Five ag tech startups split $500,000 for North Dakota farm trials

Five companies will share $500,000 from the NSF AgTech Engine to trial their technologies on North Dakota farms, after a selection panel of livestock and row-crop producers plus independent agronomists screened almost 90 proposals.

Each applicant could request up to $100,000 across five focus areas: quality, nutrition and value-added markets; regenerative systems and crop protection; breeding, genetics and predictive biology; intelligent operations and logistics; and water and resource resilience. The winners range from early research to commercialization-stage ventures.

"Farmers know what will work on their farm," said Hollie Mackey, CEO of the NSF AgTech Engine. "We're putting these tools in their hands early — in their fields, feedyards and elevators — and taking their guidance to improve technology development."

The engine links rural producers, researchers, entrepreneurs and industry partners to scale technologies aimed at food security and regional economic development.

What are the five funded projects?

• Elevator of Things (Champaign, Ill.) — A field-tested system pairing cameras and computer vision with the grain probes elevators already own. Live footage overlaid with real-time data makes grain interactions traceable, reducing disputes and protecting margins. North Dakota testing and production engineering will ready it for market, with the aim of cutting manual grain-sampling labor at harvest.
• Global Neighbor (Xenia, Ohio) — A combine-mounted Weed Seed Destroyer using dual-wavelength, nonlaser directed energy to stop weed seeds from germinating. It offers a nonchemical tool against herbicide-resistant weeds with no extra field pass.
• Scanit Technologies (Fremont, Calif.) — The AI-powered SporeCam autonomously collects airborne particles and classifies fungal pathogens against a multi-year database. Monitors go into eight North Dakota Agricultural Weather Network stations to detect six crop pathogens in real time, with free grower alerts tied to weather data.
• Seismi — A retrofit sensor that clips onto existing cattle ear tags, tracking heart rate, respiration and behavior to catch bovine respiratory disease days before symptoms show — and before treatment gets expensive. Trials run at a family farm and a large commercial feedyard.
• North Dakota State University — Researchers at NDSU's Peltier Institute for Advancement in Agriculture Technology will build a tractor-mounted cultivator using cameras and AI to spot weeds and engage individual tillers only where needed. Trials in the Red River Valley will measure weed removal, crop protection and soil disturbance.

What does this mean for input costs?

Several projects target spray and labor budgets directly. Scanit's disease alerts let growers time fungicide applications before an outbreak — or skip a spray pass entirely when pathogens are absent. Global Neighbor's harvest-time weed-seed destruction cuts herbicide reliance without adding a field pass. Seismi's early disease detection in cattle aims to cut treatment costs by catching illness before it spreads.

Elevator of Things targets the elevator side of the margin equation: transparent, traceable grain interactions that prevent disputes between producers and grain buyers.

The trials will generate performance data and producer feedback for the companies' next development stages.