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    Optimizing chickpea yield prediction under wilt disease through synergistic integration of biophysical and image parameters using machine learning models by RN Singh, P. Krishnan, C. Bharadwaj, Sonam Sah, B. Das

    Published 2025-02-01
    “…Field experiments were carried out over three years at the Indian Agricultural Research Institute research farm in New Delhi. Thermal and visible images were collected alongside the measurement of crop biophysical parameters, including leaf area index (LAI), photosynthesis, transpiration rate, stomatal conductance, relative leaf water content (RWC), membrane stability index (MSI), and NDVI, for 85 chickpea genotypes with varying levels of wilt resistance. …”
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