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Journal of Animal Science Abstract - Animal Genetics

Derivation of a new lamb survival trait for the New Zealand sheep industry1

 

This article in JAS

  1. Vol. 93 No. 8, p. 3765-3772
     
    Received: Mar 02, 2015
    Accepted: May 28, 2015
    Published: July 10, 2015


    2 Corresponding author(s): sylvie.vanderick@ulg.ac.be
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doi:10.2527/jas.2015-9058
  1. S. Vanderick 2*,
  2. B. Auvray,
  3. S.-A. Newman,
  4. K. G. Dodds,
  5. N. Gengler* and
  6. J. M. Everett-Hincks
  1. * Gembloux Agro-Bio Tech. University of Liege, Gembloux, Belgium
     Department of Mathematics and Statistics, University of Otago, P.O. Box 56, Dunedin, New Zealand
     AgResearch Limited, Invermay Agricultural Centre, AgResearch, Puddle Alley, Private Bag 50034, Mosgiel, New Zealand

Abstract

Previous research identified that a review of the current industry New Zealand lamb survival trait was necessary as its recording accuracy was reliant on farmers notifying their Sheep Improvement Limited bureau of lamb deaths. This paper reports the decision rules and genetic parameters for a new lamb survival trait for the New Zealand sheep industry. These rules define the new lamb survival trait (NEWSUR) using lamb birth fate (BFATE) codes and the presence/absence of lamb weight measurements. Six univariate animal models were tested and used to estimate variance or covariance components and the resulting direct and maternal heritabilities for NEWSUR. The models differed in the way they adjust for the effect of day of birth, the exclusion or inclusion of a litter (dam/year of birth) random effect, and the application or not of a logit transformation of the phenotypes. For both the linear and logistic methods, models including the random effect of litter provided the best fit for NEWSUR according to log-likelihood values. Log-likelihoods for the linear and logistic models cannot be compared; therefore, a cross-validation method was used to assess whether the logit transformation was appropriate by analyzing the predictive ability of the models. The mean square errors were slightly lower for the linear compared with the logistic model, and therefore, the linear model was recommended for industry use. The heritability attributed to direct effects ranged from 2 to 5.5%. A direct heritability of 5.5% resulted from a linear model without litter effect and omitting the effect of day of birth on survival, whereas a direct heritability of 2% resulted from the logistic model fitting a random litter effect. The heritability attributed to maternal genetic effects ranged from 1.9 to 7.7%. A maternal genetic heritability of 7.7% resulted from the logistic model omitting the litter effect, whereas a maternal genetic heritability of 1.9% resulted from the linear model fitting a random litter effect. The addition of the litter random effect substantially decreased the maternal heritabilities in all cases and was recommended for industry use to avoid overestimation of the maternal genetic variance. Sheep Improvement Limited has implemented NEWSUR and the associated genetic evaluation model based on information described in this paper. Industry-wide implementation will enable sheep breeders to produce more accurate genetic evaluations to their commercial clients.

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Copyright © 2015. American Society of Animal Science