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The main achievements of high-resolution NMR spectroscopy in combination with different chemometric methods in the analysis of food products in the last 40 years are reviewed. The essence of chemometric methods used for the analysis and interpretation of NMR spectra is briefly described. Sample preparation for NMR-spectroscopic analysis is characterized. Methods for the mathematical treatment of NMR spectra (smoothing, Fourier transformation, bucketing, normalization, and selection of spectral ranges) are considered. Currently available methods for the suppression of the signals of macrocomponents, including those for the simultaneous suppression of several signals, are described. The results are illustrated based on examples of analysis of different classes of foodstuffs and beverages with the use of NMR spectroscopy and chemometric methods for classification and discrimination (geographical and botanical origin as well as validating checking the brand authenticity). Keywords: NMR spectroscopy, chemometrics, food analysis, adulteration, principal component analysis, projections to latent structures DOI: 10.1134/S1061934813090098, Nuclear magnetic resonance (NMR) spectroscopy is one of the most successful and multipurpose analytical techniques [1]. NMR spectroscopy possesses a number of unique properties, which make it promising for the [...]

A comprehensive study of 603 roasted arabica coffee samples using NMR fingerprinting and multivariate data analysis was performed to differentiate coffee samples according to their geographical origin and cultivation method. Both lipophilic and hydrophilic coffee metabolites were recorded using 1 H NMR spectroscopy, and principal component analysis followed by linear discriminant analysis (PCA-LDA) was applied. Coffee samples were fist differentiated according to their continents of origin followed by discrimination of coffee samples from Brazil, Ethiopia, and Colombia from coffee samples originating from another continent. Discrimination of coffee samples according to their continent of origin and additional assignment to the countries Brazil and Ethiopia were successful. However, an unambiguous separation of Colombian coffee samples from coffee samples of another continent (other than South America) was not possible. Also, differentiation of organically and conventionally produced coffee samples by using 1 H NMR and PCA-LDA was not achieved., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The importance of animal welfare and the organic production of chicken eggs has increased in the European Union in recent years. Legal regulation for organic husbandry makes the production of organic chicken eggs more expensive compared to conventional husbandry and thus increases the risk of food fraud. Therefore, the aim of this study was to develop a non-targeted lipidomic LC-ESI-IM-qToF-MS method based on 270 egg samples, which achieved a classification accuracy of 96.3%. Subsequently, surrogate minimal depth (SMD) was applied to select important variables identified as carotenoids and lipids based on their MS/MS spectra. The LC-MS results were compared with FT-NIR spectroscopy analysis as a low-resolution screening method and achieved 80.0% accuracy. Here, SMD selected parts of the spectrum which are associated with lipids and proteins. Furthermore, we used SMD for low-level data fusion to analyze relations between the variables of the LC-MS and the FT-NIR spectroscopy datasets. Thereby, lipid-associated bands of the FT-NIR spectrum were related to the identified lipids from the LC-MS analysis, demonstrating that FT-NIR spectroscopy partially provides similar information about the lipidome. In future applications, eggs can therefore be analyzed with FT-NIR spectroscopy to identify conspicuous samples that can subsequently be counter-tested by mass spectrometry.

Meat species of raw meat and processed meat products were investigated by 1 H NMR spectroscopy with subsequent multivariate data analysis. Sample preparation was based on aqueous extraction combined with ultrafiltration in order to reduce macromolecular components in the extracts. 1 H NMR data was analyzed by using a non-targeted approach followed by principal component analysis (PCA), linear discrimination analysis (LDA), and cross-validation (CV) embedded in a Monte Carlo (MC) resampling approach. A total of 379 raw meat samples (pork, beef, poultry, and lamb) and 81 processed meat samples (pork, beef, poultry) were collected between the years 2018 and 2021. A 99% correct prediction rate was achieved if the raw meat samples were classified according to meat species. Predicting processed meat products was slightly less successful (93 %) with this approach. Furthermore, identification of spectral regions that are relevant for the classification via polar chemical markers was performed. Finally, data on polar metabolites were fused with previously published 1 H NMR data on non-polar metabolites in order to build a broader classification model and to improve prediction accuracy., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Decker, Krapf, Kuballa and Bunzel.)

