Is the Calibration Transfer of Multivariate Calibration Models between High- and Low-Field NMR Instruments Possible? A Case Study of Lignin Molecular Weight.

Although several successful applications of benchtop nuclear magnetic resonance (NMR) spectroscopy in quantitative mixture analysis exist, the possibility of calibration transfer remains mostly unexplored, especially between high- and low-field NMR. This study investigates for the first time the calibration transfer of partial least squares regressions [weight average molecular weight (Mw) of lignin] between high-field (600 MHz) NMR and benchtop NMR devices (43 and 60 MHz). For the transfer, piecewise direct standardization, calibration transfer based on canonical correlation analysis, and transfer via the extreme learning machine auto-encoder method are employed. Despite the immense resolution difference between high-field and low-field NMR instruments, the results demonstrate that the calibration transfer from high- to low-field is feasible in the case of a physical property, namely, the molecular weight, achieving validation errors close to the original calibration (down to only 1.2 times higher root mean square errors). These results introduce new perspectives for applications of benchtop NMR, in which existing calibrations from expensive high-field instruments can be transferred to cheaper benchtop instruments to economize.

Tracing the origin of paracetamol tablets by near-infrared, mid-infrared, and nuclear magnetic resonance spectroscopy using principal component analysis and linear discriminant analysis.

Most drugs are no longer produced in their own countries by the pharmaceutical companies, but by contract manufacturers or at manufacturing sites in countries that can produce more cheaply. This not only makes it difficult to trace them back but also leaves room for criminal organizations to fake them unnoticed. For these reasons, it is becoming increasingly difficult to determine the exact origin of drugs. The goal of this work was to investigate how exactly this is possible by using different spectroscopic methods like nuclear magnetic resonance and near- and mid-infrared spectroscopy in combination with multivariate data analysis. As an example, 56 out of 64 different paracetamol preparations, collected from 19 countries around the world, were chosen to investigate whether it is possible to determine the pharmaceutical company, manufacturing site, or country of origin. By means of suitable pre-processing of the spectra and the different information contained in each method, principal component analysis was able to evaluate manufacturing relationships between individual companies and to differentiate between production sites or formulations. Linear discriminant analysis showed different results depending on the spectral method and purpose. For all spectroscopic methods, it was found that the classification of the preparations to their manufacturer achieves better results than the classification to their pharmaceutical company. The best results were obtained with nuclear magnetic resonance and near-infrared data, with 94.6%/99.6% and 98.7/100% of the spectra of the preparations correctly assigned to their pharmaceutical company or manufacturer.

Lignins Isolated via Catalyst-Free Organosolv Pulping from Miscanthus x giganteus, M. sinensis, M. robustus and M. nagara: A Comparative Study.

As a low-input crop, Miscanthus offers numerous advantages that, in addition to agricultural applications, permits its exploitation for energy, fuel, and material production. Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ. Here, a comparative study is presented between lignins isolated from M. x giganteus, M. sinensis, M. robustus and M. nagara using a catalyst-free organosolv pulping process. The lignins from different plant constituents are also compared regarding their similarities and differences regarding monolignol ratio and important linkages. Results showed that the plant genotype has the weakest influence on monolignol content and interunit linkages. In contrast, structural differences are more significant among lignins of different harvest time and/or season. Analyses were performed using fast and simple methods such as nuclear magnetic resonance (NMR) spectroscopy. Data was assigned to four different linkages (A: ß-O-4 linkage, B: phenylcoumaran, C: resinol, D: ß-unsaturated ester). In conclusion, A content is particularly high in leaf-derived lignins at just under 70% and significantly lower in stem and mixture lignins at around 60% and almost 65%. The second most common linkage pattern is D in all isolated lignins, the proportion of which is also strongly dependent on the crop portion. Both stem and mixture lignins, have a relatively high share of approximately 20% or more (maximum is M. sinensis Sin2 with over 30%). In the leaf-derived lignins, the proportions are significantly lower on average. Stem samples should be chosen if the highest possible lignin content is desired, specifically from the M. x giganteus genotype, which revealed lignin contents up to 27%. Due to the better frost resistance and higher stem stability, M. nagara offers some advantages compared to M. x giganteus. Miscanthus crops are shown to be very attractive lignocellulose feedstock (LCF) for second generation biorefineries and lignin generation in Europe.

