Chemometrics authenticity

Pennington, N. et al., Red and white wine varietal authenticity using FTIR spectroscopy and chemometrics, in Abstracts of Papers, 229th ACS National Meeting American Chemical Society, San Diego, CA, 2005. 

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. 

In addition to the measured values and the analytical values (e.g. content, concentration), latent variables are included in the scheme. Latent variables can be obtained from measured values or from analytical values by means of mathematical operations (e.g. addition, subtraction, eigenanal-ysis). By means of latent variables and their typical pattern (represented in chemometric displays) special information can be obtained, e.g. on quality, genuineness, authenticity, homogeneity, origin of products, and health of patients. 

Cuny, M., Vigneau, E., Le Gall, G., Colquhoun, I., Lees, M., and Rutledge, D. N. (2008). Fruit juice authentication by FI NMR spectroscopy in combination with different chemometrics tools. Anal. Bioanal. Chem. 390,419-427. 

Downey, G., Food and food ingredient authentication by mid-infrared spectroscopy and chemometrics, Trends Anal. Chem., 17, 418 -24, 1998. 

Thousands of chemical compounds have been identified in oils and fats, although only a few hundred are used in authentication. This means that each object (food sample) may have a unique position in an abstract n-dimensional hyperspace. A concept that is difficult to interpret by analysts as a data matrix exceeding three features already poses a problem. The art of extracting chemically relevant information from data produced in chemical experiments by means of statistical and mathematical tools is called chemometrics. It is an indirect approach to the study of the effects of multivariate factors (or variables) and hidden patterns in complex sets of data. Chemometrics is routinely used for (a) exploring patterns of association in data, and (b) preparing and using multivariate classification models. The arrival of chemometrics techniques has allowed the quantitative as well as qualitative analysis of multivariate data and, in consequence, it has allowed the analysis and modelling of many different types of experiments. 

Table 7.1 Authentication of the geographical origin of virgin olive oil samples comparative results of SEXIA expert system, neural networks and the supervised chemometric procedure of stepwise linear discriminant analysis. Samples collected in the regions of Jaen (Spain)...

Table 7.2 Authentication of mono varietal virgin olive oils comparative results of fuzzy logic algorithms (Calvente and Aparicio, 1995) and the supervised chemometric procedure of linear discriminant analysis. Chemical compounds used linolenic acid, 24-methylen-cycloarthanol sterol and copaene hydrocarbon...

Chapters 6 and 7 focus on techniques used in checking for authenticity. The most useful components for detecting sophisticated adulteration are the minor components. These analyses often produce a mass of data in which a pattern is difficult to detect with an untrained eye. Chemometrics can be utilised to investigate trends and patterns and thus detect non-standard oils which might otherwise be missed. 

However, it is not just the presence or absence of an element that is useful (as most elements will be present at some concentration), but it is the relative variation in the trace element profile that is the parameter that provides the major discriminatory power. McHard et al. [16] were possibly some of the first researchers to apply a normalization procedure to multielement data in order to maximize the differences between two sets of samples. Their approach, which is now accepted as being a standard tool for use in chemometric investigations, was to identify an element whose concentration was constant, irrespective of the geographical origin of the samples, and then to normalize all other elemental data against it. In McHard s study on fruit juice, they used Zn. The authors of this chapter used Ca in an egg authenticity study, where eggshells were used as the sample matrix (unpublished data) and Mg was used in a study of Welsh onions [14]. 

Andrea, T. A. Kalayeh, H. (1991). Applications of neural networks in quantitative structure-activity relationships of dihydrofolate reductase inhibitors. Journal of Medicinal Chemistry. Vol. 34, pp. 2824-2836. ISSN 0022-2623 Aparido, R. Aparicio-Ruiz, R. (2002). Chemometrics as an aid in authentication. In Oils and Fats Authentication, M Jee (Ed.), 156-180, Blackwell Publishing and CRC Press, ISBN 1841273309, Oxford, UK and FL, USA Bishop, CM. (2000). Neural Networks for Pattern Recognition, Oxford University Press, ISBN 0198538642, NY, USA... 

Authentication of pjropohs material may be possible by a chemical fingerprint of it and, if possible, of its botanical sources. Thus, chemical fingerprinting, i.e., metabolomics and chemometrics, is an additional method that has been claimed to be included as a quality control method in order to confirm or deny the ptropohs sample being used for the manufacturing of a derived product of that resinous and complex matrix. 

Zhang, G., Ni, Y., ChnrchiU, 1., and Kokot, S. Authentication of vegetable oils on the basis of then-physico-chemical properties with the aid of chemometrics. Talanta, 70(2), 293-300. 2006. 

PyMS is capable of generating useful data on intact foodstuffs or associated microorganisms (food poisoning bacteria, for example). PyMS is based on the controlled thermal degradation of samples under inert conditions to produce mixtures of volatile compounds that are swept into the mass spectrometer ion source and ionized by El or Cl. The resulting fingerprint spectrum of the analyte contains characteristic features that can be classified by chemometric methods. Pyrolysis is sometimes combined with GC-MS in order to extract more information from the analyte. Applications of PyMS in the food sciences include quality assurance and authentication of food and drinks, analysis of cell wall material in food plants, and identification of food microorganisms. 

The methods used to attain the correct identification of olive oils will also have to take into account the potential large variability arising from variety, location and environmental differences in the compositional characteristics of pure virgin olive oils thus the availability of reliable methods for authentication of the geographical origin of the oils will be crucial. As discussed above, one possible method is Curie-point PyMS (Section 10.3.2) combined with a powerful multivariate or chemometric analysis technique such as ANNs (Section 10.4.9) (Fig. 10.14). 

Among the different chemometric methods, exploratory data analysis and pattern recognition are frequently used in the area of food analysis. Exploratory data analysis is focused on the possible relationships between samples and variables, while pattern recognition studies the behavior between samples and variables [95]. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) are the methods most commonly used for exploratory analysis and pattern recognition, respectively. The importance of these statistical tools has been demonstrated by the wide number of works in the field of food science where they have been applied. The majority of the applications are related to the characterization and authentication of olive oil, animal fats, marine and vegetable oils [95], wine [97], fruit juice [98], honey [99], cheese [100,101], and so on, although other important use of statistical tools is the detection of adulterants or frauds [96,102]. 

Bosque-Sendra, J. M., Cuadros-Rodriguez, L., Ruiz-Samblas, C., and de la Mata, A. P. 2012. Combining chromatography and chemometrics for the characterization and authentication of fats and oils from triacylglycerol compositional data—A review. Anal. Chim. Acta 724 1—11. 

Bratu, A., Mihalache, M., Hanganu, A., Chira, N.-A., Todasca, M.-C., and Rosea, S. 2012. Gas chromatography coupled with chemometric method for authentication of Romanian cheese. Rev. Chim. 63 1099-1102. 

SNIF-NMR AND CHEMOMETRIC METHODS APPLIED TO H NMR IN THE STUDY OF BRAZILIAN BRANDY AUTHENTICITY... 

The aim of this work is demonstrate the application of SNIF-NMR technique and chemometric methods applied to H NMR to determine Brazilian aguardente authenticity. 

POMODORO DIPACHINO AN AUTHENTICATION STUDY USING H-NMR AND CHEMOMETRICS - PROTECTING ITS P.G.I. EUROPEAN CERTIFICATION... 

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