Comprehensive Reviews in Food Science and Food Safety最新文献

Nonuniformity is the most critical yet unresolved bottleneck limiting the industrial adoption of multi-physical field drying (microwave, radio frequency, infrared, and ultrasound) for fruits and vegetables. While individual physical field technologies and AI applications have been reviewed separately, a conceptual framework that explains how nonuniformity originates, amplifies, and can be intelligently controlled is currently lacking. This review provides a problem-driven analysis of nonuniformity in physical field drying, proposing a three-stage cascade framework (Initiation → Amplification → Termination) to elucidate the multi-scale coupling between microscopic energy defects and macroscopic quality failure. We further critically evaluate the transition from black-box artificial intelligence (AI) modeling to advanced closed-loop intelligent control strategies involving physics-informed neural networks (PINNs) and digital twins, structured along a perception–prediction–control paradigm. The cascade framework reveals that initial minor heterogeneities are self-reinforced through positive feedback loops, necessitating early-warning prediction. AI-driven adaptive control, coupled with synergistic cross-field designs, may provide opportunities to interrupt this amplification process at early stages. We provide a strategic roadmap emphasizing multimodal sensing and physics-based hybrid modeling to achieve precision, uniformity, and sustainability in next-generation industrial drying systems. This review offers a distinctive problem‑oriented perspective that complements prior technology‑centric surveys by placing nonuniformity as the central narrative and offering a conceptual framework for its prediction and control.

Mechanical damage caused by vibration, impact, and compression during postharvest handling, transportation, and distribution is one of the main factors leading to losses and quality deterioration of fruits and vegetables. Cushioning packaging has therefore become an effective strategy for mitigating mechanical damage and maintaining produce quality. However, most conventional cushioning materials are petroleum-based plastics. With increasing environmental pollution and growing demands for sustainable development, the development of renewable and potentially lower-impact cushioning packaging materials has become an important research focus. This review provides an overview of recent advances in cushioning materials for fruit and vegetable transportation. The physiological and biochemical changes and associated quality deterioration of fruits and vegetables under mechanical stress are analyzed, including bruising, firmness loss, water loss, metabolic disturbance, changes in bioactive compounds, and decay development. The effectiveness of different cushioning systems in mitigating mechanical damage and maintaining postharvest quality is also discussed. The major raw materials used in cushioning packaging are classified according to their plant-based, animal-based, synthetic, and inorganic origins, and their functional properties and roles within material systems are summarized. In addition, the main fabrication methods are compared in terms of structure formation, mechanical performance, advantages, limitations, processing requirements, and industrial feasibility. Current challenges related to production cost, scalability, humidity sensitivity, food-contact safety, recyclability, regulatory requirements, and life cycle sustainability are further considered. This review provides a theoretical basis and practical reference for the future development and customized design of cushioning packaging materials with improved performance.

Ripened washed-rind and long-ripened cheeses owe their prized sulfurous, savory character to intensive proteolysis and amino-acid catabolism; the same activity, when poorly controlled, also generates sensory off-flavors and toxic biogenic amines (BAs). Histamine and tyramine reach up to approximately 2000–2500 and 1000–2000 mg/kg in extreme samples, although most cheeses contain far less, so that a 30-g portion of a high-histamine cheese can exceed the 50-mg per-meal intake regarded as without adverse effect in healthy adults. Flavor formation and chemical safety have traditionally been studied apart. This critical review reframes them as two outcomes of one metabolism: Proteolysis liberates a shared free amino-acid pool from which volatile sulfur compounds (VSCs) and BAs arise. Because the principal VSCs derive from methionine whereas the major BAs derive from histidine, tyrosine, ornithine, arginine, and lysine, we treat the branches not as direct competitors for one substrate but as metabolically coupled fates linked by shared proteolytic supply, overlapping physicochemical controls and microbial cross-feeding. Integrating evidence across cheese families, we reclassify the ripening microbiota into condition-dependent functional guilds, formalize metabolic bivalence (organisms that both generate flavor and degrade amines), and define a sensory inflection point separating the windowed VSC dose–response from the monotonic BA hazard. We critically appraise multi-omics, volatilomics, biosensors, machine learning, and digital twins, and outline a precision-fermentation roadmap. Current, largely in vitro, and single-variety evidence is consistent with, but does not establish, controllable decoupling, which we frame as a testable hypothesis that recasts cheese quality as a controllable metabolic-allocation problem.

