Identification of high-yielding and stable cultivars of wheat under different sowing dates: Comparison of AMMI and GGE-biplot analyses.

Majid Taherian, Fatemeh Saeidnia, Rasmieh Hamid, Seyyed Mahmood Nazeri
Author Information
  1. Majid Taherian: Agricultural and Horticultural Science Research Department, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Mashhad, 91769-83641, Iran.
  2. Fatemeh Saeidnia: Agricultural and Horticultural Science Research Department, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Mashhad, 91769-83641, Iran.
  3. Rasmieh Hamid: Plant Breeding Department, Cotton Research Institute of Iran, Agricultural Research, Education and Extension Organization, Gorgan, 49166-85915, Iran.
  4. Seyyed Mahmood Nazeri: Agricultural and Horticultural Science Research Department, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Mashhad, 91769-83641, Iran.

Abstract

Evaluating the adaptability and yield stability of wheat varieties across different sowing dates is crucial for the success of breeding programs. In this study, we used Additive Main Effects and Multiplicative Interactions (AMMI) and Genotype �� Genotype-Environment (GGE) biplot analyses to evaluate the performance of 13 wheat varieties across eight sowing dates. The main objective was to compare varieties and sowing dates to identify the most stable varieties for cultivation. Both AMMI and GGE biplot analyses showed significant effects of genotype, environment and genotype-environment (GE) interaction on grain yield. The interaction patterns identified by AMMI and GGE-biplots categorized Mihan, Oroom and Pishgam as the most stable, high yielding and early maturing wheat varieties. Furthermore, while the GGE biplot method proved to be more efficient than the AMMI model for stability analysis, our results indicate considerable overlap between the results of these two approaches. These results provide a valuable basis for optimizing genetic improvement strategies in wheat breeding programs.

Keywords

References

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