We have now added signposts to the free IAEA training and Excel add-in for chemometrics to our permanent resources lists. You can find details on our e-seminars page. To aid navigation, it is also listed within mitigation tools. The add-in is invaluable to any laboratory building an authenticity classification model based upon multivariate analysis of known reference samples.
chemometrics (21)
Compound-specific stable isotope analysis (CSIA) of food products is a relatively new and novel technique used to authenticate food and detect adulteration. This paper reviews recent applications of CSIA to authenticate the origin of different foods. CSIA δ13C values are widely used to verify geographical origin, organic production, and adulteration. The δ15N values of individual amino acids and nitrate fertilizers have proven effective to authenticate organic foods, while δ2H and δ18O values are useful to link food products with local precipitation for geographical origin verification. CSIA has a stronger analytical advantage for the authentication of food compared to bulk stable isotope analysis, especially for honey, beverages, essential oils, and processed foods.
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Herbs and Spices are a group of foods highly susceptible to adulteration and fraud because of their high value. In this study, a new high performance liquid chromatography (HPLC) method with UV–vis detection was developed for the characterisation, identification and authentication of cinnamon, oregano, thyme, sesame, bay leaf, clove, cumin, and vanilla. This was achieved by the chromatographic separation of a methanol extract, and identification of 6 phenolic biomarkers (sesamol, eugenol, thymol, carvacrol, salicylaldehyde and vanillin) analysed on 87 samples of the 8 herbs and spices. The data was first treated by PCA (principal component analysis) followed by PLS-DA (partial least squares discriminant analysis) to give good classification between the 8 herbs and spices. The assay thus provides a relatively inexpensive, quality control and screening tool to ensure a correct assurance of the studied spices and herbs.
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This new book is timely given the recent increase in sales of vegan food in particular. It aims to deal with the issues and science related to the authenticity of the most important plant foods such as cereals, nuts, legumes, table olives and olive oil, coffee, tea, fruits and vegetables, fruit juices, spices, mushrooms, beers and wines, and honey, using state-of-the-art analytical techniques and instrumentation coupled with available chemometric tools.
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The authenticity and origin of animal-derived foods are important for consumer information and prevention of food fraud. This review examines the current research techniques for verifying the authenticity and origin of animal-derived foods, in particular using stable isotope ratio analysis and spectroscopic techniques coupled with chemometrics. It covers meat, dairy, and seafood products, as well as honey. It also includes the new trend of analysing the inedible parts of animals to verify their origin.
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"Grappa" is a traditional Italian spirit drink produced from the distillation of fermented grape marc and seeds after winemaking. In the EU Spirit Drink Regulations, "grappa" is a protected name, and it has to be produced from Italian cultivated and processed grapes. Italian researchers have developed a method to authenticate "grappa" using alcohol measurement and gas chromatography analysis of the volatiles on 123 spirit samples. Of these, 43 were "grappa" and the others were spirit drinks from wine, grapes, apples and pears. The samples were divided into a training set (94 samples) of a chemometric model using linear discriminant analysis (LDA), and a validation set (29 samples) was used to test the model and gave good discrimination between the different types of spirits.
Two suspicious samples of "grappa" seized by Italian customs were also examined and analysed. Visual examination revealed differences in the cork closures and barcodes. The analytical results on the chemometric model indicated the two samples were wine spirit rather than "grappa". A further chemometric model was calculated, based on principal component analysis (PCA), which indicated that the two samples were different from wine spirit, and it was concluded that they were an adulterated "grappa" rather than wine spirit. The adulteration was not identified, and further investigation is required. However, the approach developed in this research would serve as a rapid test to authenticate "grappa", and samples not fitting the chemometric models would require further analysis if not fitting exactlyinto the different types of spirit. It is also a useful exercise in developing a method to verify a protected name in food law.
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Spectroscopic methods were used in this study for the discrimination of durum and common wheat samples since they are rapid, reliable, easy to use, low cost, environmentally friendly, and non-destructive. For this purpose, 120 common and 119 durum wheat samples with different genotypes were collected from various regions in Turkey and analysed using Raman spectroscopy, near-infrared spectroscopy (NIR), synchronous fluorescence spectroscopy (SFS), and attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR). Data analysis was performed using the principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA).
These spectroscopic tools, combined with chemometric analysis, were generally successful in distinguishing common and durum wheat flour samples. It was found that the best method was SFS with a discrimination rate of 100% based on high sensitivity (1.000) and specificity (1.000) values. The effectiveness of the models in which NIR and ATR-FTIR spectroscopies were used was found to be highly similar in terms of the discrimination of durum and common wheat samples. Data obtained from Raman Spectroscopy demonstrated that the method was less sensitive in discriminating between common and durum wheat flour samples than the other spectroscopic techniques with a quite high RMSEP value (0.441). SFS, ATR-FTIR, and NIR spectroscopies proved to be more sensitive and applicable tools than Raman spectroscopy in the discrimination of common and durum wheat samples.
