Warmed-over flavor (WOF) represents a typical off-flavor in meat products, characterized by stale, cardboard-like, and metallic notes. Growing research efforts have increasingly focused on WOF of meat products, while comprehensive and systematic reviews remain scarce. This review systematically summarizes the WOF in meat products from three interconnected perspectives: Formation mechanisms, detection technologies, and control strategies. Current evidences indicate that lipid oxidation acts as the primary driver of WOF development, while protein oxidation and microbial metabolism synergistically accelerate flavor deterioration. In detection, conventional detection methods such as TBARS and GC-MS serve as foundational approaches, whereas emerging techniques including rapid colorimetric sensing, lipidomics and imaging mass spectrometry (IMS) offer novel molecular-level insights. For control strategies, a comprehensive prevention framework spanning the entire "rearing-storage-processing-packaging" chain is proposed. Future studies should prioritize elucidating the molecular interplay between lipid and protein oxidation, developing multi-scale real-time detection platforms, and establishing green, sustainable, full-chain flavor preservation strategies.

This study investigated the interaction of blueberry anthocyanins extracts (BACNs) and bovine serum albumin (BSA), and further evaluated the application prospects of BACNs-BSA particles in Pickering emulsions. BACNs and BSA formed stable complexes through spontaneous non-covalent interactions. The hydroxyl groups of the BACNs monomers bound to the amino acid residues of BSA through strong hydrogen bonds or strong ionic bonds. Delphinidin exhibited the highest binding affinity, mainly combining with GLN-416 amino acid residues by hydrogen bonds. As the concentration of the BACNs-BSA particles increased, the droplet size of the Pickering emulsion decreased and more uniform, while viscosity and stability were simultaneously enhanced. The encapsulation efficiency (EE, >80%) and loading capacity (LC, >9.5%) indicated that the BACNs-BSA particles can serve as an effective carrier and stabilizer in Pickering emulsion system. The results may provide a theoretical basis for future studies of BACNs and BSA.

Given the significant differences in amino acid composition among proteins from various sources,the development of aminopeptidases with broad substrate spectrum can effectively support the efficient and directional hydrolysis of proteins.To overcome the narrow substrate spectrum of existing aminopeptidases,a novel aminopeptidase gene APs(Ar)-3 was screened and identified from Acinetobacter radioresistens a2,which was heterologously expressed in Escherichia coli.Enzymatic properties of APs(Ar)-3 were identified,and it was applied to the hydrolysis of oyster proteins.The results showed that APs(Ar)-3 exhibited a broad substrate spectrum,displaying prominent catalytic activity towards Ala-pNA and Arg-pNA,and was also capable of hydrolyzing hydrophobic amino acids such as Met and Leu.The optimal reaction temperature was 45℃,and the optimal reaction pH was 7.0.The enzyme maintained good stability at temperatures below45℃and within the pH range of 6.0-8.0.Co2+at 0.1 mmol/L could significantly activate the aminopeptidase activity of APs(Ar)-3,while Zn2+and Cu2+had inhibitory effects on the enzyme.In the enzymatic hydrolysis of oyster proteins,the degree of hydrolysis achieved by the synergistic action of APs(Ar)-3 with bromelain and trypsin were 57.86％and 57.61％,respectively,which were 17.2％and 10.69％higher than those of commercial aminopeptidases.Moreover,the addition of APs(Ar)-3 increased the umami taste value of the oyster protein hydrolysate and reduced its bitterness and astringency.This study aimed to provide an efficient aminopeptidase with a broad substrate spectrum for the preparation of protein hydrolysates,and offer theoretical reference and technical support for the directional hydrolysis of proteins and the high-value development and application of oyster resources.

This study extracted Yunnan Arabica coffee bean features through weighted fusion of CIE L*a*b* color histograms, Gray-level Co-occurrence Matrix-Local Binary Pattern composite textures, and morphological parameters, aiming to achieve accurate roasting degree identification and transparent decision-making. Convolutional neural networks outperformed all other models with the highest accuracy. Subsequent SHapley Additive exPlanations analysis demonstrated that key features exhibited a significant strong negative linear correlation with prediction outputs; negative contributions dominated light roasting samples, whereas robust positive contributions dominated dark roasting samples. External verification results clarified that the accuracy of dark-roasted samples reached 100.0%, that of light-roasted samples was 91.5%, and that of medium-roasted samples was 93.8%. The proposed intelligent system enabled automatic image acquisition, feature extraction, and inference, and supported connection to the Enterprise Resource Planning system for data traceability. This study broke deep learning's black-box limitation, providing a precise interpretable technique for coffee roasting standardization.

