Would you like to see your presentation here, made available to a global audience of researchers?
Add your own presentation or have us affordably record your next conference.
Contamination in the food production chain poses risks to human health, financial losses, and environmental harm due to wasted resources. Conventional methods for identifying and tracing contaminants, whether from pathogenic or spoilage microbes, often have limitations. High-throughput sequencing, combined with bioinformatics, machine learning, and AI, offers faster, more accurate identification and tracing of contamination, along with risk prediction. This novel approach enables preventive actions resulting in reduced losses, and enhanced consumer safety. This presentation will cover the technological foundations, challenges, and opportunities, as well as practical applications in contamination detection, risk prevention, and quality monitoring through real-world case studies.
