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Meta-analysis of factors affecting milk component yields in dairy cattle
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  • Meta-analysis of factors affecting milk component yields in dairy cattle
  • Meta-analysis of factors affecting milk component yields in dairy cattle
저자명
Lee. Junsung,Seo. Jakyeom,Lee. Se Young,Ki. Kwang Seok,Seo. Seongwon
간행물명
한국동물자원과학회지
권/호정보
2014년|56권 5호|pp.5-6 (2 pages)
발행정보
한국동물자원과학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

The objectives of this study were thus to identify most significant factors that determine milk component yield (MCY) using a meta-analysis and, if possible, to develop equations to predict MCY using variables that can be easily measured in the field. A literature database was constructed based on the research articles published in the Journal of Dairy Science from Oct., 2007 till May, 2010. The database consisted of a total of 442 observed means for MCY from 118 studies. The candidate factors that determine MCY were those which can be routinely measured in the field (e.g. DMI, BW, dietary forage content, chemical composition of diets). Using a simple linear regression, the best equations for predicting milk fat yield(MFY) and milk protein yield (MPY) were $MFY=0.351({pm}0.068)+0.038({pm}0.003)$ DMI ($R^2=0.27$), and $MPY=0.552({pm}0.071)+0.031({pm}0.002)DMI-0.004({pm}0.001)$ FpDM (%, forage as a percentage of dietary DM) ($R^2=0.38$), respectively. The best equation for predicting milk fat content (%) explained only 12% of variations in milk fat content, and none of a single variable can explain more than 5% of variations in milk protein content. We concluded that among the tested variables, DMI was the only significant factor that affects MFY and both DMI and FpDM significantly affect MPY. However, predictability of linear equations was relatively low. Further studies are needed to identify other variables that can predict milk component yield more accurately.