Testing the potential of the SowSIS for on-farm automatic lameness detection in breeding sows

Petra Briene, Olga Szczodry, Pieterjan De Geest, Annelies Van Nuffel, Sam Millet, Jürgen Vangeyte, Stephanie Van Weyenberg, Bart Ampe, Frank Tuyttens, Jarissa Maselyne

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureC3: Congres abstractpeer review


Lameness is a very common problem in breeding sows, which often goes undetected for long periods of time. This has severe consequences on the welfare and performance of sows. Automatic lameness detection could help pig farmers to recognize and treat the problem sooner. The Sow Stance Information System (SowSIS) consists of 4 force plates, built into an electronic sow feeder, providing non-invasive ‘stance’-output for each leg. Stance information variables can be extracted from the data. Stance data was automatically collected for 53 gestating group-housed sows for 74 days per sow. The gait of these sows was visually scored twice a week using a 150mm tagged visual analogue scale to determine their lameness status. This gait score was used as a reference and compared to the SowSIS measurements. First, significant variables were used in a multilevel linear model to predict lameness. With the model estimates, it was determined whether the model would classify a sow as lame or non-lame using gait score ≥55mm as the cut-off value. The model could detect lameness with 71.7% sensitivity, 89.7% specificity, 76.7% lame predictive value and 87.0% non-lame predictive value. The 5 severely lame sows (gait score >90mm) were all correctly classified as lame. Secondly, different linear models were tested to determine the lame leg on a sub-dataset. The support vector machine model and random forest model could predict the lame leg correctly by 100% when fitted to a validation dataset. The SowSIS shows great promise as an on-farm lameness detection system.
Oorspronkelijke taalEngels
TitelBook of Abstracts of the 70th Annual Meeting of the European Federation of Animal Science : Book of abstracts No. 25 (2019)
ISBN van geprinte versie978-90-8686-339-6
ISBN van elektronische versie978-90-8686-890-2
PublicatiestatusGepubliceerd - 26-aug.-2019
Evenement70th Annual Meeting of the European Federation of Animal Science: City of Ghent (Belgium), 26 - 30 Aug 2019 - Gent, Ghent, België
Duur: 26-aug.-201930-aug.-2019
Congresnummer: 70

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