Evaluation of genotype × environment interaction of advanced rainfed lentil genotypes by multivariate GGE biplot method

Document Type : Research Paper

Authors

1 Dryland Agricultural Research Institute, Kohgiloyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gachsaran, Iran

2 Assistant Professor,-Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Khorramabad-, Iran

3 Ardabil Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Moghan, Iran

4 Ilam Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Ilam, Iran

Abstract

Background and objectives. Given the shortcomings regarding lentil cultivars compatible with temperate and semi-temperate rainfed regions of the country, identifying genotypes with potential to be introduced as cultivars is very important. Due to genotype × environment interaction, selection of genotypes with wide adaptation to different environments is difficult. In addition to high yield, these genotypes must have yield stability in different regions, in other words, general stability. In GGE model (G+GE), the selection of stable genotypes is based on both genotype (G) and genotype × environment (GE) interaction effects.
Materials and methods. in order to evaluate yield stability of rain-fed lentil genotypes, the present study was conducted based on randomized complete block design with three replications with 14 advanced genotypes along with two local cultivars including G15 and G16 (Gachsaran and Sepehr respectively) over two years (since 2018). The experiment’s locations were Gachsaran, Khormeh Abad, Ilam and Moghan. After collecting data from eight environments, the genotype × environment interaction for grain yield was evaluated by using GGE biplot method.
Results. Principal component analysis in the GGE biplot model showed that 47.1% of the variations caused by G and GE is justified by the first two components (PC1, PC2). The mosaic plot revealed that the contribution of diversity due to genotype × environment interaction was significantly higher than the diversity caused by genotype (G) alone. Using GGE biplot model and based on representativeness and discriminating ability, Gachsaran region was identified as a desirable environment to identify variation among genotypes. G11 was the closest genotype to the ideal genotype in terms of grain yield. This genotype had the highest yield among genotypes and was in a moderate position in terms of stability. Genotype 9 was in the second place in terms of yield but had high yield stability since was the closest genotype to the ideal genotype in terms of stability. Genotypes 10 and 1 were also in the next ranks considering both yield and stability. These four genotypes had considerable advantage in terms of both average yield and yield stability compated to control cultivars (G15 and G16). In addition, G5 showed the least yield stability among all genotypes. G15 and G16 as local cultivars showed relatively low grain yield and stability compared to the most of advanced genotypes.
Conclusion. G9, G11, G10, G1 were considered as genotypes with potential to be introduced as new cultivar(s) following further experiments in private farm lands.

Keywords

References

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Journal of Crop Production
Volume 15, Issue 2
July 2022
Pages 203-218

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