Grasas y Aceites, Vol 64, No 4 (2013)

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

A. Dankowska
Faculty of Commodity Science, Poznan University of Economics, Poland

M. Małecka
Faculty of Commodity Science, Poznan University of Economics, Poland

W. Kowalewski
Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poland


The 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.


Extra virgin olive oil; Pomace olive oil; Refined olive oil; Successive projections algorithm; Synchronous fluorescence spectroscopy

Full Text:



Agiomyrgianaki A, Petrakis PV, Dais PP. 2010. Detection of refined olive oil adulteration with refined hazelnut oil by employing NMR spectroscopy and multivariate statistical analysis. Talanta 80, 2165-2171. PMid:20152467

Al-Ismail KM, Alsaed AK, Ahmad R, Al-Dabbas M. 2010. Detection of olive oil adulteration with some plant oils by GLC analysis of sterols using polar column. Food Chem. 121, 1255-1259.

Arslan D, Özcan MM 2011. Phenolic profile and antioxidant activity of olive fruits of the Turkish variety "Sariulak" from different locations. Grasas Aceites 62, 453-461.

Cichelli A, Pertesana GP. 2004. High-performance liquid chromatographic analysis of chlorophylls, pheophytins and carotenoids in virgin olive oils: chemometric approach to variety classification. J. Chromatogr. A 1046, 141-146. PMid:15387182

Dankowska A, Małecka M. 2009. Application of synchronous fluorescence spectroscopy for determination of extra virgin olive oil adulteration. Eur. J. Lipid Sci. Technol. 111, 1233-1239.

Dourtoglou VG, Dourtoglou T, Antonopoulos A, Stefanou E, Lalas S, Poulos C. 2003. Detection of olive oil adulteration using principal component analysis applied on total and regio FA content. J. Am. Oil Chem. Soc. 80, 203-208.

Fasciotti M, Pereira Netto AD. 2010. Optimization and application of methods of triacylglycerol evaluation for characterization of olive oil adulteration by soybean oil with HPLC–APCI–MS–MS. Talanta 81, 1116-1125. PMid:20298902

Fernandes-Silva AA, Falco V, Correia CM, Villalobos FJ. 2013. Sensory analysis and volatile compounds of olive oil (cv. Cobrançosa) from different irrigation regimes. Grasas Aceites 64, 59-67.

Guimet F, Boqué R, Ferré J. 2006. Application of nonnegative matrix factorization combined with Fisher's linear discriminant analysis for classification of olive oil excitation–emission fluorescence spectra. Chemom. Intell. Lab. Sys. 81, 94-106.

IOC. 2011. Trade standard applying to olive oils and olive-pomace oils. International Olive Council.

Kawakami Harrop Galvão R, Pimentel MF, Ugolino Araújo MC, Yoneyamaa T, Visani V. 2001. Aspects of the successive projections algorithm for variable selection in multivariate calibration applied to plasma emission spectrometry. Anal. Chim. Acta 443, 107-115.

Liu F, He Y. 2009. Application of successive projections algorithm for variable selection to determine organic acids of plum vinegar. Food Chem. 115, 1430-1436.

Maggio RM, Cerretani L, Chiavaro E, Kaufman T S, Bendin A. 2010. A novel chemometric strategy for the estimation of extra virgin olive oil adulteration with edible oils. Food Control 21, 890-895.

Mannina L, Segre A. 2002. High Resolution Nuclear Magnetic Resonance: From Chemical Structure to Food Authenticity. Grasas Aceites 53, 22-33.

Massart DL, Vandeginste BGM, Buydens LMC, De Jong S, Lewi PL, Smeyers-Verbeke J. 1998. Handbook of chemometrics and qualimetrics: part B. Elsevier.

Ourrach I, Rada M, Pérez-Camino MC, Benaissa M, Guinda Á. 2012. Detection of argan oil adulterated with vegetable oils: new markers. Grasas Aceites 63, 355-364.

Patra D, Mishra AK. 2002. Recent developments in multicomponent synchronous fluorescence scan analysis. Trac-Trend Anal. Chem. 21, 787-798.

