The GAIN project found that some of the most popular seafood’s in Europe appear to have a higher consumption than that reported in official statistics. The report, based on seafood demand data, focused on ten European countries and a large number of seafood products.
In addition to demand data, new supply statistics were considered to include other sources of seafood, including subsistence and illegal fishing. This showed that for cod, salmon, or tuna, consumption may be higher than previously estimated.
We are increasingly looking to trust in our food.
Sustainability has entered our plates.
We found that salmon, the most consumed farmed aquatic product in the EU, appears to have a consumption of 2.21 kg per capita, significantly higher than the 1.30 kg per capita estimates based on supply data. This means that each European consumer appears to eat almost one extra kg each year of salmon unaccounted for in official statistics. Although an extra 900 grams of salmon eaten annually by each person only corresponds to an extra meal every two months, if this gap is scaled up to the European population the numbers are of concern.
Similar numbers were determined for tuna, cod, trout, and other common seafood products. Total consumption of seafood in Europe could be as much as 4.3 kg per capita for farmed products and 8.9 kg per capita for wild-caught products.
Taken on aggregate, the mass balance gap for aquatic products, i.e. from fisheries and aquaculture combined, means that as much as one million metric tons per year of seafood could end up on European plates without being recorded in official statistics.
The most likely reason for this substantial discrepancy between supply and demand data are flaws in the datasets—collectively, this introduces substantial uncertainties for policy outcomes. The GAIN project makes a number of suggestions for improvements in this critical area—without good data, there are no good decisions.
To produce a good seafood product according to ecological, welfare and human health aspects we also have to consider the economic side of the coin. The use of sustainable alternative feed, close monitoring of the production conditions or the valorisation of side-stream products is beneficial for a more sustainable production, but will also come at a cost. How high is this cost? Which production benefit or who (the consumer?) will compensate for these costs? What about the whole sector impact?
These are very important questions for farmers and the seafood industry in general, which we seek to answer within GAIN. In order to do this on farm-scale we use a so-called “typical farm approach” implemented by the agri benchmark network headed by the Thünen Institute in Germany. This is a micro-economic tool which allows to portray the typical production of a farmed species according to real costs, techniques and other inputs: all of it in great detail. In the end we can estimate, which market returns per kg fish should be achieved in order to stay (as) profitable (as before)!
Sustainable production methods themselves already benefit the farmer, resulting in better quality fish that needs less feed to grow to the same size, or achieving higher water quality which might also allow for higher stocking densities. However, such benefits do not always outweigh the full costs that adaptations towards sustainable production might involve. As long as follow-up costs of environmental impacts are not part of the market price (which is admittedly not an easy task to determine!), price differences are at the expense of sustainable products and need a transparent justification.
Originating from Germany, where public awareness and willingness to pay for more sustainable seafood products is higher than in other countries, I am convinced that a good market transparency is the way forward and I am excited to be part of this aim in combination with more sustainable seafood production within GAIN.
*The fish bought by the electro trashers band “Scooter” in the 1990’s and being the name giver for their song “How much is the fish”, cost 3.80 Deutsche Mark and supposedly lived for at least 18 years, which seems to be a quite good deal!
Have you ever wondered what the day of a fish looks like? Or what leads to their decision making? Well I have always been curious, and I turned that curiosity into a career path.
I am a PhD student at Dalhousie University studying fish behavior in aquaculture using acoustics. Now what does that actually mean? There are many ways to study fish behavior from putting tags into a fish and tracking an individual’s movement, to using sound to track an entire populations movement. I use both in my research to help understand different aspects of where fish swim and why.
To make a complicated technology simple, I use acoustics (sounds in the water) to send a sound signal up into the cage and, depending what type of sound is returned, will determine the amount of fish and their location in the cage. This information can be extremely useful to fish farmers as it can help them determine when to start and stop feeding, as well as how their fish respond to other environmental conditions (such as storms or harmful algae blooms).
