JDS Communications (Nov 2021)

An alternative interpretation of residual feed intake by phenotypic recursive relationships in dairy cattle

  • Xiao-Lin Wu,
  • Kristen L. Parker Gaddis,
  • Javier Burchard,
  • H. Duane Norman,
  • Ezequiel Nicolazzi,
  • Erin E. Connor,
  • John B. Cole,
  • Joao Durr

Journal volume & issue
Vol. 2, no. 6
pp. 371 – 375

Abstract

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There has been increasing interest in residual feed intake (RFI) as a measure of net feed efficiency in dairy cattle. Residual feed intake phenotypes are obtained as residuals from linear regression encompassing relevant factors (i.e., energy sinks) to account for body tissue mobilization. By rearranging the single-trait linear regression, we showed a causal RFI interpretation underlying the linear regression for RFI. It postulates recursive effects in energy allocation from energy sinks on dry matter intake, but the feedback or simultaneous effects are nonexistent. A Bayesian recursive structural equation model was proposed for directly predicting RFI and energy sinks and estimating relevant genetic parameters simultaneously. A simplified Markov chain Monte Carlo algorithm was described. The recursive model is asymptotically equivalent to one-step linear regression for RFI, yet extends the analytical capacity to multiple-trait analysis.