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Automatic detection of lameness in gestating group-housed sows using positioning and acceleration measurements

Published online by Cambridge University Press:  06 January 2016

I. Traulsen ,
S. Breitenberger ,
W. Auer ,
E. Stamer ,
K. Müller  and
J. Krieter
I. Traulsen*
Affiliation:
Institute of Animal Breeding and Husbandry, Christian-Albrechts-University, Olshausenstr. 40, 24098 Kiel, Germany
S. Breitenberger
Affiliation:
Linz Center of Mechatronics GmbH, Altenberger Street 69, 4040 Linz, Austria
W. Auer
Affiliation:
MKW electronics GmbH, Jutogasse 3, 4675 Weibern, Austria
E. Stamer
Affiliation:
TiDa Tier und Daten GmbH, Bosseer Straße 4c, D-24259 Westensee/Brux, Germany
K. Müller
Affiliation:
Chamber of Agriculture Schleswig-Holstein, Gutshof 1, 24327 Blekendorf, Germany
J. Krieter
Affiliation:
Institute of Animal Breeding and Husbandry, Christian-Albrechts-University, Olshausenstr. 40, 24098 Kiel, Germany
*
†E-mail: itraulsen@tierzucht.uni-kiel.de
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Abstract

Lameness is an important issue in group-housed sows. Automatic detection systems are a beneficial diagnostic tool to support management. The aim of the present study was to evaluate data of a positioning system including acceleration measurements to detect lameness in group-housed sows. Data were acquired at the Futterkamp research farm from May 2012 until April 2013. In the gestation unit, 212 group-housed sows were equipped with an ear sensor to sample position and acceleration per sow and second. Three activity indices were calculated per sow and day: path length walked by a sow during the day (Path), number of squares (25×25 cm) visited during the day (Square) and variance of the acceleration measurement during the day (Acc). In addition, data on lameness treatments of the sows and a weekly lameness score were used as reference systems. To determine the influence of a lameness event, all indices were analysed in a linear random regression model. Test day, parity class and day before treatment had a significant influence on all activity indices (P<0.05). In healthy sows, indices Path and Square increased with increasing parity, whereas variance slightly decreased. The indices Path and Square showed a decreasing trend in a 14-day period before a lameness treatment and to a smaller extent before a lameness score of 2 (severe lameness). For the index acceleration, there was no obvious difference between the lame and non-lame periods. In conclusion, positioning and acceleration measurements with ear sensors can be used to describe the activity pattern of sows. However, improvements in sampling rate and analysis techniques should be made for a practical application as an automatic lameness detection system.

Keywords

lamenesssowsensorpositioning systemacceleration
Type
Research Article
Information
animal , Volume 10 , Issue 6 , June 2016 , pp. 970 - 977
Copyright
© The Animal Consortium 2016 