Extraction of High-Purity Lignins via Catalyst-free Organosolv Pulping from Low-Input Crops.

A catalyst-free organosolv pulping process was applied to cup plant (Silphium perfoliatum, S), Miscanthus grass (Miscanthus x giganteus, M), and the Paulownia tree (Paulownia tomentosa, P), resulting in high-purity lignins with no signals for cellulose, hemicellulose, or other impurities in two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra. Different biomass particle sizes used for the organosolv pulping (1.6-2.0 mm (1); 0.5-1.0 mm (2); <0.25 mm (3)) influenced the molecular weight and chemical structure of the isolated lignins. Principal component analysis (PCA) of 1H NMR data revealed a high intergroup variance of Miscanthus and Paulownia lignins, separating the small particle fraction from the larger ones. Furthermore, monolignol ratios identified via HSQC NMR differ significantly: Miscanthus lignins were composed of all three monolignols (guaiacyl (G), p-hydroxyphenyl (H), syringyl (S)), while for Paulownia and Silphium lignins only G and S units were observed (except for P3).

Simultaneous determination of proteins in microstructured optical fibers supported by chemometric tools.

A new perspective on the relevant problem-creating simple, rapid, and efficient protein sensors based on microstructured optical fibers using a simple homogeneous analysis format-was proposed. Commercially available long-period grating hollow core microstructured optical fibers (LPG HCMOF) were used to determine bovine serum albumin (BSA) and albumin from chicken eggs (OVA) in binary mixtures as well as immunoglobulin G (IgG) in the presence of BSA and OVA. LPG HCMOF transmission spectra allowed the detection of both BSA and OVA up to 10 mg/mL with LOD as low as 0.1 and 0.8 µg/mL, respectively. Partial least squares regression (PLS) was utilized for modeling of LPG HCMOF spectral data and quantitative analysis of BSA, OVA, total protein, and IgG in binary and ternary mixtures. Rather high coefficients of determination (R2) and low root mean square error for the calibration (RMSEC) (15%) and prediction (RMSEP) (20%) were obtained for all PLS models. The proposed approach was tested in the analysis of BSA in spiked horse blood hemolyzed (HBH). The results demonstrated the functionality of the proposed approach and offered the opportunity for the creation of a wide range of sensors for protein determination in complex mixtures. Graphical abstract.

Miscanthus x giganteus Stem Versus Leaf-Derived Lignins Differing in Monolignol Ratio and Linkage.

As a renewable, Miscanthus offers numerous advantages such as high photosynthesis activity (as a C4 plant) and an exceptional CO2 fixation rate. These properties make Miscanthus very attractive for industrial exploitation, such as lignin generation. In this paper, we present a systematic study analyzing the correlation of the lignin structure with the Miscanthus genotype and plant portion (stem versus leaf). Specifically, the ratio of the three monolignols and corresponding building blocks as well as the linkages formed between the units have been studied. The lignin amount has been determined for M. x giganteus (Gig17, Gig34, Gig35), M. nagara (NagG10), M. sinensis (Sin2), and M. robustus (Rob4) harvested at different time points (September, December, and April). The influence of the Miscanthus genotype and plant component (leaf vs. stem) has been studied to develop corresponding structure-property relationships (i.e., correlations in molecular weight, polydispersity, and decomposition temperature). Lignin isolation was performed using non-catalyzed organosolv pulping and the structure analysis includes compositional analysis, Fourier transform infradred (FTIR), ultraviolet/visible (UV-Vis), hetero-nuclear single quantum correlation nuclear magnetic resonsnce (HSQC-NMR), thermogravimetric analysis (TGA), and pyrolysis gaschromatography/mass spectrometry (GC/MS). Structural differences were found for stem and leaf-derived lignins. Compared to beech wood lignins, Miscanthus lignins possess lower molecular weight and narrow polydispersities (<1.5 Miscanthus vs. >2.5 beech) corresponding to improved homogeneity. In addition to conventional univariate analysis of FTIR spectra, multivariate chemometrics revealed distinct differences for aromatic in-plane deformations of stem versus leaf-derived lignins. These results emphasize the potential of Miscanthus as a low-input resource and a Miscanthus-derived lignin as promising agricultural feedstock.

