Genomes To Fields (G2F) Publications

Symbol Legend: * Authors contributed equally to the article

Advanced Science. 2025, 2412423 | 6 March 2025

doi:10.1002/advs.202412423

Leveraging Automated Machine Learning for Environmental Data-Driven Genetic Analysis and Genomic Prediction in Maize Hybrids

Kunhui He, Tingxi Yu, Shang Gao, Shoukun Chen, Liang Li, Xuecai Zhang, Changling Huang, Yunbi Xu, Jiankang Wang, Boddupalli M. Prasanna, Sarah Hearne, Xinhai Li, Huihui Li
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bioRχiv. 2025.01.21.634104 | 24 January 2025

doi:10.1101/2025.01.21.634104

Assessing the impact of yield plasticity on hybrid performance in maize

Jensina M. Davis, Lisa M. Coffey, Jonathan Turkus, Lina López-Corona, Kyle Linders, Chidanand Ullagaddi, Dipak K. Santra, Patrick S. Schnable, James C. Schnable
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Frontiers in Plant Science. 2024, 15: 1480463 | 9 December 2024

doi:10.3389/fpls.2024.1480463

Using the Pearson's correlation coefficient as the sole metric to measure the accuracy of quantitative trait prediction: is it sufficient?

Shouhui Pan, Zhongqiang Liu, Yanyun Han, Dongfeng Zhang, Xiangyu Zhao, Jinlong Li, Kaiyi Wang
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Genetics. 2024, iyae195 | 22 November 2024

doi:10.1093/genetics/iyae195

Global genotype by environment prediction competition reveals that diverse modeling strategies can deliver satisfactory maize yield estimates

Jacob D. Washburn, José Ignacio Varela, Alencar Xavier, Qiuyue Chen, David Ertl, Joseph L. Gage, James B. Holland, Dayane Cristina Lima, Maria Cinta Romay, Marco Lopez-Cruz, Gustavo de los Campos, Wesley Barber, Cristiano Zimmer, Ignacio Trucillo Silva, Fabiani Rocha, Renaud Rincent, Baber Ali, Haixiao Hu, Daniel E Runcie, Kirill Gusev, Andrei Slabodkin, Phillip Bax, Julie Aubert, Hugo Gangloff, Tristan Mary-Huard, Theodore Vanrenterghem, Carles Quesada-Traver, Steven Yates, Daniel Ariza-Suárez, Argeo Ulrich, Michele Wyler, Daniel R. Kick, Emily S. Bellis, Jason L. Causey, Emilio Soriano Chavez, Yixing Wang, Ved Piyush, Gayara D. Fernando, Robert K. Hu, Rachit Kumar, Annan J. Timon, Rasika Venkatesh, Kenia Segura Abá, Huan Chen, Thilanka Ranaweera, Shin-Han Shiu, Peiran Wang, Max J. Gordon, B. K. Amos, Sebastiano Busato, Daniel Perondi, Abhishek Gogna, Dennis Psaroudakis, C. P. James Chen, Hawlader A. Al-Mamun, Monica F. Danilevicz, Shriprabha R. Upadhyaya, David Edwards, Natalia de Leon
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Remote Sensing. 2024, 16(21): 4043 | 30 October 2024

doi:10.3390/rs16214043

Multimodal deep learning integration of image, weather, and phenotypic data under temporal effects for early prediction of maize yield

Danial Shamsuddin, Monica F. Danilevicz, Hawlader A. Al-Mamun, Mohammed Bennamoun, David Edwards
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Genetics. 2024, iyae171 | 29 October 2024

doi:10.1093/genetics/iyae171

MegaLMM improves genomic predictions in new environments using environmental covariates

Haixiao Hu, Renaud Rincent, Daniel E Runcie
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Crop Science. 2024 | 15 October 2024

doi:10.1002/csc2.21379

Impact of genotype x environment interaction and selection history on genomic prediction in maize (Zea mays L.)

