Research Profile: Mason Earles

Mason Earles

Dr. Mason Earles joined UC Davis in the Fall of 2019 as an assistant professor in the Departments of Viticulture & Enology and Biological and Agricultural Engineering. Prior to coming to UC Davis, he worked at Apple, Inc.

The primary focus of Dr. Earles’ current research is agricultural sensing and automation. The Earles lab is looking for opportunities to use new artificial intelligence (AI) methods to improve outcomes in viticulture, with a current focus on yield and ripeness. They are looking at how to better monitor and forecast yield through focusing on what is currently in the field, but also trying to anticipate the yield 2-3 months out. To do this, the team is building an AI-Enabled sensing kit, which they are calling “AgKit”. These sensing kits will bring together the latest in hardware and AI algorithms to run in the field with no need for internet connectivity. They aim to develop these kits to piggyback on existing farm operations so that data can be gathered without requiring additional effort. For example, they can be affixed to tractors, and data can be gathered when people are already out in the field performing other operations such as spraying. Building on this data they aim to deliver state-of-the-art performance in terms of yield monitoring and forecasting.

Looking toward the future, the Earles lab would also like to develop new techniques for better monitoring and predicting quality in terms of grape chemistry and ripeness using AI. Similarly, they would like to develop AI-enabled sensor kits that can predict early grape disease. Another research area of interest is how AI-enabled kits can be built that focus on the abiotic qualities of grapes such as drought stress. 

This coming year, Dr. Earles will be teaching three new classes. In Winter 2021, he will teach “Vineyard Sensing, Mechanization and Automation” and in Spring 2021, he will teach “Data Science for Agricultural and Environmental Application.” He is also developing a graduate class entitled “Machine Learning for Agricultural and Environmental Application” to be taught later in 2021.

You can find out more about Dr. Earles' research here.