The animal species of raw meat and processed meat products was determined by 1 H NMR spectroscopy with subsequent multivariate data analysis. Sample preparation was based on comprehensive lipid extraction to capture nonpolar and polar (amphiphilic) fat components of meat. A nontargeted approach was used to analyze the 1 H NMR data, followed by a principal component analysis, linear discrimination analysis, and cross-validation embedded in a Monte Carlo re-sampling approach. A total of 437 raw meat samples (pork, beef, poultry, and lamb) and 81 processed meat samples (pork, beef, and poultry) were collected to build and/or test the classification model. On average, 98% of the analyzed raw meat samples and 97% of the processed meat products were correctly classified with respect to meat species. Furthermore, relevant spectral regions to identify potential chemical markers such as linoleic acids, trans-fatty acids, and cholesterol for the meat species classification were described.

Coffee silver skin is produced in large amounts as a by-product during the coffee roasting process. In this study, coffee silver skin of the species Coffea arabica L. and Coffea canephora Pierre ex A. Froehner as well as silver skin pellets produced in the coffee industry were characterized with respect to both nutritional value and potential heat-induced contaminants. Enzymatic-gravimetric/chromatographic determination of the dietary fiber content showed values ranging from 59 to 67 g/100 g with a comparably high portion of soluble fiber, whereas low molecular weight soluble fiber was not detected. Compositional and methylation analysis indicated the presence of cellulose and xylans in the insoluble dietary fiber fraction, whereas pectic polysaccharides dominate the soluble dietary fiber fraction. The protein content as determined by the Kjeldahl method was in the range of 18 to 22 g/100 g, and all essential amino acids were present in coffee silver skin; whereas fat contents were low, high ash contents were determined. Elemental analysis by inductively coupled plasma mass spectrometry (ICP-MS) showed the presence of macroelements in large amounts, whereas toxic mineral elements were only detected in trace amounts or being absent. Acrylamide was quantified with levels of 24-161 µg/kg. Although 5-hydroxymethylfurfural was detected, its concentration was below the limit of determination. Furfuryl alcohol was not detected.

Toxicologically relevant levels of the psychoactive ∆ 9 -tetrahydocannabinol (∆ 9 -THC) as well as high levels of non-psychoactive cannabinoids potentially occur in CBD (cannabidiol) oils. For consumer protection in the fast-growing CBD oil market, facile and rapid quantitative methods to determine the cannabinoid content are crucial. However, the current standard method, i.e., liquid chromatography combined with tandem mass spectrometry (HPLC-MS/MS), requires a time-consuming multistep sample preparation. In this study, a quantitative nuclear magnetic resonance spectroscopy (qNMR) method for screening cannabinoids in CBD oils was developed. Contrary to the HPLC-MS/MS method, this qNMR features a simple sample preparation, i.e., only diluting the CBD oil in deuterochloroform. Pulse length-based concentration determination (PULCON) enables a direct quantification using an external standard. The signal intensities of the cannabinoids were enhanced during the NMR spectra acquisition by means of multiple suppression of the triglycerides which are a major component of the CBD oil matrix. The validation confirmed linearity for CBD, cannabinol (CBN), ∆ 9 -THC and ∆ 8 -THC in hemp seed oil with sufficient recoveries and precision for screening. Comparing the qNMR results to HPLC-MS/MS data for 46 commercial CBD oils verified the qNMR accuracy for ∆ 9 -THC and CBD, but with higher limits of detection. The developed qNMR method paves the way for increasing the sample throughput as a complementary screening before HPLC-MS/MS.

The food additive sorbic acid is considered as an effective preservative for certain cereal products, and propionic acid is commonly added in bakery wares, e.g., bread and fine bakery wares. The aim of this study was to develop and validate a new nuclear magnetic resonance spectroscopy ( 1 H NMR) method for the routine screening and quantification of sorbic and propionic acids in bread and several bakery products for quality control purposes. Results showed that none of the screened samples contained higher concentrations than regulatory maximum limits. However, for some samples, labelling of preservatives was lacking or they were used in food categories, for which the use is not approved. It can be concluded that the developed NMR method can be used for the routine screening of bakery products.

