EVALUATION OF EGG PRODUCTION CURVES OF SHIKABROWN® PARENTS USING MATHEMATICAL MODELS

EVALUATION OF EGG PRODUCTION CURVES OF SHIKABROWN® PARENTS USING MATHEMATICAL MODELS

Abstract:

This study was conducted to evaluate egg production curves of Shikabrown® parents, using mathematical models. A total of 200 birds: 100from each of the two strains of Shikabrown® parents (sire and dam) lines at the Breeding Unit of Poultry Research Programme, National Animal Production Research Institute (NAPRI) were used for the study. The birds were obtained from the selected lines (sire and dam) and were denoted as strain A and strain B, respectively. Body weight (BWT), age at sexual maturity (ASM), egg number (EGGNO), and egg weight (EWT) were examined. Four non-linear models (Logistic, Richard, Gompertz, and Exponential) and a linear model were used to predict the efficiency of weekly bodyweight and egg production traits. Genetic parameters (heritability, genotypic and phenotypic) correlations were estimated for egg production. Genetic parameters were estimated using VARCOMP procedure of SAS. The adequacies of the models were fitted using R Package, version 3.0.3.High coefficients of determination for BWT (R2 = 0.84 – 0.93) were recorded in the models for both strains. Strain A had higher R2 (0.93) for BWT in Richard, Gompertz and Exponential models while strain B recorded (R2 = 0.89) in Logistic, Richard and Gomprtz models. High coefficient of determination was obtained in a reproductive trait; egg number; in which almost all the models gave (R2 = 0.70). Exponential model recorded a higher R2 (0.93) for EGGNO in strain A. This suggests that the strains had similar age at sexual maturity and it implies that the birds‟ genetic potential can be further exploited for more genetic improvement. EWT in strain A recorded higher R2 (0.96) coefficient of determination across the four nonlinear models except linear model with (R2 = 0.95) for egg weight. Significant (P<0.05) differences were recorded within models for the egg production traits studied. Significant differences (P<0.05) were observed in the birds‟ performance for BWT and EWT, with strain B having a higher BWT (1.59±0.01) and strain A having a higher EWT (48.75±0.17). Similarly, age of xvi birds in lay had a concomitant significant differences (P<0.05) in their BWT as well as their EWT. The birds performed better for BWT and EWT in week 26 and 27 for both strains. Strain B had higher heritability estimates (h2=0.45) while the least estimates (h2=0.10) was recorded in strain A for EGGNO. ASM recorded the highest estimates (h2=0.48) in strain A while least value (h2=0.18)was observed in strain B. BWT had high genotypic correlations with EWT (rg= 0.88) and ASM (rg= 0.48) in strain A. EGGNO had low genotypic correlation with BWT (rg= 0.01). EWT had negative and low genotypic correlation with EGGNO (rg= -0.05).ASM was negatively correlated with EGGNO (rg= -0.93) and EWT (rg= -0.05). It was concluded that strain significantly (P<0.05) had effect on BWT and EWT of Shikabrown® parent with stain B performing better than strain A in BWT and strain A better than strain B in EWT. Coefficient of determination (R2) obtained from Richard; MLR and Gompertz models can be used to estimate egg number, body and egg weights. R2 identified differences between strains in predicting egg production traits. Strain B was adjudged good and profitable because the strain had the highest mean values in body weight and egg number and it is being recommended as one of the lines for future improvement of Shikabrown®. Egg weights of Shikabrown® should be improved based on the recorded genetic variability in the parents.

EVALUATION OF EGG PRODUCTION CURVES OF SHIKABROWN® PARENTS USING MATHEMATICAL MODELS

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