Comparison of Eleven Mathematical Models for describing the first Lactation Curve of Holstein Cattle in Turkey

In this study, eleven standard lactation curve models (Incomplete Gamma (WD), Quadratic (Q), Cubic (C), Linear Hyperbolic Function (LH), Inverse Polynomial Function (IP), Mixed Log (MIL), Exponential (WIL), Dhanoa (DH), Cobby and Le Du (CD), Polynomial Regression (AS) and New Model (NM)) were used to predict a typical dairy cow lactation derived as the average daily milk yield of 105 complete first lactations of Holstein- Friesian cows in one herd. Milk yield controls were made daily in this farm. Total milk yield (TMY) was calculated from observation of daily milk yield. TMY was also predicted by using 11 different models. The total milk yields predicted by the models were very close to each other and the differences between observation of TMY were not found statistically significant (P>0.05). The models were found to be adequate for estimation of milk yield. Determination coefficients (R2) of the models ranged from 67.15 % to 86.68 %. In comparison of the models, the TMY, peak yield (PY), peak time (PT), persistency (P), mean square prediction error (MSPE), approximation error ( ε ), reliability criterion for estimating trustworthiness of the determination coefficient (σ ), standard error ( θ ) and Durbin-Watson (DW) values were evaluated together. Using the AS, WD and new developed NM models accurately predicted the milk yield of Holstein cows