Dairy farmers would save a lot of money — and tears over spilled milk — if they had a way to detect mastitis early.
The bacterial infection of the udders leads to a loss of roughly $200 per cow, per year for US dairy farmers, according to the Louisiana State University Ag Center. Most of the financial hit comes from having to dump milk from mastitis-infected cows down the drain.
But Canada’s SomaDetect is hoping to change things. It’s getting ready to commercialize a solution that could change the way the industry monitors mastitis.
The New Brunswick startup today announced a $6 million Series A funding led by AgCapital Canada, a newly launched private equity fund based in Tillsonburg, Ontario.
Also participating in the round are Merck Animal Health Ventures, as well as existing investors Builders VC and Wilbur-Ellis’ Cavallo Ventures. The Series A follows an undisclosed investment from Cavallo Ventures in May 2019.
“SomaDetect really looks at the problem from a ‘farmer first’ mentality. When you look at a lot of technologies that are coming out, people don’t take that into account,” Ag Capital Canada general partner John Lasink told AFN.
“They need a technology that can integrate seamlessly into their milking systems. That’s exactly what SomaDetect has done. This requires essentially no work on the farmer’s behalf.”
Ag Capital Canada launched last March, just as the Covid-19 pandemic exploded in North America. But that didn’t stop the fund from getting off the ground – if anything, the move from physical meetings to video conferencing helped expedite their deal review process.
“We’re a relatively smaller fund with $26.5 million under management. Our largest investor is [ag lender] Farm Credit Canada,” Lasink explained. “We’ve primarily looked at getting LP investors in our fund that have some agricultural background. We have a lot of large farmers from western Canada and ag businessmen from eastern Canada, as well.”
Ag Capital Canada is targeting ag-related businesses across Canada through Series A, post-revenue deals. SomaDetect is the fund’s third investment since launching.
Bringing Merck Animal Health on board took a bit of legwork, SomaDetect founder and CEO Bethany Deshpande admitted to AFN. But the credibility that the Merck brand brings to the startup is more than worthwhile.
SomaDetect was in discussions with Merck for over a year before the major global health giant signed on the dotted line. The due diligence process was intensive and involved working with experts from many backgrounds including dairy, animal health, and technology, Deshpande said.
“Merck has a robust dairy data strategy. They have the Merck animal health platform that they’re really trying to roll out and getting data from a system like SomaDetect makes a ton of sense for what they are trying to do.”
Gearing up for commercialization
SomaDetect has developed an in-line sensor that can detect the presence of cells in milk that indicate the early onset of a mastitis infection.
The sensor emits light into the hose that transports the milk, causing particles to scatter in various directions. A portion of the light may be absorbed or reflected altering the intensity of the scattered beam. Particles of different sizes and in various concentrations will have unique scattering patterns that can be observed.
Based on the scatter pattern, the sensor can determine the somatic cell count in the milk, which is a direct indicator of whether the cow has mastitis or may soon develop clinical signs of the condition. Through the use of computer vision and deep neural networks, the sensor collects data to build algorithms that can predict the presence and concentrations of relevant compounds in raw milk.
The road to commercialization can be a long one for startups, and the first step into the market can feel like a leap of faith.
To prepare for this next step, SomaDetect has been working with Summitholm Holsteins, a dairy operation in Ontario. The farm has been an early partner in developing the technology. The startup is also planning upcoming beta tests at a variety of dairy farms in Canada to trial its next-generation sensor.
“Our goal is to cover more and more cows and get enough cows on the system. Through the beta trials, we will look at how our system performs against the status quo method of […] things like detecting pregnancy, measuring milk components, and working with our early adopters to really understand what problems they have on their farms,” Deshpande said.
After the beta tests, the plan is to start taking orders for the sensor. An ideal dairy farm will have around 2,000 cows, according to Deshpande.
“We feel we have every single thing lined up in our favor. The right partners at the table, the right farmers signed up as early adopters, and ultimately our technology solves a very real problem,” she said.
“We’ve been talking about making this transition to commercialization for about a year now and we’re incredibly excited to be where we are.”