Evaluating salinity tolerance in soybean (Glycine max L.) varieties under salinity stress: a multivariate analysis approach using PCA and GGE Biplot models

Climate change-induced salinity stress significantly threatens global soybean production. This study evaluated the physiological and photosynthetic responses of three soybean varieties (Afigat, Gishama, Pawi-2) under controlled salt stress to identify promising tolerant germplasm. We found that increasing salinity generally reduced the water content, relative water content (RWC), chlorophyll fluorescence (Fv/Fm), and photosynthetic pigments. Conversely, adaptive mechanisms were evident in the increased water uptake and retention capacities. Multivariate analysis, specifically Principal Component Analysis (PCA) and GGE Biplot models, was employed to rigorously interpret the complex physiological data. These analyses identified WUC, RWC, chlorophyll a, and Fv/Fm as the most critical indicators for salt tolerance screening. Based on these key traits, the variety Pawi-2 demonstrated superior physiological adaptation, while Gishama was the most susceptible. The research validates multivariate techniques for effective genotype selection and identifies physiologically resilient Pawi-2 as a valuable genetic resource for molecular breeding programs, which requires subsequent confirmation of agronomic performance under field conditions.