Volume 18, Issue 1 (3-2026)
J Crop Breed 2026, 18(1): 43-58 |
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Pezeshkpour P, Vaezi B, Sabzi Z, Mahinkhah M. (2026). Stability Analysis of Grain Yields of Vetch Genotypes by Multivariate Methods and the Superiority Index. J Crop Breed. 18(1), 43-58. doi:10.61882/jcb.2026.1614
URL: http://jcb.sanru.ac.ir/article-1-1614-en.html
URL: http://jcb.sanru.ac.ir/article-1-1614-en.html
1- Crop and Horticultural Science Research Department, Lorestan Agricultural and Natural Resources Research and Education Center, AREEO, Khorramabad, Iran
2- Kohgiluyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Yasuj, Iran
3- Crop and Horticultural Science Research Department, Ilam Agricultural and Natural Resources Research and Education Center, AREEO, Ilam, Iran
2- Kohgiluyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Yasuj, Iran
3- Crop and Horticultural Science Research Department, Ilam Agricultural and Natural Resources Research and Education Center, AREEO, Ilam, Iran
Abstract: (199 Views)
Extended Abstract
Background: Common vetch (Vicia sativa ssp. sativa L.) is one of the most important livestock legumes in the Mediterranean mega-environment due to its multiple uses, its high nutritional value, and its ability to grow in different environmental conditions. Increased nutritional needs for livestock require the introduction of animal feed legumes in crop rotations. Common vetch is considered among the best options to be part of crop rotations, especially in lower rainfall areas, and a good alternative to cereal monoculture, as it produces higher seed and protein yields, in comparison. Another advantage of vetch cultivation is its compatibility with organic and low-input farming systems. Its usefulness is based on the exploitation of atmospheric nitrogen, which is satisfactory in certain cultivation areas. Vetch-cereal intercrops produce considerably higher protein yields on the soil without any need for N-fertilizers. It is a usual approach to cultivate local varieties or mixtures among them to maintain yield under low-input farming systems that support mainly livestock. Autumn vetch cultivation in terms of increasing the efficiency of rainfall increases grain yield compared to spring cultivation under rainfed conditions. In addition, to maximize yield and control phenotypic expression, breeders must select specific genotypes that are stable or adapted to a specific environment. Therefore, the identification of high-yield genotypes with adaptation to a wide range of environments is one of the major goals in crop breeding programs. In multi-environment experiments, vetch yield is influenced by the genetic structure, environment, and genotype × environment interaction. To better interpret the genotype × environment interaction, the additive main effects and multiplicative interaction (AMMI) model is one of the most common methods in the study of multi-environment experiments. The current study aimed to investigate the effect of the genotype × environment interaction on vetch genotypes and to identify stable, high-yielding genotypes that are compatible with the climatic conditions of temperate rainfed regions of Iran.
Methods: In this study, eight promising vetch genotypes, along with “Maragheh” and “Tolo” cultivars, were cultivated in a randomized complete block design for five consecutive cropping years (2019-2024) in Kogiluyeh and Boyer Ahmad/Gachsaran, Lorestan/Khoramabad, Ilam/Chardavel, and Mehran. In the field, each plot consisted of four planting rows, 7 meters long, with a distance of 25 cm and a density of 150 seeds per square meter. Stability analysis was performed using the AMMI multivariate method. Statistical analyses were performed using the Metan and GGE packages of multi-environment experiments in R software.
Results: The AMMI analysis of variance showed that the effects of environment, genotype, the genotype × environment, and the first five main components were significant. Therefore, due to the significance of the genotype × environment interaction, it is possible to perform stability analysis on these data. According to AMMI analysis, the first and second main components of the genotype-environment interaction accounted for 51.6 and 25.6% of genotype × environment interaction variations, respectively. The effect of the first five main components was significant and in total explained 96.5% of the genotype × environment interaction variations. The shares of the environment, genotype, and genotype × environment interaction in the sum of total squares were 35.45, 8.908, and 55.65 percent, respectively. Among the studied genotypes, Genotype 2 with 1.451 ton/ha, followed by genotypes 1, 5, and 3, produced the highest grain yields. Based on the ASV stability index, genotypes 4, 6, and 5, based on the SIPC index, genotypes 5, 1, 2, and 4, based on the EV index, genotypes 1, 4, 3, and 10, and genotypes 5, 7, 2, and 6 based on the index Za were the most stable genotypes. Based on the simultaneous selection index of ssiASV, genotypes 1, 2, 3, and 4, based on the ssiSIPC index, genotypes 2, 1, 3, and 5, based on the ssiEV index, genotypes 1, 2, 3, and 4, based on the ssiZA index, genotypes 2, 5, and 1, and based on the ssiWAAS index, genotypes 5, 1, 2, and 7 were the best genotypes in terms of yield and stability. Based on the AMMI1 biplot, genotypes 4, 7, 5, 1, and 6 with mean grain yields higher than the overall average and lowest values of IPCA1 were identified as stable genotypes with high general compatibility. In the AMMI2 biplot, genotypes 4, 5, and 6, in addition to high general stability, produced higher grain yields than the overall average. In addition to the AMMI indices, Lin and Binn's superiority index was also used to identify the best genotypes, and based on this, genotypes 1, 3, 5, and 2 were the most stable genotypes in the studied environments.
