| تعداد نشریات | 282 |
| تعداد نشریات سازمان | 80 |
| تعداد شماره‌ها | 3,272 |
| تعداد مقالات | 36,149 |
| تعداد مشاهده مقاله | 55,713,750 |
| تعداد دریافت فایل اصل مقاله | 94,492,334 |
گزینش ژنوتیپ‌های برتر کینوآ (Chenopodium quinoa willd.) درمنطقه کاشمر به روش تحلیل نموداری | ||
| پژوهش های کاربردی زراعی | ||
| دوره 36، شماره 1 - شماره پیاپی 138، تیر 1403، صفحه 135-119 اصل مقاله (735.3 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/aj.2024.364816.1670 | ||
| نویسندگان | ||
| مجید طاهریان* 1؛ محمود باقری2 | ||
| 1عضو هیئت علمی - مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی خراسان رضوی - ایستگاه تحقیقات کشاورزی و منابع طبیعی کاشمر | ||
| 2، بخش تحقیقات سبزی و صیفی، موسسه تحقیقات اصلاح و تهیه نهال و بذر، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران. | ||
| چکیده | ||
| کینوآ (Chenopodium quinoa willd.) به دلیل تحمل بالا به تنش‌های خشکی و شوری به عنوان یک گیاه جدید موردتوجه قرار گرفته است. به‌منظور شناسایی و گزینش ژنوتیپ‌های مطلوب کینوآ، 10 ژنوتیپ کینوآ در قالب طرح بلوک‌های کـامل تصادفی در سه تکرار در ایستگاه تحقیقات کشاورزی کاشمر طی دو سال 1397 و 1398 کشت و مورد مطالعه قرار گرفتند. تجزیه واریانس مرکب داده‌ها نشان داد که اثر ژنوتیپ برای همه صفات در سطح احتمال یک درصد معنی‌دار بود در حالی که اثر متقابل ژنوتیپ×سال فقط برای صفت عملکرد معنی‌دار بود. میانگین عملکرد دانه ژنوتیپ‌های کینوآ در مجموع دو سال آزمایش، در دامنه‌ای بین 812 (Q31) تا 1246 (Titicaca) کیلوگرم در هکتار قرار داشت. از تجزیه‌های بای‌پلات ژنوتیپ×صفت (GT) و بای‌پلات ژنوتیپ×عملکرد×صفت (GYT) جهت بررسی اهداف این پژوهش استفاده شد. همبستگی عملکرد دانه با صفات طول گل‌آذین، وزن هزار دانه و میزان ساپونین دانه مثبت و قوی بود درحالی که با صفات تعداد گل‌آذین، ارتفاع بوته و قطر طوقه منفی و قوی بود. براساس نتایج GTبای‌پلات در این پژوهش مشخص شد که ژنوتیپ‌های دارای عملکرد بالا، از طول گل‌آذین و وزن هزار دانه بالاتر و تعداد گل‌آذین، قطر طوقه و ارتفاع بوته کمتر برخوردار بودند. براساس نتایج GYTبای‌پلات در این پژوهش بهترین ژنوتیپ‌ها در منطقه کاشمر براساس عملکرد دانه، وزن هزار دانه، طول گل‌آذین بالاتر، ارقام Titicaca، Giza1 و Redcarina بودند. در مجموع می‌توان عنوان کرد که روش‌های گرافیکی از کارآیی بالایی برای انتخاب ژنوتیپ‌های برتر در برنامه‌های به‌نژادی برخوردار هستند. | ||
| کلیدواژه‌ها | ||
| بای‌پلات؛ ژنوتیپ مطلوب؛ صفات موثر؛ کینوآ | ||
| عنوان مقاله [English] | ||
| Selection of quinoa superior genotypes using geraphical methods in Kashmar region | ||
| نویسندگان [English] | ||
| majid Taherian1؛ Mahmood Bagheri2 | ||
| 1researcher | ||
| 2Vegetable Crops and Pulse Crop Research Department, Seed and Plant Improvement Research Institute, AREEO, Karaj, Iran. | ||
| چکیده [English] | ||
| Introduction Quinoa (Chenopodium quinoa Willd.) is an annual seed crop from the Andean region of South America. The broad adaptation, high nutritional value, and health benefits of quinoa have contributed to its recent rise in popularity across the globe (Hinojosa et al., 2019).Quinoa seeds provide a high-quality protein diet to humans, as they typically contain significant amounts of the nine essential amino acids (Wu, 2015). Quinoa also possesses high concentrations of iron, calcium, and phosphorus (Wu, 2015; Vilcacundo and Hernández-Ledesma, 2017), has unique extrusion properties (Kowalski et al., 2016), and has important end-use quality and consumer acceptance characteristics (Aluwi et al., 2017). Quinoa has the capacity to grow and adapt to marginal environments in many regions across the globe, and it exhibits notable tolerance to abiotic stressors such as drought and salinity (Ruiz et al., 2014, 2016; Hinojosa et al., 2018). In breeding studies, when trying to develop a cultivar trait, it is possible to disrupt another trait. For this reason, the genotype × yield × trait (GYT) biplot evaluates all the traits together and provides more accurate results. In this regard, quinoa breeders should know whether any trait is negatively or positively correlated with grain yield. The aim of this study was to assess genotypes evaluation and trait profiles of quinoa using the GYT and GT biplot techniques and characterization of quinoa based on multiple traits under irrigation conditions. Materials&Methods 10 quinoa genotypes (G1-G10) were studied during 2017 and 2018 at Kashmar Agricultural Research Station. The experimental design was a randomized complete block with three replications. Several main traits