Estimation of Bluegill (Lepomis macrochirus) Proximate Composition with Regression Models

Abstract

Dry weight, protein, fat, and ash proximates were determined for 100 individual laboratory reared bluegill (Lepomis macrochirus). Regression analysis using forms of length and weight provided models for prediction of proximates. Percent dry weight was a linear function of coefficient of condition (r = 0.866). Natural logarithm of ash was a linear function of natural logarithm of length (r = 0.997). Percent fat was a function of coefficient of condition and natural logarithm of length (r = 0.796). Percent protein was a function of coefficient of condition and natural logarithm of length times natural logarithm of weight (r = 0.768). The regression models, based only on length and live weight of fish, allowed accurate prediction of bluegill proximate composition for a laboratory fish population raised on chironomid larvae.