Mason Earles
Assistant Professor of Viticulture & Enology and Biological & Agricultural Engineering, UC Davis
Co-PI and Lead of Agricultural Production Cluster
Mason is an Assistant Professor at UC Davis. He is also Co-PI and Lead of Agricultural Production Cluster for AIFS. During his doctoral and post-doctoral research, he developed computational techniques for 3D image processing and biophysical modeling in plants. His work integrated these techniques with custom instrumentation, shedding light on CO2 diffusion, photosynthesis, H2O transport, and carbohydrate metabolism across plant species.
At UC Davis, he leads the Plant AI and Biophysics Lab, aiming to create affordable AI systems that offer new insights into plant biology, enabling more precise and sustainable agricultural practices. His lab focuses on developing deep learning-powered agricultural sensing and automation systems to monitor plant biophysical status accurately, focusing on stress, productivity, and yield prediction. Further, his lab investigates plant biophysical mechanisms at various levels, seeking to understand their scalability and impact on agricultural systems while emphasizing interpretability over black-box predictions.
Project Involvement
AgML: Open-Source Infrastructure to Accelerate Scaling of Agricultural AI Technologies
Developing an AI-Enabled Toolkit for Routine Integration of Quality Traits into Molecular Breeding Strategies
Developing an AI-Enabled Toolkit for Routine Integration of Quality Traits into Molecular Breeding Strategies
AIFS Publications
Journal Article ⏐ Computers and Electronics in Agriculture 2022Journal Article ⏐ Comput. Electron. Agric. 2022Special Report: AI Institute for Next Generation Food Systems (AIFS)
Tagkopoulos, Ilias,Steve Brown,Xin Liu,Qing Zhao,Tarek I Zohdi,Mason Earles,Nitin Nitin,Daniel Runcie,Danielle G Lemay,Aaron Smith,Pamela Ronald,Hao Feng,and Gabriel YoutseyDOI: 10.1016/j.compag.2022.106819
Journal Article ⏐ Applied and Environmental Microbiology 2022Journal Article ⏐ Appl. Environ. Microbiol. 2022Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging
DOI: 10.1128/aem.01828-22
Conference Article ⏐ International Conference on Computer Vision 2021Conference Article ⏐ ICCV 2021Enlisting 3D Crop Models and GANs for More Data Efficient and Generalizable Fruit Detection
DOI: 10.1109/ICCVW54120.2021.00147
Journal Article ⏐ International Symposium on Visual Computing 2023Journal Article ⏐ ISVC 2023An Open-Source Simulation Toolbox for Annotation of Images and Point Clouds in Agricultural Scenarios
DOI: 10.1007/978-3-031-47969-4_43
Journal Article ⏐ Frontiers in Plant Science 2022Journal Article ⏐ Front. Plant Sci. 2022Non-destructive Plant Biomass Monitoring With High Spatio-Temporal Resolution Via Proximal RGB-D Imagery and End-to-End Deep Learning
DOI: 10.3389/fpls.2022.758818
Conference Article ⏐ IEEE/RSJ International Conference on Intelligent Robots and Systems 2024Conference Article ⏐ IROS 2024DAVIS-Ag: A Synthetic Plant Dataset for Developing Domain-Inspired Active Vision in Agricultural Robots
Choi, Taeyeong,Dario Guevara,Zifei Cheng,Grisha Bandodkar,Chonghan Wang,Brian N Bailey,Mason Earles,and Xin Liu
Journal Article ⏐ Plant Phenomics 2023Journal Article ⏐ Plant Phenomics 2023Standardizing and Centralizing Datasets for Efficient Training of Agricultural Deep Learning Models
DOI: 10.34133/plantphenomics.0084