1H Nuclear Magnetic Resonance Relaxometry and Magnetic Resonance Imaging and Applications in Food Science and Processing

Quantitative characterization of the crosslinking degree of hydroxypropyl guar gum fracturing fluid by low-field NMR

As a widely used water-based fracturing fluid, the performance of hydroxypropyl guar gum fracturing fluid is closely related to the degree of crosslinking, the quantitative characterization of which can reveal a detailed crosslinking mechanism and guide the preparation of fracturing fluid gels with an excellent performance. However, the commonly used high-temperature rheology method for evaluating the performance of fracturing fluids only qualitatively reflects the degree of crosslinking. In this study, low-field nuclear magnetic resonance (LF-NMR) was used to characterize the degree of crosslinking in guar gum fracturing fluid gels. The spin-spin relaxation time of the H proton in guar gum was molecularly analyzed using LF-NMR. The viscoelastic properties met the requirements when the crosslinking degree of the gel was 88-94 %. The transformation of the linear structure into a membrane structure during the crosslinking process of the guar gum fracturing fluid was confirmed by freeze-drying and scanning electron microscopy (SEM) from a microscopic perspective. The changing trend of the microstructure and viscoelastic properties of the fracturing fluid gel under different crosslinker dosages was consistent with changes in the degree of crosslinking. The LF-NMR test process is non-destructive to the gel structure, and the test results demonstrate good accuracy and repeatability.

Intelligent Rapid Detection Techniques for Low-Content Components in Fruits and Vegetables: A Comprehensive Review

Fruits and vegetables are an important part of our daily diet and contain low-content components that are crucial for our health. Detecting these components accurately is of paramount significance. However, traditional detection methods face challenges such as complex sample processing, slow detection speed, and the need for highly skilled operators. These limitations fail to meet the growing demand for intelligent and rapid detection of low-content components in fruits and vegetables. In recent years, significant progress has been made in intelligent rapid detection technology, particularly in detecting high-content components in fruits and vegetables. However, the accurate detection of low-content components remains a challenge and has gained considerable attention in current research. This review paper aims to explore and analyze several intelligent rapid detection techniques that have been extensively studied for this purpose. These techniques include near-infrared spectroscopy, Raman spectroscopy, laser-induced breakdown spectroscopy, and terahertz spectroscopy, among others. This paper provides detailed reports and analyses of the application of these methods in detecting low-content components. Furthermore, it offers a prospective exploration of their future development in this field. The goal is to contribute to the enhancement and widespread adoption of technology for detecting low-content components in fruits and vegetables. It is expected that this review will serve as a valuable reference for researchers and practitioners in this area.

Anthracene and tetraphenylsilane based conjugated porous polymer nanoparticles for sensitive detection of nitroaromatics in water

Conjugated porous polymers (CPPs) are a kind of promising sensing materials for the detection of nitroaromatic compounds, but their sensing applications in aqueous media are limited because of their poor dispersity or solubility in water. In this study, we prepared anthracene and tetraphenylsilane based CPPs named PSiAn by conventional Suzuki coupling and Suzuki-miniemulsion polymerization, respectively. The structure, morphology and porosity of the CPPs were characterized by Fourier Transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance (1H NMR), transmission electron microscope (TEM) and N2 sorption isotherm, respectively. Both of the CPPs have porous structure which is beneficial for the adsorption and diffusion of the analytes within them. The particle size of PSiAn nanoparticles prepared by Suzuki-miniemulsion polymerization is 10-40 nm from the TEM image, which facilitates the dispersion in the aqueous phase. Combined with the porosity and nanoparticle morphology, PSiAn nanoparticles realized the efficient photoluminescence (PL) sensing of nitroaromatic explosives in aqueous phase. The limit of detection (LOD) and limit of quantitation (LOQ) of PSiAn nanoparticles for 2,4,6-trinitrophenol (TNP) detection in the pure aqueous phase are 0.33 μM and 1.11 μM, respectively. Meanwhile, the good selectivity and anti-interference in presence of other nitro-compounds were observed. Furthermore, the spike/recovery test for the TNP detection in real water samples by PL sensing based on PSiAn nanoparticles indicates the quantitative recovery of TNP from 100.74 % to 101.00 %. The electrochemical test, ultraviolet-visible absorption spectra, excitation and emission spectra, and time-resolved PL spectra were investigated to explore the PL sensing mechanism. As a result, it is found that the fluorescence inner filter effect might be the predominant quenching mechanism during the detection of nitrophenolic compounds such as TNP and 4-nitrophenol (4-NP).

