Time-series models on somatic cell score improve detection of mastitis

Acta Agriculturae Scandinavica A: Animal Sciences

Volumn 58, Issue 4, 2008, Pages 165-169

  Norberg, E ^a   Korsgaard, I R ^a   Sloth, K H M N ^b   Lovendahl P ^a  

^a AARHUS UNIVERSITY   (Denmark)

^b AgroTech A/S   (Denmark)

Author keywords

Dairy cattle; Mastitis; Somatic cell score; Time series models

Indexed keywords

BOS;

EID: 57649114707     PISSN: 09064702     EISSN: 16511972     Source Type: Journal    
DOI: 10.1080/09064700802621143     Document Type: Article

References (15)

1. Cornou, C., & Lundbye-Christensen, S. (2008). Classifying sows' activity types from acceleration patters. An application of the multi-process Kalman filter. Applied Animal Behaviour Science, 111, 262-273.
2. DeMol, R. M., Keen, A., Kroeze, G. H., & Achten, J. M. F. H. (1999). Description of a detection model for oestrus and diseases in dairy cattle based on time series analysis combined with a Kalman filter. Computers and Electronics in Agriculture, 22, 171-185.
3. Emanuelson, U. (1988). Recording of production disease in cattle and possibilities for genetic improvement: A review. Livestock Production Science, 20, 89-106.
4. Friggens, N. C., Chagunda, M. G. G., Bjerring, M., Ridder, C., Højsgaard, S., & Larsen, T. (2007). Estimating the degree of mastitis from time-series measurements in milk: A test of a model based on lactate dehydrogenase measurements. Journal of Dairy Science, 90, 5415-5427.
5. Gonzalo, C., Linage, B., Carriedo, J. A., de la Fuente, F., & San Primitivo, F. (2006). Evaluation of the overall accuracy of the DeLaval cell counter for somatic cell counts in ovine milk. Journal of Dairy Science, 89, 4613-4619.
6. Madsen, P., Shariati, M., & Ødegård, J. (2008). Genetic analysis of somatic cell score in Danish Holsteins using a liability-normal mixture model. Journal of Dairy Science, 91, 4355-4364.
7. Madsen, T. N., Andersen, S., & Kristensen, A. R. (2005). Modelling the drinking patterns of young pigs using a state space model. Computers and Electronics in Agriculture, 48, 39-62.
8. Negussie, E., Koivula, M., Mäntysaari, E. A., & Lidauer, M. (2006). Genetic evaluation of somatic cell score in dairy cattle considering first and later lactations as two different but correlated traits. Journal of Animal Breeding and Genetics, 123, 224-238.
9. Nielsen, H. M., Friggens, N. C., Løvendahl, P., Jensen, J., & Ingvartsen, K. L. (2003). Influence of breed, parity and stage of lactation on lactational performance and relationship between body fatness and live weight. Livestock Production Science, 79, 119-133.
10. Norberg, E., Hogeveen, H., Korsgaard, I. R., Friggens, N. C., Sloth, K. H. M. N., & Løvendahl, P. (2004). Electrical conductivity of milk - ability to predict mastitis status. Journal of Dairy Science, 87, 1099-1107.
11. Sarikaya, H., & Bruckmaier, R. M. (2006). Importance of the sampled milk fraction for the prediction of total quarter somatic cell count. Journal of Dairy Science, 89, 4246-4250.
12. Sloth, K. H. M. N., Friggens, N. C., Løvendahl, P., Andersen, P. H., Jensen, J., & Ingvartsen, K. L. (2003). Potential for improving description of bovine udder health status by combined analysis of milk measures. Journal of Dairy Science, 86, 1221-1232.
13. Smith, A. F. M., & West, M. (1983). Monitoring renal transplants: An application of the multi-process Kalman filter. Biometrics, 39, 867-878.
14. Thysen, I. (1993). Monitoring bulk tank somatic cell counts by a multi-process Kalman filter. Acta Agriculturæ Scandinavica, Section A, Animal Science, 43, 58-64.
15. Van Bebber, J., Reinsch, N., Junge, W., & Kalm, E. (1999). Monitoring daily milk yield with a recursive test day repeatability model (Kalman filter). Journal of Dairy Science, 82, 2421-2429.