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Department of Soil and Crop Sciences
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Guo, Wenxuan
Wenxuan Guo
Assistant Professor
Office:
Lubbock
Email:
wenxuan.guo@ag.tamu.edu
Phone:
(806) 834-2266
Resume/CV
Graduate Education
M.S. Plant, Soil and Environmental Science, West Texas A&M University 2002
Ph.D. Crop Science, Texas Tech University, 2005

Specialty: Crop ecophysiology and precision agriculture

Research and Teaching:
Appointment is 75% Texas Tech University and 25% Texas A&M AgriLife Research
The goals of my research are to optimize crop production, enhance water conservation and water use efficiency, and improve profitability for sustainable agriculture using data science and precision agriculture technologies. My research efforts have focused on:

  1. Precision agriculture
  2. High-throughput plant phenotyping using unmanned aerial systems (UAS)
  3. Application of data science in agriculture

The focus of the precision agriculture program is mainly on field-scale precision water management, also called variable rate irrigation (VRI), which incorporates the spatial variability of soil physical properties, topography, and crop yield to enhance water use efficiency and water conservation. Preliminary results showed that cotton yield response to irrigation rates varied with landscape positions and soil physical properties, suggesting that site-specific irrigation can potentially optimize crop production while conserving water in fields with significant variability. The high-throughput plant phenotyping program is mainly focused on the application of UAS in assessing crop water stress and soil moisture conditions. Preliminary results showed high-resolution UAS images could estimate soil surface moisture with greater accuracy than satellite images. The results also showed that UAS has a great potential to identify cotton water stress with high-resolution images in the thermal and optical spectral bands. The data science project is mainly focused on irrigation scheduling using weather data and UAS images. The research programs help to improve water use efficiency, optimize production, and enhance agricultural sustainability.

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