Potential value of linear type traits for the prediction of intake, efficiency and economic margins in dairy cattle

R. F. Veerkamp*, G. Simm, P. Persaud

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Production, food intake, efficiency, health and reproduction are all of importance in dairy cattle breeding goals. Measuring these traits on a large scale is not easy and therefore there is great interest in correlated traits for potential use in selection indices. In this study the relationships between linear type traits, live weight and pedigree index for fat plus protein yield and (i) dry matter intake (DMI), (ii) gross energetic efficiency (EFF), (iii) margin over all food costs (MF) and (iv) margin over food, health and reproduction costs (MFHR) were investigated. Regression analysis showed that a large increase in the R2 was achieved when average live weight during lactation, live weight at calving and (i) linear type scored as a heifer (number of records available was 164) or (ii) sire transmitting ability for type (n = 302) were included in a regression model to predict either DMI, EFF, MF or MFHR. Different models showed that linear type traits were more valuable than live weight traits for the prediction of MFHR. Also, regression coefficients were obtained using Residual Maximum Likelihood procedures. Several linear type traits appeared to be of potential value for a selection index, eg angularity, rump angle and udder depth measured on the heifer. One s.d. change in angularity resulted in an increase of £79 in MFHR. The results were not conclusive enough to develop a selection index, but show that a combination of type, live weight and production are likely to be valuable components of future indices.

Original languageEnglish
Pages (from-to)179-189
Number of pages11
JournalLivestock Production Science
Volume38
Issue number3
DOIs
Publication statusPublished - 30 Apr 1994

Keywords

  • Dairy cattle
  • Feed efficiency
  • Profit
  • Type trait

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