Food Engineering Reviews最新文献

Radio frequency (RF) heating has emerged as a key innovation in food processing operations such as drying, pasteurization, and thawing due to its ability to deliver rapid and volumetric heating. However, the inherent heterogeneity of food matrices and their complex interactions with electromagnetic fields often lead to uneven electric field distribution, resulting in heating inconsistencies and potential quality deterioration. Addressing these challenges requires strategies that enhance heating uniformity while preserving food quality. A promising solution is the integration of RF heating with complementary processing technologies. Hybrid techniques such as plasma treatment, cold shock, ultraviolet (UV) irradiation, ultrasound, infrared heating, and high hydrostatic pressure processing can improve heating efficiency and mitigate the limitations of RF heating. This review systematically examines the principles of RF heating and its integration with emerging technologies. It explores the mechanisms underlying heating non-uniformity, evaluates existing solutions, and identifies future research priorities. Special attention is given to the development of customized RF heating strategies tailored to the physicochemical properties of different food matrices. Furthermore, the integration of intelligent control systems, algorithmic optimization, and interdisciplinary advancements is expected to enhance the precision and efficiency of RF heating, offering innovative solutions for high-performance thermal processing while maintaining superior food quality.

Complex coacervation is a phase separation phenomenon between two oppositely charged colloids, such as proteins and polysaccharides, when mixed in a solution. The attractive forces between the oppositely charged particles lead to the formation of a coacervate phase, which is a liquid, dense, and polymer-rich phase. Animal-based proteins and polysaccharides are commonly used to prepare high-quality bioactive compounds and are widely used to produce complex coacervations with desirable physicochemical properties. During complex coacervation, utilizing animal-based proteins, such as casein, offers several advantages. However, challenges and concerns are associated with their production, including high costs, environmental impact, the spread of animal diseases, and the emergence of drug-resistant pathogens. As an alternative to animal-based proteins, plant-based proteins are gaining traction in complex coacervation, addressing several challenges associated with animal-based protein production. Plant-based proteins provide a range of benefits that align with environmental sustainability, cost-effectiveness, and reduced concerns about animal diseases. Some key advantages of employing plant-based proteins in complex coacervation include sustainability, biocompatibility, reduced ecological impact, disease resistance, diversity of sources, consumer demand, and allergen considerations. Various physical, chemical, and biological processes are employed to enhance the characteristics of plant-based protein-polysaccharide coacervates. This comprehensive review elucidates recent advancements in the microencapsulation of bioactive compounds through complex coacervation utilizing plant-based protein-polysaccharide systems. This review serves as a valuable resource for summarizing the current state of research, identifying limitations and gaps in knowledge, and discussing challenges within the field.

The Mediterranean diet is known for its health benefits, mainly due to its diverse ingredients, such as fruits, vegetables, grains, nuts, legumes, and olive oil. This review examines the reformulation and characterization of these Mediterranean ingredients using several novel food processing and analytical technologies. Reformulation technologies discussed include microwave pasteurization, microwave vacuum drying (VMD), pulsed electric field (PEF), high-pressure homogenization (HPH), freeze drying, high hydrostatic pressure (HHP), and cold plasma technology (CP). Characterization technologies covered include Nuclear Magnetic Resonance (NMR), Electron Paramagnetic Resonance (EPR), and Near Infrared (NIR) spectroscopy. Nonthermal techniques such as PEF, HHP and CP are particularly noteworthy for their ability to preserve nutritional and sensory qualities without using high temperatures, that can degrade sensitive compounds. The main requirement for these processing methods is to ensure that the food retains its beneficial nutrients and natural flavors while extending its shelf life. Analytical techniques like NMR, EPR, and NIR spectroscopy provide detailed insights into the molecular composition and quality of food products. These techniques allow for precise optimization of processing methods, ensuring the best possible quality and nutritional value. The integration of these advanced processing and analytical techniques with traditional Mediterranean ingredients offers significant advancements in food science, improving food quality, nutritional value, and the sustainability of food production. This review aims to provide a comprehensive understanding of how these novel technologies can be applied to optimize the nutritional and sensory qualities of Mediterranean ingredients while enhancing their health-promoting capabilities.

