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

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.

Positive effects of thermosonication in Jamun fruit dairy dessert processing

The effects of thermosonication processing (TS, 90 °C, ultrasound powers of 200, 400, and 600 W) on the quality parameters of Jamun fruit dairy dessert compared to conventional heating processing (high-temperature short time, (HTST), 90 °C/20 s) were evaluated. Microbiological inactivation and stability, rheological parameters, physical properties, volatile and fatty acid profiles, and bioactive compounds were assessed. TS provided more significant microbial inactivation (1 log CFU mL-1) and higher microbial stability during storage (21 days) than HTST, with 3, 2, and 2.8 log CFU mL-1 lower counts for yeasts and molds, aerobic mesophilic bacteria, and lactic acid bacteria, respectively. In addition, TS-treated samples showed higher anti-hypertensive (>39%), antioxidant (>33%), and anti-diabetic (>27%) activities, a higher concentration of phenolic compounds (>22%), preservation of anthocyanins, and better digestibility due to the smaller fat droplet size (observed by confocal laser scanning microscopy). Furthermore, lower TS powers (200 W) improved the fatty acid (higher monounsaturated and polyunsaturated fatty acid contents, 52.78 and 132.24%) and volatile (higher number of terpenes, n = 5) profiles and decreased the atherogenic index. On the other hand, higher TS powers (600 W) maintained the rheological parameters of the control product and contributed more significantly to the functional properties of the products (antioxidant, anti-hypertensive, and anti-diabetic). In conclusion, TS proved to be efficient in treating Jamun fruit dairy dessert, opening space for new studies to define process parameters and expand TS application in other food matrices.