One of the largest river systems in South Africa, the Olifants River, has experienced 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 Lake Loskop and decreased the population at Kruger National Park. Most pansteatitisrelated
diagnoses within the region are conducted post-mortem by either gross pathology
or histology. The application of a non-lethal approach to assess the prevalence and pervasiveness
of pansteatitis in the Olifants River region would be of great importance for the
development of a management plan for this disease. In this study, several plasma-based
biomarkers accurately classified pansteatitis in Mozambique tilapia (Oreochromis mossambicus)
collected from Lake Loskop 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), in combination with total length, diagnose pansteatitis to a predictive accuracy
of 92 percent. In addition, several morphometric traits (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 within
different sites along the Olifants River.
S1 Fig. Surface plots for the top four predictive parameters (Ca2+, Na+, ALB, and TP) in
relation to standard deviation and total length (with the other three parameters were
clamped). TP (g/dL), ALB (g/dL), Na+ (mmol/L), and Ca2+ (mg/dL).