Detection and quantification of extra virgin olive oil adulteration by means of autofluorescence excitation-emission profiles combined with multi-way classification

Talanta

Volumn 178, Issue , 2018, Pages 751-762

  Durán Merás, Isabel ^a   Domínguez Manzano, Jaime ^a   Airado Rodríguez, Diego ^a   Muñoz de la Peña, Arsenio ^a  

^a UNIVERSITY OF EXTREMADURA   (Spain)

Author keywords

Adulteration; Chemometric discrimination; Front face fluorescence; Olive oils

Indexed keywords

DISCRIMINANT ANALYSIS; FLUORESCENCE; FLUORESCENCE SPECTROSCOPY; LEAST SQUARES APPROXIMATIONS;

ADULTERATION; CALIBRATION AND VALIDATIONS; CHEMOMETRIC DISCRIMINATIONS; DETECTION AND QUANTIFICATIONS; EXCITATION EMISSION MATRICES; FRONT FACE; LINEAR DISCRIMINANT ANALYSIS; OLIVE OILS;

OLIVE OIL;

OLIVE OIL;

CHEMISTRY; FOOD ANALYSIS; FOOD QUALITY; FRAUD; LEAST SQUARE ANALYSIS; PROCEDURES; SPECIES DIFFERENCE; SPECTROFLUOROMETRY;

FOOD ANALYSIS; FOOD QUALITY; FRAUD; LEAST-SQUARES ANALYSIS; OLIVE OIL; SPECIES SPECIFICITY; SPECTROMETRY, FLUORESCENCE;

EID: 85031760716     PISSN: 00399140     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.talanta.2017.09.095     Document Type: Article

References (47)

