A study of lactation curves in dairy cattle using the optimal design of experiments methodology

Abstract

In this paper, we have worked with some of the most popular models to fit the lactation curve. Lactation curves have received considerable attention in modelling dairy cattle milk production. These curves express the evolution over time of a cattle head's milk yield. Observations of milk production over a cycle have usually been carried out periodically (i.e. daily, weekly or monthly). Optimal experiment design allows one to know the times when a herd's milk production must be recorded. An experiment design is optimal when it achieves the best parameter estimates for the curve model. This work aims to study optimal designs for certain models such as quadratic polynomial, hyperbolic, exponentials and Wilmink models (WMs). Designs are observed to depend on models and must be compared to get to know if a design for a specific model has a good behaviour with another model. Design efficiency is the tool used for this comparison. Efficiency is a value between 0 and 1a design is good if its efficiency is close to 1. The WM designs perform well and are an improvement on those designs that are routinely used in daily observations. HIGHLIGHTS Optimal experiment design allows one to know the times when a herd's milk production must be recorded. The use of optimal design methodology greatly reduces the number of instances when dairy production has to be recorded. Optimal designs reduce the costs of experimentation by allowing parameters to be estimated with fewer experimental runs.