Evaluation of automated methods and development of indicators to identify erratic fish behavioral patterns under aquaculture practice
The arrival of “Agriculture 4.0” brings with it the use of sensors and big data. The present study aims to evaluate, whether these systems can be used to automatically detect erratic behavioral patterns in fish.
Being a valuable component for a healthy diet, the demand for fish is steadily increasing. As capture fisheries reached its capacity limits, fish farming experienced a steady boost since the last 20 years and discovered progressive intensification and industrialization in its production methods.
Intensive fish farming is a relatively young practice, with salmonids being among the most valuable species under cultivation. Here, the rainbow trout (Oncorhynchus mykiss) is the second most valuable of the farmed salmonids and represents the most important species in German aquaculture. Originally from North America, rainbow trout is characterized by its high adaptability, rapid growth and relatively easy keeping in different farming systems.
In recent years and similar to other animal farming practices, consumer awareness and consciousness towards finfish welfare under intensive and industrialized farming conditions increased. With the purpose of providing guidelines and recommendations to the aquaculture sector and helping to clarify consumers concerns, the present study aims to develop an automated method as well as indicators to assess fish welfare under potentially stressful conditions that fish may encounter under intensive farming conditions.
Under controlled laboratory conditions, small-scale recirculating aquaculture systems will be used to simulate different potentially stressful scenarios that fish may encounter under intensive conditions of production. Acoustic sensors and a video tracking system will be used to study fish behavior and activity levels. The obtained information will be used to identify changes in activity levels and behavior patterns when the fish are being subjected to stress. By identifying abnormal and erratic behavioral patterns, the study aims to determine indicators that can be used to assess fish welfare.
How does stress affect fish behavior in aquaculture systems? Can changes in behavioral patterns be monitored via automated systems? Which behavioral indicators can be used to assess fish welfare?
10.2016 - 9.2019
Funding program: Innovationsförderung
Project status: ongoing