Martin Costa, James B. Holland, Natalia de Leon, Shawn M. Kaeppler
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The Plant Phenome Journal. 2024, 7(1): e20113 | 29 July 2024

doi:10.1002/ppj2.20113

High temporal resolution unoccupied aerial systems phenotyping provides unique information between flight dates

Jacob D. Washburn, Alper Adak, Aaron J. DeSalvio, Mustafa A. Arik, Seth C. Murray
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Frontiers in Plant Sciences. 2024, 15: 1408047 | 24 July 2024

doi:10.3389/fpls.2024.1408047

Integrating multi-modal remote sensing, deep learning, and attention mechanisms for yield prediction in plant breeding experiments

Claudia Aviles Toledo, Melba M. Crawford, Mitchell R. Tuinstra
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G3: Genes|Genomes|Genetics. 2024, jkae092 | 22 May 2024

doi:10.1093/g3journal/jkae092

Field-based high-throughput phenotyping enhances phenomic and genomic predictions for grain yield and plant height across years in maize

Alper Adak, Aaron J DeSalvio, Mustafa A Arik, Seth C Murray
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Journal of Experimental Botany. 2024: 73(15), 5336-5354, | 8 April 2024

doi:10.1093/jxb/erac146

Climate and genetic data enhancement using deep learning analytics to improve maize yield predictability

Parisa Sarzaeim, Francisco Muñoz-Arriola, Diego Jarquín
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Agronomy. 2024: 14(4), 733 | 2 April 2024

doi:10.3390/agronomy14040733

A Method to Estimate Climate Drivers of Maize Yield Predictability Leveraging Genetic-by-Environment Interactions in the US and Canada

Parisa Sarzaeim, Francisco Muñoz-Arriola
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Journal of Agriculture, Food Systems, and Comminity Development. 2024: 13(2) | 6 March 2024

doi:10.5304/jafscd.2024.132.008

Participatory breeding in organic systems: Experiences from maize case studies in the United States

Christopher Mujjabi, Martin O. Bohn, Michelle M. Wander, Carmen M. Ugarte
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bioRχiv. 2024.02.08.579534 | 12 February 2024

doi:10.1101/2024.02.08.579534

Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions

Igor K. Fernandes, Caio C. Vieira, Kaio O. G. Dias, Samuel B. Fernandes
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Nature Communications. 2023, 14: 6904 | 30 October 2023

doi:10.1038/s41467-023-42687-4

Leveraging data from the Genomes-to-Fields Initiative to investigate genotype-by-environment interactions in maize in North America

Marco Lopez-Cruz, Fernando M. Aguate, Jacob D. Washburn, Natalia de Leon, Shawn M. Kaeppler, Dayane Cristina Lima, Ruijuan Tan, Addie Thompson, Laurence Willard De La Bretonne, Gustavo de los Campos
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BMC Research Notes. 2023, 16: 219 | 14 September 2023

doi:10.1186/s13104-023-06430-y

2020-2021 field seasons of Maize GxE project within the Genomes to Fields Initiative

Dayane Cristina Lima, Alejandro Castro Aviles, Ryan Timothy Alpers, Alden Perkins, Dylan L Schoemaker, Martin Costa, Kathryn J. Michel, Shawn Kaeppler, David Ertl, Maria Cinta Romay, Joseph L. Gage, James Holland, Timothy Beissinger, Martin Bohn, Edward Buckler, Jode Edwards, Sherry Flint-Garcia, Michael A. Gore, Candice N. Hirsch, Joseph E. Knoll, John McKay, Richard Minyo, Seth C. Murray, James Schnable, Rajandeep S. Sekhon, Maninder P. Singh, Erin E. Sparks, Peter Thomison, Addie Thompson, Mitchell Tuinstra, Jason Wallace, Jacob D. Washburn, Teclemariam Weldekidan, Wenwei Xu, Natalia de Leon
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Earth System Science Data. 2023: 15(9), 3963-3990 | 6 September 2023

doi:10.5194/essd-15-3963-2023

CLIM4OMICS: a geospatially comprehensive climate and multi-OMICS database for maize phenotype predictability in the United States and Canada

