EVALUATION OF MODELS FOR EGG PRODUCTION IN CHICKENS,

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EVALUATION OF MODELS FOR EGG PRODUCTION IN CHICKENS,

ABSTRACT

Data on the monthly egg production of 2 strains (A and B) of Rhode Island chickens (500 breeder hens per strain) were used to test the goodness of fit of six mathematical models, viz; Exponential, Parabolic exponential. Wood’s Gamma and modified Gamma by McNally, Inverse polynomial and Linear regresion. Egg production was summarised for each hen into 28-d periods, starting from the day of first egg. The models were fitted to the mean results for periods of groups of hens. The three best models with highest R2 values were further compared on their ability to predict 52-week total egg production from part-production at 16, 20, and 24 weeks, on a hen-housed basis. The effect of cycle length on goodness of fit was also examined separately tor each of the three models. The heritabilities. genetic and phenotypic relationships between egg production traits and curve parameters obtained from fitting the three models to 52-week laying records in the 2 strains were investigated. A total of 356 and 292 records for strain A and B respectively, were included in a variance component analysis of a two factor nested classification of dams within sire. The egg production cycle (i.e. number of 28-d periods) varied from 9 to 15 periods in the 2 strains. The coefficients of determination (R2) range from 0.16 to 0.95 for strain A and from 0.10 to 0.93 for strain B from fittings to mean egg production data lor groups of hens. The results suggest that the ‘best’ three models that were chosen fitted 52 week laying records quite well, judging from their respective R2 values, which were higher tor McNally (0.91 – 0.95) and Parabolic exponential (0.90 0.93) than for Wood (0.55 0.75). However, their ability to predict 52-week egg production from part-records of 16, 20 and 24 wks varied. The prediction of total production based on fit to 24 week of data was more accurate for the McNally in strain A; while the Parabolic exponential performed better than the other 2 models in strain B. The McNally model consistently predicted less than the actual 52- week (except for 24-week data in strain B). But the other 2 models tended to over estimate production. The estimates of heritabilities and correlations for production traits were moderately high, while the values obtained for curve parameters varied from low to moderate. The estimates of correlations of part-productions with 52-week production were comparatively higher than the values obtained for curve parameters with 52-week production. The low estimates of heritability obtained for curve parameters indicate that it would be better to select on functions of the parameters (such as total or part-year production) which had higher estimates than the individual curve parameters. The high genetic correlations between part-year production and total production suggests that selection for the latter based on the former would not diminish genetic progress. The decreased generation interval that would result from selection on part-record will probably more than offset the loss in efficiency if records are taken for about half of the full laying year. It was concluded that based on the goodness of fit to 52-week production record and accuracy to predict full record egg production from part record, the McNally model gave the best results, and could therefore be said to have theoretical advantages over the other models. It may thus be found useful in decision making concerning replacement of layer flocks.

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