Study on the Quality Variation and Internal Mechanisms of Frozen Oatmeal Cooked Noodles during Freeze-Thaw Cycles

Frozen staple food, attributed to its favorable taste and convenience, has a promising development potential in the future. Frequent freezing and thawing, however, will affect its quality. This study simulated several freeze-thaw cycles (FTC) that may occur during the cold chain process of frozen oatmeal cooked noodles (FOCN) production to consumption. The quality changes and their mechanisms were elucidated using methods such as differential scanning calorimetry (DSC), low-field nuclear magnetic resonance (LF-NMR), Fourier-transform infrared spectroscopy (FTIR), confocal laser scanning microscopy (CLSM), texture analysis, and sensory evaluation. The freezable water content of the FOCN decreased because of the FTC treatment, and the relative content of total water in FOCN also decreased accordingly. The increase in β-Turn after FTC induced disorder in the secondary structure of proteins, causing the protein microstructure to become loose and discontinuous, which in turn reduced the water-holding capacity of FOCN. Additionally, FTC reduced the chewiness and sensory score of FOCN. This research will contribute a theoretical foundation for optimizing the cold chain process.

Flavor enhancement during the drying of scallop (Patinopecten yessoensis) as revealed by integrated metabolomic and lipidomic analysis

Dried scallops are a typical shellfish commodity, but the molecular change mechanism in the drying process is not clear. In this paper, the effect of drying on the flavor of scallops was revealed by integrated metabolomic and lipidomic analysis. The results showed that 70 °C was the best temperature for hot air drying, and the moisture content of the scallops was less than 20% after 12 h of drying, which meets the commercial standards for dried scallops. A total of 53 volatile compounds were detected in dried scallops, of which 2,5-dimethyl pyrazine and tetramethyl pyrazine, as characteristic flavor compounds, changed significantly during drying. In addition, taste peptides such as Arg-Gly and Gly-Gly, produced by protein degradation during drying, may contribute to the umami perception of dried scallops. This study helped to increase the overall quality of dried scallops.

Observation and Measurement of Ice Morphology in Foods: A Review

Freezing is an effective technology with which to maintain food quality. However, the formation of ice crystals during this process can cause damage to the cellular structure, leading to food deterioration. A good understanding of the relationship between food microstructure and ice morphology, as well as the ability to effectively measure and control ice crystals, is very useful to achieve high-quality frozen foods. Hence, a brief discussion is presented on the fundamentals/principles of optical microscopic techniques (light microscopy), electronic microscopic techniques (transmission electron microscopy (TEM) and scanning electron microscopy (SEM)), as well as other non-invasive techniques (X-rays, spectroscopy, and magnetic resonance) and their application to measuring ice formation rates and characterizing ice crystals, providing insight into the freezing mechanisms as well as direct monitoring of the entire process. And, in addition, this review compares (the negative and positive aspects of) the use of simple and cheap but destructive technologies (optical microscopy) with detailed microscopic technologies at the micro/nanometer scale but with pretreatments that alter the original sample (SEM and TEM), and non-destructive technologies that do not require sample preparation but which have high acquisition and operational costs. Also included are images and examples which demonstrate how useful an analysis using these techniques can be.