Due to legal regulations, the rise of globalised (online) commerce and the need for public health protection, the analysis of spirit drinks (alcoholic beverages >15% vol) is a task with growing importance for governmental and commercial laboratories. In this article a newly developed method using nuclear magnetic resonance (NMR) spectroscopy for the simultaneous determination of 15 substances relevant to assessing the quality and authenticity of spirit drinks is described. The new method starts with a simple and rapid sample preparation and does not need an internal standard. For each sample, a group of 1 H-NMR spectra is recorded, among them a two-dimensional spectrum for analyte identification and one-dimensional spectra with suppression of solvent signals for quantification. Using the Pulse Length Based Concentration Determination (PULCON) method, concentrations are calculated from curve fits of the characteristic signals for each analyte. The optimisation of the spectra, their evaluation and the transfer of the results are done fully automatically. Glucose, fructose, sucrose, acetic acid, citric acid, formic acid, ethyl acetate, ethyl lactate, acetaldehyde, methanol, n-propanol, isobutanol, isopentanol, 2-phenylethanol and 5-(hydroxymethyl)furfural (HMF) can be quantified with an overall accuracy better than 8%. This new NMR-based targeted quantification method enables the simultaneous and efficient quantification of relevant spirit drinks ingredients in their typical concentration ranges in one process with good accuracy. It has proven to be a reliable method for all kinds of spirit drinks in routine food control.

Background: Coffee is a popular beverage with two species, Coffea canephora and C. arabica, being commercially exploited. The quality and commercial value of coffee is dependent on species and processing. C. arabica typically obtains a higher price on the market compared to C. canephora. Coffee beans undergo roasting during processing, resulting in the formation of flavor compounds including furfuryl alcohol which has been classified by the International Agency for Research on Cancer as possibly carcinogenic to humans (Group 2B)., Objective: The aim of this study was to identify coffee species and other properties using nuclear magnetic resonance (NMR) spectroscopy, specifically to conduct quantification of the roasting process contaminant furfuryl alcohol., Method: The quantification of furfuryl alcohol was performed from the NMR spectra using the pulse length-based concentration (PULCON) methodology. Prior to NMR analysis, samples were extracted using deuterated chloroform., Results: Roasting experiments identified the maximum roasting temperature to be the most significant factor in the formation of furfuryl alcohol. Among the coffee species, C. canephora was found to contain a relatively lower amount of furfuryl alcohol compared to C. arabica. The roasting of wet processed coffee resulted in higher contents of furfuryl alcohol. Geographical origin and variety within species had no influence on the furfuryl alcohol content., Conclusion: Validation results show that NMR spectroscopy is fit-for-purpose to obtain targeted information of coffee samples., Highlights: The PULCON NMR methodology allows a simple, rapid and accurate determination of constituents of coffee., (© AOAC INTERNATIONAL 2020. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Monitoring coffee quality as a means of detecting and preventing economically motivated fraud is an important aspect of international commerce today. Therefore, there is a compelling need for rapid high throughput validated analytical techniques such as quantitative proton nuclear magnetic resonance (NMR) spectroscopy for screening and authenticity testing. For this reason, we sought to validate an 1 H NMR spectroscopic method for the routine screening of coffee for quality and authenticity. A factorial experimental design was used to investigate the influence of the NMR device, extraction time, and nature of coffee on the content of caffeine, 16- O -methylcafestol (OMC), kahweol, furfuryl alcohol, and 5-hydroxymethylfurfural (HMF) in coffee. The method was successfully validated for specificity, selectivity, sensitivity, and linearity of detector response. The proposed method produced satisfactory precision for all analytes in roasted coffee, except for kahweol in canephora (robusta) coffee. The proposed validated method may be used for routine screening of roasted coffee for quality and authenticity control (i.e., arabica/robusta discrimination), as its applicability was demonstrated during the recent OPSON VIII Europol-Interpol operation on coffee fraud control.

Furan fatty acids (FuFAs) are a class of naturally occurring minor fatty acids with fish as the richest food source. Typically, FuFA analysis is cumbersome and involves several steps. We developed a quantitative 1 H NMR method (qNMR) in which fish oil samples were directly measured after dilution with CDCl 3 stabilized with silver (which was essential to prevent formation of radicals) and addition of an internal standard. The singlet at δ = 1.89 ppm was suitable for quantitation of monomethyl FuFAs, whereas the signal at δ = 1.83 ppm was suitable to quantitate dimethyl FuFAs. Using standard NMR tubes with 650 μL solvent, the limit of quantitation was 0.5 μg (dimethyl FuFAs) and 1.0 μg (monomethyl FuFAs). Applied to three fish oil and two enriched fish oil samples (sample weight, 10 mg), the final qNMR method resulted in similar total FuFA contents as determined in parallel by gas chromatography coupled to mass spectrometry.

