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Shen M, Sogore T, Ding T, Feng J. Modernization of digital food safety control. ADVANCES IN FOOD AND NUTRITION RESEARCH 2024; 111:93-137. [PMID: 39103219 DOI: 10.1016/bs.afnr.2024.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/07/2024]
Abstract
Foodborne illness remains a pressing global issue due to the complexities of modern food supply chains and the vast array of potential contaminants that can arise at every stage of food processing from farm to fork. Traditional food safety control systems are increasingly challenged to identify these intricate hazards. The U.S. Food and Drug Administration's (FDA) New Era of Smarter Food Safety represents a revolutionary shift in food safety methodology by leveraging cutting-edge digital technologies. Digital food safety control systems employ modern solutions to monitor food quality by efficiently detecting in real time a wide range of contaminants across diverse food matrices within a short timeframe. These systems also utilize digital tools for data analysis, providing highly predictive assessments of food safety risks. In addition, digital food safety systems can deliver a secure and reliable food supply chain with comprehensive traceability, safeguarding public health through innovative technological approaches. By utilizing new digital food safety methods, food safety authorities and businesses can establish an efficient regulatory framework that genuinely ensures food safety. These cutting-edge approaches, when applied throughout the food chain, enable the delivery of safe, contaminant-free food products to consumers.
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Affiliation(s)
- Mofei Shen
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, P.R. China; Zhejiang University Zhongyuan Institute, Zhengzhou, Henan, P.R. China
| | - Tahirou Sogore
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, P.R. China
| | - Tian Ding
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, P.R. China; Future Food Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, Zhejiang, P.R. China
| | - Jinsong Feng
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, P.R. China; Future Food Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, Zhejiang, P.R. China.
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Fernández González A, Badía Laíño R, Costa-Fernández JM, Soldado A. Progress and Challenge of Sensors for Dairy Food Safety Monitoring. SENSORS (BASEL, SWITZERLAND) 2024; 24:1383. [PMID: 38474919 DOI: 10.3390/s24051383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/15/2024] [Accepted: 02/19/2024] [Indexed: 03/14/2024]
Abstract
One of the most consumed foods is milk and milk products, and guaranteeing the suitability of these products is one of the major concerns in our society. This has led to the development of numerous sensors to enhance quality controls in the food chain. However, this is not a simple task, because it is necessary to establish the parameters to be analyzed and often, not only one compound is responsible for food contamination or degradation. To attempt to address this problem, a multiplex analysis together with a non-directed (e.g., general parameters such as pH) analysis are the most relevant alternatives to identifying the safety of dairy food. In recent years, the use of new technologies in the development of devices/platforms with optical or electrochemical signals has accelerated and intensified the pursuit of systems that provide a simple, rapid, cost-effective, and/or multiparametric response to the presence of contaminants, markers of various diseases, and/or indicators of safety levels. However, achieving the simultaneous determination of two or more analytes in situ, in a single measurement, and in real time, using only one working 'real sensor', remains one of the most daunting challenges, primarily due to the complexity of the sample matrix. To address these requirements, different approaches have been explored. The state of the art on food safety sensors will be summarized in this review including optical, electrochemical, and other sensor-based detection methods such as magnetoelastic or mass-based sensors.
