Food Engineering Reviews最新文献

{"title":"From Stone Tools to (very) High Pressure: Pressure-Based Evolution in Food Processing","authors":"Robert Sevenich,&nbsp;Dietrich Knorr","doi":"10.1007/s12393-025-09422-9","DOIUrl":"10.1007/s12393-025-09422-9","url":null,"abstract":"<div><p>Stone tools were the oldest pressure-related food processing tools (approx. 3.3 million years ago) until the use of fire for thermal processing (approx. 0.5–0.3 million years ago) became the prime food processing aid. During the last 40 years, gentle, resource-efficient pressure-related technologies for partial replacement of thermal processes were developed and gained rapid dissemination and acceptance. This paper provides an overview of food processes where pressure is the key mode of action ranging from negative pressures (below 0.00001 MPa) to very high pressure (1400 MPa). Working principles, applications, advantages/limitations as well as needs and opportunities for these processes using dynamic or static pressures are presented. Based on the high number of existing and developing pressure-related unit operations, we propose a new pressure-based food processes classifications system organized in pressure ranges (max. 0.1, 1.0, 10, 100, 1000, &gt; 1000 MPa) embracing the temperature range used in food processing.</p></div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"645 - 670"},"PeriodicalIF":7.6,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12393-025-09422-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning in Cheese-Making: Methods, Applications, and the Future","authors":"Daniel Pardo,&nbsp;Manuel Castillo,&nbsp;Mehmet Oguz Mulayim,&nbsp;Jesus Cerquides","doi":"10.1007/s12393-025-09420-x","DOIUrl":"10.1007/s12393-025-09420-x","url":null,"abstract":"<div><p>Cheese-making is a complex process involving numerous stages, with multiple factors contributing and complex interactions occurring among the physicochemical elements involved. Understanding the process and optimizing its stages has attracted the attention of numerous investigations. In recent years, Machine Learning (ML) has established itself as one of the most advanced tools for data analysis and modeling thanks to its ability to capture complex and non-linear patterns. In the area of food science and engineering, these algorithms have started to be used as an alternative to more traditional statistical and mathematical prediction models. This paper explores the main research on ML applied to the study of cheese, from its production stages (i.e., fermentation or coagulation process) to the final product (i.e., detection of adulterations or food fraud). Particularly, we review 42 papers published between January 2014 and January 2025, with the aim of identifying common approaches. First, we present an explanation of the main concepts required to bring these approaches closer to researchers who are not experienced in applying ML. Then, we analyze the selected publications to detail the tasks of interest and the algorithms proposed to solve them. Finally, we detect gaps and opportunities to incorporate ML into future cheese research.</p></div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"505 - 531"},"PeriodicalIF":7.6,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12393-025-09420-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping the AI Landscape in Food Science and Engineering: A Bibliometric Analysis Enhanced with Interactive Digital Tools and Company Case Studies","authors":"Jordan Pennells,&nbsp;Peter Watkins,&nbsp;Alexander L. Bowler,&nbsp;Nicholas J. Watson,&nbsp;Kai Knoerzer","doi":"10.1007/s12393-025-09413-w","DOIUrl":"10.1007/s12393-025-09413-w","url":null,"abstract":"<div><p>The proliferation of research on Artificial Intelligence (AI) in food science and engineering has made it increasingly difficult to synthesise relevant insights effectively. Although AI adoption in the food industry has grown, it lags behind sectors like finance and healthcare due to the complexity of food systems, including high process variability, risk aversion towards novel technologies, and constrained investment appetite. Historically, computational techniques and AI-adjacent technologies like expert systems and empirical modelling have supported food research and development for decades. More recently, AI applications have broadened to include process control, food safety, ingredient and product quality, sensory evaluation, traceability, and supply chain management. In response to the rapid increase in AI-related food science publications – particularly since 2019 – this review introduces tools for dynamically synthesising and exploring this evolving knowledge base. We present an interactive dashboard that integrates a curated dataset of food AI review articles with advanced bibliometric analyses, enabling user-driven exploration of research trends and thematic relationships. Additionally, we demonstrate the use of customised large language model (LLM) tools for targeted literature interrogation, enhancing accessibility for researchers and industry stakeholders. Complementing this academic synthesis, we profile selected industry case studies where AI plays a central role in ingredient discovery, product development, intelligent sorting, and sensory analytics. By combining interactive research tools with real-world case studies, this review offers a comprehensive snapshot of Food AI and begins to bridge the gap between academic research and industry implementation, providing a valuable resource for those seeking both domain-specific knowledge and actionable insights.</p></div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"465 - 489"},"PeriodicalIF":7.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12393-025-09413-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review on Electroporation Mechanisms for PEF-Assisted Extraction and Microbial Inactivation","authors":"Mehul Chudasama,&nbsp;Dhananjay Kumar Singh,&nbsp;Rama Chandra Pradhan","doi":"10.1007/s12393-025-09416-7","DOIUrl":"10.1007/s12393-025-09416-7","url":null,"abstract":"<div>\u0000 \u0000 <p>Pulsed Electric Field (PEF) is an emerging non-thermal food processing technology utilizing electroporation to engineer food matrices for microbial inactivation, bioactive compounds extraction, and modification of the food structure while maintaining nutritional and sensory qualities. The purpose of this review article is to present important mechanisms, characteristics, design considerations, enhance energy efficiency, and process scalability for optimal PEF operation with regard to three significant influencing parameters i.e., electric field strength, pulse length, and material conductivity. Discussions on applications in juice extraction, protein recovery, and microbial control highlight scaling issues, economic feasibility, and promising treatment uniformity across various food matrices. Future perspectives focus on the potential of PEF in sustainable food processing, development of functional foods, and how PEF interacts with innovative techniques like AI-driven optimization and hybrid processing. This review provides a perspective on the application of PEF technology for sustainable and eco-efficient food systems that can meet consumer requirements on nutrient retention and minimal processing.