Pod Set in Soybean: Investigations with SOYPODP, a Whole Plant Model

The ability of soybean [Glycine max (L.) Merr.] to adjust its pod load to environmental conditions is an important, but not well understood, part of the yield production process. To better understand this process at the whole plant level, a single‐node model (SOYPOD) was extended to predict pod set...

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Veröffentlicht in:Agronomy journal 2015-01, Vol.107 (1), p.349-360
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description The ability of soybean [Glycine max (L.) Merr.] to adjust its pod load to environmental conditions is an important, but not well understood, part of the yield production process. To better understand this process at the whole plant level, a single‐node model (SOYPOD) was extended to predict pod set of whole plants. Pod survival in SOYPODP was determined by comparing assimilate from photosynthesis (calculated from solar radiation) to pod requirements during initial pod growth. Measured profiles of flowers per node and pod and seed growth rates were used as input. Pods that do not receive adequate assimilate for a specified number of consecutive days do not survive. When inter‐nodal movement of assimilate was prohibited and the nodal assimilate production profile matched the input flower profile, pod set on the stem matched measured profiles of two field‐grown cultivars. In this form, SOYPODP accurately mimicked known responses of pod number to variation in assimilate supply, nodes per plant and individual seed growth rate. Competition for assimilate at a node‐controlled pod set, so increasing uniformity of pod development (more flowers or a shorter flowering period) increased pod set. Increasing nodal variation in the beginning of pod development reduced the sensitivity of the plant to short‐term fluctuations in assimilate supply. Variation in uniformity of pod development at a node was responsible for increases in pod set with no change in assimilate availability. The value of these increases is not clear, but it seems unlikely that they would affect yield.
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title Pod Set in Soybean: Investigations with SOYPODP, a Whole Plant Model
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