Integration of UAV Remote Sensing and Variable-Rate Spraying in Efficient Rice Blast Control

Abstract

Drone-based remote sensing and precision spraying present a novel method for sustainable crop protection. This research focused on identifying rice blast disease in paddy fields through the use of drone-mounted multispectral sensors and assessing the effectiveness of drone sprayers for targeted pesticide application. The severity of the disease was mapped utilizing NDVI, NDRE, and canopy temperature indices, which exhibited strong correlations with ground-truth observations (r = –0.82 for NDVI, r = –0.76 for NDRE, r = +0.70 for canopy temperature).Prescription maps facilitated variable-rate fungicide application via a drone sprayer, in contrast to traditional knapsack spraying. The findings indicated that drone-based variable spraying led to a 44% reduction in pesticide usage, an 11.6% increase in yield, and enhanced disease control efficacy. ANOVA analysis confirmed significant differences among the treatments (p < 0.001). This study illustrates the potential of UAV-based disease monitoring and spraying as a cost-effective and environmentally friendly approach to crop protection in rice agriculture.