Optimizing UAV Spraying for Sustainable Agriculture: A Life Cycle and Efficiency Analysis in India

Shefali Vinod Ramteke, Pritish Kumar Varadwaj () and Vineet Tiwari ()
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Shefali Vinod Ramteke: Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj 211015, India
Pritish Kumar Varadwaj: Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj 211015, India
Vineet Tiwari: Department of Management Studies, Indian Institute of Information Technology Allahabad, Prayagraj 211015, India

Sustainability, 2025, vol. 17, issue 13, 1-30

Abstract: Problem: Agriculture in India faces pressing challenges related to water scarcity, excessive pesticide use, and inefficient energy consumption, impacting both economic sustainability and environmental health. Methodology: This study integrates Life Cycle Assessment (LCA), Data Envelopment Analysis (DEA), Intelligent Management Models (IMMs), and Multi-Criteria Decision Analysis (MCDA) to assess the economic and environmental benefits of UAV-based spraying in Indian agriculture. Data were collected from UAV service providers and field trials in Punjab, Haryana, and Rajasthan. Results: UAV spraying achieved a 70% reduction in water use, 40% reduction in pesticide consumption, and a 50% reduction in CO 2 emissions compared to conventional spraying. DEA results showed higher efficiency scores for UAVs, while IMM optimization achieved 95% pesticide coverage and reduced drift by 80%. Implications: MCDA ranked government subsidies as the most effective policy intervention. These findings support UAV spraying as a viable, scalable solution for climate-smart agriculture in India, offering both productivity and sustainability gains.

Keywords: Data Envelopment Analysis; Intelligent Management Model; Life Cycle Assessment; Multi-Criteria Decision Analysis; precision agriculture; UAV spraying (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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