Parisa Sarzaeim, Francisco Muñoz-Arriola, Diego Jarquín, Hasnat Aslam, Natalia De Leon Gatti
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BMC Research Notes. 2023, 16:148 | 17 July 2023

doi:10.1186/s13104-023-06421-z

Genomes to Fields 2022 Maize Genotype by Environment Prediction Competition

Dayane Cristina Lima, Jacob D. Washburn, José Ignacio Varela, Qiuyue Chen, Joseph L. Gage, Maria Cinta Romay, James Holland, David Ertl, Marco Lopez-Cruz, Fernando M. Aguate, Gustavo de los Campos, Shawn Kaeppler, Timothy Beissinger, Martin Bohn, Edward Buckler, Jode Edwards, Sherry Flint-Garcia, Michael A. Gore, Candice N. Hirsch, Joseph E. Knoll, John McKay, Richard Minyo, Seth C. Murray, Osler A. Ortez, James C. Schnable, Rajandeep S. Sekhon, Maninder P. Singh, Erin E. Sparks, Addie Thompson, Mitchell Tuinstra, Jason Wallace, Teclemariam Weldekidan, Wenwei Xu, Natalia de Leon
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BMC Genomic Data. 2023, 24:24 | 25 May 2023

doi:10.1186/s12863-023-01129-2

2018-2019 field seasons of the Maize Genomes to Fields (G2F) G x E project

Dayane Cristina Lima, Alejandro Castro Aviles, Ryan Timothy Alpers, Bridget A. McFarland, Shawn Kaeppler, David Ertl, Maria Cinta Romay, Joseph L. Gage, James Holland, Timothy Beissinger, Martin Bohn, Edward Buckler, Jode Edwards, Sherry Flint-Garcia, Candice N. Hirsch, Elizabeth Hood, David C. Hooker, Joseph E. Knoll, Judith M. Kolkman, Sanzhen Liu, John McKay, Richard Minyo, Danilo E. Moreta, Seth C. Murray, Rebecca Nelson, James C. Schnable, Rajandeep S. Sekhon, Maninder P. Singh, Peter Thomison, Addie Thompson, Mitchell Tuinstra, Jason Wallace, Jacob D. Washburn, Teclemariam Weldekidan, Randall J. Wisser, Wenwei Xu, Natalia de Leon
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arXiv. 2211.05986 | 11 November 2022

doi:10.48550/arXiv.2211.05986

DeepG2P: Fusing Multi-Modal Data to Improve Crop Production

Swati Sharma, Aditi Partap, Maria Angels de Luis Balaguer, Sara Malvar, Ranveer Chandra
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Crop Science. 2022, 63(2): 511-534 | 5 October 2022

doi:10.1002/csc2.20857

Calibration of a crop growth model in APSIM for 15 publicly available corn hybrids in North America

Cassandra Anne Winn,Sotirios Archontoulis,Jode Edwards
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G3: Genes|Genomes|Genetics. 2022, jkac226 | 19 September 2022

doi:10.1093/g3journal/jkac226

learnMET: an R package to apply machine learning methods for genomic prediction using multi-environment trial data

Cathy C. Westhues, Henner Simianer, Timothy M. Beissinger
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bioRχiv. 2022.07.29.502051 | 30 June 2022

doi:10.1101/2022.07.29.502051

Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning

Daniel R. Kick, Jason G. Wallace, James C. Schnable, Judith M. Kolkman, Barış Alaca, Timothy M. Beissinger, David Ertl, Sherry Flint-Garcia, Joseph L. Gage, Candice N. Hirsch, Joseph E. Knoll, Natalia de Leon, Dayane C. Lima, Danilo Moreta, Maninder P. Singh, Teclemariam Weldekidan, Jacob D. Washburn
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Proceedings Volume 11414, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V. 1141402 | 13 May 2022

doi:10.1117/12.2558729

Investigating the potential of satellite imagery for high-throughput field phenotyping applications

