Comprehensive Reviews in Food Science and Food Safety最新文献

Deep learning-based image recognition is increasingly reshaping food science, enabling intelligent systems for online grading, rapid quality evaluation, and food safety monitoring. Nevertheless, the adoption of such approaches in food-related domains is often hindered by fragmented practices, limited domain-specific guidance, and methodological inconsistencies. This review synthesizes a modular end-to-end workflow, spanning task formulation, model development, and application, specifically designed for food science. Three representative case studies are examined to illustrate common applications and practices, while highlighting recurring challenges such as limited data availability, inconsistent annotations, and obstacles to submodel integration that constrain reproducibility and scalability. A set of domain-specific strategies is proposed to address these challenges, covering task decomposition, dataset refinement, annotation and label management, image preprocessing, data augmentation, architecture selection, and submodel integration. Looking ahead, we suggest that future efforts prioritize the development of standardized toolkits—task guidance systems, unified modeling toolchains, and model integration platforms—to enable reliable, generalizable, and impactful computer vision solutions for real-world challenges in food science and technology.

Chinese acid-curd cheeses (CACCs) are known for their long history and distinctive acidification process. Although they are recognized as important sources of bioactive peptides (BPs), a comprehensive synthesis of current knowledge on the formation, bioactivity, and structure–activity relationships of CACC-derived bioactive peptides (CACCBPs) remains limited. To address this gap, this review summarizes and critically evaluates recent advances in the generation, identification, functional properties, and potential applications of CACCBPs. CACCBPs are predominantly generated through acid hydrolysis and microbial proteolysis of caseins, with β-casein serving as the primary precursor. The integration of peptidomics, molecular docking, network pharmacology, and complementary bioinformatics tools has significantly advanced the discovery and characterization of these peptides. CACCBPs exhibit a wide range of health-promoting properties, including antioxidant, hypoglycemic, antihypertensive, and immunomodulatory activities. Mechanistic studies revealed that CACCBPs exert their effects by modulating key signaling pathways (e.g., Keap1-Nrf2 and Nrf2/NF-κB/MAPK/PHD-2) and by interacting with potential receptors (e.g., Keap1, ACE, and α-glucosidase). This review also provides a systematic discussion of structure–activity relationships, emphasizing the roles of molecular weight, amino acid composition, and hydrophobicity in determining peptide function. Despite their promise, challenges remain in large-scale production, in vivo efficacy verification, and peptide stability improvement. Future research should integrate advanced technologies and interdisciplinary approaches, conduct comprehensive clinical evaluations of safety and efficacy, investigate absorption and metabolic pathways in detail, and enhance the stability and bioavailability of peptides to support their practical application in functional foods and health products.

Sensory attributes are the primary factors in the food product evaluation. However, traditional thermal processing often compromises the sensory qualities of foods, prompting the exploration of nonthermal technologies that preserve sensory attributes. Among emerging approaches, magnetic field (MF) treatment offers significant advantages in improving the sensory qualities of food products due to its noninvasive and residue-free potential. Therefore, this review deeply focused on the effectiveness of MF treatment on the sensory quality, particularly the flavor profile, texture properties, and coloration. MF has shown promise in improving flavor attributes by reducing degradation, modulating enzyme activity, and preserving volatile compounds; Concerning texture properties, MF contributes to delaying softening, modulating protein structure, and forming smaller ice crystals, thereby maintaining tissue integrity and improving texture properties; In terms of color, MF can inhibit enzymatic browning, modulate protein structure, and reduce respiration rates, enabling coloration retention and achieving more fresh-like qualities. In addition, outlining key challenges and future perspective were also discussed. Overall, MF interacts with food matrices by primarily modulating enzyme activity, protein conformation, and water behavior, influencing flavor, texture, and color profiles. This highlights that MF represents a promising nonthermal strategy for improving sensory quality in minimally processed food products.

The flavor complexity of mead is influenced by various factors, including the geographic origin of honey, botanical sources, fermentation processes, and the addition of fruits and herbs. Chemical characteristics of mead are regulated by factors such as honey origin, yeast metabolism, latitude, climate, light intensity, and fermentation parameters, which collectively affect the formation of volatile and nonvolatile compounds. This review examines the chemical profiling of mead, with a particular focus on detecting volatile compounds. Advanced analytical techniques like HS–SPME–GC–MS, RP–UHPLC–ESI–MS, and GC × GC–HRMS are employed to detect and quantify these compounds. Quantitative methods, such as the internal standard method and standard addition method, effectively mitigate interference from high-sugar matrices in mead, ensuring accurate results. The flavor characteristics of mead, especially pure mead, are primarily determined by the choice of honey, typically exhibiting floral, fruity, and sweet honey flavors. European meads are marked by phenolic compounds and fruity esters, Asian meads are rich in terpenes and phenolic compounds, North American and South American meads are characterized by methoxy-aromatic compounds and lactones, while African meads contain unique ester and sulfur compounds. Despite challenges like the lack of standardized methods and regional imbalances in research, standardizing methods and integrating “omics” technologies will help uncover regional characteristics in mead production and promote its global recognition and development.

