One of the most commonly used food preparation methods is deep-fat frying. The improvement of the quality of used frying oil (UFO) is important because the reuse of frying oil could provide significant savings to the food industry. This study aimed to enhance the quality of used sunflower oil by using chitosan aerogels (CA), which can be considered as novel adsorbents with an increased surface area compared to chitosan powder. Aerogels are novel nanostructured materials with high porosity and large surface area. In this study, CA were produced by drying the 2% (w/v) chitosan gels using supercritical drying. In the study, 32 consecutive deep-fat frying were performed using potato slices in sunflower oil at 180 ± 5 °C. The effect of the adsorbent concentration (0.5, 1, and 2% (w/w)) and different adsorption temperatures (90, 135, and 180 °C) were studied by examining the UFO before and after the adsorption treatments. The physicochemical properties of the oil were analyzed by determining free fatty acid (FFA) content, total polar compounds (TPC), smoke point, p-anisidine value (p-AnV), and color (CIE L*, a*, b*). Moreover, the structural changes of aerogels after the adsorption process were investigated by Fourier Transform Infrared spectroscopy (FTIR) and Nuclear Magnetic Resonance (NMR). CA could reduce the % FFA values from 0.44% to 0.18% due to the ionic interaction between CA and FFA. In addition, TPC value and the smoke point increased after the treatments. The p-AnV was compensated with CA, indicating that secondary oxidation products were adsorbed. Moreover, CA caused a darker color after the adsorption treatments. Additionally, compared with magnesium silicate, the same concentrations of CA were found more effective in improving all the quality parameters of oil except for the L* values.

In this study, the adsorption and inhibition of lipid oxidation propertises of curcumin embeded ovalbumin (OVA)/sodium carboxymethylcellulose (CMC) were investigated. The results demonstrated that the adsorption of curcumin and OVA/CMC particles at the oil-water interface might form a dual protection. The larger emulsion droplets were formed at an OVA/CMC ratio of 1:2 (pH 4.4) due to bridging flocculation. In the other two ratios (1:1, 2:1), the emulsions showed good stability after 32 days of storage. At the ratios of 1:2, 1:1, and 2:1, the oxidation rate of the oil in the emulsion stabilized by OVA/CMC and OVA/CMC-Cur particles reduced by 16.2% and 37.9%, 4.9% and 38.9%, and 8.8% and 35.8%, respectively, than the pure oil. At the ratios of 1:1 and 2:1, the emulsion stabilized by the OVA/CMC-Cur particles demonstrated excellent antioxidant resistance and storage stability, particularly at the ratio of 1:1.

Biogenic amines (BAs) generally result from the decarboxylation reaction of free amino acids as a result of the activity of different microorganisms. A build-up of these compounds can result in food being spoilt. Therefore, the rapid and precise detection of BAs like histamine is an important task for food safety. This research aimed to explore the potential of Fourier-Transform Mid-Infrared (FT-MIR) spectroscopy combined with chemometric methods to assess histamine in fresh tuna quantitatively. Based on the FT-MIR data, partial least squares regression models for the prediction of histamine were successfully constructed with R2 > 0.90. Machine learning algorithms (partial least squares-discrimination analysis, k-nearest neighbors, and support vector machine) were applied, and excellent discrimination results were achieved based on the limits specified in two different legislations (EU and FDA). The results support the use of a rapid, economic and reliable approach for the discrimination of samples that could pose a health risk to consumers.

Volatile flavor is a key indicator of food quality which can directly affect consumer preference and purchase intention. Electronic nose is considered as a promising intelligent sensory analysis tool for food flavor assessment, however, extracting effective features from the gas sensor array is still a major challenge, which largely determines the performance of subsequent classifiers. Here, a parallel long short-term memory (LSTM) network is proposed as a feature extractor for automatically extracting features from the whole time series of sensor responses in flavor discrimination of five Chinese vinegars. The network was trained by the temporal data from the sensor array and yielded different feature patterns corresponding to different vinegars, which were then fed to other conventional classifiers for pattern recognition. We also evaluated the influence of the extracted feature dimension that is related to the dimension of the hidden state of the LSTM layer on the classification performance. The results indicate that a larger dimension of extracted feature is unnecessary for promoting classification accuracy, instead, the optimum dimension 4 of the hidden state gives the highest accuracy of 95.8% in this application under the softmax evaluator. Moreover, much higher accuracies were obtained when combined with other sophisticated classifiers such as support vector machine. The results demonstrate that the proposed network is competent to extract features directly and automatically from the temporal data of the electronic nose.

