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dc.contributor.authorPaul, Daniel
dc.date.accessioned2025-03-04T08:43:41Z
dc.date.available2025-03-04T08:43:41Z
dc.date.issued2024-08
dc.identifier.urihttps://dspace.nm-aist.ac.tz/handle/20.500.12479/2931
dc.description.abstractThe Diamondback moth (DBM), scientifically called Plutella xylostella, a highly destructive and rapidly spreading agricultural pest originally from Europe. This particular pest presents a notable risk to the overall global food security, with estimates suggesting that periodic out breaks of DBM lead to annual crop losses of up to $US 4−5 billion worldwide. Given the potential for such substantial losses, it is crucial to employ various methods and techniques to understand the factors affecting the interaction between DBM and cabbages, which, in turn, impact cabbage biomass. In this research, two mathematical models were developed to assess the effects of pesticides, inter-cropping methods, and an Integrated Pest Management strategy on DBMinfestations in cabbage biomass. The first model focused on the impact of pesticides through nonlinear Ordinary Differential Equations (ODEs) to analyze the interaction between DBMandcabbage biomass. The model’s results indicated that the use of pesticides effectively eliminate DBM in a cabbage farm. The second nonlinear ODEs model assessed the impact of providing pest control education to farmers and deploying predators in cabbage farms. We found that provision of pest control education alone could reduce the negative impact of the DBM on final cabbage biomass by 10%. However, when both tactics were implemented to gether, the pest population was reduced by 40%–80%. In both proposed models, the MATLAB was employed for simulations to affirm the validity of the analytical results. In brief, the find ings of this research highlighted the importance of mathematical models as useful instruments for comprehending the management of DBM in cabbage crops.en_US
dc.language.isoenen_US
dc.publisherNM-AISTen_US
dc.titleModeling of diamondback moth infestations in cabbages with control strategiesen_US
dc.typeThesisen_US


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