M. Roostaei, J. Jafarzadeh, E. Roohi, Hossein Nazary, R. Rajabi, R. Mohammadi, G. Khalilzadeh, F. Seif, Seyyed Mohammad Mehdi Mirfatah, S. S. Amiri, Hoosein Hatamzadeh, M. Ahmadi
{"title":"雨养冬小麦基因型与环境互作及产量稳定性分析","authors":"M. Roostaei, J. Jafarzadeh, E. Roohi, Hossein Nazary, R. Rajabi, R. Mohammadi, G. Khalilzadeh, F. Seif, Seyyed Mohammad Mehdi Mirfatah, S. S. Amiri, Hoosein Hatamzadeh, M. Ahmadi","doi":"10.1017/S0014479722000345","DOIUrl":null,"url":null,"abstract":"Abstract The genotype × environment (GE) interaction analysis is fundamental in crop breeding programs to guide selection and for recommendation of high performing and stable genotypes for breeding objectives. This study aimed at quantifying the GE interaction effects and determines grain yield stability among winter bread wheat genotypes under rainfed conditions of Iran. Twenty-four winter wheat genotypes were evaluated under nine test locations using a randomized complete blocks design with four replications during three cropping seasons (2019–21). The additive main effects and multiplicative interaction (AMMI) model and several parametric and nonparametric stability statistics were applied for analysis of grain yield data collected from the experiments. AMMI analysis of variance for grain yield revealed significant effects (p < 0.01) for genotype, environment, and GE interaction. The environment was the main source of variation and accounted for 83.5% of the total yield variation, followed by GE (6.5%) and genotype (1.0%) effects. The AMMI biplot analysis indicated the genotypes G3, G23, G22, G10, and G19 as high yielding with stability performance across environments. Genotypes G14, G13, G20, and G9 showed large positive interaction with the environments featuring the highest rainfall during growing season, while genotypes G7, G6, and G21 had a large positive interaction with environments with low rainfall. Spearman’s rank correlation analysis revealed that the AMMI stability value, Shukla’s stability variance (σ2 i), Wricke’s ecovalence (W2 i), coefficient of determination (R2 i), variance in regression deviations (S2 di), and nonparametric statistic of S2 (i) were not correlated with mean yield in tested genotypes, showing they are related to static/biological concept of stability. In contrast, the genotypic superiority index (Pi) and regression coefficient (bi) were significantly correlated (p < 0.01) with mean yield and corresponded to dynamic/agronomic concept of stability. These findings suggest that selection of genotypes should be considered based on selection objectives of using the various stability parameters described here. In conclusion, the selected genotypes in this study should be recommended as new cultivars or parental lines for grain yield and stability improvement under rainfed conditions of Iran or similar agro-ecologies.","PeriodicalId":12245,"journal":{"name":"Experimental Agriculture","volume":" ","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2022-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Genotype × environment interaction and stability analyses of grain yield in rainfed winter bread wheat\",\"authors\":\"M. Roostaei, J. Jafarzadeh, E. Roohi, Hossein Nazary, R. Rajabi, R. Mohammadi, G. Khalilzadeh, F. Seif, Seyyed Mohammad Mehdi Mirfatah, S. S. Amiri, Hoosein Hatamzadeh, M. Ahmadi\",\"doi\":\"10.1017/S0014479722000345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The genotype × environment (GE) interaction analysis is fundamental in crop breeding programs to guide selection and for recommendation of high performing and stable genotypes for breeding objectives. This study aimed at quantifying the GE interaction effects and determines grain yield stability among winter bread wheat genotypes under rainfed conditions of Iran. Twenty-four winter wheat genotypes were evaluated under nine test locations using a randomized complete blocks design with four replications during three cropping seasons (2019–21). The additive main effects and multiplicative interaction (AMMI) model and several parametric and nonparametric stability statistics were applied for analysis of grain yield data collected from the experiments. AMMI analysis of variance for grain yield revealed significant effects (p < 0.01) for genotype, environment, and GE interaction. The environment was the main source of variation and accounted for 83.5% of the total yield variation, followed by GE (6.5%) and genotype (1.0%) effects. The AMMI biplot analysis indicated the genotypes G3, G23, G22, G10, and