Automated multicomponent phospholipid analysis using 31P NMR spectroscopy: example of vegetable lecithin and krill oil.

Nuclear magnetic resonance (NMR) spectroscopy is widely applied in the field of metabolomics due to its quantitative nature and the reproducibility of data generated. However, one of the main challenges in routine NMR analysis is to obtain valuable information from large datasets of raw data in a high-throughput, automatic, and reproducible manner. In this study, a method to automatically annotate and quantify 12 phospholipids (PLs) in vegetable lecithin (soy, sunflower, rape) and krill oil is introduced. Automated routines were written in MATLAB environment for quantification of phosphatidylcholine (PC), phosphatidylinositol (PI), lyso-phosphatidylcholine (LPC), phosphatidylserine (PS), phosphatidylethanolamine (PE), diphosphatidylglycerol or cardiolipin (DPG), phosphatidylglycerol (PG), and lyso-phosphatidylethanolamine (LPE) in lecithin and of PC, PC-ether, LPC, PE, N-acyl phosphatidylethanolamine (APE), and LPE in krill oil matrix. The routine includes NMR spectra import, extraction of data points, peaking of local minima and local maxima in the data, integration, quantitation against internal standard, reporting of results as Word file, and their importing in our internal database. Our extensive studies on a representative set of more than 1000 lecithin (soy, rape, sunflower) and krill samples showed that the routine can automatically and accurately calculate the concentrations of all PLs. No systematic or proportional differences between automated and manual evaluation were detected. The developed automated program produces accurate results and requires less than 5 s for each analysis. This tool is already used in high-throughput PL analysis of krill and lecithin and will be adjusted to other matrices (egg, milk, chocolate, etc.) as well.

Monitoring daily routine performance in quantitative NMR (qNMR) spectroscopy: Is the system suitability test necessary?

Nuclear magnetic resonance spectrometry (NMR) finds numerous applications in pharmacy, cosmetic, and food control as well as in developing tools for "big data" analysis. However, there remains a need for automated tools to assess instrument system suitability in real time for each particular routine sample. An automated procedure has been introduced to monitor a number of characteristics (resolution, symmetry, and half width) in real time after the measurement of two samples distributed by the vendor (0.3% CHCl3 in acetone-d6 with tetramethylsilane and 2 mM sucrose in H2 O-D2 O). The results over 11 months were discussed in terms of average values, standard deviations, and spectrometer variability. Moreover, multivariate statistical procedure was implemented to evaluate metrics generated from three NMR spectrometers. Performance of three NMR spectrometers (500 MHz with BBO Prodigy Cryoprobe, 500 MHz with BBFOPLUS SmartProbe, and 600 MHz with BBO Cryoprobe) differed significantly. The developed routine was also applied to calculate the performance characteristics during routine quantitative NMR experiments. The procedure was evaluated for NMR spectra of 659 active pharmaceutical ingredients dissolved in CDCl3 , DMSO, and CH3 OD. This test is more preferable than the routine procedure using standard solutions because the performance is estimated separately for each matrix at the specific time point of measurements. Our automated routine is the ideal tool for any NMR laboratory. In full automation, the NMR data are validated directly for each sample, making unnecessary daily measurements of standard solutions and manual evaluation to their NMR spectra.

Blood species discrimination using proton nuclear magnetic resonance spectroscopy.

