Trait-based clustering and index ranking to identify high-yielding spring wheat genotypes under the conditions of northern Kazakhstan

Brazilian Journal of Biology, 2025

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DOI 10.1590/1519-6984.300898
Data confidence 70 medium
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Abstract

This article presents the results of a multi-year evaluation of spring bread wheat based on key morphological and yield-related traits under the conditions of Northern Kazakhstan. Descriptive statistics, correlation and cluster analysis, and selection index methods were applied. Strong positive correlations were identified between the traits of number of grains per spike, productive tillering, and grain yield. Cluster analysis distinguished three groups of genotypes differing in productivity and qualitative characteristics. The use of selection indices allowed to identify the most promising genotypes combining desirable traits. The results highlight the effectiveness of an integrated approach to the selection of breeding material and its relevance for the development of adapted wheat varieties under changing climatic conditions.