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JXB Advance Access published online on June 10, 2009

Journal of Experimental Botany, doi:10.1093/jxb/erp177
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© 2009 The Author(s).
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. This paper is available online free of all access charges (see
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RESEARCH PAPER

Use of network analysis to capture key traits affecting tomato organoleptic quality

Paola Carli1, Serena Arima2, Vincenzo Fogliano3, Luca Tardella2, Luigi Frusciante1 and Maria R. Ercolano1,*

1Department of Soil, Plant and Environmental and Animal Production Sciences, University of Naples ‘Federico II’, Via Università 100, 80055 Portici (NA), Italy
2Department of Statistics, Probability and Applied Statistics, University of Rome ‘La Sapienza’, P.le Aldo Moro 5, 00185 Rome, Italy
3Department of Food Science, University of Naples ‘Federico II’, Via Università 100, 80055 Portici (NA), Italy

* To whom correspondence should be addressed. E-mail: ercolano{at}unina.it

The long-term objective of tomato breeders is to identify metabolites that contribute to defining the target flavour and to design strategies to enhance it. This paper reports the results of network analysis, based on metabolic phenotypic and sensory data, to highlight important relationships among such traits. This tool allowed a reduction in data set complexity, building a network consisting of 35 nodes and 74 links corresponding to the 74 significant (positive or negative) correlations among the variables studied. A number of links among traits contributing to fruit organoleptic quality and to the perception of sensory attributes were identified. Modular partitioning of the characteristics involved in fruit organoleptic perception captured the essential fruit parameters that regulate interactions among different class traits. The main feature of the network was the presence of three nodes interconnected among themselves (dry matter, pH, and °Brix) and with other traits, and nodes with widely different linkage degrees. Identification of strong associations between some metabolic and sensory traits, such as citric acid with tomato smell, glycine with tomato smell, and granulosity with dry matter, suggests a basis for more targeted investigations in the future.

Key words: Flavour, metabolic profiling, network analysis, sensory analysis, tomato

Received 20 March 2009; Revised 30 April 2009 Accepted 6 May 2009


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