Predicting ad libitum dry matter intake and yields of Jersey cows.
Two data files were used that contained weekly mean values for ad libitum DMI of lactating Jersey cows along with appropriate cow, ration, and environmental traits for predicting DMI. One data file (n = 666) was used to develop prediction equations for DMI because that file represented a number of separate experiments and contained more diversity in potential predictors, especially those related to ration, such as forage type. The other data file (n = 1613) was used primarily to verify these equations. Milk protein yield displaced 4% FCM output as a prediction variable and improved the R2 by several units but was not used in the final equations, however, for the sake of simplicity. All equations contained adjustments for the effects of heat stress, parity (1 vs. > 1), DIM > 15, BW, use of recombinant bST, and other significant independent variables. Equations were developed to predict DMI of cows fed individually or in groups and to predict daily yields of 4% FCM and milk protein; equations accounted for 0.69, 0.74, 0.81, and 0.76 of the variation in the dependent variables with standard deviations of 1.7, 1.6, 2.7, and 0.084 kg/ d, respectively. These equations should be applied to the development of software for computerized dairy ration balancing.
Holter
J B
JB
Department of Animal and Nutritional Sciences, University of New Hampshire, Durham 03824, USA.
West
J W
JW
McGilliard
M L
ML
Pell
A N
AN
D000821:Animal Feed; D000818:Animals; D001835:Body Weight; D002417:Cattle / Q000502:physiology*; D004043:Dietary Fiber / Q000008:administration & dosage; D004435:Eating; D005260:Female; D013006:Growth Hormone / Q000008:administration & dosage; D050356:Lipid Metabolism; D008892:Milk / Q000737:chemistry / Q000378:metabolism; D008894:Milk Proteins / Q000378:metabolism; D010298:Parity; D012044:Regression Analysis; D012820:Silage
D004043:Dietary Fiber; D008894:Milk Proteins; D013006:Growth Hormone