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Comparative growth of jipe tilapia, oreochromis jipe and nile tilapia, oreochromis niloticus using regression modeling

• Authors Details :  
• Job Ombiro Omweno,  
• Paul Sagwe Orina,  
• Albert Getabu,  
• Peter Maangi Ondieki

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Regression modeling analyses the relationship between two or more variables and can be used to predict the response variable from one or more independent variables. The present study uses linear regression analysis to evaluate the growth in the two fish species of genus Oreochromis, Nile tilapia and Jipe tilapia, under aquaculture conditions. The models were fitted using a collection of functions in the R-software library. The final models were selected using the goodness of fit criteria based on the coefficient of differentiation, the model p- values and Akaike information criteria. The significance of the linear relationship between predictor variables and the mean response was tested by comparing the computed standardized parameter estimates, whereas the confidence intervals were constructed to assess the uncertainty of predicting the response variable and determine outliers in the model. Generally, both species exhibited good condition during growth and all the measured water quality variables significantly afffected growth (p<0.05). However, only temperature and dissolved oxygen produced the most important linear relationship with fish weight. The study recommends that data from a controlled experiment should be used the determine the interactions between the two growth variables.

Article Subject Details

• Biological Sciences
• Mathematics
• Research methodology
• Statistics

Article Keywords Details

• Length-Weight Relationships
• Oreochromis jipe
• Oreochromis niloticus
• R-Software
• Regression models

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