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Considerations when combining data from multiple nutrition experiments to estimate genetic parameters for feed

L C Hardie1, L E Armentano2, R D Shaver2

  • 1Department of Animal Sciences, Iowa State University, Ames 50011.

Journal of Dairy Science
|February 10, 2015
PubMed
Summary
This summary is machine-generated.

Combining data from multiple nutrition studies helps estimate genetic parameters for feed efficiency in cows. This approach uses cohort data to calculate diet energy densities, improving residual feed intake calculations.

Keywords:
energy densityfeed efficiencygenetic selectionresidual feed intake

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Area of Science:

  • Animal Science
  • Genetics
  • Nutritional Physiology

Background:

  • Genomic selection requires reference populations linking genotypes to phenotypes.
  • Measuring feed efficiency in livestock is crucial but challenging, often necessitating data sharing.
  • International collaboration is vital for traits that are costly or difficult to measure.

Purpose of the Study:

  • To estimate genetic parameters for feed efficiency by combining data from multiple nutrition studies.
  • To assess the feasibility of using experimental cohorts to estimate diet net energy of lactation (NE(L)) densities.
  • To improve the calculation of residual feed intake (RFI) by accounting for diet energy variations.

Main Methods:

  • Utilized individual feed intake and production data from 13 Midwestern nutrition experiments involving 600 lactating cows.
  • Calculated two measures of residual feed intake: RFI(Mcal) and RFI(kg), based on NE(L) intake or dry matter intake (DMI).
  • Estimated realized NE(L) densities for 46 cow cohorts based on energy expenditures (milk, body weight change, maintenance) and DMI.

Main Results:

  • Heritability estimates for both RFI(kg) and RFI(Mcal) were 0.04 using a single-trait animal model.
  • The average realized energy density of diets was 1.58 Mcal/kg.
  • The method provided a way to standardize intake data across different conditions.

Conclusions:

  • Combining data from similar nutrition studies is a viable strategy for estimating genetic parameters for feed efficiency.
  • Estimating realized diet energy density within cohorts can refine RFI calculations.
  • This approach may aid in standardizing intake data and exploring genotype-by-diet interactions.