Evaluation of multicomplex systems on pomegranate concentrate loaded alginate hydrogels by low-field NMR relaxometry: physicochemical characterization and controlled release study

Alginate (ALG) and various gums are potential biomaterials to be employed in hydrogel designs for both food and biomedical applications. This study evaluated a multicomplex design by combining food grade polymers to examine their polymer-polymer interactions and design an oral delivery system for pomegranate concentrate (PC). ALG was replaced with gum tragacanth (GT), xanthan (XN) and their equal combinations (GT:XN) at 50% ratio in hydrogel fabrication. In addition to CaCI2 in binding solution, honey (H) and chitosan (CH) were also used during physical crosslinking. Relaxation time constants in NMR indicated poor ability of GT for water entrapment especially in the presence of honey (S2H). They also confirmed FTIR results indicating similar trends. Strong negative correlations were observed between T2 and texture results. GT replacement of ALG especially in the use of single CaCI2 (S2) promoted higher PC release up to 80% in digestive media compared to XN substitution (S3). This study promoted use of LF NMR as an indicator for polymer mixture characterization in complex gels. ALG based gels could be modified by replacing ALG with different kinds of gums and with use of different binding solutions to regulate target compound release in food and pharmaceutical fields.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-023-05730-2.

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.

Rapid and Simultaneous Measurement of Fat and Moisture Contents in Pork by Low-Field Nuclear Magnetic Resonance

In order to improve the efficiency of Soxhlet extraction and oven drying, low-field nuclear magnetic resonance (LF-NMR) technology was used to detect fat and moisture contents in pork. The transverse relaxation time (T2) distribution curves were constructed by Carr−Purcell−Meiboom−Gill (CPMG) experiments. In addition, the optimal conditions of adding MnCl2 aqueous solution was explored to separate water and fat signal peaks. Finally, the reliability of this method for the determination of fat and moisture contents in pork was verified. The present study showed that adding 1.5 mL of 20% MnCl2 aqueous solution solution at 50 °C can isolate and obtain a stable peak of fat. The lard and 0.85% MnCl2 aqueous solution were used as the standards for fat and moisture measurements, respectively, and calibration curves with R2 = 0.9999 were obtained. In addition, the repeatability and reproducibility of this method were 1.71~3.10%. There was a significant correlation (p < 0.05) between the LF-NMR method and the conventional methods (Soxhlet extraction and oven drying), and the R2 was 0.9987 and 0.9207 for fat and moisture, respectively. All the results proved that LF-NMR could determine fat and moisture contents in pork rapidly and simultaneously.

Span of regularization for solution of inverse problems with application to magnetic resonance relaxometry of the brain

We present a new regularization method for the solution of the Fredholm integral equation (FIE) of the first kind, in which we incorporate solutions corresponding to a range of Tikhonov regularizers into the end result. This method identifies solutions within a much larger function space, spanned by this set of regularized solutions, than is available to conventional regularization methods. An additional key development is the use of dictionary functions derived from noise-corrupted inversion of the discretized FIE. In effect, we combine the stability of solutions with greater degrees of regularization with the resolution of those that are less regularized. The span of regularizations (SpanReg) method may be widely applicable throughout the field of inverse problems.

The use of time domain 1 H NMR to study proton dynamics in starch-rich foods: A review

Starch is a major contributor to the carbohydrate portion of our diet. When it is present with water, it undergoes several transformations during heating and/or cooling making it an essential structure-forming component in starch-rich food systems (e.g., bread and cake). Time domain proton nuclear magnetic resonance (TD ¹ H NMR) is a useful technique to study starch-water interactions by evaluation of molecular mobility and water distribution. The data obtained correspond to changes in starch structure and the state of water during or resulting from processing. When this technique was first applied to starch(-rich) foods, significant challenges were encountered during data interpretation of complex food systems (e.g., cake or biscuit) due to the presence of multiple constituents (proteins, carbohydrates, lipids, etc.). This article discusses the principles of TD ¹ H NMR and the tools applied that improved characterization and interpretation of TD NMR data. More in particular, the major differences in proton distribution of various dough and cooked/baked food systems are examined. The application of variable-temperature TD ¹ H NMR is also discussed as it demonstrates exceptional ability to elucidate the molecular dynamics of starch transitions (e.g., gelatinization, gelation) in dough/batter systems during heating/cooling. In conclusion, TD NMR is considered a valuable tool to understand the behavior of starch and water that relate to the characteristics and/or quality of starchy food products. Such insights are crucial for food product optimization and development in response to the needs of the food industry.

