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The field phenotyping platform's next darling: Dicotyledons

The genetic information and functional properties of plants have been further identified with the completion of the whole-genome sequencing of numerous crop species and the rapid development of high-throughput phenotyping technologies, laying a suitable foundation for advanced precision agriculture...

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Autores principales: Li, Xiuni, Xu, Xiangyao, Chen, Menggen, Xu, Mei, Wang, Wenyan, Liu, Chunyan, Yu, Liang, Liu, Weiguo, Yang, Wenyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449727/
https://www.ncbi.nlm.nih.gov/pubmed/36092402
http://dx.doi.org/10.3389/fpls.2022.935748
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author Li, Xiuni
Xu, Xiangyao
Chen, Menggen
Xu, Mei
Wang, Wenyan
Liu, Chunyan
Yu, Liang
Liu, Weiguo
Yang, Wenyu
author_facet Li, Xiuni
Xu, Xiangyao
Chen, Menggen
Xu, Mei
Wang, Wenyan
Liu, Chunyan
Yu, Liang
Liu, Weiguo
Yang, Wenyu
author_sort Li, Xiuni
collection PubMed
description The genetic information and functional properties of plants have been further identified with the completion of the whole-genome sequencing of numerous crop species and the rapid development of high-throughput phenotyping technologies, laying a suitable foundation for advanced precision agriculture and enhanced genetic gains. Collecting phenotypic data from dicotyledonous crops in the field has been identified as a key factor in the collection of large-scale phenotypic data of crops. On the one hand, dicotyledonous plants account for 4/5 of all angiosperm species and play a critical role in agriculture. However, their morphology is complex, and an abundance of dicot phenotypic information is available, which is critical for the analysis of high-throughput phenotypic data in the field. As a result, the focus of this paper is on the major advancements in ground-based, air-based, and space-based field phenotyping platforms over the last few decades and the research progress in the high-throughput phenotyping of dicotyledonous field crop plants in terms of morphological indicators, physiological and biochemical indicators, biotic/abiotic stress indicators, and yield indicators. Finally, the future development of dicots in the field is explored from the perspectives of identifying new unified phenotypic criteria, developing a high-performance infrastructure platform, creating a phenotypic big data knowledge map, and merging the data with those of multiomic techniques.
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spelling pubmed-94497272022-09-08 The field phenotyping platform's next darling: Dicotyledons Li, Xiuni Xu, Xiangyao Chen, Menggen Xu, Mei Wang, Wenyan Liu, Chunyan Yu, Liang Liu, Weiguo Yang, Wenyu Front Plant Sci Plant Science The genetic information and functional properties of plants have been further identified with the completion of the whole-genome sequencing of numerous crop species and the rapid development of high-throughput phenotyping technologies, laying a suitable foundation for advanced precision agriculture and enhanced genetic gains. Collecting phenotypic data from dicotyledonous crops in the field has been identified as a key factor in the collection of large-scale phenotypic data of crops. On the one hand, dicotyledonous plants account for 4/5 of all angiosperm species and play a critical role in agriculture. However, their morphology is complex, and an abundance of dicot phenotypic information is available, which is critical for the analysis of high-throughput phenotypic data in the field. As a result, the focus of this paper is on the major advancements in ground-based, air-based, and space-based field phenotyping platforms over the last few decades and the research progress in the high-throughput phenotyping of dicotyledonous field crop plants in terms of morphological indicators, physiological and biochemical indicators, biotic/abiotic stress indicators, and yield indicators. Finally, the future development of dicots in the field is explored from the perspectives of identifying new unified phenotypic criteria, developing a high-performance infrastructure platform, creating a phenotypic big data knowledge map, and merging the data with those of multiomic techniques. Frontiers Media S.A. 2022-08-24 /pmc/articles/PMC9449727/ /pubmed/36092402 http://dx.doi.org/10.3389/fpls.2022.935748 Text en Copyright © 2022 Li, Xu, Chen, Xu, Wang, Liu, Yu, Liu and Yang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Li, Xiuni
Xu, Xiangyao
Chen, Menggen
Xu, Mei
Wang, Wenyan
Liu, Chunyan
Yu, Liang
Liu, Weiguo
Yang, Wenyu
The field phenotyping platform's next darling: Dicotyledons
title The field phenotyping platform's next darling: Dicotyledons
title_full The field phenotyping platform's next darling: Dicotyledons
title_fullStr The field phenotyping platform's next darling: Dicotyledons
title_full_unstemmed The field phenotyping platform's next darling: Dicotyledons
title_short The field phenotyping platform's next darling: Dicotyledons
title_sort field phenotyping platform's next darling: dicotyledons
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9449727/
https://www.ncbi.nlm.nih.gov/pubmed/36092402
http://dx.doi.org/10.3389/fpls.2022.935748
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