mathematical modeling of egg production curve in khazak indigenous hens

The number of eggs produced in a given period (egg production rate) is an important trait in layers that change over time and can be presented as a curve. this study aimed to fit the weekly egg production data of khazak indigenous hens using non-linear regression models and to select an appropriate model for describing the egg production curve for this bird. biweekly egg production of 144 laying hens over 52 weeks of egg production was used to evaluate the egg production curve. seven non-linear models (gamma, mcnally, compartmental ii, nelder, yang, lokhorst, and narushin-takma) were fitted to egg production data. the four goodness fit criteria (akaike’ s information criterion, mean square error, log likelihood, and bayesian information criterion) were used to compare the models. the results of the goodness of fit criteria showed that the narushin-takma and yang models were the best and worst models, respectively, for describing the egg production curve of khazak hens. the time and egg production at the peak with the narushin-takma model was similar to the actual values, and this model was significantly better than other studied models. the correlation between actual and predicted egg production indicated that the narushin-takma model could accurately predict the egg production of this breed. as a result, the narushin-takma model can be used to predict the egg production curve of khazak hens in breeding programs and nutritional management.