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Existing beef cow feed intake prediction equations were evaluated using recent data. New models were developed, accounting for 68% of intake variation, offering improved accuracy for nonlactating and lactating beef cows.

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Area of Science:

  • Animal Science
  • Ruminant Nutrition
  • Beef Cattle Production

Background:

  • Accurate prediction of feed intake is crucial for efficient beef cow management.
  • Existing equations, such as those from NRC (1987, 1996), have limitations in predicting dry matter intake (DMI) in beef cows.
  • Previous models were developed using data predating 2002 and may not reflect current production systems.

Purpose of the Study:

  • To validate the accuracy of existing feed intake prediction equations using recent data (post-2002).
  • To develop and propose alternative, more accurate prediction models for beef cow feed intake.

Main Methods:

  • Evaluated six established feed intake prediction equations (NRC 1987, NRC 1996, Hibberd and Thrift 1992).
  • Compiled a dataset of 53 nonlactating and 32 lactating cow treatment means from studies published since 2002.
  • Developed new empirical models using regression analysis, incorporating shrunk body weight (SBW) and diet net energy for maintenance (NEm).

Main Results:

  • The NRC (1996) equation underestimated feed intake for nonlactating cows (average deviation 2.4 kg/d) and lactating cows (average deviation 3.0 kg/d).
  • Both nonlactating and lactating equations showed significant deviations in slope and intercept compared to observed data.
  • The best-fit empirical model developed in this study explained 68% of the variation in daily feed intake.

Conclusions:

  • Existing feed intake prediction equations require updating to accurately reflect current beef cow production.
  • The newly developed empirical models show promise for improved DMI prediction in beef cows.
  • Further validation of the proposed equations with independent datasets is recommended.