Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot Systems
2024
Kécia M. Bastos | Jardel P. Barcelos | Guilherme F. Orioli | Sheila T. Nascimento
In line with the concept of precision agriculture, this study aimed to validate the use of digital aerial images captured using a remotely piloted aircraft (RPA) for collecting zootechnical data on cattle feedlot systems in a tropical environment. Images were captured on 21 non-consecutive days in 110 pens with up to 150 animals each. Conventional and RPA-based methods were adopted to determine animal behavior, feed trough levels, animal counts, and pen conditions. Data analysis revealed almost perfect agreement (kappa coefficient = 0.901) between trough readings taken by conventional and RPA methods as well as substantial agreement for fecal score (kappa coefficient = 0.785) and surface conditions (kappa coefficient = 0.737). However, animal counts and water quality scores showed only fair agreement, suggesting challenges in using RPA for these specific tasks. The results indicated that RPA represents a viable alternative to conventional methods for monitoring zootechnical indices in feedlots, offering benefits in terms of accuracy, efficiency, and cost-effectiveness. The implementation of RPA-based methods holds potential for improving animal management, welfare, and yield in feedlot systems.
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