i. e., days to heading (DH), days to maturity (DMA), plant height (PLH), thousand kernel weight (TKW), length of Inflorescences (LI), saponin content (S) and grain yield (GY) were recorded for all genotypes. Genotype by yield by trait (GYT) biplot and genotype by trait (GT) biplot methods were used to select and characterize superior genotypes based on multiple traits. The combined analysis of variance for GY and other traits was conducted using ADEL-R software. The GYT biplot and GT biplot methodologies were employed to select and characterize quinoa genotypes based on multiple traits using GEA-R software. Results&Discussion The combined analysis of variance showed that the effect of genotype and genotype×year was significant at 1% probability level for all traits whereas the effect of genotype×year was significantn only for GY. On the whole, the mean of GY for the evaluated genotypes in the all years of the trial varied from 812 (Q31) to 1246 (Titicaca) kg/ha. Based on GT-Biplot polygon, Titicaca, Redcarina and Giza1 genotypes displayed high grain yield, thousand kernel weight, length of Inflorescences and saponin content. The vector view of GT biplot showed high positive correlation between grain yield with thousand kernel weight, length of Inflorescences, saponin content and negative correlation with number of Inflorescences, plant height and diameter of plant crown. Based on the GYT results, the genotypes Titicaca, Redcarina and Giza1 were the best in combining grain yield with the evaluated traits, respectively. According to the GYT index, Titicaca, Redcarina and Giza1 had the highest values, respectively. On the other hand, these theree cultivars did not have negative values for combined yield with different traits. This indicated the relative superiority of these genotypes in combining grain yield with the evaluated traits. The value of GYT index for Q18 genotyoe was close to zero (0.001) and this means that this genotype had average values of traits in this study. Conclusion: Based on the results, the cultivars Titicaca, Redcarina and Giza1 were the most high-yielding genotypes as were characterized by high thousand kernel weight, length of Inflorescences and saponin content and low to medium plant height and diameter of plant crown in Kashmar condition. Also the GYT and GT biplot offer a useful analytic tool for examining the variation among sets of genotypes, exploring multiple trait data, which will aide in multi-trait selection. | ||
| کلیدواژه‌ها [English] | ||
| Biplot, Effective traits, Ideal genotype, Quinoa | ||
| مراجع | ||
|
Abasi, S., Cordnaeich, A. and Bagheri, M. 2018. Evaluation of genetic diversity of new chenopodium quinoa (Chenopodium quinoa Willd) cultivars based on agromorphological traits. 15th National Iranian Congress Science Congress, 2-5 Sep. 2019. Karaj, Iran. (In Persian with English abstract). Afiah, S., Hassan, W. and Al Kady, A.M.A. 2018. Assessment of six qinoa (Chenopodium quinoa Willd.) genotypes for seed yield and its attributes under Toshka conditions. Zagazig Journal of Agriculture Research, 45 (6B):2281-2294. Bagheri, M., Miri, Kh., Kloshkam, S. G., Anafjeh, Z., and Keshavarz, S. 2022. Assessment of adaptability and seed yield stability of autumn sown quinoa (Chenopodium quinoa Willd.) genotypes using AMMI analysis. Seed and Plant. 38: 453-472. (in Persian with English abstract). Bagheri, M., Zamani, M.R., Shouride, H., Molaei, A.R., Mansourian, A. and Heydari, F. 2018. Evaluation of compatibility of quinoa genotypes in Mashhad and Isfahan. Final Research Project Report, Agricultural Research and Information Center, Registration No. 53795. (In Persian with English abstract). Gholizadeh, A., and Dehghani, H. 2016. Graphic analysis of trait relations of Iranian bread wheat germplasm under non-saline and saline conditions using the biplot method. Genetika, 48(2): 473-486. Jacobsen, S.E., Mujica, A., Jensen, C., 2003. The resistanceof quinoa (Chenopodium quinoa Willd.) to adverse abiotic factors. Food Reviews International, 19: 99-109. Karahan, T., and Akgün, I. 2020. Selection of barley (Hordeum vulgare L.) genotypes by GYT (genotype × yield × trait) biplot technique and its comparison with GT (genotype × trait). Applied Ecology and Environmental Research, 18(1):1347-1359. Kendal, E. 2020. Evaluation of some