Food and Bioprocess Technology最新文献

The water holding capacity (WHC) of complex food systems, such as lettuce during freezing, is governed by microstructural integrity. Optically quantifying this integrity, however, remains a challenge, as conventional optical methods typically probe chemical signatures rather than the underlying physical architecture. This study introduces a snapshot Mueller matrix polarimetric imaging system, employing quad-channel parallel demodulation, to directly assess microstructural changes and track the dynamic evolution of WHC in frozen lettuce. By acquiring full Mueller matrices and leveraging machine learning, we established quantitative models to predict WHC from 18 derived polarimetric features. The random forest regression (RFR) model yielded the highest predictive accuracy on an independent test set (R² = 0.8718, RMSE = 0.0356). Feature importance analysis confirmed that parameters reflecting tissue anisotropy (m11, m22) and disorder (depolarization, Δ) were the most critical predictors, establishing a direct link between the optical measurement and physical degradation. Pixel-wise mapping visualized the spatio-temporal evolution of WHC, revealing a transition from initial, heterogeneous damage to widespread structural collapse. Notably, the system’s parallel architecture acquires the four analysis-state images in a single snapshot for each illumination state. This synchronous demodulation provides inherent data consistency and represents a simplified design compared to sequential analysis schemes. This research establishes Mueller matrix polarimetry as a powerful paradigm for optical food quality inspection. By directly correlating optical signatures with microstructural integrity, it also demonstrates significant potential for intelligent online monitoring in agricultural product processing.

The effects of cold nitrogen Gliding Arc Discharge (GAD) plasma species on natural microbial contamination, physicochemical quality, and storage stability of apricot kernels were investigated. Plasma parameters, including gas flow rate (GF, 0.5–0.9 mL/min), electrode tip distance (ED, 0.6–1.0 cm), and treatment time (2–10 min) were optimized using a Box-Behnken design. Optimal conditions were determined for single-objective reduction of total mold-yeast count (0.9 mL/min GF, 0.6 cm ED, 4.18 min; plasma-I) and for multi-objective reduction of both total mold–yeast and total mesophilic aerobic bacteria (TMAB) counts (0.9 mL/min GF, 0.6 cm ED, 7.65 min; plasma-II). Plasma-II treatment achieved the highest microbial reductions of 22.1% for total mold–yeast and 7.7% for TMAB, indicating a modest decontamination effect. These microbial reductions persisted after 30 days of storage at 25 °C. Quality parameters, including moisture content, water activity, color, total phenolics, FRAP, ABTS, tocopherol isomers, free fatty acids, and fatty acid composition, were preserved after plasma-II treatment (p > 0.05). However, DPPH value decreased by 59.5% and 40.1% in plasma-I and II-treated samples, respectively, compared to the control (p < 0.05). After accelerated storage at 60 °C for 30 days, both plasma treatments led to a decrease in DPPH as well as FRAP and ABTS values of samples compared to control, but the highest decrease was determined for plasma-I (p < 0.05). This study showed that cold nitrogen GAD plasma treatment resulted in modest but measurable reductions in natural microbial contamination while maintaining storage stability of apricot kernels without compromising their physicochemical quality attributes.

Brewer’s spent grain (BSG) is a major by-product of brewing industries and a potential protein source for valorisation. Conventional protein extraction methods often yield low protein recovery and poor techno-functional properties due to the rigid fibre matrix of the BSG. This study evaluated the effect of high hydrostatic pressure (HHP)-assisted BSG protein extraction (0.1, 300, 450, and 600 MPa) on protein extraction efficiency, structural modification, and techno-functional properties of BSG protein isolate (PI). Regardless of pressure, HHP-assisted extraction significantly enhanced protein recovery and purity of BSG PI compared to the control. Amino acid profiles also varied among different pressure levels, indicating the recovery of slightly different protein fractions. Major conformational changes were observed at 600 MPa, resulting in increased protein solubility. Free thiol content was unaffected up to 450 MPa but increased at 600 MPa compared with 300 and 450 MPa. In general, the emulsion activity index (EAI) decreased in all HHP-treated groups compared to the control except at 450 MPa, whereas the emulsion stability index (ESI) was unaffected. Foaming capacity (F₀) remained unchanged, but foam stability (FS) increased three-fold at 600 MPa compared to the control. The least gelation concentration (LGC) was reduced to 7% in all HHP-treated BSG PI compared to the control (9%). Overall, current results showed that HHP-assisted extraction sustainably improves BSG PI extraction efficiency and induces structural changes that enhance most techno-functional properties, except for the EAI, supporting the use of BSG PI as a sustainable alternative protein ingredient.

