Multivariate screening in food adulteration: Untargeted versus targeted modelling

Food Chemistry

Volumn 147, Issue , 2014, Pages 177-181

  López, M Isabel ^a   Trullols, Esther ^b   Callao, M Pilar ^a   Ruisánchez, Itziar ^a  

^a UNIVERSITAT ROVIRA I VIRGILI   (Spain)

^b R+D+i Department   (Spain)

Author keywords

Adulteration; Food fraud; Hazelnut; Multivariate screening; SIMCA classification; Untargeted modelling

Indexed keywords

ADULTERATION; CHICKPEA FLOUR; CLASSIFICATION TECHNIQUE; FOOD ADULTERATIONS; HAZELNUT; HAZELNUT PASTE; NEAR INFRA RED; SCREENING STRATEGY;

CRIME;

INFRARED DEVICES;

ALMOND; ARTICLE; CHICKPEA; CLASSIFICATION; CORYLUS AVELLANA; FOOD ADULTERATION; FOOD PROCESSING; FOOD SAFETY; FRAUD; SCREENING;

CICER ARIETINUM; CORYLUS; PRUNUS DULCIS;

ADULTERATION; FOOD FRAUD; HAZELNUT; MULTIVARIATE SCREENING; SIMCA CLASSIFICATION; UNTARGETED MODELLING;

CICER; CORYLUS; FLOUR; FOOD CONTAMINATION; PRUNUS; SPECTROSCOPY, NEAR-INFRARED;

EID: 84885491927     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2013.09.139     Document Type: Article

References (28)