barley genotypes with genotype by yield*trait (GYT) biplot method. Agriculture and Forestry, 66 (2): 137-150. Kendal, E., Karaman, M., Tekdal, S., and Dogan, S. 2019. Analysis of promising barley (Hordeum vulgare L.) lines performance by AMMI and GGE biplot in multiple traits and environment. Applied Ecology and Environmental Research, 17(2): 5219-5233. Kroonenberg, P. M. 1995. Introduction to biplots for G×E tables. Department of mathematics, research report 51. University of Queensland. Merrick, L. F., Glover, K. D., Yabwalo, D., and Byamukama, E. 2020. Use of genotype by yield*trait (GYT) Analysis to select hard red spring wheat with elevated performance for agronomic and disease resistance traits. Crop Breeding, Genetics and Genomics, 2(2): 1-18. Miri, Kh. 2017. Evaluation of compatibility of quinoa genotypes to Iranshahr region. Final Report of the Research Project. Baluchestan Agriculture and Natural Resources Research and Training Center, Iranshahr, Iran. Agricultural Research and Extension Research Organization. (In Persian with English abstract). Mohamed Al-Naggar, A. M., Mahmoud Younis, A. S., Mohamed Atta, M., Lotfy Abd El-Moneim, M. and Sabry Al-Metwally, M. 2021. Multivariate of genetic diversity among thirty-seven Chenopodium quinoa genotypes under organic and mineral fertilzation. Plant Cell Biotechnology and Molecular Biology, 23 (7&8): 72-93. Mohammadi, R., and Amri, A. 2011. Graphic analysis of trait relations and genotype evaluation in durum wheat. Journal of Crop Improvement, 25: 680-696. Pacheco, A., Rodríguez, F., Alvarado, G., and Burgueño, J. 2017. "ADEL-R. Analysis and design of experiments with R for Windows. Version 2.0", https://hdl.handle.net/11529/10857, CIMMYT Research Data & Software Repository Network, V3. Pacheco, A., Vargas, M., Alvarado, G., Rodríguez, F., Crossa, J., and Burgueño, J. 2015. "GEA-R (Genotype x Environment Analysis with R for Windows) Version 4.1", https://hdl.handle.net/11529/10203, CIMMYT Research Data & Software Repository Network, V16. Rahmati, M., Ahmadi, A., Hossein Pour, T., Hamidiyan, K., and Reisvand, M. 2021. Evaluation of yield potential of barley genotypes and identification of traits related to improving grain yield under rainfed conditions. Iranian Journal of Dryland Agriculture, 10 (1): 57-71 (In Persian). Sepahvand, N.A., Tavazoa, M. and Kohbazi, M. 2010. Quinoa valuable plant for alimentary security and adaptation agricultural in Iran. 11th National Iranian Crop Science Congress. 24-26 Jul. 2010. Tehran, Iran. (In Persian with English abstract). Taherian, M. 2023. Identification of Superior Barley Genotypes (Hordeum vulgare L.) Based on Yield Stability and Optimal Agronomic Traits in Khorasan Razavi Province. Journal of Crop Breeding, 15 (47): 174-185 (in Persian with English abstract). Taherian, M. and Nikkhah, H. R. 2022. Analysis of yield stability, heritability and characterization of barley promising lines in Nishabour. Applied Research in Field Crops, 35 (3): 28-45(in Persian with English abstract). Taherian, M. and Nikkhah, H. R. 2022. Evaluation and Characterization of Barley Inbred Lines in Temperate Regions of Country. Journal of Crop Breeding, 14 (43):105-116 (in Persian with English abstract). Tavoosi, M. and Sepahvand, N. A. 2012. Evaluation of different genotypes of quinoa for yield and other phenological characteristics in khuzestan. 12th Iranian Genetic Congress. 21-23 May, 2012. Shahid Beheshti University, Tehran, Iran. (In Persian with English abstract). Thiam, E., Allaoui, A. and Benlhabib, O. 2021. Quinoa productivity and stability evaluation through varietal and environmental interaction. Plants, 10 (714): 1-14. Xu, N., Fok, M., Li, J., Yang, X., and Yan, W. 2017. Optimization of cotton variety registration criteria aided with a genotype- by-trait biplot analysis. Scientific Reports, 7: 17237. Yan, W. 2001. GGE biplot–A Windows application for graphical analysis of multi-environment trial data and other types of two-way data. Agronomy Journal, 93: 1111–1118. Yan, W., and Kang, M.S. 2003. GGE Biplot Analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press, Boca Raton, FL. Yan, W., and Rajcan, I. 2002. Biplot analysis of sites and trait relations of soybean in Ontario. Crop Science, 42: 11-20. | ||
|
آمار تعداد مشاهده مقاله: 633 تعداد دریافت فایل اصل مقاله: 457 |
||