Food Engineering Reviews最新文献

Microwave sterilization has seen many innovative solutions to solve its primary problem of non-uniform heating. Since its initial studies in the late 1940s, there were solutions that were put forward to address, such as using mechanical holders to contain the inner pressure of the package with food materials, use of fluids instead of mechanical holders, use of strong containers or polymeric packages, and use of monolayer and multilayer packaging. But even all these solutions could not entirely solve the problem of non-uniform heating. After the 2000s, the rise in numerous numerical simulations and modelling software, opened the doors to further explore this field of research with more details and to numerically model the multi-physics phenomenon. However, studies have still not been sufficient to commercially deploy microwave sterilization systems to their full potential. Challenges such as temperature measurement, pressure measurement and control, usage of the right packaging material, and homogeneous heat distribution are still to be addressed, all while developing an energy-efficient process using numerical modelling and simulation tools. Hence, this review aims to study the microwave sterilization systems since the early days of research and the packaging aspect during the microwave sterilization process. The review also explores the potential held by the numerical simulation and modelling tools in this field of microwave sterilization.

This comprehensive review highlights the innovative applications of eco-friendly nanofibers in facilitating microbial activity and functionality for the advancement of sustainable agri-food systems. It provides an in-depth exploration of nanofiber-based biocomposites, with a specific focus on the encapsulation of bacterial cells within nanofibers. The review emphasizes the pivotal role of advanced 3D nanostructured scaffolds, appropriately designed for the encapsulation and survivability of these bacterial cells in response to specific environmental triggers. Furthermore, this paper delves into the utilization of nanofibers as nanocarriers to enhance the functionality of bacteria. It illustrates the need for comprehensive safety assessments, especially considering the potential risks involved. The assessment establishes a connection between the technical discussions and the environmental regulations that support the implementation of sustainable practices within the agri-food sector. The review highlights the vital role played by international guidelines, such as those established by the United Nations Environment Program (UNEP) and the Food and Agriculture Organization (FAO), in guiding the formulation of national and regional policies. By interconnecting these strategic principles with technological advancements in nanofiber technology, the review favors the incorporation of “green”, eco-friendly nanofiber production via an electrospinning method to revolutionize the agri-food sector. This holistic approach aims to address current challenges, paving the way for sustainable progress.

Regardless of the targeted microbe type, a thermal or nonthermal food preservation or disinfection method’s efficacy is primarily assessed based on its kinetics. Yet, there is growing realization that inactivation kinetics and the individual microbes’ spectrum of vulnerabilities or resistances to a lethal agent are two sides of the same coin. This creates the possibility to convert traditional survival data plotted on linear or semilogarithmic coordinates to temporal distributions of the individual microbes’ deactivation, or vice versa. Such conversions are demonstrated with simulated microbial survival patterns generated with different kinds of survival models: the two-parameter Weibull distribution of which the single-parameter loglinear model is a special case, the normal, lognormal, and Fermi distribution functions, which imply that complete microbial inactivation is theoretically impossible, the three-parameter Gompertz survival model which allows for definite residual survival, and the three-parameter version of the beta distribution function, allowing for a definite thermal death time beyond which no survivors will ever be found. Also provided are simulated examples of the survival patterns of mixed microbial populations, and they all demonstrate that the common shapes of microbial survival curves do not contain enough information to infer whether the targeted microbial population is genetically or physiologically uniform or a mixture of subpopulations. The presented analysis lends support to the notion that any proposed microbial survival kinetic model’s validity should be tested by its ability to predict survival patterns not used in its formulation and not by statistical fit criteria.

