Age–related optimal performance of ISA Brown layers in the tropics

Main Article Content

A. Yakubu
S. Aguda


The identification of appropriate models to optimize the performance of layers will help boost poultry production. This study aimed at evaluating the production characteristics of Isa Brown layers in cages and to estimate the age of optimal production using two different regression models. A total of two hundred and forty hens on cage were utilized in the study. There were three replicates of sixteen cells each containing five birds. The parameters measured were weekly body weight (BW), feed intake (FI), water intake (WI), number of birds that died (mortality, MTLY), cumulative egg number (CEN) per week, hen-day egg production (HDEP), hen–housed egg production (HHEP) and egg weight (EW). Data were collected from 25 to 70 weeks of age. The effect of age (25, 30, 35, 40, 45, 50, 55, 60, 65 and 70 weeks) on weekly BW, FI, WI, MTLY, CEN, HDEP, HHEP and EW was determined using one-way analysis of variance (ANOVA). Where there were significant differences in the means of the seven production parameters based on age, they were separated using Duncan’s Multiple Range Test procedure. Linear and quadratic functions were fitted to predict the performance parameters from age. With the exception of MTLY (P > 0.05) which was not affected by age, other parameters increased significantly (P < 0.05) with age. The quadratic model appeared to be better in forecasting performance parameters [coefficient of determination (R2) of: 0.863 versus 0.761 (BW), 0.797 versus 0.793 (FI), 0.745 versus 0.531 (WI), 0.853 versus 0.414 (CEN), 0.843 versus 0.380 (HDEP), 0.870 versus 0.483 (HHEP) and 0.876 versus 0.838 (EW)]. This prediction model revealed that BW, FI, CEN, HDEP, HHEP and EW would attain optimal limits at ages 64.93, 66.67, 53.49, 53.30, 54.23 and 81.28 weeks of laying, respectively. The implication is that at appropriate ages based on the quadratic models, the production characteristics of Isa Brown layers can be targeted for maximal production.

Article Details

Research Article