Blood species identification is an important challenge in forensic science. Conventional methods used for blood species analysis are destructive and associated with time-consuming sample preparation steps. Nuclear magnetic resonance (NMR) spectroscopy is known for its nondestructive properties and fast results. This research study presents a proton (1H) NMR method to discriminate blood species including human, cat, dog, elephant, and bison. Characteristic signals acting as markers are observed for each species. Moreover, the data are evaluated by principle component analysis (PCA) and support vector machines (SVM). A 100% correct species recognition between human and nonhuman species is achieved using radial basis kernel function (RBF) and standardized data. The research study shows that 1H NMR spectroscopy is a powerful tool for differentiating human and nonhuman blood showing a great significance to forensic science.

Multicomponent quantitative spectroscopic analysis without reference substances based on ICA modelling.

A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.

Practical guide for selection of 1 H qNMR acquisition and processing parameters confirmed by automated spectra evaluation.

In our recent paper, a new technique for automated spectra integration and quality control of the acquired results in qNMR was developed and validated (Monakhova & Diehl, Magn. Res. Chem. 2017, doi: 10.1002/mrc.4591). The present study is focused on the influence of acquisition and postacquisition parameters on the developed automated routine in particular, and on the quantitative NMR (qNMR) results in general, which has not been undertaken previously in a systematic and automated manner. Results are presented for a number of model mixtures and authentic pharmaceutical products measured on 500- and 600-MHz NMR spectrometers. The influence of the most important acquisition (spectral width, transmitter [frequency] offset, number of scans, and time domain) and processing (size of real spectrum, deconvolution, Gaussian window multiplication, and line broadening) parameters for qNMR was automatically investigated. Moderate modification of the majority of the investigated parameters from default instrument settings within evaluated ranges does not significantly affect the trueness and precision of the qNMR. Lite Gaussian window multiplication resulted in accuracy improvement of the qNMR output and is recommended for routine measurements. In general, given that the acquisition and processing parameters were selected based on the presented guidelines, automated qNMR analysis can be employed for reproducible high-precision concentration measurements in practice.

Facilitating the performance of qNMR analysis using automated quantification and results verification.

Quantitative nuclear magnetic resonance (qNMR) is considered as a powerful tool for measuring the absolute amount of small molecules in complex mixtures. However, verification of the accuracy of such quantification is not a trivial task. In particular, preprocessing and integration steps are challenging and potentially erroneous. A script was developed in Matlab environment to automate qNMR analysis. Verification of the results is based on two evolving integration profiles. The analysis of binary mixtures of internal standards as well as pharmaceutical products has shown that all common artifacts (phase and baseline distortion, impurities) can be easily recognized in routine qNMR experiments. In the absence of distortion, deviation between automatically (mean value of several integrals) and manually calculated values was generally below 0.1%. The routine is independent of multiplet pattern, solvent, spectrometer, nuclei type and pulse sequence used. In general, the usage of the developed script can facilitate and verify results of routine qNMR analysis in an automatic manner. Copyright © 2017 John Wiley & Sons, Ltd.

Transfer of multivariate regression models between high-resolution NMR instruments: application to authenticity control of sunflower lecithin.

In recent years the number of spectroscopic studies utilizing multivariate techniques and involving different laboratories has been dramatically increased. In this paper the protocol for calibration transfer of partial least square regression model between high-resolution nuclear magnetic resonance (NMR) spectrometers of different frequencies and equipped with different probes was established. As the test system previously published quantitative model to predict the concentration of blended soy species in sunflower lecithin was used. For multivariate modelling piecewise direct standardization (PDS), direct standardization, and hybrid calibration were employed. PDS showed the best performance for estimating lecithin falsification regarding its vegetable origin resulting in a significant decrease in root mean square error of prediction from 5.0 to 7.3% without standardization to 2.9-3.2% for PDS. Acceptable calibration transfer model was obtained by direct standardization, but this standardization approach introduces unfavourable noise to the spectral data. Hybrid calibration is least recommended for high-resolution NMR data. The sensitivity of instrument transfer methods with respect to the type of spectrometer, the number of samples and the subset selection was also discussed. The study showed the necessity of applying a proper standardization procedure in cases when multivariate model has to be applied to the spectra recorded on a secondary NMR spectrometer even with the same magnetic field strength. Copyright © 2016 John Wiley & Sons, Ltd.

