Volume 17, Issue 1 (3-2026)
J Crop Breed 2026, 17(1): 25-36 |
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Mehripour Azbarmi H, Saba J, Alizadeh B, Gholizadeh A, Shekari F. (2026). Pattern Analysis of the Genotype × Environment Interaction of Seed Yield in Winter Oilseed Rape (WOSR) Mutant Lines using the AMMI Multivariate Method. J Crop Breed. 17(1), 25-36. doi:10.61186/jcb.17.1.25
URL: http://jcb.sanru.ac.ir/article-1-1560-en.html
URL: http://jcb.sanru.ac.ir/article-1-1560-en.html
1- Department of Plant Production and Genetics, Faculty of Agriculture, University of Zanjan, Zanjan, Iran
2- Department of Oil Crops Research, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
3- Department of Crop and Horticultural Science Research, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran
2- Department of Oil Crops Research, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
3- Department of Crop and Horticultural Science Research, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran
Abstract: (406 Views)
Extended Abstract
Background: Oilseeds are one of the most important sources of energy all over the world. As an important crop, rapeseed oil has high nutritional and economic value. Rapeseed is one of the most important sources of vegetable oil in the world, and its seed contains more than 40% oil. The meal obtained from oil extraction contains more than 35% protein, and currently it ranks third among oil plants after soybean and oil palm in the world. The economic yield of rapeseed can be increased by using new and high-yield varieties. Evaluating promising advanced lines of soybean under different environmental conditions is essential in identifying and selecting superior lines with high and stable yield potential. The genotype × environment interaction is a major challenge in the study of quantitative traits because it reduces yield stability in different environments, complicates the interpretation of genetic experiments, and makes predictions difficult. Therefore, it is very important to know the type and nature of the interaction effect and achieve verities that have the least role in creating interaction effects. Various methods have been introduced to evaluate the interaction effect, each of which examines the nature of the interaction effect from a specific point of view. The multivariate method of additive main effects and multiplicative interaction (AMMI) is a method with suitable efficiency to investigate the genotype × environment interaction effect and provides good information about studied genotypes and environments. This study aimed to investigate the genotype × environment interaction effect using the AMMI method to evaluate genotypes, environments, and relationships between genotypes and environments. Finally, this study sought to identify stable rapeseed genotypes with high grain yields under different environmental conditions.
Methods: Nine lines and six cultivars were evaluated in a randomized complete block design with three replications in six experimental field stations (Karaj, Kermanshah, Isfahan, Hamadan, Zarghan, and Qazvin) during two cropping seasons. The genotype × environment interaction was analyzed using the AMMI method. Plants were harvested at maturity, and then the seed yield was recorded for each genotype at each test environment.
Results: Results of the combined analysis of variance (ANOVA) indicated that the effects of environments (E), genotypes (G), and the genotype × environment (G × E) interaction were significant on seed yield. The results of the ANOVA indicated that 77.56, 3.96, and 18.48% of total variation were related to the E, G, and G × E interaction effects, respectively. The results showed that the first four principal components of AMMI were significant and described 80.35% of the variance of the G × E interaction. The results showed that the average yield of the studied genotypes was in the range of 2669-3398 with a total average of 3065 kg.ha-1. Genotypes G1 and G15 produced the lowest and highest seed yields, respectively, and the average seed yields of genotypes G3, G4, G6, G7, G8, and G9 were higher than the total average seed yield. Based on the average of sum ranks (ASR), G2, G11, G6, and G9 genotypes with the lowest ASR values were the most stable, while G10, G12, G3, and G13 genotypes with the highest ASR values were the most unstable genotypes. Among the stable genotypes, G6 and G9 were recognized as genotypes with good seed yield and general compatibility due to their higher average seed yields. Furthermore, the Zarghan location was recognized as the most ideal environment for distinguishing and separating rapeseed genotypes due to its high interaction. The cluster analysis classified the studied environments into three groups. The Isfahan, Hamedan, Zarghan, and Karaj locations were placed in a group in both years, indicating that these locations had high predictability and repeatability power.
