Discrimination of edible olive oils by means of synchronous fluorescence spectroscopy with multivariate data analysis

Abstract

RESUMEN Discriminación de aceites de oliva comestibles mediante espectroscopía de fluorescencia sincrónica y análisis multivarianteSe ha investigado el potencial de la espectroscopía de fluorescencia para la clasificación de los aceite de oliva. Para ello, se recogieron espectros de fluorescencia sincrónica en el rango de 240-700 nm con intervalos de longitud de onda de 10, 30, 60 y 80 nm. Las proyecciones algorítmicas sucesivas (SPA) se aplicaron para la determinación de las longitudes de onda representativas mientras que el método de análisis discriminante lineal (LDA) se empleó para clasificar los aceites de oliva. Se obtuvo un error de clasificación del método bajo (0,9-6,4%) para las medidas recogidas en todos los intervalos de onda. La mejor precisión de clasificación se obtuvo para intensidades de fluorescencia sincrónica adquiridos a 10 longitudes de onda seleccionadas con intervalos de longitud de onda de 10 nm. PALABRAS CLAVE: Aceite de oliva refinado -Aceite de oliva virgen extra -Aceite de orujo -Espectroscopía de fluorescencia sincrónica -Proyecciones algorítmicas sucesivas. SUMMARY Discrimination of edible olive oils by means of synchronous fluorescence spectroscopy with multivariate data analysisThe potential of fluorescence spectroscopy for the classification of olive oils was investigated. Synchronous fluorescence spectra were collected in the region of 240-700 nm with the wavelength intervals of 10, 30, 60 and 80 nm. Successive projection algorithm (SPA) was applied for the determination of representative wavelengths while the linear discriminant analysis (LDA) method was used to classify olive oils. The classification error of the method was low (0,9-6,4%) for measurements collected at all wavelength intervals. The best classification accuracy was obtained for synchronous fluorescence intensities acquired at 10 selected wavelengths with the wavelength interval equal to 10 nm. KEY-WORDS: Extra virgin olive oil -Pomace olive oil -Refined olive oil -Successive projections algorithmSynchronous fluorescence spectroscopy.

Authentication of <i>Eucommia ulmoides</i> Seed Oil Using Fourier Transform Infrared and Synchronous Fluorescence Spectroscopy Combined with Chemometrics

“…Three different wavelength regions, namely, 250-700 nm, 300-500 nm, and 600-700 nm, were used for authentication EUSO coupled with PCA and chemometric multivariate regression analysis based on fluorescence detection. The quantitative adulteration of oil was investigated based on fluorescence spectroscopy combined with multivariate data analysis 39,40 , in which the sample preparation in these studies was complicated and the detected limit 8.9 was higher than that in our study. In contrast with these studies, the oil sample preparation of the proposed SyFS method is very simple, i.e., no need of dilution of oil samples in n-hexane.…”

Study on pesticide residues classification of lettuce leaves based on polarization spectroscopy

“…SPA was a forward variable selection for mulitivariate calibration, which employs operations in a vector space to obtain variables with the smallest collinearly (Dankowska, Malecka, & Kowalewski, 2013). Besides, this method has been proposed for the building of multivariate calibration models and subsequently extended to solve classification problems (Assis, Oliveira, & Sena, 2018).…”

Application of synchronous fluorescence spectroscopy with multivariate data analysis for determination of butter adulteration

“…Hence, the SPA‐MLR models are considered to be comparable to or better than the full spectrum PLS or PCR models for UV‐Vis (Ugolino Araújo et al ., ) and NIR spectra analysis (Kawakami Harrop Galvão et al ., ). Recently, SPA was applied for variable selection to determine organic acid of plum vinegar (Vis/NIR) (Liu & He, ), classification of coffees (UV‐Vis) (Polari Souto et al ., ), edible oils (UV‐Vis) (Pontes et al ., ) and seed and olive oils (synchronous fluorescence spectroscopy) (Dankowska et al ., ,b).…”