Emulsions serve vital roles in the food industry, including structural design and delivery of functional components. As thermodynamically unstable systems, emulsions undergo various destabilization processes over time. Therefore, understanding the instability mechanisms of emulsions and how to combat them have been long-term research topics. Although extensive research has focused on the impacts of the aqueous phase and emulsifiers on emulsion stability, the regulatory role of the oil phase has long been undervalued, and the underlying mechanisms remain to be fully elucidated. This review mainly summarizes the influence of the oil phase on the formation and stability of food emulsions based on reported research, aiming to provide useful principles and rational references for future research. We focus on destabilization phenomena and mechanisms, as well as the effects of the physicochemical properties of the oil phase, including polarity, carbon chain length, degree of unsaturation, oxidation state, and other physical attributes such as density, viscosity, and water solubility. From a multi-scale perspective, we discuss the mechanisms by which the oil phase regulates emulsion formation and stability, including the adsorption kinetics, interfacial thickness, and interfacial rheological properties of emulsifiers, as well as the droplet size distribution and zeta potential of emulsions. In addition, the adaptability of various emulsifiers with specific oil phases is discussed, with emphasis on challenging systems including volatile essential oils, oxidation-prone polyunsaturated lipids, and aerated emulsions. This review highlights the pivotal role of the oil phase and provides a theoretical basis for the rational design and quality control of food emulsions.

Mushrooms are a novel and sustainable source of dietary protein with potential applications in the food system. Proteins found in mushrooms have balanced amino acids along with moderate digestibility. Mushroom proteins have a wide range of applications, and they are currently being used as fortifiers, dairy alternatives, meat analogs, and as functional ingredients. However, the complex native structure of mushroom proteins limits their functional applications, such as solubility, emulsifiability, and foaming properties. The existing reviews primarily emphasize the nutritional, extraction, and bioactive aspects of mushrooms or mushroom by-products, whereas the present review discusses protein extraction methods, modification strategies, structure–function relationships, and industrial applications, as well as food product development using modified mushroom proteins. Various modification and processing strategies, such as ultrasound-assisted processing, enzymatic hydrolysis, and pH-shifting, have been explored to enhance the yield and functional characteristics, such as solubility, emulsification, and digestibility of mushroom proteins, and ∼90% protein solubility has been achieved in certain studies. The combined ultrasound (20 kHz, 100% amplitude, 5 min, continuous mode) and TGase treatment (TGase, 0.4% w/v) of Trametes versicolor protein showed the higher oil-holding capacity (2.09%) and foaming capacity (123.1%) compared to control (1.43% and 57.7%, respectively), whereas, the ultrasound in combination with pH (pH 12) showed better in vitro digestibility (93.72%) than control (81.15%). With proper technological advancements, mushroom proteins can serve as a low-cost, high-return solution that supports both human nutrition and sustainable agricultural growth. However, challenges such as large-scale production, process standardization, and commercial availability need future research to enable food applications.

Optical nondestructive evaluation has become an indispensable tool for quality assessment in the food industry. Revealing light propagation mechanisms in multilayered fruit and vegetable tissues improves detection model accuracy and robustness. In fact, most natural and processed fruit and vegetable materials inherently exhibit layered structures, leading to inevitable deviations in optical signals interpretation and quality prediction. The complex structure and heterogeneous composition of fruit and vegetable matrices pose great challenges to light–tissue interaction analysis. This review summarizes the layer-specific differences in optical properties based on structural and compositional heterogeneity of fruit and vegetable matrices, using representative cases of other food matrices for comparison. It further addresses light propagation in multilayered fruit and vegetable tissues together with research on the optimization of detection parameters. Finally, a unified framework is proposed that integrates physicochemical properties, optical properties, and photon transport simulations to achieve mechanism-guided optimization for nondestructive detection. Notably, the advances of Monte Carlo (MC) simulation empowered by artificial intelligence (AI) are highlighted in denoising, accelerating computation, and improving prediction accuracy. AI-assisted MC simulation provides support for the efficient and high-precision prediction of light propagation in multilayer tissues, and lays a solid foundation for the progress of food photonics.