Artificial Neural Network (ANN) as a Tool to Reduce Human-Animal Interaction Improves Senegalese Sole Production

Manipulation is usually required for biomass calculation and food estimation for optimal fish growth in production facilities. However, the advances in computer-based systems have opened a new range of applied possibilities. In this study we used image analysis and a neural network algorithm that al...

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Published in:Biomolecules (Basel, Switzerland) Switzerland), 2019-11, Vol.9 (12), p.778
Main Authors: Martínez-Vázquez, Juan M, Valcarce, David G, Riesco, Marta F, Sanz Marco, Vicent, Matsuoka, Morito, Robles, Vanesa
Format: Article
Language:English
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Summary:Manipulation is usually required for biomass calculation and food estimation for optimal fish growth in production facilities. However, the advances in computer-based systems have opened a new range of applied possibilities. In this study we used image analysis and a neural network algorithm that allowed us to successfully provide highly accurate biomass data. This developed system allowed us to compare the effects of reduced levels of human-animal interaction on the culture of adult Senegalese sole ( ) in terms of body weight gain. For this purpose, 30 adult fish were split into two homogeneous groups formed by three replicates ( =5) each: a control group (CTRL), which was standard manipulated and an experimental group (EXP), which was maintained under a lower human-animal interaction culture using our system for biomass calculation. Visible implant elastomer was, for the first time, applied as tagging technology for tracking soles during the experiment (four months). The experimental group achieved a statistically significant weight gain (
ISSN:2218-273X
2218-273X
DOI:10.3390/biom9120778