chemometrics (6)

A Novel Approach for Scotch Whisky Authentication

Scotch whisky, a popular high value spirit drink, is vulnerable to fraud. In this study, a non-targeted screening (metabolomics fingerprinting) of volatile and semi-volatile substances was used. After pre-concentration, gas chromatography (GC) coupled to tandem mass spectrometry (Q-TOF mass analyser) was employed. Unsupervised principle component analysis (PCA) and supervised partial least squares discriminant analysis (PLS–DA) were used for evaluation of data obtained by analysis of a unique set of 171 authentic whisky samples. A very good separation of malt whiskies according to the type of cask in which they were matured (bourbon versus bourbon and wine) was achieved, and significant ´markers´ for bourbon and wine cask maturation, such as N-(3-methylbutyl) acetamide and 5-oxooxolane-2-carboxylic acid, were identified. This unique sample set was used to construct a statistical model for distinguishing malt and blended whiskies. In the final phase, 20 fake samples were analysed, and the data processed in the same way. Some differences could be observed in the (semi)volatile profiles of authentic and fake samples. Employing the statistical model developed by PLS-DA for this purpose, marker compounds that positively distinguish fake samples were identified.

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Small amounts of low cost carob flour do not change the colour, aroma or taste characteristics of cocoa powder. Therefore, Spanish researchers have developed a NIR (near infra-red) method combined with chemometrics to determine that adulteration with carob flour has  taken place, and the amount of carob flour that has been used. Data sets using cocoa powders with different alkalisation levels, carob flours with three different roasting degrees, and adulterated samples prepared by blending cocoa powders with carob flour at several proportions, were obtained. For qualitative results, a principal component analysis (PCA) and a partial least squares discriminant analysis (PLS-DA) were used, giving a 100% classification accuracy to distinguish pure cocoa powders from adulterated samples. For quantitative analysis, a partial least squares (PLS) regression analysis was performed giving a root mean square error of prediction of 3.2%, thus making the method fit for purpose for determining the amount of carob flour in cocoa powder within this error.

              Read the abstract at: cocoa powder adulteration with carob flour

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Multispectral Imaging for Plant Food Quality

This article is a comprehensive review of the use of multispectral imaging combined with chemometrics to determine the composition and quality of various plant-based foods; cereals (wheat, maize), legumes (soybean, peanut), tubers (potato, sweet potato), fruits (apple, pear, kiwi), and vegetables (white radish, sugar beet).  The method is rapid and can give a visualisation of for example the distribution fructose, glucose and sucrose in unripe and ripe fruit. Future developments should make it a useful industrial tool to control raw materials and production. 

Read the full article at: Multispectral imaging of plant foods

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Canadian researchers have developed a Fourier transformed-infrared (FT-IR) spectroscopy optimised protocol for analysing both qualitatively and quantitatively beef mince potentially adulterated with six types of beef and/or pork offal (beef tripe, beef liver, beef omasum, pork heart, pork kidney and pork liver). Two dimensional PCA (principal component analysis) chemometric analysis was applied to the authentic dataset of FT-IR spectra, but did not give sufficient discrimination. An optimised chemometric model based on LDA (linear discriminant analysis), PCA-DA, and PLS-DA (partial least squares-discriminant analysis) was found to give more accurate determination and low error rate for 3 classes of samples- beef, beef offal or pork offal. Once the offal is identified, a further chemometric analysis - PLSR (PLS regression) can be performed to determine accurately the amount of offal present. 

Read the full paper at: FTIR Method for Offal in Beef Mince 

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Chinese researchers measured the free amino acid content in five unifloral honeys (Chinese chastetree, acacia, rape, lungan and jujube) from different locations in China using reverse-phase HPLC. Multivariate statistical analyses of the 16 amino acids employing CA (cluster analysis), PCA (principal component analysis), and DA (discriminant analysis) showed that samples could be classified correctly according to their botanical origin. Additionally, DA offered a more precise mode to determine the botanical origin of Chinese honey.

Read the full paper at: Amino acids in Chinese honey

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Marketing of cocoa and chocolate products made from single origin cocoa is becoming more popular. However, a reliable analytical method able to verify the geographical origin of cocoa is lacking. The potential of HR MAS 1H NMR (Magic-angle spinning NMR in solid state) on cocoa powder combined with chemometrics for metabolic profiling was assessed for the geographical origins of 60 fermented and dried cocoa beans of 23 different cocoa producing countries from the three major crop-growing areas (Africa, Central/South America, Asia/Oceania) was evaluated. The same samples were also subjected to extraction and analysis with liquid solution 1H NMR. The same metabolites were determined by both methods apart from the additional determination of of cocoa lipids by HR MAS 1H NMR, which were lost in the extraction for liquid 1H NMR. HR MAS 1H NMR  gave better discrimination in the verification of geographical origin.

Read the abstract at: NMR determination of cocoa origin

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