Current Research

Partners in Success

The intersection between farmer experimentation and university research

Sun rising over a corn field with very young corn plants, and white gentlemen who is mostly unseen bending to touch an individual corn plant with affection

There is a critical need to co-create mechanisms that promote producer-led experimentation, while also creating a data pipeline for university research. Co-creation is significant because it improves the relevance of the science, while also improving the autonomy of producers for independent experimentation. Our rationale is that a co-creation process will enhance producer efforts to obtain higher quality data, improve their capacity to translate research findings, and facilitate gathering of usable on-farm data. We are partnering with other stakeholders to target a producer-initiated research question to evaluate our co-creation approach, innovating in participatory research, and simultaneously offering Extension opportunities in related topics to broader audiences. This work is supported by USDA NIFA CARE award #2022-68008-36356.

Data Science for Decision Making

Applying deep learning models to automate identification of erroneous data points

AI-generated photorealistic image of small corn plants with a sunflare in the background. The image as a digital overlay meant to imply computer data associated with the corn plants.

Producers rely on automated yield monitoring devices to understand crop yield and yield variability in their farm fields. Yield data, is however, error prone and requires human experts to properly filter out invalid data points. This project investigates the role artificial intelligence, commonly referred to as "AI," can play in supporting agricultural decision making and farm management practices that arise from yield data. The hypothesis is that AI-based models can provide open, equitable, efficient, and objective yield data cleaning tools that automate and improve the quality of yield data processing. This work is supported by USDA NIFA DSFAS award #2024-67021-4252.

Closing the Conservation Yield Gap

Collaboration with USDA ARS

Early career female scientist in field clothes, standing in a field of young cotton. Her arm is outstretched and her palm open to release a small drone. There is nice warm lighting on the field and a wide open sky in the background. A good day for flying and collecting data.

This project builds foundational knowledge to support profitable adoption of conservation practices that build soil health and resiliency in corn and cotton production systems. At the same time, this project innovates through use of emerging technologies for data capture and analyses. This work is supported by USDA ARS under agreement #58-6064-3-007.

Making Christmas a Little Greener

Building economic and ecologic sustainability for Christmas tree farms

Mixed height Christmas trees in a field with grass covering the ground. Taller non-Christmas trees are in the background. Everything is green. Must be spring!

Growing Christmas trees takes time—up to five years before they’re ready to sell. During that time, the trees can be damaged by bugs, diseases, and bad weather. In the southeastern US, Christmas tree farmers face extra challenges because there isn’t enough local research to guide them. They often have to rely on advice meant for other parts of the country, which doesn’t always work well in the Southeast’s unique climate and soil. This can lead to wasted money, extra work, and harm to the environment. This integrated research and Extension effort equips growers with digital tools that improve their long-term viability, with a focus on water stress and disease management. This project creates a positive impact by improving both the productivity and sustainability of Christmas tree farms, helping to keep the cost of real Christmas trees affordable and competitive with artificial trees. This work is supported by USDA NIFA SMF award #2024-09740.