Sindhuja Sankaran, Chongyuan Zhang, J. Preston Hurst, Afef Marzougui, Arun Narenthiran Veeranampalayam-Sivakumar, Jiating Li, James Schnable, Yeyin Shi
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arXiv. 2203.15629 | 29 March 2022

doi:10.48550/arXiv.2203.15629

Stochastic Conservative Contextual Linear Bandits

Jiabin Lin, Xian Yeow Lee, Talukder Jubery, Shana Moothedath, Soumik Sarkar, Baskar Ganapathysubramanian
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G3: Genes|Genomes|Genetics. 2022, 12(2) | 28 December 2021

doi:10.1093/g3journal/jkab440

Environment-specific genomic prediction ability in maize using environmental covariates depends on environmental similarity to training data

Anna R. Rogers, James B. Holland
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Frontiers in Plant Sciences. 2021, 12: 2529 | 11 November 2021

doi:10.3389/fpls.2021.699589

Prediction of Maize Phenotypic Traits With Genomic and Environmental Predictors Using Gradient Boosting Frameworks

Cathy C. Westhues, Gregory S. Mahone, Sofia da Silva, Patrick Thorwarth, Malthe Schmidt, Jan-Christoph Richter, Henner Simianer, Timothy M. Beissinger
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Theoretical and Applied Genetics. 2021, 134: 3997-4001 | 27 August 2021

doi:10.1007/s00122-021-03943-7

Predicting phenotypes from genetic, environment, management, and historical data using CNNs

Jacob D. Washburn, Emre Cimen, Guillaume Ramstein, Timothy Reeves, Patrick O'Briant, Greg McLean, Mark Cooper, Graeme Hammer, Edward S. Buckler
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Frontiers in Genetics. 2021, 11: 1819 | 8 Mach 2021

doi:10.3389/fgene.2020.592769

Utility of Climatic Information via Combining Ability Models to Improve Genomic Prediction for Yield within the Genomes to Fields Maize Project

Diego Jarquín, Natalia de Leon, Cinta Romay, Martin Bohn, Edward S. Buckler, Ignacio Ciampitti, Jode Edwards, David Ertl, Sherry Flint-Garcia, Michael A. Gore, Christopher Graham, Candice N. Hirsch, James B. Holland, David Hooker, Shawn M. Kaeppler, Joseph Knoll, Elizabeth C. Lee, Carolyn J. Lawrence-Dill, Jonathan P. Lynch, Stephen P. Moose, Seth C. Murray, Rebecca Nelson, Torbert Rocheford, James C. Schnable, Patrick S. Schnable, Margaret Smith, Nathan Springer, Peter Thomison, Mitch Tuinstra, Randall J. Wisser, Wenwei Xu, Jianming Yu, Aaron Lorenz
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G3: Genes|Genomes|Genetics. 2021, 11(2): jkaa050 | 4 January 2021

doi:10.1093/g3journal/jkaa050

The Importance of Dominance and Genotype-by-Environment Interactions on Grain Yield Variation in a Large-Scale Public Cooperative Maize Experiment

