Journal of Food Measurement and Characterization最新文献

‘Hom Nil’ is a popular Thai purple rice cultivar rich in anthocyanins. Germination and parboiling further enhance its health-promoting properties. This study investigated the thin-layer drying kinetics and moisture sorption behavior of germinated parboiled rice (GPR). Equilibrium moisture content was measured at 20, 40, and 60 °C across relative humidity (RH) levels of 10 to 85% using a dynamic vapor sorption system for both paddy and husked GPR. At a fixed RH, moisture content decreased with increasing temperature. Sorption isotherms exhibited hysteresis, with desorption values higher than adsorption values. Five modified sorption models (GAB, Oswin, Halsey, Henderson, and Chung−Pfost) were evaluated. The modified Halsey model provided the best fit to the data. Drying experiments were conducted at 40, 50, 60, 70, and 80 °C under air velocities of 0.2–1.3 m s⁻¹ using both over-flow and through-flow modes. The Page model provided the best fit under all conditions. Drying temperature significantly affected drying rate and time. Drying mode also significantly influenced the drying rate, with the through-flow mode leading to faster moisture removal than the over-flow mode, due to higher heat and mass transfer. These findings provide essential parameters for optimizing GPR drying and storage.

The pupal shells of the black soldier fly (BSF) show great potential in the production of chitin and chitosan. Compared to the traditional chemical acid–base deproteinization method, this study was devoted to the development of a more environmentally friendly enzymatic deproteinization technique to extract higher quality chitosan. Response surface methodology (RSM) was used to determine the optimal conditions for enzymatic hydrolysis in terms of reaction time (3.2 h), reaction temperature (49 °C) and enzyme/substrate ratio (5.4:100). The physicochemical properties of chitosan CS_E obtained by protease hydrolysis and chitosan CS_C obtained by traditional acid–base method were determined and chitosan samples CS_E and CS_C were characterized by Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM). The results showed that the yield of CS_E was significantly higher at 18.85 ± 0.02% than that of CS_C at 11.29 ± 0.03%. Chitosan extracted from BSF pupal shells by enzymatic deproteinization showed antimicrobial activity against all tested bacterial strains, with relatively high antibacterial activity against Staphylococcus aureus (14.41 ± 0.54 mm), Escherichia coli (18.01 ± 0.66 mm). The superior yield and antimicrobial properties of chitosan extracted via enzymatic deproteinization suggest broad potential applications beyond biomedical sciences, including food preservation and water treatment fields where antimicrobial agents are highly sought. Future research is recommended to explore these applications, thereby maximizing the benefits of this environmentally friendly extraction method.

Uneven heat distribution and overheating are common challenges in microwave (MW) drying, often leading to inconsistent product quality. This study aims to improve the heating uniformity of coffee beans during MW drying by developing a mixing mechanism consisting of two plastic tubes and a cross-shaped mixing blade integrated into the MW cavity. Experimental data were fitted to mathematical models to describe the drying kinetics. Semi-wet processed coffee beans were dried in a MW system operating at 330 W (2450 MHz) with controlled temperatures of 40–55 °C. For comparison, a separate batch was dried in a conventional oven at 50 °C. The drying process was terminated when the final moisture content reached 11–12% (wet basis). MW drying with the mixing mechanism achieved this target in 2 h, significantly shorter than MW drying without mixing (5 h) and oven drying (14 h). Mixing improved heating uniformity by reducing temperature differences (ΔT) and the heating uniformity index (λ). Without mixing, surface temperatures exceeded 55 °C (peaking at 64 °C), exacerbating uneven heat distribution. The logarithmic model most accurately described the drying kinetics, which exhibited only a falling rate period. These results demonstrate that integrating a mixing mechanism into MW drying systems enhances heating uniformity and drastically shortens drying time for coffee beans. The findings underscore the potential of optimized MW technology to improve efficiency and consistency in food processing applications beyond coffee.

The proposed work is the outcome of the application of, advanced optimization techniques like Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) to predict and optimize the flaxseed oil yield and antioxidant activity through supercritical CO₂ (SC-CO₂) extraction. A Box-Behnken design (BBD) of RSM has been used to design and evaluated the impact of five most important key variables that are temperature, pressure, co-solvent concentration, CO₂ flow rate, and particle size. The proposed ANN model, comprising five input variables and one hidden layer, demonstrated superior predictive performance compared to RSM, with higher accuracy and lower mean square error. It predicted that the optimal conditions of 300 bar pressure, 60 °C temperature, 8% ethanol, 6 g/min CO₂ flow, and 0.50 mm particle size, yielding 0.33 g/g oil and 36.73% antioxidant activity, both closely aligned with experimental results. Flaxseed oil is rich in bioactive compounds such as total phenolic content (67.13 mg GAE/100 g), total flavonoid content (24.00 mg QE/100 g), and total tocopherol content (29.16 mg/100 g), enhancing its nutraceutical value. It also comprises a huge quantity of polyunsaturated fatty acids (67.4%), oleic acid and predominantly linolenic acid (51.57%). The combined use of RSM and ANN not only enables efficient extraction but also establishes a scalable, eco-friendly model for future industrial applications. This study advocates the advances in green extraction by enabling accurate, scalable, and sustainable processes through predictive modeling. The approach is versatile and applicable to other plant-based bioactive. Future work may explore hybrid modeling, real-time control, and life-cycle assessment to enhance industrial relevance.