Conclusion: Based on the results of the AMMI method, G6 and G9 were better than the other genotypes for seed yield and stability and showed high general adaptation to all environments. Additionally, the Zarghan location was recognized as the most ideal environment due to its high interaction for distinguishing and separating rapeseed genotypes. Generally, the results showed the efficiency of the AMMI method in investigating the G × E interaction effect and providing good information about the studied genotypes and environments.
Background: Oilseeds are one of the most important sources of energy all over the world. As an important crop, rapeseed oil has high nutritional and economic value. Rapeseed is one of the most important sources of vegetable oil in the world, and its seed contains more than 40% oil. The meal obtained from oil extraction contains more than 35% protein, and currently it ranks third among oil plants after soybean and oil palm in the world. The economic yield of rapeseed can be increased by using new and high-yield varieties. Evaluating promising advanced lines of soybean under different environmental conditions is essential in identifying and selecting superior lines with high and stable yield potential. The genotype × environment interaction is a major challenge in the study of quantitative traits because it reduces yield stability in different environments, complicates the interpretation of genetic experiments, and makes predictions difficult. Therefore, it is very important to know the type and nature of the interaction effect and achieve verities that have the least role in creating interaction effects. Various methods have been introduced to evaluate the interaction effect, each of which examines the nature of the interaction effect from a specific point of view. The multivariate method of additive main effects and multiplicative interaction (AMMI) is a method with suitable efficiency to investigate the genotype × environment interaction effect and provides good information about studied genotypes and environments. This study aimed to investigate the genotype × environment interaction effect using the AMMI method to evaluate genotypes, environments, and relationships between genotypes and environments. Finally, this study sought to identify stable rapeseed genotypes with high grain yields under different environmental conditions.
Methods: Nine lines and six cultivars were evaluated in a randomized complete block design with three replications in six experimental field stations (Karaj, Kermanshah, Isfahan, Hamadan, Zarghan, and Qazvin) during two cropping seasons. The genotype × environment interaction was analyzed using the AMMI method. Plants were harvested at maturity, and then the seed yield was recorded for each genotype at each test environment.
Results: Results of the combined analysis of variance (ANOVA) indicated that the effects of environments (E), genotypes (G), and the genotype × environment (G × E) interaction were significant on seed yield. The results of the ANOVA indicated that 77.56, 3.96, and 18.48% of total variation were related to the E, G, and G × E interaction effects, respectively. The results showed that the first four principal components of AMMI were significant and described 80.35% of the variance of the G × E interaction. The results showed that the average yield of the studied genotypes was in the range of 2669-3398 with a total average of 3065 kg.ha-1. Genotypes G1 and G15 produced the lowest and highest seed yields, respectively, and the average seed yields of genotypes G3, G4, G6, G7, G8, and G9 were higher than the total average seed yield. Based on the average of sum ranks (ASR), G2, G11, G6, and G9 genotypes with the lowest ASR values were the most stable, while G10, G12, G3, and G13 genotypes with the highest ASR values were the most unstable genotypes. Among the stable genotypes, G6 and G9 were recognized as genotypes with good seed yield and general compatibility due to their higher average seed yields. Furthermore, the Zarghan location was recognized as the most ideal environment for distinguishing and separating rapeseed genotypes due to its high interaction. The cluster analysis classified the studied environments into three groups. The Isfahan, Hamedan, Zarghan, and Karaj locations were placed in a group in both years, indicating that these locations had high predictability and repeatability power.
Conclusion: Based on the results of the AMMI method, G6 and G9 were better than the other genotypes for seed yield and stability and showed high general adaptation to all environments. Additionally, the Zarghan location was recognized as the most ideal environment due to its high interaction for distinguishing and separating rapeseed genotypes. Generally, the results showed the efficiency of the AMMI method in investigating the G × E interaction effect and providing good information about the studied genotypes and environments.
Keywords: Additive main effects and multiplicative interaction, Genotype × environment interaction, Grain yield, Rapeseed
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