Papers

• CMAViT: Integrating Climate, Management, and Remote Sensing Data for Crop Yield Prediction With Multimodel Vision Transformers — (2026)

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• Are vision-language models ready to zero-shot replace supervised classification models in agriculture? — Ranario, Earl, Earles, J. Mason (2026) Code Website

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• Using Vision Language Foundation Models to Generate Plant Simulation Configurations via In-Context Learning — Heesup Yun, Isaac Kazuo Uyehara, Earl Ranario, Lars Lundqvist, Christine H. Diepenbrock, Brian N. Bailey, J. Mason Earles (2026) Website

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• Evapotranspiration Forecasting for Weather-Driven Agricultural Water Management by Harnessing Deep Learning — (2025)
• Enabling Plant Phenotyping in Weedy Environments using Multi-Modal Imagery via Synthetic and Generated Training Data — (2025)
• Integration of crop modeling and sensing into molecular breeding for nutritional quality and stress tolerance — (2025)
• California Crop Yield Benchmark: Combining Satellite Image, Climate, Evapotranspiration, and Soil Data Layers for County-Level Yield Forecasting of Over 70 Crops — Hamid Kamangir, Mona Hajiesmaeeli, J. Mason Earles (2025) Code

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• iNatAg: Multi-Class Classification Models Enabled by a Large-Scale Benchmark Dataset with 4.7M Images of 2,959 Crop and Weed Species — Naitik Jain, Amogh Joshi, J. Mason Earles (2025) Code

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• Strawberry fruit yield forecasting using image-based time-series plant phenological stages sequences — Andres Montes de Oca, Troy Magney, Stavros G. Vougioukas, Dario Racano, Alejandro Torrez-Orozco, Steven A. Fennimore, Frank N. Martin, J. Mason Earles (2025) Code