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Affiliation(s)
- Alfonso Fernández González
- Department of Physical and Analytical Chemistry, Faculty of Chemistry, University of Oviedo, Avda. Julián Clavería 8, 33006 Oviedo, Asturias, Spain
| | - Rosana Badía Laíño
- Department of Physical and Analytical Chemistry, Faculty of Chemistry, University of Oviedo, Avda. Julián Clavería 8, 33006 Oviedo, Asturias, Spain
| | - José M Costa-Fernández
- Department of Physical and Analytical Chemistry, Faculty of Chemistry, University of Oviedo, Avda. Julián Clavería 8, 33006 Oviedo, Asturias, Spain
| | - Ana Soldado
- Department of Physical and Analytical Chemistry, Faculty of Chemistry, University of Oviedo, Avda. Julián Clavería 8, 33006 Oviedo, Asturias, Spain
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Shruti A, Bage N, Kar P. Nanomaterials based sensors for analysis of food safety. Food Chem 2024; 433:137284. [PMID: 37703589 DOI: 10.1016/j.foodchem.2023.137284] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 08/10/2023] [Accepted: 08/23/2023] [Indexed: 09/15/2023]
Abstract
The freshnessof the food is a major issue because spoiled food lacks critical nutrients for growth and could be harmful to human health if consumed directly. Nanomaterials are captivating due to their unique properties like large surface area, high selectivity, small dimension, great biocompatibility and conductivity, real-time onsite analysis, etc. which give them an advantage over conventional evaluation techniques. Despite these advantages of nanomaterials used in food safety and their preservation, food products can still get affected by various environmental factors (like pH, temperature, etc.), making the use of time-temperature indicators more condescending. This review is a comprehensive study on food safety, its causes, the responsible analytes, their remedies by various nanomaterials, the development of various nanosensors, and the various challenges faced in maintaining food safety standards to reduce the risk of contaminants.
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Affiliation(s)
- Asparshika Shruti
- Department of Chemistry, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India
| | - Nirgaman Bage
- Department of Chemistry, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India
| | - Pradip Kar
- Department of Chemistry, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India.
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Hossain MI, Faruk MO, Subahan Mahbub Tuha MA, Mimi S, Islam KR, Sarafat Ali DM, Sahabuddin M. Comparative safety analysis of newly prepackaged backed food products and those approaching the expiry date in Bangladesh. Heliyon 2023; 9:e17513. [PMID: 37456032 PMCID: PMC10345249 DOI: 10.1016/j.heliyon.2023.e17513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 06/12/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023] Open
Abstract
PURPOSE The enrichment of microbial growth in prepackaged, frozen food goods from the day of manufacturing to the day of expiration has been the subject of recurrent concerns. These fortified foods are widely consumed by individuals of all ages in poor nations due to their ability to satisfy even the smallest of appetites. People often disregard the expiration dates printed on food packaging despite the fact that manufacturers are required by law to do so. This research looked into whether or not it was safe to consume packaged foods that were getting close to their expiration date. Finding out if people are exposed to hazardous microorganisms and how much bacteria is created daily on them. MATERIALS AND METHODS We collected six prepackaged backed food products samples of three types separately, where three were collected around manufacturing days and three were nearly expired days from different companies. We have assayed and identified the foodborne microbial communities among the samples by morphological study and different types of biochemical tests. After that, we tested how well various popular antibiotics worked against those isolates. RESULTS It showed that there are more bacterial communities that grow gradually day by day on prepackaged backed food products and nearly expired products that contain a large number of food-borne disease-causing bacteria that show mostly resistance against commonly used antibiotics. CONCLUSION Although nowadays the demand for prepackaged backed food products is increasing as ready-to-eat processed foods, mostly in developing countries, there's a serious health risk if we take the products that were produced a long time ago.
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Olakanmi SJ, Jayas DS, Paliwal J. Applications of imaging systems for the assessment of quality characteristics of bread and other baked goods: A review. Compr Rev Food Sci Food Saf 2023; 22:1817-1838. [PMID: 36916025 DOI: 10.1111/1541-4337.13131] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 01/10/2023] [Accepted: 02/13/2023] [Indexed: 03/16/2023]
Abstract
One of the most widely researched topics in the food industry is bread quality analysis. Different techniques have been developed to assess the quality characteristics of bakery products. However, in the last few decades, the advancement in sensor and computational technologies has increased the use of computer vision to analyze food quality (e.g., bakery products). Despite a large number of publications on the application of imaging methods in the bakery industry, comprehensive reviews detailing the use of conventional analytical techniques and imaging methods for the quality analysis of baked goods are limited. Therefore, this review aims to critically analyze the conventional methods and explore the potential of imaging techniques for the quality assessment of baked products. This review provides an in-depth assessment of the different conventional techniques used for the quality analysis of baked goods which include methods to record the physical characteristics of bread and analyze its quality, sensory-based methods, nutritional-based methods, and the use of dough rheological data for end-product quality prediction. Furthermore, an overview of the image processing stages is presented herein. We also discuss, comprehensively, the applications of imaging techniques for assessing the quality of bread and other baked goods. These applications include studying and predicting baked goods' quality characteristics (color, texture, size, and shape) and classifying them based on these features. The limitations of both conventional techniques (e.g., destructive, laborious, error-prone, and expensive) and imaging methods (e.g., illumination, humidity, and noise) and the future direction of the use of imaging methods for quality analysis of bakery products are discussed.
