Animal (Sep 2022)

Describing the distribution type of DM intake for dairy cow pens based on pen characteristics

  • P.M. Lucey,
  • H.A. Rossow

Journal volume & issue
Vol. 17
p. 100888

Abstract

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In practice, cows are fed by pen, but a diet is formulated to the nutrient requirements of a single cow. If the DM intake (DMI) of a pen were equal for all cows, this approach would have no error, but cows are grouped into pens on pregnancy and other management factors creating a distribution of DMI. The goal of precision feeding is to meet the requirements of individual animals to increase efficiency and reduce environmental impact but is not achieved when a group is fed as if the individuals have uniform requirements and the DMI distribution is not normal. The hypothesis of this work is that the DMI of cow pens are not normally distributed and the total DMI from the best-fit distribution shape for a cow pen will have lower percentage error to the observed DMI than a prediction of a single DMI that is fed at a uniform level and assumes a normal distribution. Our objective was to describe the distribution shape of DMI by week of lactation, and for different pen types. Pens were generated by randomly assorting cows by the week of lactation from a database into different categories of pen for size and lactation period. These pens were fitted to the best distribution type, and its parameters were used to randomly generate distribution plots that predict the total DMI for each pen. A second predictive model estimated the DMI of each pen using an empirical equation of DMI that was multiplied by the number of cows in the pen to represent feeding of a uniform DMI quantity. The percentage error for the distribution shape model was significantly lower than the empirical model with pen errors being less than 1%. The beta distribution type was the most common distribution to best represent the data of pen DMI. Describing the distribution and using it to predict a total pen DMI provides accurate estimates of feed quantity for a group. Reducing error by using the distribution of DMI for feed formulation, instead of the nutrient requirements of an individual animal can provide a precision nutrition approach to group feeding.

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