Freezing is a widely used technology for food processing that not only lowers the temperature of food below its freezing point but also inhibits microbial activity and slows down biochemical reactions to enable long-term preservation. However, the freeze thawing cycle can cause various chemical and physical damages to food, which are the main influencing mechanisms of low-temperature preservation. The size of ice crystals determines the degree of physical damage to cells, which has a significant impact on the freezing quality. Magnetic field (MF) treatment is a physical method that has been found to be milder, more effective, and have no obvious side effects compared to chemical treatments. Numerous studies have reported that MF promotes the cold storage of food, prolongs shelf life, inhibits ice crystal nucleation, increases supercooling, accelerates freezing speed, and reduces ice crystal sizes significantly. However, the role of MF in ice nuclei formation is still unresolved, and there are inconsistencies in research results and a lack of clear understanding of its potential mechanism. This paper aims to introduce the influence of MF on the formation and growth of ice crystals, summarize freezing curves on water and salt solutions, and analyze MF applications from two aspects: the thermodynamic mechanism and molecular dynamics point of view for freezing processes. Additionally, it discusses the problems encountered in recent researches and presents future development trends. The conclusion can be drawn that MF demonstrates great application potential in the field of freezing processes and food quality attribute evaluation. However, many questions remain with little consensus in the literature regarding their roles, and the mechanism of action is not unified. The application of MF in food freezing processes is still challenging. This paper hopes to provide guidance for future work on food freezing and contribute to the advancement of this field.

Ohmic heating (OH) of food has been investigated for many years as an alternative to conventional heating because it allows fast and homogeneous heating. The processing parameters that influence the most uniformity of the heating in OH are the electric field strength and the frequency. Therefore, recent trends have focused on studying the application of frequencies in the order of kHz and electric fields higher than 100 V/cm. In this regard, and considering only the applied field strength in a way to easily differentiate them, three ohmic systems could be distinguished: OH (< 100 V/cm), moderated electric fields (MEF) (100–1000 V/cm), and ohmic-pulsed electric fields (ohmic-PEF) (> 1000 V/cm). The advantages of applying higher electric fields (MEF and ohmic-PEF) over OH are, on the one hand, their much higher heating rate and, on the other hand, their capability to electroporate cells, causing the release of intracellular ionic compounds, and therefore, uniformizing the electrical conductivity of the product. This strategy is especially interesting for large solid foods where conventional heating applications lead to large temperature gradients and quality losses due to surface overtreatment. Therefore, the aim of this work is to review the state of the art of OH technologies, focusing on MEF and ohmic-PEF. The advantages and disadvantages of MEF and ohmic-PEF compared to OH and their potential for improving processes in the food industry are also discussed.

As a new generation of energy-carrying electromagnetic fields (after the electromagnetic field acts on the material, it is absorbed and converted into heat, providing energy for material drying), high-efficiency drying technology, microwave drying (MD), infrared drying (IRD), and radiofrequency drying (RFD) are widely used in agricultural product processing, but uneven drying is the main technical problem for the application and promotion of this technical means. Through the jet mode of pulse generated by compressed air, the materials can be evenly mixed on a large spatial scale. At the same time, air spouting has little effect on the energy transmission and distribution of energy-carrying electromagnetic fields, which is an important means to improve the uniformity of microwave and infrared efficient drying. This paper summarizes the working principle, innovative development, and numerical simulation of spouted bed in microwave and infrared drying; focuses on the cooperative working mode, drying object, and product characteristics of spouting technology in microwave hot air drying, microwave vacuum drying (MVD), and microwave freeze drying (MFD); and expounds the application and technical advantages of spouting technology in IRD. The feasibility of applying spouting technology in RFD was proposed. The review materials provide technical reference for improving the quality of microwave, infrared energy-carrying electromagnetic field efficient drying agricultural products.

A dynamic (e.g., non-isothermal) kinetic model of microbial survival during a lethal process or growth under favorable conditions is either in the form of a differential rate equation from the start or obtained from an algebraic static model by derivation. Examples of the first kind are the original and modified versions of the logistic (Verhulst) equation and of the second the dynamic Weibull survival or Gompertz growth models. In the first-order inactivation kinetics, the isothermal logarithmic survival rate is a function of temperature only. Therefore, converting its static algebraic form into a dynamic differential rate equation, or vice versa, is straightforward. There is also no issue where both the static and dynamic versions of the survival or growth model are already in the form of a differential rate equation as in the logistic equation of growth. In contrast, converting the nonlinear static algebraic Weibull survival model or the Gompertz growth model into a dynamic differential rate equation, requires replacement of the nominal time t by t*, defined as the time which corresponds to the momentary static survival or growth ratio at the momentary temperature. This replacement of the nominal time in the rate equation with a term that contains the momentary survival or growth ratio eliminates inevitable inconsistencies and renders the resulting dynamic model truly predictive. The concept is demonstrated with simulated dynamic microbial survival patterns during a hypothetical thermal sterilization where the temperature fluctuates and with simulated dynamic microbial growth in storage where the temperature oscillates.

