Low-field NMR for quality control on oils

Characterization of fatty acid forms using benchtop NMR in omega-3 oil supplements

Omega-3 fatty acid supplements, such as fish oil and plant-based oils, have gained popularity because of their potential health benefits. However, the quality and composition of these supplements can vary widely, particularly in terms of the two main forms of omega-3 fatty acids: triacylglycerols (TAGs) and ethyl esters (EEs). TAGs are the natural form found in fish oil but are prone to oxidation, whereas EEs are more stable but less well absorbed by the body. Differentiating between these forms is crucial for assessing the efficacy and tolerance of omega-3 supplements. This article describes a novel approach to differentiate between TAG and EE forms of omega-3 fatty acids in dietary supplements, utilizing a 60-MHz benchtop nuclear magnetic resonance (NMR) spectrometer. The proposed method using 1H and 1H-1H COSY NMR provides a quick and accurate approach to screen the forms of omega-3 fatty acids and evaluate their ratios. The presence of diacylglycerol (DAGs) in some supplements was also highlighted by this method and adds some information about the process used (i.e., esterification/enrichment). The affordability and user-friendliness of benchtop NMR equipment make this method feasible for food processing companies or quality control laboratories. In this study, 24 oil supplements were analyzed using NMR analysis in order to demonstrate the potential of this method for the differentiation of TAG and EE forms in omega-3 supplements.

Combined nuclear magnetic resonance methods in quality control of lubricants in green energy production

NMR methods were applied for lubricant analysis. Different factors influence the real aging of lubricants on diverse length scales and are captured by NMR. Chemical conversion of additives is addressed by NMR spectroscopy. High-field NMR experiments allow the identification and quantification of chemical components and are transferred to benchtop devices. Molecular dynamics and contaminations like fuel or abrasion are addressed via NMR relaxation and diffusion. Quality parameters were extracted via suitable data analysis of NMR raw data, which allow the detection of aging and indicate changes in the oil composition. At the same time, the methodology is optimized to the conditions in quality control. The feasibility is shown the example of a series of lubricants from applications in regenerative energy production, namely, wind turbine oils and biogas motor oils.

Chemical Analysis of an Isotopically Labeled Molecule Using Two-Dimensional NMR Spectroscopy at 34 μT

Low-field nuclear magnetic resonance (NMR) spectroscopy, conducted at or below a few millitesla, provides only limited spectral information due to its inability to resolve chemical shifts. Thus, chemical analysis based on this technique remains challenging. One potential solution to overcome this limitation is the use of isotopically labeled molecules. However, such compounds, particularly their use in two-dimensional (2D) NMR techniques, have rarely been studied. This study presents the results of both experimental and simulated correlation spectroscopy (COSY) on 1-13C-ethanol at 34.38 μT. The strong heteronuclear coupling in this molecule breaks the magnetic equivalence, causing all J-couplings, including homonuclear coupling, to split the 1H spectrum. The obtained COSY spectrum clearly shows the spectral details. Furthermore, we observed that homonuclear coupling between 1H spins generated cross-peaks only when the associated 1H spins were coupled to identical 13C spin states. Our findings demonstrate that a low-field 2D spectrum, even with a moderate spectral line width, can reveal the J-coupling networks of isotopically labeled molecules.

Quantitative comparison and rapid discrimination of Panax notoginseng powder and Caulis clematidis armandii using NMR combined with pattern recognition

BACKGROUND

The market demand for Panax notoginseng (P. notoginseng) is growing rapidly because of its useful properties in food and medicine. However, the frequent adulteration of P. notoginseng seriously affects the health of consumers and is a great challenge to food safety. In this study, low- and high-field nuclear magnetic resonance (LF/HF-NMR) were applied to detect the transverse relaxation distribution of P. notoginseng contaminated with different ratios of Caulis clematidis armandii (CCA) and the components in P. notoginseng and CCA, respectively.

