The project will develop tools to monitor mortality and to be able to notify whether there is increased or high mortality in one facility or in several facilities in one area. In addition, it will be investigated how management of fish and implementation of new technologies will affect disease-caused mortality.
The project is based on 16 years of production data and collection of detailed data from the industry.
Limiting mortality must be top priority in an ethical, sustainable production of fish. Low mortality is one of several indicators of good animal welfare, and it is important to highlight the possibilities the industry has to limit the mortality in the production of farmed fish.
This project will therefore help the industry, the authorities and others to understand what causes mortality in the aquaculture industry. The goal is to develop a portal where mortality is displayed in real time in an interactive map or other graphic representation. Unexpectedly high mortality or unusual occurrences of mortality will be flagged in the portal as soon as it occurs, allowing a quick launch of investigations to uncover the causes.
Another aim of the project is to provide an in-depth description of mortality and how it varies with season and year, and between farms and geographical areas. Based on this, the authorities and producers will be able to define which levels of mortality are acceptable for each production unit. This can, among other things, provide a background for assessing their performance in relation to reducing mortality.
The project is based on 16 years of production data and data collection from the industry. Detailed daily production data from salmon producers will be used in a model for daily mortality, where all relevant factors that can affect mortality will be studied. For example, mechanical lice treatments and other handling are included, as well as information on the type of production, type of plant and type of fish. The model will then be used to quantify the effect of each factor on total mortality, and how this effect depends on when in an eventual disease course the event occurs.
Project manager
Partners
Norwegian Computing Center
