Southern land-grant scientists are utilizing artificial intelligence to help farmers save on labor costs and time through research on precision spraying, disease detection, food quality control, animal health and wheat production.

Oklahoma State University

ExtensionBot, a chatbot app developed by Oklahoma State University Agriculture and the Extension Foundation, launched in September to provide the public with Extension information in community health, family and consumer sciences, 4-H youth development, and agricultural and natural resources. Its narrative interface combined with AI technology improves accessibility and use of Extension content that currently exists online.

Another OSU app in the beginning stages of development is BudgetBot, an AI-powered advisor that simplifies decision-making for underserved, small- and medium-sized agricultural producers by providing easy access to research-based information. Using advanced AI software, BudgetBot connects to structured and unstructured data sources, delivering clear, actionable insights in text and visual formats. Designed to overcome complex, hard-to-use farm budgeting solutions, the app offers real-time data on commodity prices, production inputs and performance metrics.

Finally, researchers in the OSU Department of Plant and Soil Sciences are in the testing phase of a variety selection tool for wheat producers. Although such tools already exist, OSU researchers are throwing AI into the mix to increase the tool’s efficiency. Wheat producers can ask questions about specific production systems and manipulate wheat harvest data to illustrate production systems.

The University of Florida Institute of Food and Agricultural Sciences

University of Florida scientists are helping growers save time and money with Agroview, technology that uses images from drones, satellites and the ground to assess plant stress and count and categorize plants based on their height and canopy area. It also estimates plant-nutrient content and can reduce data collection, analysis time and cost by up to 90% compared to manual data collection.

Two UF/IFAS scientists designed a precision weed sprayer that uses images of weeds to train computers to identify them. Growers can use the pictures to know when, where and how to control pests. This precision agriculture data has helped farmers reduce pesticide use by up to 90%.

Virginia Tech

Researchers are also interested in identifying and eliminating weeds without harming crops at Virginia Tech. U.S. growers spend approximately $6 to $8 billion annually on herbicides in addition to rising labor costs for specialty crops.

A researcher at the Eastern Shore Agricultural Research and Extension Center is leading a project to automate the process of drone spray technology and machine learning to conduct real-time weed detection. The project aims to standardize the process and bring drone technology to farmers’ fields to save time and money.

Testing unmanned aerial systems is the first step, but the goal is to automate the process and conduct real-time weed detection and spray applications.

University of Georgia College of Agricultural and Environmental Sciences

The College of Agricultural and Environmental Sciences Precision Food Systems Lab uses precision sensing technologies and AI to create digital technologies, including “digital twins” and augmented reality for food processing and quality control.

A digital twin is a virtual model of a physical object, like a food item, that researchers can use to simulate its life cycle and assess production processes. The technology collects data on a piece of food, its processing operations, distribution and shelf life. Next, the virtual model develops the digital counterpart of those processes or products to optimize unit operations and quality monitoring in the supply chain.

Fort Valley State University 

Small and limited-resource farmers in the southern United States and South Africa will soon have immediate access to their veterinarian and agronomist with just a click of the finger.

Researchers at Fort Valley State University in Georgia are using a $750,000 grant from the U.S. Department of Agriculture’s National Institute of Food and Agriculture to develop a precision animal health management app. The research team found many limited-resource farmers have access to mobile phones but may not have funds or access to a veterinarian.

The app aims to use geographic information systems technology and AI computer modeling to develop an automated, cell phone-based decision support system for farmers in the U.S. and South Africa to improve animal health in their small ruminants (sheep and goats).

For example, a farmer can take pictures of an ailing goat’s eyes with a cell phone and upload the images to the free app. The farmer will receive immediate information on the goat’s condition and how to improve its health.