Classification of yerba mate (Ilex paraguariensis) according to the country of origin based on element concentrations

Authentication of yerba mate according to the country of origin by using Fourier transform infrared (FTIR) associated with chemometrics

“…The loading of the first two LVs, with 54.98% of the total variance, is highly correlated with this region of the spectrum. These results corroborate those reported by Marcelo, Martins, Pozebon, Dressler, et al (2014). By using PCA and NIR, these authors also observed that the yerba mate classification was more accurate when the signals of CH 3 , CH 2 and CH were considered.…”

“…As reported by Marcelo, Martins, Pozebon, Dressler, et al (2014), variable selection was necessary in order to improve the classification of yerba mate by PLS-DA and SVM-DA of the NIR reflectance spectra. In the present study, variable selection was not necessary because all samples in the training and test groups were classified correctly by the SVM-DA of the entire reflectance spectrum.…”

“…Cozzolino et al (2010) identified yerba mate from Argentina and Uruguay by means of near-infrared spectroscopy (NIR) and multivariate analysis of the NIR spectra, whereas linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA) were used. Using a similar approach, Marcelo, Martins, Pozebon, Dressler, et al (2014) identified yerba mate from Argentina, Brazil, Uruguay and Paraguay. In this case, unsupervised methods such hierarchical cluster analysis (HCA) and principal component analysis (PCA), and supervised methods such as k-nearest neighbour (kNN), soft independent modelling class analogy (SIMCA), PLS-DA and support vector machine discriminant analysis *Corresponding author.…”

“…These authors used the SNV method to normalise the data. Marcelo, Martins, Pozebon, Dressler, et al (2014) normalised the data to a maximum value of 1 for each sample to remove the baseline offset. The data were then derived at first order using the Savitzky-Golay algorithm (second-order polynomial and 15 points per window).…”

Elemental and Isotopic Mass Spectrometry

“…The selection of the internal standards is performed, classically, by the following criteria: (1) they are not present in the sample; (2) the sample matrix or analyte elements do not spectrally interfere with them; (3) they do not spectrally interfere with the analyte masses; (4) they should not be elements that are considered environmental contaminants; (5) they are usually grouped with analyte elements of a similar mass range; for example, a low-mass internal standard is grouped with the low-mass analyte elements and so on up the mass range; (6) they should be of a similar ionization potential to the groups of analyte elements so they behave in a similar manner in the plasma; (7) some of the most common elements/masses reported to be good candidates for internal standards include 9 Be, 45 Sc, 59 Co, 74 Ge, 89 Y, 103 Rh, 115 In, 169 Tm, 175 Lu, 187 Re, and 232 Th. With this method of correction, a small group of elements are spiked into the samples, calibration standards, and blank.…”