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Affiliation(s)
- Sunday J Olakanmi
- Department of Biosystems Engineering, 75 Chancellors Circle, University of Manitoba, Winnipeg, Manitoba, R3T 5V6, Canada
| | - Digvir S Jayas
- Department of Biosystems Engineering, 75 Chancellors Circle, University of Manitoba, Winnipeg, Manitoba, R3T 5V6, Canada
| | - Jitendra Paliwal
- Department of Biosystems Engineering, 75 Chancellors Circle, University of Manitoba, Winnipeg, Manitoba, R3T 5V6, Canada
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Hassoun A, Jagtap S, Trollman H, Garcia-Garcia G, Abdullah NA, Goksen G, Bader F, Ozogul F, Barba FJ, Cropotova J, Munekata PE, Lorenzo JM. Food processing 4.0: Current and future developments spurred by the fourth industrial revolution. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Min W, Liu C, Xu L, Jiang S. Applications of knowledge graphs for food science and industry. PATTERNS (NEW YORK, N.Y.) 2022; 3:100484. [PMID: 35607620 PMCID: PMC9122965 DOI: 10.1016/j.patter.2022.100484] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The deployment of various networks (e.g., Internet of Things [IoT] and mobile networks), databases (e.g., nutrition tables and food compositional databases), and social media (e.g., Instagram and Twitter) generates huge amounts of food data, which present researchers with an unprecedented opportunity to study various problems and applications in food science and industry via data-driven computational methods. However, these multi-source heterogeneous food data appear as information silos, leading to difficulty in fully exploiting these food data. The knowledge graph provides a unified and standardized conceptual terminology in a structured form, and thus can effectively organize these food data to benefit various applications. In this review, we provide a brief introduction to knowledge graphs and the evolution of food knowledge organization mainly from food ontology to food knowledge graphs. We then summarize seven representative applications of food knowledge graphs, such as new recipe development, diet-disease correlation discovery, and personalized dietary recommendation. We also discuss future directions in this field, such as multimodal food knowledge graph construction and food knowledge graphs for human health.
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Affiliation(s)
- Weiqing Min
- Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chunlin Liu
- Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Leyi Xu
- Soochow University, Suzhou, Jiangsu 215006, China
| | - Shuqiang Jiang
- Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
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Fan KJ, Su WH. Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review. BIOSENSORS 2022; 12:bios12020076. [PMID: 35200337 PMCID: PMC8869398 DOI: 10.3390/bios12020076] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/21/2022] [Accepted: 01/26/2022] [Indexed: 05/12/2023]
Abstract
Fluorescence spectroscopy, color imaging and multispectral imaging (MSI) have emerged as effective analytical methods for the non-destructive detection of quality attributes of various white meat products such as fish, shrimp, chicken, duck and goose. Based on machine learning and convolutional neural network, these techniques can not only be used to determine the freshness and category of white meat through imaging and analysis, but can also be used to detect various harmful substances in meat products to prevent stale and spoiled meat from entering the market and causing harm to consumer health and even the ecosystem. The development of quality inspection systems based on such techniques to measure and classify white meat quality parameters will help improve the productivity and economic efficiency of the meat industry, as well as the health of consumers. Herein, a comprehensive review and discussion of the literature on fluorescence spectroscopy, color imaging and MSI is presented. The principles of these three techniques, the quality analysis models selected and the research results of non-destructive determinations of white meat quality over the last decade or so are analyzed and summarized. The review is conducted in this highly practical research field in order to provide information for future research directions. The conclusions detail how these efficient and convenient imaging and analytical techniques can be used for non-destructive quality evaluation of white meat in the laboratory and in industry.
