات، آموزش و ترویج کشاورزی, موسسه تحقیقات اصلاح و تهیه نهال و بذر, ایران, دانشگاه آزاد اسلامی واحد کرج, گروه زراعت و اصلاح نباتات, ایران
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پست الکترونیکی
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mostafavik@gmail.com
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identification of drought-tolerant genotypes of barley (hordeum vulgare l.) based on selection indices
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Authors
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ghavidel shahin ,pour-aboughadareh alireza ,mostafavi khodadad
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Abstract
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introduction: drought stress or water deficit has been known as one of the most important abiotic stresses so it considerably is decreased crop production. barley (hordeum vulgare l.) is the fourth most important cereal crop in the world after wheat, rice and corn. among cereals, barley is the most tolerant crop against abiotic stresses and due to this capability is cultivated in a wide range of climates. the objective of the current study was to identify the superior drought-tolerant genotypes using grain yield and several yield-based indices of tolerance and susceptibility by applying various multivariate selection models.materials and methods: in the present study a set of promising genotypes of barley including 17 new genotypes along with a jolge cultivar (as a check) was investigated through two separate experiments based on a randomized complete block design (rcbd) with three replications at the cereal research station, seed and plant improvement institute, karaj, iran during two consecutive growing seasons (2019-2020 and 2020-2021) cropping seasons. after sowing, the number of irrigations was one time in autumn and five times in spring. drought stress treatment was applied after anthesis, and irrigation was stopped for all stressed plot until seed repining stage. after collecting experimental data and estimating grain yield, several yield-based drought tolerance and susceptible indices were calculated. a heatmap-based correlation method was used to investigate association among calculated indices and grain yield data. then three selection indices such as multi-trait genotype-ideotype distance index (mgidi), factor analysis and ideotype design via best linear unbiased prediction (fai-blup), and smith-hazel (sh) were exploited to identify the most tolerant-genotypes. all statistical analyses were computed using ipastic and r softwares.results and discussion: based on combined analysis of variance for grain yield data showed significant differences for year, environment, and genotype main effects, as well as, the interaction effects for year × genotype, and year × environment × genotype. the result obtained from screening barley genotypes using drought tolerance and susceptible indices revealed good repeatability so that some of the investigated genotypes appeared in the same pattern in each year of experiments. based on the spearman’s correlation coefficients, grain yields (yp and ys) positively and significantly correlated with mp, gmp, and sti indices in the first year. in the second year, a positive and significant correlation was observed between grain yields with sti, mp, gmp, and hm indices. based on the averaged two-year data, grain yields significantly and positively correlated with hm, sti, mp, and gmp indices, supporting the repeatability of our findings. to identify the most tolerant genotypes based on multi-indices, we used three multi-trait selection indices such as mgidi, fai-blup, and sh. accordingly, genotypes numbers g7, g9, and g16 for the first year, g4, g13, and g17 for the second year, and three genotypes g7, g13, and g16 over two years were selected as superior genotypes using the mgidi index. based on the fai-blup index, the following genotypes were identified as the most tolerant genotypes: g7, g9, and g17 in the first year; g4, g9, and g13 in the second year; g7, g13, and g16 in over two years. the result of screening genotypes using the smith-hazel index showed that three sets of genotypes including g4/g7/g13, g13/g14/g16, and g2/g3/g18 were identified as the high-yielding and most tolerant genotypes in each year and averaged two years, respectively. the venn-plot rendered based on three selection indices revealed that genotype numbers g7 and g13 were superior genotypes in the first and second years.conclusion: in conclusion, our results indicated that g13 “comp.cr229//as46/pro/3/srs/4/express/5/d10*2” with the highest grain yield in both control and drought stress conditions as well as the best ranking pattern for all drought tolerance indices can be a candidate as a superior drought-tolerant genotype for further studies before commercial introduction.
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Keywords
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correlation coefficient ,grain yield ,mgidi index ,multivariate models
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