This analysis reveals machine learning predicts metabolites related to drought resilience in cotton, suggesting improved stress management strategies.
Hyperspectral indices integrated with physiology predicted metabolites such as Rubisco activity across early, mid, and late flowering drought, establishing a rapid, non-destructive framework to detect sink limitations and identify cotton resilience to stage-specific stress and fiber quality decline.
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Cisse et al. (2025) studied this question.
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