| 저자(한글) |
Lee, Junsung,Seo, Jakyeom,Lee, Se Young,Ki, Kwang Seok,Seo, Seongwon |
| 초록 |
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. |
