Daily milk yield correction factors: What are they?

Xiao-Lin Wu; George R Wiggans; H Duane Norman; Asha M Miles; Curtis P Van Tassell; Ransom L Baldwin Vi; Javier Burchard; Joao Durr

doi:10.3168/jdsc.2022-0230

Daily milk yield correction factors: What are they?

JDS Commun. 2022 Dec 1;4(1):40-45. doi: 10.3168/jdsc.2022-0230. eCollection 2023 Jan.

Authors

Xiao-Lin Wu^{1

2}, George R Wiggans¹, H Duane Norman¹, Asha M Miles³, Curtis P Van Tassell³, Ransom L Baldwin Vi³, Javier Burchard¹, Joao Durr¹

Affiliations

¹ Council on Dairy Cattle Breeding, Bowie, MD 20716.
² Department of Animal and Dairy Sciences, University of Wisconsin, Madison 53706.
³ USDA, Agricultural Research Service, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705-2350.

Abstract

Cows are typically milked 2 or more times on a test-day, but not all these milkings are sampled and weighed. The initial approach estimated a test-day yield with doubled morning (AM) or evening (PM) yield in the AM-PM milking plans, assuming equal AM and PM milking intervals. However, AM and PM milking intervals can vary, and milk secretion rates may be different between day and night. Statistical methods have been proposed to estimate daily yields in dairy cows, focusing on various yield correction factors in 2 broad categories: additive correction factors (ACF) and multiplicative correction factors (MCF). The ACF are evaluated by the average differences between AM and PM milk yield for various milking interval classes, coupled with other categorical variables. We show that an ACF model is equivalent to a regression model of daily yield on categorical regressor variables, and a continuous variable for AM or PM yield with a fixed regression coefficient of 2.0. Similarly, a linear regression model can be implemented as an ACF model with the regression coefficient for AM or PM yield estimated from the data. The linear regression models improved the accuracy of the estimates compared with the ACF models. The MCF are ratios of daily yield to yield from single milkings, but their statistical interpretations vary. Overall, MCF were more accurate for estimating daily milk yield than ACF. The MCF have biological and statistical challenges. Systematic biases occurred when ACF or MCF were computed on discretized milking interval classes, leading to accuracy loss. An exponential regression model was proposed as an alternative model for estimating daily milk yields, which improved the accuracy. Characterization of ACF and MCF showed how they improved the accuracy compared with doubling AM or PM yield as the daily milk yield. All the methods performed similarly with equal AM and PM milkings. The methods were explicitly described to estimate daily milk yield in AM and PM milking plans. Still, the principles generally apply to cows milked more than 2 times a day and apply similarly to the estimation of daily fat and protein yields with some necessary modifications.