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

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.

Mulch materials in processing tomato: a multivariate approach

“…Tomato production was expressed through both marketable yield and marketable mean fruit weight; marketable and total fruit number, total yield and total and 2007and PC3 in 2008, in accordance with the results obtained by Carli et al (2009), and indicates that the red colour intensification in tomato fruits led to a decrease in the lightness of the fruit.…”

“…In 2007, marketable mean fruit weight was opposite to the total soluble solids and fruit dry matter (PC3) ( Table 1), in agreement with Molyneux et al (2004) and Ignatova et al (2008). However, these findings differ from those obtained by Carli et al (2009), who found a positive correlation between yield and fruit dry matter content. Particularly in 2007 (PC3 , Table 1), a strong positive correlation between total soluble solids and fruit dry matter was observed (Pearson correlation coefficient, 0.71), in agreement with Candido et al (2006) when comparing the effect of soil solarisation on a tomato crop.…”

Metabolomics reveals organ-specific metabolic rearrangements during early tomato seedling development

“…Genomics, in combination with metabolomics approaches have already allowed us to increase our understanding of important biochemical processes of tomato fruit development (Carrari et al 2006;Moco et al 2007;Capanoglu et al 2008;Carli et al 2009;Osorio et al 2011;Rohrmann et al 2011). A vast complexity of primary metabolites and secondary metabolites has been identified as being important factors involved in fruit ripening, quality and flavor.…”

The use of network analysis to uncover homeostatic responses of a drought-tolerant sugarcane cultivar under severe water deficit and phosphorus supply

“…Thus, the global connectance (C g ) analysis has been applied to access specific changes in biological networks built with elements of different natures, such as morphological (Amzallag 2001b;Souza et al 2004), photochemical ) and biochemical (Carli et al 2009), as well as with leaf gas exchange data (Prado et al 2004;Souza et al 2005Souza et al , 2009). The number and strength of connections among elements in a network are strongly related to system stability (Trewavas 1986;Edelman and Gally 2001;Souza et al 2004Souza et al , 2005Souza et al , 2009).…”