Guilherme Amorim Franchi

TY - JOUR

T1 - Estimating body weight in conventional growing pigs using a depth camera

AU - Amorim Franchi, Guilherme

AU - Bus, Jacinta

AU - Boumans, Iris

AU - Bokkers, Eddie

AU - Jensen, Margit Bak

AU - Pedersen, Lene Juul

PY - 2023/2

Y1 - 2023/2

N2 - 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.

AB - 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.

KW - 3D image

KW - Animal welfare

KW - Precision livestock farming

KW - Sensors

KW - Sus scrofa

KW - Weight gain

UR - http://www.scopus.com/inward/record.url?scp=85139190172&partnerID=8YFLogxK

U2 - 10.1016/j.atech.2022.100117

DO - 10.1016/j.atech.2022.100117

M3 - Journal article

VL - 3

JO - Smart Agricultural Technology

JF - Smart Agricultural Technology

M1 - 100117

ER -