Technical and economic aspects of Alternaria mycotoxin management in tomatoes in China

My PhD research explores a new way to control emerging mycotoxins in tomatoes by predicting the risk before contamination occurs. Some fungi, such as Alternaria species, produce toxins that are difficult to remove once they enter food and may pose health risks to consumers. Rather than focusing only on visible plant disease, my work developed and tested a prediction model that estimates the likelihood of Alternaria mycotoxin contamination using weather conditions, crop growth stages, and fungal behavior. This model serves as a proof of concept for a smarter control approach that supports timely and informed decisions in tomato production. By combining laboratory measurements, data analysis, and economic evaluation, the research shows how prediction-based control can improve food safety management and help producers respond more effectively to emerging mycotoxin risks, especially in tomato production systems in China.