Conventional mixed matrix membranes (MMMs) are organic-inorganic hybrids. Following analogous structural logic, we develop a fully bio-based quasi-mixed matrix membrane (Quasi-MMM) using ferulic acid (FA) as a dual-functional organic filler in a chitosan-caseinate matrix. FA establishes covalent ester/amide linkages and an extensive hydrogen-bonding network with the biopolymer continuous phase, emulating the matrix-filler synergy of classical MMMs while imparting sustained antioxidant activity. The resulting dense membrane exhibits robust mechanical strength (∼ 55 MPa), tunable barrier properties, enhanced hydrophilicity and anomalously slow FA release (∼50% over 25 d) governed by non-Fickian transport. When coated on cherry tomatoes and stored at 4 °C for 25 d, the Quasi-MMM reduces malondialdehyde accumulation by >35%, suppresses microbial growth by >2 log CFU·g-1, and maintains firmness, ascorbic acid, and total phenolics near initial levels. This Quasi-MMM concept offers a viable green strategy for postharvest preservation by integrating structural reinforcement and continuous bioactive protection within a single, entirely organic platform.

In recent years, with the popularization of the concept of healthy diet, foods with glycemic index (GI) less than or equal to 55 (low GI) have gradually become the focus of consumers' attention. Among them, low GI noodles is a staple food that can regulate the level of blood sugar after meals, which have the advantages of reducing post-meal blood sugar fluctuations, preventing cardiovascular disease, regulating insulin levels, and enhancing satiety. In this manuscript, the research status of low GI noodles in recent years are summarized. The concept, classification, measurement method and influencing factors of GI are briefly described firstly, and then the influence mechanism of different types of raw materials, raw and auxiliary materials and different processing methods on the texture characteristics, sensory evaluation and starch content of low GI noodles are discussed, mainly focuses on the effects of different types of products on the level of postprandial blood glucose. Finally, the development prospect of low GI noodles is anticipated, in order to provide a theoretical basis for future research and market application in this field.

The hydrophilic soybean isolate protein (SPI) was utilized to improve the strong hydrophobicity of Zein by pHdriven Co-assembly technology. The effects of three pH cycling (pH 7-12-7, pH 7-12-9, pH 7-9-7) on assembly, morphology, surface properties, and emulsification performance of Zein-SPI composite particles were investigated. Results showed that the pH cycle significantly governed the denaturation-aggregation behavior. Severe cycling (pH 7-12-7) led to extensive protein unfolding, forming large, irregular aggregates with high turbidity (1212.73 nm). In contrast, the mild pH 7-9-7 system facilitated a balanced unfolding-refolding process, producing smaller nanoparticles (654.81 nm). In addition, SPI modification effectively reduced Zein-SPI composite particles size and enhanced surface hydrophilicity compared to Zein-only particles. Dialysis was performed as a necessary step to remove salt ions introduced during pH adjustment. Post-dialysis, the intrinsic particle properties were revealed: the pH 7-9-7 system exhibited the smallest particle size (324.05 nm) and a three-phase contact angle closest to 90 degrees (102 degrees), indicating favorable surface wettability. Consequently, the corresponding Pickering emulsion displayed the smallest, most uniform droplet size and improved emulsifying performance. Finally, this work highlights that synergizing mild pH cycling with dialysis is an effective approach to engineer protein-based particles with tailored surface emulsifying performance for Pickering emulsion applications.

Harman and norharman were the most representative (3-carboline heterocyclic amines (HAs). Their formation mechanisms were investigated in model systems containing intramuscular fat, D-glucose, D-ribose, and Dglucose-6-phosphate under varying conditions, and predictive models were developed. Results showed that at 90-210 degrees C, reaction times of 10-60 min, pH 5.5-8.0, and different additive levels, intramuscular fat increased harman and norharman formation by 16-275% and 16-284%, respectively, compared with the control group without additives, while D-glucose, D-ribose, and D-glucose-6-phosphate exhibited stronger enhancing effects, promoting the formation of harman by 50-753%, 18-718%, and 46-1586%, and norharman by 68-396%, 36-391%, and 11-107%, respectively, relative to the control. This indicated that sugar-derived reactive carbonyl species (RCSs) play a stronger role in promoting harman and norharman formation than lipid-derived RCSs under identical processing conditions. Furthermore, both linear and polynomial regression models effectively described the formation trends, with R2 values of 0.916 and 0.981, respectively, and a range of 0.608 to 0.999. For the optimal Partial Least Squares Regression (PLSR) models, harman achieved calibration (R2c) and prediction (R2p) values of 0.75-0.87 and 0.73-0.86; for norharman, 0.75-0.78 and 0.74-0.75. These results confirmed that harman and norharman can be accurately quantified and monitored during the smoking and roasting of meat products.

