The use of information technology in aquaculture management

The recent advances in information technology (IT) have had profound impacts on all walks of life and aquaculture is no exception. The growing importance of aquaculture as an alternative source of protein has further emphasized the need to adapt and develop advanced IT for the better management of aquaculture facilities as well as the regional planning for aquaculture development. It is the objective of this paper to review the use and potential prospects of IT in aquaculture management. The information technologies considered are instrumentation and process control, data management, computerized models, decision support systems, artificial intelligence and expert systems, image processing and pattern recognition, geographical information systems, and information centres and networks. The review includes a brief introduction of each of the aforementioned technologies, followed by a survey of their current application as well as their potential use in aquaculture management. Abstract The recent advances in information technology (IT) have had profound impacts on all walks of life and aquaculture is no exception. The growing importance of aquaculture as an alternative source of protein has further emphasized the need to adapt and develop advanced IT for the better management of aquaculture facilities as well as the regional planning for aquaculture development. It is the objective of this paper to review the use and potential prospects of IT in aquaculture management. The information technologies considered are instrumentation and process control, data management, computerized models, decision support systems, artificial intelligence and expert systems, image processing and pattern recognition, geographical information systems, and information centres and networks. The review includes a brief introduction of each of the aforementioned technologies, followed by a survey of their current application as well as their potential use in aquaculture management

Shrimp closed-loop supply chain network design

none3Recent developments in food industries have attracted both academic and industrial practitioners. Shrimp as a well-known, rich, and sought-after seafood, is generally obtained from either marine environments or aquaculture. Central prominence of Shrimp Supply Chain (SSC) is brought about by numerous factors such as high demand, market price, and diverse fisheries or aquaculture locations. In this respect, this paper considers SSC as a set of distribution centers, wholesalers, shrimp processing factories, markets, shrimp waste powder factory, and shrimp waste powder market. Subsequently, a mathematical model is proposed for the SSC, whose aim is to minimize the total cost through the supply chain. The SSC model is NP-hard and is not able to solve large-size problems. Therefore, three well-known metaheuristics accompanied by two hybrid ones are exerted. Moreover, a real-world application with 15 test problems are established to validate the model. Finally, the results confirm that the SSC model and the solution methods are effective and useful to achieve cost savings.openMosallanezhad B.; Hajiaghaei-Keshteli M.; Triki C.Mosallanezhad, B.; Hajiaghaei-Keshteli, M.; Triki, C

Agent-based modeling for environmental management. Case study: virus dynamics affecting Norwegian fish farming in fjords

