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Type: Artigo
Title: A Computational Environment To Support Research In Sugarcane Agriculture
Author: Driemeier
Carlos; Ling
Liu Yi; Sanches
Guilherme M.; Pontes
Angelica O.; Graziano Magalhaes
Paulo S.; Ferreira
Joao E.
Abstract: Sugarcane is an important crop for tropical and sub-tropical countries. Like other crops, sugarcane agricultural research and practice is becoming increasingly data intensive, with several modeling frameworks developed to simulate biophysical processes in farming systems, all dependent on databases for accurate predictions of crop production. We developed a computational environment to support experiments in sugarcane agriculture and this article describes data acquisition, formatting, storage, and analysis. The potential to support creation of new agricultural knowledge is demonstrated through joint analysis of three experiments in sugarcane precision agriculture. Analysis of these case studies emphasizes spatial and temporal variations in soil attributes, sugarcane quality, and sugarcane yield. The developed computational framework will aid data-driven advances in sugarcane agricultural research. (C) 2016 Elsevier B.V. All rights reserved.
Subject: Precision Agriculture
Editor: Elsevier Sci LTD
Rights: fechado
Identifier DOI: 10.1016/j.compag.2016.10.002
Date Issue: 2016
Appears in Collections:Unicamp - Artigos e Outros Documentos

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