TY - JOUR
T1 - Decoding plant–environment interactions that influence crop agronomic traits
AU - Mochida, Keiichi
AU - Nishii, Ryuei
AU - Hirayama, Takashi
N1 - Funding Information:
Grant-in-Aid for Scientific Research (C) [19K11861 to K.M. and R.N.] of the Japan Society for the Promotion of Science (JSPS) and JST CREST [ JPMJCR16O4 to K.M. and T.H.].
Publisher Copyright:
© The Author(s) 2020. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.
PY - 2020/8/1
Y1 - 2020/8/1
N2 - 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.
AB - 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.
KW - Genome to phenome
KW - Life-course approach
KW - Multi-omics
KW - Plant phenomics
KW - Sensor
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U2 - 10.1093/pcp/pcaa064
DO - 10.1093/pcp/pcaa064
M3 - Review article
C2 - 32392328
AN - SCOPUS:85089712583
SN - 0032-0781
VL - 61
SP - 1408
EP - 1418
JO - Plant and Cell Physiology
JF - Plant and Cell Physiology
IS - 8
ER -