Demand for fish products has been rising in Austria and Europe for years. Consumers value the high quality and regional production of Austrian fish products. The aim of the "Austrian Aquaculture Strategy - Austrian Strategy for the Promotion of National Fish Production" is to increase the degree of self-sufficiency while maintaining the small-scale structure with its regional, high-quality products and promoting ecologically sustainable and competitive aquaculture.
In order to support Austrian production and counteract the misuse of designations of origin, it is necessary to be able to determine the origin of fish products analytically. The ORIGINICS project - "Microbiome analysis to determine the origin of fish" is therefore intended to contribute to the establishment of an analytical tool to prove the origin of Austrian freshwater fish. The project was carried out jointly with the Federal Office for Water Management (BAW) and was scheduled to run for three years.
The aim of the ORIGINICS project was to test whether the microorganism community (microbiome) of fish is suitable for determining their geographical origin. Flow-through systems from five different locations in Lower Austria were selected for the project. Monthly sampling was carried out using rainbow trout(Oncorhynchus mykiss) as an example. High-throughput sequencing (NGS - Next Generation Sequencing) was used to determine the bacterial populations.
As part of the ORIGINICS project, a method for determining the bacterial population (microbiome) of fish was established and a separate database for storing sequencing results of bacterial populations, analysing data and calculating prediction models was developed (ProbASS - Sample Analysis and Statistical System). Statistical learning was also used to develop the prediction method.
In principle, it can be deduced from the results that the comparison of a specific fish sample with other fish samples can be predicted very well. The probability of a correct prediction is 90 %. Predicting the origin of a fish sample based solely on water data is more difficult with the selected statistical model and resulted in a correct prediction of a maximum of 70 %.
Last updated: 11.01.2024