Modelling lactation curve for fat to protein ratio in Holstein cows
Journal Title: Animal Science Papers and Reports - Year 2016, Vol 34, Issue 3
Abstract
The objective of this study was to examine seven mathematical models to evaluate their efficiency in describing the lactation curve for fat to protein ratio (FPR) in the first three lactations of Iranian Holsteins. Data were 8,103,044 test-day records for FPR from the first three lactations of Iranian Holstein cows which were collected in 2392 dairy herds from 1991 to 2014 by the Animal Breeding Center of Iran. Each model was fitted to test-day records of FPR using the NLIN and MODEL procedures in SAS. The models were tested for goodness of fit using adjusted coefficient of determination, root mean square error, Durbin-Watson statistic (DW), Akaike’s information criterion (AIC) and Bayesian information criterion (BIC). The highest values of FPR were observed in early lactation, which was followed by a decline as the lactation progressed and an increase toward the end of the lactation period. For the first three parities, Dijkstra model provided the lowest AIC and BIC values, whereas Nelder model had the greatest values of AIC and BIC. Therefore, Dijkstra equation provided the best fit of FPR for the first three parities of Holstein cows, and Nelder model was fitted worst. According to DW values, it seems that there was only a slight or no problem of residual autocorrelation for FPR in Iranian Holsteins. After selecting an appropriate mathematical model to describe lactation curve of FPR, it is possible to develop an optimal strategy to obtain a desired shape of lactation curve through modifying the parameters of model.
Authors and Affiliations
Navid Ghavi Hossein-Zadeh
Keywords
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