Digitalization, data analytics and artificial intelligence

We are at the very beginning of understanding how we can apply digital tools to improve our farming operations. Today, everyday salmon farming is largely based on the experience of our very talented employees, in addition to the increasing body of scientific research and knowledge. Going forward, we believe digital tools and analytics will add to this decision making, for instance by predicting biological events ahead of time, allowing the farmer to apply stronger preventative measures. We call it Grieg Seafood Precision Farming.

Utilizing data analytics to improve

While still early days, we are working on a number of analytics projects, such as:

• We used regression analyses to better understand the cause of the disease Pancras Disease in Rogaland
• We have analyzed drivers for growth and mortality in Shetland. The results back up our improvement strategy in the region
• We are developing a model for daily prediction of harmful algal blooms in British Columbia
• We analyze causes of winter wounds to improve fish welfare
• We see improved feed conversion ratio partially due to our Operations Center in Rogaland
• Though digital tools, we compare the effect from feeding on growth, regardless of fish size, between all sites, allowing us to benchmark and improve

We have started building a HUB for analyses for the entire Group, and conducted data analyses in all regions. Analyses consist of regressions, machine learning and AI, as well as prediction models.

Operational Centers in the regions

We are creating hubs in each region where we will control all Precision Farming activities. These centers go beyond feeding operations.

We have tested a pilot installation for integrated operations for our marine facilities in Rogaland. The Operational Center has gradually taken over responsibility and execution of several production-related tasks. An integrated management and control system monitors and provides decision support to farming processes.

The goal is to improve fish health and welfare through closer monitoring with early warning algorithms, better coordination of on-site operations and optimizing the feed factor.