Method for short-term prediction of milk yield at the quarter level to improve udder health monitoring
- Author
- Ines Adriaens, Tjebbe Huybrechts, Ben Aernouts, Katleen Geerinckx, Sofie Piepers (UGent) , Bart De Ketelaere and Wouter Saeys
- Organization
- 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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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8580270
- 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.
- 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.
- Chicago author-date
- 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.
- Chicago author-date (all authors)
- 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.
- 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.
- IEEE
- [1]I. Adriaens et al., “Method for short-term prediction of milk yield at the quarter level to improve udder health monitoring,” JOURNAL OF DAIRY SCIENCE, vol. 101, no. 11, pp. 10327–10336, 2018.
@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},
keywords = {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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