RESULTS

Fifty-seven kinds of major and minor components in P. notoginseng and CCA were identified and quantified from their high-resolution NMR spectra, and there were significant differences in ginsenosides, sucrose, and glucose between P. notoginseng and CCA. Furthermore, the partial least squares regression analysis results indicated that LF-NMR parameters (T₂₁ and S₂₁ ) changed linearly as the ratio of CCA increased, and these changes were attributed to the variations in polysaccharide and sucrose in adulterated P. notoginseng.

CONCLUSION

In the relaxation time-based pattern recognition models, the authentic P. notoginseng powder could be classified with 100% accuracy from adulterated P. notoginseng when the adulteration ratio was greater than 30%, demonstrating the possibility of LF-NMR, in combination with pattern recognition, for rapid discrimination of food authenticity. © 2022 Society of Chemical Industry.

Mass spectrometry molecular fingerprinting of mineral and synthetic lubricant oils

The molecular composition of lubricating oils has a strong impact on how automotive engines function, but the techniques used to monitor the quality parameters of these oils only inspect their gross physical-chemical properties such as viscosity, color, and bulk spectroscopy profiles; hence, bad-quality, adulterated, or counterfeit oils are hard to detect. Herein, we investigated the ability of direct infusion electrospray ionization mass spectrometry (ESI-MS) to provide simple, rapid but characteristic fingerprint profiles for such oils of the mineral and synthetic types. After a simple aqueous extraction, ESI-MS analyses, particularly in the positive ion mode, did indeed show characteristic molecular markers with unique profiles, which were confirmed and more clearly visualized by partial least squares-discriminant analysis (PLS-DA). Nuclear magnetic resonance and Fourier transform infrared-attenuated total reflection spectroscopy were also tested for the bulk samples but showed nearly identical spectra, thus failing to reveal their distinct molecular composition and to differentiate the oil samples. To simulate adulteration, mixtures of mineral and synthetic oils were also analyzed by ESI(+)-MS, and additions as low as 1% of mineral oil to synthetic oil could be detected. The technique therefore offers a simple and fast but powerful tool to monitor the molecular composition of lubricant oils, particularly vias their more polar constituents.

Inline NMR via a Dedicated V-Shaped Sensor

Process monitoring and control require dedicated and reliable measures which reflect the status of the process under investigation. Although nuclear magnetic resonance is known to be a versatile analytical technique, it is only seldomly found in process monitoring. Single-sided nuclear magnetic resonance is one well known approach for being applied in process monitoring. The dedicated V-sensor is a recent approach that allows the inline investigation of materials in a pipe non-destructively and non-invasively. An open geometry of the radiofrequency unit is realized using a tailored coil, enabling the sensor to be applied for manifold mobile applications in in-line process monitoring. Stationary liquids were measured, and their properties were integrally quantified as the basis for successful process monitoring. The sensor, in its inline version, is presented along with its characteristics. An exemplary field of application is battery production in terms of anode slurries; thus, the first results on graphite slurries will demonstrate the added value of the sensor in process monitoring.

Semi-Autonomic AI LF-NMR Sensor for Industrial Prediction of Edible Oil Oxidation Status

The evaluation of an oil's oxidation status during industrial production is highly important for monitoring the oil's purity and nutritional value during production, transportation, storage, and cooking. The oil and food industry is seeking a real-time, non-destructive, rapid, robust, and low-cost sensor for nutritional oil's material characterization. Towards this goal, a ¹H LF-NMR relaxation sensor application based on the chemical and structural profiling of non-oxidized and oxidized oils was developed. This study dealt with a relatively large-scale oil oxidation database, which included crude data of a ¹H LF-NMR relaxation curve, and its reconstruction into T₁ and T₂ spectral fingerprints, self-diffusion coefficient D, and conventional standard chemical test results. This study used a convolutional neural network (CNN) that was trained to classify T₂ relaxation curves into three ordinal classes representing three different oil oxidation levels (non-oxidized, partial oxidation, and high level of oxidation). Supervised learning was used on the T₂ signals paired with the ground-truth labels of oxidation values as per conventional chemical lab oxidation tests. The test data results (not used for training) show a high classification accuracy (95%). The proposed AI method integrates a large training set, an LF-NMR sensor, and a machine learning program that meets the requirements of the oil and food industry and can be further developed for other applications.

