New approaches in the chemometric analysis of infrared spectra of extra-virgin olive oils

SORT

Volumn 38, Issue 2, 2014, Pages 231-250

  Sánchez Rodríguez, María Isabel ^a   Sánchez López, Elena M ^a   Marinas, Alberto ^a   Caridad, José Ma ^a   Urbano, Francisco José ^a   Marinas, José Ma ^a  

^a UNIVERSITY OF CÓRDOBA   (Spain)

Author keywords

Cross validation; Extra virgin olive oil; Infrared spectroscopy; Partial least squares regression

Indexed keywords

GAS CHROMATOGRAPHY; GAS OILS; INFRARED DEVICES; INFRARED SPECTROSCOPY; LEAST SQUARES APPROXIMATIONS; MATRIX ALGEBRA; MEAN SQUARE ERROR; POLYUNSATURATED FATTY ACIDS; RANDOM ERRORS; REGRESSION ANALYSIS; SYSTEMATIC ERRORS;

CHEMOMETRIC ANALYSIS; CHEMOMETRIC APPROACH; CROSS VALIDATION; EXTRA VIRGIN OLIVE OIL; MID-INFRARED SPECTRA; PARTIAL LEAST SQUARE (PLS); PARTIAL LEAST SQUARES REGRESSION; QUANTITATIVE INFORMATION;

OLIVE OIL;

EID: 84916933839     PISSN: 16962281     EISSN: 20138830     Source Type: Journal    
DOI: None     Document Type: Article

References (37)

