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Mathematical modeling of optimal biological pest control strategies for eficient and sustainable sugarcane production

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Ethanol is a good choice as a fuel and additive because it is produced from renewable resources; promises cleaner combustion leading to a cleaner environment; produces relatively low levels of greenhouse gas emissions over its lifecycle; can be seamlessly integrated into the existing transportation system; provides a new outlet for agricultural products; reduces the global dependence on depleting reserves of crude oil; and has a potential to have a large-scale impact. The increase in world demand for ethanol will bring an increase of the sugarcane planted in Brazil. One of challenges of the improvements in the farming and harvesting of cane is the biological pest control. Inspite of the biological control of Diatraea saccharalis by Cotesia flavipes is considered successful in Brazil, there are some areas where Cotesia flavipes has not the good control. The using of the parasitoid Trichogramma galloi is considered an interesting option in this case. In other hand, the dynamics of pest – parasitoid populations become complex, making the prediction of outbreaks difficult. Understanding the processes of these interactions can lead to a mathematical modeling playing a decisive role in controlling pest populations and contributing to the stability of natural systems. The main aim of this project is to apply methods from optimal control theory and from the theory of dynamic systems to the mathematical modeling of biological pest control strategies. The specific aims of this project are: modify existing and/or develop new mathematical models adequate to represent interactions between the sugarcane pests and its enemy populations; identify coefficient and parameters of proposed mathematical models and determine the equilibrium level of sugarcane ecosystems from mathematical models; formulate and solve the biological pest control in sugarcane as optimal control problem that determine algorithms of the optimal strategy, minimizing cost functional; colaborate the computational tools based on above mentioned algorithms; undergo numerical simulations for different possible scenarios of biological pest control in sugarcane based on the mathematical models. (AU)

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