Tender coconut water (TCW) is a nutrient-rich natural beverage with several health benefits and is highly prone to spoilage once extracted from the nut due to microbial contamination and its nutrient-rich composition. Conventional heat thermal preservation methods, like pasteurization, often degrade sensitive nutrients and affect sensory quality. In contrast, non-thermal methods like high-pressure processing (HPP) and pulsed electric field (PEF) have shown promise for better quality retention. In this study, the effects of PEF (16 kV/cm for 0.84 s; 12,000 pulses × 70 µs pulse width), HPP (475 MPa for 6 min), combined treatment (PEF + HPP), and thermal processing (90 °C for 5 min) on the overall quality of TCW during refrigerated storage were evaluated. The impact of these treatments on mineral content and volatile composition was also assessed. Results revealed that PEF and HPP enhanced total phenolic content and antioxidant activity significantly (p < 0.05) and by at least 10%, whereas combined and conventional heat treatments caused significant reductions (p < 0.05). No significant differences were observed in pH, total soluble solids, viscosity, and sugar content immediately after treatment. Complete inactivation of polyphenol oxidase was achieved by PEF, combined, and conventional heat treatments, while peroxidase remained more resistant. Microbial counts remained within acceptable limits across treatments. During storage, a gradual decline in pH, viscosity, protein, and vitamin C, along with increased microbial growth, enzyme activity, and reducing sugars, was noted. Based on sensory evaluation, physicochemical stability, nutritional retention, and cost considerations, PEF emerged as the most effective method for preserving TCW quality for up to 25 days under refrigeration.

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Food allergy is a major food safety and public health concern, driven by the increasing consumption of processed foods and the globalization of food supply chains. Industrial processing can profoundly alter the structure, digestibility, and immunoreactivity of food proteins, thereby either attenuating or enhancing their allergenic potential. This review provides a critical and mechanistic overview of how conventional and emerging processing technologies modulate the allergenicity of major food allergens from animal, plant, and microbial sources. Across diverse processing strategies, allergen risk modulation can be systematically interpreted through four fundamental processing-induced “epitope-fate” mechanisms: (i) destruction of epitopes via targeted hydrolysis or enzymatic cleavage, (ii) masking or inactivation of epitopes through aggregation or cross-linking, (iii) exposure or creation of neo-epitopes driven by protein unfolding or chemical modification, and (iv) physical removal of allergenic fractions using separation approaches such as ultrafiltration. The effects of thermal (boiling, frying, roasting), non-thermal (high-pressure processing, irradiation, pulsed light, cold plasma), and bioprocessing methods (enzymatic hydrolysis, fermentation) on allergenicity are comparatively evaluated. Our analysis shows that no single method consistently reduces allergen risk. Thermal treatments vary based on conditions, while high-pressure and enzymatic approaches are more reliable. Robust allergen risk mitigation is most reliably achieved through sequenced, orthogonal processing combinations, which integrate moderate unfolding, targeted proteolysis or fermentation, and physical clearance steps while actively managing trade-offs among efficacy, product quality, industrial feasibility, and the risk of process-induced neo-allergenicity.