Both the German and European organic food markets are growing fast, and there is also a rising demand for organic chicken eggs. Consumers are willing to pay higher prices for organic eggs produced in an animal-appropriate environment considering animal welfare. Strict labelling requirements do not prevent chicken eggs from being a subject of food fraud. Conventionally produced (barn/free-range) eggs can easily be mislabeled as organic eggs. Especially because the demand for organically produced chicken eggs is likely to exceed supply in the future, mislabeling appears to be a realistic scenario. Therefore, there is a need for analytical methods that are suitable to classify eggs as being either conventionally or organically produced. Nuclear magnetic resonance (NMR) spectroscopy in combination with multivariate data analysis is a suitable tool to screen eggs according to the different systems of husbandry. Sample preparation is based on a fat extraction method, which was optimised for application to freeze-dried egg yolk. Samples were analysed using typical q-NMR parameters. A nontargeted approach was used for the analysis of the 1 H NMR data. Principal component analysis (PCA) was applied followed by a linear discriminant analysis (PCA-LDA) and Monte Carlo cross-validation. In total, 344 chicken eggs (214 barn/free-range eggs and 130 eggs from organic farms), most of them originating from Germany, were used to build and validate the prediction model. The results showed that the prediction model allowed for the correct classification of about 93% of the organic eggs., (© 2019 John Wiley & Sons, Ltd.)

The four heat-induced coffee contaminants-acrylamide, furfuryl alcohol (FA), furan and 5-hydroxymethylfurfural (HMF)-were analyzed in a collective of commercial samples as well as in Coffea a rabica seeds roasted under controlled conditions from very light Scandinavian style to very dark Neapolitan style profiles. Regarding acrylamide, average contents in commercial samples were lower than in a previous study in 2002 (195 compared to 303 µg/kg). The roasting experiment confirmed the inverse relationship between roasting degree and acrylamide content, i.e., the lighter the coffee, the higher the acrylamide content. However, FA, furan and HMF were inversely related to acrylamide and found in higher contents in darker roasts. Therefore, mitigation measures must consider all contaminants and not be focused isolatedly on acrylamide, specifically since FA and HMF are contained in much higher contents with lower margins of exposure compared to acrylamide., Competing Interests: The authors declare no conflict of interest.

Mineral oils (such as paraffinum liquidum or white oil), which consist of mineral oil saturated hydrocarbons (MOSH) and mineral oil aromatic hydrocarbons (MOAH), are widely applied in various consumer products such as medicines and cosmetics. Contamination of food with mineral oil may occur by migration of mineral oil containing products from packaging materials, or during the food production process, as well as by environmental contamination during agricultural production. Considerable analytical interest was initiated by the potential adverse health effects, especially carcinogenic effects of some aromatic hydrocarbons. This article reviews the history of mineral oil analysis, starting with gravimetric and photometric methods, followed by on-line-coupled liquid chromatography with gas chromatography and flame ionization detection (LC-GC-FID), which still is considered as gold standard for MOSH-MOAH analysis. Comprehensive tables of applications in the fields of cosmetics, foods, food contact materials, and living organisms are provided. Further methods including GCxGC-MS methods are reviewed, which may be suitable for confirmation of LC-GC-FID results and identification of compound classes. As alternative to chromatography, nuclear magnetic resonance (NMR) spectroscopy has recently been suggested for MOSH-MOAH analysis, especially with the possibility of detecting only the toxicologically relevant aromatic rings. Furthermore, NMR may offer potential as rapid screening especially with low-field instruments usable for raw material control., Competing Interests: Declaration Of Conflicting Interests:The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Beverage fraud involving counterfeiting of brand spirits is an increasing problem not only due to deception of the consumer but also because it poses health risks e.g. from possible methanol admixture. Suspicious spirit samples from Russia and Kenya were analysed using 1 H nuclear magnetic resonance (NMR) spectroscopy in comparison to authentic products. Using linear regression analysis of spectral integral values, 4 counterfeited samples from Russia and 2 from Kenya were easily identifiable with R 2  < 0.7. Sensory analysis using triangle test methodology confirmed significant taste differences between counterfeited and authentic samples but the assessors were unable to correctly identify the counterfeited product in the majority of cases. An important conclusion is that consumers cannot assumed to be self-responsible when consuming counterfeit alcohol because there is no general ability to organoleptically detect counterfeit alcohol., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Mineral hydrocarbons consist of two fractions, mineral oil saturated hydrocarbons (MOSH) and mineral oil aromatic hydrocarbons (MOAH). MOAH is a potential public health hazard because it may include carcinogenic polycyclic compounds. In the present study, 400 MHz nuclear magnetic resonance (NMR) spectroscopy was introduced, in the context of official controls, to measure MOSH and MOAH in raw materials or pure mineral hydrocarbon final products (cosmetics and medicinal products). Quantitative determination (qNMR) has been established using the ERETIC methodology (electronic reference to access in vivo concentrations) based on the PULCON principle (pulse length based concentration determination). Various mineral hydrocarbons (e.g., white oils, paraffins or petroleum jelly) were dissolved in deuterated chloroform. The ERETIC factor was established using a quantification reference sample containing ethylbenzene and tetrachloronitrobenzene. The following spectral regions were integrated: MOSH δ 3.0 - 0.2 ppm and MOAH δ 9.2 - 6.5, excluding solvent signals. Validation showed a sufficient precision of the method with a coefficient of variation <6% and a limit of detection <0.1 g/100 g. The applicability of the method was proven by analysing 27 authentic samples with MOSH and MOAH contents in the range of 90-109 g/100 g and 0.02-1.10 g/100 g, respectively. It is important to distinguish this new NMR-approach from the hyphenated liquid chromatography-gas chromatography methodology previously used to characterize MOSH/MOAH amounts in cosmetic products. For mineral hydrocarbon raw materials or pure mineral hydrocarbon-based cosmetic products, NMR delivers higher specificity without any sample preparation besides dilution. Our sample survey shows that previous methods may have overestimated the MOAH amount in mineral oil products and opens new paths to characterize this fraction. Therefore, the developed method can be applied for routine monitoring of consumer products aiming to minimize public health risks., Competing Interests: Competing interests: No competing interests were disclosed.

