AgroClimate Smart Crop Season : uma abordagem na simplificação de modelos de simulação para sistemas de auxílio à tomada de decisão

• Autor(a) principal: Perondi, Daniel
• Data de Publicação: 2017
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca de teses e dissertações da Universidade de Passo Fundo (BDTD UPF)
• Texto Completo: http://10.0.217.128:8080/jspui/handle/tede/31
• topic: Computação; Simulação (Computadores); Planejamento agrícola; Processo decisório; Computing; Simulation (Computers); Agricultural planning; Decision-making process.; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

Extreme weather events such as frost, high temperatures and dry spell periods affect the agricultural crops development. The knowledge about the probability of a specific weather event happen at a phenological stage has a big importance for the good season planning. Using crop simulation models associated with these situations help in decision-making and enables the definition of the best management practices. Thus, the objectives of this work are simplify the CROPGRO-Soybean, CERES-Maize and NWheat phenological modules, define extreme weather events probabilities and develop a webbased tool to simulate the planting dates for agricultural crops. The following results were obtained: new models to simulate phenological stages, using less parameters for the simulation and simulate the same growth stages date occurrence, compared with the original models; algorithms capable of analyze meteorological station data and define probabilities of low temperatures, high temperatures and dry spell periods for each day of the year; a tool that allows the management of fields and seasons, as well as the planning of a new season through simulations which show phenological stages windows with extreme weather events. Thus, the new phenology models developed together with the definition of extreme weather events probabilities and with the web tool for crop planning that were developed in this research become relevant to the areas of computer science, simulation and agriculture