Abstract
Isotopic experiments are conducted to evaluate turnover rates in fish tissue, especially as a function of nutrition. In 2007, Cerling et al. proposed an approach they named the reaction progress variable, which among other functions, allows to correct for growth during the period of data collection and to treat the isotopic incorporation system as a linear function, irrespective of the growth rate model. The objective of present study was to apply “the reaction progress variable” approach to describe stable isotope turnover in muscle tissue of pacu fed a lysine-deficient and a lysine-supplemented diet in order to determine the incorporation rates of nitrogen-free compounds, considering the correction for increases in mass during turnover. Since in muscle tissue carbon compounds are proteins, nucleic acids, lipids and carbohydrates and nitrogen compounds include only proteins and nucleic acids, the incorporation rates of nitrogen-free compounds were calculated by the difference between the incorporation rates of carbon and nitrogen compounds. The δ13C and δ15N values were adjusted for the increase in mass of fish to determine incorporation rate constants through linear fit. High turnover rates were observed when the increase in mass was considered. There was no effect of the diets on the incorporation rates of carbon compounds into muscle tissue of juvenile pacu. Fish fed the lysine-deficient diet exhibited a higher metabolic δ15N turnover rate, probably because of the greater degradation of nitrogen compounds; consequently, the incorporation rate of nitrogen-free compounds was 1.23% day−1. A higher incorporation rate of nitrogen compounds was observed in fish fed the lysine-supplemented diet and the incorporation rate of nitrogen-free compounds was therefore lower in this group (0.05% day−1). The incorporation rate of nitrogen-free compounds (e.g., lipids and glycogen) into muscle tissue was higher in juvenile pacu fed the lysine-deficient diet compared to animals receiving the lysine-supplemented diet. We therefore propose to adopt the reaction progress variable approach as a more useful tool for describing isotopic incorporation datasets.
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