Abstract
A comparative study of blood chemistry and histology was conducted on two groups of mullets (Mugilidae) living under different conditions with different feed sources. The aquaculture influenced mullet group (AIM), was collected near fish farms and the control group of mullet (CM) was caught in the waters without any aquaculture activities. Histological and biochemical procedures were employed to study liver histomorphology, plasma aspartate and alanine aminotransferase (AST, ALT), triglyceride (TRIG), cholesterol (CHOL), glucose (GLU) and total protein (TP) of both AIM and CM. Moderate histological changes (lipid infiltration) were observed in the liver of AIM. Significant changes in plasma variables were observed in AIM. Blood chemistry variables measured proved to be good indicators of artificial feed effects. Classical statistical approaches were applied to the blood chemistry and histopathology data. For the first time machine learning techniques were used to generate comprehensible classification models and to explore blood chemistry variable importance, strength, their mutual interactions or dependencies, and to investigate reliability of particular variables within the groups.
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