Non-Conventional Time Domain (TD)-NMR Approaches for Food Quality: Case of Gelatin-Based Candies as a Model Food

The TD-NMR technique mostly involves the use of T1 (spin-lattice) and T2 (spin-spin) relaxation times to explain the changes occurring in food systems. However, these relaxation times are affected by many factors and might not always be the best indicators to work with in food-related TD-NMR studies. In this study, the non-conventional TD-NMR approaches of Solid Echo (SE)/Magic Sandwich Echo (MSE) and Spin Diffusion in food systems were used for the first time. Soft confectionary gelatin gels were formulated and conventional (T1) and non-conventional (SE, MSE and Spin Diffusion) TD-NMR experiments were performed. Corn syrups with different glucose/fructose compositions were used to prepare the soft candies. Hardness, °Brix (°Bx), and water activity (aw) measurements were also conducted complementary to NMR experiments. Relaxation times changed (p < 0.05) with respect to syrup type with no obvious trend. SE/MSE experiments were performed to calculate the crystallinity of the samples. Samples prepared with fructose had the lowest crystallinity values (p < 0.05). Spin Diffusion experiments were performed by using Goldman−Shen pulse sequence and the interface thickness (d) was calculated. Interface thickness values showed a wide range of variation (p < 0.05). Results showed that non-conventional NMR approaches had high potential to be utilized in food systems for quality control purposes.

Effects of drying strategies on sporulation and titer of microbial ecological agents with Bacillus subtilis

Drying operation is beneficial to the preservation and transportation of microbial ecological agents. In this study, drying kinetics and water distribution variations in solid biomass medium during hot air drying (HAD) and vacuum freeze drying (VFD) were systematically investigated. Meanwhile, the effects of different drying strategies on the sporulation of Bacillus subtilis and the titer of microbial ecological agents were compared. The results showed that both HAD and VFD induced rapid water removal from the solid biomass medium. VFD retained bound water and maintained the porous structure of the solid medium. Both HAD and VFD induced sporulation. The expression level of sporulation-regulatory genes spo0A, sigF, and sigE followed the order 80°C-HAD > 60°C-HAD > VFD. The spore number in the medium after 80°C-HAD drying for 6 h was 0.72 × 10¹⁰/g dry medium, which was 9.1 and 12.5% larger than that of the medium with 60°C-HAD and VFD, respectively. Therefore, 80°C-HAD is an effective drying strategy for promoting sporulation, which improves the titer of microbial ecological agents with B. subtilis.

Non-Invasive Method to Predict the Composition of Requeijão Cremoso Directly in Commercial Packages Using Time Domain NMR Relaxometry and Chemometrics

Low Field Time-Domain Nuclear Magnetic Resonance (TD-NMR) relaxometry was used to determine moisture, fat, and defatted dry matter contents in “requeijão cremoso” (RC) processed cheese directly in commercial packaged (plastic cups or tubes with approximately 200 g). Forty-five samples of commercial RC types (traditional, light, lactose-free, vegan, and fiber) were analyzed using longitudinal (T₁) and transverse (T₂) relaxation measurements in a wide bore Halbach magnet (0.23 T) with a 100 mm probe. The T₁ and T₂ analyses were performed using CWFP-T₁ (Continuous Wave Free Precession) and CPMG (Carr-Purcell-Meiboom-Gill) single shot pulses. The scores of the principal component analysis (PCA) of CWFP-T₁ and CPMG signals did not show clustering related to the RC types. Optimization by variable selection was carried out with ordered predictors selection (OPS), providing simpler and predictive partial least squares (PLS) calibration models. The best results were obtained with CWFP-T₁ data, with root-mean-square errors of prediction (RMSEP) of 1.38, 4.71, 3.28, and 3.00% for defatted dry mass, fat in the dry and wet matter, and moisture, respectively. Therefore, CWFP-T₁ data modeled with chemometrics can be a fast method to monitor the quality of RC directly in commercial packages.