In this research, curcumin (Cur) was encapsulated in succinylated soy protein isolate (SSPI) emulsion and combined with chitosan (CS) to prepare a smart film. The good adsorption ability of SSPI at the oil-water interface provides good physical stability for preparing Cur-loaded emulsion. These CS smart films containing SSPI emulsions with different curcumin content were evaluated on the structure, mechanical, barrier, antioxidant, antibacterial properties, and controlled release behavior. SEM and FT-IR results showed that the Cur-loaded emulsion was compatible with the CS matrix. By adding the emulsion, the film blocked 97.11% of ultraviolet radiation, reduced the water vapor transmission rate by 42%, and improved the swelling degree (32.26%), water solubility (12%), thermal stability and elongation at break (70.79 %) (p < 0.05). In addition, the film has a high antibacterial effect on Staphylococcus aureus and Escherichia coli (Bacterial inhibition zone diameter: 19.59 mm and 18.66 mm) and the release rate of curcumin in the film reaches 82.60%, mainly following the Fickian diffusion. The film gradually turns red under alkaline conditions, a property that makes the films successful in monitoring the deterioration of pork during storage. Adding SSPI emulsions and curcumin to films has great potential for food freshness monitoring and packaging.

Wheat germ is an agricultural but low-economic by-product for animal feed or waste due to its susceptibility of hydrolytic/oxidative rancidities. Here, we use controllable extrusion to treat wheat germ, and with assistance of exogenous starch as lipid protective factor at different ratios (0:10 2:8, 3:7, 4:6). Oxidation of optimized germ extrudate was slowed down during storage, with total lipid retention rate reach up to ∼88.3%. Extrusion dynamic analysis showed that relatively high screw speed (100–150 rpm) significantly shortened mean residence time, increased axial diffusion velocity and reduced the loss of free and bound lipid. Type Ⅱ starch-lipid complex was changed to type Ⅰ during extrusion, with thermal transition peak declined. Wheat germ lipid was most evenly distributed under 100 rpm extrusion. The hydrogen bonding interaction between exogenous starch and lipids in wheat germ was strengthened, with significant modification in water absorption, water solubility, expansion and textual indexes.

In this study, a new bloom-reducing approach, modifying the surface of crystalline sugar was introduced and confirmed through two methods (circularity and Casson viscosity). Targeting the effects of sucrose shape on bloom, model chocolates were formulated with 2 sucrose surfaces (before and after modification) at 3 sucrose volume fractions (0.15, 0.50, and 0.75) in the nonfat particle phase. Bloom was evaluated by changes in whiteness index (ΔWI) and white area percentage (WA%), accompanied by polymorphic transition evaluations. Surface morphology during storage was also evaluated by scanning electron microscopy (SEM) to quantify surface roughness and porosity. Bloom and SEM results both showed similar trends: smoothing sucrose particle surface as well as reducing sucrose fraction volume significantly reduced bloom and surface morphological (roughness and porosity) change, indicating that sucrose surface modification may have a significant impact on the particulate microstructures in chocolate thus impeding bloom formation during storage.

This study addresses the accurate estimation of kimchi cabbage mass, as cabbage leaves exhibit size variability and complex leaf structures. Conventional mass estimation methods, which rely solely on external imaging, often overlook leaf gaps. To improve accuracy, we propose an innovative computer vision system utilizing hybrid-view images and detailed saturation analysis. Our system quantifies the impact of leaf gaps on mass using features from the saturation channel of images of bisected cabbage. Our proposed method can be easily integrated into existing workflows and has the potential to improve labor efficiency. Our approach outperforms the conventional method (R2 of 0.66 and relative error of 8.68%), achieving a 0.92 R2 value and lowering the relative error to 4.22%. This advancement offers a robust solution for the mass estimation of kimchi cabbage and suggests potential applications for other foods and crops with internal voids.