Reducing energy and environmental footprint in agriculture: A study on drone spraying vs. conventional methods.
Agricultural practices significantly contribute to resource depletion and greenhouse gas emissions, underscoring the urgent need for environmental sustainability in this sector. This research assesses the energy efficiency and environmental impacts of Unmanned Aerial Vehicle (UAV) technology compare...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0323779 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Agricultural practices significantly contribute to resource depletion and greenhouse gas emissions, underscoring the urgent need for environmental sustainability in this sector. This research assesses the energy efficiency and environmental impacts of Unmanned Aerial Vehicle (UAV) technology compared to traditional spraying methods for wheat farms in Lorestan province, Iran. Experiments were conducted randomly with three repetitions, and data were analyzed using Simapro Impact 2002 + software, evaluating four primary categories and 15 midpoint indicators. The findings reveal that conventional spraying consumes 2.43 times more energy than drone spraying, with values of 365.26 MJ/ha and 146.84 MJ/ha, respectively. Additionally, the Global Warming Potential (GWP) for pesticide application is 41.284 kg CO2ha-1 for conventional methods and 14.485 kg CO2ha-1 for drones. Diesel emissions from tractors in traditional spraying represent the most significant environmental burden, while battery production and charging for drones contribute the largest share among various impacts. These results highlight the potential of UAV technology to enhance energy efficiency and reduce environmental harm, promoting sustainable agricultural practices. Nonetheless, battery limitations and the need for training remain challenges, and further studies are required to assess long-term impacts and scalability. |
|---|---|
| ISSN: | 1932-6203 |