1H LF-NMR Self-Diffusion Measurements for Rapid Monitoring of an Edible Oil's Food Quality with Respect to Its Oxidation Status

The food quality of edible oils is dependent on basic chemical and structural changes that can occur by oxidation during preparation and storage. A rapid and efficient analytical method of the different steps of oil oxidation is described using a time-domain nuclear magnetic resonance (TD-NMR) sensor for measuring signals related to the chemical and physical properties of the oil. The degree of thermal oxidation of edible oils at 80 °C was measured by the conventional methodologies of peroxide and aldehyde analysis. Intact non-modified samples of the same oils were more rapidly analyzed for oxidation using a TD-NMR sensor for 2D T₁-T₂ and self-diffusion (D) measurements. A good linear correlation between the D values and the conventional chemical analysis was achieved, with the highest correlation of R² = 0.8536 for the D vs. the aldehyde concentrations during the thermal oxidation of poly-unsaturated linseed oils, the oil most susceptible to oxidation. A good correlation between the D and aldehyde levels was also achieved for all the other oils. The possibility to simplify and minimize the time of oxidative analysis using the TD NMR sensors D values is discussed as an indicator of the oil’s oxidation quality, as a rapid and accurate methodology for the oil industry.

Homonuclear J-coupling spectroscopy using J-synchronized echo detection

In the strong coupling regime with J-coupling much larger than chemical shift differences, J-coupling spectroscopy enables spectral identification of molecules even when conventional NMR fails. While this classically required the presence of a heteronucleus, we recently showed that J-coupling spectra can be acquired in many homonuclear systems using spin-lock induced crossing (SLIC). Here, we present an alternative method using a spin echo train in lieu of a spin-locking SLIC pulse, which has a number of advantages. In particular, spin echo acquisition within the pulse train enables simultaneous collection of time and frequency data. The resulting 2D spectrum can be used to study dynamic spin evolution, and the time domain data can be averaged to create a 1D J-coupling spectrum with increased signal-to-noise ratio.

Time Domain (TD) Proton NMR Analysis of the Oxidative Safety and Quality of Lipid-Rich Foods

Food safety monitoring is highly important due to the generation of unhealthy components within many food products during harvesting, processing, storage, transportation and cooking. Current technologies for food safety analysis often require sample extraction and the modification of the complex chemical and morphological structures of foods, and are either time consuming, have insufficient component resolution or require costly and complex instrumentation. In addition to the detection of unhealthy chemical toxins and microbes, food safety needs further developments in (a) monitoring the optimal nutritional compositions in many different food categories and (b) minimizing the potential chemical changes of food components into unhealthy products at different stages from food production until digestion. Here, we review an efficient methodology for overcoming the present analytical limitations of monitoring a food's composition, with an emphasis on oxidized food components, such as polyunsaturated fatty acids, in complex structures, including food emulsions, using compact instruments for simple real-time analysis. An intelligent low-field proton NMR as a time domain (TD) NMR relaxation sensor technology for the monitoring of T₂ (spin-spin) and T₁ (spin-lattice) energy relaxation times is reviewed to support decision-making by producers, retailers and consumers in regard to food safety and nutritional value during production, shipping, storage and consumption.

Differentiation among dairy products by combination of fast field cycling NMR relaxometry data and chemometrics

A set of commercial milk and Sicilian cheeses was analysed by a combination of fast field cycling (FFC) nuclear magnetic resonance (NMR) relaxometry and chemometrics. The NMR dispersion (NMRD) curves were successfully analysed with a mathematical model applied on Parmigiano-Reggiano (PR) cheese. Regression parameters were led back to the molecular components of cheeses (water trapped in casein micelles, proteins and fats) and milk samples (water belonging to hydration shells around dispersed colloidal particles of different sizes and bulk water). The application of chemometric analysis on relaxometric data enabled differentiating milk from cheeses and revealing differences within the two sample groups of either cheeses or milk samples. Marked differences among cheeses were evidenced by statistical analysis of the sole quadrupolar peaks parameters, suggesting that these contain information on the nature of the milk used during cheese production. Hence, combination of FFC NMR and chemometrics represents a powerful tool to investigate alterations in dairy products.

