Research Plant Physiologist · USDA-ARS

N. Ace Pugh,
Ph.D.

crop phenomics × remote sensing × crop breeding and genetics × data science × machine learning

About Me

Nicholas Ace Pugh is a USDA-ARS Research Plant Physiologist at the Cropping Systems Research Laboratory in Lubbock, TX. His research interests include plant breeding and genetics, remote sensing and digital agriculture, and the applied use of artificial intelligence.

Download CV Get in touch
  • #crop-phenomics
  • #remote-sensing
  • #crop-breeding-and-genetics
  • #data-science
  • #machine-learning
📚 My Research

I’m a research scientist at the USDA-ARS. My mission is to use remote sensing and artificial intelligence tools to augment the breeding and production of key crop species.

I use a wide range of remote sensing tools such as small unoccupied aircraft systems (sUAS), or “drones”, satellite imagery, and field-based proximal sensors. Once these data are collected, I use machine learning techniques to estimate or predict key traits including yield, drought tolerance, quality, and more.

Please contact me if you’d like to ask about my work or if you’re interested in collaborating!

Disclaimer: The views expressed on this website are my own and do not necessarily reflect the views of the USDA or the U.S. Government.

Featured Publications
High-throughput phenotyping of stay-green in a sorghum breeding program using unmanned aerial vehicles and machine learning
Yield prediction in a peanut breeding program using remote sensing data and machine learning algorithms
Comparison of image georeferencing strategies for agricultural applications of small unoccupied aircraft systems
A statistical evaluation of replicated block designs and spatial variability in sorghum performance trials
Temporal Estimates of Crop Growth in Sorghum and Maize Breeding Enabled by Unmanned Aerial Systems
Recent Publications
Timothy S. Goebel, James R. Mahan, Paxton Payton, Andrew Young, N. Ace Pugh, Ph.D., Zhanguo Xin, John E. Stout, Robert J. Lascano (2025). Quantifying Temporal Distortions of Artificial UAV Crop Canopy Temperature Measurements. In Advances in Remote Sensing.
DOI
N. Ace Pugh, Ph.D., Andrew Young, Yves Emendack, Jacobo Sanchez, Zhanguo Xin, Chad Hayes (2025). High-throughput phenotyping of stay-green in a sorghum breeding program using unmanned aerial vehicles and machine learning. In The Plant Phenome.
DOI
N. Ace Pugh, Ph.D., Andrew Young, Manisha Ojha, Yves Emendack, Jacobo Sanchez, Zhanguo Xin, Naveen Puppala (2024). Yield prediction in a peanut breeding program using remote sensing data and machine learning algorithms. In Frontiers in Plant Science.
DOI
Chad Hayes, Yves Emendack, Jacobo Sanchez, John Burke, N. Ace Pugh, Ph.D., Zhanguo Xin, William L. Rooney (2023). Evaluation of Diverse Sorghum for Leaf Dhurrin Content and Post-Anthesis (Stay-Green) Drought Tolerance. In MDPI Crops.
DOI
Zhanguo Xin, Yinping Jiao, Gloria Burow, Chad Hayes, Junping Chen, John Burke, N. Ace Pugh, Ph.D., Doreen Ware (2023). Registration of 252 sequenced sorghum mutants as a community reverse genetic resource. In Journal of Plant Registrations.
DOI
See all publications
Recent Blog Posts
Research Update
Research Update
see all