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ID 61304
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Mochida, Keiichi Institute of Plant Science and Resources, Okayama University ORCID Kaken ID publons researchmap
Nishii, Ryuei School of Information and Data Sciences, Nagasaki University
Hirayama, Takashi Institute of Plant Science and Resources, Okayama University ORCID Kaken ID publons researchmap
Abstract
To ensure food security in the face of increasing global demand due to population growth and progressive urbanization, it will be crucial to integrate emerging technologies in multiple disciplines to accelerate overall throughput of gene discovery and crop breeding. Plant agronomic traits often appear during the plants’ later growth stages due to the cumulative effects of their lifetime interactions with the environment. Therefore, decoding plant–environment interactions by elucidating plants’ temporal physiological responses to environmental changes throughout their lifespans will facilitate the identification of genetic and environmental factors, timing and pathways that influence complex end-point agronomic traits, such as yield. Here, we discuss the expected role of the life-course approach to monitoring plant and crop health status in improving crop productivity by enhancing the understanding of plant–environment interactions. We review recent advances in analytical technologies for monitoring health status in plants based on multi-omics analyses and strategies for integrating heterogeneous datasets from multiple omics areas to identify informative factors associated with traits of interest. In addition, we showcase emerging phenomics techniques that enable the noninvasive and continuous monitoring of plant growth by various means, including three-dimensional phenotyping, plant root phenotyping, implantable/injectable sensors and affordable phenotyping devices. Finally, we present an integrated review of analytical technologies and applications for monitoring plant growth, developed across disciplines, such as plant science, data science and sensors and Internet-of-things technologies, to improve plant productivity.
Keywords
Genome to phenome
Life-course approach
Multi-omics
Plant phenomics
Sensor.
Published Date
2020-05-11
Publication Title
Plant and Cell Physiology
Volume
volume61
Issue
issue8
Publisher
Oxford University Press
Start Page
1408
End Page
1418
ISSN
0032-0781
NCID
AA0077511X
Content Type
Journal Article
language
English
OAI-PMH Set
岡山大学
Copyright Holders
© The Author(s) 2020.
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publisher
PubMed ID
DOI
Web of Science KeyUT
Related Url
isVersionOf https://doi.org/10.1093/pcp/pcaa064
License
http://creativecommons.org/licenses/by/4.0/
Funder Name
Japan Society for the Promotion of Science
助成番号
19K11861