Geographical origin discrimination of lentils (Lens culinaris Medik.) using 1H NMR fingerprinting and multivariate statistical analyses. (15th December 2017)

• Record Type: Journal Article
• Authors: Longobardi, Francesco; Innamorato, Valentina; Di Gioia, Annalisa; Ventrella, Andrea; Lippolis, Vincenzo; Logrieco, Antonio F.; Catucci, Lucia; Agostiano, Angela
• Is Part Of: Food chemistry. Volume 237(2017)
• Page Start: 743
• Page End: 748
• Publication Date: 2017-12-15
• Subjects: 1H NMR fingerprinting -- Lentils -- Geographical origin -- Chemometrics; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2017.05.159
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Geographic origin of lentils was discriminated by 1 H NMR fingerprint and chemometrics. 1 H NMR was used in an untargeted approach. Different supervised methods were tested. External validation procedures were applied on the supervised models. LDA gave 100% classification and test set prediction performances. Abstract: Lentil samples coming from two different countries, i.e. Italy and Canada, were analysed using untargeted 1 H NMR fingerprinting in combination with chemometrics in order to build models able to classify them according to their geographical origin. For such aim, Soft Independent Modelling of Class Analogy (SIMCA), k-Nearest Neighbor (k-NN), Principal Component Analysis followed by Linear Discriminant Analysis (PCA-LDA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were applied to the NMR data and the results were compared. The best combination of average recognition (100%) and cross-validation prediction abilities (96.7%) was obtained for the PCA-LDA. All the statistical models were validated both by using a test set and by carrying out a Monte Carlo Cross Validation: the obtained performances were found to be satisfying for all the models, with prediction abilities higher than 95% demonstrating the suitability of the developed methods. Finally, the metabolites that mostly contributed to the lentil discrimination were indicated.