Evaluation of grain yield stability of promising quinoa genotypes (Chenopodium quinoa Willd.) using graphical methods

Document Type : Original Article

Authors

1 Ph. D. Student,, Department of Plant Production and Genetic Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

2 Professor, Department of Plant Production and Genetic Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

3 Ph.D, graduate, Department of Plant Production and Genetic Engineering, Faculty of Agricultural Sciences,University of Guilan, Rasht, Iran

10.22034/plant.2024.141091.1092

Abstract

Genotype × environment interaction is the main limiting factor in identifying superior genotypes in plant breeding programs. This research was conducted with the aim of investigating the genotype × environment interaction and selecting high-yielding and stable quinoa genotypes using AMMI (Additive Main effects and Multiplicative Interaction) and GGE (Genotype plus Genotype by Environment interaction) biplot methods. A number of 30 different quinoa genotypes prepared from the IPK Institute of Germany with different origins were cultivated as plant materials of this experiment in the form of randomized complete block design in two environments, Buin Zahra and Takestan, during the two crop years of 2022-2023. The results showed that the variance caused by the effects of genotype, environment and genotype × environment interaction was significant for grain yield and this trait was more affected by genotypic diversity. The variation of genotype × environment interaction in the AMMI method was explained by the Two principal components. Using this method, genotypes G14, G11, G12, G23, G1, G5 and G13 were recognized as high-yielding and stable genotypes, and the Takestan environment in the second year was introduced as a stable and high-yielding environment. Also, the first two main components in GGE biplot method explained about 92% of the variation of genotype and genotype × environment interaction for grain yield. In this method, the studied environments were placed in two mega-environments. All environments had high differentiation ability for grain yield in the studied genotypes. G11 and G14 genotypes were identified as ideal genotypes. Finally, based on both AMMI and GGE bi-plot methods, genotypes G5, G11, G12, G13, G14 and G23 among the quinoa genotypes studied were identified as high-yielding and stable genotypes, and Buin Zahra environment was introduced as an ideal environment.

Keywords

References

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