AI microscope gets $2.3M to automate livestock parasite testing

Appalachian State University researchers have developed an AI-driven robotic microscope designed to automate fecal egg counting for livestock parasite detection, securing $2.3 million in funding from NCInnovation, a state program that supports commercializing research discoveries. The technology aims to reduce the time and cost of parasite testing while improving accuracy, potentially benefiting North Carolina‘s billion-dollar agricultural industry by preventing livestock deaths and reducing unnecessary treatments.

How it works: The system combines three key technologies to automate a traditionally tedious manual process.

• A robotic microscope automatically moves around fecal samples and generates multiple images, creating large datasets for analysis.
• AI algorithms segment the data into regions of interest and classify whether those regions contain parasite eggs or other materials.
• The automation removes human bias and fatigue that typically occurs during manual counting sessions that can last hours.

Why this matters: Parasite detection is critical for livestock health and economic stability in North Carolina’s agricultural sector.

• Fecal egg counting identifies parasites living in farm animals’ intestines by counting eggs per gram of manure, with high levels potentially causing animal death if untreated.
• The technology could enable more frequent testing at lower costs, potentially preventing larger outbreaks and reducing unnecessary treatments that build parasite resistance.
• North Carolina’s cattle, poultry, and small ruminants like goats and sheep are all significantly impacted by fecal parasites.

Development timeline: The project is currently at Technology Readiness Level 3, with plans to advance through field testing over the next two years.

• TRL 3 means all key system components have been validated separately, according to project lead Zach Russell, an assistant professor of physics and astronomy at Appalachian State.
• The NCInnovation funding will support progression through TRL 4, where components are integrated into one system, and TRL 5, which involves field studies at Cooperative Extension offices or local veterinarians.
• Following field testing, the team plans to work with the N.C. Department of Agriculture for certification and quality assurance.

Target market: The researchers are focusing on expert users rather than direct farmer adoption.

• Initial targets include Cooperative Extension offices and NCDA veterinary labs, followed by veterinarians.
• “We’re trying to get these into the hands of the experts, supplementing their expertise,” Russell explained.

What they’re saying: Russell emphasized the technology’s potential to address regional agricultural challenges.

• “The motivation for this collaboration came from looking at what problems needed to be solved in our area … seeing what we could do with the technology that we were using in the university setting to have a more regional and local impact.”
• He noted that manual fecal egg counting is “like looking for a needle in a hay stack” and that “somebody might be looking through a microscope for tens of minutes, or even hours, counting hundreds or more of very small cells.”

Funding context: The NCInnovation grant supporting this research faces potential budget challenges as North Carolina legislators consider “clawing back” funding or changing the program’s endowment model.