Parameter Visualization of Benchtop Nuclear Magnetic Resonance Spectra toward Food Process Monitoring

Low-cost and user-friendly benchtop low-field nuclear magnetic resonance (NMR) spectrometers are typically used to monitor food processes in the food industry. Because of excessive spectral overlap, it is difficult to characterize food mixtures using low-field NMR spectroscopy. In addition, for standard compounds, low-field benchtop NMR data are typically unavailable compared to high-field NMR data, which have been accumulated and are reusable in public databases. This work focused on NMR parameter visualization of the chemical structure and mobility of mixtures and the use of high-field NMR data to analyze benchtop NMR data to characterize food process samples. We developed a tool to easily process benchtop NMR data and obtain chemical shifts and T2 relaxation times of peaks, as well as transform high-field NMR data into low-field NMR data. Line broadening and time–frequency analysis methods were adopted for data processing. This tool can visualize NMR parameters to characterize changes in the components and mobilities of food process samples using benchtop NMR data. In addition, assignment errors were smaller when the spectra of standard compounds were identified by transferring the high-field NMR data to low-field NMR data rather than directly using experimentally obtained low-field NMR spectra.

LF-NMR/MRI Determination of Different 6-Benzylaminopurine Concentrations and Their Effects on Soybean Moisture

In this study, we aimed to clarify the distribution and dynamics of water in the Xudou 20 soybean cultivar post-germination after culturing plants with various concentrations of 6-benzylaminopurine (6-BA). Low-field nuclear magnetic resonance and magnetic resonance imaging (LF-NMR/MRI), as well as principal component analysis (PCA), were used for the investigation. Results showed that low concentrations of 6-BA promoted soybean germination and high concentrations inhibited soybean germination, with 5 mg/l of 6-BA producing the most optimal conditions for growth. Moreover, the T ₂₂ determination of weakly bound water increased with increasing 6-BA concentration, and the PCA effectively distinguished soybeans cultured at different 6-BA concentrations. This study provides a method for the rapid detection of 6-BA concentration in bean sprouts and provides theoretical support and bean sprout quality assessment.

Investigation of the Hydration Behavior of Different Sugars by Time Domain-NMR

The hydration behavior of sugars varies from each other and examining the underlying mechanism is challenging. In this study, the hydration behavior of glucose, fructose, allulose (aka rare sugar), and sucrose have been explored using different Time Domain Nuclear Magnetic Resonance (TD-NMR) approaches (relaxation times, self-diffusion, and Magic Sandwich Echo (MSE)). For that purpose, the effects of different sugar concentrations (2.5%, 5%, 10%, 15%, 20%, 30%, and 40%) (w/v) and hydration at different times for 1 day were investigated by T₂ relaxation times and self-diffusion coefficients. Crystallinity values of the solid and hydrated sugars were also determined with MSE. Change in T₂ relaxation times with concentration showed that the fastest binding with water (parallel with the shortest T₂ values) was observed for sucrose for all concentrations followed by glucose, fructose, and allulose. Furthermore, dependency of T₂ relaxation times with hydration time showed that sucrose was the fastest in binding with water followed by glucose, fructose, and allulose. The study showed that allulose, one of the most famous rare sugars that is known to be a natural low-calorie sugar alternative, had the lowest interaction with water than the other sugars. TD-NMR was suggested as a practical, quick, and accurate technique to determine the hydration behavior of sugars.

Water and lipid migration in salted duck eggs during storage with different packaging conditions as studied using LF-NMR and MRI techniques

Herein, the water and lipid migration of salted duck eggs during storage were systematically explored in three different packaging conditions of long-term salting, no packaging, and vacuum packaging. Bound water, multilayer bound water, lipid, and bulk water were observed in the whole duck egg by low-field nuclear magnetic resonance (LF-NMR) relaxation. Five weeks of salting process led to the redistribution of water and lipid due to the watery state of egg white and the gelation of egg yolk due to the permeation of salt, and boiling mainly caused an obvious decrease in the mobility of bulk water due to the gelation of egg white. Among these three conditions, long-term salting with 6 months storage caused the most serious redistribution of water and lipid as well as the rupture of the vitelline membrane, but could prevent the oxidation of egg yolk. Vacuum packaging had the least influence on the water and lipid distribution, mass change, and water content but led to lipid oxidation with high degree in egg yolk. However, the most obvious mass loss was observed in the salted duck eggs during the storage without packaging. In addition, principal component analysis of Carr-Purcell-Meiboom-Gill data suggested that LF-NMR could distinguish the salted duck eggs with different storage times during the early stage of the storage. Practical Application Water and lipid migration of salted duck eggs during storage with three packaging conditions were explored by using low-field nuclear magnetic resonance and magnetic resonance imaging. Understanding the impacts of packaging conditions on water and lipid migration of salted duck eggs during storage could provide a new method for the quality identification.