Conclusion: In general, genotypes 1 (V.S.IVAT- 2003), 2 (V.S.IVAT- 2556), and 5 (V.S.IVAT- 2709) produced high yields in most of the environments based on different indices and showed good stability in most methods. Therefore, they could be candidates for the introduction of new cultivars.
Background: Common vetch (Vicia sativa ssp. sativa L.) is one of the most important livestock legumes in the Mediterranean mega-environment due to its multiple uses, its high nutritional value, and its ability to grow in different environmental conditions. Increased nutritional needs for livestock require the introduction of animal feed legumes in crop rotations. Common vetch is considered among the best options to be part of crop rotations, especially in lower rainfall areas, and a good alternative to cereal monoculture, as it produces higher seed and protein yields, in comparison. Another advantage of vetch cultivation is its compatibility with organic and low-input farming systems. Its usefulness is based on the exploitation of atmospheric nitrogen, which is satisfactory in certain cultivation areas. Vetch-cereal intercrops produce considerably higher protein yields on the soil without any need for N-fertilizers. It is a usual approach to cultivate local varieties or mixtures among them to maintain yield under low-input farming systems that support mainly livestock. Autumn vetch cultivation in terms of increasing the efficiency of rainfall increases grain yield compared to spring cultivation under rainfed conditions. In addition, to maximize yield and control phenotypic expression, breeders must select specific genotypes that are stable or adapted to a specific environment. Therefore, the identification of high-yield genotypes with adaptation to a wide range of environments is one of the major goals in crop breeding programs. In multi-environment experiments, vetch yield is influenced by the genetic structure, environment, and genotype × environment interaction. To better interpret the genotype × environment interaction, the additive main effects and multiplicative interaction (AMMI) model is one of the most common methods in the study of multi-environment experiments. The current study aimed to investigate the effect of the genotype × environment interaction on vetch genotypes and to identify stable, high-yielding genotypes that are compatible with the climatic conditions of temperate rainfed regions of Iran.
Methods: In this study, eight promising vetch genotypes, along with “Maragheh” and “Tolo” cultivars, were cultivated in a randomized complete block design for five consecutive cropping years (2019-2024) in Kogiluyeh and Boyer Ahmad/Gachsaran, Lorestan/Khoramabad, Ilam/Chardavel, and Mehran. In the field, each plot consisted of four planting rows, 7 meters long, with a distance of 25 cm and a density of 150 seeds per square meter. Stability analysis was performed using the AMMI multivariate method. Statistical analyses were performed using the Metan and GGE packages of multi-environment experiments in R software.
Results: The AMMI analysis of variance showed that the effects of environment, genotype, the genotype × environment, and the first five main components were significant. Therefore, due to the significance of the genotype × environment interaction, it is possible to perform stability analysis on these data. According to AMMI analysis, the first and second main components of the genotype-environment interaction accounted for 51.6 and 25.6% of genotype × environment interaction variations, respectively. The effect of the first five main components was significant and in total explained 96.5% of the genotype × environment interaction variations. The shares of the environment, genotype, and genotype × environment interaction in the sum of total squares were 35.45, 8.908, and 55.65 percent, respectively. Among the studied genotypes, Genotype 2 with 1.451 ton/ha, followed by genotypes 1, 5, and 3, produced the highest grain yields. Based on the ASV stability index, genotypes 4, 6, and 5, based on the SIPC index, genotypes 5, 1, 2, and 4, based on the EV index, genotypes 1, 4, 3, and 10, and genotypes 5, 7, 2, and 6 based on the index Za were the most stable genotypes. Based on the simultaneous selection index of ssiASV, genotypes 1, 2, 3, and 4, based on the ssiSIPC index, genotypes 2, 1, 3, and 5, based on the ssiEV index, genotypes 1, 2, 3, and 4, based on the ssiZA index, genotypes 2, 5, and 1, and based on the ssiWAAS index, genotypes 5, 1, 2, and 7 were the best genotypes in terms of yield and stability. Based on the AMMI1 biplot, genotypes 4, 7, 5, 1, and 6 with mean grain yields higher than the overall average and lowest values of IPCA1 were identified as stable genotypes with high general compatibility. In the AMMI2 biplot, genotypes 4, 5, and 6, in addition to high general stability, produced higher grain yields than the overall average. In addition to the AMMI indices, Lin and Binn's superiority index was also used to identify the best genotypes, and based on this, genotypes 1, 3, 5, and 2 were the most stable genotypes in the studied environments.
Conclusion: In general, genotypes 1 (V.S.IVAT- 2003), 2 (V.S.IVAT- 2556), and 5 (V.S.IVAT- 2709) produced high yields in most of the environments based on different indices and showed good stability in most methods. Therefore, they could be candidates for the introduction of new cultivars.
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