To address the limitations of single spectroscopic techniques and meet the demand for non-destructive geographical origin traceability of lotus seeds, this study integrated near-infrared spectroscopy (NIRS) and hyperspectral imaging (HSI) data to construct a lightweight convolutional neural network (CNNs) for accurate origin identification of lotus seeds from three core producing regions. We compared low-level and mid-level data fusion strategies, established models with multiple spectral pretreatments and feature selection algorithms, evaluated model robustness via repeated validation and independent external verification, and interpreted the model decision mechanism using gradient-weighted class activation mapping (Grad-CAM). Results showed that mid-level data fusion achieved an overall classification accuracy over 95%, with optimal combinations reaching 100% accuracy. The proposed model significantly outperformed conventional models, with the optimal overall accuracy of 98.68% for support vector machine (SVM) and 98.89% for random forest (RF). This method provides a high-precision, interpretable non-destructive solution for geographical origin identification of agricultural products.

Oil separation limits peanut butter quality and shelf life. This study investigated the effect of heat-induced aggregation of peanut protein isolate (PPI) at 60–100 °C on its structural, functional properties, and evaluated its application as a stabilizer in peanut butter. Thermal treatment altered PPI conformation—most notably a reduction in α-helix and an increase in β-sheet content—leading to enhanced surface hydrophobicity, emulsifying capacity, and oil-binding ability. PPI treated at 100 °C (PPI-100) exhibited the strongest stabilizing performance, and its incorporation (2%) into peanut butter reduced oil separation by 20.1% while improving rheological and textural attributes. During 60 days of room-temperature storage, peanut butter formulated with PPI-100 showed only 5.2% phase separation, confirming markedly improved physical stability. These findings highlight the potential of heat-treated PPI, within the tested upper thermal limit of 100 °C, as a viable clean-label stabilizer for emulsion foods including peanut butter.

Microplastics, pervasive environmental pollutants derived from synergistic physicochemical and biological degradation, threaten ecosystems and human health through bioaccumulation and inherent toxicity. While mainstream removal technologies exhibit inconsistent and often insufficient efficiency, Fenton-based advanced oxidation processes emerge as a promising solution, leveraging controllable and sustained radical generation to drive efficient microplastic decomposition via radical-mediated chain scission. This review systematically delineates radical formation mechanisms across diverse Fenton systems, particularly energy-assisted configurations where external inputs synergize with oxidant-catalyst interactions to enhance reactive species production. Through a comparative analysis of diverse Fenton-based systems, it elucidates structure-degradability relationships by delineating their distinct radical-mediated degradation pathways for key microplastic polymers. Critical operational parameters are integrated into a unified framework, revealing that pH governs catalyst stability and radical availability, temperature accelerates reaction kinetics and substrate accessibility, and oxidant-to-catalyst ratios optimize radical yield while minimizing scavenging effects. Performance comparison of prominent Fenton systems demonstrates high efficacy for numerous microplastics, yet underscores persistent challenges in mineralizing recalcitrant structures. Current evidence from ecotoxicological assessments, including computational modeling and bioassays, largely demonstrates a low ecological risk associated with the oxidative intermediates. Finally, we outline research priorities for next-generation Fenton technologies, emphasizing the development of tailored systems designed for recalcitrant structural frameworks, catalysts that not only boost degradation efficiency but also facilitate transformation into valorized by-products, as well as the integration of complementary energy inputs to significantly advance contaminant removal performance.

Understanding the ion-channel interaction involved in bio membranes is essential for designing artificial membrane with high performance. In this study, we have fabricated ion-selective membranes using MOF channel and Diethylenetriaminepentaacetic acid (DTPA) molecules as building units. Coordination DTPA molecules not only adjust the pore size but also offer high affinity towards interfering ion for the resulting membranes. The DTPA-modified channels can recognize mono-/divalent cations and achieve an enhanced K+/Mg2+ selectivity of up to 109, which surpass that of the original channels. Characterizations and theoretical simulations indicate that the strong coordinative interaction between DTPA with divalent cations groups hinder their transport, allowing weakly bound monovalent cations to permeate faster. Our findings provide a novel design paradigm for mimicking the efficient ion selectivity of biological systems within artificial solid-state nanochannels.

