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Current Global Trends in Food Safety and Risk Prediction
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This review paper looks at how food safety is changing, moving from reacting to problems after they happen to predicting and preventing them using tools like AI, DNA testing, and smart sensors. It also flags growing concerns like climate change spreading toxic mold in crops, microplastics and nanoplastics contaminating our food, and antibiotic-resistant germs—all issues that build up in the body over time and are harder to catch with old-school testing methods. The takeaway: keeping food safe in the coming years will require smarter technology, better tracking of contaminants like microplastics, and stronger global cooperation—not just farms and factories doing things
The study substantiates the shift from traditional reactive control methods to a proactive model of intelligent risk management. Particular emphasis is placed on the "One Health" concept, which integrates human, animal, and ecosystem health within a unified monitoring system; special attention is also given to the destabilizing impact of climate change on food quality and safety—specifically through the spread of mycotoxins and alterations to the planet's microbial landscape. The study provides a detailed analysis of the potential of next-generation sequencing (NGS) for the metagenomic profiling of facilities, the role of nanotechnology in developing precision sensors and active packaging, and the application of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas systems for rapid pathogen diagnostics. Digital architectures for ensuring food safety are examined, with artificial intelligence (AI) and big data analytics presented as key tools for predictive modeling. The data presented address emerging threats such as micro- and nanoplastic contamination, antimicrobial resistance (AMR), and the safety of alternative protein sources. The study demonstrates that systemic contaminants necessitate new approaches to toxicological assessment due to their cumulative effects. It highlights that, by 2026, corporate legal liability will be inextricably linked to digital transparency and the ethics of AI algorithm usage. The study concludes that food safety in 2026 will increasingly depend on the integration of advanced technologies, environmental responsibility, and global digital cooperation.
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Future trends in Food Science and Foodomics: a perspective view by the Editorial Team of Exploration of Foods and Foodomics
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A panel of food science experts discussed emerging trends across food safety, authenticity, processing, and bioactivity, including the growing concern about microplastic and nanoplastic contamination in food. The article highlights the need for better analytical methods to detect micro- and nanoplastics in food products and to understand their effects on the food supply chain. Researchers also discussed the potential risks of introducing recycled plastics into food packaging.
Global food safety policies: Standards, challenges, and compliance
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This review examines global food safety policies and identifies microplastics as one of several emerging chemical contaminants posing challenges to regulatory systems. The study found that foodborne diseases affect approximately 600 million people annually and highlights the need for effective surveillance systems, traceability technologies, and international cooperation to address new threats including microplastic contamination.
Recent trend in safety and environmental regulation and artificial intelligence application for food packaging
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This review paper summarizes global trends in rules for food packaging safety and environmental impact, and how artificial intelligence is being used to address related challenges. It describes AI being applied to predict chemical leaching, detect microplastics, and help design more sustainable, bio-based packaging materials.
Toxicological impacts and mitigation strategies of food contaminants: a global perspective and comprehensive narrative review
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This comprehensive review examines the toxicological impacts of food contaminants, including heavy metals, mycotoxins, pesticides, and microplastics, from a global health perspective. Researchers synthesized evidence on the cellular and molecular mechanisms of harm caused by these contaminants and assessed current monitoring and mitigation strategies. The study calls for stronger international coordination to address the growing complexity of food safety challenges.
Artificial intelligence-driven detection of microplastics in food: A comprehensive review of sources, health risks, detection techniques, and emerging artificial intelligence solutions
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This review compares traditional and advanced methods for detecting microplastics in food, finding that while older techniques provide basic information, newer technologies like infrared spectroscopy and mass spectrometry can identify much smaller particles with greater accuracy. The study highlights how artificial intelligence can significantly improve the speed and precision of microplastic detection in food products. As global plastic production continues to rise, better detection methods are essential for monitoring food safety and protecting human health.
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