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References

Alsaaod, M, Römer, C, Kleinmanns, J, Hendriksen, K, Rose-Meierhöfer, S, Plümer, L and Büscher, W 2012. Electronic detection of lameness in dairy cows through measuring pedometric activity and lying behavior. Applied Animal Behaviour Science 142, 134–141.Google Scholar
Blackie, N, Bleach, E, Amory, J and Scaife, J 2011. Impact of lameness on gait characteristics and lying behaviour of zero grazed dairy cattle in early lactation. Applied Animal Behaviour Science 129, 67–73.Google Scholar
Bonde, M, Rousing, T, Badsberg, JH and Sørensen, JT 2004. Associations between lying-down behaviour problems and body condition, limb disorders and skin lesions of lactating sows housed in farrowing crates in commercial sow herds. Livestock Production Science 87, 179–187.CrossRefGoogle Scholar
Buchner, H, Savelberg, H, Schamhardt, HC and Barneveld, A 1996. Head and trunk movement adaptations in horses with experimentally induced fore- or hindlimb lameness. Equine Veterinary Journal 28, 71–76.Google Scholar
Cador, C, Pol, F, Hamoniaux, M, Dorenlor, V, Eveno, E, Guyomarc’h, C and Rose, N 2014. Risk factors associated with leg disorders of gestating sows in different group-housing systems: a cross-sectional study in 108 farrow-to-finish farms in France. Preventive Veterinary Medicine 116, 102–110.CrossRefGoogle ScholarPubMed
Corr, SA, McCorquodale, CC, McGovern, RE, Gentle, MJ and Bennett, D 2003. Evaluation of ground reaction forces produced by chickens walking on a force plate. American Journal of Veterinary Research 64, 76–82.Google Scholar
D’Eath, RB 2012. Repeated locomotion scoring of a sow herd to measure lameness: consistency over time, the effect of sow characteristics and inter-observer reliability. Animal Welfare 21, 219–231.Google Scholar
Díaz, JA and Boyle, LA 2014. Effect of rubber slat mats on the behaviour and welfare of group housed pregnant sows. Applied Animal Behaviour Science 151, 13–23.Google Scholar
Engblom, L, Eliasson-Selling, L, Lundeheim, N, Belák, K, Andersson, K and Dalin, A 2008. Post mortem findings in sows and gilts euthanised or found dead in a large Swedish herd. Acta Veterinaria Scandinavica 50, 25–34.Google Scholar
Fall, N, Gröhn, Y, Forslund, K, Essen-Gustafsson, B, Niskanen, R and Emanuelson, U 2008. An observational study on early-lactation metabolic profiles in Swedish organically and conventionally managed dairy cows. Journal of Dairy Science 91, 3983–3992.Google Scholar
Gjein, H and Larssen, R 1995. The effect of claw lesions and claw infections on lameness in loose housing of pregnant sows. Acta Veterinaria Scandinavica 36, 451–459.CrossRefGoogle ScholarPubMed
Heinonen, M, Oravainen, J, Orro, T, Seppä-Lassila, L, Ala-Kurikka, E, Virolainen, J, Last, A and Peltoniemi, OA 2006. Lameness and fertility of sows and gilts in randomly selected loose-housed herds in Finland. The Veterinary Record 159, 383–387.Google Scholar
Heinonen, M, Peltoniemi, O and Valros, A 2013. Impact of lameness and claw lesions in sows on welfare, health and production. Livestock Science 156, 2–9.CrossRefGoogle Scholar
Hurvich, CM and Tsai, C 1989. Regression and time series model selection in small samples. Biometrika 76, 297–307.CrossRefGoogle Scholar
Jørgensen, B 2000. Osteochondrosis/osteoarthrosis and claw disorders in sows, associated with leg weakness. Acta Veterinaria Scandinavica 41, 123–138.CrossRefGoogle ScholarPubMed
Juarez, S, Robinson, P, DePeters, E and Price, E 2003. Impact of lameness on behavior and productivity of lactating Holstein cows. Applied Animal Behaviour Science 83, 1–14.Google Scholar
Keegan, KG, Wilson, DA, Wilson, DJ, Smith, B, Gaughan, EM, Pleasant, RS, Lillich, J.D. and Kramer, J 1998. Evaluation of mild lameness in horses trotting on a treadmill by clinicians and interns or residents and correlation of their assessments with kinematic gait analysis. American Journal of Veterinary Research 59, 1370–1377.Google Scholar
Kramer, E, Stamer, E, Spilke, J, Thaller, G and Krieter, J 2009. Analysis of water intake and dry matter intake using different lactation curve models. Journal of Dairy Science 92, 4072–4081.Google Scholar