This study evaluates the isolation of Indian brown teff starch using four extraction methods: 0.25% and 0.50% sodium hydroxide (NaOH), 0.1% sodium metabisulphite (Na₂S₂O₅), 0.1% citric acid (CA), and distilled water (DW). Among the methods, 0.50% NaOH achieved the highest starch purity (95.45%) and yield (51.75%), while DW produced the lowest purity (87.31%) and yield (40.50%). Functional properties varied significantly, with amylose content ranging from 20.20 to 22.13%, and water-binding capacities between 152.7% and 155.9%. The swelling power and solubility increased simultaneously with temperature. Thermal analysis showed gelatinization onset temperatures of 28.83–32.12 °C and enthalpy values of 11.15–14.85 J/g. Pasting properties revealed peak viscosities from 1751 to 4352 cP, with NaOH treatments enhancing viscosity parameters. X-ray diffraction showed an A-type. Scanning Electron Microscopy (SEM) confirmed smooth starch granules with polygonal shapes, while Fourier Transform Infrared (FTIR) spectroscopy identified characteristic vibrational bands. Indian brown teff starch is a versatile material suitable for both food and non-food applications. It can be used as a thickener, fat replacer, biodegradable packaging material, pharmaceutical ingredient, and industrial binder. The high purity and thermal stability of starch, especially when extracted with NaOH, improves its performance in these applications.

Traditional crops have gained considerable importance in biomedical research due to emerging evidence suggesting their positive impact on human health. The two important Himalayan crops i.e., Finger millet (Eleusine coracana (L.) Gaertn.) and Dolichos beans (Lablab purpureus L. Sweet) are considered nutritious and wholesome due to their high fibre content. The primary objective of this research is to assess the antioxidant potential of different extracts (aqueous-methanol, hexane, and aqueous) obtained from Eleusine coracana (L.) Gaertn. and Lablab purpureus L. The in-vitro assays including 2,2-diphenyl-1-picrylhydrazyl (DPPH•) radical scavenging assay, Ferric Reducing Antioxidant Power (FRAP) and % metal chelating methods were employed to evaluate the antioxidant activity of various extracts from E. coracana (L.) Gaertn. and L. purpureus L. Phytochemical analysis of both plants was conducted using UPLC-MS/MS. The in-vitro assays conducted on different plant extracts indicated that aqueous methanol extracts exhibited the highest antioxidant activity in terms of EC50 values of DPPH• radical scavenging activity 85.51 ± 1.87 and 291.42 ± 0.11 µg/mL; FRAP 2.01 ± 0.01 and 2.08 ± 0.10 mM FeSO₄/mg extract; metal chelation 52.83 ± 1.58 and 74.62 ± 0.01% respectively in S1 and S2 sample, possibly due to their higher total phenolic content (TPC). Phytochemical analysis revealed the presence of compounds such as n-feruloyltyramine, tricetin, kaempferol (or luteolin)-o-glucoside/isomers, delphinidin-3-o-arabinoside, quercetin and fisetin in Eleusine coracana (L.) Gaertn., and diferulic acid, cyanidin-3-o-glucoside, 3-o-methylquercetin, delphinidin-3-o-arabinoside, quercetin and cinnamic acid glucoside in Lablab purpureus subsp. purpureus. Aqueous methanolic extract demonstrated the most potent antioxidant activity. Therefore, incorporating these crops into the diet may contribute to promoting a healthy and fulfilling lifestyle.

Accurate ingredient-level segmentation is critical for intelligent dietary assessment, yet it remains challenging due to severe class imbalance and the visual ambiguity of cooked foods. This study aims to enhance segmentation accuracy, particularly for low-prevalence ingredients, by incorporating domain-specific culinary knowledge into deep learning models. We propose a general framework that leverages ingredient co-occurrence relationship constraints to guide the training of deep learning segmentation models. By statistically analyzing ingredient pairing patterns in large-scale datasets (FoodSeg103 and Recipe1M +), we construct co-occurrence matrices that capture the likelihood of ingredients appearing together. These matrices are integrated into the loss function of a U-Net architecture with various state-of-the-art encoders, providing contextual priors to improve model learning. Our method achieves significant and statistically significant performance gains across multiple encoder backbones. On the FoodSeg103 dataset, it improves the mean Intersection over Union (mIoU) by up to 3.72% and the F1-score by 3.65%. More notably, when utilizing the larger Recipe1M + dataset to construct the co-occurrence matrix, the mIoU improvement reaches a remarkable 16.54%, demonstrating strong generalization capabilities. Critically, for the EfficientNet-b7 model using the Recipe1M + matrix, the approach achieves a dramatic 755% improvement in mIoU for the least frequent 10% of ingredient classes, effectively mitigating the class imbalance problem. The approach maintains real-time inference capability with a latency of 15.68 ms on a standard GPU. This work effectively addresses the class imbalance problem in food segmentation by integrating external culinary knowledge through co-occurrence matrices. The consistent and statistically significant performance improvements validate the framework's robustness. The method offers strong practical value for applications in automated dietary monitoring systems, smart dining platforms, and nutritional analysis tools.