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• Leaf hyperspectral reflectance detects pre‐visual stress to Fusarium wilt in strawberries — Jessie Au, Christopher Y. S. Wong, Dominique D. A. Pincot, Frank N. Martin, Rishav Ray, J. Mason Earles, Troy S. Magney (2025)
• Enhancing AI microscopy for foodborne bacterial classification using adversarial domain adaptation to address optical and biological variability — Siddhartha Bhattacharya, Aarham Wasit, J. Mason Earles, Nitin Nitin, Jiyoon Yi (2025) Code
• Comparison of Mask-R-CNN and Thresholding-Based Segmentation for High-Throughput Phenotyping of Walnut Kernel Color — Steven H. Lee, Sean McDowell, Charles Leslie, Kristina McCreery, J. Mason Earles, Patrick J. Brown (2025)
• AgRowStitch: A High-fidelity Image Stitching Pipeline for Ground-based Agricultural Images — Uyehara, Isaac Kazuo, Yun, Heesup, Ranario, Earl, Earles, J. Mason (2025) Code
• AGILE: A Diffusion-Based Attention-Guided Image and Label Translation for Efficient Cross-Domain Plant Trait Identification — Earl Ranario, Lars Lundqvist, Heesup Yun, Brian N. Bailey, J. Mason Earles (2025) Code Website
• Forecasting Satellite-based Actual Evapotranspiration using Deep Learning in California Cropping Systems — (2024)
• VisTA-SR: improving the accuracy and resolution of low-cost thermal imaging cameras for agriculture — (2024) Website
• The AIFS Institute: Building a better food system through AI — Ilias Tagkopoulos, J. Mason Earles, Danielle G. Lemay, Xin Liu, Nitin Nitin, Aaron D. Smith, Tarek I. Zohdi, Stephen F. Brown (2024)
• Simulation of Automatically Annotated Visible and Multi-/Hyperspectral Images Using the Helios 3D Plant and Radiative Transfer Modeling Framework — Tong Lei, Jan Graefe, Ismael K. Mayanja, J. Mason Earles, Brian N. Bailey (2024)
• Enhancing AI microscopy for foodborne bacterial classification via adversarial domain adaptation across optical and biological variability — Bhattacharya, Siddhartha, Wasit, Aarham, Earles, J. Mason, Nitin, Nitin, Ma, Luyao, Yi, Jiyoon (2024)
• Deep learning enabled rapid classification of yeast species in food by imaging of yeast microcolonies — Hyeon Woo Park, J. Mason Earles, Nitin Nitin (2024)
• Predicting Crop Yield Lows Through Highs via Binned Deep Imbalanced Regression — Hamid Kamangir, J. Mason Earles (2024) Code
• Large-scale spatio-temporal yield estimation via deep learning using satellite and management data fusion in vineyards — Hamid Kamangir, Brent S. Sams, Nick Dokoozlian, Luis Sanchez, J. Mason Earles (2024) Code
• DAVIS-Ag: A Synthetic Plant Dataset for Prototyping Domain-Inspired Active Vision in Agricultural Robots — Taeyeong Choi, Dario Guevara, Zifei Cheng, Grisha Bandodkar, Chonghan Wang, Brian N. Bailey, J. Mason Earles, Xin Liu (2024) Code
• Site-Specific Soil Pest Management in Strawberry and Vegetable Cropping Systems Using Crop Rotation and a Needs-Based Variable Rate Fumigation Strategy — (2023)
• Novel algorithms for high-resolution prediction of canopy evapotranspiration in grapevine — Matthew Jenkins, Autumn Mannsfeld, Shayla Nikzad, Jean-Jacques Lambert, Konrad Miller, Mark Burns, J. Mason Earles, David E. Block (2023)
• Erratum for Ma et al., “Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging” — Luyao Ma, Jiyoon Yi, Nicharee Wisuthiphaet, J. Mason Earles, Nitin Nitin (2023)
• Biometeorological Dataset for 'Novel algorithms for high resolution prediction of canopy evapotranspiration in grapevine' — Jenkins, Matthew, Mannsfeld, Autumn, Nikzad, Shayla, Lambert, Jean-Jacques, Miller, Konrad, Burns, Mark, Earles, J. Mason, Block, David E. (2023)
• Automated parameterization of stomatal conductance models from thermal imagery by leveraging synthetic images generated from Helios 3D biophysical model simulations — Ismael Mayanja, Heesup Yun, J. Mason Earles, Brian N. Bailey (2023)
• An Open Source Simulation Toolbox for Annotation of Images and Point Clouds in Agricultural Scenarios — Dario Guevara, Amogh Joshi, Pranav Raja, Elisabeth Forrestel, Brian Bailey, J. Mason Earles (2023)
• AI-enabled biosensing for rapid pathogen detection: From liquid food to agricultural water — Jiyoon Yi, Nicharee Wisuthiphaet, Pranav Raja, Nitin Nitin, J. Mason Earles (2023)
• Leveraging Artificial Intelligence in the Improvement of Yield and Quality in Nutritional Security Crops — (2022)
• End-to-end prediction of uniaxial compression profiles of apples during in vitro digestion using time-series micro-computed tomography and deep learning — (2022)
• End-to-end deep learning for directly estimating grape yield from ground-based imagery — (2022)
• Structural and functional leaf diversity lead to variability in photosynthetic capacity across a range of Juglans regia genotypes — Mina Momayyezi, Devin A. Rippner, Fiona V. Duong, Pranav V. Raja, Patrick J. Brown, Daniel A. Kluepfel, J. Mason Earles, Elisabeth J. Forrestel, Matthew E. Gilbert, Andrew J. McElrone (2022)
• Standardizing and Centralizing Datasets to Enable Efficient Training of Agricultural Deep Learning Models — Joshi, Amogh, Guevara, Dario, Earles, J. Mason (2022) Code
• Non-destructive Plant Biomass Monitoring With High Spatio-Temporal Resolution via Proximal RGB-D Imagery and End-to-End Deep Learning — Nicolas Buxbaum, Johann Heinrich Lieth, J. Mason Earles (2022)
• Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging — Luyao Ma, Jiyoon Yi, Nicharee Wisuthiphaet, J. Mason Earles, Nitin Nitin (2022)
• A workflow for segmenting soil and plant X-ray CT images with deep learning in Googles Colaboratory — Rippner, Devin A., Raja, Pranav, Earles, J. Mason, Buchko, Alexander, Momayyezi, Mina, Duong, Fiona, Parkinson, Dilworth, Forrestel, Elizabeth, Shackel, Ken, Neyhart, Jeffrey, McElrone, Andrew J. (2022)
• Site-specific soil pest management in strawberry & vegetable cropping systems — (2021)
• The three‐dimensional construction of leaves is coordinated with water use efficiency in conifers — Santiago Trueba, Guillaume Théroux‐Rancourt, J. Mason Earles, Thomas N. Buckley, David Love, Daniel M. Johnson, Craig Brodersen (2021)
• The 3D construction of leaves is coordinated with water use efficiency in conifers — Santiago Trueba, Guillaume Théroux-Rancourt, J. Mason Earles, Thomas N. Buckley, David Love, Daniel M Johnson, Craig Brodersen (2021)
• Supplementary Tables from Maximum CO₂ diffusion inside leaves is limited by the scaling of cell size and genome size — Théroux-Rancourt, Guillaume, Roddy, Adam B., J. Mason Earles, Gilbert, Matthew E., Zwieniecki, Maciej A., C. Kevin Boyce, Tholen, Danny, McElrone, Andrew J., Simonin, Kevin A., Brodersen, Craig R. (2021)
• Simultaneously Predicting Multiple Plant Traits from Multiple Sensors via Deformable CNN Regression — Raja, Pranav, Olenskyj, Alex, Kamangir, Hamid, Earles, J. Mason (2021)
• R script used to generate the theoretical conductance values based on cell size and leaf porosity. from Maximum CO₂ diffusion inside leaves is limited by the scaling of cell size and genome size — Théroux-Rancourt, Guillaume, Roddy, Adam B., J. Mason Earles, Gilbert, Matthew E., Zwieniecki, Maciej A., C. Kevin Boyce, Tholen, Danny, McElrone, Andrew J., Simonin, Kevin A., Brodersen, Craig R. (2021)
• R script used to generate the theoretical conductance values based on cell size and leaf porosity. from Maximum CO₂ diffusion inside leaves is limited by the scaling of cell size and genome size — Théroux-Rancourt, Guillaume, Roddy, Adam B., J. Mason Earles, Gilbert, Matthew E., Zwieniecki, Maciej A., C. Kevin Boyce, Tholen, Danny, McElrone, Andrew J., Simonin, Kevin A., Brodersen, Craig R. (2021)
• Maximum CO ₂ diffusion inside leaves is limited by the scaling of cell size and genome size — Guillaume Théroux-Rancourt, Adam B. Roddy, J. Mason Earles, Matthew E. Gilbert, Maciej A. Zwieniecki, C. Kevin Boyce, Danny Tholen, Andrew J. McElrone, Kevin A. Simonin, Craig R. Brodersen (2021)
• Improving Walnut (J. regia) Kernel Color Analyses — Steven Lee, J. Mason Earles, Sean McDowell, Patrick Brown (2021)
• Enlisting 3D Crop Models and GANs for More Data Efficient and Generalizable Fruit Detection — Zhenghao Fei, Alex Olenskyj, Brian N. Bailey, J. Mason Earles (2021) Code
• MicroCT data to 'Maximum CO2 diffusion inside leaves is limited by the scaling of cell size and genome size' — Théroux-Rancourt, Guillaume, Roddy, Adam. B., Earles, J. Mason, Boyce, C. Kevin, Zwieniecki, Maciej A., McElrone, Andrew J., Brodersen, Craig R. (2020)
• MicroCT data to 'Maximum CO2 diffusion inside leaves is limited by the scaling of cell size and genome size' — Théroux-Rancourt, Guillaume, Roddy, Adam. B., Earles, J. Mason, Boyce, C. Kevin, Zwieniecki, Maciej A., McElrone, Andrew J., Brodersen, Craig R. (2020)
• Maximum CO ₂ diffusion inside leaves is limited by the scaling of cell size and genome size — Guillaume Théroux-Rancourt, Adam B. Roddy, J. Mason Earles, Matthew E. Gilbert, Maciej A. Zwieniecki, C. Kevin Boyce, Danny Tholen, Andrew J. McElrone, Kevin A. Simonin, Craig R. Brodersen (2020)
• Image Dataset for 'Digitally deconstructing leaves in 3D using X-ray microcomputed tomography and machine learning' — Théroux-Rancourt, Guillaume, Jenkins, Matthew R., Earles, J. Mason (2020)
• Image Dataset for 'Digitally deconstructing leaves in 3D using X-ray microcomputed tomography and machine learning' — Théroux-Rancourt, Guillaume, Jenkins, Matthew R., Earles, J. Mason (2020)
• Digitally deconstructing leaves in 3D using X‐ray microcomputed tomography and machine learning — Guillaume Théroux‐Rancourt, Matthew R. Jenkins, Craig R. Brodersen, Andrew McElrone, Elisabeth J. Forrestel, J. Mason Earles (2020)
• Spatiotemporal Coupling of Vessel Cavitation and Discharge of Stored Xylem Water in a Tree Sapling — Thorsten Knipfer, Clarissa Reyes, J. Mason Earles, Z. Carter Berry, Daniel M. Johnson, Craig R. Brodersen, Andrew J. McElrone (2019)
• Dynamics of carbohydrate storage in trees — Tixier, Aude, Orozco, Jessica, Amico Roxas, Adèle, Guzman, Paula, Earles, J. Mason, Sperling, Or, Zwieniecki, Maciej (2019)
• Digitally Deconstructing Leaves in 3D Using X-ray Microcomputed Tomography and Machine Learning — Guillaume Théroux-Rancourt, Matthew R. Jenkins, Craig R. Brodersen, Andrew McElrone, Elisabeth J. Forrestel, J. Mason Earles (2019)
• In vivo quantification of plant starch reserves at micrometer resolution using X‑ray microCT imaging and machine learning — (2018)
