Assessment of spline functions for estimating growth curve parameters of FUNAABAlpha chickens

Abstract

The objective of this study was to fit four spline linear regression models to describe the growth of FUNAAB-Alpha Chickens (FAC). Body weight  records of 300 FAC raised from day old till the 20th week were used to fit spline models of 3 (SP3), 4 (SP4), 5 (SP5) and 6 knots (SP6) using the REG procedure of SAS®. The data were first plotted to determine the most appropriate location of knots and they were placed at 4^th, 10^th and 16^th week of age for SP3; 4^th, 8^th, 12^th and 16^th week for SP4; 4^th, 7^th, 10^th, 14^th and 18^th week for SP5 and 3^rd, 6^th, 9^th, 12^th, 15^th and 18^th week for SP6, respectively. The hatch weight predicted by SP3 was observed to be highest while SP6 predicted the lowest hatch weight for male and female FAC. Regression coefficients ranged from -38.47 to 47.46 and -39.40 to 40.47 for the male and female, respectively. For all the models, the highest magnitude of these coefficients were estimated at early ages after hatching (at 3 to 10 weeks of age). Based on Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC) as the goodness-of-fit selection criteria, SP3 had the lowest value for AIC and BIC for male FAC while SP4 had the lowest value of AIC and BIC for the female FAC. It was concluded that spline models of lower knots (SP3 and SP4) were the best fit to describe the growth of male and female FAC respectively, and that growth rate at early stages of life of FAC may be good predictors of later growth  performance.

Keywords: Spline models, FAC, Knots, hatch weight, Akaike Information criterion.