This study aimed to investigate a sustainable biotechnological method for producing salt-reduced baked goods without compromising sensory appeal or texture, in line with current health recommendations. A yeast-leavened bread was formulated by incorporating, at 10% (w/w dough), a biomolecule-enriched bioingredient based on fermented hempseed or wheat gluten flour mixed to wheat flour, acting as salt replacer to achieve a 50% reduction in salt. The bioingredients, obtained using Lactiplantibacillus plantarum ITM21B as a starter culture under two Fermentation Conditions (FC1: Dough Yield 500, 37 °C and FC2: Dough Yield 250, 25 °C), were characterized for strain growth, pH, total titratable acidity (TTA), organic acids (lactic, acetic, propionic, phenyllactic and hydroxy-phenyllactic), total proteins, total free amino acids (TFAA) and L-glutamic acid. The two bioingredients obtained under FC2, which were particularly rich in biomolecules, were then incorporated in 50% salt-reduced bread formulation (6.7 g/kg) and processed in an industrially relevant pilot plant. The presence of both bioingredients resulted in a twofold increase of L-glutamic acid content compared with the Control bread (standard salt content, no bioingredient). Additionally, breads containing the bioingredients exhibited significantly reduced hardness and chewiness, as well as a softer crumb, with the strongest effects observed in breads containing hempseed-based bioingredient. Sensory analysis revealed that despite the salt reduction, bread enriched with the hempseed bioingredient was well-accepted by panelists, showing color, crust and crumb firmness, staling, odor, taste and sapidity attributes comparable to the Control bread. In conclusion, the addition of 10% hempseed-based bioingredient improved texture and increased L-glutamic acid levels, effectively compensating for the reduced salt in sensory evaluations.

Egg defect detection is essential for ensuring food safety and quality in the egg production industry. This study introduces a novel approach for egg defect detection by integrating a multi-head self-attention (MHSA) mechanism into the AlexNet convolutional neural network (CNN) to overcome the limitations of traditional CNNs in capturing long-range dependencies and global context. A machine vision system equipped with a constant-speed rotating mechanism was developed to capture multi-view images of each egg’s surface. Each egg was imaged from six angles, generating a dataset of 2400 images categorized into four classes: bloodstained, cracked, dirty, and intact. The collected images were pre-processed through segmentation and cropping before being fed into the MHSA-AlexNet architecture. The extracted feature maps were flattened and passed through an MHSA layer with eight attention heads, followed by a fully connected layer and Softmax classifier. The proposed MHSA-AlexNet model achieved an average accuracy of 0.9847, outperforming the baseline AlexNet and surpassing other state-of-the-art CNNs. The model also surpassed conventional machine learning models, including Naïve Bayes, Random Forest, and Support Vector Machine, by 36.35–66.81%. Comparison with prior studies demonstrated that MHSA-AlexNet achieved superior accuracy, emphasizing the effectiveness of integrating self-attention mechanisms for egg defect detection.

This study evaluated the efficacy of five physical technologies, including catalytic infrared (CIR), radiofrequency (RF), pulsed light (PL), low-temperature plasma (LTP), and ozone (O₃), for inactivating aflatoxigenic Aspergillus flavus (A. flavus) in rice. Individually, these treatments showed limited antimicrobial activity, with ozone performing the highest efficacy among single treatments (p < 0.05). Combining treatments produced synergistic effects: CIR or RF with PL or LTP significantly reduced microbial counts by 1.0—3.0 log (p < 0.05), whereas integrating ozone with tempering (60℃, 240 min) achieved effective antifungal activity and shortened the required exposure time. The sequence of treatments showed no significant effect. Mechanistic analysis revealed that both thermal and non-thermal effects disrupted spore cell walls and membranes, significantly increasing electrolyte leakage (p < 0.05). Microscopic images showed structural collapse and perforation under combined treatments. Rice quality was largely maintained. Thermal treatments significantly improved head rice yield (HRY) (from 52.3% to 60.6%) (p < 0.05) through moisture migration, while ozone treatment decreased amylose content (AC) from 16.93% to 14.83% (p < 0.05). Heat retention mitigated these effects and balanced quality parameters. Overall, combining physical technologies with controlled tempering significantly enhances A. flavus inactivation while preserving rice quality. These findings demonstrate a feasible, non-chemical strategy for enhancing fungal safety in rice while maintaining processing quality.

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