Background: Norwegian fish-farming industry is an important industry, rapidly growing, and facing significant challenges such as the spread of pathogens1, trade-off between locations, fish production and health. There is a need for research, i.e. the development of theories (models), methods, techniques and tools for analysis, prediction and management, i.e. strategy development, policy design and decision making, to facilitate a sustainable industry. Loss due to the disease outbreaks in the aquaculture systems pose a large risk to a sustainable fish industry system, and pose a risk to the coastal and fjord ecosystem systems as a whole. Norwegian marine aquaculture systems are located in open areas (i.e. fjords) where they overlap and interact with other systems (e.g. transport, wild life, tourist, etc.). For instance, shedding viruses from aquaculture sites affect the wild fish in the whole fjord system. Fish disease spread and pathogen transmission in such complex systems, is process that it is difficult to predict, analyze, and control. There are several time-variant factors such as fish density, environmental conditions and other biological factors that affect the spread process. In this thesis, we developed methods to examine these factors on fish disease spread in fish populations and on pathogen spread in the time-space domain. Then we develop methods to control and manage the aquaculture system by finding optimal system settings in order to have a minimum infection risk and a high production capacity. Aim: The overall objective of the thesis is to develop agent-based models, methods and tools to facilitate the management of aquaculture production in Norwegian fjords by predicting the pathogen dynamics, distribution, and transmission in marine aquaculture systems. Specifically, the objectives are to assess agent-based modeling as an approach to understanding fish disease spread processes, to develop agent-based models that help us predict, analyze and understand disease dynamics in the context of various scenarios, and to develop a framework to optimize the location and the load of the aquaculture systems so as to minimize the infection risk in a growing fish industry. Methods: We use agent-based method to build models to simulate disease dynamics in fish populations and to simulate pathogen transmission between several aquaculture sites in a Norwegian fjord. Also, we use particle swarm optimization algorithm to identify agent-based models’ parameters so as to optimize the dynamics of the system model. In this context, we present a framework for using a particle swarm optimization algorithm to identify the parameter values of the agent-based model of aquaculture system that are expected to yield the optimal fish densities and farm locations that avoid the risk of spreading disease. The use of particle swarm optimization algorithm helps in identifying optimal agent-based models’ input parameters depending on the feedback from the agentbased models’ outputs. Results: As the thesis is built on three main studies, the results of the thesis work can be divided into three components. In the first study, we developed many agent-based models to simulate fish disease spread in stand-alone fish populations. We test the models in different scenarios by varying the agents (i.e. fish and pathogens) parameters, environment parameters (i.e. seawater temperature and currents), and interactions (interaction between agents-agents, and agents-environment) parameters. We use sensitivity analysis method to test different key input parameters such as fish density, fish swimming behavior, seawater temperature, and sea currents to show their effects on the disease spread process. Exploring the sensitivity of fish disease dynamics to these key parameters helps in combatting fish disease spread. In the second study, we build infection risk maps in a space-time domain, by developing agent-based models to identify the pathogen transmission patterns. The agent-based method helps us advance our understanding of pathogen transmission and builds risk maps to help us reduce the spread of infectious fish diseases. By using this method, we may study the spatial and dynamic aspects of the spread of infections and address the stochastic nature of the infection process. In the third study, we developed a framework for the optimization of the aquaculture systems. The framework uses particle swarm optimization algorithm to optimize agent-based models’ parameters so as to optimize the objective function. The framework was tested by developing a model to find optimal fish densities and farm locations in marine aquaculture system in a Norwegian fjord. Results show so that the rapid convergence of the presented particle swarm optimization algorithm to the optimal solution, - the algorithm requires a maximum of 18 iterations to find the best solution which can increase the fish density to three times while keeping the risk of infection at an accepted level. Conclusion: There are many contributions of this research work. First, we assessed the agent-based modeling as a method to simulate and analyze fish disease spread dynamics as a foundation for managing aquaculture systems. Results from this study demonstrate how effective the use of agentbased method is in the simulation of infectious diseases. By using this method, we are able to study spatial aspects of the spread of fish diseases and address the stochastic nature of infections process. Agent-based models are flexible, and they can include many external factors that affect fish disease dynamics such as interactions with wild fish and ship traffic. Agent-based models successfully help us to overcome the problem associated with lack of data in fish disease transmission and contribute to our understanding of different cause-effects relationships in the dynamics of fish diseases. Secondly, we developed methods to build infection risk maps in a space-time domain conditioned upon the identification of the pathogen transmission patterns in such a space-time domain, so as to help prevent and, if needed, combat infectious fish diseases by informing the management of the fish industry in Norway. Finally, we developed a method by which we may optimize the fish densities and farm locations of aquaculture systems so as to ensure a sustainable fish industry with a minimum risk of infection and a high production capacity. This PhD study offers new research-based approaches, models and tools for analysis, predictions and management that can be used to facilitate a sustainable development of the marine aquaculture industry with a maximal economic outcome and a minimal environmental impact

Shrimp closed-loop supply chain network design

Recent developments in food industries have attracted both academic and industrial practitioners. Shrimp as a well-known, rich, and sought-after seafood, is generally obtained from either marine environments or aquaculture. Central prominence of Shrimp Supply Chain (SSC) is brought about by numerous factors such as high demand, market price, and diverse fisheries or aquaculture locations. In this respect, this paper considers SSC as a set of distribution centers, wholesalers, shrimp processing factories, markets, shrimp waste powder factory, and shrimp waste powder market. Subsequently, a mathematical model is proposed for the SSC, whose aim is to minimize the total cost through the supply chain. The SSC model is NP-hard and is not able to solve large-size problems. Therefore, three well-known metaheuristics accompanied by two hybrid ones are exerted. Moreover, a real-world application with 15 test problems are established to validate the model. Finally, the results confirm that the SSC model and the solution methods are effective and useful to achieve cost savings

Nutrient policies and the performance of aquaculture in developed countries - a literature review

