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JXB Advance Access originally published online on October 18, 2005
Journal of Experimental Botany 2005 56(422):3071-3081; doi:10.1093/jxb/eri304
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© The Author [2005]. Published by Oxford University Press [on behalf of the Society for Experimental Biology]. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

RESEARCH PAPER

Simulating genotypic variation of fruit quality in an advanced peachxPrunus davidiana cross

B. Quilot1,*, M. Génard2, F. Lescourret2 and J. Kervella1

1Unité de Génétique et Amélioration des Fruits et Légumes, INRA, Domaine St Maurice, BP94, F-84143 Montfavet Cedex, France
2Unité de Recherche Plantes et Systèmes de Culture Horticoles, INRA, Domaine St Paul, Site Agroparc, F-84914 Avignon Cedex 9, France

* To whom correspondence should be addressed. Fax: +33 4 32 72 27 02. E-mail: quilot{at}avignon.inra.fr

Ecophysiological models are increasingly expected to describe genotypic variation within breeding populations. Accordingly, the ability of an ecophysiological model of peach to explain variation in fruit quality among 100 genotypes of a second backcross progeny derived from a clone of wild peach (Prunus davidiana) crossed with two commercial nectarine (Prunus persica) varieties was explored. Experimental measurements were carried out to calibrate the model for each genotype. The predictive quality of the model was tested on several independent datasets. The genotypic variation in dry and fresh growth of the fruit and the stone were effectively described by the model. Prediction of the amount of total sugar in flesh at maturity was accurate, whereas prediction of flesh dry matter content and total sugar concentration was suitable but less accurate. This approach and the results have allowed physiological processes to be ranked according to their contribution to the variation in fruit quality between genotypes. Fruit growth demand and the hydraulic conductance in the fruit were the main processes that explained the fruit quality variation. Shortcomings and further potential uses of the model are discussed.

Key words: Fruit, genotypic variation, growth, modelling, Prunus persica, sugars


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