ATR-FTIR-based rapid solution for the discrimination of lentils from different origins, with a special focus on PGI and Slow Food typical varieties

被引:8
作者
Biancolillo, A. [1 ]
Foschi, M. [1 ]
Di Micco, M. [1 ]
Di Donato, F. [1 ]
D'Archivio, A. A. [1 ]
机构
[1] Univ Aquila, Dept Phys & Chem Sci, Via Vetoio, I-67100 Laquila, Italy
关键词
Lentils; Classification; Geographical origin; PLS-DA; SIMCA; LENS-CULINARIS MEDIK; PARTIAL LEAST-SQUARES; GEOGRAPHICAL ORIGIN; INFRARED-SPECTROSCOPY; IDENTIFICATION; ADULTERATION; LANDRACES; DIVERSITY;
D O I
10.1016/j.microc.2022.107327
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Three hundred forty-six (346) samples of lentils have been collected and analyzed by ATR-MIR spectroscopy. Of the investigated individuals, 283 were harvested in two Central-Italy regions (Umbria and Abruzzo), whereas the others were grown in Canada. At first, Partial Least Squares Discriminant Analysis (PLS-DA) was used to discriminate samples among the three origins. The outcome of PLS-DA analysis was noteworthy: only one individual (over 86 of the external test set) was erroneously assigned by the model, indicating the suitability of the proposed approach. Furthermore, Variable Importance in Projection (VIP) was exploited to inquire which spectral variables significantly contribute to the discrimination. Eventually, the focus has been circumscribed to two categories of high-valued lentils, e.g., lentils from Castelluccio di Norcia (CDN), a sub-set of the Umbria class, and from Santo Stefano di Sessanio (SSS), a sub-set of the Abruzzo class. These are of particular interest because CDN presents the Protected Geographical Indication (PGI) while SSS belongs to the Slow Food Presidium. The models for these classes provided interesting results.
引用
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页数:8
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