1. Jabeur, H., Zribi, A., Makni, J., Rebai, A., Abdelhedi, R., Bouaziz, M., Detection of chemlali extra-virgin olive oil adulteration mixed with soybean oil, corn oil, and sunflower oil by using GC and HPLC. J. Agric. Food Chem. 62 (2014), 4893–4904.
2. Bagur-González, M.G., Pérez-Castaño, E., Sánchez-Viñas, M., Gázquez-Evangelista, D., Using the liquid-chromatographic-fingerprint of sterols fraction to discriminate virgin olive from other edible oils. J. Chromatogr. A 1380 (2015), 64–70.
3. Yang, Y., Ferro, M.D., Cavaco, I., Liang, Y., Detection and identification of extra virgin olive oil adulteration by GC-MS combined with chemometrics. J. Agric. Food Chem. 61 (2013), 3693–3702.
4. Rohman, A., Man, Y.B.C., Fourier transform infrared (FTIR) spectroscopy for analysis of extra virgin olive oil adulterated with palm oil. Food Res. Int. 43 (2010), 886–892.
5. Vasconcelos, M., Coelho, L., Barros, A., de.Almeida, J.M.M.M., Study of adulteration of extra virgin olive oil with peanut oil using FTIR spectroscopy and chemometrics. Cogent Food Agric., 1, 2015, 1018695.
6. López-Díez, E.C., Bianchi, G., Goodacre, R., Rapid quantitative assessment of the adulteration of virgin olive oils with hazelnut oils using raman spectroscopy and chemometrics. J. Agric. Food Chem. 51 (2003), 6145–6150.
7. Baeten, V., Fernández Pierna, J.A., Dardenne, P., Meurens, M., García-González, D.L., Aparicio-Ruiz, R., Detection of the presence of hazelnut oil in olive oil by FT-Raman and FT-MIR spectroscopy. J. Agric. Food Chem. 53 (2005), 6201–6206.
8. Sánchez-Hernández, L., Marina, M.L., Crego, A.L., A capillary electrophoresis–tandem mass spectrometry methodology for the determination of non-protein amino acids in vegetable oils as novel markers for the detection of adulterations in olive oils. J. Chromatogr. A 1218 (2011), 4944–4951.
9. Sánchez-Hernández, L., Castro-Puyana, M., Marina, M.L., Crego, A.L., Determination of betaines in vegetable oils by capillary electrophoresis tandem mass spectrometry –application to the detection of olive oil adulteration with seed oils. Electrophoresis 32 (2011), 1394–1401.
10. Jabeur, H., Zribi, A., Bouaziz, M., Extra-virgin olive oil and cheap vegetable oils: distinction and detection of adulteration as determined by GC and chemometrics. Food Anal. Methods 9 (2016), 712–723.
11. Torrecilla, J.S., Rojo, E., Dominguez, J.C., Rodríguez, F., Novel Method, A., To quantify the adulteration of extra virgin olive oil with low-grade olive oils by UV−vis. J. Agric. Food Chem. 58 (2010), 1679–1684.
12. Aroca-Santos, R., Cancilla, J.C., Matute, G., Torrecilla, J.S., Identifying and quantifying adulterants in extra virgin olive oil of the picual varietal by absorption spectroscopy and nonlinear modeling. J. Agric. Food Chem. 63 (2015), 5646–5652.
13. De Luca, M., Restuccia, D., Clodoveo, M.L., Puoci, F., Ragno, G., Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes. Food Chem. 202 (2016), 432–437.
14. Poulli, K.I., Mousdis, G.A., Georgiou, C.A., Synchronous fluorescence spectroscopy for quantitative determination of virgin olive oil adulteration with sunflower oil. Anal. Bioanal. Chem. 386 (2006), 1571–1575.
15. Dankowska, A., Małecka, M., Kowalewski, W., Discrimination of edible olive oils by means of synchronous fluorescence spectroscopy with multivariate data analysis. Grasas Aceites 64 (2013), 425–431.
16. Mu, T., Chen, S., Zhang, Y., Chen, H., Guo, P., Meng, F., Portable detection and quantification of olive oil adulteration by 473-nm laser-induced fluorescence. Food Anal. Methods 9 (2016), 275–279.
17. Aparicio, R., Morales, M.T., Aparicio-Ruiz, R., Tena, N., García-González, D.L., Authenticity of olive oil: mapping and comparing official methods and promising alternatives. Food Res. Int. 54 (2013), 2025–2038.
18. Christensen, J., Norgaard, L., Bro, R., Engelsen, S.B., Multivariate autofluorescence of intact food systems. Chem. Rev. 106 (2006), 1979–1994.
19. Airado-Rodríguez, D., Durán-Merás, I., Galeano-Díaz, T., Wold, J.P., Front-face fluorescence spectroscopy: a new tool for control in the wine industry. J. Food Compos. Anal. 24 (2011), 257–264.
20. Guimet, F., Ferré J., Boqué R., Study of oils from the protected denomination of origin “Siurana” using excitation-emission fluorescence spectroscopy and three-way methods of analysis. Grasas Aceites 56 (2005), 292–297.
21. Guimet, F., Ferré J., Boqué R., Rapid detection of olive–pomace oil adulteration in extra virgin olive oils from the protected denomination of origin «Siurana» using excitation–emission fluorescence spectroscopy and three-way methods of analysis. Anal. Chim. Acta 544 (2005), 143–152.
22. Guimet, F., Boqué R., Ferré J., Cluster analysis applied to the exploratory analysis of commercial spanish olive oils by means of excitation-emission fluorescence spectroscopy. J. Agric. Food Chem. 52 (2004), 6673–6679.