• Insight into the physiological role of water absorption via the leaf surface from a rehydration kinetics perspective — Paula Guzmán‐Delgado, J. Mason Earles, Maciej A. Zwieniecki (2018)
• Extreme mid‐winter drought weakens tree hydraulic–carbohydrate systems and slows growth — J. Mason Earles, Jens T. Stevens, Or Sperling, Jessica Orozco, Malcolm P. North, Maciej A. Zwieniecki (2018)
• Embracing 3D Complexity in Leaf Carbon–Water Exchange — J. Mason Earles, Thomas N. Buckley, Craig R. Brodersen, Florian A. Busch, F. Javier Cano, Brendan Choat, John R. Evans, Graham D. Farquhar, Richard Harwood, Minh Huynh, Grace P. John, Megan L. Miller, Fulton E. Rockwell, Lawren Sack, Christine Scoffoni, Paul C. Struik, Alex Wu, Xinyou Yin, Margaret M. Barbour (2018)
• Diurnal Variation in Nonstructural Carbohydrate Storage in Trees: Remobilization and Vertical Mixing — Aude Tixier, Jessica Orozco, Adele Amico Roxas, J. Mason Earles, Maciej A. Zwieniecki (2018)
• Changes in xylem conducting capacity and water storage across species: how can variable air content of xylem cells affect sap flow? — A.J. McElrone, J. Mason Earles, T.M. Knipfer, C.P. Albuquerque, C.R. Brodersen, I.F. Cuneo (2018)
• Beyond porosity: 3D leaf intercellular airspace traits that impact mesophyll conductance — J. Mason Earles, Guillaume Théroux‐Rancourt, Matthew E. Gilbert, Danny Tholen, Andrew J. McElrone, Craig R. Brodersen (2018)
• Beyond Porosity: 3D Leaf Intercellular Airspace Traits That Impact Mesophyll Conductance — J. Mason Earles, Guillaume Theroux-Rancourt, Adam B. Roddy, Matthew E. Gilbert, Andrew J. McElrone, Craig R. Brodersen (2018)
• In vivo quantification of plant starch reserves at micrometer resolution using X‐ray microCT imaging and machine learning — J. Mason Earles, Thorsten Knipfer, Aude Tixier, Jessica Orozco, Clarissa Reyes, Maciej A. Zwieniecki, Craig R. Brodersen, Andrew J. McElrone (2018)
• The bias of a two‐dimensional view: comparing two‐dimensional and three‐dimensional mesophyll surface area estimates using noninvasive imaging — Guillaume Théroux‐Rancourt, J. Mason Earles, Matthew E. Gilbert, Maciej A. Zwieniecki, C. Kevin Boyce, Andrew J. McElrone, Craig R. Brodersen (2017)
• Storage Compartments for Capillary Water Rarely Refill in an Intact Woody Plant  — Thorsten Knipfer, Italo F. Cuneo, J. Mason Earles, Clarissa Reyes, Craig R. Brodersen, Andrew J. McElrone (2017)
• Spring bud growth depends on sugar delivery by xylem and water recirculation by phloem Münch flow in Juglans regia — Aude Tixier, Or Sperling, Jessica Orozco, Bruce Lampinen, Adele Amico Roxas, Sebastian Saa, J. Mason Earles, Maciej A. Zwieniecki (2017)
• Excess Diffuse Light Absorption in Upper Mesophyll Limits CO₂ Drawdown and Depresses Photosynthesis — J. Mason Earles, Guillaume Théroux-Rancourt, Matthew E. Gilbert, Andrew J. McElrone, Craig R. Brodersen (2017)
• Angiosperms evolved a higher mesophyll surface area per volume to maximize exchange surface under a low CO2 world — Guillaume Théroux‐Rancourt, J. Mason Earles, Matthew E. Gilbert, Maciej A. Zwieniecki, C. Kevin Boyce, Andrew J. McElrone, Craig R. Brodersen (2017)
• Long‐term climate and competition explain forest mortality patterns under extreme drought — Derek J. N. Young, Jens T. Stevens, J. Mason Earles, Jeffrey Moore, Adam Ellis, Amy L. Jirka, Andrew M. Latimer (2016)
• Long-term climate and competition explain regional forest mortality patterns under extreme drought — Derek J. N. Young, Andrew M. Latimer, Jens T. Stevens, J. Mason Earles, Adam Ellis, A. Jirka, Jeffrey Moore (2016)
• Data from: Long-term climate and competition explain forest mortality patterns under extreme drought — Young, Derek J. N., Stevens, Jens T., Earles, J. Mason, Moore, Jeffrey, Ellis, Adam, Jirka, Amy L., Latimer, Andrew M. (2016)
• Appendix A. A table depicting stand characteristics of modeled mixed-conifer conditions and a figure showing carbon carrying capacity for 24 scenarios examined. — J. Mason Earles, North, Malcolm P., Hurteau, Matthew D. (2016)
• Frost Induces Respiration and Accelerates Carbon Depletion in Trees — Or Sperling, J. Mason Earles, Francesca Secchi, Jessie Godfrey, Maciej A. Zwieniecki (2015)
• Bark water uptake promotes localized hydraulic recovery in coastal redwood crown — J. Mason Earles, Or Sperling, Lucas C. R. Silva, Andrew J. McElrone, Craig R. Brodersen, Malcolm P. North, Maciej A. Zwieniecki (2015)
• Wildfire and drought dynamics destabilize carbon stores of fire‐suppressed forests — J. Mason Earles, Malcolm P. North, Matthew D. Hurteau (2014)
• Integrated economic equilibrium and life cycle assessment modeling for policy‐based consequential LCA — (2013)
• Timing of carbon emissions from global forest clearance — J. Mason Earles, Sonia Yeh, Kenneth E. Skog (2012)
• LCA and Forest Biorefining: Environmental Assessment of a Modified OSB Mill and an Integrated Partial Equilibrium Framework for Policy Analysis — J. Mason Earles (2011)
• Improving the Environmental Profile of Wood Panels via Co-Production of Ethanol and Acetic Acid — J. Mason Earles, Anthony Halog, Stephen Shaler (2011)
• Consequential life cycle assessment: a review — J. Mason Earles, Anthony Halog (2011)
• Comparative life cycle assessment of biofuel produced in two forest product biorefineries — J. Mason Earles, Anthony Halog (2010)

