A computational environment to support research in sugarcane agriculture

Autor(es)

Driemeier, Carlos ; Ling, Liu Yi ; Sanches, Guilherme M. ; Pontes, Angelica O. ; Graziano Magalhaes, Paulo S. ; Ferreira, Joao E.

• Tipo de documento: Artigo Científico
• Fonte: COMPUTERS AND ELECTRONICS IN AGRICULTURE; v. 130, p. 13-19, NOV 15 2016.
• Citações Web of Science: 7

Resumo

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. (AU)

• Processo FAPESP: 15/01587-0 - Armazenagem, modelagem e análise de sistemas dinâmicos para aplicações em e-Science
• Beneficiário: João Eduardo Ferreira
• Linha de fomento: Auxílio à Pesquisa - Programa eScience e Data Science - Temático