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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A computational environment to support research in sugarcane agriculture

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Author(s):
Driemeier, Carlos ; Ling, Liu Yi ; Sanches, Guilherme M. ; Pontes, Angelica O. ; Graziano Magalhaes, Paulo S. ; Ferreira, Joao E.
Total Authors: 6
Document type: Journal article
Source: COMPUTERS AND ELECTRONICS IN AGRICULTURE; v. 130, p. 13-19, NOV 15 2016.
Web of Science Citations: 7
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. (AU)

FAPESP's process: 15/01587-0 - Storage, modeling and analysis of dynamical systems for e-Science applications
Grantee:João Eduardo Ferreira
Support Opportunities: Research Grants - eScience and Data Science Program - Thematic Grants