Is individual seed weight distribution within soybean plants hierarchically structured?

Abstract

Individual seed weight (SWi) varies within a plant and collectively determines average seed weight (SWa). Unlike in cereals, this variation has not been thoroughly examined in soybean to identify underlying patterns. Understanding these patterns may help explain the physiological mechanisms driving SWa responses to genotype × environment interactions. This study aimed to investigate whether SWi follows a hierarchical pattern within a soybean plant, and to evaluate the stability of this pattern when resource availability is increased at R3 or R6. A field experiment was conducted using three treatments arranged in four randomized complete blocks: an unmanipulated control, thinning at R3, and thinning at R6. In both thinning treatments, two-thirds of the plants per plot were removed to increase resource availability per plant for the remaining plants. The weight of every individual seed was measured across different morphological positions in the plant: main stem and branches, nodes along the stem, pods within nodes, and seeds within pods. Thinning at R3 nearly doubled plant yield, mainly due to a 69% increase in seed number (SN), accompanied by a much smaller increase in SWa (13%), indicating source limitation during the critical period of SN determination. In contrast, thinning at R6 did not affect SN or SWa, suggesting that yield was not strongly limited by assimilate availability during the second half of the effective seed filling period. Across all treatments, SWi followed a consistent hierarchical pattern: seeds from central stem nodes were the heaviest; within nodes, earlier-developing pods had heavier seeds than later-developing pods; and within pods, seeds closest to the pedicel were the lightest. The consistency of intraplant SWi patterns across contrasting resource availability per plant indicates that SWi distribution is a constitutive trait (at least in indeterminate soybeans) that must be considered when interpreting responses of SWa to environmental variations and, in particular, to source–sink manipulation treatments.