This story was first published in the Davis College NewsCenter. See the original article here.
Cutting edge agriculture featuring UAV Remote Sensing, EC Mapping, RTK Automatic Guidance and Data Processing, along with oral and poster presentations, were part of a Precision Agriculture Workshop on Friday (Aug. 9) at Texas Tech’s Department of Plant & Soil Science Building and the Quaker Research Farm.
The technology demonstrations and workshop were related to the education and training component of a USDA-funded grant, called Capacity Building for AI-driven Research and Education on UAS Applications in Precision Agriculture. The institutions participating in the event include Texas Tech, Texas A&M University, West Texas A&M University, Texas A&M AgriLife Research and Extension, and the USDA's Agricultural Research Service.
Presentations included a program overview by Wenxuan Guo, an Associate Professor of Crop Ecophysiology & Precision Agriculture at Texas Tech University and Texas A&M AgriLife Research. That portion of the program was followed by ‘Application of UAV images in cotton cultivar selection’ Craig Bednarz team, West Texas A&M; ‘Use of thermal remote sensing for monitoring cotton performance,’ Nithya Rajan Team, Texas A&M; ‘Technology demonstration (Guidance system and EC mapping)’ Wenxuan Guo Team; and ‘Technology demonstration (UAV image acquisition).’ Wenxuan Guo Team.
Afternoon sessions featured ‘Effects of spatial resolution on assessing cotton water stress using UAV images, Oluwatola Adedeji; ‘UAV and Sentinel-2 Images in estimating cotton nitrogen content’ Rupak Karn; ‘Sorghum phenotyping using UAV images’ Gene Salyer and Bishnu Ghimire; and ‘UAV image processing’ Oluwatola Adedeji.
The workshop concluded with ‘Predicting within-field cotton yield variability using DSSAT for decision support in precision agriculture’ Bishnu Ghimire; ‘Within-field cotton yield prediction using time series PlanetScope satellite imagery and deep learning’ Rupak Karn; ‘An economic analysis of climate resilience of cropping systems in the Texas High Plains’ Chenggang Wang Team; ‘EC data processing’ Bishnu Ghimire; and ‘Image data processing and machine learning in agriculture’ Victor Sheng Team.
Guo’s research is centered on research efforts in precision agriculture, environmental sciences, remote sensing in agriculture, especially UAV application in precision plant phenotyping. Prior to joining the Texas Tech faculty in 2016, he served as a global environmental modeling scientist with Monsanto in St. Louis. His doctorate in agronomy is from Texas Tech.