Team

Current Members

Apoorva Jha (PhD Student)

Earl Ranario (PhD Student) 

Hamid Kamangir (Postdoc) 

Heesup Yun (PhD Student) 

Lars Lundqvist (Undergrad)

Mason Earles (PI)

Riley Hibbard (MS Student)

Vishal Singh (PhD Student)

Past Members

Alex Olenskyj (Postdoc)

Amogh Joshi (High Schooler) 

Autumn Mansfield (Undergrad)

Dario Guevara (Postdoc)

Jiyoon Yi (Postdoc)

Nico Buxbaum (MS)

Noah Tarr (MS)

Pranav Raja (MS)

Sean McDowell (Undergrad)

Zhenghao Fei (Postdoc)

Code

• Lab — UC Davis research lab focused on developing AI-enabled solutions for agriculture and food systems.
• GEMINI — G×E×M Innovation in Intelligence for Climate Adaptation: a state-of-the-art breeding toolkit combining AI-enabled sensing, 3-D crop modeling, and molecular breeding to accelerate stress-resistant, nutritious staple crops for low and middle-income countries. GEMINI App
• AgML — A centralized framework for agricultural machine learning. Provides access to public agricultural datasets for common deep learning tasks, with standard benchmarks, pretrained models, and synthetic data generation.