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 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 (Solea senegalensis) in terms of body weight gain. For this purpose, 30 adult fish were split into two homogeneous groups formed by three replicates (n = 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 (p < 0.0100) while CTRL animals did not report a statistical before-after weight increase. Individual body weight increment was lower (p < 0.0100) in standard-handled animals. In conclusion, our experimental approach provides evidence that our developed system for biomass calculation, which implies lower human-animal interaction, improves biomass gain in Senegalese sole individuals in a short period of time. View Full-Text

Keywords: Senegalese sole; production science; biomass; artificial neural network

▼ Show Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Supplementary Material

Supplementary File 1:
PDF-Document (PDF, 172 KiB)

Share and Cite

MDPI and ACS Style

Martínez-Vázquez, J.M.; Valcarce, D.G.; Riesco, M.F.; Marco, V.S.; Matsuoka, M.; Robles, V. Artificial Neural Network (ANN) as a Tool to Reduce Human-Animal Interaction Improves Senegalese Sole Production. Biomolecules 2019, 9, 778. https://doi.org/10.3390/biom9120778

AMA Style

Martínez-Vázquez JM, Valcarce DG, Riesco MF, Marco VS, Matsuoka M, Robles V. Artificial Neural Network (ANN) as a Tool to Reduce Human-Animal Interaction Improves Senegalese Sole Production. Biomolecules. 2019; 9(12):778. https://doi.org/10.3390/biom9120778

Chicago/Turabian Style

Martínez-Vázquez, Juan M., David G. Valcarce, Marta F. Riesco, Vicent S. Marco, Morito Matsuoka, and Vanesa Robles. 2019. "Artificial Neural Network (ANN) as a Tool to Reduce Human-Animal Interaction Improves Senegalese Sole Production" Biomolecules 9, no. 12: 778. https://doi.org/10.3390/biom9120778

Find Other Styles

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Abstract views Pdf views Html views

Article Menu

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

Abstract

Supplementary Material

Share and Cite

Article Metrics

Article Access Statistics

Article Access Map by Country/Region

Further Information

Guidelines

MDPI Initiatives

Follow MDPI