Application of multidimensional and conventional fluorescence techniques for classification of beverages originating from various berry fruit

• Autor(a) principal: Sikorska, Ewa
• Data de Publicação: 2020
• Outros Autores: Wlodarska, Katarzyna, Khmelinskii, Igor
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.1/16645
• topic: Berry fruit beverages; Excitation-emission matrix; Synchronous fluorescence; PARAFAC; PLS-DA; classification

The objectives of this study were to characterize fluorescence of beverages from berry fruit, including chokeberry, blackcurrant, raspberry and strawberry, and to develop classification models based on different types of fluorescence spectra to identify beverages depending on the fruit species. Total fluorescence spectra (excitation-emission matrices, EEMs) and total synchronous fluorescence spectra (TSFS) were recorded for a series of commercial berry fruit beverages. An analysis of EEMs using parallel factor analysis (PARAFAC) revealed four components characterized by the excitation/emission maxima at 275/326, 319/410, 414/600, and 360/460 nm, respectively. Based on the spectral profiles, these components were assigned to various groups of phenolic compounds. Partial least squares discriminant analysis was used to develop the classification models. The analysis was performed on PARAFAC scores, unfolded EEMs (uEEMs), unfolded TSFS (uTSFS), and additionally on conventional emission spectra (EMS) measured at particular excitation wavelengths and single synchronous fluorescence spectra (SFS). The classification models with the same average classification error of 4.86% were obtained for the analysis of both the entire uEEMs and uTSFS. Among models based on the individual spectra, the lowest error of 4.42% was obtained for SFS measured at Delta lambda = 40 nm, and an error of 7.64% was obtained for EMS measured at the excitation wavelength of 360 nm. The classification model based on the PARAFAC scores had the highest error of 15.27%. The present results show good potential of fluorescence as rapid and reagent-free tool for authenticity evaluation of berry beverages.