Discriminación de aceites de oliva comestibles mediante espectroscopía de fluorescencia sincrónica y análisis multivariante
DOI:
https://doi.org/10.3989/gya.012613Palabras clave:
Aceite de oliva refinado, Aceite de oliva virgen extra, Aceite de orujo, Espectroscopía de fluorescencia sincrónica, Proyecciones algorítmicas sucesivasResumen
Se 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.
Descargas
Citas
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. http://dx.doi.org/10.1016/j.talanta.2009.11.024 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. http://dx.doi.org/10.1016/j.foodchem.2010.01.016
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. http://dx.doi.org/10.3989/gya.034311
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. http://dx.doi.org/10.1002/ejlt.200800295
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. http://dx.doi.org/10.1007/s11746-003-0677-1
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. http://dx.doi.org/10.1016/j.talanta.2010.02.006 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. http://dx.doi.org/10.3989/gya.069712
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. http://dx.doi.org/10.1016/j.chemolab.2005.10.003
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. http://dx.doi.org/10.1016/S0003-2670(01)01182-5
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. http://dx.doi.org/10.1016/j.foodchem.2009.01.073
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. http://dx.doi.org/10.1016/j.foodcont.2009.12.006
Mannina L, Segre A. 2002. High Resolution Nuclear Magnetic Resonance: From Chemical Structure to Food Authenticity. Grasas Aceites 53, 22-33. http://dx.doi.org/10.3989/gya.2002.v53.i1.287
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. http://dx.doi.org/10.3989/gya.047212
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. http://dx.doi.org/10.1016/j.foodchem.2009.05.078
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. http://dx.doi.org/10.1016/j.chemolab.2004.12.001
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. http://dx.doi.org/10.1007/s00216-006-0729-2 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. http://dx.doi.org/10.1007/s00216-006-0729-2 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. http://dx.doi.org/10.1016/j.aca.2005.03.061
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. http://dx.doi.org/10.1016/j.aca.2005.07.057
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. http://dx.doi.org/10.1007/s00217-004-0874-9
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. http://dx.doi.org/10.1016/j.foodchem.2004.02.028
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. http://dx.doi.org/10.1023/B:JOFL.0000014656.75245.62 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. http://dx.doi.org/10.1016/j.foodres.2009.10.008
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. http://dx.doi.org/10.1016/S0169-7439(01)00119-8
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. http://dx.doi.org/10.1021/jf0207124 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. http://dx.doi.org/10.1007/s00217-011-1520-y
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. http://dx.doi.org/10.1007/BF02540514
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2013 Consejo Superior de Investigaciones Científicas (CSIC)
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
© CSIC. Los originales publicados en las ediciones impresa y electrónica de esta Revista son propiedad del Consejo Superior de Investigaciones Científicas, siendo necesario citar la procedencia en cualquier reproducción parcial o total.
Salvo indicación contraria, todos los contenidos de la edición electrónica se distribuyen bajo una licencia de uso y distribución “Creative Commons Reconocimiento 4.0 Internacional ” (CC BY 4.0). Consulte la versión informativa y el texto legal de la licencia. Esta circunstancia ha de hacerse constar expresamente de esta forma cuando sea necesario.
No se autoriza el depósito en repositorios, páginas web personales o similares de cualquier otra versión distinta a la publicada por el editor.