Olive oil holds a significant position in the global vegetable oil market, often reaching high prices compared to other vegetable oils. However, like other oils, it is vulnerable to oxidation, which can degrade its quality during storage, making it essential to determine its shelf-life. So, kinetic or empirical models have been developed to estimate how long olive oil can maintain the legal quality standards necessary for its commercial classification or to be marketed with nutritional or health claim. This study reviews recent advancements in modelling approaches to predict the shelf-life of olive oil under different storage conditions, namely storage duration (from 2 months to 2 years), temperature (20–50 ºC), and light exposure (light versus dark storage). Most models estimate the timeframe in which olive oil remains compliant with regulatory requirements for specific commercial grades, namely extra virgin olive oil, with fewer models addressing health-related claims. Developed models include pseudo zero-, pseudo first-, and pseudo second-order kinetic models and empirical models, derived from experimental data on the oil’s chemical stability over time. While empirical models can be highly accurate, they often require extensive chemical data, including for compounds for which no legal thresholds exist, and complex statistical techniques, limiting their use by non-specialists. In contrast, kinetic models offer simpler and user-friendly mathematical equations. Nonetheless, olive oil’s shelf-life predictions remain influenced by factors such as initial oil composition, packaging materials, and storage conditions, underscoring the ongoing need to refine the predictive models.

The drying of fresh ginger is crucial for establishing its edible and medicinal worth during post-harvest management.Microwave drying (MD) represents a high efficiency and environmental sustainability technology that continues to garner attention for its pivotal role in advancing the sustainable development of fresh ginger. In light of this, this paper summarizes the fundamentals of microwave technology and the application of different drying modes in the drying fresh ginger, and systematically explores the parametric effects the MD of fresh ginger, its quality characterization and challenges. The findings indicate that dielectric loss serves as the central mechanism due to water as a typical dipole polarization inducing molecular vibration, rotation and friction to generate heat in MD process. The issues of non-uniform energy distribution, variable drying outcomes and the scaling-up of industrialization are still major challenges for microwave applications. In the future, potential solutions should be to strengthen the industrialization of microwave technology. In particular, it is of great significance to develop efficient and stable scale equipment, integrate artificial intelligence to optimize temperature and humidity control, and conduct in-depth research on microwave-material interaction mechanism based on numerical simulation. These technological breakthroughs will accelerate the industrial large-scale application of fresh ginger MD.

Food packaging in space missions is a challenge because of the specific needs of the food by the explorers as they go through long distances in space. The scope of this review paper is, therefore, aimed to discuss recent advances in specific food packaging practices for space missions based on the materials, technologies, and methodologies in coping with environmental and technological challenges of space. That enables this paper to elaborate on other contemporary packaging materials, like biodegradable polymers and edible films, which are both biodegradable and protective of goods against the space environment. In addition, it assesses smart packaging systems for foods, which can trace the quality and contamination of food items and technologies such as vacuum packaging and modified atmospheric packaging for longevity. Based on the review of the literature on current research, issues, and future developments, this paper identifies theoretical and practical implications of the multisource approach to designing safe, sustainable, and high-performance packaging for space food. The study also reports specific research gaps and offers possible trends for future developments regarding this central feature of space mission planning.

The growing demand for sustainable and high-performance food packaging has led to the exploration of green nanomaterials as viable alternatives to synthetic counterparts. Traditional packaging materials often struggle to provide sufficient protection against oxygen, moisture, and UV light, which accelerates food spoilage and reduces shelf life. This review examines the role of biodegradable and bio-based nanomaterials; such as cellulose nanocrystals; carbon dots, and sulfur quantum dots, in enhancing barrier properties essential for food preservation. A comparative analysis between synthetic and green nanomaterials denotes the urgent need for eco-friendly alternatives, emphasizing their sustainability, biodegradability, and reduced environmental footprint. Main mechanisms contributing to barrier enhancement, including the tortuosity effect, gas and moisture transmission control, and nanoparticle morphology influence, are critically analyzed with recent experimental data. Equally, the impact of nanomaterials on the crystallization behavior of film substrates is discussed to highlight their role in improving structural integrity and overall performance. The review also explores the integration of these nanomaterials into flexible and rigid food packaging systems, with an emphasis on their ability to provide antimicrobial activity and UV protection. Furthermore, while the potential of green nanomaterials is significant, this review addresses primary hurdles such as toxicity concerns, environmental impact, and scalability issues. The role of regulatory frameworks in ensuring food safety and consumer protection is also discussed. Finally, future perspectives on advancing sustainable nanotechnology in food packaging are proposed, identifying leading research directions, including the development of multifunctional nanomaterials that enhance barrier properties while offering active sensing capabilities for real-time food quality monitoring. By bridging the gap between experimental findings and practical applications, this review provides outlook on how green nanomaterials can revolutionize the food packaging industry toward a more sustainable future.

