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Multiple simulations for estimating the spatial variability of productivity of sugar cane using the model APSIM

Grant number: 13/21141-1
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): February 01, 2014
Effective date (End): January 31, 2015
Field of knowledge:Agronomical Sciences - Agricultural Engineering
Principal researcher:Paulo Sergio Graziano Magalhães
Grantee:Gustavo Frizarin Pereira Ferraz
Home Institution: Faculdade de Engenharia Agrícola (FEAGRI). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil


The production of sugar cane has become a protagonist of growth of the agricultural, environmental and economic scenarios of Brazil, driven mainly by the production of biofuel. The country holds the world leader in the production of sugar cane, which follows on a sharp curve and upward growth, implying the expansion to new areas and especially in advancing the implementation of new technologies seeking technification, optimization of processes and increased yield in areas already planted. In this scenario it can be observed the importance of developing tools that help to expand productivity and simultaneously preserve the environment. Precision agriculture (PA) is one of many solutions with the potential to contribute in this segment, as it allows better understand and more precisely control the spatial variability inherent in the soil, in order to achieve greater productivity, and economic returns, and respect for environment. Models which represent and simulate agronomic systems are one of the tools that are part of the PA. Crop models can be used to understand the performance, variability in time and space from which optimization and forecasting results can be achieved. The Agricultural Production System Simulator (APSIM) is a "framework" for modeling modular unit developed by Agricultural Research and Production Systems in Australia, to simulate biophysical process in farming systems, especially when there is interest in the results of economic and ecological management practices in the face of climate risk. In this sense, the theme of this project (which is included in a larger project) is to compare the spatial variability of production estimated by the simulator ASPIM with spatial variability measured in an area of cultivation of sugar cane, characterized and monitored by PA techniques.

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