A nuclear magnetic resonance (NMR) method was developed to quantify cations in mineral water. The procedure was based on integration of signals from metal-ethylenediaminetetraacetic acid (EDTA) complexes at δ 2.70ppm for Mg 2+ and δ 2.56ppm for Ca 2+ . The limits of detection were below 0.5mg/L. Lack of precision did not exceed 5%. Linearity was between 1 and 500mg/L. Correlation between NMR and a reference chromatographic method was significant (p<0.0001, R 2 =0.99). PLS models were also established to estimate Na + and K + contents. R 2 was 0.85 and 0.83, respectively. Root mean square errors of cross validation (RMSECV) were 8.0mg/L and 1.9mg/L for Na + and K + , respectively. The method was applied successfully for the analysis of 31 mineral water samples. This method is a useful tool for quantification of important cations in mineral water and might easily be adapted to other food matrices., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

A simple, rapid, and selective quantitative nuclear magnetic resonance spectroscopic method was evaluated for the determination of the content of fluorinated pharmaceuticals. 19 F NMR spectra were either obtained in dimethylsulfoxide- d 6 or aqueous buffer, using trifluoroacetic acid as internal standard. Quantification of 13 fluorine-containing pharmaceuticals spanning various pharmacological classes was accomplished using the proposed method. The method was found to be fit for purpose (interday precision 1.2% relative standard deviation) and may thus be applied for routine analysis and quality control of fluorine-containing pharmaceuticals due to its simplicity, nondestructive sample measurement, reliability, and high specificity. Therefore, 19 F NMR may serve as a suitable analytical tool for the identification and selective determination of fluorinated pharmaceuticals used as reference materials and bulk samples.