Authentication of the origin of sucrose-based sugar products using quantitative natural abundance (13) C NMR.

BACKGROUND: Due to possible falsification of sugar cane products with cheaper alternative (sugar beet) on the market, a simple analytical methodology needs to be developed to control the authenticity of sugar products. RESULTS: A direct (13) C nuclear magnetic resonance (NMR) method has been validated to differentiate between sucrose-based sugar products produced from sugar beet (C3 plant) and sugar cane (C4 plant). The method is based on calculating relative (13) C content of the C1, C2, C5, and the C1, C4, C5, C6 positions of the glycosyl and fructosyl moieties of the sucrose molecule, respectively. NMR acquisition parameters and data processing have been optimized to reach a high level of intraday and interday precision (<0.2%). Good linearity (R(2) = 0.93) was obtained for the beet sugar-cane sugar blends containing from 0 to 100 wt% of beet sugar. The method was applied to ten commercial sucrose-based sugar products of different botanical origin. Principal component analysis (PCA) was applied to the relative peak areas for replicate measurements to visualize the difference between studied products. CONCLUSION: The (13) C NMR method is a good alternative to complex isotope ratio mass spectrometry measurements for routine detection and semi-quantification of adulteration of commercial cane sugar (C4 plant) with less expensive beet sugar (C3 plant). © 2015 Society of Chemical Industry.

Standardless multicomponent qNMR analysis of compounds with overlapped resonances based on the combination of ICA and PULCON.

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.

Investigation into the structural composition of hydroalcoholic solutions as basis for the development of multiple suppression pulse sequences for NMR measurement of alcoholic beverages.

An eight-fold suppression pulse sequence was recently developed to improve sensitivity in (1) H NMR measurements of alcoholic beverages [Magn. Res. Chem. 2011 (49): 734-739]. To ensure that only one combined hydroxyl peak from water and ethanol appears in the spectrum, adjustment to a certain range of ethanol concentrations was required. To explain this observation, the structure of water-ethanol solutions was studied. Hydroalcoholic solutions showed extreme behavior at 25% vol, 46% vol, and 83% vol ethanol according to (1) H NMR experiments. Near-infrared spectroscopy confirmed the occurrence of four significant compounds ('individual' ethanol and water structures as well as two water-ethanol complexes of defined composition - 1 : 1 and 1 : 3). The successful multiple suppression can be achieved for every kind of alcoholic beverage with different alcoholic strengths, when the final ethanol concentration is adjusted to a range between 25% vol and 46% vol (e.g. using dilution or pure ethanol addition). In this optimum region, an individual ethanol peak was not detected, because the 'individual' water structure and the 1 : 1 ethanol-water complex predominate. The nature of molecular association in ethanol-water solutions is essential to elucidate NMR method development for measurement of alcoholic beverages. The presented approach can be used to optimize other NMR suppression protocols for binary water-organic solvent mixtures, where hydrogen bonding plays a dominant role.

Independent component analysis (ICA) algorithms for improved spectral deconvolution of overlapped signals in 1H NMR analysis: application to foods and related products.

The major challenge facing NMR spectroscopic mixture analysis is the overlapping of signals and the arising impossibility to easily recover the structures for identification of the individual components and to integrate separated signals for quantification. In this paper, various independent component analysis (ICA) algorithms [mutual information least dependent component analysis (MILCA); stochastic non-negative ICA (SNICA); joint approximate diagonalization of eigenmatrices (JADE); and robust, accurate, direct ICA algorithm (RADICAL)] as well as deconvolution methods [simple-to-use-interactive self-modeling mixture analysis (SIMPLISMA) and multivariate curve resolution-alternating least squares (MCR-ALS)] are applied for simultaneous (1)H NMR spectroscopic determination of organic substances in complex mixtures. Among others, we studied constituents of the following matrices: honey, soft drinks, and liquids used in electronic cigarettes. Good quality spectral resolution of up to eight-component mixtures was achieved (correlation coefficients between resolved and experimental spectra were not less than 0.90). In general, the relative errors in the recovered concentrations were below 12%. SIMPLISMA and MILCA algorithms were found to be preferable for NMR spectra deconvolution and showed similar performance. The proposed method was used for analysis of authentic samples. The resolved ICA concentrations match well with the results of reference gas chromatography-mass spectrometry as well as the MCR-ALS algorithm used for comparison. ICA deconvolution considerably improves the application range of direct NMR spectroscopy for analysis of complex mixtures.