A peaking static (isothermal) microbial growth curve recorded in an isolated habitat is viewed as a manifestation of a conflict between the tendency of healthy cells to multiply by division, and the habitat’s progressive depletion of resources and deterioration which is intensified by the rising population’s density. This scenario can be described mathematically by the product of a monotonically rising growth term such as a stretched exponential (Weibull) term, representing the habitat’s uninterrupted growth potential, by a stretched exponential (Weibull) decay term, representing the fall of the cells’ survival probability and increased mortality rate. An alternative is to have the growth potential represented by the Verhulst/logistic differential rate model, and the decline by a superimposed falling log-logistic algebraic term that becomes negative as growth turns into mortality. Yet another alternative is a scaled version of a beta-distribution function-based model, which captures both the rise and fall regimes in a single algebraic expression. For dynamic (notably non-isothermal) growth, a convenient model has the basic structure of the static Verhulst/logistic rate model equation, except that its parameters are entered as functions of time. In contrast with the other model equations the Verhulst/logistic mode conversion from a static to dynamic state does not require the use of inverse functions, and hence special programming.

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Traditional assessment (e.g., visual inspection and biochemical analysis) is the prevailing method for meat quality assessment in the food industry. However, this approach is time-consuming, laborious, costly, and subjective. In response to the inherent limitations associated with conventional assessment, RGB (red–green–blue) cameras, hyperspectral imaging, and structured illumination reflectance imaging are gaining ample attention in the food industry. These techniques are increasingly applied to various aspects of meat quality and safety assessments, encompassing parameters such as tenderness, chemical composition, adulteration, and overall quality traits. This review focuses on scientific articles published in the past five years that leverage these machine vision techniques to address challenges in the meat processing industry. These machine-vision techniques are briefly introduced, shedding light on their principles and applications. Moreover, this review identifies the challenges and strengths associated with these technologies. To provide comprehensive insights, this review includes thoughtful solutions to overcome the challenges posed by these advanced techniques in the context of meat quality assessment within the food industry. Furthermore, we suggest a novel approach for meat processing which is integrating hyperspectral imaging with structured illumination reflectance imaging for easy detection of both surface and internal quality assessment in meat.

The incorporation of Artificial Intelligence (AI) could deliver a new era in food manufacturing, marked by increased operational efficiencies, higher product quality, and better safety standards. This review offers an in-depth examination of the field's evolution, outlines the leading AI methodologies, and investigates their applications in food manufacturing. This review begins with an introduction to AI and its historical context before classifying the main AI methods used in food manufacturing as machine learning, computer vision, robotics, and natural language processing. Machine learning has emerged as an AI application in many areas of food manufacturing due to its ability to learn from data and make predictions. Computer vision is a popular form of AI and plays an important role in visual inspections, ensuring product consistency and detecting defects. Robotics, in conjunction with AI, has automated a wide range of labour-intensive tasks, from packaging to palletizing, resulting in significant improvements in operational efficiency. Natural language processing has found applications in customer service and compliance, allowing for more efficient interactions and regulatory compliance. AI applications in food manufacturing are numerous and diverse and key areas such as ingredient sorting, quality assessment, process optimization, and supply chain management are highlighted in this review. Finally, we present issues that the industry is encountering in the implementation of AI, as well as a research agenda based on the findings. In-depth analysis provided in this review including the field's evolution, main AI methods used, and their applications in food manufacturing, can provide valuable insights for researchers, practitioners, and decisionmakers in applications of AI in food manufacturing.