Estimation of 305-day milk yield from test-day records of Chinese Holstein cattle

Autor: Ling-na Kong, Jian-bin Li, Rong-ling Li, Xiu-xin Zhao, Ya-bin Ma, Shao-hua Sun, Jin-ming Huang, Zhi-hua Ju, Ming-hai Hou, Ji-feng Zhong
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Journal of Applied Animal Research, Vol 46, Iss 1, Pp 791-797 (2018)
Druh dokumentu: article
ISSN: 0971-2119
0974-1844
09712119
DOI: 10.1080/09712119.2017.1403918
Popis: This study compared six models, namely the Gaines, Sikka, Nelder, Wood, Dhanoa and Hayashi models, for the estimation of 305 days milk yield in Chinese Holstein cattle. We compared their ability to reliably predict 305-day lactation yield from incomplete (3 or 6 test-day (TD)) records. Our findings revealed that the accuracies (ACC) were 0.6655–0.9948, 0.8652–0.9977 and 0.9169–0.9968, whereas the mean square errors (MSE) were 0.0121–2.4807, 0.0139–1.0716 and 0.0170–0.5528 when 3 TD records were used in the first, second and higher lactations, respectively; when 6 TD records were used, the ACC were 0.8800–0.9992, 0.8742–0.9998 and 0.7950–0.9996, whereas the MSE values were 0.0017–0.3348, 0.0011– 0.8605 and 0.0021–1.4869 in the first, second and higher lactations, respectively. All the models were fitted more accurately with 6 TD than 3 TD records. Further analysis revealed that the curves made by the Nelder, Wood and Dhanoa models were close to the actual curves. These three models can be used to predict the 305-day yield for management decisions in farms and for the genetic evaluation of Chinese Holstein cattle.
Databáze: Directory of Open Access Journals
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