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

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.

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Publication Details

Journal
Journal of Experimental Agriculture International
Published
2025-10-04
DOI
https://doi.org/10.9734/jeai/2025/v47i103796
Primary Topic
Industrial Technology and Control Systems
Type
article
Field-Weighted Citation Impact
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article

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

S. R. N. Reddy, U. Murali Krishna, Mahesh Palkuru
Journal of Experimental Agriculture International
Industrial Technology and Control Systems
article

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

S. R. N. Reddy, U. Murali Krishna, Mahesh Palkuru
article en

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.

Journal of Experimental Agriculture InternationalVol. 47(10)
Jawaharlal Nehru Krishi Vishwa Vidyalaya (IN), University of Hyderabad (IN), Dr. Reddy's Laboratories (India) (IN)
Openalex Percentile: Top 66%
Industrial Technology and Control Systems
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