Machine learning reveals guard cell starch as a key factor in optimizing stomatal conductance and carbon assimilation across plant lineages, suggesting new engineering targets.
Engineering rapid stomatal responses to improve the coordination between stomatal conductance and carbon assimilation under fluctuating light conditions is crucial for enhancing crop productivity while conserving water. To identify promising engineering targets, we applied machine learning models to analyze published data from diverse plant lineages to reveal the primary factors driving the natural variation in the speed of stomatal opening. We highlight the versatile role of guard cell starch in integrating and modulating some of these factors and suggest starch as a previously overlooked target for optimizing stomatal function.
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Zhang et al. (2025) studied this question.
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