Abstract
Food legumes (Fabaceae) form an important part of the human diet; besides, several Fabaceae species are acknowledged for their high levels of bioactive compounds, among which are isoflavones, being recognised for their varied types of biological activity. The aim of this work was to classify different varieties of three types of legumes (chickpeas, lentils and beans) according to their isoflavone contents. The analysis of isoflavones was carried out using high-performance liquid chromatography coupled to triple quadrupole tandem mass spectrometry (HPLC-MS/MS). To extract the analytes, a modified QuEChERS approach was used. The chromatographic peak areas obtained, after scaling in Pareto mode, were used to build statistical models. Both supervised and unsupervised techniques were applied for the classification of the different types of pulses analysed in the study: principal component analysis (PCA), hierarchical cluster analysis (HCA) and partial least squares discriminant analysis (PLS-DA). The statistical models were validated by internal validation, obtaining satisfactory results for the different matrices. PCA models allowed the differentiation between subspecies, but not subspecies, varieties or ecotypes. The results provided by HCA and PLS-DA revealed that the different species and subspecies of beans and the different varieties and subvarieties of lentils can be distinguished, and even the different ecotypes of the same variety in the case of chickpeas. This study revealed that it was possible to differentiate among species, subspecies, varieties and even ecotypes of different types of legumes based on their isoflavone content.
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