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بررسی عملکرد دانه و برخی از صفات مهم زراعی در ژنوتیپ‌های بهاره خزانه بین‌المللی گندم مناطق معتدل کشور | ||
| پژوهش های کاربردی زراعی | ||
| دوره 33، شماره 4 - شماره پیاپی 129، اسفند 1399، صفحه 40-61 اصل مقاله (926.79 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/aj.2021.125628.1387 | ||
| نویسندگان | ||
| سعید باقری کیا* 1؛ فرشاد بختیار2؛ نوید شارسودا3 | ||
| 1گروه اصلاح نباتات و بیوتکنولوژی، دانشکده تولید گیاهی، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، ایران | ||
| 2استاد یار موسسه تحقیقات اصلاح و تهیه نهال و بذر، سازمان تحقیقات، ترویج و آموزش کشاورزی، کرج، ایران | ||
| 3کارشناس موسسه تحقیقات اصلاح و تهیه نهال و بذر، سازمان تحقیقات، ترویج و آموزش کشاورزی، کرج، ایران | ||
| چکیده | ||
| در آزمایش‌های چندمکانی به علت وجود اثرمتقابل ژنوتیپ در محیط انتخاب ژنوتیپ‌های دارای پایداری وسیع در مکان‌های مختلف دشوار بوده و استفاده از روش GGE بای‌پلات می‌تواند سودمند باشد. هدف از انجام این پژوهش انتخاب لاین‌های برتر گندم نان بهاره با عملکرد دانه بالا، مقاوم به بیماری‌های زنگ زرد و قهوه‌ای و دارای صفات مطلوب زراعی از میان خزانه دریافتی از مرکز بین المللی تحقیقات کشاورزی در مناطق خشک (ICARDA) در اقلیم معتدل کشور بود. برای این منظور 50 ژنوتیپ گندم نان (با احتساب رقم پارسی به عنوان شاهد) در سال زراعی 96-95 در قالب طرح بلوک‌های کامل تصادفی در دو تکرار در سه ایستگاه کرج، کرمانشاه و زرقان مورد بررسی قرار گرفتند. نتایج تجزیه واریانس مرکب نشان داد که اثرمتقابل ژنوتیپ در محیط از نظر آماری معنی‌دار بود. مقایسه میانگین ژنوتیپ‌ها نشان داد که ژنوتیپ شماره 32 بیشترین عملکرد و ژنوتیپ شماره 25 کمترین عملکرد را داشتند. بررسی هم‌زمان پایداری و عملکرد ژنوتیپ‌ها با استفاده از بای‌پلات مختصات محیط متوسط نشان داد که ژنوتیپ‌های 32، 18، 24، 28، 31، 14، 33، 19، 29 و 2 دارای بالاترین عملکرد بودند که از میان آن‌ها، ژنوتیپ‌های 32، 18، 24، 14، 29 و 2 دارای عملکرد دانه پایدارتری بودند. در نهایت با در نظر گرفتن واکنش به بیماری و سایر خصوصیات مطلوب مورد نظر، تعداد هشت ژنوتیپ با شماره‌های 32، 24، 28، 14، 33، 19، 29 و 2 به عنوان لاین‌های برتر انتخاب و به آزمایش مقایسه عملکرد مقدماتی سراسری اقلیم معتدل برای مطالعات تکمیلی هدایت شدند. | ||
| کلیدواژه‌ها | ||
| بای‌پلات؛ تنوع؛ سازگاری؛ گزینش؛ گندم نان | ||
| عنوان مقاله [English] | ||
| Evaluation of grain yield and some important agronomic traits in spring wheat international nurseries in moderate climate regions of Iran. | ||
| نویسندگان [English] | ||
| Saeed Bagherikia1؛ Farshad Bakhtiar2؛ Navid Sharsoda3 | ||
| 1Plant Breeding and Biotechnology Department, Faculty of Plant Production, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran. | ||
| 2Assistant Professor, Seed and plant Improvement Institute, Agriculture Research Education and Extension Organization (AREEO), Karaj, Iran | ||
| 3Researcher, Seed and plant Improvement Institute, Agriculture Research Education and Extension Organization (AREEO), Karaj, Iran | ||
| چکیده [English] | ||
| Introduction: Variation and selection play a key role in breeding programs. The proper selection is related to the desired variation in the desired trait. In order to take advantage of the existing variation; the evaluation of germplasm resources is necessary. Genotype–environment interactions are particularly important for breeders and one of the complex issues in breeding programs is the selection of high yielding and stable crop genotypes. Therefore, knowledge of the genotype–environment interactions is a necessity to evaluate new cultivars in different environments. GGE biplot model is one of the most used multivariate methods in the study of genotype–environment interactions that is performed based on principal component analysis (Yan et al., 2010). Materials and Methods: In order to select the superior lines from the elite spring bread wheat yield trial (17ESBWYT), 50 spring bread wheat lines (considering Parsi culivar as a local check) were studied at three stations (Karaj, Kermanshah and Zarghan), which represent moderate climate regions of Iran. The experiments were conducted in the randomized complete block design (RCBD) with three replications in the 2016- 2017 growing season. The plant materials had been received from the international center for agricultural