ASSESSMENT OF SPLINE FUNCTIONS FOR ESTIMATING GROWTH CURVE PARAMETERS OF FUNAAB-ALPHA 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  measurements 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, 10 and 16th week of age for SP3, 4, 8, 12 and 16th week for SP4, 4, 7, 10, 14 and 18th week for SP5 and 3, 6, 9, 12, 15 and 18th week for SP6 respectively. The hatch weight predicted by SP3 were observed to be highest while SP6 predicted the lowest hatch weight for male and female FAC. For all the models, the greatest growth rates were predicted for the first 3-10 weeks after hatching. Based on Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC) as the goodness-of-fit selection criteria, SP3 had the lowest value of AIC and BIC for male while SP3 and SP4, with similar values, had the lowest value of AIC and BIC for the female FAC. It was concluded that the spline models of lower knots (SP3 and SP4) were the best fit to describe the growth of FAC.