NONLINEAR REGRESSION MODELLING OF RELATIONSHIP AMONG GROWTH PARAMETERS OF TILAPIA (Oreochromisniloticus)

Abstract

Nile tilapia (Oreochromisniloticus) is a globally significant and economically vital fish species, requiring effective management to sustain its benefits for local communities. This study utilized secondary data from a mixed factorial experiment to examine the effects of water temperature, location, and week on Nile tilapia growth. The growth parameters considered include total length, standard length, and weight. Water temperature levels considered include room temperature (20°C) as control, 28°C, 30°C, and 32°C for 12-week period and three(3) locations. Nonlinear regression techniques were used to model the relationships between total length and weight, and standard length and weight, under each temperature level. Analysis of variance (ANOVA) technique was then used to examine the effects of location, week, and temperature on fish weight. The constructed nonlinear models were then compared using the error sum of squares (SSE) criterion in F-test. The findings showed that model three is the best fit with SSE of 3137.143 and 3099.227, respectively, for total length x weightandstandard length x weightinteraction effects. ANOVA revealed significant effects of location, week, and temperature, along with their interactions (except location x weekfor total and standard lengths), on fish weight with p-values below 0.0001 (p < 0.0001). Estimated marginal means indicated a consistent increase in fish weight across all temperatures. The fitted regression model between total and standard lengths explained 96% of the total variability, indicatingan excellent fit. These findings provide valuable insights for fisheries managers and scientists to enhance tilapia stock managementand exploration.