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Multi-Environment Yield Stability and Performance Assessment of Dual-Purpose Barley Genotypes Using Integrated Ammi, Blup, and Non-Parametric Statistical Frameworks

DOI https://doi.org/10.55640/corr-v04i04-03
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Dr. Budi Santoso 1 , Prof. Sari Wulandari 1 ,
4 Department of Scientific Policy Analysis Indonesian Institute of Knowledge Systems, Jakarta, Indonesia
4 University of Technology and Innovation, Yogyakarta, Indonesia

Abstract

The evaluation of genotype × environment interaction (GEI) is a fundamental requirement in crop improvement programs, particularly for dual-purpose barley where both forage and grain productivity must be optimized under variable agro-ecological conditions. This study presents an integrated analytical framework combining Additive Main Effects and Multiplicative Interaction (AMMI), Best Linear Unbiased Prediction (BLUP), and non-parametric stability measures to assess yield performance and stability of barley genotypes across multi-environment trials. The objective is to identify high-yielding and stable genotypes suitable for diverse production environments by leveraging complementary statistical methodologies.

Existing literature highlights the importance of integrating parametric and non-parametric approaches for robust stability assessment, as demonstrated in barley and other cereal crops (Mehraban et al., 2019; PourAboughadareh et al., 2022). Comparative frameworks such as AMMI and BLUP have been widely used for improving selection accuracy under GEI complexity (Gonçalves et al., 2020). Furthermore, simulation-based and online computational tools for stability analysis enhance interpretability and decision-making in breeding programs (Pour-Aboughadareh et al., 2019).

The integrated framework in this study synthesizes variance decomposition, multiplicative interaction modeling, and rank-based stability indices to improve selection efficiency. Results indicate that combining AMMI, BLUP, and non-parametric metrics improves the reliability of genotype classification under heterogeneous environmental conditions. The study contributes to precision breeding strategies for barley improvement programs targeting yield stability under climate variability.

Keywords

Barley genotypes, genotype × environment interaction, AMMI model, BLUP analysis

References

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