Evaluation of Yield Traits and Correlation Analysis for Screening Waterlogging-Tolerant Soybean (Glycine max L.) Genotypes

Soybean (Glycine max L.) is a major oilseed crop valued for its nutritional composition and its role in sustainable agriculture. In rainfed regions like Madhya Pradesh, waterlogging due to erratic monsoon rainfall significantly limits soybean productivity. This study aimed to identify waterlogging-tolerant soybean genotypes through integrated evaluation of yield traits and correlation analysis. The experiment was conducted during the Kharif season (2023–24) at the Demonstration cum Experimental Farm of Shri Vaishnav Institute of Agriculture, SVVV, Indore, using 45 genotypes in a randomized block design with two replications. Seeds were sown by dibbling, and standard agronomic practices were followed under simulated waterlogged conditions. Traits including number of pods per plant, number of seeds per pod, 100-seed weight, seed yield, biological yield, and harvest index were recorded. Correlation analyses (Pearson and Spearman) revealed significant associations of seed yield with pod number, seed weight, and plant height. Genotypes NRC 258, JS 21-72, AMS 2014-1, and RVSM 2011-35 exhibited superior yield performance and resilience. Mahalanobis D² intercluster analysis showed maximum genetic divergence between Cluster III and Cluster IV, indicating potential for heterotic breeding. Combining phenotypic screening, correlation metrics, and multivariate clustering provides a strategy for selecting waterlogging-tolerant soybean genotypes suitable for stress-prone agroecologies.