Polari Souto UTC, Coelho Pontes MJ, Cirino Silva E, Harrop Galvão RK, Ugulino Araújo MC, Castriani Sanches FA, Silva Cunha FA, Ribeiro Oliveira MS. 2010. UV–Vis spectrometric classification of coffees by SPA–LDA. Food Chem. 119, 368-371.

Pontes MJC, Kawakami Harrop Galvão R, Ugulino Araújo MC, Teles Moreira PN, Pessoa Neto OD, Emídio José G, Bezerra Saldanha TC. 2005. The successive projections algorithm for spectral variable selection in classification problems. Chemom. Intell. Lab. Sys. 78, 11-18.

Poulli KI, Mousdis GA, Georgiou CA. 2006. Synchronous fluorescence spectroscopy for quantitative determination of virgin olive oil adulteration with sunflower oil. Anal. Bioanal. Chem. 386, 1571-1575. PMid:16953317

Poulli KI, Mousdis GA, Georgiou CA. 2006. Synchronous fluorescence spectroscopy for quantitative determination of virgin olive oil adulteration with sunflower oil. Anal. Bioanal. Chem. 86, 1571-1575. PMid:16953317

Poulli KI. Mousdis GA, Georgiou C.A. 2005. Classification of edible and lampante virgin olive oil based on synchronous fluorescence and total luminescence spectroscopy. Anal. Chim. Acta 542, 151-156.

Rezzia S, Axelsonb DE, Hébergera K, Renieroa F, Marianid C, Guilloua C. 2005. Classification of olive oils using high throughput flow 1H NMR fingerprinting with principal component analysis, linear discriminant analysis and probabilistic neural networks. Anal. Chim. Acta 552, 13-24.

Sayago A, Morales MT, Aparicio R. 2004. Detection of hazelnut oil in virgin olive oil by a spectrofluorimetric method. Eur. Food Res. Technol. 218, 480-483.

Sikorska E, Górecki T, Khmelinskii IV, Sikorski M, Kozioł J. 2005. Classification of edible oils using synchronous scanning fluorescence spectroscopy. Food Chem. 89, 217-225.

Sikorska E, Romaniuk A, Khmelinskii,IV, Herance R, Bourdelande JL, Sikorski M, Kozioł J. 2004. Characterization of edible oils using total luminescence spectroscopy. J Fluoresc. 14, 25-35. PMid:15622857

Sinelli N, Cerretani L, di Egidio V, Bendini A, Casiraghi E. 2010. Application of near (NIR) infrared and mid (MIR) infrared spectroscopy as a rapid tool to classify extra virgin olive oil on the basis of fruity attribute intensity. Food Res. Inter. 43, 369-375.

Ugolino Araújo MC, Bezerra Saldanha TC, Kawakami Harrop Galvão R, Yoneyama T, Chame HC, Visani V. 2001. The successive projections algorithm for variable selection inspectroscopic multicomponent analysis. Chemom. Intell. Lab. Sys. 57, 65-73.

Vaz Freire L, Gouveia JM, Costa Freitas AM. 2008. Analytical characteristics of olive oils produced by two different extraction techniques, in the Portuguese olive variety Galega Vulgar. Grasas Aceites 59, 260-266.

Vlahov G, Del Re P, Simone N. 2003. Determination of geographical origin of olive oils using 13C nuclear magnetic resonance spectroscopy. I − Classification of olive oils of the puglia region with denomination of protected origin. J. Agric. Food Chem. 51, 5612-5615. PMid:12952409

Wu Y, Zhang H, Han J, Wang B, Wang W, Ju X, Chen Y. 2011. PCR-CE-SSCP applied to detect cheap oil blended in olive oil. Eur. Food Res. and Technol. 233, 313-324.

Zamora R, Navarro JL, Hidalgo FJ. 1994. Identification and classification of olive oils by high-resolution13C nuclear magnetic resonance. J. Am. Oil Chem. Soc. 71, 361-364.

Copyright (c) 2013 Consejo Superior de Investigaciones Científicas (CSIC)

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Contact us

Technical support