The intramolecular Diels-Alder reaction of diarylheptanoids--quantum chemical calculation of structural features favoring the formation of phenylphenalenones.

Diarylheptanoids have been reported as biosynthetic precursors of phenylphenalenones in plants. Quantum chemical calculations of molecular geometry and orbitals were used to elaborate which structural features are required to determine if diarylheptanoids can undergo an intramolecular Diel-Alder reaction to form phenylphenalenones. The computational data showed that an ortho-quinone- or a hydoxyketone-bearing ring A, containing the dienophile moiety, and a heptadiene chain with conjugated cisoid double bonds at C-4/C-6 and a saturated segment consisting of two sp3-carbon atoms, are required. Only four diarylheptanoids out of eighteen studied compounds proved to be suitable candidates. Among them are two 3,5-dideoxy compounds and two other compounds oxygenated only at C-3, suggesting that lachnanthocarpone, a representative of the 6-oxygenated phenylphenalenones, and anigorufone, a representative of the 6-deoxy phenylphenalenones, are not connected via a precursor-product relationship ("late reduction at C-6") but formed through partially separate pathways.

Multicomponent analysis of dietary supplements containing glucosamine and chondroitin: comparative low- and high-field NMR spectroscopic study.

With the prevalence of glucosamine- and chondroitin-containing dietary supplements for people with osteoarthritis in the marketplace, it is important to have an accurate and reproducible analytical method for the quantitation of these compounds in finished products. NMR spectroscopic method based both on low- (80 MHz) and high- (500-600 MHz) field NMR instrumentation was established, compared and validated for the determination of chondroitin sulfate and glucosamine in dietary supplements. The proposed method was applied for analysis of 20 different dietary supplements. In the majority of cases, quantification results obtained on the low-field NMR spectrometer are similar to those obtained with high-field 500-600 MHz NMR devices. Validation results in terms of accuracy, precision, reproducibility, limit of detection and recovery demonstrated that the developed method is fit for purpose for the marketed products. The NMR method was extended to the analysis of methylsulfonylmethane, adulterant maltodextrin, acetate and inorganic ions. Low-field NMR can be a quicker and cheaper alternative to more expensive high-field NMR measurements for quality control of the investigated dietary supplements. High-field NMR instrumentation can be more favorable for samples with complex composition due to better resolution, simultaneously giving the possibility of analysis of inorganic species such as potassium and chloride.

Rapid determination of coenzyme Q10 in food supplements using 1H NMR spectroscopy.

A methodology utilizing 1H NMR spectroscopy has been developed to measure the concentration of coenzyme Q10 (CoQ10) in dietary supplements. For sample preparation, a very simple dilution with deuterated chloroform and addition of internal standard is sufficient. CoQ10 produces a distinct peak of the CH groups in the isoprene side chain of the molecule in the δ 5.15 - 5.05 ppm range, where it can be distinguished from other matrix compounds. The method was shown to be of adequate sensitivity with a limit of detection (LOD) of 7.8 mg/L, to control the CoQ10 content in the majority of the products. The precision expressed as relative standard deviation was around 5 %; linearity was observed from 14 to 2000 mg/L (R = 0.99). The developed methodology was applied for the analysis of 21 food supplements (capsules, tablets, and liquid products). On the basis of the labeled amounts, only two products contained substantially lower concentrations of CoQ10 (57 % and 51 %). All other concentrations varied between 83 % and 190 % with respect to labeling. The developed NMR method may be used by quality assurance laboratories for routine control of CoQ10 products.