Today, about 80% of the global finfish and crustacean aquaculture production are raised in ponds. However, the relation between fish nutrition and pond functioning is still poorly understood. The first aim of this PhD project is to investigate causal relations in ponds between nutrient management, water quality and fish performance.
The obtained information will be used to develop a predictive model to help farmers to avoid overfeeding, to minimize pollution and to improve the nutrient utilization efficiency. By having feed automation systems linked to a smartphone app, the stability and consistency of aquaculture processes will be improved, which will lead to a more predictable and stable production process.
The outcomes of this project will contribute to the development of a smartphone app that monitors fish activity and water quality. This smartphone app will send early warning messages to farmers allowing them to adjust pond operation and management before adverse culture conditions develop.