research in the dry areas (ICARDA). The measured traits included days to heading (DHE), days to maturity (DMA), plant height (PLH), thousand grain weight (TKW), seed filling period (SFP), seed filling rate (SFR), grain yield (GY), relative yield to mean (RYM), relative yield to local check (RYLC) and plant response to yellow rust (YR) and leaf rust (LR). Homogeneity of the variances in different environments was tested following Bartlett's test. Then, the combined analysis of variance and stability analysis were performed using GGE biplot method. Data was analyzed using GGE biplot4, heatmapper, SAS and Excel. Results and Discussion: The combined analysis of variance confirmed that the effects of environment, genotype and interaction between them were statistically significant. Mean comparison of grain yield showed that the highest grain yield (6.489-ton ha-1 ) was achieved with the genotype no 32 and the lowest grain yield (4.728-ton ha-1) was related to the genotype no 25. Total mean of grain yield at stations of Karaj, Kermanshah and Zarghan was 6.589, 5.317 and 4.753-ton ha-1 respectively. The correlation biplot of the environments revealed that the location of Kermanshah had a positive correlation with Karaj and Zarghan, because the angles of the vectors were less than 90◦, exhibiting a positive correlation among the environments. Also, there was a weak correlation between Karaj and Zarghan, indicating that two environments have been almost independent of each other because the angle of the vectors was 90◦ (Yan & Rajcan, 2002). The yield and stability of the genotypes were evaluated using the average-environment coordination (AEC) view. Presence of genotypes on this axis is approximation of grain yield (Yan et al., 2000). Hence, the genotypes no 32, 18, 24, 28, 31, 14, 33, 19, 29 and 2 had the highest grain yield. The vertical axis of AEC biplot also showed the interaction between genotype and environment and determined the stability of the genotypes. Therefore, among the genotypes that gave a high grain yield, the genotypes no 32, 18, 24, 14, 29 and 2 were the most stable for grain yield. The final selection of the genotypes was carried out considering the response of genotypes to yellow rust and leaf rust and other desirable traits. Conclusion: In the current study, 50 genotypes of bread wheat were evaluated in terms of grain yield, response to yellow rust and leaf rust and some desirable agronomic traits at three stations (Karaj, Kermanshah and Zarghan) representing moderate climate regions of Iran. Considering the results of GGE biplot method and response to yellow rust, leaf rust and other desirable agronomic traits, eight genotypes: no 32, 24, 28, 14, 33, 19, 29, and 2 were selected as superior lines and were conducted to preliminary regional wheat yield trial (PRYWT) in the moderate climate regions of Iran. It is hoped that in the coming years a new cultivar will be released among the selected genotypes in wheat breeding programs in moderate climate regions of Iran, after preliminary and adaptation experiments. | ||
| کلیدواژه‌ها [English] | ||
| Biplot, bread wheat, compatibility, selection, variation | ||
| مراجع | ||
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Ahmadi, J., Mohammadi, A., and Najafi Mirak, T. 2012. Targeting promising bread wheat (Triticum aestivum L.) lines for cold climate growing environments using AMMI and SREG GGE Biplot analyses. Journal of Agricultural Science and Technology, 14(3):645-657. Bagherikia, S., Karimzadeh, G., and Naghavi, M.R. 2013. Identification of wheat rust resistance genes (Lr26, Sr31, Yr9) using specific PCR. Crop Biotechnolgy, 3(5): 129-138. (In Persian with English Summary). Bagherikia, S., Karimzadeh, G., and Naghavi, M.R. 2014. Distribution of 1AL. 1RS and 1BL. 1RS wheat-rye translocations in Triticum aestivum using specific PCR. Biochemical systematics and ecology, 55: 20-26. Berzonsky, W.A., and Francki, M.G. 1999. Biochemical, molecular, and cytogenetic technologies for characterizing 1RS in wheat: A review. Euphytica, 108: 1-19. Blanche, S.B., and Myers, G.O. 2006. Identifying discriminating locations for cultivar selection in