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Herbs and spices have been shown to be the group of foods most susceptible to adulteration. This extensive review by Polish researchers examines the application of different types of NMR (nuclear magnetic resonance) combined with chemometrics to characterise and distinguish authentic and adulterated spice samples.
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Garlic is widely used in cooking all over the world. Researchers at Queens University Belfast have verified whether NIR (near infrared) and FTIR (Fourier transform infrared) spectroscopy with chemometric analysis can detect garlic mixed with possible adulterants. Authentic and adulterated garlic (with talc, maltodextrin, corn starch, cornflour, peanut butter powder, sodium caseinate, potato starch, rice flour, cassava and white maize meal) samples were prepared at 20–90% levels, and NIR and FTIR spectra of the samples obtained. Principal component analysis (PCA) models were created to establish if there was separation of garlic from the adulterants.Orthogonal partial least squares – discriminant analysis (OPLS-DA) models were then developed to be able to detect and classify the levels of adulteration correctly using both NIR and FTIR.
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This study compared the capabilities of three spectroscopic techniques as fast screening platforms for honey authentication purposes. Multifloral honeys were collected in the three main honey-producing regions of Argentina over four harvesting seasons to give a total of 502 samples. Spectra were run on each of the samples with FT-MIR ( Fourier transform mid-infrared), NIR (near infrared) and FT-Raman (Fourier transform Raman) spectroscopy. The spectroscopic platforms were compared on the basis of the classification performance achieved under a supervised chemometric approach. Very good classification scores to distinguish the three Argentian regions were achieved by all the spectroscopies, and a nearly perfect classification was provided by FT-MIR. The results obtained in the present work suggested that FT-MIR had the best potential for fingerprinting-based honey authentication, and demonstrated that sufficient accuracy levels to be commercially useful can be reached.
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Food fraud and adulteration is a major concern in terms of economic and public health.Multivariate methods combined with spectroscopic techniques have shown promise as a novel analytical strategy for addressing issues related to food fraud that cannot be solved by the analysis of one variable, particularly in complex matrices such distilled beverages.
This review describes and discusses different aspects of whisky production, and recent developments of laboratory, in field and high throughput analysis. In particular, recent applications detailing the use of vibrational spectroscopy techniques combined with data analytical methods used to not only distinguish between brand and origin of whiskey but to also detect adulteration are presented.
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The main authenticity issues associated with EVOO’s quality involve the organoleptic properties (EVOO or defective), mislabelling of production type (organic or conventional), variety and geographical origin, and adulteration. Greek researchers have reviewed the various "omics" (mainly genomics and metabolomics) using HRMS with various chemometric tools presenting the various workflows to verify critical aspects of olive oil authenticity.
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Lard is a cheaper saturated fat than butter. A rapid method for its detection was developed using a portable Raman spectrometer combined with chemometrics. Samples of butter adulterated with different amounts of lard from 0-100% were prepared and their Raman spectra recorded. Chemometric analysis was applied for the classification and discrimination of butter and lard-adulterated samples, as well as the quantification of lard in butter samples. This method could be applied for in-situ analysis or quality control of butter samples.
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This review by Polish researchers reviews the use of spectroscopic methods in testing the authenticity of some selected herbs and spices. The review covers the spectroscopic techniques - IR, NMR, UV in combination with advanced statistical methods (PCA, CA) to confirm either the origin of the product or distinguishes the herbs or spices from any adulterating ingredients.
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Modern analytical measurement technologies for food authentication, such as infrared, NMR, mass spectrometry and chromatography, produce the data (spectrum, chromatogram) recorded in digital form. A measurement on a single sample typically comprises thousands of numbers, which is many more than the number of samples, meaning that the experiment overall is underdetermined. Furthermore, chemically different specimens often give rise to quite similar measurements, especially in some of the spectroscopy methods, where there are large numbers of overlapped spectral bands. The techniques of multivariate analysis are especially suitable for dealing with this kind of data to get the best out of these complex and unwieldy datasets.
In this scientific opinion paper, the advantages of a multivariate strategy compared with univariate assessments are discussed, and selected techniques that are now well established in analytical chemistry, such as the data compression methods of principal component analysis are examined. Predictive approaches suitable for authentication applications: discriminant and classification strategies, and class-modelling techniques are also considered. Validation is critical to the application of multivariate techniques. Also, the wider aspects of experimental design, such as the importance of representative sampling are discussed and illustrated from real-world examples of food authenticity problems.
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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
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
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
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
