Outer product analysis of electronic nose and visible spectra: application to the measurement of peach fruit characteristics

Abstract Visual aspect and aroma are among the most important features of fruit that determine consumer preferences. Electronic nose and spectroscopic techniques have shown positive results in evaluating some basic analytical parameters of fruit and global features such as the cultivar. In this paper, we illustrate and discuss a study aimed at evaluating the improvement derived by the fusion of visible spectra and electronic nose data. These experiments were performed on a population of yellow peaches belonging to two cultivars. Each sample was measured by visible optical spectroscopy and by electronic nose. In addition, a number of reference parameters were also measured by conventional destructive methodologies. Collected data were analysed individually and then fused together in order to classify the two cultivars and to estimate the reference parameters. Data fusion was performed building the outer product matrix for each measurement. The set of matrices was then successively unfolded and analysed by conventional chemometrics tools. Results were improved using outer products, for instance in classification average percentage errors of 25, 10, and 7 for electronic nose, spectra, and outer product, respectively was achieved. Regression analysis provides the evidence of a substantial orthogonal appearance of the datasets, which offer former hidden information on fruit classification.