Digitalised tools and tech solutions

In this step, we present you with an interview with a fish health data analyst from Manolin.

We discussed with her the increasing value of data in aquaculture, and how predictive forecasting software is changing the face of marine farming.

Natalie, thank you for joining us. Can you briefly introduce yourself to our students?

Thanks for having me. My name is Natalie Brennan and I’m a fish health specialist at Manolin, a data analytics company that has been working with fish farms to forecast, predict and manage disease in order to optimise fish health.

Many have heard of forecasting in terms of weather, but probably not in the context of fish farming. How do predictive analytics work in aquaculture?

The principles are actually the same: You look at factors, like the occurrence of a disease or a toxic algae bloom, in the past to predict the likelihood of an occurrence in the future.

In practice, we create forecasts for fish farms. For example, we recently developed a forecast for Pancreas Disease (PD), which is a disease found in salmon that can be transmitted between farms during production, and limits salmon growth. To predict the development of this disease, we collect data to identify which factors (like sea temperature, the number of boats to a farm, etc.) impacted the past development of PD.

We then run algorithms to assess the relationships between these factors. Based on these relationships, the computer can forecast when there is a low, medium, or high chance of developing PD in the near future. Essentially, this technology gives farmers the tools to use past events as a means to make the most educated decisions in the future on how to maximise and maintain the welfare of their fish.

So, how exactly could digitalisation help with fish welfare then?

To understand how it can impact fish health, it’s important to understand how fish health is broadly maintained in the first place. Essentially, the health of a fish is dependent on 3 main areas:

1. Presence of disease/pathogens
2. The environment (e.g. ocean currents, temperatures, and salinity)
3. The fish itself (e.g. genetics, feed, and overall health)

A fish can get sick or die when the conditions in these areas go too far outside their ideal level. To give you an example, if the water temperature is slightly too warm, and there is an increase in harmful bacteria in the water, then an action like moving the fish from one pen to another (usually somewhat harmless) could be enough to push the fish over a critical threshold of what the fish can withstand before falling ill or dying.

By understanding the relationships between these factors and how it impacts the fish, our forecast models help fish farmers see challenges or threats to fish health sooner. It gives them the opportunity to take preventative measures to keep the fish healthy, rather than dealing with the consequences once fish are already in a vulnerable position.

Fish farmers already do some of this analysis in their heads, and with years of experience they get very good. But there are limits, as the human mind can only manage so many factors and the relationships between them. This is where computers and data science techniques come in. Combined with a farmer’s knowledge, it provides a much more powerful analytic tool to give the fish the best possible living conditions.

If going digital means more recording of information, could consumers expect to see greater product transparency as a result?

In short, yes, definitely. With more fish and environmental data recording from farming operations and other sources, consumers will be able to know more about both where their product comes from and what has happened to it. Combined with technology like blockchain, this data can then be safeguarded against change or corruption, as well. It provides added transparency to consumers by raising the level of accountability farms have to their product. Increasing transparency opens the door for a more open and productive dialogue between consumers and industry.

You work primarily with the Norwegian salmon farming industry, has it been difficult gaining support for a software product in a traditionally hands-on industry?

It has been an interesting journey for sure, and because we are tying data science to traditional fish farming, there has certainly been a lot of education on both sides. Visiting farms in small remote Norwegian towns helps us to understand the issues and limitations they face on a case-by-case basis. We are personally involved and try to understand as much as we can about how each company has grown and overcome challenges, and this has helped bridge that critical gap between data scientists and farmers. It’s incredibly important to build those relationships so we can work alongside farmers to provide the digital data tools that will help with some of those challenges.

Can increased digitalisation make any positive steps towards sustainability in fish farming?

Absolutely, it does in a few ways:

• Increased transparency. So much of the discussion around sustainability occurs with the wrong information. More publicly available and accurate data gives consumers insight into the real facts behind their food. For example, many believe that farmed salmon are fuelled by chemical and antibiotic treatments, when in reality, since the ‘90s antibiotic use in Norwegian salmon has decreased by 99%, and chemical treatments are similarly limited to a fraction of what was once permitted. Going digital will help share these facts, which are already available to those within the industry, with those outside of it (consumers, policymakers, etc.).
• Becoming more efficient. More data means more knowledge, about both the good and bad aspects of your operation. You need to know where the biggest holes in the boat are before you can plug them.
• Preventing fish from getting sick. Forecasting and predicting health issues before they happen allows farmers to minimise damage through informed management.
• Implementation of sustainable practices. More data on the ocean and how activities impact it means more information available for its better management so that sustainable practices can be implemented faster.

Lastly, where do you personally hope to see the future of fish farming heading?

Being a relatively young industry (in the west at least), I hope to see it learn and build upon both the mistakes and successes of agriculture. The industry is growing rapidly with huge potential; especially if we continue to develop offshore technology.

As consumers, we are much more demanding and aware of the importance of sustainable food production than ever. My personal hope is that this focus and awareness on sustainable food production and environmental management becomes part of the core DNA that makes up aquaculture food production. I hope technology, transparency and trust continue to also be a critical part of where aquaculture is heading: A food production method that represents the values of many today.

And if I am honest, the time I have spent in the Norwegian industry, visiting farms and talking with all sorts of people in the industry, has shown me that it is heading in that direction. It’s an exciting space to work in and I look forward to more passionate people bringing new ideas to the industry in the time to come.

Authors: Oliver Fredriksson & Natalie Brennan

Let’s discuss:

• How do you feel about the use of technology to increase sustainability and transparency in fish farming and fishery management?

Let us know in the comments below!