Law, AM 2007. Simulation modeling and analysis, 4th edition. McGraw-Hill, Boston, MA, USA.Google Scholar
Littell, RC, Milliken, GA, Stroup, WW, Wolfinger, RD and Schabenberger, O 2006. SAS for mixed models, user’s manual. SAS Institute Inc., Cary, NC, USA, pp. 174–203.Google Scholar
Main, DC, Clegg, J, Spatz, A and Green, LE 2000. Repeatability of a lameness scoring system for finishing pigs. The Veterinary Record 147, 574–576.CrossRefGoogle ScholarPubMed
McGlone, JJ and Newby, BE 1994. Space requirements for finishing pigs in confinement: behavior and performance while group size and space vary. Applied Animal Behaviour Science 39, 331–338.Google Scholar
Mohling, CM, Johnson, AK, Coetzee, JF, Karriker, LA, Abell, CE, Millman, ST and Stalder, KJ 2014. Kinematics as objective tools to evaluate lameness phases in multiparous sows. Livestock Science 165, 120–128.Google Scholar
Nalon, E, Conte, S, Maes, D, Tuyttens, F and Devillers, N 2013. Assessment of lameness and claw lesions in sows. Livestock Science 156, 10–23.Google Scholar
Pichler, M, Rudic, B, Breitenberger, S and Auer, W 2014. Robust positioning of livestock in harsh agricultural environments. In 14th Mechatronics Forum International Conference (Mechatronics 2014). Karlstad, Sweden, 16-18 June 2014. ed. LJ De Vin), pp. 527–534. Curran, Red Hook, NY, USA.Google Scholar
Pluym, L, van Nuffel, A and Maes, D 2013aTreatment and prevention of lameness with special emphasis on claw disorders in group-housed sows. Livestock Science 156, 36–43.Google Scholar
Pluym, LM, Maes, D, Vangeyte, J, Mertens, K, Baert, J, van Weyenberg, S, Millet, S and van Nuffel, A 2013bDevelopment of a system for automatic measurements of force and visual stance variables for objective lameness detection in sows: SowSIS. Biosystems Engineering 116, 64–74.CrossRefGoogle Scholar
SAS Institute 2014. SAS/STAT user’s guide version 9.3. SAS Institute Inc., Cary, NC, USA.Google Scholar
Sawalha, RM, Keown, JF, Kachman, SD and van Vleck, LD 2005. Evaluation of autoregressive covariance structures for test-day records of Holstein cows: estimates of parameters. Journal of Dairy Science 88, 2632–2642.Google Scholar
Schwarz, G 1978. Estimating the dimension of a model. The Annals of Statistics 6, 461–464.Google Scholar
Stavrakakis, S, Guy, JH, Warlow, O, Johnson, GR and Edwards, SA 2014. Walking kinematics of growing pigs associated with differences in musculoskeletal conformation, subjective gait score and osteochondrosis. Livestock Science 165, 104–113.CrossRefGoogle Scholar
Sun, G, Fitzgerald, RF, Stalder, KJ, Karriker, KJ, Johnson, AK and Hoff, SJ 2011. Development of an embedded microcomputer-based force plate system for measuring sow weight distribution and detection of lameness. Applied Engineering in Agriculture 27, 475–482.Google Scholar
Tapper, KR, Johnson, AK, Karriker, LA, Stalder, KJ, Parsons, RL, Wang, C and Millman, ST 2013. Pressure algometry and thermal sensitivity for assessing pain sensitivity and effects of flunixin meglumine and sodium salicylate in a transient lameness model in sows. Livestock Science 157, 245–253.Google Scholar
Tuyttens, F, de Graaf, S, Heerkens, J, Jacobs, L, Nalon, E, Ott, S, Stadig, L, van Laer, E and Ampe, B 2014. Observer bias in animal behaviour research: can we believe what we score, if we score what we believe? Animal Behaviour 90, 273–280.Google Scholar
von Wachenfelt, H, Nilsson, C and Pinzke, S 2010. Gait and force analysis of provoked pig gait on clean and fouled rubber mat surfaces. Biosystems Engineering 106, 86–96.Google Scholar
Vorstenbosch, M, Buchner, H, Savelberg, H, Schamhardt, HC and Barneveld, A 1997. Modeling study of compensatory head movements in lame horses. American Journal of Veterinary Research 58, 713–718.Google Scholar
Weary, DM, Huzzey, JM and von Keyserlingk, MAG 2009. Board-invited review: using behavior to predict and identify ill health in animals. Journal of Animal Science 87, 770–777.Google Scholar
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