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Amani H, Baranyai L, Badak-Kerti K, Mousavi Khaneghah A. Influence of Baking Temperature and Formulation on Physical, Sensorial, and Morphological Properties of Pogácsa Cake: An Image Analysis Study. Foods 2022; 11:foods11030321. [PMID: 35159471 PMCID: PMC8834173 DOI: 10.3390/foods11030321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 12/30/2021] [Accepted: 01/14/2022] [Indexed: 12/10/2022] Open
Abstract
Pogácsa is a high-demand bakery product with a unique texture, where crumb structure is a determining factor for its textural quality and consumer acceptability. At present, there is no non-destructive in-line inspection method for textural quality assessment of pogácsa. Therefore, this study was aimed to evaluate the texture of pogácsa using the image processing technique, which was prepared using different cheeses with varying moisture contents (MC) and was baked at 200 and 215 °C. Samples were assessed for textural, visual, physical, and sensorial properties. The findings indicated that the highest porosity (72.75%) was found for the sample baked at 215 °C with low-moisture cheese (58%), while the lowest porosity (32.66%) was observed for cheese-free sample baked at 200 °C. Pore volumetric ratio and MC showed strong correlations (p < 0.01) with hardness (−0.90 and −0.89), resilience (0.87 and 0.83), cohesiveness (0.84 and 0.82), springiness (0.87 and 0.90), gumminess (−0.92 and −0.92), and chewiness (−0.92 and −0.92), respectively. The pore volumetric ratio showed a strong correlation (p < 0.01) with reference porosity (0.71). Overall, the current study indicated that adding cheese with varying MC and baking temperature could affect the texture of pogácsa cake, which could be detected by image analysis.
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Affiliation(s)
- Hanieh Amani
- Department of Grains and Industrial Plants Processing, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary;
- Correspondence: (H.A.); (A.M.K.) or (A.M.K.)
| | - László Baranyai
- Department of Measurements and Process Control, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary;
| | - Katalin Badak-Kerti
- Department of Grains and Industrial Plants Processing, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, Hungary;
| | - Amin Mousavi Khaneghah
- Department of Food Science and Nutrition, Faculty of Food Engineering, University of Campinas, Campinas 13083-862, SP, Brazil
- Correspondence: (H.A.); (A.M.K.) or (A.M.K.)
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Zhou Q, Zhang H, Wang S. Artificial intelligence, big data, and blockchain in food safety. INTERNATIONAL JOURNAL OF FOOD ENGINEERING 2021. [DOI: 10.1515/ijfe-2021-0299] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
Food safety plays an essential role in our daily lives, and it becomes serious with the development of worldwide trade. To tackle the food safety issues, many advanced technologies have been developed to monitor the process of the food industry (FI) to ensure food safety, including the process of food production, processing, transporting, storage, and retailing. These technologies are often referred to as artificial intelligence (AI), big data, and blockchain, which have been widely applied in many research areas. In this review, we introduce these technologies and their applications in the food safety domain. Firstly, basic concepts of these technologies are presented. Then, applications for food safety from a data perspective based on these technologies are analyzed. Finally, future challenges of the applications of AI, big data, and blockchain are discussed.
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Affiliation(s)
- Qinqin Zhou
- College of Food Science and Engineering, Nanjing University of Finance and Economics , Nanjing 210023 , China
| | - Hao Zhang
- College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics , Nanjing 210016 , China
| | - Suya Wang
- College of Food Science and Engineering, Nanjing University of Finance and Economics , Nanjing 210023 , China
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