Investigating the effect of temporal, geographic, and management factors on US Holstein lactation curve parameters

Abstract

We fit the Wood's lactation model to an extensive database of test-day milk production records of US Holstein cows to obtain lactation-specific parameter estimates and investigated the effects of temporal, spatial, and management factors on lactation curve parameters and 305-d milk yield. Our approach included 2 steps as follows: (1) individual animal-parity parameter estimation with nonlinear least-squares optimization of the Wood's lactation curve parameters, and (2) mixedeffects model analysis of 8,595,413 sets of parameter estimates from individual lactation curves. Further, we conducted an analysis that included all parities and a separate analysis for first lactation heifers. Results showed that parity had the most significant effect on the scale (parameter a), the rate of decay (parameter c), and the 305-d milk yield. The month of calving had the largest effect on the rate of increase (parameter b) for models fit with data from all lactations. The calving month had the most significant effect on all lactation curve parameters for first lactation models. However, age at first calving, year, and milking frequency accounted for a higher proportion of the variance than month for first lactation 305-d milk yield. All parameter estimates and 305-d milk yield increased as parity increased; parameter a and 305-d milk yield rose, and parameters b and c decreased as year and milking frequency increased. Calving month estimates parameters a, b, c, and 305-d milk yield were the lowest values for September, May, June, and July, respectively. The results also indicated the random effects of herd and cow improved model fit. Lactation curve parameter estimates from the mixed-model analysis of individual lactation curve fits describe well US Holstein lactation curves according to temporal, spatial, and management factors.

Characteristics of Lactation Curve and Reproduction in Dairy Cattle

“…According to Hossein-Zadeh (2019), cows that produced twins had different values of Wood's model parameters compared to single-calf cows. Li et al (2022) conducted a large-scale study (8,595,413 lactations of cows from all regions of the USA) of the influence of environmental factors (milking frequency, parity, year and month of calving, region of the country) on parameters of the Wood lactation curve model. They found that parity most likely affects the scaling parameter (a), the post-peak lactation decline parameter (c) and milk yield for 305 days, while the month of calving most affects the pre-peak lactation raise parameter (b).…”