Dynamics and control of poultry diseases in Ashanti Region

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2005-11-10
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The thesis deals with five important diseases in poultry namely. Coccidiosis, New castle. Helminthiasis, Gumboro and Bacterial diseases. The objective is to find out whether rainfall and temperature have any effect on these diseases so that plans can be made to control these diseases. A brief description of each the diseases are given. Time series models, in particular, autoregressive models were used to identify models for the various diseases. It was found out that the correlations of Newcastle diseases with temperature and total rainfall were not significant. However, with the univariate analysis, Newcastle disease turned out to be an autoregressive model of order one: AR(1). Coccidiosis also turned out to be an autoregressive model of order one: AR( 1). Bacterial disease had an autoregressive model of order two; AR(2). Gumboro disease also an autoregressive model of order two; AR(2). Coccidiosis had an autoregressive exogenous model of order two, ARX(2) with minimum temperature. The correlation of Gumboro and total rainfall was significant. Gumboro and total rainfall came out to have autoregressive exogenous model of order two, ARX(2). Gumboro also had an autoregressive exogenous model of order two, ARX(2) with minimum temperature. Helminthiasis and Bacterial diseases correlated best with average temperature. The autoregressive exogenous model for mortality in Helminthiasis versus maximum temperature was of order two, ARX(2). Bacterial diseases mortality versus maximum temperature was an autoregressive exogenous model of order two. ARX(2). Protein is a very important nutrient in the diet of humans. Poultry meat is a source of animal protein. Poultry diseases have been claiming the lives of birds. This situation obviously reduces the amount of animal protein poultry farmers could have produced for human consumption. This thesis has identified the models of these important poultry diseases in Ashanti region. In conclusion it is hoped that the models will alert farmers to know when to take precautions to avoid the occurrences of outbreaks.
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A thesis submitted to the Board of Postgraduate Studies, Kwame Nkrumah University of Science and Technology in partial fulfilment of the requirements for the degree of Master of Science in Mathematics, 2005
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