Comparison of mathematical models to describe the lactation curve in mares
DOI:
https://doi.org/10.15381/rivep.v35i1.25463Keywords:
equine, lactation, mare's milk, mathematical models, nonlinear regressionAbstract
Six non-linear mathematical models were evaluated (Wood, modified Wood, Quadratic, Sikka, Singh-Gopal and Cobby) to determine their ability to fit to describe the lactation curve in mares. The modeling was carried out from 197 records of milk production from mares between 2 and 190 days of lactation. The models were fitted using non-linear regression algorithms and were evaluated through the following comparison criteria: MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error), RMSE (Root Mean Squared Error), AIC (Akaike information criterion), BIC (Bayesian information criterion) and residual analysis. The Wood, Singh-Gopal, modified Wood and Sikka models predicted that maximum milk production varies between 10 and 13 kg/day, which occurs between 30 and 42 days postpartum. According to the criteria evaluated, the Wood and Singh-Gopal models presented the best fit and were suitable for modeling lactation curves in equids.
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Copyright (c) 2024 Ricardo Rosero-Noguera, Sandra L. Posada-Ochoa, Jose R. Martinez-Aranzales
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