Location: Environmental Microbial & Food Safety Laboratory
Project Number: 8042-32420-009-031-A
Project Type: Cooperative Agreement
Start Date: Oct 1, 2023
End Date: Aug 15, 2024
Objective:
This collaborative project aims to enhance the food safety of fresh produce via AI and robot-enabled anti-microbial coating formulation and synthesis.
The main objectives are to:
1) develop an accurate prediction model that can expedite the research and development of the targeted coatings;
2) syntheses and characterize the as-prepared coatings for their physio-chemical properties and pathogen inhibition efficacies.
Approach:
First, an automated pipetting robot will be used to prepare a library of over 2,000 aqueous mixtures. The coating uniformity of these mixtures will be evaluated to train a support-vector machine classifier. Next, through active learning loops with data augmentation, more than 200 all-natural barrier coatings will be fabricated and characterized in stages, enabling the construction of an artificial neural network prediction model. Finally, the prediction model will be capable of performing two-way design tasks. This includes predicting the barrier properties (such as oxygen permeability and antibacterial efficacy) of an all-natural coating based on its composition, as well as automating the inverse design of all-natural barrier coatings that inhibit pathogen growth on fresh produce.
