Cluster and Correlation Analysis of Valuable Traits of Bean Cultivars Under Irrigation Conditions in Kazakhstan

Abstract

This study aimed to investigate a diverse collection of beans accessions under irrigation conditions in the Almaty region of Kazakhstan to identify promising genotypes for breeding. Over a ten-year period (2014–2024), 300 accessions were analyzed, of which 100 were selected for detailed assessment based on key agronomic traits including earliness, productivity, seed weight, disease resistance, protein content, and adaptability to mechanized harvesting. Cluster and correlation analyses were employed to classify accessions and determine interrelations among traits. Cluster analysis revealed three major groups based on productivity and seed quality traits. Correlation analysis indicated strong positive associations between plant productivity components such as number of productive nodes, number of pods per plant, and seed weight per plant (r = 0.91). A moderate positive correlation (r = 0.52) was found between 1000-seed weight and overall plant weight, while negative correlations were observed between productivity traits and seed protein content. The findings provide valuable insights for developing high-yielding, protein-rich, and machine-harvest-adapted beans varieties suitable for the agroclimatic conditions of Kazakhstan.