Comparison of linear and nonlinear functions and covariance structures to estimate feed intake pattern in growing pigs

Abstract

The objective of this study was to find the best function and covariance structure to estimate feed intake pattern in growing pigs for breeding purposes in order to optimise the feed intake curve corresponding to lean growth rate. Daily feed intake from 81 group-housed pigs was recorded using electronic feeders. The animals were tested during 120 days on average, from 30 to 119 kg. Polynomials, Kanis, yield–density, segmented and sigmoidal functions showed high similarity in goodness-of-fit. For selection on early feed intake, linear-segmented, logistic and Richards functions resulted in the most usable estimates within the test period. As shown by simulation, parameters of logistic function resulted in the lowest bias. Covariance among residuals of subsequent daily feed intakes was accounted for using the structures variance components, compound symmetry (CS), first-order autoregressive AR[1], first-order autoregressive moving-average ARMA[1,1], heterogeneous CS, heterogeneous AR[1] and the power-of-the-mean variance model. Correlation structure ARMA[1,1] resulted in the best fit of the data, with estimates for autoregressive parameter ρ from 0.90 to 0.97 and for moving average parameter λ from 0.35 to 0.51. The power-of-the-mean variance model was a good characterisation of variance heterogeneity and the final estimated power was 2.008 with standard error 0.3245. Based on these results, linear-segmented and logistic functions were the most parsimonious functions to characterise feed intake from which selection criteria can be derived, such as the age at which the feed intake plateau or the age at which the maximum increment in feed intake per day is reached in order to change feed intake curve corresponding to lean growth curve.