Journal of Agriculture and Food Research, Journal Year: 2025, Volume and Issue: unknown, P. 101787 - 101787
Published: March 1, 2025
Language: Английский
ACS Omega, Journal Year: 2023, Volume and Issue: 8(24), P. 21377 - 21390
Published: June 8, 2023
Toxicology is undergoing a digital revolution, with mobile apps, sensors, artificial intelligence (AI), and machine learning enabling better record-keeping, data analysis, risk assessment. Additionally, computational toxicology assessment have led to more accurate predictions of chemical hazards, reducing the burden laboratory studies. Blockchain technology emerging as promising approach increase transparency, particularly in management processing genomic related food safety. Robotics, smart agriculture, feedstock offer new opportunities for collecting, analyzing, evaluating data, while wearable devices can predict toxicity monitor health-related issues. The review article focuses on potential technologies improve public health field toxicology. By examining key topics such blockchain technology, smoking toxicology, security, this provides an overview how digitalization influencing As well highlighting future directions research, demonstrates enhance communication efficiency. integration has revolutionized great improving promoting health.
Language: Английский
Citations
66
Advanced Materials, Journal Year: 2023, Volume and Issue: 36(1)
Published: April 22, 2023
Abstract Despite extensive commercial and regulatory interventions, food spoilage contamination continue to impose massive ramifications on human health the global economy. Recognizing that such issues will be significantly eliminated by accurate timely monitoring of quality markers, smart sensors have garnered significant interest as platforms for both real‐time, in‐package on‐site testing. In cases, sensitivity, stability, efficiency developed are largely informed underlying material design, driving focus toward creation advanced materials optimized applications. Herein, a comprehensive review emerging intelligent in this space is provided, through lens three key markers – biogenic amines, pH, pathogenic microbes. Each sensing platform presented with targeted consideration contributions metallic or polymeric substrate mechanism detection performance. Further, real‐world applicability works considered respect their capabilities, adherence, potential. Finally, situational assessment current state technologies discussing material‐centric strategies address existing limitations, concerns, considerations.
Language: Английский
Citations
63
Comprehensive Reviews in Food Science and Food Safety, Journal Year: 2024, Volume and Issue: 23(1)
Published: Jan. 1, 2024
Abstract To enhance the resilience of food systems to safety risks, it is vitally important for national authorities and international organizations be able identify emerging risks provide early warning signals in a timely manner. This review provides an overview existing experimental applications artificial intelligence (AI), big data, internet things as part risk identification tools methods domain. There ongoing rapid development fed by numerous, real‐time, diverse data with aim risks. The suitability AI support such illustrated two cases which climate change drives emergence namely, harmful algal blooms affecting seafood fungal growth mycotoxin formation crops. Automation machine learning are crucial future real‐time systems. Although these developments increase feasibility effectiveness prospective tools, their implementation may prove challenging, particularly low‐ middle‐income countries due low connectivity availability. It advocated overcome challenges improving capability capacity authorities, well enhancing collaboration private sector organizations.
Language: Английский
Citations
38
Food Chemistry, Journal Year: 2024, Volume and Issue: 445, P. 138700 - 138700
Published: Feb. 10, 2024
Language: Английский
Citations
30
Trends in Food Science & Technology, Journal Year: 2024, Volume and Issue: 146, P. 104396 - 104396
Published: Feb. 21, 2024
Language: Английский
Citations
29
Comprehensive Reviews in Food Science and Food Safety, Journal Year: 2024, Volume and Issue: 23(1)
Published: Jan. 1, 2024
Abstract In recent years, the food industry has shown a growing interest in development of rapid and nondestructive analytical methods. However, utilization solitary detection technique offers only constrained extent physical or chemical insights regarding sample under examination. To overcome this limitation, amalgamation spectroscopy with data fusion strategies emerged as promising approach. This comprehensive review delves into fundamental principles merits low‐level, mid‐level, high‐level within domain analysis. Various techniques encompassing spectra‐to‐spectra, spectra‐to‐machine vision, spectra‐to‐electronic nose, spectra‐to‐nuclear magnetic resonance are summarized. Moreover, also provides an overview latest applications spectral (SDFTs) for classification, adulteration, quality evaluation, contaminant purview safety It addresses current challenges future prospects associated SDFTs real‐world applications. Despite extant technical intricacy, ongoing evolution online platforms emergence smartphone‐based multi‐sensor technology augur well pragmatic realization SDFTs, endowing them formidable capabilities both qualitative quantitative analysis realm
Language: Английский
Citations
24
Food Packaging and Shelf Life, Journal Year: 2024, Volume and Issue: 43, P. 101287 - 101287
Published: April 22, 2024
Language: Английский
Citations
21
Food Control, Journal Year: 2024, Volume and Issue: 162, P. 110471 - 110471
Published: March 25, 2024
Language: Английский
Citations
20
Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 435, P. 140566 - 140566
Published: Jan. 1, 2024
Language: Английский
Citations
17
Deleted Journal, Journal Year: 2025, Volume and Issue: 7(1)
Published: Jan. 11, 2025
Abstract Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, quality, and security. This review synthesizes advancements AI-driven technologies, such machine learning, deep natural language processing, computer vision, their applications across supply chain, based on comprehensive analysis literature published from 1990 to 2024. AI enhances safety through real-time contamination detection, predictive risk modeling, compliance monitoring, reducing public health risks. It improves quality by automating defect optimizing shelf-life predictions, ensuring consistency taste, texture, appearance. Furthermore, addresses security enabling resource-efficient agriculture, yield forecasting, chain optimization ensure availability accessibility nutritious resources. also highlights integration with advanced processing techniques high-pressure ultraviolet treatment, pulsed electric fields, cold plasma, irradiation, which microbial extend shelf life, enhance product quality. Additionally, technologies Internet Things, blockchain, AI-powered sensors enables proactive management, analytics, automated control. By examining these innovations' potential transparency, efficiency, decision-making within systems, this identifies current research gaps proposes strategies address barriers data limitations, model generalizability, ethical concerns. These insights underscore critical role advancing safer, higher-quality, more secure guiding future fostering sustainable systems that benefit consumer trust.
Language: Английский
Citations
11