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The Effect of Fish Size and Condition on the Content of Twelve Essential and Non Essential Elements in Aristichthys nobilis from Pakistan
M. Naeem*, A. Salam, S. S. Tahir1 and N. Rauf 1
Institute of Pure and Applied Biology, Bahauddin Zakariya University, Multan 60800; 1Central Laboratory for Environmental Analysis, Pakistan Environmental Protection Agency, Islamabad, Pakistan
*Corresponding author:


The correlation coefficients between fish size (body weight and total length) and metal contents i.e. sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), manganese (Mn), iron (Fe), copper (Cu), zinc (Zn), chromium (Cr), cobalt (Co), cadmium (Cd) and lead (Pb) in whole fish (Aristichthys nobilis) were determined.  A total of 71 fish samples were collected from hatcheries and fish reservoirs located in Islamabad and Fatehjung.  Highly significant (P<0.001) relationship between metal concentrations and fish size was found. Most of the studied metals (Na, K, Ca, Mg, Cu, Zn, Cr, Cd, and Pb) were found to increase in direct proportion to an increase in body weight indicating isometrically increase, while Mn, Fe and Co showed significant proportional increase in metal concentration with increasing body weight indicating positive allometry. Whereas all metals showed isometric growth, however, Na, Mn, Fe, Cu, and Co showed positive allometry in relation to total length. By applying multiple regression analysis calculation of correlation coefficient (r) between different variables and wet body weight, condition factor the value of (r) found to be highly significant (P<0.001) in examined fish except Na, Ca, Cu, Zn, Cd and Pb while for total length the same results found except Ca, Cd, Zn and Pb. Variance inflation factor values of regression coefficients in multiple regression analysis for each variable were lesser than 10. It can be concluded that metal levels in fish were lower than the recommended values in fish and fishery products set by FAO.

Key words: Aristichthys nobilis; Metal Composition; Fish size; Condition factor; Predictive equation


ISSN 0253-8318 (Print)
ISSN 2074-7764 (Online)