Food Engineering Reviews最新文献

Artichoke (Cynara cardunculus var. scolymus) is a traditional component of the Mediterranean diet, and an important source of bioactive and nutritional compounds (phenolic compounds, inulin, dietary fiber, vitamins, minerals, etc.). However, an important amount of artichoke by-products is discarded during industrial processing, whose waste represents a rich source of bioactive and nutritional compounds. A current trend for food engineering is the valorization of these rich plant by-products to contribute to the circular economy model and resource optimization. However, the edible part of the artichoke and its by-products have different compositions and behave differently when subjected to several food manufacturing operations. This behavior has not been deeply studied in many cases and especially for artichoke by-products. To contribute to that, the first part of this review deeply reviewed the bioactive and nutritional profile of artichoke by-products, as well as its comparison with the artichoke edible part. In the second part, we reviewed the effects of industrial operations (conditioning, transformation, preservation) on the bioactive and nutritional compounds of artichoke by-products and edible parts. Therefore, we hope that this review will be a valuable tool for food engineering to develop new processes for the conservation and revaluation of these important bioactive and nutritional compounds, both from the edible part of the artichoke and its by-products.

This review article explores the significant role of in silico simulations as complements to in vivo and in vitro experiments, particularly in enhancing our understanding of gastric flow, digestion, and drug dissolution. By synthesizing decades of research on numerical stomach models, this paper highlights the profound impact computational fluid dynamics (CFD) and other simulation techniques have on elucidating the influence of gastric motility and the physical properties of stomach contents on nutrient absorption and drug release. These simulation studies provide more detailed information for us to advance our understanding of drug delivery in stomach and to support the formulation of functional foods tailored for specific metabolic health requirements. Additionally, these models offer valuable forecasts that aid in refining surgical methods and therapeutic approaches, especially for managing conditions such as gastroparesis. By advancing our fundamental understanding of digestive mechanisms, in silico studies contribute significantly to the development of innovative treatments and the enhanced management of gastrointestinal disorders, underscoring the transformative potential of computational tools in nutritional science and biomedicine.

Pectin, a versatile biopolymer found in plant cell walls, is crucial in the food, pharmaceutical, and cosmetic industries due to its gelling, thickening, and stabilizing properties. As demand increases, efficient and sustainable extraction methods are essential to maximize yield and quality from agro-industrial byproducts. This review critically evaluates and compares conventional and emerging pectin extraction techniques, focusing on their potential to enhance yield and quality while promoting sustainability. The synthesis of data includes traditional methods (acid and enzymatic processes) and novel assisted extractions such as Microwave (MAE), Ultrasound (UAE), High Hydrostatic Pressure (HHP), Manosonication Extraction, Radio Frequency, Electromagnetic Induction Heating, High-Speed Shearing, Deep Eutectic Solvents (DES), Subcritical Water (SWE), Ohmic Heating, Pulsed Electric Fields, Moderate Electric Fields and Induced Voltage (IVAE). The analysis encompasses yield, quality parameters, processing time, and environmental impact. Results indicate that modern extraction methods outperform traditional techniques in terms of yield and quality. Notably, MAE and UAE achieve similar yields in less time compared to traditional methods, while HHP and IVAE methods produce pectin with enhanced gelling properties. DES and SWE extractions emerge as environmentally friendly alternatives, utilizing biodegradable solvents. Despite their advantages, these innovative techniques face challenges such as high initial costs and the need for precise parameter control. This review underscores the transformative potential of these methods in pectin production, offering both performance enhancements and environmental benefits. Future research should prioritize scaling up these techniques for industrial applications, optimizing process parameters, and conducting comprehensive techno-economic analyses to balance efficiency, quality, and economic viability.

This comprehensive review highlights the significant strides made in the field of food freshness detection through the integration of deep learning and imaging techniques. By leveraging advanced neural networks, researchers have developed innovative methodologies that enhance the accuracy and efficiency of freshness monitoring. The fusion of various imaging modalities, with sophisticated deep learning algorithms has enabled more precise detection of quality attributes and spoilage indicators. This multidimensional approach not only improves the reliability of freshness assessments but also provides a more holistic view of condition of the food. Additionally, the review underscores the growing potential for these technologies to be applied in real-time monitoring systems, offering valuable insights for both producers and consumers. The advancements discussed pave the way for future research and development, emphasizing the need for continued innovation in integrating these technologies to address the challenges of food safety and quality assurance in an increasingly complex and dynamic market.

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Processing of food should adopt an energy efficient path such as renewable energy, instead of conventional energy intensified units. Solar energy is one such option, which is cost effective and energy efficient. But developing a cost-effective solar product with optimised design factors to produce premium quality food is bit challenging. The solar components are to be designed and selected to attest to maximum utilisation of solar energy and its conversion. The review is structured into five parts. The first part explores the different types and limitations of solar dryer, the second part focuses on various design and fabrication aspects of each and every component of a solar dryers, the third part focusses on selection criteria, fourth part elaborates on the environment, economic and social aspects of solar dryer and fifth part focusses on challenges and future prospects. SWOT analysis of various types of solar dryer is also presented in this work. Upgrading solar dryers with modern technologies for maximum efficiency with distributed production and feasibility of drying multiple food products, will yield higher payback. However, the quality of dried food, especially the aroma and nutrition value will significantly affect the revenue generation.

