Volume 17, Issue 1 (3-2026)
J Crop Breed 2026, 17(1): 129-141 |
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Sasani S, Saed-Moucheshi A. (2026). Screening Elite Genotypes of Durum Wheat Based on Univariate and Multivariate Stability Models under Unpredictable Environments. J Crop Breed. 17(1), 129-141. doi:10.61186/jcb.17.1.129
URL: http://jcb.sanru.ac.ir/article-1-1555-en.html
URL: http://jcb.sanru.ac.ir/article-1-1555-en.html
1- Crop and Horticultural Science Research Department, Kermanshah Agricultural and Natural Resources Research and Education Center, AREEO, Kermanshah, Iran
Abstract: (473 Views)
Extended Abstract
Background: As one of the most influential cereals, wheat is among the most important food sources in Asian countries, including Iran, which has more cultivated area than other plant crops in Iran. Durum wheat is a type of tetraploid wheat that is particularly important for use in the food industry, especially pasta production. Durum wheat is a good source of dietary fiber, protein, and a wide range of vitamins and minerals such as iron, magnesium, and B vitamins, making it a healthy and nutritious food. This product also has a special economic importance for Iran and is a strategic product that has a significant impact on the country's agricultural economy. Based on the stability and productivity of plants in changing environmental conditions, plant breeders can develop products that are more flexible and have good stability even in the face of climate change and other environmental challenges. The upcoming study aims to investigate the durum wheat genotypes produced by Iranian breeders and their response to environmental changes to make it possible to introduce these genotypes as cultivars that can be planted by farmers.
Methods: To verify the feasibility of introducing new durum wheat varieties with high yields and stable performance in different environmental conditions, 18 genotypes of durum wheat along with two control varieties (Hana and Parsi) were studied in four crop years at the research station of the Agricultural Research and Training Center and The natural resources of Kermanshah Province (Islamabad West Agricultural Research Station) based on a completely randomized block design in three replications and four consecutive years from 2013 to 2016. After adjusting the data, composite variance analysis was performed considering year × genotype in relation to grain yield. Due to the significance of the genotype × environment interaction effect, the averages were compared for genotypes and the environment, as well as for their interaction, and stability analysis was calculated by univariate and multivariate methods. The univariate methods included environmental variance parameters (S2), coefficient of environmental changes related to all investigated environments (CV), Rick's equivalence (W2), Shukla's stability variance (Shukla-Var), regression coefficients based on the Eberhart-Russell model to analyze the genotype × environment interaction effect on the regression components (b), the standard error value or deviation from the regression line in the Eberhart-Russell model (Sd), and the explanatory coefficient value of the regression model in the Eberhart-Russell model (R2). Moreover, multivariate methods, including the AMMI method, the GGE method, and the heat mapping method, were used to analyze the stability of genotypes. SAS software was used for calculations related to composite analysis of variance (ANOVA) and mean comparison. Univariate stability calculations were done using the codes written by the authors in the matrix language of SAS software, which is known as Interactive Matrix Language. R software and the agricolae library were used for calculations related to multivariate methods in AMMI and GGE models. Heat mapping was also done in R software with the ggcorrplot library.
Results: The composite ANOVA in this research showed the significance of the main effects of genotype and environment alone and the genotype × environment interaction effect in grain yield. Due to the significant genotype × environment interaction effect, the response of genotypes to different environments is different. Thus, analysis of stability was carried out by univariate and multivariate methods to allow for the introduction of new durum cultivars with high potential in terms of grain yield and production stability in different environments. The heat mapping results showed that this method could separate the three environmental groups and confirmed the average comparison results. The number of separated groups of genotypes based on experimental environments also included four different groups. The different stability methods used in this research also showed differences in relation to the stability and sensitivity of genotypes. Therefore, the ranking method was used based on different sustainability models. Accordingly, genotypes 3, 13, 14, and 16 produced high final yields and good stability (above average), and genotypes 18 and 19 showed high stability and good total yields based on all stability methods. The first four genotypes, with good stability, produced a higher average yield than both controls, but the next two genotypes, with high stability, showed a higher yield than the Hana variety and less than the Parsi variety.
Conclusion: Different methods of univariate stability, including environmental variance, coefficient of environmental change, Shokla variance, the regression sum of squares method, regression coefficient, the residual of the regression model, and explanatory coefficient, along with multivariate methods, including AMMI and GGE models as well as the heat mapping method were examined to estimate the stability and the response of 18 durum wheat genotypes along with two control varieties (Hana and Parsi). It was found that heat mapping had a good performance in assessing the response of the genotypes to environmental conditions and could separate three environmental groups, which confirmed the results of the average comparison. The number of separated groups of genotypes based on experimental environments included four different groups. Based on the stability analysis results, genotypes 14, 16, 13, and 3 produced high final yields and good stability (above average) based on all stability methods, and genotypes 19 and 18 showed high stability and good total yields (above average). The first four genotypes, with good stability, produced higher average yields than both controls, but the next two genotypes, with high stability, showed higher yields than the Hana variety and less than the Parsi variety. Finally, it is suggested that these six genotypes enter the regional research-promotion tests for further investigation so that the most suitable ones are finally introduced as a new variety of durum wheat.
