Fish health predictor shows high accuracy level
An application that can help fish farmers to predict disease outbreaks has been found to have 93% accuracy or more. The developer, Manolin, has announced its results after a year tracking health challenges for salmon farmers across Norway.
Manolin’s fish health forecasting tool was launched in February 2020. It uses machine learning to predict the early onset of PD (pancreas disease) and ISA (infectious salmon anaemia), based on a range of data inputs, and is the only commercially available disease forecasting tool for farmers in Norway.
Manolin’s Chief Technology Officer and co-founder John Costantino said: “This is a true breakthrough moment for our company and the industry as a whole. The last few months have been a culmination of many years of work—integrating numerous data silos, filling the gaps in industry data, expanding on academia’s disease research, and making it accessible for all farmers with user-friendly software.”
Manolin was founded in 2018 and is based in Bergen, Norway and Denver in the USA. Its machine learning models are powered by millions of data points including live disease outbreak reports, oceanographic forecasts, marine sensors, boat traffic, marine activity across all 600 active farms, and more than two decades of historical data.
Tore Holand, board member in several Norwegian farm companies, says, “It’s important for the industry to continue to raise its standards. Manolin has built a tool that doesn’t replace but works with farmers’ experience and expertise. With these types of insights, farmers can keep finding new ways to rethink their processes and improve. To be a part of the future, one needs to keep up with the technological advances.”
Manolin’s customers in aquaculture include Kvarøy Fiskeoppdrett, Lingalaks, Hofseth Aqua, and Firda Seafood.
Manolin raised 8m NOK (£680,000) last year from Boost VC, Hatch AS, and Innovation Norway, and recently added to its fish health and engineering teams. The company is expanding its forecasting tools to include feeding, growth, and mortality models.