G19 as high yielding with stability performance across environments. Genotypes G14, G13, G20, and G9 showed large positive interaction with the environments featuring the highest rainfall during growing season, while genotypes G7, G6, and G21 had a large positive interaction with environments with low rainfall. Spearman’s rank correlation analysis revealed that the AMMI stability value, Shukla’s stability variance (σ2 i), Wricke’s ecovalence (W2 i), coefficient of determination (R2 i), variance in regression deviations (S2 di), and nonparametric statistic of S2 (i) were not correlated with mean yield in tested genotypes, showing they are related to static/biological concept of stability. In contrast, the genotypic superiority index (Pi) and regression coefficient (bi) were significantly correlated (p < 0.01) with mean yield and corresponded to dynamic/agronomic concept of stability. These findings suggest that selection of genotypes should be considered based on selection objectives of using the various stability parameters described here. 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Genotype × environment interaction and stability analyses of grain yield in rainfed winter bread wheat
Abstract The genotype × environment (GE) interaction analysis is fundamental in crop breeding programs to guide selection and for recommendation of high performing and stable genotypes for breeding objectives. This study aimed at quantifying the GE interaction effects and determines grain yield stability among winter bread wheat genotypes under rainfed conditions of Iran. Twenty-four winter wheat genotypes were evaluated under nine test locations using a randomized complete blocks design with four replications during three cropping seasons (2019–21). The additive main effects and multiplicative interaction (AMMI) model and several parametric and nonparametric stability statistics were applied for analysis of grain yield data collected from the experiments. AMMI analysis of variance for grain yield revealed significant effects (p < 0.01) for genotype, environment, and GE interaction. The environment was the main source of variation and accounted for 83.5% of the total yield variation, followed by GE (6.5%) and genotype (1.0%) effects. The AMMI biplot analysis indicated the genotypes G3, G23, G22, G10, and G19 as high yielding with stability performance across environments. Genotypes G14, G13, G20, and G9 showed large positive interaction with the environments featuring the highest rainfall during growing season, while genotypes G7, G6, and G21 had a large positive interaction with environments with low rainfall. Spearman’s rank correlation analysis revealed that the AMMI stability value, Shukla’s stability variance (σ2 i), Wricke’s ecovalence (W2 i), coefficient of determination (R2 i), variance in regression deviations (S2 di), and nonparametric statistic of S2 (i) were not correlated with mean yield in tested genotypes, showing they are related to static/biological concept of stability. In contrast, the genotypic superiority index (Pi) and regression coefficient (bi) were significantly correlated (p < 0.01) with mean yield and corresponded to dynamic/agronomic concept of stability. These findings suggest that selection of genotypes should be considered based on selection objectives of using the various stability parameters described here. In conclusion, the selected genotypes in this study should be recommended as new cultivars or parental lines for grain yield and stability improvement under rainfed conditions of Iran or similar agro-ecologies.
期刊介绍:
With a focus on the tropical and sub-tropical regions of the world, Experimental Agriculture publishes the results of original research on field, plantation and herbage crops grown for food or feed, or for industrial purposes, and on farming systems, including livestock and people. It reports experimental work designed to explain how crops respond to the environment in biological and physical terms, and on the social and economic issues that may influence the uptake of the results of research by policy makers and farmers, including the role of institutions and partnerships in delivering impact. The journal also publishes accounts and critical discussions of new quantitative and qualitative methods in agricultural and ecosystems research, and of contemporary issues arising in countries where agricultural production needs to develop rapidly. There is a regular book review section and occasional, often invited, reviews of research.