Fluorescence spectroscopy application for Argentinean yerba mate (Ilex paraguariensis) classification assessing first- and second-order data structure properties

SANTOS, M.C.D.; AZCARATE, S.M.; LIMA, K.M.G.; GOICOECHEA, H.C.

MICROCHEMICAL JOURNAL

ELSEVIER SCIENCE BV

Año: 2020 vol. 155

0026-265X

This paper uses fluorescence spectroscopy in order to evaluate the potential of this technique to classifyArgentinean yerba mate from three commercial categories. An extraction method based on ultrasound forsample preparation is proposed. Acquired fluorescence first- and second-order data were analyzed by differentchemometric approaches. Aimed at enhancing data interpretability and to reduce redundant information amongthe retained variables and maximize their relationship regarding the sample, several variable selection algorithms were evaluated. Two three-way algorithms, PARAFAC and n-PLS, were applied to EEMs. Several two-wayalgorithms such as PCA, SPA, GA, PLS were used previous to model data gathered from emission spectra recorded at the 410 nm excitation and unfolded EEMs. Sample categorization was performed using LDA or QDA asclassification techniques. The ability of the models to predict samples was evaluated based on sensitivity andspecificity. First-order models reached 89.6% on sensitivity and 90.9% on specificity. Second-order modelsachieved up to 100% sensitivity and specificity demonstrating that the EEM matrix provides relevant additionalinformation revealing a significant effect on the classification results.