Anna R. Rogers, Jeffrey C. Dunne, Cinta Romay, Martin Bohn, Edward S. Buckler, Ignacio A. Ciampitti, Jode Edwards, David Ertl, Sherry Flint-Garcia, Michael A. Gore, Christopher Graham, Candice N. Hirsch, Elizabeth Hood, David C. Hooker, Joseph Knoll, Elizabeth C. Lee, Aaron Lorenz, Jonathan P. Lynch, John McKay, Stephen P. Moose, Seth C. Murray, Rebecca Nelson, Torbert Rocheford, James C. Schnable, Patrick S. Schnable, Rajandeep Sekhon, Maninder Singh, Margaret Smith, Nathan Springer, Kurt Thelen, Peter Thomison, Addie Thompson, Mitch Tuinstra, Jason Wallace, Randall J. Wisser, Wenwei Xu, A. R. Gilmour, Shawn M. Kaeppler, Natalia De Leon, James B. Holland
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Transactions of the ASABE. 64(3): 879-891 | 1 January 2021

doi:10.13031/trans.14197

Can High-Resolution Satellite Multispectral Imagery Be Used to Phenotype Canopy Traits and Yield Potential in Field Conditions?

Sindhuja Sankaran, Afef Marzougui, J. Preston Hurst, Chongyuan Zhang, James C. Schnable, Yeyin Shi
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Theoretical and Applied Genetics. 2020 | 1 July 2020

doi:10.1007/s00122-020-03637-6

Temporal covariance structure of multi-spectral phenotypes and their predictive ability for end-of-season traits in maize

Mahlet T. Anche, Nicholas S. Kaczmar, Nicolas Morales, James W. Clohessy, Daniel C. Ilut, Michael A. Gore, Kelly R. Robbins
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The Plant Phenome Journal. 2020, 3(1): e20004 | 15 May 2020

doi:10.1002/ppj2.20004

ImageBreed: Open-access plant breeding web-database for image-based phenotyping

Nicolas Morales, Nicholas S. Kaczmar, Nicholas Santantonio, Michael A. Gore, Lukas A. Mueller, Kelly R. Robbins
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Field Crops Research. 2020, 249: 107737 | 1 April 2020

doi:10.1016/j.fcr.2020.107737

Stalk bending strength is strongly associated with maize stalk lodging incidence across multiple environments

Rajandeep S. Sekhon, Chase N. Joyner, Arlyn J. Ackerman, Christopher S. McMahan, Douglas D. Cook, Daniel J. Robertson
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BMC Research Notes. 2020, 13: 71 | 12 February 2020

doi:10.1186/s13104-020-4922-8

Maize genomes to fields (G2F): 2014–2017 field seasons: genotype, phenotype, climatic, soil, and inbred ear image datasets

Bridget A. McFarland*, Naser AlKhalifah*, Martin Bohn, Jessica Bubert, Edward S. Buckler, Ignacio Ciampitti, Jode Edwards, David Ertl, Joseph L. Gage, Celeste M. Falcon, Sherry Flint-Garcia, Michael A. Gore, Christopher Graham, Candice N. Hirsch, James B. Holland, Elizabeth Hood, David Hooker, Diego Jarquín, Shawn M. Kaeppler, Joseph Knoll, Greg Kruger, Nick Lauter, Elizabeth C. Lee, Dayane C. Lima, Aaron Lorenz, Jonathan P. Lynch, John McKay, Nathan D. Miller, Stephen P. Moose, Seth C. Murray, Rebecca Nelson, Christina Poudyal, Torbert Rocheford, Oscar Rodriguez, Maria Cinta Romay, James C. Schnable, Patrick S. Schnable, Brian Scully, Rajandeep Sekhon, Kevin Silverstein, Maninder Singh, Margaret Smith, Edgar P. Spalding, Nathan Springer, Kurt Thelen, Peter Thomison, Mitchell Tuinstra, Jason Wallace, Ramona Walls, David Wills, Randall J. Wisser, Wenwei Xu, Cheng-Ting Yeh, Natalia de Leon
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Crop Science. 2020, 60(1): 62-81| 19 December 2019

doi:10.2135/cropsci2019.05.0294

Relative utility of agronomic, phenological, and morphological traits for assessing genotype-by-environment interaction in maize inbreds

