Journal of Food Process Engineering最新文献

Design and field evaluation of a glass fiber-reinforced plastic (GFRP) maize cob dryer with an Arduino-based humidity-responsive airflow control system is presented. The portable, 1-t capacity dryer uses a perforated GFRP bed, a transparent polyethylene roof for passive solar heating, and an automated fan to maintain a drier chamber microclimate. Field trials during the post-monsoon Kharif period showed drying of intact cobs from ~36% to ~17% (w.b.) within 8–9 days, and no visible fungal colonies were detected in dried samples. Structural assessment demonstrated safe operation of the GFRP bed under full load. Compared with typical open-sun drying durations reported in the literature for the same season, the system provides a shorter and more controlled drying period (literature-based comparison). The dryer offers a low-energy, portable option to reduce weather-related drying risks and postharvest losses for smallholder farmers.

Golden pomfret, with its abundant production, ease of capture, tender and flavorful flesh, and rich content of unsaturated fatty acids, has gained widespread popularity among consumers. However, with the development of the society, the traditional meat freshness testing methods can't satisfy the requirements of modern fisheries for rapid, nondestructive and accurate testing of aquatic products. Gas-sensor technology can achieve rapid and nondestructive determination of freshness by detecting volatile odors in aquatic products. However, the sensor is easily influenced by the interference of environmental factors due to its high sensitivity. How to eliminate the interference factors and realize the rapid detection of aquatic product quality has become a new research direction. Therefore, we analyze the basic working mechanism of the gas sensor based on the target molecule's adsorption characteristics. After the preprocessing such as filtering and de-noising the original response curve of the sensor, we propose a feature value extraction method which is more suitable for the adsorption principle of the gas sensor. The method combines the mechanical features of the sensor adsorption process so that the feature values extracted can more accurately reflect the nature of the interaction between the target gas and the sensor surface, thereby enhancing the sensitivity of the model to freshness. We applied this feature extraction method to obtain three feature value parameters, and then we used various machine learning algorithms to build the golden pomfret freshness prediction model. The comparative analysis of these models showed that the model based on the Random Forest algorithm achieved an accuracy of 0.776 ± 0.041, a precision of 0.751 ± 0.040, a recall of 0.721 ± 0.065, and an F1-score of 0.722 ± 0.056 under five-fold cross-validation. The model implementation has been basically satisfied to predict the golden pomfret freshness. Our study provides a methodological reference for feature extraction in gas-sensing applications and supports other research on quality evaluation of golden pomfret and other aquatic products.

Ultrasound (US) and ultra-high pressure (UHP) are emerging non-thermal processing technologies with strong potential for modulating volatile compounds and improving the sensory properties of foods. This study evaluated how US and UHP treatments applied to freshly fermented blueberry vinegar affected volatile profiles and basic quality indices after 4 weeks of storage at 25°C. Analytical methods included physicochemical assays, gas chromatography–mass spectrometry, clustering, and principal component analysis. UHP treatment increased total ester content by about 29% (from 4.05 to 5.22 g/100 mL) and reduced acetic acid by approximately 54% (from 10,709.72 to 4879.86 μg/L) compared with the 4-week control (p < 0.05), which may be associated with enhanced fruity aroma and reduced perceived sourness. In contrast, US treatment had a milder influence, mainly reducing low-boiling-point esters and unpleasant odor compounds, while short-duration exposure slightly elevated aldehyde and ketone levels. These findings demonstrate that US and UHP regulate flavor compounds through distinct mechanisms and highlight their potential as targeted strategies for improving the flavor quality of blueberry vinegar during non-thermal processing.

Flavor loss is a major challenge in thermally processed ready-to-eat (RTE) foods such as semolina pudding, which relies on the characteristic aroma of cardamom. The volatile and thermolabile nature of cardamom essential oil limits flavor retention during processing and storage. To overcome this, cardamom essential oil was encapsulated using hydroxypropyl-β-cyclodextrin (HP-β-CD) to enhance flavor stability. A cardamom inclusion complex (Car-HP-β-CD-IC) with 79.21% encapsulation efficiency and a 1:1 stoichiometric ratio was developed, and FTIR confirmed complex formation at 1150–1020 cm⁻¹. The encapsulated complex was incorporated into semolina pudding and packaged in two retortable multilayer pouches: OP (PET/Nylon/Al-foil/cPP) and TP (PET/Nylon/cPP), along with corresponding control samples. All samples were thermally processed and stored at 5°C and 25°C for 12 months. Volatile compounds were analyzed using HS-GC–MS/MS and E-nose, along with lipid oxidation measurements. Encapsulation significantly improved (p < 0.05) retention of methyl oleate (11.30%) and methyl linoleate (12.92%), particularly, in OP-packaged samples stored at 5°C. After 12 months at 25°C, OP pouches retained significantly (p ≤ 0.05) higher (11.7% and 23.9%) 1,8-cineole (a major contributor to PC1 separation in E-nose PCA analysis) than TP in both encapsulated and control samples, respectively. Further, encapsulated samples exhibited minimal temperature effects, whereas control TP samples showed ~46.4% lower cineole retention at 5°C than at ambient conditions, indicating that cold storage alone is ineffective without encapsulation. First-order kinetics revealed 22.74% slower cineole degradation in encapsulated OP-packaged samples than in unencapsulated controls at 25°C, demonstrating the synergistic role of encapsulation and high-barrier OP packaging in flavor preservation.

