Fishery Products Safety, Processing and Utilization DOI Open Access
U. Samarajeewa

Published: March 11, 2024

Abstract Global marine fish harvest has reached a plateau over the last decade. Efforts to increase aquaculture tend face limitations in water resources and contamination problems. Of current at least 50% is discarded as waste. The chemical microbiological contaminations limit utilization of harvested fish. There need improve preservation minimize spoilage process them into more appealing products. Instead resorting individual food processing methods, efficiency could best be increased by combination conventional modern or combinations methods. Fish waste rich source oils containing essential fatty acids, polypeptides, amino polysaccharides that utilized through upscaling scientifically proven new technologies. Separation collagens, gelatins, bioactive peptides, edible oils, chitosan form primary stages products purification meet quality safety standards, desirable industrial characteristics. diversity information generated methods requires advanced data handling prediction systems, such artificial intelligence, address get out utilization.

Language: Английский

The Role of Artificial Intelligence in Advancing Food Safety: A Strategic Path to Zero Contamination DOI
Sobia Naseem, Muhammad Rizwan

Food Control, Journal Year: 2025, Volume and Issue: unknown, P. 111292 - 111292

Published: March 1, 2025

Language: Английский

Citations

2
Advancements in food quality monitoring: integrating biosensors for precision detection DOI Creative Commons
Soumitra Nath

Sustainable Food Technology, Journal Year: 2024, Volume and Issue: 2(4), P. 976 - 992

Published: Jan. 1, 2024

The integration of advanced biosensors enhances the detection contaminants in food. This approach addresses challenges related to sensitivity, specificity, and environmental factors, ensuring food safety quality.

Language: Английский

Citations

15
Advancing tea detection with artificial intelligence: strategies, progress, and future prospects DOI

Qilin Xu,

Yifeng Zhou, Linlin Wu

et al.

Trends in Food Science & Technology, Journal Year: 2024, Volume and Issue: unknown, P. 104731 - 104731

Published: Sept. 1, 2024

Language: Английский

Citations

9
Genomic synergy in food traceability: Enhancing global food safety and security DOI
Jacob Tizhe Liberty

Ecological Genetics and Genomics, Journal Year: 2025, Volume and Issue: 34, P. 100324 - 100324

Published: Jan. 5, 2025

Language: Английский

Citations

1
Future Trends in Food and Dairy Process Engineering and Business: A Comprehensive Exploration DOI
S. S. Yadav, Kambhampati Vivek, Sabyasachi Mishra

et al.

Food engineering series, Journal Year: 2025, Volume and Issue: unknown, P. 515 - 534

Published: Jan. 1, 2025

Language: Английский

Citations

1
Food and Supplement Safety Using Data Science and ML Ensuring Quality and Compliance DOI
Pawan Whig, Balaji Dhamodharan, Vijaya Lakshmi Pavani Molli

et al.

Advances in medical diagnosis, treatment, and care (AMDTC) book series, Journal Year: 2024, Volume and Issue: unknown, P. 547 - 571

Published: Aug. 9, 2024

Data science is playing a crucial role in enhancing food and supplement safety, ensuring that products meet regulatory standards are safe for consumption. This chapter explores the application of data techniques monitoring safety quality dietary supplements. The authors examine methodologies used collection, analysis, predictive modeling to detect contaminants, adulteration, compliance with regulations. also covers integration big sources, such as laboratory results, consumer feedback, supply chain data, provide comprehensive assessments. Case studies real-world applications illustrate how can preemptively identify potential issues improve compliance. aims detailed understanding leveraging enhance thereby protecting public health.

Language: Английский

Citations

6
Unveiling the chemical complexity of food-risk components: A comprehensive data resource guide in 2024 DOI Creative Commons
Dachuan Zhang, Dongliang Liu,

Jiayi Jing

et al.

Trends in Food Science & Technology, Journal Year: 2024, Volume and Issue: 148, P. 104513 - 104513

Published: April 26, 2024

With the influence of climate change, environmental pollution, industrial development, and new agricultural practices, increasing amounts chemical substances with potential risks—both anthropogenic biogenic—enter food supply chain ultimately affect human health, entailing challenges to safety security. Although some food-risk components (FRCs) have been accessed regulated, toxicity exposure level numerous detected in remain unknown, leaving questions on their effect safety. Therefore, multiple databases emerging FRCs constructed aid risk assessment, regulation, communication; however, focus areas, data content, quality, accessibility not systematically summarized, which hinders development applications data-driven methods field. The major objective this review is comprehensively introduce representative FRC different along presentation, quality availability, successful applications. Over past decades, over 50 released widely used hazard identification, prediction, contributing significantly scientific research, policymaking, education. However, our analysis unveils persistent such as delayed updates, concerns, reproducibility issues, suboptimal inadequate coverage underdeveloped regions. To address these shortcomings, we propose an initiative aimed at enhancing future FRC-related resources, prioritizing principles findability, accessibility, interoperability, reusability. Additionally, highlight strategies, e.g., natural language processing, cheminformatics, suspect non-targeted analysis, genome mining, for detection outside existing databases. By embracing initiatives lay groundwork a robust framework facilitating enhanced assessment informed decision-making face evolving challenges.

