BACKGROUND

AI guided ultrasonic cleaning of produce will be examined. The initial experiments will focus on enhanced cleaning effectiveness due to shear induced on the produce surface by bubble enhanced ultrasonic cleaning. Range of amplitudes considered is such that we span cases from oscillating non-condensing gas bubbles to cavitation near an artificial leaf surface. The artificial plant leaf surface is developed in Feng lab (UIUC) in order to mimic the surface topology, hydrophobicity, and surface chemistry of real lettuce leaf, but allowing for repeatable well-controlled studies.

GOALS

• Develop and optimize an AI-assisted ultrasonic fresh produce sanitation system to significantly improve the efficacy of current fresh produce sanitation operations.
• Develop a sub-pilot scale continuous-flow ultrasonic fresh produce washing testbed.
• Quantify cavitation activity on produce surfaces using high-speed imagining and X-ray techniques.
• Develop electrical sensors measuring chlorine concentration and pH level based on graphene field-effect transistor (FET) sensors.
• Perform machine learning (ML)-based response surface modeling of fresh produce washing process.

IMPACT

• Enable an intelligent produce washing process to ensure maximized sanitation efficacy for different produce types.