Celeste M. Falcon, Shawn M. Kaeppler, Edgar P. Spalding, Nathan D. Miller, Nicholas Haase, Naser AlKhalifah, Martin Bohn, Edward S. Buckler, Darwin A. Campbell, Ignacio Ciampitti, Lisa Coffey, Jode Edwards, David Ertl, Sherry Flint-Garcia, Michael A. Gore, Christopher Graham, Candice N. Hirsch, James B. Holland, Diego Jarquín, Joseph Knoll, Nick Lauter, Carolyn J. Lawrence-Dill, Elizabeth C. Lee, Aaron Lorenz, Jonathan P. Lynch, Seth C. Murray, Rebecca Nelson, Cinta M. Romay, Torbert Rocheford, Patrick S. Schnable, Brian Scully, Margaret Smith, Nathan Springer, Mitch Tuinstra, Renee Walton, Teclemariam Weldekidan, Randall J. Wisser, Wenwei Xu, Natalia de Leon
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Frontiers in Plant Science. 2019, 10: 1550 | 12 December 2019

doi:10.3389/fpls.2019.01550

Millimeter-Level Plant Disease Detection From Aerial Photographs via Deep Learning and Crowdsourced Data

Tyr Wiesner-Hanks, Harvey Wu, Ethan Stewart, Chad DeChant, Nicholas Kaczmar, Hod Lipson, Michael A. Gore, Rebecca J. Nelson
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The Plant Genome Journal. 2019, 2(1): 190011 | 22 November 2019

doi:10.2135/tppj2019.07.0011

In-Field whole-plant maize architecture characterized by subcanopy rovers and latent space phenotyping

Joseph L. Gage, Elliot Richards, Nicholas Lepak, Nicholas Kaczmar, Chinmay Soman, Girish Chowdhary, Michael A. Gore, Edward S. Buckler
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The Plant Phenome Journal. 2019, 2(1) | 7 November 2019

doi:10.2135/tppj2019.03.0006

Autonomous detection of plant disease symptoms directly from aerial imagery

Harvey Wu, Tyr Wiesner-Hanks, Ethan L. Stewart, Chad DeChant, Nicholas Kaczmar, Michael A. Gore, Rebecca J. Nelson, Hod Lipson
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Remote Sensing. 2019, 11: 2209 | 29 July 2019

doi:10.3390/rs11192209

Quantitative phenotyping of northern leaf blight in uav images using deep learning

Ethan L. Stewart, Tyr Wiesner-Hanks, Nicholas Kaczmar, Chad DeChant, Harvey Wu, Hod Lipson, Rebecca J. Nelson, Michael A. Gore
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Plant Phenome Journal. 2019, 2: 190004 | 11 July 2019

doi:10.2135/tppj2019.02.0004

Prediction of maize grain yield before maturity using improved temporal height estimates of unmanned aerial systems

Steven L. Anderson, Seth C. Murray, Lonesome Malambo, Colby Ratcliff, Sorin Popescu, Dale Cope, Anjin Chang, Jinha Jung, J. Alex Thomasson
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Crop Science. 2019, 59(4): 1406-1410 | 27 June 2019

doi:10.2135/cropsci2019.02.0071

Idea factory: the maize genomes to fields initiative

Carolyn J. Lawrence-Dill, Patrick S. Schnable, Nathan M. Springer
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Computers and Electronics in Agriculture. 2019, 160: 71-81 | 16 March 2019

doi:10.1016/j.compag.2019.03.009

NU-Spidercam: A large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research

