• Livestock
• Economics

A model to predict the variation in nutrient utilisation for different purposes in monogastric animals

We developed a modelling approach that has multiple applications in precision livestock farming, nutrition, and selective breeding. The approach is demonstrated through three case studies on monogastric livestock: growth in pigs, and reproduction in sows and in laying hens. Comparison of trait variability across these species and traits shows common aspects that they share as well as their distinctive features. This methodology comprises a data-driven (top-down) approach, where models are fitted to phenotypic trait data obtained from multiple individual animals; and a simulation (bottom-up) approach, where population phenotypic variation is derived and summarised by the average and deviation (i.e., median and confidence interval) for each modelled trait. The approach has the following benefits in relation to current alternatives: 1) Making no prior assumptions about the distributions of traits and their correlations within the population; specifically, it is assumed that the population traits are distributed according to the trait distribution in the group of sampled animals (nonparametric approach). 2) Being computationally faster than current parametric approaches; specifically, the distribution of traits in the wider population is inferred from that in the sample through a process of individual resampling. 3) Having no specific requirements on the size and quality of the datasets input.