This study explored the self-removal efficiency and mechanisms of a photodynamically mediated 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-oxidized chitin grafted with 5-aminolevulinic acid (ALA) film against Vibrio parahaemolyticus biofilms via an endogenous photosensitization pathway. Results showed that the grafted ALA induced the production of endogenous protoporphyrin IX (PpIX), which in situ generated much reactive oxygen species (ROS) under blue LED irradiation. The ROS damaged the structural integrity and induced the unfolding of extracellular proteins, key component of extracellular polymeric substances (EPS), as well as decreased their hydrophobicity and adhesion work by 43.3%, which attenuated the interfacial adhesion of proteins. All the changes caused significant reduction in the colloidal stability and adhesive strength of EPS matrix on the surfaces of films, which eventually disintegrated the biofilms. Consequently, the films achieved over 99.6% inactivation of viable cells and 78.0% reduction of biofilm biomass. This study fabricated a novel antibacterial packaging film that initiates attacks from internal cells to eradicate biofilms.

Hyaluronic acid (HA), a natural bioactive polysaccharide, has emerged as a core material in interdisciplinary bioactive delivery systems due to its excellent biocompatibility, shear-thinning properties, and CD44 receptor targeting capability. This review summarizes the design, controlled-release, and applications of HA-based systems. In biomedicine, HA carriers enable targeted cancer therapy and bone defect repair. Responsive 3D-printed hydrogels support targeted drug delivery and bone regeneration. HA microneedles and nanoemulsions enhance transdermal absorption of actives. Injectable hydrogels provide long-term soft tissue augmentation, indicating nutraceutical potential. In the food industry, HA-gelatin layer-by-layer (LbL) microcapsules improve probiotic antioxidant capacity and survival. HA-based Pickering emulsions also enhance curcumin stability, digestibility, and bioavailability. Future developments focus on "goalkeeper"-style multifunctional smart HA synergistic delivery systems and localized/sustained gene delivery, and safety assessments for new HA-based systems also require careful consideration.

Inspired by the hierarchical protective structure of citrus pericarp, a biomimetic ternary film is fabricated for high-performance grape preservation. The system comprises an outer gellan gum (GG) layer mimicking hydrophobic epicuticular wax and an inner chitosan (CH) matrix reproducing the cushioning albedo tissue. Eugenol-loaded alginate microcapsules (MCs), analogous to citrus oil glands, enable sustained release. Optimized MCs (Alginate:eugenol = 3:1) achieve 91.0% encapsulation efficiency and biphasic release over 60 h. When integrated into GG/CH films, MCs enhance mechanical strength to over 50 MPa, increase opacity to over 0.83, and increase hydrophilicity (contact angle ∼85°). During 15-day storage, coated grapes exhibit reduced weight loss (∼25.2% vs. 31.9% control), maintained firmness (∼4 N), suppressed microbial growth (1.5-log reduction), and alleviated oxidative damage, along with inhibited changes in soluble solids, titratable acidity, and total phenolics. This biomimetic strategy integrates structural design with active delivery, offering a sustainable approach for prolonging the fruit shelf life.

Convolutional neural networks (CNNs) have attracted extensive attention in food quality analysis, owing to their outstanding ability to process multi-dimensional food quality data. This review summarizes the research progress and potential development trends of 1D-CNNs, 2D-CNNs, and 3D-CNNs in food quality evaluation, with a specific focus on their applications in three key data types: spectral data, image data, and spectral-spatial fused information. Nevertheless, the application of CNNs in food quality analysis still faces several persistent challenges, such as issues related to data quality, high model complexity coupled with poor interpretability, substantial computational costs, and inadequate model generalization. This review can shed new insights for promoting the wider adoption of CNNs in the food industry, and further drive the development of more intelligent and sustainable food quality perception systems.

The aim of this study was to optimize ultrasonic-microwave cooperative extraction (UMCE) conditions for flavonoids from Citri Reticulatae Pericarpium (CRP) and to evaluate the antioxidant activities of the purified flavonoid compounds. Using a Box-Behnken design for the experimental study, the influence of each variable on yield was determined, and the optimal conditions for the extraction of these compounds were discovered. The optimal parameters for maximum yield were determined to be 160 W ultrasonic power, 630 W microwave power, 68 °C temperature, 40 min, 57% ethanol and 1:20 ratio of solid to liquid. The primary flavonoids present were hesperidin (13.99 mg/g), nobiletin (4.02 mg/g) and tangeretin (3.80 mg/g). The antioxidant test results showed that hesperidin had greater antioxidant activity than both nobiletin and tangeretin. Based on the results of this study, ultrasonic-microwave cooperative extraction was shown to be an effective approach for enhancing flavonoid recovery from CRP. These findings provide useful insights into the extraction and antioxidant properties of CRP flavonoids and may contribute to the future development of value-added applications of CRP resources.