Geng Bai, Yufeng Ge, David Scoby, Bryan Leavitt, Vincent Stoerger, Norbert Kirchgessner, Suat Irmak, George Graef, James Schnable, Tala Awada
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BCB '18: Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. 2018, pp. 155-164 | August 29 - September 1, 2018

doi:10.1145/3233547.3233593

Detecting divergent subpopulations in phenomics data using interesting flares

Methun Kamruzzaman, Ananth Kalyanaraman, Bala Krishnamoorthy
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BMC Research Notes. 2018, 11: 452 | 9 July 2018

doi:10.1186/s13104-018-3508-1

Maize genomes to fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets

Naser AlKhalifah*, Darwin A. Campbell*, Celeste M. Falcon*, Jack M. Gardiner*, Nathan D. Miller*, Maria Cinta Romay*, Ramona Walls*, Renee Walton*, Cheng-Ting Yeh*, Martin Bohn, Jessica Bubert, Edward S. Buckler, Ignacio Ciampitti, Sherry Flint-Garcia, Michael A. Gore, Christopher Graham, Candice Hirsch, James B. Holland, David Hooker, Shawn Kaeppler, Joseph Knoll, Nick Lauter, Elizabeth C. Lee, Aaron Lorenz, Jonathan P. Lynch, Stephen P. Moose, Seth C. Murray, Rebecca Nelson, Torbert Rocheford, Oscar Rodriguez, James C. Schnable, Brian Scully, Margaret Smith, Nathan Springer, Peter Thomison, Mitchell Tuinstra, Randall J. Wisser, Wenwei Xu, David Ertl, Patrick S. Schnable, Natalia De Leon, Edgar P. Spalding, Jode Edwards, Carolyn J. Lawrence-Dill
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BMC Research Notes. 2018, 11: 440 | 3 July 2018

doi:10.1186/s13104-018-3548-6

Image set for deep learning: field images of maize annotated with disease symptoms

Tyr Wiesner-Hanks, Ethan L. Stewart, Nicholas Kaczmar, Chad DeChant, Harvey Wu, Rebecca J. Nelson, Hod Lipson, Michael A. Gore
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Genomes to Fields NIFA Fact Workshop Whitepaper | January 28-30, 2018

2018 NIFA FACT workshop: high throughput, field-based phenotyping technologies for the genomes to fields (G2F) initiative

Carolyn J. Lawrence-Dill, Patrick Schnable, Nathan Springer, and: Natalia De Leon, Jode Edwards, David Ertl, Shawn Kaeppler, Nick Lauter, John McKay, Francisco Munoz-Arriola, Seth Murray, Duke Pauli, Nathalia Penna Cruzato, Colby Ratcliff, James Schnable, Kevin Silverstein, Edgar P. Spalding, Addie Thompson, Ruth Wagner, Jason Wallace, Justin Walley, Jianming Yu.
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Nature Communications. 2017, 8(1): 1348 | 7 November 2017

doi:10.1038/s41467-017-01450-2

The effect of artificial selection on phenotypic plasticity in maize

Joseph L. Gage, Diego Jarquín, Cinta Romay, Aaron Lorenz, Edward S. Buckler, Shawn Kaeppler, Naser Alkhalifah, Martin Bohn, Darwin A. Campbell, Jode Edwards, David Ertl, Sherry Flint-Garcia, Jack Gardiner, Byron Good, Candice N. Hirsch, Jim Holland, David C. Hooker, Joseph Knoll, Judith Kolkman, Greg Kruger, Nick Lauter, Carolyn J. Lawrence-Dill, Elizabeth Lee, Jonathan Lynch, Seth C. Murray, Rebecca Nelson, Jane Petzoldt, Torbert Rocheford, James Schnable, Patrick S. Schnable, Brian Scully, Margaret Smith, Nathan M. Springer, Srikant Srinivasan, Renee Walton, Teclemariam Weldekidan, Randall J. Wisser, Wenwei Xu, Jianming Yu, Natalia de Leon
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Phytopathology. 2017, 107: 1426-1432 | 24 August 2017

doi:10.1094/PHYTO-11-16-0417-R

Automated identification of northern leaf blight-infected maize plants from field imagery using deep learning

Chad DeChant, Tyr Wiesner-Hanks, Siyuan Chen, Ethan L. Stewart, Jason Yosinski, Michael A. Gore, Rebecca J. Nelson, Hod Lipson
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