Development of a comprehensive evaluation system and models to determine soybean seed vigor

Abstract

High-vigor soybean seeds are critical for efficient production owing to their favorable growth properties and high yield potential. The evaluation and identification of high-vigor germplasms are essential for increasing soybean production capacity. Currently, there is no universally accepted evaluation system to test for soybean seed vigor. In this study, 11 seed vigor-related traits were measured across 126 soybean landraces via an artificial accelerated aging technique. The ratios of these 11 traits, which were calculated before and after artificial accelerated aging, were used as vigor indicators in principal component analysis (PCA), ultimately yielding two principal component factors. These factors were then combined via membership function standardization to calculate a comprehensive seed vigor evaluation value (V value), thereby establishing an evaluation system. Cluster analysis based on the V value was used to classify seed vigor into five levels and identify seven high-vigor germplasms: ZDD12322, ZDD06438, ZDD11951, ZDD08251, ZDD12436, ZDD02315, and ZDD15624. Through stepwise regression analysis, the optimal seed vigor predictive model was defined as V = −0.026 + 0.625 × RSL + 0.485 × RGI. This model revealed that the relative seedling length (RSL) and relative germination index (RGI) had significant positive effects on seed vigor. This study provides a valuable framework for seed quality control and selection, facilitating presowing vigor assessments to increase soybean planting efficiency and yield.