Eutrophication is a serious problem in many parts of the world, and aquaculture production can contribute to the problem as well as be part of its solution. Nutrient polices in developed countries are often command-and-control policies that may have contributed to the slow growth of the sector. We perform a literature review to investigate how current nutrient polices affect the sector and if economic incentive policies have greater potential to support sector growth. Although the literature is limited in many aspects, the results indicate that this may be the case. Given that the ability to measure, monitor and control has improved over time, possibilities for using economic incentive policies have increased. For example, subsidies that are results-based, i.e., based on the amount of emissions that are reduced, could be used. It is also possible for aquaculture production to benefit from being included in emissions trading systems, where these are available

Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems

The electrical power system is undergoing a revolution enabled by advances in telecommunications, computer hardware and software, measurement, metering systems, IoT, and power electronics. Furthermore, the increasing integration of intermittent renewable energy sources, energy storage devices, and electric vehicles and the drive for energy efficiency have pushed power systems to modernise and adopt new technologies. The resulting smart grid is characterised, in part, by a bi-directional flow of energy and information. The evolution of the power grid, as well as its interconnection with energy storage systems and renewable energy sources, has created new opportunities for optimising not only their techno-economic aspects at the planning stages but also their control and operation. However, new challenges emerge in the optimization of these systems due to their complexity and nonlinear dynamic behaviour as well as the uncertainties involved.This volume is a selection of 20 papers carefully made by the editors from the MDPI topic “Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems”, which was closed in April 2022. The selected papers address the above challenges and exemplify the significant benefits that optimisation and nonlinear control techniques can bring to modern power and energy systems

Fish behavior and its use in the capture and culture of fishes

Fishery management, Behaviour, Food fish, Fish culture, Conferences

Evaluating and optimizing stock enhancement of a natural flatfish stock

The overall objective of this thesis is to evaluate and optimize a stock enhancement program of natural population of flatfish in which artificially reared fish are released in coastal areas using turbot (Psetta maxima) as model. Biological and ecological criteria are developed to evaluate the likelihood for success, i.e. increasing the stock size, based on ecological knowledge. Special reference is given to processes involved in the regulation of the natural population, such as density-dependent and density-independent mortality and growth. Field data on the temporal and spatial variation in the abundance of age-0 turbot is analyzed and implications for stock enhancement are discussed. It is concluded that there is a solid theoretical background indicating that stock enhancement through releases of artificially reared juvenile individuals is a viable option for the turbot stock. Support for the hypothesis that stock enhancement is a viable option is provided by the results of a series of filed experiments conducted under a stock enhancement program in the southern part of Denmark. The focus of these experiments was on the growth and mortality of released fish in comparison to wild fish, and the importance of the characteristics of the release habitat. The growth of the released fish was similar to, or higher than, that of their wild counterparts, and the mortality, even though highly variable, was on a comparable level. No indication of replacement of the wild individuals with released ones was found. The importance of the release habitat was investigated by releasing turbot into three areas that differed in wind exposure. The area with the highest degree of wind-exposure was, as predicted, the area where the highest abundance of wild juvenile turbot was found. The highest growth of released individuals was not found in this area but was found in the one characterized by the lowest degree of wind-exposure, an atypical nursery ground for turbot. The effect of the release habitat on the growth could be related to the quality of the prey items observed in the stomachs of wild turbot sampled in the three areas. Besides the choice of a suitable release habitat, the release size of the fish and the conditioning to the release habitat was shown to be critical for survival of released fish. In order to study the mortality of the released fish, a methodology applying diffusion theory was developed and tested. Using this method the post-release mortality was found to be as high as 14%•day–1 for the 9 day period examined in 7.5 cm sized fish. Mortality decreased with increasing release size and became negligible at a release size of 17cm. After conditioning reared fish to the release environment allowing fish to develop their natural burrowing behavior prior to release, the post-release mortality was found to be insignificant. Since it was possible to enhance the turbot stock through releases of artificially breed individuals, stock enhancement may be considered as a supplement to traditional stock management. It can be applied in species with a turbot like life cycle where density-dependent regulation occurs early in life, and where the cost of production young fish is less than the gain in fisheries yield. As long as the artificially reared juveniles are added to the population after the stage where density-dependent regulation occurs, it can be expected that the released fish will contribute to the natural stock. Further, in order to optimize the outcome when stock enhancing, two aspects should be given special attention, 1) finding a proper release habitat where not only the food quantity but also its quality provides optimal growth conditions and 2) the risk of a server loss of fish during the post release period which can be avoided either by manipulating the size of the individuals released or by applying a conditioning period prior to the release