23. R. Bro, Multiway analysis in the food industry. Models, Algorithms and Applications. 〈https://www.researchgate.net/publication/2407346_Multiway_analysis_in_the_food_industry_Models_algorithms_and_applications〉.
24. Olivieri, A.C., Wu, H.L., Yu, R.Q., MVC2: a MATLAB graphical interface toolbox for second-order multivariate calibration. Chemom. Intell. Lab. Syst. 96 (2009), 246–251.
25. Olivieri, A., Escandar, G.M., Practical Three-Way Calibration. 2014, Elsevier, Waltham.
26. Kemsley, E.K., A genetic algorithm (GA) approach to the calculation of canonical variates (CVs). TrAC Trends Anal. Chem. 17 (1998), 24–34.
27. Berrueta, L.A., Alonso-Salces, R.M., Héberger, K., Supervised pattern recognition in food analysis. J. Chromatogr. A 1158 (2007), 196–214.
28. Arruda, A.F., Goicoechea, H.C., Santos, M., Campiglia, A.D., Olivieri, A.C., Solid−liquid extraction room temperature phosphorimetry and pattern recognition for screening polycyclic aromatic hydrocarbons and polychlorinated biphenyls in water samples. Environ. Sci. Technol. 37 (2003), 1385–1391.
29. Indahl, U.G., The geometry of PLS1 explained properly: 10 key notes on mathematical properties of and some alternative algorithmic approaches to PLS1 modelling. J. Chemom. 28 (2014), 168–180.
30. Barker, M., Rayens, W., Partial least squares for discrimination. J. Chemom. 17 (2003), 166–173.
31. Ouertani, S.S., Mazerolles, G., Boccard, J., Rudaz, S., Hanafi, M., Multi-way PLS for discrimination: compact form equivalent to the tri-linear PLS2 procedure and its monotony convergence. Chemom. Intell. Lab. Syst. 133 (2014), 25–32.
32. Brereton, R.G., Lloyd, G.R., Partial least squares discriminant analysis: taking the magic away. J. Chemom. 28 (2014), 213–225.
33. de Almeida, M.R., Correa, D.N., Rocha, W.F.C., Scafi, F.J.O., Poppi, R.J., Discrimination between authentic and counterfeit banknotes using Raman spectroscopy and PLS-DA with uncertainty estimation. Microchem. J. 109 (2013), 170–177.
34. Ballabio, D., Consonni, V., Classification tools in chemistry. Part 1: linear models. PLS-DA. Anal. Methods 5 (2013), 3790–3798.
35. Papadopoulos, K., Triantis, T., Tzikis, C.H., Nikokavoura, A., Dimotikali, D., Investigations of the adulteration of extra virgin olive oils with seed oils using their weak chemiluminescence. Anal. Chim. Acta 464 (2002), 135–140.
36. Zandomeneghi, M., Carbonaro, L., Caffarata, C., Fluorescence of vegetable oils: olive oils. J. Agric. Food Chem. 53 (2005), 759–766.
37. Cheikhousman, R., Zude, M., Bouveresse, D.J.R., Léger, C.L., Rutledge, D.N., Birlouez-Aragon, I., Fluorescence spectroscopy for monitoring deterioration of extra virgin olive oil during heating. Anal. Bioanal. Chem. 382 (2005), 1438–1443.
38. Galeano Díaz, T., Durán Merás, I., Correa, C.A., Roldán, B., Cáceres, M.I. Rodríguez, Simultaneous fluorometric determination of chlorophylls a and B and pheophytins a and b in olive oil by partial least-squares calibration. J. Agric. Food Chem. 51 (2003), 6934–6940.
39. Kyriakidis, N.B., Skarkalis, P., Fluorescence spectra measurement in olive oil and other vegetable oils. J. AOAC Int. 83 (2000), 1435–1439.
40. Sikorska, E., Khmelinskii, I., Sikorski, M., Analysis of olive oils by fluorescence spectroscopy: methods and applications. Dimitrios, B., (eds.) Olive Oil-Constituents, Quality, Health Properties and Bioconversion, 2012, In TechOpen (Chapter 4).
41. Bro, R., PARAFAC tutorial and applications. Chemom. Intell. Lab. Syst. 38 (1997), 149–171.
42. Bro, R., Kiers, H.A.L., A new efficient method for determining the number of components in PARAFAC models. J. Chemom. 17 (2003), 274–286.
43. Escandar, G.M., Goicoechea, H.C., Muñoz de la Peña, A., Olivieri, A.C., Second- and higher-order data generation and calibration: a tutorial. Anal. Chim. Acta 806 (2014), 8–26.
44. Muñoz de la Peña, A., Espinosa Mansilla, A., González Gómez, D., Olivieri, A.C., Goicoechea, H.C., Interference-free analysis using three-way fluorescence data and the parallel factor model. Determination of fluoroquinolone antibiotics in human serum. Anal. Chem. 75 (2003), 2640–2646.
45. Guimet, F., Ferre, J., Boque, R., Rius, F.X., Application of unfold principal component analysis and parallel factor analysis to the exploratory analysis of olive oils by means of excitation-emission matrix fluorescence spectroscopy. Anal. Chim. Acta 515 (2004), 75–85.
46. Muñoz de la Peña, A., Mujumdar, N., Heider, E.C., Goicoechea, H.C., Muñoz de la Peña, D., Campiglia, A.D., Nondestructive total excitation–emission fluorescence microscopy combined with multi-way chemometric analysis for visually indistinguishable single fiber discrimination. Anal. Chem. 88 (2016), 2967–2975.
47. Haaland, D.M., Thomas, E.V., Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information. Anal. Chem. 60 (1988), 1193–1202.