Determining the Factors Affecting 305-Day Milk Yield of Dairy Cows with Regression Tree
2021
Serdar Genç | Mehmet Mendes
The purpose of this study was to determine the factors affecting the 305-day milk yield of dairy cattle by using Regression Tree Analysis (RTA). The data set of this study consisted of 8 different cattle breeds grown in Turkey. Breed (B), Province (P), Lactation Length (LL), Service Period (SP), Dry Period (DP), Parity (PR), Calving Year (CY), Calving Age (CA) and Calving Month (CM) were used to predict the 305-day milk yield. Results of RTM showed that the usage of this method might be appropriate for determining the important factors that would be able to affect the 305-day milk yield (R2=71.3%). It was seen that the most important factors affecting the 305-day milk yield were the Breed, Lactation Length, Province, and Parity. Therefore, those selected factors were more efficient than the others in predicting the 305-day milk yield. RTA results also indicated that the lowest milk yield was estimated for Jersey, Jersey Crossbred, and Yerli Kara. Among the highest 305-day milk yield cows, the milk yield estimates of the cows in the second, third, fourth, fifth, and the sixth parities were found significantly higher than that of the cows in the first and seventh parities.
Mostrar más [+] Menos [-]Palabras clave de AGROVOC
Información bibliográfica
Este registro bibliográfico ha sido proporcionado por Directory of Open Access Journals
