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Method for short-term prediction of milk yield at the quarter level to improve udder health monitoring

(2018) JOURNAL OF DAIRY SCIENCE. 101(11). p.10327-10336
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Abstract
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.
Keywords
dairy cow, milk loss, udder health, linear mixed model, CLINICAL MASTITIS, LACTATION CURVE, DAIRY-COWS, BOVINE MASTITIS, MODEL, INTERVAL, SYSTEM

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Chicago
Adriaens, Ines, Tjebbe Huybrechts, Ben Aernouts, Katleen Geerinckx, Sofie Piepers, Bart De Ketelaere, and Wouter Saeys. 2018. “Method for Short-term Prediction of Milk Yield at the Quarter Level to Improve Udder Health Monitoring.” Journal of Dairy Science 101 (11): 10327–10336.
APA
Adriaens, I., Huybrechts, T., Aernouts, B., Geerinckx, K., Piepers, S., De Ketelaere, B., & Saeys, W. (2018). Method for short-term prediction of milk yield at the quarter level to improve udder health monitoring. JOURNAL OF DAIRY SCIENCE, 101(11), 10327–10336.
Vancouver
1.
Adriaens I, Huybrechts T, Aernouts B, Geerinckx K, Piepers S, De Ketelaere B, et al. Method for short-term prediction of milk yield at the quarter level to improve udder health monitoring. JOURNAL OF DAIRY SCIENCE. 2018;101(11):10327–36.
MLA
Adriaens, Ines, Tjebbe Huybrechts, Ben Aernouts, et al. “Method for Short-term Prediction of Milk Yield at the Quarter Level to Improve Udder Health Monitoring.” JOURNAL OF DAIRY SCIENCE 101.11 (2018): 10327–10336. Print.
@article{8580270,
  abstract     = {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.},
  author       = {Adriaens, Ines and Huybrechts, Tjebbe and Aernouts, Ben and Geerinckx, Katleen and Piepers, Sofie and De Ketelaere, Bart and Saeys, Wouter},
  issn         = {0022-0302},
  journal      = {JOURNAL OF DAIRY SCIENCE},
  keyword      = {dairy cow,milk loss,udder health,linear mixed model,CLINICAL MASTITIS,LACTATION CURVE,DAIRY-COWS,BOVINE MASTITIS,MODEL,INTERVAL,SYSTEM},
  language     = {eng},
  number       = {11},
  pages        = {10327--10336},
  title        = {Method for short-term prediction of milk yield at the quarter level to improve udder health monitoring},
  url          = {http://dx.doi.org/10.3168/jds.2018-14696},
  volume       = {101},
  year         = {2018},
}

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