Proton Low Field NMR Relaxation Time Domain Sensor for Monitoring of Oxidation Stability of PUFA-Rich Oils and Emulsion Products

Unraveling the role of probiotics in affecting the structure of monoglyceride gelled emulsions: A low-field 1H NMR study

The capacity of monoglyceride (MG) gelled emulsions (MEs) in protecting probiotic cells of Lacticaseibacillus rhamnosus against stresses suffered during food processing, storage, and human digestion has been recently demonstrated. These findings open new perspectives on the possible participation of probiotics in the stabilization of emulsion structure. To unravel this aspect, rheological analysis and Low-Field 1H NMR investigations were performed on MEs having different aqueous phases (water or skimmed milk) and stored for increasing time (1 and 14 days) at 4 °C. Loaded and unloaded samples were considered. Results highlighted that probiotics initially hindered the ability of MG to self-assemble in the multiphase environment, interacting in some way with MG crystalline lamellar structure, as confirmed by rheological and 1H NMR analysis. During storage, an increase of proton compartmentation was observed in loaded MEs indicating the role of probiotics in stabilizing MG structure at a molecular level. Such a result was more evident when the system was composed of milk, suggesting that the presence of milk-native components (i.e., lactose, proteins, and minerals) favored the cell-structure interactions. Such preliminary results could open new perspectives in considering probiotic cells as having an active role in the stabilization of food structure.

Microwaved-Assisted Synthesis of Starch-Based Biopolymer Membranes for Novel Green Electrochemical Energy Storage Devices

The investigated starch biopolymer membrane was found to be a sustainable alternative to currently reported and used separators due to its properties, which were evaluated using physicochemical characterization. The molecular dynamics of the biomembrane were analyzed using low-field nuclear magnetic resonance (LF NMR) as well as Raman and infrared spectroscopy, which proved that the chemical composition of the obtained membrane did not degrade during microwave-assisted polymerization. Easily and cheaply prepared through microwave-assisted polymerization, the starch membrane was successfully used as a biodegradable membrane separating the positive and negative electrodes in electric double-layer capacitors (EDLCs). The obtained results for the electrochemical characterization via cyclic voltammetry (CV), galvanostatic charge with potential limitation (GCPL), and electrochemical impedance spectroscopy (EIS) show a capacitance of 30 F g-1 and a resistance of 2 Ohms; moreover, the longevity of the EDLC during electrochemical floating exceeded more than 200 h or a cyclic ability of 50,000 cycles. Furthermore, due to the flexibility of the membrane, it can be easily used in novel, flexible energy storage systems. This proves that this novel biomembrane can be a significant step toward ecologically friendly energy storage devices and could be considered a cheaper alternative to currently used materials, which cannot easily biodegrade over time in comparison to biopolymers.

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.

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.

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.

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.

Low-Field NMR Study of Shortcake Biscuits with Cricket Powder, and Their Nutritional and Physical Characteristics

The growing human population renders challenges for the future supply of food products with high nutritional value. Here, we enhanced the functional and nutritional value of biscuits, a popular sweet snack, by replacing the wheat flour with 2%, 6%, or 10% (w/w) cricket powder. Consumer acceptance ratings for reference and 2% augmented cookies were comparable, whereas the higher levels of enhancement received inferior consumer scores. This relatively small change in biscuit recipe provided significant and nutritionally desirable enhancements in the biscuits, observed in a series of analyses. An increase in the protein content was observed, including essential amino acids, as well as minerals and fat. This conversion also affected the physical properties of the biscuits, including hardness, and water molecular dynamics measured by 1H NMR. Cricket powder-augmented biscuits join the line of enhanced, functionally superior food products. This and similar food augmentation provide a viable scenario to meet the human food demands in the future.