Mycotoxins like aflatoxins and zearalenone pose significant risks to the pet food industry, causing severe health issues such as immune suppression, organ damage, and even cancer. Researchers at the Chinese Academy of Agricultural Sciences have developed an innovative detection method combining electronic nose (E-nose) technology with machine learning. This approach accurately identified zearalenone contamination in 142 pet food samples with 90.1% accuracy, offering a faster, cost-effective, and reliable alternative to traditional detection methods. By enabling real-time analysis and reducing costs, this technology has the potential to revolutionize mycotoxin management in the pet food industry, improving safety standards and protecting pet health.
Advertisement