Recent developments in alternative drying techniques have significantly heightened interest in innovative technologies that improve the yield and quality of dried goods, enhance energy efficiency, and facilitate continuous monitoring of drying processes. Artificial intelligence (AI)-enabled optical sensing technologies have emerged as promising tools for smart and precise monitoring of food drying processes. Food industries can leverage AI-enabled optical sensing technologies to gain a comprehensive understanding of drying dynamics, optimize process parameters, identify potential issues, and ensure product consistency and quality. This review systematically discusses the application of selected optical sensing technologies, such as near-infrared (NIR) spectroscopy, hyperspectral imaging, and conventional imaging (i.e., computer vision) powered by AI. After covering the basics of optical sensing technologies for smart drying and an overview of different drying methods, it explores various optical sensing techniques for monitoring and quality control of drying processes. Additionally, the review addresses the limitations of these optical sensing technologies and their prospects in smart drying.

Ethylene is a natural plant hormone crucial in fruit ripening and senescence. Excessive ethylene production can lead to premature spoilage of fruit and vegetables. Cold plasma as a gas purification technology can be used for ethylene synergism control. This review provides a comprehensive overview of ethylene as a plant hormone, including its sources, biosynthesis, and roles. It explores the pathways of plasma generation and examines the chemical properties of plasma. The primary focus is recent progress in cold plasma technology for ethylene synergism control and insights on advanced plasma-integrated catalysts and plasma-integrated food packaging are discussed. Using plasma-integrated catalysts and food packaging shows promise for ethylene control in various applications. The synergistic effects resulting from the plasma-integrated catalyst systems improve the energy efficiency of the process and inhibit the formation of by-products and the cold plasma-integrated food packaging system effectively inhibits ethylene autocatalysis while maintaining the integrity of the produce. Furthermore, the integration of intelligent systems for ethylene monitoring is identified as an area of opportunity for further research and development.

Artificial intelligence (AI) is a cutting-edge technology that emulates human-like intelligence or human brain-like cognitive abilities. Through AI, machines have become capable of performing tasks previously reserved for human expertise. This paper explores the vast array of applications for AI in agriculture, spanning from pre-harvest operations to post-harvest activities. The applications encompass precision farming, controlled environment agriculture, food processing, post-harvest handling, and storage. Integrating AI into each stage of the food processing industry has led to substantial enhancements in efficiency, product quantity, and quality. This work provides a comprehensive summary of the applications of AI in the food processing industry, delving into the various methodologies developed to address challenges within the food supply chain that profoundly impact the food processing sector. The focus is on how AI technologies have revolutionized and optimized different unit operations in food processing. By harnessing AI's potential, industries have experienced improvements in yield, minimized waste, and streamlined production processes. The paper underscores the transformational role of AI in shaping the future of agriculture and food processing, highlighting its potential to alleviate pressing challenges in food production, distribution, and sustainability. Moreover, it emphasizes the need for continued research and development to ensure responsible and ethical AI adoption while harnessing its benefits to meet the growing demands of a global population. Overall, the study aims to contribute to a deeper understanding of AI's revolutionary impact in reshaping the food processing landscape and ensuring food security for future generations.

The electrostatic spinning nanofibers have attracted more attention in recent years. It is reported that electrostatic spinning nanofibers play an important role in many fields such as pharmaceutics, biomedical, and environmental filtration, as well as in the field of foods, which was mainly due to their high specific surface area, high porosity and good functional ability. This paper introduces the concept, principles, and different preparation methods of electrostatic spinning technology. To better prepare researchers to “conceptualize” their research designs from the laboratory to the marketplace, the paper also describes electrospinning equipment at different scales and their limitations. In addition, the recent research progress and applications of electrostatic spinning nanofibers in the food industry are summarized. Also, the challenges and prospects are discussed for their further applications. This work may provide help to better understand the mechanism and application of this technology in food fields.

This comprehensive study delves into advanced dehydration techniques and processing technologies in the realm of coffee manufacturing. It offers a comparative analysis of these techniques, specifically focusing on green coffee beans and instant coffee production. The examination encompasses the pivotal steps of grading, roasting, grinding, extraction, and dehydration, which form the core of the coffee manufacturing process. In the context of instant coffee production, two primary dehydration methods, spray-drying and freeze-drying, are scrutinized for their roles in water removal from coffee extracts and slurries and their impact on final product quality and efficiency. This study emphasizes the significance of dehydration processes as the linchpin of manufacturing optimization, considering their prominence in coffee production plants. Furthermore, the research extends to investigate the diverse extraction techniques, additional processes, and critical technologies, such as agglomeration, used in the production of coffee instant powder. Quality control, life cycle analysis, and assurance are scrutinized to provide insights into the overall sustainability of coffee manufacturing. The examination also explores the environmental impact, byproducts, and nuanced properties of coffee powder across different production systems. In essence, this review serves as a valuable resource for industry professionals, researchers, and coffee enthusiasts, offering a holistic understanding of advanced coffee dehydration techniques and their impact on quality, efficiency, and sustainability in the context of both green coffee beans and instant coffee production.