The aim of studying fish movement is to help farmers better understand their fish and assist them in mitigating any stress that could impact the fish’s well-being. By providing this information, we can help make happier, healthier fish to help feed our growing population.
I am Edouard, a French engineer working within GAIN for Università Ca’Foscari (UNIVE) in Venice, Italy. In my previous life, I was busy launching satellites. Now I am discovering the fascinating world of aquaculture and finding out that dynamic systems and data assimilation are becoming key tools in managing aquafarms. Within the GAIN project I’m trying to set up a model of a trout farm based on data provided from Troticoltura Leonardi located in Preore (Trentino, Italy).
Rainbow trout farming is the main fish farming activity in northern Italy, allowed by the presence of many watercourses coming from the Alpes Mountains. The last Italian census of aquaculture (PO FEAMP 2014-2020) counted 310 freshwater farming companies, most of them producing rainbow trout (Oncorhynchus mykiss). These farms are mainly located in Northern Italy, particularly in 3 different regions: Veneto (70 farms), Friuli Venezia Giulia (68) and Trentino Alto Adige (58).
If on the one hand trout farming is a traditional productive activity in Italy, on the other hand the new generation of farmers are looking forward to exploring the application of new technologies and collaboration leading to the optimization of management practices. This is the case of Dr. Matteo Leonardi who together with his company, Troticoltura Leonardi S.r.l., is involved in GAIN as an associated partner. But, how can a traditional productive activity such as trout farming be eco-intensified? This was the question risen by GAIN and now, at the beginning of the second year of the project, everything is ready to answer that question!
On July 16th 2019, with my colleagues Roberto Pastres and Andrea Forchino we met Filippo Faccenda (Fondazione Edmund Mach – FEM) and Mateo Leonardi at Preore in Troticoltura Leonardi aquafarm.
It was first an opportunity to monitor the sensors that were immersed at the beginning of July: water quality sensors provided and managed by FEM, and the daily biomass system. Second, it was the occasion to acquire the first data in order to accomplish an in-situ validation of the acquisition systems. Concerning water quality sensor, it was installed in one of the six raceways of the farm to continuously record data on ammonia, nitrates, redox potential, pH, dissolved oxygen, and temperature. All sensors are working well and the activities of the next weeks will be focused on the periodic transfer from the site to the IBM Castor platform, both from the technical and organizational point of view. These data will be crucial in trying to model the relationship between biomass growth, oxygen rate, temperature and feeding strategy.
But the meeting was also a good way to share again the objectives of the GAIN project related to Troticoltura Leonardi: Matteo Leonardi explained again his farming process and the concerns related to the lack of forecast in the frame of oxygen concentration (and its regulation) and its influence on feeding assimilation. Both inner products (oxygen and feeding) are for the farmer two important costs, as well as two central parameters for the welfare of the rainbow trout.
It was then the opportunity to confirm again the pertinence of the objectives of the GAIN project regarding farmers concerns and the challenges they face everyday in growing trout in raceways with water that continuously fluctuates in quality (due to its origin in natural water courses).
The GAIN work will now consist in modelling the biomass growth, the oxygen concentration variation due to animals behavior, and the evolution of temperature, seeking to build reliable forecasts that can support the farmer in his day-to-day decisions, reducing the costs and increasing welfare of the fishes. In one word, optimizing the process!
Blockchain is a form of distributed ledger technology (DLT), which is still in its early stage. A practical application of this technology is the well-known cryptocurrency Bitcoin, however, less known to the public are the applications beyond cryptocurrencies. This technology also shows potential to improve traceability and transparency in supply chains and could therefore change stakeholders and consumers perspectives towards commodities, practices and products.
This is due to the essence of blockchain technology, which consists of a chain of data packed “blocks” that records and verifies transactions that take place across a peer-to-peer network. The data in these blocks is secured with a cryptographic signature, called a hash, which should be identical in the next block in order to verify that the data is not manipulated. This mechanism provides security and guarantees that the data is immutable.