1. D. Behmer FT-NIR spectroscopy for the edible oil industry Food Science and Technology 24 4 2010 47 48
2. J.S. Bonvehi, and F.V. Coll Detecting vegetable oil adulteration in hazelnut paste (Corylus avellana L.) International Journal of Food Science and Technology 44 3 2009 456 466
3. C.D. Calvano, C. De Ceglie, A. Monopoli, and C.G. Zambonin Detection of sheep and goat milk adulterations by direct MALDI-TOF MS analysis of milk tryptic digests Journal of Mass Spectrometry 47 9 2012 1141 1149
4. R. Consonni, L.R. Cagliani, and C. Cogliati NMR based geographical characterisation of roasted coffee Talanta 88 2012 420 426
5. M. Daszykowski, B. Walczak, and D.L. Massart Representative subset selection Analytica Chimica Acta 468 1 2002 91 103 (Pubitemid 35223122)
6. C.V. Di Anibal, L.F. Marsal, M.P. Callao, and I. Ruisánchez Surface enhanced raman spectroscopy (SERS) and multivariate analysis as a screening tool for detecting Sudan I dye in culinary spices Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 87 2012 135 141
7. C.V. Di Anibal, M. Odena, I. Ruisánchez, and M.P. Callao Determining the adulteration of spices with Sudan I-IV dyes by UV-visible spectroscopy and multivariate classification techniques Talanta 79 3 2009 887 892
8. C.V. Di Anibal, I. Ruisánchez, and M.P. Callao High-resolution 1H nuclear magnetic resonance spectrometry combined with chemometric treatment to identify adulteration of culinary spices with Sudan dyes Food Chemistry 124 3 2011 1139 1145
9. V. Di Stefano, G. Avellone, D. Bongiorno, V. Cunsolo, V. Muccilli, and S. Sforza Applications of liquid chromatography-mass spectrometry for food analysis Journal of Chromatography A 1259 2012 74 85
10. C. Durante, R. Bro, and M. Cocchi A classification tool for N-way array based on SIMCA methodology Chemometrics and Intelligent Laboratory Systems 106 1 2011 73 85
11. P.K. Ghosh, and D.S. Jayas Use of spectroscopic data for automation in food processing industry Sensing and Instrumentation for Food Quality and Safety 3 1 2009 3 11
12. F. Guy, S. Prache, A. Thomas, D. Bauchart, and D. Andueza Prediction of lamb meat fatty acid composition using near-infrared reflectance spectroscopy (NIRS) Food Chemistry 127 3 2011 1280 1286
13. S.A. Haughey, S.F. Graham, E. Cancouët, and C.T. Elliott The application of near-infrared reflectance spectroscopy (NIRS) to detect melamine adulteration of soya bean meal Food Chemistry 136 3-4 2013 1557 1561
14. R. Karoui, and J. De Baerdemaeker A review of the analytical methods coupled with chemometric tools for the determination of the quality and identity of dairy products Food Chemistry 102 3 2007 621 640 (Pubitemid 46111042)
15. R. Krska, A. Becalski, E. Braekevelt, T. Koerner, X. Cao, and R. Dabeka Challenges and trends in the determination of selected chemical contaminants and allergens in food Analytical and Bioanalytical Chemistry 402 1 2012 139 162
16. M.R. Kunz, J. Ottaway, J.H. Kalivas, C.A. Georgiou, and G.A. Mousdis Updating a synchronous fluorescence spectroscopic virgin olive oil adulteration calibration to a new geographical region Journal of Agricultural and Food Chemistry 59 4 2011 1051 1057
17. E.C. López-Díez, G. Bianchi, and R. Goodacre Rapid quantitative assessment of the adulteration of virgin olive oils with hazelnut oils using raman spectroscopy and chemometrics Journal of Agricultural and Food Chemistry 51 21 2003 6145 6150
18. L. Mannina, M. D'Imperio, D. Capitani, S. Rezzi, C. Guillou, and T. Mavromoustakos 1H NMR-based protocol for the detection of adulterations of refined olive oil with refined hazelnut oil Journal of Agricultural and Food Chemistry 57 24 2009 11550 11556
19. J.C. Moore, J. Spink, and M. Lipp Development and application of a database of food ingredient fraud and economically motivated adulteration from 1980 to 2010 Journal of Food Science 77 4 2012 R118 R126
20. P. Oliveri, M.C. Casolino, M. Casale, L. Medini, F. Mare, and S. Lanteri A spectral transfer procedure for application of a single class-model to spectra recorded by different near-infrared spectrometers for authentication of olives in brine Analytica Chimica Acta 761 2013 46 52
21. P. Oliveri, and G. Downey Multivariate class modeling for the verification of food-authenticity claims TrAC - Trends in Analytical Chemistry 35 2012 74 86
22. A. Rius, M.P. Callao, and F.X. Rius Multivariate statistical process control applied to sulfate determination by sequential injection analysis Analyst 122 8 1997 737 741 (Pubitemid 27373060)
23. T. Szigedi, J. Lénárt, M. Dernovics, S. Turza, and M. Fodor Protein content determination in Brassica oleracea species using FT-NIR technique and PLS regression International Journal of Food Science and Technology 47 2 2012 436 440
24. R. Vitale, M. Bevilacqua, R. Bucci, A.D. Magrì, A.L. Magrì, and F. Marini A rapid and non-invasive method for authenticating the origin of pistachio samples by NIR spectroscopy and chemometrics Chemometrics and Intelligent Laboratory Systems 121 2013 90 99
25. S. Wold Pattern recognition by means of disjoint principal components models Pattern recognition 8 3 1976 127 139
26. L. Xu, C. Cai, and D. Deng Multivariate quality control solved by one-class partial least squares regression: identification of adulterated peanut oils by mid-infrared spectroscopy Journal of Chemometrics 25 10 2011 568 574
27. L. Xu, Z. Ye, S. Yan, P. Shi, H. Cui, and X. Fu Combining local wavelength information and ensemble learning to enhance the specificity of class modeling techniques: identification of food geographical origins and adulteration Analytica Chimica Acta 754 2012 31 38
28. Q. Zhang, C. Liu, Z. Sun, X. Hu, Q. Shen, and J. Wu Authentication of edible vegetable oils adulterated with used frying oil by fourier transform infrared spectroscopy Food Chemistry 132 3 2012 1607 1613