Testing the potential of the Sow Stance Information System (SowSIS) based on a force plate system built into an electronic sow feeder for on-farm automatic lameness detection in breeding sows
Briene, Petra; Szczodry, Olga; De Geest, Pieterjanet al.
2021 • In Biosystems Engineering, 204, p. 270 - 282
Breeding sows; Electronic sow feeder; Force plate; Lameness detection; Stance; Classification models; Data collection; Linear mixed models; Multi variables; Predictive values; Random forest modeling; Visual analogue scale; Control and Systems Engineering; Food Science; Animal Science and Zoology; Agronomy and Crop Science; Soil Science
Abstract :
[en] Lameness is a common problem in breeding sows, which often goes undetected for long periods with severe consequences for animal welfare and farm productivity. Automatic lameness detection could help pig farmers to recognise and treat lameness sooner. The SowSIS (Sow Stance Information System) is a device consisting of four force plates and providing non-invasive force measurements per leg of the sow. In this study, the SowSIS was built into electronic sow feeders and validated for lameness detection in group-housed gestating sows. Data was automatically collected for 71 sows. Visual gait scoring was performed twice a week using a 150-mm tagged visual analogue scale to determine the sows' lameness status. Only data from 32 gait scoring days were included, adding up to 674 sow days. A sow was classified as lame using >60 mm as the cut-off value for the visual gait scores. Stance variables were calculated from the SowSIS data per sow per day. First, a multivariable linear mixed model was used to detect lameness, using stance variables with significant influence on the gait score. The model's performance was 78.5% sensitivity, 81.4% specificity, 80.7% accuracy, 57.4% lame predictive value and 92.2% non-lame predictive value. Second, five types of classification models were tested to determine the lame leg on a sub-dataset. The random forest model could predict the lame leg correctly 90% of the time. The SowSIS shows great promise as an on-farm lameness detection system, as it allows continuous non-invasive data collection in a practical setting.
Disciplines :
Animal production & animal husbandry
Author, co-author :
Briene, Petra ; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium
Szczodry, Olga ; Université de Liège - ULiège > Sphères ; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium
De Geest, Pieterjan ; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium
Van Weyenberg, Stephanie; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium
Van Nuffel, Annelies; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium
Vangeyte, Jürgen; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium
Millet, Sam; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium
Ampe, Bart; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium
Tuyttens, Frank A.M.; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium ; Ghent University, Veterinary Sciences, Merelbeke, Belgium
Maselyne, Jarissa; ILVO (Flanders Research Institute for Agriculture, Fisheries and Food), Merelbeke, Belgium
Language :
English
Title :
Testing the potential of the Sow Stance Information System (SowSIS) based on a force plate system built into an electronic sow feeder for on-farm automatic lameness detection in breeding sows
This research is part of a PhD programme funded by ILVO. The authors wish to thank the technicians of the Agricultural Engineering group of ILVO for the building, installing and technical support of the SowSIS. The authors also wish to thank José Rivera, the animal caretakers and interns of the experimental farm at ILVO for helping to collect the lameness data.
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