So far, retailers have been focusing in ways to improve trust in their own supply chains while simplifying problem solving. Consumers on the other hand are becoming increasingly aware of sustainability and social issues: a trend that is expected to be the standard in the future. However, supply chains are often complex networks of (international) stakeholders with their own practices and perspectives towards sustainability.
Currently a large proportion of these stakeholders use paperwork or traditional computer systems to keep track of commodities and products and most of these systems do not interact directly across the supply chain. This results in a lack of traceability and transparency throughout the supply chain all the way up to the consumer. However, the ability of a blockchain to securely verify and store up-to-date data across a commonly shared network could provide a more accurate insight into stakeholder practices along the supply chain.
The accessibility to the layers of data depends on the type of blockchain (public or private) and could differ between stakeholder depending on their authorization level. This could mean that e.g. consumers could access sustainability data about a product through an app, while other stakeholders could access information about certain ingredients, origin and waste hotspots.
This technology shows potential to improve the traceability and transparency of supply chains, by feeding the blockchain with manual input of data or by combining this technology with Internet of Things (IoT), such as GPS trackers, light, temperature, humidity, oxygen and movement sensors. This provides the stakeholders along the supply chain and the final consumer not only with information about the previous product conditions, but also about the specific stakeholders handling their commodities and products. This information alone or combined with other available information (e.g. license and certification) provides a transparent insight in the ‘social and environmental conscience’ along the supply chain, sharing business practices and attitudes of stakeholders towards sustainability.
Additionally, advanced sensors, modelling tools and apps could provide the consumer with a wider range of information about commodities or products, such as environmental footprints (water, land, carbon and energy). On the other side, producers could have access to information highlighting energy hotspots, waste streams and by-products, leading to better decision making. This could decrease waste production and the loss of valuable ingredients and resources, supporting circular economy principles.
Consumer demand for safe seafood is another present-day concern that will tend to have more relevance in future generations eating habits. Technologies that enable fish consumers to better ‘fact-check’ the origin, fish species, movements or condition of their food, with easy-to-use traceability and transparency tools can have a role to play.
Still, as with any new technology or innovation, there are issues that must be solved, and others that are yet to surface. The drivers and barriers of blockchain technology for consumers, small and large scale fish farmers and other stakeholders along the supply chain is relatively unknown. There are certainly many challenges that need to be addressed in converting real life into the blockchain.
The rapid increase in sensor capacities and computational power are opening new avenues for the aquaculture industry. Mirroring developments in agriculture, interconnected Internet of Things (IoT) sensors, big data analytics, and Artificial intelligence (AI) promise to revolutionise aquaculture supply and value chains. However, the application of the Precision Agriculture framework and tools is very challenging, requiring detailed knowledge on a three-dimensional system in the harsh ocean environment: it is not easy to observe what is happening in a 20 m deep cage containing about 150,000 individuals, while making sense of these observations in a chaotic environment pose very real challenges!
GAIN comes on the scene at this very exciting time: we are assessing the performances of new, market-ready sensors for non-invasive monitoring of fish distribution and behaviour, as well as key environmental variables (e.g. water temperature, dissolved oxygen). We are processing these complex data using machine learning and big data analytics, discovering patterns and anomalies which can facilitate the optimisation of feeding and other husbandry operations (e.g. net changes).
In late June, I left a very hot Venice and traveled north to Norway, to the midnight sun village of Inndyr, in Nordland County, to discuss the preliminary results of our comprehensive monitoring programme with Giulia and Ronald (GIFAS), who have installed and are looking after the sensors, and with Fearghal (IBM Research), expert in AI and IoT. Inndyr is located in the Gildeskål municipality which, in Viking times, was a renowned meeting point for the whole region. Aquaculture is the backbone of the local economy, to which our industry partner GIFAS (Gildeskål Forskningsstasjon AS) provided a relevant contribution in its thirty years of activities, which were celebrated this year. Far from being seen as an environmentally unfriendly activity, in this area aquaculture provides jobs, fosters educational activities and also represents a touristic attraction. Domus Pisces is a building owned by Nordland county and used by both the local highschool (Meløy VGS avd. Inndyr) and GIFAS. GIFAS uses it both for running cleaner fish tank-based trials and for promotion of aquaculture. For the latter purpose, GIFAS has an aquarium containing salmon, a hall exhibiting informative, aquaculture-themed posters and a small souvenir shop. In addition, the promotional centre of GIFAS runs tours to its research and commercial sites and these services are used by tourists, school and universities, amongst others.
