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Predictive Blood Chemistry Parameters for Pansteatitis-Affected Mozambique Tilapia (Oreochromis mossambicus)

Published

Author(s)

John Bowden, Theresa M. Cantu, Robert W. Chapman, Stephen E. Somerville, Matthew P. Guillette, Hannes Botha, Andre Hoffman, Wilmien Luus-Powell, Willem J. Smit, Jeffrey Lebepe, Jan Myburgh, Danny Govender, Jonathan Tucker, Louis J. Guillette Jr., Ashley S. Boggs-Russell

Abstract

One of the largest river systems in South Africa, the Olifants River, has witnessed significant changes in water quality due to anthropogenic activities. Since 2005, there have been various “outbreaks” of the inflammatory disease pansteatitis in several vertebrate species. Large-scale pansteatitis-related mortality events have decimated the crocodile population at Loskop Dam and decreased the population at Kruger National Park by a conservative estimate of 20 percent. Most pansteatitis-related surveys within the region occur post-mortem by either gross pathology or histology. The discovery and application of a non-lethal approach to assess the prevalence and pervasiveness of pansteatitis in the Olifants region would be of great importance for the management of this disease. In this study, several plasma-based biomarkers accurately classified pansteatitis in Mozambique tilapia (Oreochromis mossambicus) collected from Loskop Dam using a commercially available benchtop blood chemistry analyzer combined with data interpretation via artificial neural network analysis. According to the model, four blood chemistry parameters (calcium, sodium, total protein and albumin) diagnoses disease to a predictive accuracy of 92 percent. In addition, several physical attributes (total length, age, weight) were also associated with pansteatitis. On-going research will focus on further evaluating the use of blood chemistry to classify pansteatitis across different species, trophic levels and sites.
Citation
PLoS One
Volume
11
Issue
4

Keywords

Pansteatitis, Mozambique tilapia, VetScan analyzer, blood chemistry parameters, artificial neural network, environmental health assessment

Citation

Bowden, J. , Cantu, T. , Chapman, R. , Somerville, S. , Guillette, M. , Botha, H. , Hoffman, A. , Luus-Powell, W. , Smit, W. , Lebepe, J. , Myburgh, J. , Govender, D. , Tucker, J. , Guillette, L. and Boggs-Russell, A. (2016), Predictive Blood Chemistry Parameters for Pansteatitis-Affected Mozambique Tilapia (Oreochromis mossambicus), PLoS One, [online], https://doi.org/10.1371/journal.pone.0153874 (Accessed May 29, 2024)

Issues

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Created April 26, 2016, Updated February 4, 2020