Target list building for volatile metabolite profiling of fruit.

Fruit flavour is the combination of numerous biochemicals: sugars for sweetness, acids for sourness and volatile metabolites for aroma. The objective of this study was to establish a method to develop a target list of statistically relevant compounds for the characterization of melon from non-targeted data, while preserving the profile information. Five different varieties were sampled (sampling 12 biological replicates from 12 plants) using dynamic headspace extraction, then analysed by gas chromatography-mass spectrometry in full scan mode. Using Metalign and SIMCA-P software the raw data was spectrally aligned and then subjected to principal component analysis (PCA). The principal component analysis plot showed good separation of the five varieties based on their full scan GC-MS profile. Mass spectral data points responsible for the differences between varieties were highlighted by further statistical analysis. The mass spectra were then reconstructed and the corresponding chemicals identified using library search or reference standards were available to create a new target component list. To validate the new target list, the initial data set was re-processed using the targeted approach and the results subjected again to principal component analysis. The two representations showed excellent agreement on the separation of the five varieties. The new target list obtained from this study can be applied to differentiate and characterize the volatile profile of melon varieties using a list of statistically significant compounds.