Louisiana. Crop Science, 46(2):946-949. Camargo, A.V., Mott, R., Gardner, K.A., Mackay, I.J., Corke, F., Doonan, J. H., Kim, J.T., and Bentley, A. R. 2016. Determining phenological patterns associated with the onset of senescence in a wheat MAGIC mapping population. Frontiers in Plant Science, 7: 1540. Dehghani, H., Ebadi, A., and Yousefi, A. 2006. Biplot analysis of genotype by environment interaction for barley yield in Iran. Agronomy Journal, 98(2):388-393. Dehghani, H., Sabaghnia, N., and Moghaddam, M. 2009. Interpretation of genotype-by-environment interaction for late maize hybrids’ grain yield using a biplot method. Turkish Journal of Agriculture and Forestry, 33(2):139-148. Dryland Agricultural Research Institute (DARI) Available at Web sitehttp://dari.areeo.ac.ir/HomePage.aspx?TabID=12462&Site=dari.areeo.ac&Lang=fa-IR (accessed 18 february 2020). Egli, D.B. 2004. Seed-fill duration and yield of grain crops. In: Sparks, D.L (ed.) Advances in Agronomy. 83:243-279 PP., Elsevier Press, UK. Elias, A.A., Robbins, K.R., Doerge, R., and Tuinstra M.R. 2016. Half a century of studying genotype× environment interactions in plant breeding experiments. Crop Science, 56(5):2090-2105. Esmaeilzadeh Moghaddam, M., Tahmasebi, S., Lotf Ali Ayeneh, G.H.A., Akbari Moghadam, H., Mahmoudi, K.H., Sayyahfar, M., Tabib Ghaffari, S.M., and Zali, H. 2018. Evaluation of grain yield stability of bread wheat (Triticum aestivum L.) promising lines in warm and dry regions of Iran. Iranian Journal of Crop Sciences, 20(1): 270-283. (In Persian with English Summary). Farshadfar, E., Mahtabi, E., and Jowkar, M.M. 2013. Evaluation of genotype× environment interaction in chickpea genotypes using path analysis. International Journal of Advanced Biological and Biomedical Research, 1(6):583-593. Graybosch, R. A. 2001. Mini review: uneasy unions: quality effects of rye chromatin transfers to wheat. Journal of Cereal Science, 33: 3-16. Jagadish, K.S., Kishor, K., Polavarapu, B., Bahuguna, R.N., von Wirén, N., and Sreenivasulu, N. 2015. Staying alive or going to die during terminal senescence-an enigma surrounding yield stability. Frontiers in Plant Science, 6: 1070. Kang, M.S. 1997. Using genotype-by-environment interaction for crop cultivar development. In: Sparks, D.L (ed.) Advances in agronomy. 62: 199-252 pp., Academic Press, USA. Kang, M.S. 2002. Genotype–environment interaction: progress and prospects. In: Kang, M.S (ed.) Quantitative genetics, genomics, and plant breeding. 221-243 pp., CABI International, UK. Koocheki, A. R., Sorkhi Laleloo, B., and Eslamzadeh Hesari, M.R. 2012. Yield stability of barley elite genotypes in cold regions of iran using GGE biplot. Seed and Plant Improvement Journal, 28 (4) 533-543. (In Persian with English Summary). Mohammadi, M., Hosseinpour, T., Armion, M., Khanzadeh, H., and Ghojogh, H. 2016. Analysis of genotype, environment and genotype× environment interaction in bread wheat genotypes using GGE biplot. Agricultural Communications, 4(3):1-8. Mohammadi, R., Armion, M., Sadeghzadeh, B., Golkari, S., Khalilzadeh, G.H., Ahmadi, H., Abedi-Asl, G.H., and Eskandari, M. 2016b. Assessment of grain yield stability and adaptability of rainfed durum wheat breeding lines. Applied Field Crops Research, 29 (4): 25-42. (In Persian with English Summary). Mohammadi, R., Farshadfar, E., and Amri, A. 2015. Interpreting genotype× environment interactions for grain yield of rainfed durum wheat in Iran. The Crop Journal, 3(6):526-535. Mohammadi, R., Haghparast, R., Amri, A., and Ceccarelli, S. 2010. Yield stability of rainfed durum wheat and GGE biplot analysis of multi-environment trials. Crop and Pasture Science, 61(1):92-101. Najafi Mirak, T., Dastfal, M., Andarzian, B., Farzadi, H., Bahari, M., and Zali, H. 2018. Evaluation of durum wheat cultivars and promising lines for yield and yield stability in warm and dry areas using AMMI model and GGE biplot. Journal of Crop Breeding, 10(28): 1-12. (In Persian with English Summary). Omrani, S., Mohammad Naji, A., and Esmaeilzadeh Moghaddam, M. 2017. Yield stability analysis of promising bread wheat lines in southern warm and dry agroclimatic zone of Iran using GGE