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Computational decision-making support tool for the optimized application of phytopharmaceuticals

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Nowadays, agriculture deals with intensive production, plagues, pests and inefficient use of natural and energy resources, also due to global temperature increase and climate change. This work seeks to answer the need to create new decision support tools for the application of phytopharmaceuticals. Mathematical objective functions capable of answering two problems were gathered. The first simulates the route and life cycle of a phytopharmaceutical. The second objective function provides the ideal quantities of phytopharmaceutical to be applied, based on climatic conditions, temperature, size of the tree canopy and dimensions of the agricultural fields.

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Computational decision-making tool Dispersion Phytopharmaceuticals Glyphosate Optimization Python

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