1. Aguilera, A. M., Escabias, M., Preda, C. and Saporta, G. (2010). Using basis expansions for estimating functional PLS regression. Applications with chemometric data. Chemometrics and Intelligent Laboratory Systems, 104, 289-305.
2. Baeten, V., Aparicio, R., Marigheto, N. and Wilson, R. (2003). Manual del aceite de oliva. AMV ediciones, Mundi-Prensa.
3. Baeten, V., Fernández Pierna, J. A., Dardenne, P., Meurens, M., García-González, D. L. and Aparicio-Ruiz, R. (2005). Detection of the presence of hazelnut oil in olive oil by FT-Raman and FT-MIR spectroscopy. Journal of agricultural and food chemistry, 53(16), 6201-6206.
4. Berrueta, L. A., Alonso-Salces, R. M. and Héberger, K. (2007). Supervised pattern recognition in food analysis. Journal of Chromatography A, 1158, 196-214.
5. Bertran, E., Blanco, M., Coello, J., Iturriaga, H., Maspoch, S. and Montoliu, I. (2000). Near infrared spectrometry and pattern recognition as screening methods for the authentication of virgin olive oils of very close geographical origins. Journal of Near Infrared Spectroscopy, 8, 45.
6. Casale, M., Oliveri, P., Casolino, C., Sinelli, N., Zunin, P., Armanino, C., Forina, M. and Lanteri, S. (2012). Characterization of PDO olive oil Chianti Classico by non-selective (UV-visible, NIR and MIR spectroscopy) and selective (fatty acid composition) analytical techniques. Analytical Chimica Acta, 712, 56-63.
7. Commission regulation (EU) No 61/2011 of 24 January 2011 amending Regulation (EEC) No 2568/91 on the characteristics of olive oil and olive-residue oil and on the relevant methods of analysis.
8. D'Imperio, M., Mannina, L., Capitani, D., Bidet, O., Rossi, E., Bucarelli, F.M., Quaglia, G. B. and Segre, A. (2007). NMR and statistical study of olive oils from Lazio: a geographical, ecological and agronomic characterization. Food chemistry, 105(3), 1256-1267.
9. Dupuy, N., Galtier, O., Ollivier, D., Vanloot, P. and Artaud, J. (2010a). Comparison between NIR, MIR, concatenated NIR and MIR analysis and hierarchical PLS model. Application to virgin olive oil analysis. Analytica chimica acta, 666(1), 23-31.
10. Dupuy, N., Galtier, O., Le Dréau, Y., Pinatel, C., Kister, J. and Artaud, J. (2010b). Chemometric analysis of combined NIR and MIR spectra to characterize French olives. European Journal of Lipid Science and Technology, 112(4), 463-475.
11. Escabias, M., Aguilera, A. M. and Valderrama, M. J. (2007). Functional PLS logit regression model. Computational Statistics and Data Analysis, 51, 4891-4902.
12. Frank, I. E. and Friedman, J. H. (1993). A statistical view of some chemometrics regression tools. Technometrics, 35(2), 109-135.
13. Forina, M., Lanteri, S., Armanino, C., Casolino, C., Casale, M. and Oliveri, P. (2008). P-PARVUS. Dip. Chimica e Tecnologie Farmaceutiche e Alimentari, University of Genova, http://www.parvus.unige.it.
14. Galtier, O., Abbas, O., Le Dréau, Y., Rebufa, C., Kister, J., Artaud, J. and Dupuy, N. (2011). Comparison of PLS1-DA, PLS2-DA and SIMCA for classification by origin of crude petroleum oils by MIR and virgin olive oils by NIR for different spectral regions. Vibrational Spectroscopy, 55(1), 132-140.
15. Galtier, O., Dupuy, N., Le Dréau, Y., Ollivier, D., Pinatel, C., Kister, J. and Artaud, J. (2007). Geographic origins and compositions of virgin olive oils determinated by chemometric analysis of NIR spectra. Analytica chimica acta, 595(1), 136-144.
16. Gowen, A. A., Downewy, G., Esquerre, C. and O'Donnell, C. P. (2010). Preventing over-fitting in PLS calibration models of near-infrared (NIR) spectroscopy data using regression coefficients. Journal of Chemometrics, 25, 375-381.
17. Guillén, M. D. and Cabo, N. (1997). Characterization of edible oils and lard by Fourier transform infrared spectroscopy. Relationships between composition and frequency of concrete bands in the fingerprint region. Journal of the American Oil Chemists' Society, 74(10), 1281-1286.
18. Guillén, M. D. and Cabo, N. (1998). Relationships between the composition of edible oils and lard and the ratio of the absorbance of specific bands of their Fourier transform infrared spectra. Role of some bands of the fingerprint region. Journal of Agricultural and Food Chemistry, 46, 1788-1793.
19. Guillén, M. D. and Cabo, N. (1999). Usefulness of the frequencies of some Fourier transform infrared spectroscopic bands for evaluating the composition of edible oil mixtures. European Journal of Lipid Sciences and Technology, 1, 71-76.
20. 1H nuclear magnetic resonance. Journal of the Science of Food and Agriculture, 83(4), 338-346.
21. Relationships between composition and frequency of concrete bands in the fingerprint region. Journal of the American Oil Chemists' Society, 4(10), 1281-1286.
22. Gurdeniz, G. and Ozen, B. (2009). Detection of adulteration of extra-virgin olive oil by chemometric analysis of mid-infrared spectral data. Food chemistry, 116(2), 519-525.
23. International Olive Oil Council, 200 (COI / T.20 / Doc. no. 24 / 2001a). Preparation of the fatty acid methyl esters from olive oil and olive-pomace oil.
24. International Olive Oil Council, 200 (COI / T.20 / Doc. no. 17 / 2001b). Determination of trans unsaturated fatty acids by capillary column gas chromatography.
25. Maggio, R. M., Valli, E., Bendini, A., G ómez-Caravaca, A. M., Toschi, T. G. and Cerretani, L. (2011). A spectroscopic and chemometric study of virgin olive oils subjected to thermal stress. Food Chemistry, 127, 216-221.
26. Marron, J. S. and Alonso, A. M. (2014). Overview of object oriented data analysis. Biometrical Journal, 56, doi: 10.1002/bimj.201300072.
27. Ö ztürk, B., Yalçin, A. and Ö zdemir, D. (2010). Determination of olive oil adulteration with vegetable oils by near infrared spectroscopy coupled with multivariate calibration. Journal of Near Infrared Spectroscopy, 18, 191-201.
28. Preda, C. and Saporta, G. (2005). PLS regression on a stochastic process. Computational Statistics and Data Analysis, 48, 149-158.
29. Preda, C., Saporta, G. and Lévéder, C. (2007). PLS classification of functional data. Computational Statistics, 22, 223-235.
30. 1H NMR fingerprinting with principal component analysis, linear discriminant analysis and probabilistic neural networks. Analytica Chimica Acta, 552(1), 13-.24.
31. Rohman, A. and Che Man, Y. B. (2010). Fourier transform infrared (FTIR) spectroscopy for analysis of extra virgin olive oil adulteration with palm oil. Food research international, 43, 886-892.
32. Sánchez-Rodríguez, M. I., Sánchez-López, E., Caridad, J.M.,Marinas, A.,Marinas, J.M. and Urbano, F. J. (2013). New insights into evaluation of regression models through a descompositon of the prediction errors: application to near-infrared spectral data. Statistics and Operations Research Transactions (SORT), 37(1), 57-78.
33. Sánchez-Rodríguez, M. I. and Caridad, J. M. (2014). Modelling and partial least squares approaches in OODA. Biometrical Journal, 37(1), 771-773.
34. Sinelli, N., Casiraghi, E., Tura, D. and Downey, G. (2008). Characterisation and classification of Italian virgin olive oils by near-and mid-infrared spectroscopy. Journal of Near Infrared Spectroscopy, 16, 335-342.
35. Sinelly, N., Cerretani, L., Di Egidio, V., Bendini, A. and Casiraghi, E. (2010). Application fo near (NIR) infrared and mid (MIR) infrared spectroscopy as a rapid tool to classify extra virgir olive oil on the basis of fruity attribute intensity. Food research international, 43, 369-375.
36. Vlachos, N., Skopelitis, Y., Psaroudaki, M., Konstantinidou, V., Chatzilazarou, A. and Tegou, E. (2006). Applications of Fourier transform-infrared spectroscopy to edible oils. Analytica Chimica Acta, 573-574, 459-465.
37. Zhang, Q., Liu, C., Sun, Z., Hu, X., Shen, Q. and Wu, J. (2012). Authentication of edible vegetable oils adulteration with used frying oil by Fourier transform infrared spectroscopy. Food Chemistry, 132, 1607-1613.