biplot model. Journal of Crop Breeding, 23(9): 157-165. (In Persian with English Summary). Peterson, R.F., Campbell, A.B., and Hannah, A.E. 1948. A diagrammatic scale for estimating rust intensity on leaves and stems of cereals. Canadian journal of research, 26(5):496-500. Poehlman, J.M. 2013. Breeding field crops: Springer Science & Business Media, USA, 723 pp. Pourdad, S.S., and Jamshid Moghaddam, M., 2013. Study on genotype × environment interaction through GGE biplot for seed yield in spring rapeseed (Brassica napus L.) in rain-fed condition. Journal of Crop Breeding, 5(12): 1-14. (In Persian with English Summary). Rabinovich, S. 1998. Importance of wheat-rye translocations for breeding modern cultivar of Triticum aestivum L. Euphytica, 100: 323-340. Reif, J.C., Zhang, P., Dreisigacker, S., Warburton, M.L., van Ginkel, M., Hoisington, D., Bohn, M., and Melchinger, A.E. 2005. Wheat genetic diversity trends during domestication and breeding. Theoretical and Applied Genetics, 110(5):859-864. Roozeboom, K.L., Schapaugh, W.T., Tuinstra, M.R., Vanderlip, R.L., and Milliken, G.A. 2008. Testing wheat in variable environments: genotype, environment, interaction effects, and grouping test locations. Crop Science, 48(1):317-330. Rubenstein, K.D., and Heisey, P. 2003. Plant genetic resources: New rules for international exchange. Bioversity's Regional Office for the Americas, IPGRI. Villa Gualino, Turin, Italy 63. Seed and Plant Improvement Institute (SPII) Available at Web site http://spii.ir/HomePage.aspx?TabID=5232&Site=DouranPortal&Lang=fa-IR (accessed 30 february 2019a). Seed and Plant Improvement Institute (SPII) Available at Web site http://spii.ir/_DouranPortal/documents/vizhehnameh/%D9%88%DB%8C%DA%98%D9%87%20%D9%86%D8%A7%D9%85%D9%87%20%D8%B3%D9%88%D9%85%DB%8C%D9%86%20%D8%AC%D8%B4%D9%86%D9%88%D8%A7%D8%B1%D9%87%20%20%D8%A7%D8%B1%D9%82%D8%A7%D9%85.pdf (accessed 30 february 2019b). Shahryari Nasab, M., Chogan, R., Khodarahmi, M., Masomi, A., and Khavari Khorasani, S. 2016. Genotype× environment interaction for grain yield of maize hybrids using the GGE biplot. Journal of Crop Breeding, 7(16): 123-129. (In Persian with English Summary). Sharma, S., DeMason, D. A., Ehdaie, B., Lukaszewski, A. J., and Waines, J. G. 2010. Dosage effect of the short arm of chromosome 1 of rye on root morphology and anatomy in bread wheat. Journal of Experimental Botany, 61: 2623-2633. Simmonds, J., Scott, P., Leverington-Waite, M., Turner, A.S., Brinton, J., Korzun, V., Snape, J., and Uauy, C., 2014. Identification and independent validation of a stable yield and thousand grain weight QTL on chromosome 6A of hexaploid wheat (Triticum aestivum L.). BMC Plant Biology, 14(1), p.191. Singh, B.D. 2015. Plant breeding: principles and methods: Kalyani publishers, India. Trubacheeva, N., Rosseeva, L., Belan, I., Osadchaya, T., Kravtsova, L., Kolmakov, Y. V., Blokhina, N., and Pershina, L. 2011. Characteristics of common wheat cultivars of West Siberia carrying the wheat-rye 1RS.1BL translocation. Russian Journal of Genetics, 47: 13-18. Yan, W. 2001. GGEbiplot-a Windows application for graphical analysis of multienvironment trial data and other types of two-way data. Agronomy Journal, 93(5):1111-1118. Yan, W., and Kang, M.S. 2002. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists: CRC press, USA, 288 PP. Yan, W., and Rajcan, I. 2002. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science, 42(1):11-20. Yan, W., Frégeau-Reid, J., Pageau, D., Martin, R., Mitchell-Fetch, J., Etienne, M., Rowsell, J., Mike Price, P.S., and de Haan, B.. 2010. Identifying essential test locations for oat breeding in eastern Canada. Crop Science, 50(2):504-515. Yan, W., Hunt, L.A, Sheng, Q., and Szlavnics, Z. 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science, 40(3):597-605. Zali, H., Sofalian, O., Hasanloo, T., and Asghari, A. 2016. AMMI and GGE biplot analysis of yield stability and drought tolerance in Brassica napus L. Agricultural Communications, 4(1):1-8. | ||
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آمار تعداد مشاهده مقاله: 501 تعداد دریافت فایل اصل مقاله: 331 |
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