Mixture resolution according to the percentage of robusta variety in order to detect adulteration in roasted coffee by near infrared spectroscopy.

Near infrared spectroscopy (NIRS), combined with multivariate calibration methods, has been used to quantify the robusta variety content of roasted coffee samples, as a means for controlling and avoiding coffee adulteration, which is a very important issue taking into account the great variability of the final sale price depending on coffee varietal origin. In pursuit of this aim, PLS regression and a wavelet-based pre-processing method that we have recently developed called OWAVEC were applied, in order to simultaneously operate two crucial pre-processing steps in multivariate calibration: signal correction and data compression. Several pre-processing methods (mean centering, first derivative and two orthogonal signal correction methods, OSC and DOSC) were additionally applied in order to find calibration models with as best a predictive ability as possible and to evaluate the performance of the OWAVEC method, comparing the respective quality of the different regression models constructed. The calibration model developed after pre-processing derivative spectra by OWAVEC provided high quality results (0.79% RMSEP), the percentage of robusta variety being predicted with a reliability notably better than that associated with the models constructed from raw spectra and also from data corrected by other orthogonal signal correction methods, and showing a higher model simplicity.

[1]  M. Lees.  Food authenticity and traceability. , 2003 .

[2]  Junbin Gao,et al.  A review on applications of wavelet transform techniques in chemical analysis: 1989–1997 , 1998 .

[3]  Authentication of Whole and Ground Coffee Beans by near Infrared Reflectance Spectroscopy , 1994 .

[4]  Antonio González,et al.  Characterization of arabica and robusta roasted coffee varieties and mixture resolution according to their metal content , 1999 .

[5]  Francesco Palmisano,et al.  Solid-phase microextraction-gas chromatography mass spectrometry and multivariate analysis for the characterization of roasted coffees. , 2005, Talanta.

[6]  E. K. Kemsley,et al.  Near- and Mid-Infrared Spectroscopies in Food Authentication: Coffee Varietal Identification , 1997 .

[7]  L. Mondello,et al.  Reliable characterization of coffee bean aroma profiles by automated headspace solid phase microextraction-gas chromatography-mass spectrometry with the support of a dual-filter mass spectra library. , 2005, Journal of separation science.

[8]  Tom Fearn,et al.  Practical Nir Spectroscopy With Applications in Food and Beverage Analysis , 1993 .

[9]  F. Pablos,et al.  Discrimination between arabica and robusta green coffee varieties according to their chemical composition. , 1998, Talanta.

[10]  K. Jetter,et al.  Principles and applications of wavelet transformation to chemometrics , 2000 .

[11]  M. León-Camacho,et al.  HPLC analysis of tocopherols and triglycerides in coffee and their use as authentication parameters , 2001 .

[12]  Age K. Smilde,et al.  Direct orthogonal signal correction , 2001 .

[13]  Romain Briandet,et al.  Approaches to Adulteration Detection in Instant Coffees using Infrared Spectroscopy and Chemometrics , 1996 .

[14]  M. Dennis,et al.  Analytical Methods Of Food Authentication , 1997 .

[15]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[16]  Jean-Michel Poggi,et al.  Wavelets and their applications , 2007 .

[17]  M. León-Camacho,et al.  Fatty acid profiles as discriminant parameters for coffee varieties differentiation. , 2001, Talanta.

[18]  Consuelo Pizarro,et al.  Generalization of OWAVEC method for simultaneous noise suppression, data compression and orthogonal signal correction , 2005 .

[19]  S. Casal,et al.  Discrimination between arabica and robusta coffee species on the basis of their amino acid enantiomers. , 2003, Journal of agricultural and food chemistry.

[20]  R. Bonner,et al.  Application of wavelet transforms to experimental spectra : Smoothing, denoising, and data set compression , 1997 .

[21]  Douglas B. Kell,et al.  Wavelet Denoising of Infrared Spectra , 1997 .

[22]  Andrea Illy,et al.  Espresso coffee : the science of quality , 2005 .

[23]  G. Lercker,et al.  Determinazione del caffè robusta nelle miscele commerciali con l'arabica , 1995 .

[24]  J. M. González-Sáiz,et al.  Multivariate calibration of near infrared spectra by orthogonal WAVElet correction using a genetic algorithm , 2006 .

[25]  E. K. Kemsley,et al.  Discrimination between Coffea arabica and Coffea canephora variant robusta beans using infrared spectroscopy , 1995 .

[26]  Romain Briandet,et al.  Discrimination of Arabica and Robusta in Instant Coffee by Fourier Transform Infrared Spectroscopy and Chemometrics , 1996 .

[27]  M. León-Camacho,et al.  Authentication of green coffee varieties according to their sterolic profile , 1998 .

[28]  Desire L. Massart,et al.  Wavelets — something for analytical chemistry? , 1997 .

[29]  Desire L. Massart,et al.  Noise suppression and signal compression using the wavelet packet transform , 1997 .

[30]  Authentication of Coffee Bean Variety by Near-infrared Reflectance Spectroscopy of Dried Extract , 1996 .

[31]  P. R. Kulkarni,et al.  Handbook of indices of food quality and authenticity , 1997 .

[32]  Ronald R. Coifman,et al.  Wavelet analysis and signal processing , 1990 .

[33]  M. León-Camacho,et al.  Determination of the arabica/robusta composition of roasted coffee according to their sterolic content , 1999 .

[34]  J. M. González-Sáiz,et al.  An evaluation of orthogonal signal correction methods for the characterisation of arabica and robusta coffee varieties by NIRS , 2004 .

[35]  G. Pellegrino,et al.  Characterization of roasted coffee and coffee beverages by solid phase microextraction-gas chromatography and principal component analysis , 1997 .

[36]  S. Wold,et al.  PLS regression on wavelet compressed NIR spectra , 1998 .

[37]  Consuelo Pizarro,et al.  OWAVEC: a combination of wavelet analysis and an orthogonalization algorithm as a pre-processing step in multivariate calibration , 2004 .

[38]  Beata Walczak,et al.  Wavelets in Chemistry , 2001 .