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Advisor(s)
Abstract(s)
This manuscript describes and evaluates the FEEDNETICS model, a detailed mechanistic
nutrient-based model that has been developed to be used as a data interpretation and decisionsupport tool by fish farmers, aquafeed producers, aquaculture consultants and researchers. The
modelling framework comprises two main components: (i) fish model, that simulates at the individual
level the fish growth, composition, and nutrient utilization, following basic physical principles and
prior information on the organization and control of biochemical/metabolic processes; and (ii) farm
model, that upscales all information to the population level. The model was calibrated and validated
for five commercially relevant farmed fish species, i.e., gilthead seabream (Sparus aurata), European
seabass (Dicentrarchus labrax), Atlantic salmon (Salmo salar), rainbow trout (Oncorhynchus mykiss),
and Nile tilapia (Oreochromis niloticus), using data sets covering a wide range of rearing and feeding
conditions. The results of the validation of the model for fish growth are consistent between species,
presenting a mean absolute percentage error (MAPE) between 11.7 and 13.8%. Several uses cases
are presented, illustrating how this tool can be used to complement experimental trial design and
interpretation, and to evaluate nutritional and environmental effects at the farm level. FEEDNETICS
provides a means of transforming data into useful information, thus contributing to more efficient
fish farming
Description
Keywords
Aquaculture Fish nutrition Precision fish farming Mechanistic nutrient-based model Numerical model Decision-support tool
Citation
Journal of Marine Science and Engineering 11 (3): 472 (2023)
Publisher
MDPI