To address the limited applicability of traditional diffusion theories in the curing of collagen-based foods, this study aimed to construct a multi-factor coupled effective diffusion coefficient model suitable for pork skin (a representative of collagen-based foods). The experiment used pork skin cured with different NaCl concentrations (2%–8%) for 24 h as the research object. Parameters such as porosity and tortuosity were measured. Combined with the verification of Fick's model, the model was derived by coupling percolation, fractal and other theories. Origin 2021 was used for data analysis, and SPSS 27 was employed for analysis of variance (ANOVA) with a significance level of p < 0.05. The results showed that the model's prediction deviations were only 0.18%–0.52% at NaCl concentrations of 2%–6%, while it failed at 8% high salt concentration due to collagen denaturation. The model simplified the measurement process, reduced the number of samples, and revealed the influence of microstructure on mass transfer. In conclusion, the model is accurate and reliable within the low-salt range, providing theoretical support for the precise processing of collagen-based materials in the food industry. It needs further optimization to adapt to high-salt environments.

Nutritional emulsions are extensively used as carrier systems in foods for special medical purposes and health supplements. The rational addition and utilization of calcium are critical for realizing its functional value in supporting bone development, maintaining metabolic homeostasis, and regulating enzymatic activities. However, calcium absorption is readily affected by various physiological factors, limiting its bioavailability. In this study, a nano-casein emulsion (NCE) was prepared using a two-stage high-pressure homogenization (rated at 8000 L/h throughput) on an industrial production line. Its physicochemical properties, in vitro digestion behavior, oral bioavailability, storage stability, and biocompatibility were evaluated. Compared with conventional casein emulsion (CE) prepared without high-pressure homogenization, NCE exhibited a mean particle size of 260 ± 2.2 nm, which was 60.76% smaller than CE (662.64 ± 39.68 nm), with improved colloidal stability and viscoelasticity. Simulated gastrointestinal digestion and Caco-2 cell transport assay demonstrated that NCE markedly increased amino acid release and intestinal absorption, achieving 2.2-fold higher transport efficiency than CE. The calcium absorption rate was also improved (46.0% ± 3.1% vs. 40.0% ± 0.04%, *p < 0.05). Pharmacokinetic analysis further confirmed higher in vivo bioavailability, with a peak serum calcium concentration (C_max) of 100 ± 0.426 μg/mL and an AUC increase of 67.20% compared to CE. NCE exhibited excellent physical stability, with a low instability index (0.0055 ± 0.0007) compared to CE (0.0655 ± 0.0007, ***p < 0.001), and maintained uniformity without phase separation during 15-day storage, confirming superior colloidal and storage stability. No adverse effects or histopathological abnormalities were observed in SD rats, confirming good biocompatibility. These results indicated that industrial-scale nano-casein emulsions provided a stable and scalable delivery system to enhance calcium and amino acid bioavailability, offering practical support for their commercial application in functional nutrition products.

Low-moisture foods (LMFs) have an extended shelf life due to their low water activity (≤ 0.85). These foods remain vulnerable to microbial contamination leading to foodborne illnesses and outbreaks. Conventional preservation methods help reduce microbial risks but negatively impact the sensory and nutritional quality of LMFs. Therefore, there is a growing need for advanced preservation techniques like irradiation, focusing on ensuring microbial safety without compromising overall food quality. This review discusses the effects of ionizing irradiations (gamma, x-ray, and e-beam), cold plasma (CP), and food matrix properties on microbial reduction and mycotoxin degradation. Ionizing irradiation demonstrates high efficacy in microbial (4–5 log CFU/g reductions) and mycotoxin reduction (60%–80% at 2–5 kGy) through deep penetration, microbial DNA disruption, and oxidative damage. Gamma irradiation, with superior penetration, achieves 3–6 log CFU/g reductions of Salmonella and Listeria at 1–5 kGy in dense foods. E-beams, with lower penetration, remain effective at higher doses (5–10 kGy), with high D₁₀ values suggesting pathogen-specific resistance. In contrast, CP shows considerable potential for surface decontamination and generates reactive species (RS) leading to microbial inactivation via lipid peroxidation and protein denaturation. CP results in 2–5 log CFU/g reductions of bacteria and fungi and 50%–70% mycotoxin reduction. Future research should optimize irradiation for complete sterilization of LMFs and refine CP for surface decontamination. Additionally, advancing equipment design and scaling both technologies are crucial for effective industrial application, and enhancing LMF safety and shelf life are covered in this review.

During rice processing, collision is a main interaction lowering economic benefit for grain broken, leading to the crucial role of grain collision fracture control. In this study, a self-established collision test platform combined with in situ high-speed imaging is built. Effects of collision velocity (12.56–69.08 m/s) and rice variety (indica, japonica, glutinous) on rice damage and crack propagation are researched. The grain fracture morphology and behavior were in-depth analyzed. A rice grain cohesive zone model (CZM) is built, and the collision behavior is simulated with finite element modeling (FEM). Results revealed four collision damage stages: no damage (Stage A, < 18.84 m/s), micro-cracking (Stage B, 18.84–37.68 m/s), macro-cracking (Stage C, 37.68–50.24 m/s), and fragmentation (Stage D, > 50.24 m/s). Rice type leads to different crack patterns, with indica rice showing T-shape crack and glutinous rice Y-shape crack. Using 3D microscopy to observe “cross-coupled” crack networks originating from collision points. Primary cracks propagate along the short axis, with secondary cracks branching at angles to the long axis. Rice crack FEM simulation showed that the brown rice modeling crack forming and fracture match with experiment testing. Stress concentration exists in the contact center zone, and a main transverse crack formed. Peak collision force increased with increasing velocity. The research provides theoretical support for rice processing optimization and machine design.