Background: As one of the most influential cereals, wheat is among the most important food sources in Asian countries, including Iran, which has more cultivated area than other plant crops in Iran. Durum wheat is a type of tetraploid wheat that is particularly important for use in the food industry, especially pasta production. Durum wheat is a good source of dietary fiber, protein, and a wide range of vitamins and minerals such as iron, magnesium, and B vitamins, making it a healthy and nutritious food. This product also has a special economic importance for Iran and is a strategic product that has a significant impact on the country's agricultural economy. Based on the stability and productivity of plants in changing environmental conditions, plant breeders can develop products that are more flexible and have good stability even in the face of climate change and other environmental challenges. The upcoming study aims to investigate the durum wheat genotypes produced by Iranian breeders and their response to environmental changes to make it possible to introduce these genotypes as cultivars that can be planted by farmers.
Methods: To verify the feasibility of introducing new durum wheat varieties with high yields and stable performance in different environmental conditions, 18 genotypes of durum wheat along with two control varieties (Hana and Parsi) were studied in four crop years at the research station of the Agricultural Research and Training Center and The natural resources of Kermanshah Province (Islamabad West Agricultural Research Station) based on a completely randomized block design in three replications and four consecutive years from 2013 to 2016. After adjusting the data, composite variance analysis was performed considering year × genotype in relation to grain yield. Due to the significance of the genotype × environment interaction effect, the averages were compared for genotypes and the environment, as well as for their interaction, and stability analysis was calculated by univariate and multivariate methods. The univariate methods included environmental variance parameters (S2), coefficient of environmental changes related to all investigated environments (CV), Rick's equivalence (W2), Shukla's stability variance (Shukla-Var), regression coefficients based on the Eberhart-Russell model to analyze the genotype × environment interaction effect on the regression components (b), the standard error value or deviation from the regression line in the Eberhart-Russell model (Sd), and the explanatory coefficient value of the regression model in the Eberhart-Russell model (R2). Moreover, multivariate methods, including the AMMI method, the GGE method, and the heat mapping method, were used to analyze the stability of genotypes. SAS software was used for calculations related to composite analysis of variance (ANOVA) and mean comparison. Univariate stability calculations were done using the codes written by the authors in the matrix language of SAS software, which is known as Interactive Matrix Language. R software and the agricolae library were used for calculations related to multivariate methods in AMMI and GGE models. Heat mapping was also done in R software with the ggcorrplot library.
Results: The composite ANOVA in this research showed the significance of the main effects of genotype and environment alone and the genotype × environment interaction effect in grain yield. Due to the significant genotype × environment interaction effect, the response of genotypes to different environments is different. Thus, analysis of stability was carried out by univariate and multivariate methods to allow for the introduction of new durum cultivars with high potential in terms of grain yield and production stability in different environments. The heat mapping results showed that this method could separate the three environmental groups and confirmed the average comparison results. The number of separated groups of genotypes based on experimental environments also included four different groups. The different stability methods used in this research also showed differences in relation to the stability and sensitivity of genotypes. Therefore, the ranking method was used based on different sustainability models. Accordingly, genotypes 3, 13, 14, and 16 produced high final yields and good stability (above average), and genotypes 18 and 19 showed high stability and good total yields based on all stability methods. The first four genotypes, with good stability, produced a higher average yield than both controls, but the next two genotypes, with high stability, showed a higher yield than the Hana variety and less than the Parsi variety.
Conclusion: Different methods of univariate stability, including environmental variance, coefficient of environmental change, Shokla variance, the regression sum of squares method, regression coefficient, the residual of the regression model, and explanatory coefficient, along with multivariate methods, including AMMI and GGE models as well as the heat mapping method were examined to estimate the stability and the response of 18 durum wheat genotypes along with two control varieties (Hana and Parsi). It was found that heat mapping had a good performance in assessing the response of the genotypes to environmental conditions and could separate three environmental groups, which confirmed the results of the average comparison. The number of separated groups of genotypes based on experimental environments included four different groups. Based on the stability analysis results, genotypes 14, 16, 13, and 3 produced high final yields and good stability (above average) based on all stability methods, and genotypes 19 and 18 showed high stability and good total yields (above average). The first four genotypes, with good stability, produced higher average yields than both controls, but the next two genotypes, with high stability, showed higher yields than the Hana variety and less than the Parsi variety. Finally, it is suggested that these six genotypes enter the regional research-promotion tests for further investigation so that the most suitable ones are finally introduced as a new variety of durum wheat.
Keywords: AMMI, Clustering, Environmental Coefficient of Variation, GGE Biplot, Heatmap, Univariate Stability Analysis
Type of Study: Research |
Subject:
اصلاح نباتات، بیومتری
Received: 2024/05/10 | Accepted: 2024/10/27
Received: 2024/05/10 | Accepted: 2024/10/27
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