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Statistical Methods Revisited for Estimating Daily Milk Yields: How Well do They Work?
Xiao-Lin Wu1,2, George R Wiggans1, H Duane Norman1
1Council on Dairy Cattle Breeding, Bowie, MD, United States.
Frontiers in Genetics
|August 29, 2022
Summary
Estimating daily milk yields (DMY) in cows is crucial. The exponential regression model offers the most accurate method for calculating DMY, outperforming other statistical approaches.
Area of Science:
- Animal Science
- Dairy Science
- Statistical Modeling
Background:
- Cost-effective milking plans supplement standard testing schemes.
- Accurate estimation of daily milk yields (DMY) is essential for dairy management.
- Existing methods for DMY estimation often rely on yield correction factors.
Purpose of the Study:
- To evaluate the performance of statistical methods for estimating DMY in Holstein and Jersey cows.
- To compare existing methods with a novel exponential regression model.
- To assess the impact of milking intervals on DMY estimation accuracy.
Main Methods:
- 10-fold cross-validation was used to assess method performance.
- Evaluated Additive Correction Factors (ACF), Multiplicative Correction Factors (MCF), linear regression, and an exponential regression model.
- Analyzed the influence of AM-PM milking interval variations on DMY estimates.
Main Results:
- All evaluated methods demonstrated high precision in DMY estimates.
- MCF and linear regression models showed smaller squared biases and greater accuracy than ACF models.
- The exponential regression model exhibited the highest accuracies and smallest squared biases for DMY estimation.
Conclusions:
- The exponential regression model is the most accurate method for estimating DMY in AM-PM milking plans.
- Unequal milking intervals significantly impact DMY estimation accuracy.
- The principles are applicable to cows milked more than twice daily.
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