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The study evaluated 30 genotypes of foxtail millet at Millets Research Station Dholi, RPCAU, Pusa, during Kharif 2021. A randomized block design with three replications was used. Before selecting genotypes based on micronutrient content (Fe and Zn) for nutritional quality traits, it's crucial to understand their potential impact on yield. The study examined the relationships between quality traits and yield attributes in foxtail millet genotypes using a diverse range of genotypes. Correlation analysis under normal condition revealed positive relationships, particularly between panicle girth and number of productive tillers per plant, grain yield per plant and days to maturity, days to 50% flowering and iron content and days to 50% flowering and zinc content, with correlation coefficients ranging from 0.307 to 0.333. This indicates that these traits collectively enhance plant productivity under favorable conditions. However, under drought conditions, the relationships shift. Grain yield per plant showed significant positive correlation only with days to 50% lowering and number of productive tillers per plant with panicle girth, with correlation coefficients of 0.315 and 0.314, respectively. Further, significantly negative correlation of days to maturity with number of productive tillers per plant, panicle girth and zinc content was observed. Similarly, days to 50% flowering was found negatively correlated with panicle girth. This suggests that under water stress, fewer traits positively influence yield, with panicle girth becoming a crucial factor in maintaining grain yield. This analysis highlights how environmental conditions affect the relationships between plant traits. Under normal conditions, a broader set of traits, including micronutrient levels, contribute to productivity. In contrast, under drought stress, the focus shifts to key traits like panicle girth, essential for resilience and yield stability. These insights can improve and speed up breeding programs aiming to enhance drought tolerance in crops, by prioritizing traits that significantly impact yield under adverse conditions.
Gandhi et al. (Tue,) studied this question.