To ensure food safety and uphold high standards, the food business must overcome significant obstacles. In recent years, promising answers to these issues have emerged in the form of artificial intelligence (AI) and machine learning (ML). This thorough review paper analyses the various uses of AI and ML in food quality management and safety evaluation, offering insightful information for academics, business people and legislators. The evaluation highlights the value of food quality assessment and control in consideration of growing consumer demand and regulatory scrutiny. The powerful capabilities of AI and ML are touted as having the potential to revolutionize these procedures. This study illustrates the numerous uses of AI and ML in food quality management through an in-depth exploration of these technologies. Defect detection and consistency evaluation are made possible using computer vision techniques, and intelligent data analysis and real-time monitoring are made possible by natural language processing. Deep learning techniques also provide reliable approaches for pattern recognition and anomaly detection, thus maintaining consistency in quality across manufacturing batches. This review emphasizes the efficiency of AI and ML in detecting dangerous microorganisms, allergies and chemical pollutants with regard to food safety evaluation. Consumer health risks are reduced because of the rapid identification of safety issues made possible by integrating data from diverse sources, including sensors and IoT devices. The assessment discusses issues and restrictions related to the application of AI and ML in the food business while appreciating the impressive progress that has been made. Continuous efforts are being made to improve model interpretability and reduce biases, which calls for careful evaluation of data quality, quantity and privacy issues. To assure compliance with food safety norms and regulations, the article also covers regulatory approval and validation of AI-generated outcomes. The revolutionary potential of AI and ML in raising food industry standards and preserving public health is highlighted on future perspectives that concentrate on new trends and potential innovations. This comprehensive review reveals that the integration of AI and ML technologies in food quality control and safety not only enhances efficiency, minimizes risks and ensures regulatory compliance but also heralds a new era of personalized nutrition, autonomous monitoring and global collaboration, signifying a transformative paradigm in the food industry.

Needleless electrospinning, an electrohydrodynamic process, is an emerging approach to producing nanofiber mats from an open liquid surface. Importantly, the approach offers 3–250 times higher production rates than needle-based electrospinning systems and has the potential to develop biocompatible and biodegradable nanofibers that have numerous applications in the food industry. The electrospinning potential of various biomaterials (from plant and animal sources) in needleless configurations is highlighted in this review. Also, the factors influencing the production rate and quality of needleless electrospun nanofibers are emphasized. Further, the reported uses of needleless electrospun nanofiber mats in food applications like packaging, filtration, bioactive encapsulation, enzyme immobilization, and food quality sensing are presented. Finally, challenges and areas to be explored further are summarized, considering prospects. Electrospun nanofibers are valued for their characteristics and unique capabilities. However, often, scale-up production is challenging, limiting its usage in multiple commercial applications. Overcoming this concern, needleless electrospinning is a viable approach for scaling up the production of nanofibers. Offering properties on par with conventional electrospinning, the needleless approach is finding expanding avenues in different sectors.

For high-moisture foods, the water latent heat of fusion during a phase change process causes a significant discontinuity in the temperature-dependent apparent specific heat of food products, which leads to complications during the numerical solution of heat transfer problems. The discontinuity in the apparent specific heat as a function of temperature can be alleviated by smoothing. Previously, a piecewise approximation smoothing method was developed and extensively used. In this study, different approaches which are based on curve fitting, the use of a sigmoid function, and data interpolation were developed. The performance of these methods in numerical simulations of food freezing and thawing processes was evaluated. The heat transfer model was implemented with the MATLAB PDE Toolbox. Simulated temperature profiles of representative freezing/thawing processes showed a reasonable agreement with experimental values collected from the literature. The optimal smoothing method showed comparatively less numerical oscillation, higher accuracy, faster computation speed, and simplicity in implementation. Recommendations were provided for the utilization of the smoothing methods under different circumstances.