Items Tagged with 'predictive modeling'

Wageningen University researchers developed a hybrid machine learning modeling framework that considers crop growth stages, various future scenarios, and a large geographic region. The model predicted deoxynivalenol will present the greatest risk, with coastal countries, the UK, and northern France most affected.

Predictive models help inform decision-making, and can also serve as documentation toward customers, regulators, and third-party auditors. This article examines DMRI Predict, a collection of predictive models that can be used to assess food safety and spoilage (both microbiological and sensory) of meat and meat products.

Wageningen University Food Safety Research recently launched a four-year project with the goal of developing an early warning system to detect the presence of mycotoxins in European cereal grains.

A session at the 2022 International Association for Food Protection (IAFP) Annual Meeting discussed recent developments in applications of predictive tools for meat and poultry products.