Chemometrics foods

Chudzinska, M. and Baralkiewicz, D. (2010). Estimation of honey authenticity by multielements characteristics using inductively coupled plasma-mass spectrometry (ICP-MS) combined with chemometrics. Food Chem. Toxicol. 48, 284-290. 

Kim, S., Burgula, Y., Ojanen-Reuhs, T., Cousin, M. A., Reuhs, B. L., and Mauer, U. J. (2006b). Differentiation of crude lipopolysaccharides from Escherichia coli strains using Eourier transform infrared spectroscopy and chemometrics. /. Food Sci. 71, M57-M61. 

Ollivier, D., Artaud, J., Pinatel, C., Durbec, J., andGuerere, M., Differentiation of French virgin oil RDOs by sensory characteristics, fatty acids and triacylglycerol compositions and chemometrics, Food Chem., 97, 382-393, 2006. 

Ni, Y., W. Xiao, and S. Kokot. 2009. A differential kinetic spectrophotometric method for determination of three sulphanilamide artificial sweeteners with the aid of chemometrics. Food Chem. 113 1339-1345. 

Savorani F, Rasmussen MA, Mitkelsen MS, Engelsen SB. A primer to nutritional metabolomics by NMR spectroscopy and chemometrics. Food Res Int 2013 In Press. http //dx. doi.org/10.1016/j.foodres.2012.12.025. (http //www.sciencedirect.com/science/article/pii/ S0963996912005480). 

Mocak, J. Jurasek, P. Phillips, G.O, Vargas, S. Casadei, E. Ghikamai, B.N. (1998). The classification of natural gums. X. Chemometric characterization of exudate gums that conform to the revised specification of the gum arabic for food use, and the identification of adulterants. Food Hydrocolloids, Vol. 12, No. 2, (April 1998), pp 141-150, ISSN 0268-005X. 

The identification of synthetic colorants (pure or mixtures) in foods is usually carried out using spectrophotometry but the resolution of complex mixtures in food requires a previous separation of extract components by SPE and chromatographic techifiques. Dual wavelength, solid phase, and derivative spectrophotometric methods combined with chemometric approaches have been used. ... 

Because of peak overlappings in the first- and second-derivative spectra, conventional spectrophotometry cannot be applied satisfactorily for quantitative analysis, and the interpretation cannot be resolved by the zero-crossing technique. A chemometric approach improves precision and predictability, e.g., by the application of classical least sqnares (CLS), principal component regression (PCR), partial least squares (PLS), and iterative target transformation factor analysis (ITTFA), appropriate interpretations were found from the direct and first- and second-derivative absorption spectra. When five colorant combinations of sixteen mixtures of colorants from commercial food products were evaluated, the results were compared by the application of different chemometric approaches. The ITTFA analysis offered better precision than CLS, PCR, and PLS, and calibrations based on first-derivative data provided some advantages for all four methods. ... 

All these methods give similar results but their sensitivities and resolutions are different. For example, UV-Vis spectrophotometry gives good results if a single colorant or mixture of colorants (with different absorption spectra) were previously separated by SPE, ion pair formation, and a good previous extraction. Due to their added-value capability, HPLC and CE became the ideal techniques for the analysis of multicomponent mixtures of natural and synthetic colorants found in drinks. To make correct evaluations in complex dye mixtures, a chemometric multicomponent analysis (PLS, nonlinear regression) is necessary to discriminate colorant contributions from other food constituents (sugars, phenolics, etc.). 

M. Forina, S. Lanteri and C. Armanino, Chemometrics in Food Chemistry. Topics Curr. Chem., 141 (1987) 93-143. 

Daniel-Kelly, J. F., Downey, G., and Fouratier, V. (2004). Initial study of honey adulteration by sugar solutions using midinfrared (MIR) spectroscopy and chemometrics. /. Agric. Food Chem. 52, 33-39. 

Latorre, M. J., Pena, R., Pita, C., Botana, A., Garcia, S., and Herrero, C. (1999). Chemometric classification of honeys according to their t q)e. II. Metal content data. Food Chem. 66, 263-268. 

NMR spectroscopy is one of the most widely used analytical tools for the study of molecular structure and dynamics. Spin relaxation and diffusion have been used to characterize protein dynamics [1, 2], polymer systems[3, 4], porous media [5-8], and heterogeneous fluids such as crude oils [9-12]. There has been a growing body of work to extend NMR to other areas of applications, such as material science [13] and the petroleum industry [11, 14—16]. NMR and MRI have been used extensively for research in food science and in production quality control [17-20]. For example, NMR is used to determine moisture content and solid fat fraction [20]. Multi-component analysis techniques, such as chemometrics as used by Brown et al. [21], are often employed to distinguish the components, e.g., oil and water. 

Barnes, R. J., Dhanoa, M. S., Lister, S. J. Appl. Spectrosc. 43,1989, 772-777. Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra. Barnes, R. J., Dhanoa, M. S., Lister, S. J. J. Near Infrared Spectrosc. 1, 1993, 185-186. Correction of the description of standard normal variate (SNV) and De-Trend transformations in practical spectroscopy with applications in food and beverage analysis. Brereton, R. G. Chemometrics—Data Analysis for the Laboratory and Chemical Plant. Wiley, Chichester, United Kingdom, 2006. 

Because NIR was initially used for food and agriculture products, it has evolved as a technique for complex matrices. Many types of hardware have become available for NIR work interference filters, gratings, interferometers, diode arrays, and acousto-optic tunable filters. And, as it was originally developed for complex mixtures, chemometrics has been an integral part of any NIR analysis for the last few decades. NIR practitioners are quite comfortable with multivariate equations and development of equations for complex matrices. 

G. Del Campo, J.I. Santos, N. Iturriza, I. Berregi, and A. Munduate, Use of the H nuclear magnetic resonance spectra signals from polyphenols and acids for chemometric characterization of cider apple juices, J. Agric. Food Chem., 54, 3095-3100 (2006). 

G.E. Pereira, J-P. Gaudillere, C. Van Leeuwen, et al., H NMR and chemometrics to characterize mature grape berries in four wine-growing areas in Bordeaux, France, J. Agric. Food Chem., 53, 6382-6389 (2005). 

R. Consonni and L.R. Cagliani, Geographical characterization of polyfloral and acacia honeys by nuclear magnetic resonance and chemometrics, J. Agric. Food Chem., 56(16), 6873-6880 (2008). 

More extensive use of isomer specific analysis, when combined with chemometric techniques, should improve insight into how residues in the environment relate to their sources. This approach could lead to a quantitative description of changes in the composition of these chemicals as they pass through the food chain and are distributed in the environment. 

There is probably more experience of NIR spectroscopy in continuous process monitoring than any other spectroscopic technique [ 100]. The technique has been used for qualitative and quantitative measurements in the agricultural, food, chemical and pharmaceutical industries for several decades [101]. Because of the complexity of correlations within the spectra, the technique has almost driven the specialism of chemometrics, which is essential for extracting useful information. In this section, we shall explore how NIR spectroscopy has achieved this dominant position and how it measures up against alternative techniques as a process-monitoring technique for continuous processes. 

Casaiias, R., Gonzalez, M., Rodriguez, E., Morrero, A., Diaz, C. (2002). Chemometric studies of chemical compounds in five cultivars of potatoes from Tenerife. J. Agric. Food Chem., 50, 2076-2082. 

This close connection and reciprocal necessity between food chemistry and chemo-metrics are shown by the several chemometrical methods being planned or further developed for these purposes or being tested in food chemistry problems. 

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