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Prediction of breeding values for average fruit weight in mango using a multivariate individual mixed model

Hardner, C. M. and Bally, I. S. E. and Wright, C. L. (2012) Prediction of breeding values for average fruit weight in mango using a multivariate individual mixed model. Euphytica, 186 (2). pp. 463-477. ISSN 0014-2336

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Article Link(s): http://dx.doi.org/10.1007/s10681-012-0639-7

Abstract

Mango is an important horticultural fruit crop and breeding is a key strategy to improve ongoing sustainability. Knowledge of breeding values of potential parents is important for maximising progress from breeding. This study successfully employed a mixed linear model methods incorporating a pedigree to predict breeding values for average fruit weight from highly unbalanced data for genotypes planted over three field trials and assessed over several harvest seasons. Average fruit weight was found to be under strong additive genetic control. There was high correlation between hybrids propagated as seedlings and hybrids propagated as scions grafted onto rootstocks. Estimates of additive genetic correlation among trials ranged from 0.69 to 0.88 with correlations among harvest seasons within trials greater than 0.96. These results suggest that progress from selection for broad adaptation can be achieved, particularly as no repeatable environmental factor that could be used to predict G x E could be identified. Predicted breeding values for 35 known cultivars are presented for use in ongoing breeding programs.

Item Type:Article
Business groups:Horticulture and Forestry Science
Additional Information:ISI Document Delivery No.: 951CK Times Cited: 0 Cited Reference Count: 76 Hardner, C. M. Bally, I. S. E. Wright, C. L. Queensland Department of Primary Industries and Fisheries; Northern Territory Department of Resources; Western Australian Department of Agriculture; CSIRO We would like to acknowledge the efforts of Peter Johnson, Ping Lu, Alonzo Gonzales, David Hamilton, Richard Brettell, Sam Blakie, Chris Wicks, and Waren Muller, who contributed to the collection of the phenotypic data set used in this analysis. We would like to acknowledge the Queensland Department of Primary Industries and Fisheries, the Northern Territory Department of Resources, the Western Australian Department of Agriculture and CSIRO for their financial support of the National Mango Breeding project. We also thank Professor Ari Verbyla (University of Adelaide and CSIRO) for providing code for calculation of the probability of the Log-likelihood ratio statistic when the parameter is at the boundary after Stram and Lee 1996. Springer Dordrecht
Keywords:BLUP Linear mixed model Heritability Genetic correlation Genotype-by-environment interaction estimate genetic-parameters linear unbiased prediction x environment interactions subdivided target regions selection response phenotypic correlations quantitative traits eucalyptus-globulus quality traits genotype
Subjects:Plant culture > Fruit and fruit culture
Science > Botany > Genetics
Deposited On:09 Apr 2014 05:09
Last Modified:10 Apr 2014 15:08

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