Estimating oxygen consumption of rainbow trout (Oncorhynchus mykiss) in a raceway: a Precision Fish Farming approach

The Precision Fish Farming (PFF) approach was applied to the estimation of fish oxygen consumption of rainbow trout in a raceway farm. A dynamic model, simulating the evolution of Dissolved Oxygen concentration, was identified: the daily oscillation of the fish oxygen consumption rate was simulated by means of a sinusoidal function. The model was applied to the data set collected during a fourweek field study, which was carried out in July 2019. Water temperature and Dissolved Oxygen concentration were measured with an hourly frequency in farm influent and effluent. Fish biomass was monitored on a daily basis by combining the data provided by a state-of-the art system for noninvasive estimation of fish weight distribution with mortality counting. The monitoring period was partitioned into two time-windows, as fish was not fed during the first two weeks. These windows were further partitioned into a calibration and validation set. Three model parameters, i.e. the average daily respiration rate, the amplitude of its daily oscillation, and its phase, were estimated by fitting the model output to the time series of DO concentration in the effluent. The results of the calibration show that: 1) the daily average oxygen consumption rate is consistent with the literature; 2) the amplitude of the daily oscillation when fish is regularly fed is more than twice that estimated for fasting fish. The results of the validation suggest that the model could be used to implement a cost-effective automatic control of oxygen supply, based on the short-term prediction of oxygen demand