Language: Английский

Citations

5
Progressive Analytical Techniques Utilized for the Detection of Contaminants Attributed to Food Safety and Security DOI Creative Commons

Anjali Bharti,

Utkarsh Jain, Nidhi Chauhan

et al.

Talanta Open, Journal Year: 2024, Volume and Issue: unknown, P. 100368 - 100368

Published: Oct. 1, 2024

Language: Английский

Citations

4
Sensors for food and beverage DOI Open Access
Fabio Mencarelli

Journal of the Science of Food and Agriculture, Journal Year: 2025, Volume and Issue: 105(3), P. 1407 - 1407

Published: Jan. 13, 2025

Searching 'Sensors in Food Science and Technology' on Google will present you with about 85 million results. By specifying 'microsensors', it goes down rapidly to 100 000, 250 000 if we search for 'nano'. Thus, only a small part of micro- nanosensors are used the food chain. chains today very complex millions items produced. The revenue 2023 was equal 8.5 trillions dollars is continuously rising.1 delivery revenues worldwide estimated at just over one trillion US dollars. Drink industry largest manufacturing sector European Union (EU) economy, employing 4.6 workers 291 companies.2 generates highest turnover, value added employment EU industry, being well ahead other sectors such as automotive industry. Small medium sized enterprises (SMEs) play key role this sector. Consumer perception has evolved high level awareness, which led generalized lack confidence. Indeed, products must guarantee not proper sensorial nutritional characteristics, but also safety an affordable price meet consumer's expectation. To face problem, needs provide quality safe consumer. Recent scientific findings allow stakeholder set appropriate rigorous standards help robust cost-effective risk analysis concepts. Real-time rapid detection tools ensure security chain, including defense, aid managing hazards risks processing, distribution sale. A possible solution enhance maintain could be effective process-technology control. This achieved by clear definitions product quality, sensory, physical, chemical, microbiological attributes/criteria, way measured perceived. recent review provides overview existing experimental applications artificial intelligence (AI), big data internet things early warning emerging identification methods domain.3 Europe controls enormous amount marketed means Safety Authority (EFSA) independent advice food-related risks. However, required fit give mandatory list ingredients processed composition. In addition, always performed during production wine, olive oil, milk derivatives, fruit juice, meat fish derivatives. gives processor continuous constant monitoring ongoing process. Unfortunately, take into account that 90% world's cargo transported maritime containers 2% physically inspected customs authorities, opens possibility illicit activities,4 so can imagine importance having analytical control system. Today, information communication technologies (and more recently things) development new instruments cost effective, reliable, environmentally sustainable. particularly true analyses cloud. Each juice producer or person have customized sensors. there growing request sensors, based different respect conventional ones, answer company requests. main reason up Special Issue: answering challenging researchers innovative, mainly prototype, microsensors applied matrices. For example, graphene sensors hazelnut rancidity electronic tongue wine discrimination, again use generation nose online oil analysis, addition application NIR (i.e. near infrared) polyphenol grape hot topic. Wine matrix received attention great contribution most brilliant NIR, testing fluorescence specific components. Finally, wearable sensor sensory evaluation, comprising innovative approach further basis analysis.

Language: Английский

Citations

0
Deep learning technology: enabling safe communication via the internet of things DOI Creative Commons
Ramiz Salama, Hitesh Mohapatra,

Tuğşad Tülbentçi

et al.

Frontiers in Communications and Networks, Journal Year: 2025, Volume and Issue: 6

Published: Feb. 4, 2025

Introduction The Internet of Things (IoT) is a new technology that connects billions devices. Despite offering many advantages, the diversified architecture and wide connectivity IoT make it vulnerable to various cyberattacks, potentially leading data breaches financial loss. Preventing such attacks on ecosystem essential ensuring its security. Methods This paper introduces software-defined network (SDN)-enabled solution for vulnerability discovery in systems, leveraging deep learning. Specifically, Cuda-deep neural (Cu-DNN), Cuda-bidirectional long short-term memory (Cu-BLSTM), Cuda-gated recurrent unit (Cu-DNNGRU) classifiers are utilized effective threat detection. approach includes 10-fold cross-validation process ensure impartiality findings. most recent publicly available CICIDS2021 dataset was used train hybrid model. Results proposed method achieves an impressive recall rate 99.96% accuracy 99.87%, demonstrating effectiveness. model also compared benchmark classifiers, including Cuda-Deep Neural Network, Cuda-Gated Recurrent Unit, (Cu-DNNLSTM Cu-GRULSTM). Discussion Our technique outperforms existing based evaluation criteria as F1-score, speed efficiency, accuracy, precision. shows strength detection highlights potential combining SDN with learning assessment.

Language: Английский

Citations

0