This study is the first to evaluate the potential of Calligonum azel Maire as a food ingredient. The plant materials flowers, leaves, stems and roots were analyzed by wet-chemical and instrumental methods for major and minor composition. The highest protein and sugar contents were recorded in the flowers (17.8% and 1.6% respectively), while the fat content was most abundant in the leaves (2.9%). Hexane extracts screened by gas chromatography (GC) for fatty acid composition showed 14 major compounds such as oleic acid, linoleic acid and palmitic acid, but also ω3 and ω6 unsaturated fatty acids. The essential oils extracted by hydrodistillation were screened by GC/MS and 31 compounds were identified including estragole, naphthalene, anethole, phytol and curcumene. The HPLC-DAD screening revealed that the methanolic extracts do not contain any pharmacologically active compound with adverse properties, but quercetin, hordenine and vanillin were abundant in the flowers, leaves and roots. Proton nuclear magnetic resonance ( 1 H NMR) spectroscopy showed that glucose, sucrose and fructose were abundant in acetone and methanol extracts, while urea and glycerol were abundant in the aqueous extracts. A sensory evaluation of the aqueous infusions showed properties of the flowers reminiscent of other herbal teas. In conclusion, our results corroborate the suitability of the traditionally described use of Calligonum azel Maire as food and feed. The further study of this plant as a sustainable nutritional ingredient appears to be worthwhile., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The consumption of alcoholic beverages has been classified as carcinogenic to humans by the International Agency for Research on Cancer (IARC) since 1988. More recently, in 2010, ethanol as the major constituent of alcoholic beverages and its metabolite acetaldehyde were also classified as carcinogenic to humans. Alcoholic beverages as multi-component mixtures may additionally contain further known or suspected human carcinogens as constituent or contaminant. This review will discuss the occurrence and toxicology of eighteen carcinogenic compounds (acetaldehyde, acrylamide, aflatoxins, arsenic, benzene, cadmium, ethanol, ethyl carbamate, formaldehyde, furan, glyphosate, lead, 3-MCPD, 4-methylimidazole, N-nitrosodimethylamine, pulegone, ochratoxin A, safrole) occurring in alcoholic beverages as identified based on monograph reviews by the IARC. For most of the compounds of alcoholic beverages, quantitative risk assessment provided evidence for only a very low risk (such as margins of exposure above 10,000). The highest risk was found for ethanol, which may reach exposures in ranges known to increase the cancer risk even at moderate drinking (margin of exposure around 1). Other constituents that could pose a risk to the drinker were inorganic lead, arsenic, acetaldehyde, cadmium and ethyl carbamate, for most of which mitigation by good manufacturing practices is possible. Nevertheless, due to the major effect of ethanol, the cancer burden due to alcohol consumption can only be reduced by reducing alcohol consumption in general or by lowering the alcoholic strength of beverages.

During sampling and analysis of alcohol-free beverages for food control purposes, a comparably high contamination of benzene (up to 4.6μg/L) has been detected in cherry-flavoured products, even when they were not preserved using benzoic acid (which is a known precursor of benzene formation). There has been some speculation in the literature that formation may occur from benzaldehyde, which is contained in natural and artificial cherry flavours. In this study, model experiments were able to confirm that benzaldehyde does indeed degrade to benzene under heating conditions, and especially in the presence of ascorbic acid. Analysis of a large collective of authentic beverages from the market (n=170) further confirmed that benzene content is significantly correlated to the presence of benzaldehyde (r=0.61, p<0.0001). In the case of cherry flavoured beverages, industrial best practices should include monitoring for benzene. Formulations containing either benzoic acid or benzaldehyde in combination with ascorbic acid should be avoided., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The increased sales of organically produced food create a strong need for analytical methods, which could authenticate organic and conventional products. Combined chemometric analysis of (1)H NMR-, (13)C NMR-spectroscopy data, stable-isotope data (IRMS) and α-linolenic acid content (gas chromatography) was used to differentiate organic and conventional milk. In total 85 raw, pasteurized and ultra-heat treated (UHT) milk samples (52 organic and 33 conventional) were collected between August 2013 and May 2014. The carbon isotope ratios of milk protein and milk fat as well as the α-linolenic acid content of these samples were determined. Additionally, the milk fat was analyzed by (1)H and (13)C NMR spectroscopy. The chemometric analysis of combined data (IRMS, GC, NMR) resulted in more precise authentication of German raw and retail milk with a considerably increased classification rate of 95% compared to 81% for NMR and 90% for IRMS using linear discriminate analysis., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

A fast and reliable nuclear magnetic resonance (NMR) method for quantitative analysis of targeted compounds with overlapped signals in complex mixtures has been established. The method is based on the combination of chemometric treatment for spectra deconvolution and the PULCON principle (pulse length based concentration determination) for quantification. Independent component analysis (ICA) (mutual information least dependent component analysis (MILCA) algorithm) was applied for spectra deconvolution in up to six component mixtures with known composition. The resolved matrices (independent components, ICs and ICA scores) were used for identification of analytes, calculating their relative concentrations and absolute integral intensity of selected resonances. The absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated using the PULCON principle. Instead of conventional application of absolute integral intensity in case of undisturbed signals, the multiplication of resolved IC absolute integral and its relative concentration in the mixture for each component was used. Correction factors that are required for quantification and are unique for each analyte were also estimated. The proposed method was applied for analysis of up to five components in lemon and orange juice samples with recoveries between 90% and 111%. The total duration of analysis is approximately 45 min including measurements, spectra decomposition and quantification. The results demonstrated that the proposed method is a promising tool for rapid simultaneous quantification of up to six components in case of spectral overlap and the absence of reference materials., (Copyright © 2015 John Wiley & Sons, Ltd.)