Climate change–driven temperature increases pose significant risks to specialty crop production, particularly for heat-sensitive crops such as broccoli. Conventional methods for evaluating heat tolerance rely on visual assessments, destructive sampling, and post-harvest yield measurements, which often detect stress only after irreversible physiological damage has occurred. This study investigates whether unmanned aerial vehicle (UAV)-based multispectral imaging can detect early indicators of heat stress in broccoli cultivars before the appearance of visible symptoms.

Broccoli cultivars were subjected to heat stress and imaged using UAVs equipped with multispectral sensors. Calibrated spectral reflectance data were processed to generate vegetation indices indicative of canopy vigor and physiological status. Statistical analyses were conducted to compare cultivar-specific spectral responses and to evaluate the temporal relationship between spectral divergence and observable stress markers.

Preliminary results demonstrate that significant differences in vegetation index values emerged among cultivars before visible wilting or chlorosis occurred. Heat-tolerant cultivars maintained higher vegetation index values under elevated temperatures, suggesting greater physiological stability and stress resilience. These findings support the use of UAV-based multispectral imaging as a non-destructive, scalable approach for early phenotyping of heat tolerance. Integrating remote sensing technologies into cultivar performance evaluate may enhance selection efficiency and contribute to the development of climate-resilient agricultural systems.