Headline News

Manolin releases salmon disease prediction model

Monday, March 22, 2021

Manolin released a machine learning model that predicts the early onset of pancreas disease and ISA with greater than 93% accuracy. It is the only commercially available disease forecasting tool for farmers in Norway.

The company has been working for the past few years integrating numerous disparate data sources, filling the gaps in industry data, and thoroughly studying academia’s available disease research. To forecast fish disease, a deep learning method of artificial intelligence known as a neural network is used. 

When new data is collected, the model responds immediately. On the farm, this means that the moment a mortality event, dip in feeding, lice treatment, or storm occurs, the platform (and farmer) benefits from it.

“Our model has had a lot to learn from. Manolin’s years of mining, manipulating, and formatting data points across Norway and combining them with anonymized private farm data has given us a powerful data set, and it’s only growing as we continue to build and connect with more farmers,” the company said.

The company ingests millions of data points throughout each day:

  • Live disease outbreak reports.
  • Treatment activity across all 600 active salmon farms in Norway.
  • Data from government institutions like Fiskeridirektoratet, Veterinærinstituttet, Mattilsynet, IMR, and Meterologisk Institutt.
  • Oceanographic forecasts, marine sensors, and boat traffic data.
  • More than 50 daily farm production and environmental factors.
  • More than 20 years of historical industry data.

“This is constantly running behind the scenes of our dashboard, filling the gaps in industry data and automatically alerting farmers when something isn’t right. Computers predict disease, but farmers prevent it,” the company said.

 

Follow Us

We are social. Connect with us on:

Sign Up For Our Publications

Select a newsletter/magazine and submit your e-mail to subscribe.

Aquafeed Publications
HATCHERY Feed & Management Publications