Estimating body weight in conventional growing pigs using a depth camera
Franchi, Guilherme Amorim (Aarhus University. Department of Animal and Veterinary Sciences)
Bus, Jacinta D. (Wageningen University and Research. Animal Production Systems Group)
Boumans, Iris J. M. M (Wageningen University and Research. Animal Production Systems Group)
Bokkers, Eddie (Wageningen University and Research. Animal Production Systems Group)
Jensen, Margit Bak (Aarhus University. Department of Animal and Veterinary Sciences)
Pedersen, Lene Juul (Aarhus University. Department of Animal and Veterinary Sciences)

Date:	2023
Abstract:	Automated body weight (BW) estimation can be a useful tool for continuous monitoring of growth in commercial pigs, whereas deviations could indicate welfare problems. We validated a depth camera for BW estimation in 251 conventional growing pigs on two farms. Scale-based BW of individual pigs was used as gold standard (Farm 1: 107 pigs, BW range: 16-130 kg, recorded on three days; Farm 2: 144 pigs BW range: 20-114 kg, recorded on nine days). The camera was placed above the individual feeding station (Farm 1) or multi-partitioned feeder (Farm 2) and combined with a radio frequency identification system. Whenever a pig visited the feeding site, three-dimensional images were taken, and all individual daily images were used to calculate the median individual estimated BW. The pen estimated BW was calculated by taking the median of all daily picture estimates. A very high agreement (Concordance Correlation Coefficient >0. 96) between scale-based BW and estimated BW was found on both farms at individual and pen level. Additionally, the individual-level and pen-level BW estimation errors of the median weight over the fattening period were low on both farms (≤3. 6%). Yet, the camera's BW estimation performance decreased in pigs weighing >110 kg on Farm 1. Whereas, on Farm 2, the performance decreased when pigs weighed approximately 60 kg and were subjected to a typical dietary change, which potentially increased the competition for access to the multi-partitioned feeder and, consequently, limited body boundary detection.
Grants:	European Commission 862919
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Sus scrofa ; Precision livestock farming ; Sensors ; 3D image ; Weight gain ; Animal welfare
Published in:	Smart Agricultural Technology, Vol. 3 (February 2023) , art. 100117, ISSN 2772-3755

DOI: 10.1016/j.atech.2022.100117

6 p, 6.4 MB

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Articles > Research articles
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