Graphical Abstract

This study aimed to produce antioxidant-rich colored tofu using natural pigments (curcumin, monascus red, and gardenia blue) to address color instability issues in fruit/vegetable-based tofu while enhancing functional properties. Preparation conditions were optimized by varying soybean-to-water ratios (1:5–1:7), coagulants (GDL, CaCl₂), coagulant concentrations (0.3–0.5%), temperatures (85–95 °C), and pigment types. Optimized tofu was characterized for yield, gel strength, water-holding capacity (WHC), pH, texture, color, sensory attributes, and antioxidant activity (DPPH, ABTS, FRAP assays) before/after frying. Optimal conditions used a 1:5 soybean/water ratio, 0.5% GDL coagulant at 85 °C. Colored tofu exhibited similar yield and pH to white tofu but higher hardness, chewiness, and sensory scores. Red and yellow tofu showed significantly increased antioxidant activity versus white tofu before frying (e.g., DPPH: 71.82% and 73.57% vs. 50.73%) and retained superiority after frying (e.g., DPPH: 45.06% and 51.67% vs. 20.80%). Blue tofu’s antioxidant activity improved post-frying but was unchanged pre-frying. Frying reduced brightness (L) while increasing redness (a) and yellowness (b*) in all samples. Curcumin and monascus red pigments enhance tofu’s visual appeal, texture, and antioxidant properties, even post-frying. This approach offers a promising strategy to develop functional tofu with stable color and health benefits.

The reuse and valorization of solid by-products from olive oil mills are attracting growing interest in the food, pharmaceutical, and cosmetics sectors due to the recovery of vital bioactive compounds and residual oil, which can be incorporated into functional foods, cosmetics, and pharmaceuticals products. This study investigates, for the first time, the chemical composition, biological activities, and potential valorization of Chemlal olive pomace from Algeria, both fresh and dried. The pomace was showed standard compliant values for moisture, acidity, and pH, a high phenolic content (50.56 g GAE/kg before drying and 63.53 g GAE/kg after drying), with significant antioxidant activity (DPPH• inhibition of 78.34% before drying and 89.53% after drying). Fourier-transform infrared (FTIR) spectroscopy confirmed the presence of functional groups associated with phenolic compounds, triglycerides, and fatty acids, indicating strong potential for functional compounds recovery. The extracted oil had slightly elevated acidity and dominant oleic acid content (64.60%), consistent with conventional olive oil profiles. Notably, the oil also exhibited good antioxidant activity (87.43%), and a measurable phenolic content (30.98 g GAE/kg). These findings contribute to the existing body of knowledge on olive pomace and highlight its potential as a valuable resource for the agri-food and pharmaceutical industries. They also emphasize the importance of drying as a crucial pre-treatment for stabilization and optimal valorization.

The process variables viz. polysaccharide, glycerol, and purple rice husk extract (PRHE) effect on the response variables like film thickness, moisture content, water solubility (WS), and swelling index (SI) of the edible film developed with Artemesia vulgaris seed polysaccharide (AVSP) using Central- Composite response surface design. The results of the experimental runs were analysed using analysis of variance (ANOVA), and second-order polynomial models were developed from the experimental design, yielding a reliable and satisfactory fit with the corresponding experimental data, along with a high coefficient of determination (R² >0.89). In contrast, the effect of the interaction of glycerol and purple rice husk value was found to be significant (p < 0.05) on WS response. In addition, 3D response surface plots were established to investigate the relationship between process variables and the responses. According to FTIR data, there is a greater hydrogen bonding between the polysaccharide and phenolic components of PRHE. The inclusion of anthocyanin enhanced the crystallinity of the treated film, but the addition of polysaccharide decreased it, according to XRD data. Based on the DSC data, adding polysaccharide decreased the Tg, whereas adding the treated film marginally raised it. When compared to the polysaccharide film, the treated film showed better biodegradability, also degraded completely by day 3. The market film remains fully intact, showing no signs of degradation and antioxidant qualities, and antimicrobial potential, at extract concentrations, treated film had a 6 µg/ml increase in E. coli and a 10 µg/ml increase in S. aureus, suggesting at relatively low additive levels making these films bio-beneficial and sustainable. Results revealed that optimized AVSP edible films incorporated with purple rice husks were effectively produced and can be successfully applied in the food packaging industry.

Graphical abstract