Rapid Identification of Adulteration in Edible Vegetable Oils Based on Low-Field Nuclear Magnetic Resonance Relaxation Fingerprints

Most current approaches applied for the essential identification of adulteration in edible vegetable oils are of limited practical benefit because they require long analysis times, professional training, and costly instrumentation. The present work addresses this issue by developing a novel simple, accurate, and rapid identification approach based on the magnetic resonance relaxation fingerprints obtained from low-field nuclear magnetic resonance spectroscopy measurements of edible vegetable oils. The relaxation fingerprints obtained for six types of edible vegetable oil, including flaxseed oil, olive oil, soybean oil, corn oil, peanut oil, and sunflower oil, are demonstrated to have sufficiently unique characteristics to enable the identification of the individual types of oil in a sample. By using principal component analysis, three characteristic regions in the fingerprints were screened out to create a novel three-dimensional characteristic coordination system for oil discrimination and adulteration identification. Univariate analysis and partial least squares regression were used to successfully quantify the oil adulteration in adulterated binary oil samples, indicating the great potential of the present approach on both identification and quantification of edible oil adulteration.

Recent Applications of Benchtop Nuclear Magnetic Resonance Spectroscopy

Benchtop nuclear magnetic resonance (NMR) spectroscopy uses small permanent magnets to generate magnetic fields and therefore offers the advantages of operational simplicity and reasonable cost, presenting a viable alternative to high-field NMR spectroscopy. In particular, the use of benchtop NMR spectroscopy for rapid in-field analysis, e.g., for quality control or forensic science purposes, has attracted considerable attention. As benchtop NMR spectrometers are sufficiently compact to be operated in a fume hood, they can be efficiently used for real-time reaction and process monitoring. This review introduces the recent applications of benchtop NMR spectroscopy in diverse fields, including food science, pharmaceuticals, process and reaction monitoring, metabolomics, and polymer materials.

Dedicated NMR sensor to analyze relaxation and diffusion in liquids and its application to characterize lubricants

A dedicated nuclear magnetic resonance (NMR) sensor was designed for the analysis of liquids. The magnets are arranged in a V shape, creating a spatially dependent magnetic field in the gap. Measurements of samples with diverse diameters are possible underdefined magnetic field gradients at a given position. The magnet thus combines properties of single sided NMR with high static magnetic field gradients and classical time domain (TD) devices with lower to almost zero gradients. The sensor can easily be adapted to the requirements of the considered investigation; probes can be customized. On the example of lubricants and their aging, the added value and applicability of this sensor in quality control are highlighted in this publication. Relaxation and diffusion were measured by Carr-Purcell-Meiboom-Gill (CPMG) while varying the echo time τ_e and quantified via numerical modeling. Especially, relaxation shows a high sensitivity towards aging of lubricants such as particulate abrasion and changes in molecular dynamics induced, for example, by additive depletion. The applicability of this NMR sensor in quality control is demonstrated on the example of engine and transmission oils as well as of lubrication greases.

Homonuclear J-Coupling Spectroscopy at Low Magnetic Fields using Spin-Lock Induced Crossing*

Nuclear magnetic resonance (NMR) spectroscopy usually requires high magnetic fields to create spectral resolution among different proton species. Although proton signals can also be detected at low fields the spectrum exhibits a single line if J-coupling is stronger than chemical shift dispersion. In this work, we demonstrate that the spectra can nevertheless be acquired in this strong-coupling regime using a novel pulse sequence called spin-lock induced crossing (SLIC). This techniques probes energy level crossings induced by a weak spin-locking pulse and produces a unique J-coupling spectrum for most organic molecules. Unlike other forms of low-field J-coupling spectroscopy, our technique does not require the presence of heteronuclei and can be used for most compounds in their native state. We performed SLIC spectroscopy on a number of small molecules at 276 kHz and 20.8 MHZ and show that the simulated SLIC spectra agree well with measurements.

