Evaluation of Alternative Nonlinear Mixed Effects Models of Swine Growth

Alternative versions of a common three-parameter nonlinear growth function were evaluated on two groups of gilts. Gilts were randomly assigned to be reared under all-in, all-out (AIAO; n = 96) or continuous flow (CF) management (n = 96). The addition of a single random effect, in which the mature BW of each pig varies, provided a substantially better fit and smaller parameter standard errors. This model predicts a constant coefficient of variation between pigs. The addition of a second random effect further improved the likelihood statistics and reduced the residual standard deviation, although the impact was much smaller. The inclusion of the second random effect accounts for different patterns of growth between pigs. Variations in the growth patterns allow greater fleiibility to describe the underlying variance/covariance structure of the serial live BW. For all miied effects models, the mean and approiimate variation in age required for pigs to reach a specific BW can be predicted. After 104 d of age, the growth of CF gilts declined more rapidly, and the standard deviation in days required to reach specific target BW (TBW) (110, 120, or 130 kg) increased more rapidly than for the AIAO gilts. These models are also easily adaptable to stochastic modeling.