Authors: Mohamed-Mahmoud Memmah; Bénédicte Quilot-Turion; Antoine Rolland
Addresses: INRA, UR1115 PSH, Domaine Saint Paul, F-84914 Avignon Cedex 9, France ' INRA, UR1052 GAFL, Domaine Saint Maurice, F-84143 Montfavet Cedex 9, France ' Laboratoire ERIC, Université de Lyon, 69676 Bron, France
Abstract: The model-based design of virtual fruit ideotypes using multi-objective optimisation algorithms could produce a high number of contrasted fruits. The breeder (decision-maker) will need an automatic tool allowing him/her to sort these contrasted ideotypes into predefined categories corresponding to several targeted traits. This paper aims to develop such a decision-making module to sort a set of fruit ideotypes into one of five preference-ordered categories in the context of brown rot-peach fruit pathosystem. First, a set of ideotypes with contrasted trade-off between three criteria was produced using multi-objective optimisation algorithms. Then, two multi-criteria decision-making methods (ELECTRE-Tri and DRSA: dominance-based rough set approach) were tested in order to reproduce the classification made by the decision-maker. Such a non-typical classification seemed difficult to be reproduced by the ELECTRE-TRI method while the decision rule-based method gave very good results (only 10% wrong assignments). The proposed decision-making tool is very useful to speed-up the model-based design of fruit ideotypes, i.e., breeding.
Keywords: MCDM; multicriteria decision making; ELECTRE-TRI; MR-sort; dominance-based rough sets; DRSA; model-based design; sustainable agriculture; multi-objective optimisation; virtual peaches; virtual fruit ideotypes; virtualisation; eco-friendly; environmentally friendly; sustainability; greening; environment friendly; sustainable development; decision makers; targeted traits; preference ordering; brown rot; non-typical classification; rule-based methods; decision making tools; fruit breeders; fruit breeding.
International Journal of Multicriteria Decision Making, 2014 Vol.4 No.4, pp.348 - 366
Received: 24 Sep 2013
Accepted: 14 May 2014
Published online: 14 Jan 2015 *