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Across-site heterogeneity of genetic and environmental variances in the genetic evaluation of Eucalyptus globulus trials for height growth


Costa e Silva, J and Dutkowski, GW and Borralho, NMG, Across-site heterogeneity of genetic and environmental variances in the genetic evaluation of Eucalyptus globulus trials for height growth, Annals of Forest Science, 62, (2) pp. 183-191. ISSN 1286-4560 (2005) [Refereed Article]

DOI: doi:10.1051/forest:2005010


Height data from six 3-year-old Eucalyptus globulus trials with cloned progenies were jointly analysed with a heterogeneous variances model. Significant heterogeneity between trial sites was detected for additive genetic and environmental variances, corresponding to coefficients of variation of 41% and 26%, respectively. Two additive genetic and four environmental variances were significantly different from common estimates across all trials. Significant heterogeneity was also detected for heritability estimates, which ranged from 13.5% to 40.3%. Genetic evaluations of parents and clones within full-sib families were obtained from the heterogeneous variances model, and from a simpler model assuming variance homogeneity across trial sites and using either unadjusted data or data pre-adjusted by scale transformations. Changes in predictions of breeding values, top ranking genotypes and selection responses were examined to assess the impact of ignoring heterogeneous variances on the genetic evaluation. Clones were more sensitive than parents to the assumption of homogeneous variances in the evaluation model. Nevertheless, ignoring variance heterogeneity decreased the response to clonal selection by only 2% relatively to the evaluation based on the heterogeneous variances model. Pre-adjusting the data to constant phenotypic or environmental variances reduced the variance heterogeneity. The latter scale transformation was somewhat more effective in increasing fairness of selection, and resulted in close to optimal ranking and selection response. On the basis of the results of this study, Best Linear Unbiased Prediction was fairly robust to erroneously assuming homogeneous variances in a genetic evaluation model. © INRA, EDP Sciences, 2005.

Item Details

Item Type:Refereed Article
Research Division:Agricultural, Veterinary and Food Sciences
Research Group:Forestry sciences
Research Field:Tree improvement (incl. selection and breeding)
Objective Division:Plant Production and Plant Primary Products
Objective Group:Environmentally sustainable plant production
Objective Field:Environmentally sustainable plant production not elsewhere classified
UTAS Author:Dutkowski, GW (Mr Greg Dutkowski)
ID Code:38577
Year Published:2005
Web of Science® Times Cited:29
Deposited By:Plant Science
Deposited On:2005-08-01
Last Modified:2006-05-09

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