Jason Ward

Assistant Professor

  • 919-515-8985
  • D S Weaver Labs NA

Current Projects Seeking Graduate Students

Improving Harvest Efficiency with Machine Data

Peanut harvesting is a complex series of field activities requiring multiple passes across the field with multiple implements.  There is limited time to get the job done before harvest will suffer.  Optimizing harvest efficiency, machine sizing, and machine settings are essential to getting in and out of the field as quickly as possible.  Modern farm equipment can generate substantial data during day-to-day operations.  The tools now exist to tap into this data and leverage that information to ensure that harvest operations are running as smooth as possible.  The objectives of this project are to collect that machine data and use it to measure harvest field operation efficiency and to understand how to best manage the equipment to save time and money.  The same data can be used to understand how to mitigate harvest risk within the allowable working days by properly sizing machines to the farm.

Seeking MS student starting Fall 2018.


Quantifying Crop Lodging Damage with UAV Imagery

In North Carolina, harvest season is hurricane season.  The possibility for weather-related crop damage is a real danger for producers.  After a weather event crop health must be quickly assessed for the amount and severity of damage.  The producer can then choose to prioritize harvest differently based on those results or make an insurance claim for assistance with that field.  The objectives of this study are to compare specific measurement technologies to find the best suite of tools to quantify the severity of damage and area of impact.  The measures impacts will be compared to the physiological impacts on the crop.  Finally, a best method of federal or commercial reporting and securing that data to current standards will be developed.

Seeking MS or PhD student, depending on project scope.  Immediate availability.


Cotton Quality Mapping

Modern cotton harvesting equipment has the capability to weigh, estimate moisture content of, and discretely identify round modules when completed.  These data along with bale location should allow tracking of gin fiber quality data all the way back to a field area via the permanent bale indicator (PBI) assigned at the gin and the radio-frequency Harvest ID (HID) tag assigned at harvest.  The ultimate purpose of this project is a proof-of-concept linking fiber quality data to specific field locations within a cotton field.

Seeking MS or PhD student, depending on project scope.  Immediate availability.


B.S. 2003

Biosystems and Agricultural Engineering

University of Kentucky

M.S. 2004

Biosystems and Agricultural Engineering

University of Kentucky

Ph.D. 2012

Biological Engineering

Mississippi State University

Research Description

The Advanced Ag Lab works at the intersection of technology and farming. We leverage an understanding of agricultural methods and practices combined with technology, sensors, equipment, robotics, and data management to drive real-world decision making. We conduct applied research to identify existing or create new data in the modern precision agriculture environment and work closely with commodity experts to move from data collection to actionable insight. We develop and deliver innovative Extension programming that make the technology already on the farm more accessible and valuable. We defines precision agriculture as a methodology of data-driven decision making to improve output, manage impact, or reduce waste. This approach allows us to work across commodities and market sectors to create useful tools which allow best management at higher resolutions no matter the crop, animal, or equipment involved.