Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot Systems
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 1...
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MDPI AG
2024-11-01
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| Series: | AgriEngineering |
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| Online Access: | https://www.mdpi.com/2624-7402/6/4/253 |
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| author | Kécia M. Bastos Jardel P. Barcelos Guilherme F. Orioli Sheila T. Nascimento |
| author_facet | Kécia M. Bastos Jardel P. Barcelos Guilherme F. Orioli Sheila T. Nascimento |
| author_sort | Kécia M. Bastos |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-0b2b8d7dcac9475da113191f520ca8a9 |
| institution | DOAJ |
| issn | 2624-7402 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AgriEngineering |
| spelling | doaj-art-0b2b8d7dcac9475da113191f520ca8a92025-08-20T02:53:34ZengMDPI AGAgriEngineering2624-74022024-11-01644460447510.3390/agriengineering6040253Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot SystemsKécia M. Bastos0Jardel P. Barcelos1Guilherme F. Orioli2Sheila T. Nascimento3Department of Animal Science, State University of Maringá, Maringá 87020-900, PR, BrazilDepartment of Animal Science, State University of Maringá, Maringá 87020-900, PR, BrazilDepartment of Animal Science, State University of Maringá, Maringá 87020-900, PR, BrazilDepartment of Animal Science, State University of Maringá, Maringá 87020-900, PR, BrazilIn 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.https://www.mdpi.com/2624-7402/6/4/253aerial imaginganimal welfarebeef cattlecattlefeedlotRPA |
| spellingShingle | Kécia M. Bastos Jardel P. Barcelos Guilherme F. Orioli Sheila T. Nascimento Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot Systems AgriEngineering aerial imaging animal welfare beef cattle cattle feedlot RPA |
| title | Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot Systems |
| title_full | Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot Systems |
| title_fullStr | Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot Systems |
| title_full_unstemmed | Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot Systems |
| title_short | Use of Drones for Trough Reading, Animal Counting, and Production Monitoring in Feedlot Systems |
| title_sort | use of drones for trough reading animal counting and production monitoring in feedlot systems |
| topic | aerial imaging animal welfare beef cattle cattle feedlot RPA |
| url | https://www.mdpi.com/2624-7402/6/4/253 |
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