The research project deploys advanced imaging techniques to capture leaf physiological traits and analyze anatomical features in grain amaranths under heat and drought stress. It aims to connect stress phenotypes with gene networks through multi-omics analyses. Machine learning tools facilitate data assimilation, classification, and climate-resistant leaf trait prediction. This approach enhances our understanding of grain amaranths' resilience in adverse environmental conditions.
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