Abstract
Geographical classification and authentication of lentils (Lens culinaris Medik.) was attempted by discriminant and modelling pattern-recognition methods applied to multi-elemental composition determined by means of inductively coupled plasma optical emission spectrometry (ICP-OES). After microwave-assisted digestion, the content of 15 elements was determined in 89 Italian lentil samples produced in three relatively close areas of the Central Apennines (Castelluccio di Norcia, Colfiorito and Santo Stefano di Sessanio) and 20 samples imported from Canada. Preliminary exploration of the ICP-OES data revealed a visible effect of the production year on the mineral composition. A good geographical classification of the lentil samples was obtained by discriminant approaches. Class models generated by Soft Independent Model Class Analogy presented high sensitivity (all the calibration and external samples were correctly accepted by the target classes) and good specificity since most of non-compliant samples were refused by each of the four modelled classes.
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