Great Northern Salmon breaks barriers in production modelling
Production planning sets the stage for success in land-based salmon farming. Design and operation practices are only as good as the depth of upfront planning. And such planning must be based on input data from actual fish performance and welfare for salmon in conditions relevant to any given farm.
Risk mitigation in land-based farming begins with a deep understanding of salmon needs and the range of conditions a farm will operate under, while also accounting for biological variability and deviations from performance assumptions.
Static production spreadsheets will never capture the real-world situation farmers face. A likely outcome of that is a lack of operator ability to meet targets, and potentially very costly fixes after production realities play out.
Over the past 2 years, GNS has developed dynamic production models that enable testing of range of scenarios to optimize production and remove bottlenecks. Millions of data points break down operations to daily fish movements and tasks. Management can then stress-test the model and establish tools to deliver on their targets across a range of scenarios. The outcome is more effective risk mitigation and improved probability of
reaching targets.
GNS can run “live” simulations of its entire system to determine how different conditions or events impact key production metrics. That has informed our design decisions and operating procedures. This is valuable IP that sets us apart from others.
The production plan can handle biological deviations that are an inevitable part of commercial fish farming without compromising on the biomass output. Such deviations can affect fish logistics throughout the farm, create bottlenecks, or lead to underperformance in output. Active scenario testing can inform strategies to manage deviations through farm designs and practices that maintain targeted output. If such scenarios have not been analyzed for a farm, the farm is not well-prepared to handle growth variations.
Optimized tank layouts and fish logistics are another example. By having a continuous turnover of fish through the production units and a well-balanced distribution of the biomass, GNS has achieved 90+ percent tank utilization efficiency while allowing lower average fish densities per module. That translates into lower CAPEX, better water quality, better fish-welfare, and a higher probability of reaching targets. To do this, a farm must have a plan for daily production logistics before starting design.
Smolt stocking can have a big impact on operations. A consistent supply fully aligned with the grow-out production plan is critical in an operation with weekly harvesting. Delays in supply, deviations in size or quantity, or deviations in quality can have an impact on production outcomes. Thus, a grow-out operation should control its smolt supply and seamlessly integrate it into the production planning. The GNS production plan allows for extra time and capacity during the smolt stage to ensure that the fish entering the grow-out facility are the right size to achieve the targets.
In the end, deep hands-on farming experience combined with sharp analytical capabilities is necessary to develop resilient production plans. This is the starting point for delivering on biomass and quality targets, on schedule, in the land-based segment.