SEMEARE Computational Methodology

This book presents SEMEARE, a methodology for defining sowing periods for agricultural crops, with four stages, including planning, modeling, experimentation, and decision making. For validation, MarkSimGCM, a climate data simulator, was used to generate daily data, and DSSAT, Version 4.5, with the CERES-Maize Model, was used to simulate corn crop growth. This work is based on a generic methodology, which allows the use of different agricultural crop simulation models and climate data, interacting with different decision support systems in the agricultural field.

Autorentext
Albino holds a Bachelor's degree in Computer Engineering (2012) and a Master's degree in Applied Computing (2015) from the State University of Ponta Grossa - UEPG. He is a specialist in Media in Education from the State University of the Midwest - UNICENTRO (2015). He is a professor and technical consultant in the field of computing and education.