The edible oil refining process is critical for improving oil quality and extending its shelf-life. By-products from refining, including gums, soapstock, spent bleaching earth (SBE), and deodorizer distillate (DD), are generated in large volumes and often discarded despite being rich in valuable phytonutrients such as tocopherols, phytosterols, and polyphenols. Valorization is a sustainable approach to address these by-products in response to the increasing demand for adapting sustainable practices in the food industry. This review focuses on the by-products resulting from the refining of the top three oilseeds, soybean, rapeseed/canola, and sunflower and examines their potential for sustainable valorization. To that end, available literature relating to the effects of chemical and physical refining processes on phytonutrient content is explored, with an emphasis on the losses of individual phytonutrients that occur during refining stages. Main strategies used for recovering these compounds from refining by-products, particularly DD, are discussed. Beyond recovery, the potential of biotechnological approaches for producing other valuable compounds, such as enzymes, is highlighted. Furthermore, the integration of phytonutrient recovery with microbial bioprocesses, such as fermentation, is suggested for refining by-products, such as DD, to address the remaining oily waste after phytonutrient recovery and achieve “zero-waste” concept. This approach can provide an opportunity to minimize waste, reduce environmental impacts, and align valorization with the principles of a circular economy. By exploiting all ingredients in by-products, this approach can maximize value addition and generate new economic opportunities.

Ultrasound technology, due to its unique acoustic cavitation effect, significantly enhances heat and mass transfer and is widely applied in unit operations of food processing. However, the common standing wave effect in conventional single-frequency power ultrasound creates alternating regions of acoustic pressure nodes and antinodes, resulting in a highly uneven distribution of the acoustic field. This makes it difficult to meet the dual requirements of the modern food industry for precise control and high efficiency in processing technologies. This comprehensive review aims to systematically integrate the molecular mechanisms and practical applications of multi-frequency power ultrasound (MFPU) in food processing, establishing a unified theoretical framework to elucidate its advantages over traditional single-frequency systems. Systematic literature analysis indicates that MFPU demonstrates significant advantages in food processing applications. Research reveals that these advantages stem from nonlinear interactions, which surpass the simple linear superposition model of traditional single-frequency systems. These synergistic effects generate a uniform cavitation field, effectively eliminating the inherent standing wave limitations of conventional single-frequency systems, and exhibit universal applicability across diverse food matrices ranging from protein modification to complex tissue processing. Studies confirm that MFPU represents a transformative technology in food manufacturing. It not only addresses the technical limitations of existing processing methods but also provides an integrated solution combining efficiency enhancement with quality preservation. Translating these proven advantages into industrial practice requires establishing a deeper understanding of the mechanisms at the molecular level, developing standardized parameters, and creating intelligent process control systems.

Nitrite (NO₂⁻), a critical inorganic nitrogenous compound, has extensive applications in the food industry. However, its excessive intake poses significant health and ecological risks. Therefore, the accurate quantitative detection of NO₂⁻ is of great importance for both scientific research and practical applications. In recent years, optical sensing technology has emerged as a key tool for NO₂⁻ detection in food samples, due to its high sensitivity, rapid response, and user-friendly operation. This paper provides a systematic review of the detection principles underlying typical optical sensing techniques, including ultraviolet–visible absorption spectroscopy/colorimetry, fluorescence spectroscopy, surface-enhanced Raman spectroscopy, and chemiluminescence/electrochemiluminescence. It highlights recent advancements in NO₂⁻ analysis using these techniques, both individually and in multimodal. Despite their many advantages, current optical sensing techniques for NO₂⁻ face several practical challenges, such as limited anti-interference capabilities, difficulties in synergistically optimizing sensitivity and selectivity, and issues with real-sample applicability. This paper explores potential solutions to these challenges in-depth and outlines the primary directions for future research. Optical sensing technology has made important breakthroughs in the field of nitrite detection, exhibiting considerable potential for application. In view of the existing technical problems and practical application challenges, it is urgent to deepen the research, so as to provide more reliable technical support for food quality monitoring.