Multiphase Flow Regime Characterization and Liquid Flow Measurement Using Low-Field Magnetic Resonance Imaging

Multiphase flow metering with operationally robust, low-cost real-time systems that provide accuracy across a broad range of produced volumes and fluid properties, is a requirement across a range of process industries, particularly those concerning petroleum. Especially the wide variety of multiphase flow profiles that can be encountered in the field provides challenges in terms of metering accuracy. Recently, low-field magnetic resonance (MR) measurement technology has been introduced as a feasible solution for the petroleum industry. In this work, we study two phase air-water horizontal flows using MR technology. We show that low-field MR technology applied to multiphase flow has the capability to measure the instantaneous liquid holdup and liquid flow velocity using a constant gradient low flip angle CPMG (LFA-CPMG) pulse sequence. LFA-CPMG allows representative sampling of the correlations between liquid holdup and liquid flow velocity, which allows multiphase flow profiles to be characterized. Flow measurements based on this method allow liquid flow rate determination with an accuracy that is independent of the multiphase flow profile observed in horizontal pipe flow for a wide dynamic range in terms of the average gas and liquid flow rates.

Perspectives in process analytics using low field NMR

Low field NMR is a powerful analytical tool which creates an enormous added value in process analytics. Based on specific applications in process analytics and perspectives for low field NMR in form of spectroscopy, relaxation, diffusion, and imaging in quality control, diverse applications and technical realizations like spectrometers, time domain NMR, mobile NMR sensors and MRI will be discussed.

Low-field benchtop NMR spectroscopy: status and prospects in natural product analysis†

INTRODUCTION

Since a couple of years, low-field (LF) nuclear magnetic resonance (NMR) spectrometers (40-100 MHz) have re-entered the market. They are used for various purposes including analyses of natural products. Similar to high-field instruments (300-1200 MHz), modern LF instruments can measure multiple nuclei and record two-dimensional (2D) NMR spectra.

OBJECTIVE

To review the commercial availability as well as applications, advantages, limitations, and prospects of LF-NMR spectrometers for the purpose of natural products analysis.

METHOD

Commercial LF instruments were compared. A literature search was performed for articles using and discussing modern LF-NMR. Next, the articles relevant to natural products were read and summarised.

RESULTS

Seventy articles were reviewed. Most appeared in 2018 and 2019. Low costs and ease of operation are most often mentioned as reasons for using LF-NMR.

CONCLUSION

As the spectral resolution of LF instruments is limited, they are not used for structure elucidation of new natural products but rather applied for quality control (QC), forensics, food and health research, process control and teaching. Chemometric data handling is valuable. LF-NMR is a rapidly developing niche and new instruments keep being introduced.

High-Resolution Magic Angle Spinning (HR-MAS) NMR-Based Fingerprints Determination in the Medicinal Plant Berberis laurina

Berberis laurina (Berberidaceae) is a well-known medicinal plant used in traditional medicine since ancient times; however, it is scarcely studied to a large-scale fingerprint. This work presents a broad-range fingerprints determination through high-resolution magical angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy, a well-established flexible analytical method and one of most powerful "omics" platforms. It had been intended to describe a large range of chemical compositions in all plant parts. Beyond that, HR-MAS NMR allowed the direct investigation of botanical material (leaves, stems, and roots) in their natural, unaltered states, preventing molecular changes. The study revealed 17 metabolites, including caffeic acid, and berberine, a remarkable alkaloid from the genus Berberis L. The metabolic pattern changes of the leaves in the course of time were found to be seasonally dependent, probably due to the variability of seasonal and environmental trends. This metabolites overview is of great importance in understanding plant (bio)chemistry and mediating plant survival and is influenceable by interacting environmental means. Moreover, the study will be helpful in medicinal purposes, health sciences, crop evaluations, and genetic and biotechnological research.