</p>\u0000 </div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"706 - 726"},"PeriodicalIF":7.6,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maximizing Benefits from Numerical Simulation for Food Process Optimization and Further Advancement by Integration of AI","authors":"Jorge Rivera,&nbsp;Henry Jaeger","doi":"10.1007/s12393-025-09417-6","DOIUrl":"10.1007/s12393-025-09417-6","url":null,"abstract":"<div><p>The implementation of innovative volumetric food preservation technologies has the potential to reduce the overprocessing of products, by intensifying the preservation effects of treatments and reducing their exposure to them. However, empirical data are insufficient for engineers and food technologists to optimize and develop safe processing protocols. It is therefore essential to develop digital models that can provide a comprehensive representation of the system, as well as a foundation for the computer-assisted optimization of novel technologies. However, a gap in the literature hinders the acquisition of the insights necessary to accomplish this task. This review paper provides an overview of conventional and innovative preservation technologies, outlining their fundamental principles and operational mechanisms. It then presents a comprehensive examination of the numerical methodologies employed for the digital simulation of these technologies, delineating their distinctive requirements. Furthermore, the review assesses potential strategies for ensuring the reliability of data validation and techniques for reducing the complexity of numerical modelling with artificial intelligence (AI). This literature review identified the requisite knowledge for the implementation of numerical simulations and important details that need to be considered to avoid the divergence of the calculations and save costly computational hours. Furthermore, the review proposed a time–temperature integrator-based validation for the obtained data and evaluated the benefits of supporting numerical simulations with AI.</p></div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"490 - 504"},"PeriodicalIF":7.6,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12393-025-09417-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Concept to Commercialization: Unlocking the Potential of High-Pressure Thermal Processing","authors":"Kai Knoerzer,&nbsp;Robert Sevenich","doi":"10.1007/s12393-025-09414-9","DOIUrl":"10.1007/s12393-025-09414-9","url":null,"abstract":"<div><p>High-Pressure Thermal Processing (HPTP) is an emerging food preservation technology that combines elevated pressure with moderate to high temperatures to achieve microbial inactivation while preserving product quality. This review presents a comprehensive overview of the scientific principles, technological developments, and potential commercial applications of HPTP. Key mechanisms such as adiabatic compression heating and the synergistic effects of pressure and temperature are explored alongside advances in equipment design, predictive modeling, and process optimization. The manuscript also highlights applications across diverse food categories, including juices, dairy, meats, seafood, and ready-to-eat meals, and emphasizes HPTP’s ability to reduce the formation of heat-induced food processing contaminants. Recent innovations, such as multilayer canister systems enabling HPTP in conventional HPP equipment, are discussed in the context of scaling the technology from research to industrial use. As consumer demand for minimally processed, high-quality foods continue to rise, HPTP stands poised to play a transformative role in the future of food processing.</p></div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"627 - 644"},"PeriodicalIF":7.6,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12393-025-09414-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovative Strategies for Enhancing Heating Uniformity and Quality in Radio Frequency Food Processing: Challenges and Future Directions","authors":"Yuqing Zhang,&nbsp;Xiangyi Wang,&nbsp;Yandi Zeng,&nbsp;Qian Hao,&nbsp;Shaojin Wang,&nbsp;Zhi Huang","doi":"10.1007/s12393-025-09410-z","DOIUrl":"10.1007/s12393-025-09410-z","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"756 - 775"},"PeriodicalIF":7.6,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reformulation and Characterization of Mediterranean Ingredients by Novel Technologies","authors":"Elif Gokçen Ates,&nbsp;Murad Bal,&nbsp;Melis Cetin Karasu,&nbsp;Neriman Ezgi Cifte,&nbsp;Furkan Erdem,&nbsp;Muhammed Rasim Gul,&nbsp;Ozan Tas,&nbsp;Gokcem Tonyali Karsli,&nbsp;Sanda Pleslić,&nbsp;Kristina Smokrović,&nbsp;Nadica Maltar-Strmečki,&nbsp;Mohamad G. Abiad,&nbsp;Josipa Dukić,&nbsp;Anet Režek Jambrak,&nbsp;Rose Daphnee Tchonkouang,&nbsp;Margarida C. Vieira,&nbsp;Maria Dulce Antunes,&nbsp;Behic Mert,&nbsp;Gulum Sumnu,&nbsp;Hami Alpas,&nbsp;Mecit Oztop","doi":"10.1007/s12393-025-09401-0","DOIUrl":"10.1007/s12393-025-09401-0","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"671 - 705"},"PeriodicalIF":7.6,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12393-025-09401-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Shelf-Life of Olive Oil Under Different Storage Conditions: A Review of Predictive Models","authors":"Nuno Ferreiro,&nbsp;Ana C. A. Veloso,&nbsp;José Alberto Pereira,&nbsp;Nuno Rodrigues,&nbsp;António M. Peres","doi":"10.1007/s12393-025-09409-6","DOIUrl":"10.1007/s12393-025-09409-6","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"608 - 626"},"PeriodicalIF":7.6,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12393-025-09409-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancements in Microwave Drying of Fresh Ginger: Drying Mode, Influencing Factors, Quality Characteristics and Challenges","authors":"Yaping Wang,&nbsp;Yu Xi,&nbsp;Junping Bian,&nbsp;Xinjing Fu,&nbsp;Wenhua Zi","doi":"10.1007/s12393-025-09406-9","DOIUrl":"10.1007/s12393-025-09406-9","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":565,"journal":{"name":"Food Engineering Reviews","volume":"17 3","pages":"727 - 755"},"PeriodicalIF":7.6,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}