Stabilization of parameter estimates from multiexponential decay through extension into higher dimensions

Analysis of multiexponential decay has remained a topic of active research for over 200 years. This attests to the widespread importance of this problem and to the profound difficulties in characterizing the underlying monoexponential decays. Here, we demonstrate the fundamental improvement in stability and conditioning of this classic problem through extension to a second dimension; we present statistical analysis, Monte-Carlo simulations, and experimental magnetic resonance relaxometry data to support this remarkable fact. Our results are readily generalizable to higher dimensions and provide a potential means of circumventing conventional limits on multiexponential parameter estimation.

Evaluation of processing mechanism in Astragali Radix by low-field nuclear magnetic resonance and magnetic resonance imaging

Astragali Radix (Huangqi) is an important herb medicine that is always processed into pieces for clinical use. Many operations need to be performed before use, among which drying of Astragali Radix (AR) pieces is a key step. Unfortunately, research on its drying mechanism is still limited. Low-field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI) techniques were applied to study the moisture state and distribution during drying. The content of bioactive components and texture changes were measured by HPLC and texture analyzer, respectively. The moisture content of the AR pieces decreased significantly during drying, and the time to reach the drying equilibrium were different at different temperatures. The time when at 70°C, 80°C, and 90°C reach complete drying are 180 min, 150 min and 120 min, respectively. 80°C was determined as the optimum drying temperature, and it was observed that the four flavonoids and astragaloside IV have some thermal stability in AR pieces. When dried at 80°C, although the total water content decreased, the free water content decreased from 99.38% to 15.49%, in contrast to the increase in bound water content from 0.62% to 84.51%. The texture parameters such as hardness changed to some extent, with the hardness rising most significantly from 686.23 g to 2656.67 g. Correlation analysis revealed some connection between moisture content and LF-NMR and texture analyzer parameters, but the springiness did not show a clear correlation with most parameters. This study shows that HPLC, LF-NMR, MRI, and texture analyzers provide a scientific basis for elucidating the drying principles of AR pieces. The method is useful and shows potential for extension and application; therefore, it can be easily extended to other natural herb medicines.

Changes in Physicochemical Properties and Qualities of Red Brown Rice at Different Storage Temperatures

The effects of storage temperature on the physicochemical properties and qualities of red brown rice were investigated in this study. The samples were vacuum-packed in nylon/polyethylene pouches and stored at 15 °C, 25 °C and 35 °C for 12 weeks. The moisture content decreased as storage time was prolonged. Rice stored at 15 °C and 25 °C had a lower falling range of water content compared to the samples stored at 35 °C. Free fatty acid values increased fastest when samples were stored at a high temperature, and the rise can be effectively delayed at low temperatures. The pH of residual cooking water and adhesiveness decreased, while the heating water absorption rate and hardness increased during storage for red and brown rice. Low-field nuclear magnetic resonance results indicate that water molecules migrated, the binding force of H protons became stronger and the bonds between molecules became closer with increased storage duration. Temperature had an obvious correlation with starch granules and protein structure, characterized by a scanning electron microscope and Fourier transform infrared spectroscopy. Low temperatures significantly retarded those changes. The results indicate that storage temperature is a vital factor affecting the physicochemical properties and qualities of red brown rice and provided reference and theoretical basis for the actual storage of red brown rice.

Detection of Authenticity and Quality of the Turkish Delights (Lokum) by Means of Conventional and Fast Field Cycling Nuclear Magnetic Resonance Relaxometry

Turkish delights (lokum) are traditional confectionery products that contain mainly sucrose as the sugar source and starch as the gelling agent. However, manufacturers sometimes might prefer to use corn syrup instead of sucrose to decrease the cost. This jeopardizes the originality of Turkish delights and leads to production of adulterated samples. In this study, Turkish delights were formulated using sucrose (original sample) and different types of corn syrups (SBF10, SCG40, and SCG60). Results clearly indicated that corn-syrup-containing samples had improved textural properties and were less prone to crystallization. However, this case affected authenticity of the products negatively. Both time domain nuclear magnetic resonance (TD NMR) and fast field cycling nuclear magnetic resonance (FFC NMR) techniques were found to be effective to discriminate the original samples from the corn-syrup-containing samples. In addition, quantitative analysis of FFC NMR showed that, apart from the rotational motions, molecules in Turkish delights (mainly water and also sugar molecules) undergo two types of translational dynamics.

