Thermal Imaging and Disease Detection in Patharchatta Plant

Abstract

Abstract: Plant diseases cause significant agricultural losses, affecting both crop yield and quality. Early detection is crucial for effective disease management. This study explores thermal imaging as a non-invasive method for identifying plant stress in Patharchatta (Kalanchoe pinnata). Two cases were analyzed: wilting due to dehydration and black spot disease from overwatering.Thermal thresholds of 16°C (early stress) and 18°C (critical damage) were experimentally identified, particularly in fungal-infected Patharchatta plants.A thermal image-based classification model was developed to support detection, achieving over 91% accuracy.The findings demonstrate that thermal imaging is a promising, real-time toolfor early disease detection, enabling proactive plant health management.

Code and data availability

The paper's thermal image dataset (>100 images) and CNN model are not publicly deposited; the only availability statement is on-request from the corresponding author, with no authors' public URL provided.

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