Intra-regional classification of grape seeds produced in Mendoza province (Argentina) by multi-elemental analysis and chemometrics tools.
The feasibility of the application of chemometric techniques associated with multi-element analysis for the classification of grape seeds according to their provenance vineyard soil was investigated. Grape seed samples from different localities of Mendoza province (Argentina) were evaluated. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of twenty-nine elements (Ag, As, Ce, Co, Cs, Cu, Eu, Fe, Ga, Gd, La, Lu, Mn, Mo, Nb, Nd, Ni, Pr, Rb, Sm, Te, Ti, Tl, Tm, U, V, Y, Zn and Zr). Once the analytical data were collected, supervised pattern recognition techniques such as linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), k-nearest neighbors (k-NN), support vector machine (SVM) and Random Forest (RF) were applied to construct classification/discrimination rules. The results indicated that nonlinear methods, RF and SVM, perform best with up to 98% and 93% accuracy rate, respectively, and therefore are excellent tools for classification of grapes.
['Canizo|Brenda V|BV|', 'Escudero|Leticia B|LB|', 'Pérez|María B|MB|', 'Pellerano|Roberto G|RG|', 'Wuilloud|Rodolfo G|RG|']
D001118:Argentina D016002:Discriminant Analysis D016018:Least-Squares Analysis D013058:Mass Spectrometry D008670:Metals D012639:Seeds D012987:Soil D027843:Vitis
Grape seeds Multi-elemental analysis Chemometrics ICP-MS Multivariate classification