EFFECTS OF DIFFERENT SOURCES OF DIETARY FIBRE ON LENGTH-WEIGHT RELATIONSHIP OF LEMON FIN BARB HYBRID (Barbonymus gonionotus ♀ × Hypsibarbus wetmorei ♂) FINGERLINGS - Jimoh, Wasiu Adeyemi (Journal of Agricultural Sciences (Belgrade), 2020)
A 56-day study was done to examine the effect of different sources of dietary fibre on the length-weight relationship of lemon fin barb hybrid (Barbonymus gonionotus ♀ Hypsibarbus wetmorei ♂) using five dietary treatments; control and test dietary treatments containing different leaf meals of high dietary fibre added at 10% inclusion level to a basal diet containing fish meal, soybean meal and rice bran. Weight of fish in each treatment was measured using a sensitive weighing balance while the total length was measured with 15cm long ruler following standard procedures. The logarithmic transformation of the values obtained from the weight and length measurements were done. This was depicted using scatter diagrams. SPSS version 17.0 was used in regressing length against weight to obtain the various components of the regression equations. The Levene test of homogeneity and interaction between covariate LogL and independent variable (Treatments) were not significant F(4,85)=0.838, p>0.05; F(4,84)=1.345,p>0.05 respectively indicating that our data have not violated the assumption of homogeneity of variance. The various regression models developed for fish across various dietary treatments were statistically significant (p<0.01). The t-values for components of the regression equation such as intercept/constant (a) and slopes were all statistically significant except the t-value for intercept/constant (a) of CTR. There was no significant effect of dietary treatments on LogW after controlling for logL, F(4,84)=1.296 p>0.05 revealing that the regression lines were not significantly different from each other. Partial Eta squared of 0.058 indicating small effect size of the dietary treatment was recorded and 0.86 were recorded for LogL meaning a large effect size that 86% of the variation in LogW was explained by LogL which was significant (F(1,84)=515.15, p<0.001). The regression models can be used interchangeably, any of the regression models can be used for estimation or prediction when using any of the dietary treatments, as the regression lines were not significantly different from each other