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Method for short-term prediction of milk yield at the quarter level to improve udder health monitoring
- Adriaens, Ines, Huybrechts, Tjebbe, Aernouts, Ben, Geerinckx, Katleen, Piepers, Sofie, De Ketelaere, Bart, Saeys, Wouter
- Journal of dairy science 2018 v.101 no.11 pp. 10327-10336
- data collection, farms, lactation, mastitis, milk, milk yield, milking frequency, milking machines, monitoring, prediction, statistical models, udder quarters, wood, Sweden
- Udder health problems are often associated with milk losses. These losses are different between quarters, as infected quarters are affected both by systemic and pathogen-specific local effects, whereas noninfected quarters are only subject to systemic effects. To gain insight in these losses and the milk yield dynamics during disease, it is essential to have a reliable reference for quarter-level milk yield in an unperturbed state, mimicking its potential yield. We developed a novel methodology to predict this quarter milk yield per milking session, using an historical data set of 504 lactations collected on a test farm by an automated milking system from DeLaval (Tumba, Sweden). Using a linear mixed model framework in which covariates associated with the linearized Wood model and the milking interval are included, we were able to describe quarter-level yield per milking session with a proportional error below 10%. Applying this model enables us to predict the milk yield of individual quarters 1 to 50 d ahead with a mean prediction error ranging between 8 and 20%, depending on the amount of historical data available to estimate the random effect covariates for the predicted lactation. The developed methodology was illustrated using 2 examples for which quarter-level milk losses are calculated during clinical mastitis. These showed that the quarter-level mixed model allows us to gain insight in quarter lactation dynamics and enables to calculate milk losses in different situations.