Water Dynamics in Whey-Protein-Based Composite Hydrogels by Means of NMR Relaxometry

Whey-protein-isolate-based composite hydrogels with encapsulated black carrot (Daucus carota) extract were prepared by heat-induced gelation. The hydrogels were blended with gum tragacanth, pectin and xanthan gum polysaccharides for modulating their properties. 1H spin-lattice relaxation experiments were performed in a broad frequency range, from 4 kHz to 30 MHz, to obtain insight into the influence of the different polysaccharides and of the presence of black carrot on dynamical properties of water molecules in the hydrogel network. The 1H spin-lattice relaxation data were decomposed into relaxation contributions associated with confined and free water fractions. The population of the confined water fraction and the value of the translation diffusion coefficient of water molecules in the vicinity of the macromolecular network were quantitatively determined on the basis of the relaxation data. Moreover, it was demonstrated that the translation diffusion is highly anisotropic (two-dimensional, 2D).

Effect of pre-frying on distribution of protons and physicochemical qualities of mackerel

BACKGROUND

In this work, low-field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging were used to investigate the changes in protons (from water and oil) distribution of mackerel during the frying process. The relationship between proton migration and some physicochemical indexes was established by partial least squares regression (PLSR). The changing mechanism of the quality characteristics and physicochemical properties of fish meat under different frying conditions was analysed by LF-NMR combined with PLSR, which provided theoretical support for the development of canned mackerel food.

RESULTS

LF-NMR results showed that three kinds of T₂ protons assigned to protein-water interaction (T₂₁ ), multilayer bound water (T₂₂ ), oil and free water (T₂₃ ), respectively. As the frying temperature increased, protons from the T₂₂ peak significantly decreased, while protons from the T₂₃ peak remarkably increased. The microstructure of fried mackerel was destroyed; cooking loss, oil content, a* value, b* value, hardness and chewiness increased; and the protein content and L* value decreased. Furthermore, PLSR analysis revealed that significant correlation was observed between the cooking loss, TPA parameter (chewiness), colour parameter (L*) and LF-NMR parameters.

CONCLUSION

Different frying temperatures and times had a strong effect on the physicochemical properties of mackerel. Good prediction models could be established by proton migration using the LF-NMR technique and PLSR for fried mackerel. Quality control of fried fish could be realized by monitoring the change in LF-NMR data. © 2021 Society of Chemical Industry.

A One-Dimensional U-Net-Based Calibration-Transfer Method for Low-Field Nuclear Magnetic Resonance Signals

The reconstruction of the statistical analysis model of an instrument is a time-consuming and expensive process. Herein, the feasibility of spectral model calibration-transfer application to the same type of low-field nuclear magnetic resonance (LF-NMR) instrument was investigated using a one-dimensional U-net (1D U-net). Unlike conventional calibration-transfer algorithms such as direct standardization (DS), the 1D U-net network can reduce the error between the master and slave instruments through iterative cycles. The calibration-transfer ability was verified; three experiments that entailed the use of edible oil and copper sulfate (CuSO₄) samples were implemented. The analysis of the spectral responses and feature analysis of the edible oil samples revealed that the signal of the slave instrument calibrated using the 1D U-net most resembled the signal of the master instrument, and its relative residual value was reduced to 0.0045. Further analysis of the CuSO₄ concentration prediction showed that on the support vector regression (SVR) model constructed using the master instrument, the signal of the slave instrument calibrated by the 1D U-net was more similar to the response of the master instrument, and its root mean square error (RMSE) was only 0.01606 mmol/L. Thus, 1D U-net is a viable candidate for calibration-transfer applications to LF-NMR instruments.

