DIGITAL TWIN PROTOTYPES IN FLOW-THROUGH SYSTEMS FOR FINFISH

The virtual, digital counterpart of a physical object referred as digital twin derives from the Internet of Things (IoT) and involves real time acquisition and processing of large data sets. A fully implemented system ultimately enables real-time and remote management, as well as the reproduction of real or forecasted scenarios. Despite such potential, the adoption of digital twin features by smaller enterprises, including by aquaculture SMEs, has been comparatively slow (Uhlemann et al., 2017). Under the emerging framework of Precision Fish Farming, we set up digital twin prototypes for land-based farms of Rainbow trout (Oncorhynchus mykiss), European seabass (Dicentrarchus labrax) and Gilthead seabream (Sparus aurata), with the aim of supporting producers in optimizing feeding practices and oxygen supply with respect to 1) growth performances; 2) fish welfare, and 3) environmental loads. The digital twins were conceptualized targeting rearing cycles at Preore Farm (Trentino-Alto Adige, Italy), for trout, and Vigneto Farm (Tuscany, Italy), for seabass and seabream. The twins rely on integrated mathematical models which are fed with farm data sets and simulate several dynamic processes, allowing the estimation of key parameters such as feed digestibility, fish appetite, ammonia excretion rate, fish size distribution and dissolved oxygen consumption.