CropSight: a scalable and open-source information management system for distributed plant phenotyping and IoT-based crop management
Author(s) -
Daniel Reynolds,
Joshua Ball,
Alan Bauer,
Robert Davey,
Simon Griffiths,
Ji Zhou
Publication year - 2019
Publication title -
gigascience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.947
H-Index - 54
ISSN - 2047-217X
DOI - 10.1093/gigascience/giz009
Subject(s) - computer science , scalability , database , precision agriculture , agriculture , biology , ecology
High-quality plant phenotyping and climate data lay the foundation for phenotypic analysis and genotype-environment interaction, providing important evidence not only for plant scientists to understand the dynamics between crop performance, genotypes, and environmental factors but also for agronomists and farmers to closely monitor crops in fluctuating agricultural conditions. With the rise of Internet of Things technologies (IoT) in recent years, many IoT-based remote sensing devices have been applied to plant phenotyping and crop monitoring, which are generating terabytes of biological datasets every day. However, it is still technically challenging to calibrate, annotate, and aggregate the big data effectively, especially when they were produced in multiple locations and at different scales.
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