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

Use of network analysis to capture key traits affecting tomato organoleptic quality / P., Carli; Arima, Serena; V., Fogliano; Tardella, Luca; A., Barone; L., Frusciante; M. R., Ercolano. - In: JOURNAL OF EXPERIMENTAL BOTANY. - ISSN 0022-0957. - STAMPA. - 60:12(2009), pp. 3379-3386. [10.1093/jxb/erp177]

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

ARIMA, SERENA;TARDELLA, Luca;
2009

Abstract

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
2009
01 Pubblicazione su rivista::01a Articolo in rivista
Use of network analysis to capture key traits affecting tomato organoleptic quality / P., Carli; Arima, Serena; V., Fogliano; Tardella, Luca; A., Barone; L., Frusciante; M. R., Ercolano. - In: JOURNAL OF EXPERIMENTAL BOTANY. - ISSN 0022-0957. - STAMPA. - 60:12(2009), pp. 3379-3386. [10.1093/jxb/erp177]
File allegati a questo prodotto
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/353821
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? 9
  • Scopus 38
  • ???jsp.display-item.citation.isi??? 34
social impact