Giulia and Ronald welcomed myself and Fearghal at GIFAS headquarters in Inndyr. We sat down in a cosy meeting room and started looking at data collected in the last five months. Our observing system was installed at GIFAS salmon production site Rossøya, about 10 minutes by boat from Inndyr.
We equipped one of the 90 m circumference cages that you can see in the picture above with ABM, a close-to-market system for detecting individual fish position and estimating its weight and swimming speed. The 20 m-deep cage was stocked with about 150,000 fish: we have been following their growth and behaviour day by day since February 2019.
ABM was selected because it could represent the silver bullet for dealing with the three-dimensionality issue: it provides data along the vertical water column and, with up to 50,000 detections per day, statistics concerning fish average weight are based on a representative sample size. Fish distribution is displayed every five minutes on a dashboard, allowing barge operators to inspect their feeding behaviour (feeding fish tend to congregate near the surface), as seen in Fig.1.
We also deployed sensors for measuring water temperature (below, left), dissolved oxygen (below, right) and water current every 10 minutes. The upper-portion of the cage is surrounded by an impermeable barrier to prevent lice entry. This may also reduce the water flow and circulation, thus affecting dissolved oxygen levels which may affect fish appetite and, ultimately, growth.
Water temperature profile.
Dissolved oxygen profile.
The data are flowing to a cloud platform designed by IBM: Fearghal and his colleagues are crunching these numbers in order to extract useful information to improve feeding efficiency, provide accurate predictions of salmon growth, and disseminate early-warning on anomalous patterns. We are eager to see the results: keep following the blog and you’ll be the first to know!
In the biological world, the rapid advances in big data genetic technologies have allowed us unprecedented insights into how organisms function in and adapt to their ever-changing ecosystems. We are regularly unraveling the DNA code for different species in our quest to answer questions related to disease prevention, food production, industrial bio-products and general organism health.
We can now look at the very essence of our biology and see what genes are being turned off and on in relation to specific environmental stressors and even predict the potential for certain disease risks in the future for humans. The social and legal implications of this level of insight are still being grappled with, inside and outside of courtrooms.
One of the dramatic offshoots of the genetic technology has been the rebirth of the science of microbiology. In the past, up to 99% of the bacteria were not identifiable with classic taxonomic methods such as shape definition, ability to be stained, or the ability to digest sugars—now bacteria are regularly being identified through their DNA fingerprints. The field of microbial ecology has exploded with recent studies.
And it turns out that the bacteria all around us may be the “dark matter” that is holding all of our biological universe together—they’re involved in almost every aspect of life-processes with the various species. Perhaps this is not surprising as bacteria represented the first forms of life on this planet 3.5 billion years ago as stromatolites.
They have co-evolved with all the subsequent lifeforms from the start and can be found in every environment on earth. In medicine, studies such as the American Gut Project are showing direct linkages of bacteria to many of the current maladies that afflict the human condition such as: allergies, autism, autoimmune diseases, cancer, diabetes, gastric ulcers, inflammatory bowel diseases and obesity to name a few.
So it shouldn’t be surprising that bacteria also play a major role in aquatic ecosystem processes. Studies in Canada, United States, Norway, China, Australia and others are all using this genetic technology to help society understand the dynamics of underwater ecosystems and the health of the organisms within.
This technological approach with bacteria is also being applied within GAIN to help understand some of the ecological dynamics in aquaculture farms. Because bacteria grow in hours, microbes may match well with the time resolution of big data physical measurements and may become part of a method that can be used to fine-tune aquaculture activities.