Modeling lactation curve and comparison of model’s fitness to different lactation data of indigenous and crossbred cows

Five lactation curve models were compared for their fitness to milk data of indigenous and crossbred cows using data from Bako Agricultural Research Center and Debre Zeit Research Station. The fit of the models was compared using the model R2 value. The overall mean R2 value was 81.5 ± 0.12% and was significantly (p < 0.001) affected by model type, data type, sire breed, parity, calving season and year, location and the interactions of model type with these fixed effects. The mean R2 values for the Incomplete Gamma with two parameters (IG (b = 1)), Inverse polynomial (IP), Exponential, Incomplete Gamma (IG (b ≠ 1)) and Parabolic exponential models were 90.1 ± 0.26, 90.2 ± 0.26, 67.2 ± 0.28, 74.7 ± 0.26 and 77.8 ± 0.26 percent, respectively. Higher values of R2 were obtained for the Debre Zeit (80.5 %) herd than Bako. The sire breeds Friesian (81.6%) crosses had significantly the highest R2 value compared to the other sire breeds. Cows that calved during Arfasa (83.4%) had a higher fit than those in other calving seasons. Among the data types considered, highest R2 was observed for monthly mean (85.6%) and monthly total (85.6 %) milk data types. Besides, cows in the sixth parity (81.3 %) and those that calved in 1993 (84.5 %) had the highest R2 value. The highest R2 was obtained for IP fitted to monthly mean (95.4 %) and monthly total (95.4 %) milk data followed by the IG (b = 1) fitted to monthly mean (93.2 %) and monthly total (93.2 %) milk data types. The IP followed by IG (b = 1) fitted to milk data of the crossbreds had the highest R2. The reverse is true for the indigenous breeds. Among the model type x parity, model type x season and model type x location interaction groups, the IP followed by IG (b = 1) had the highest R2 for all parities, calving seasons and locations. From this study it can be concluded Five lactation curve models were compared for their fitness to milk data of indigenous and crossbred cows using data from Bako Agricultural Research Center and Debre Zeit Research Station. The fit of the models was compared using the model R2 value. The overall mean R2 value was 81.5 ± 0.12% and was significantly (p < 0.001) affected by model type, data type, sire breed, parity, calving season and year, location and the interactions of model type with these fixed effects. The mean R2 values for the Incomplete Gamma with two parameters (IG (b = 1)), Inverse polynomial (IP), Exponential, Incomplete Gamma (IG (b ≠ 1)) and Parabolic exponential models were 90.1 ± 0.26, 90.2 ± 0.26, 67.2 ± 0.28, 74.7 ± 0.26 and 77.8 ± 0.26 percent, respectively. Higher values of R2 were obtained for the Debre Zeit (80.5 %) herd than Bako. The sire breeds Friesian (81.6%) crosses had significantly the highest R2 value compared to the other sire breeds. Cows that calved during Arfasa (83.4%) had a higher fit than those in other calving seasons. Among the data types considered, highest R2 was observed for monthly mean (85.6%) and monthly total (85.6 %) milk data types. Besides, cows in the sixth parity (81.3 %) and those that calved in 1993 (84.5 %) had the highest R2 value. The highest R2 was obtained for IP fitted to monthly mean (95.4 %) and monthly total (95.4 %) milk data followed by the IG (b = 1) fitted to monthly mean (93.2 %) and monthly total (93.2 %) milk data types. The IP followed by IG (b = 1) fitted to milk data of the crossbreds had the highest R2. The reverse is true for the indigenous breeds. Among the model type x parity, model type x season and model type x location interaction groups, the IP followed by IG (b = 1) had the highest R2 for all parities, calving seasons and locations. From this study it can be conclude