SomaDetect technology brings transparency to dairy farms
The company aims to bring SomaDetect technology to the market in Spring 2018 once it completes the pilot program in New York, and anticipates it will be well-received by the dairy farming industry.
The company won $1m in funding two months ago through the 43North startup competition, which included a free incubator office space in Buffalo, New York.
SomaDetect competed against other startups with “user-friendly mobile apps” more directly related to the consumers’ daily routines, according to CEO Bethany Desphande.
“In the startup space it’s (SomaDetect) easy to overlook because it’s things that most people haven’t dealt with or haven’t learned about,” Desphande told DairyReporter.
“What was really clear is that people care about their food, and people care about the farmers making their food.”
How it works
SomaDetect uses light scattering sensory technology to analyze the dispersal of particles in a raw milk sample. The technology can analyze every major compound of the milk in real time helping dairy farmers identify red flags such as a high somatic cell count, a precursor to herd diseases such as mastitis or the nutritional disorder, ketosis.
Through an automatic alert system, “farmers can know in seconds whether they’re milking a cow with a high or low somatic cell count,” Desphande said.
By making rapid, real-time assessments of a cow’s health, dairy farmers can be proactive in treating a cow with very early signs of health issues, resulting in higher-quality milk and improved herd health.
Better data for dairy farmers
Prior to launching SomaDetect, Desphande was connected to a community of dairy farmers through the dairy innovation organization Milk2020 in her home province of New Brunswick, Canada.
“We’re a bunch of scientist- and developer-type folks that didn’t come from dairy,” she said. “Much of what we’re able to measure comes from suggestions from farmers.”
By visiting local dairies, she learned many farmers were limited to monthly milk reports or visual observation of the cows’ udders that could mainly only detect diseases like Mastitis after they had already developed.
“These diseases often go undetected because they don’t have access to data on a regular basis. They aren’t able to know what’s going on in their individual cows,” Desphande said.
As a result, farmers had to make decisions without precise information available and go off of averaged, whole-herd data.
“We’re going from watching this intermittedly to having access to long-term data,” she said.
