A collaborative strategy of multi-technology integration for mycotoxin risk assessment and early warning in edible and medicinal plants.
Fang L, Liu X, Liu K, Feng L, Tang Z, Li Z, Zhang D, Yang W, Guo DA.
Medicinal Plants
Job's tears grain and lily bulbs sold in herbal markets and health food stores were contaminated with harmful mold toxins in over 9 out of 10 batches tested — a reminder that 'natural' or 'medicinal' doesn't mean safe from invisible fungal hazards.
Scientists tested four plants commonly used as both food and herbal medicine and found that nearly all of them contained at least one type of mold poison, called a mycotoxin. They used DNA technology to identify which molds were responsible, and then trained a computer model to scan the plants with a special light sensor — no chemicals needed — to quickly flag which batches were most dangerous. The AI tool was remarkably accurate, correctly identifying high-risk samples nearly every time.
Key Findings
240 out of 259 batches (92.66%) tested positive for at least one mycotoxin across four edible and medicinal plants.
Aflatoxin B1, sterigmatocystin, alternariol monomethyl ether, and zearalenone were flagged as priority public health risks via Monte Carlo probabilistic exposure modeling.
Two machine learning models (KNN and SVM) achieved 100% classification accuracy for most target mycotoxins in lab testing, with external validation reaching 90–100% predictive accuracy.
chevron_right Technical Summary
Researchers tested 259 batches of four medicinal and edible plants for mold toxins, finding contamination in over 92% of samples. They combined advanced chemical analysis, DNA sequencing of fungi, and AI-powered near-infrared light scanning to identify risks and build a rapid screening tool that achieved up to 100% accuracy in detecting dangerous toxin levels.
Abstract Preview
<h4>Background</h4>Mycotoxins are toxic secondary metabolites of toxigenic fungi, posing a significant threat to human health due to their widespread contamination in edible and medicinal plants (E...
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