ArticleJournal of applied genetics2026
Multi-trait stability index in the selection of high-yielding and stable barley genotypes.
Article in Journal of applied genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Assessing the stability and adaptability of wheat genotypes in well-watered and rainfed conditions using AMMI, BLUP, GGE biplot and MTSI approaches.Scientific reports · 2026Article
- Identification of promising sweet sorghum advanced lines for bioenergy production under Mediterranean conditions.BMC plant biology · 2026Article
- Effect of the genetic and environment interaction on yield, Fe and Zn content among locally cultivated common bean (Frontiers in plant science · 2026Article
- Multilevel analysis of salt stress responses in sorghum during seed germination.Frontiers in plant science · 2026Article
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Authors and funding
5 authors.
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Abstract
The analysis of genotype-by-environment interaction (GEI) in multi-environmental trials (METs) represents a crucial component of breeding programs prior to the release of new commercial cultivars tailored for specific regions or diverse environmental conditions. Moreover, emphasizing individual traits during selection can yield misleading conclusions. Consequently, the implementation of robust selection models is essential for identifying superior genotypes based on multiple traits. The present dataset demonstrates the utility of the multi-trait stability index (MTSI) in identifying high-yielding and stable barley genotypes across ten diverse environments. The evaluated phenological and agronomic traits included days to heading, days to physiological maturity, grain-filling period, plant height, thousand-kernel weight, and grain yield. A combined analysis of variance (ANOVA) revealed significant effects attributable to environments (E), genotypes (G), and their interaction (GEI) across all assessed traits. Correlation analysis further indicated positive associations between all measured traits and grain yield. In the MTSI model, three first factors accounted for 75% of the total phenotypic variation observed across the test environments. The highest selection gain percentages were recorded for thousand-kernel weight and grain yield. Among the genotypes evaluated, G3, G10, and G14, characterized by the lowest values of the MTSI index, were identified as superior in terms of grain yield, stability, and desirable agronomic attributes. In conclusion, the findings highlight the efficacy of the MTSI in reliably identifying superior genotypes in METs. The results demonstrate that the MTSI index not only enhances the efficiency of the selection process but also improves the accuracy of genotype evaluation and ranking across heterogeneous environmental conditions. This underscores the potential of the MTSI index to support informed breeding decisions, ultimately facilitating the development of high-performing plant varieties that exhibit both yield stability and adaptability across diverse environments.
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