Quality Characteristics and Moisture Mobility of Giant Salamander (Andrias davidianus) Jerky during Roasting Process

Quality attributes and water mobility of giant salamander jerkies (GSJs) during roasting process (160°C, for 0, 20, 40, 60, and 80 min) were investigated. The results showed that $a^{\ast },b^{\ast }$ values and shear force increased of GSJs roasting from 20 to 80 min, while $L^{\ast }$ , yield, and moisture content decreased significantly ( $p<0.05$ ). Sensory assessment showed that GSJs at a roasting time of 40–60 min had higher scores. GSJs contained great amount of healthy unsaturated fatty acids (including DHA and EPA), and the total amino acids and essential amino acids were among 59.33–71.77 g·100 g−1 and 25.94–31.40 g·100 g−1, respectively. The mobility of the immobilized moisture and free moisture were shrunk dramatically during roasting. The proton density weighted images also exhibited the moisture shrinkage during roasting. In addition, T22 and T23 were positively correlated with MRI signal, moisture content, and yield of GSJs, but negatively correlated with shear force and overall acceptability, respectively. Thus, in view of various quality attributes and sensory evaluation, a roasting time of 40–60 min was favored for nutritive GSJs production. LF-NMR and MRI might be employed to profile the quality characteristics during roasting as a rapid and nondestructive analytical tool.

Rapid screening for hazelnut oil and high-oleic sunflower oil in extra virgin olive oil using low-field nuclear magnetic resonance relaxometry and machine learning

BACKGROUND

As extra virgin olive oil (EVOO) has high commercial value, it is routinely adulterated with other oils. The present study investigated the feasibility of rapidly identifying adulterated EVOO using low-field nuclear magnetic resonance (LF-NMR) relaxometry and machine learning approaches (decision tree, K-nearest neighbor, linear discriminant analysis, support vector machines and convolutional neural network (CNN)).

RESULTS

LF-NMR spectroscopy effectively distinguished pure EVOO from that which was adulterated with hazelnut oil (HO) and high-oleic sunflower oil (HOSO). The applied CNN algorithm had an accuracy of 89.29%, a precision of 81.25% and a recall of 81.25%, and enabled the rapid (2 min) discrimination of pure EVOO that was adulterated with HO and HOSO in the volumetric ratio range of 10-100%.

CONCLUSIONS

LF-NMR coupled with the CNN algorithm is a viable candidate for rapid EVOO authentication. © 2020 Society of Chemical Industry.

Applications of Non-invasive and Novel Methods of Low-Field Nuclear Magnetic Resonance and Magnetic Resonance Imaging in Aquatic Products

Aquatic products, such as fish, are popular throughout the world due to their satisfying flavor characteristics as well as rich animal nutrition, and they provide high-value food therapy, but they are easily oxidized and spoiled. It is necessary to detect aquatic products through rapid and accurate technology. Low-field nuclear magnetic resonance (LF-NMR) and magnetic resonance imaging (MRI) have been widely used in the aquatic product industry due to their sensitivity, fast analysis, non-destructive nature and low cost. The applications of LF-NMR in the measurement of aquatic product quality and nutrients (water, fat, and protein) are summarized in this paper. Applications in aquatic products have been shown to depend on deep processing, storage and authentication. This review discusses the application of MRI technology in the quality control of aquatic products. Therefore, this review will guide the application of the aquatic products industry and aims to supply the reader with both the theory of the method and practical applications of the method for use as a rapid and non-destructive technology in scientific research and the industrial industry.

Improvement strategies of food supply chain through novel food processing technologies during COVID-19 pandemic

Coronavirus disease-19 (COVID-19) is a contagious disease caused by a novel corona virus (SARS-CoV-2). No medical intervention has yet succeeded, though vaccine success is expected soon. However, it may take months or years to reach the vaccine to the whole population of the world. Therefore, the technological preparedness is worth to discuss for the smooth running of food processing activities. We have explained the impact of the COVID-19 pandemic on the food supply chain (FSC) and then discussed the technological interventions to overcome these impacts. The novel and smart technologies during food processing to minimize human-to-human and human-to-food contact were compiled. The potential virus-decontamination technologies were also discussed. Finally, we concluded that these technologies would make food processing activities smarter, which would ultimately help to run the FSC smoothly during COVID-19 pandemic.