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Advances in field-based high-throughput photosynthetic phenotyping
Gas exchange techniques revolutionized plant research and advanced understanding, including associated fluxes and efficiencies, of photosynthesis, photorespiration, and respiration of plants from cellular to ecosystem scales. These techniques remain the gold standard for inferring photosynthetic rat...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9126737/ https://www.ncbi.nlm.nih.gov/pubmed/35218184 http://dx.doi.org/10.1093/jxb/erac077 |
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author | Fu, Peng Montes, Christopher M Siebers, Matthew H Gomez-Casanovas, Nuria McGrath, Justin M Ainsworth, Elizabeth A Bernacchi, Carl J |
author_facet | Fu, Peng Montes, Christopher M Siebers, Matthew H Gomez-Casanovas, Nuria McGrath, Justin M Ainsworth, Elizabeth A Bernacchi, Carl J |
author_sort | Fu, Peng |
collection | PubMed |
description | Gas exchange techniques revolutionized plant research and advanced understanding, including associated fluxes and efficiencies, of photosynthesis, photorespiration, and respiration of plants from cellular to ecosystem scales. These techniques remain the gold standard for inferring photosynthetic rates and underlying physiology/biochemistry, although their utility for high-throughput phenotyping (HTP) of photosynthesis is limited both by the number of gas exchange systems available and the number of personnel available to operate the equipment. Remote sensing techniques have long been used to assess ecosystem productivity at coarse spatial and temporal resolutions, and advances in sensor technology coupled with advanced statistical techniques are expanding remote sensing tools to finer spatial scales and increasing the number and complexity of phenotypes that can be extracted. In this review, we outline the photosynthetic phenotypes of interest to the plant science community and describe the advances in high-throughput techniques to characterize photosynthesis at spatial scales useful to infer treatment or genotypic variation in field-based experiments or breeding trials. We will accomplish this objective by presenting six lessons learned thus far through the development and application of proximal/remote sensing-based measurements and the accompanying statistical analyses. We will conclude by outlining what we perceive as the current limitations, bottlenecks, and opportunities facing HTP of photosynthesis. |
format | Online Article Text |
id | pubmed-9126737 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-91267372022-05-24 Advances in field-based high-throughput photosynthetic phenotyping Fu, Peng Montes, Christopher M Siebers, Matthew H Gomez-Casanovas, Nuria McGrath, Justin M Ainsworth, Elizabeth A Bernacchi, Carl J J Exp Bot Review Papers Gas exchange techniques revolutionized plant research and advanced understanding, including associated fluxes and efficiencies, of photosynthesis, photorespiration, and respiration of plants from cellular to ecosystem scales. These techniques remain the gold standard for inferring photosynthetic rates and underlying physiology/biochemistry, although their utility for high-throughput phenotyping (HTP) of photosynthesis is limited both by the number of gas exchange systems available and the number of personnel available to operate the equipment. Remote sensing techniques have long been used to assess ecosystem productivity at coarse spatial and temporal resolutions, and advances in sensor technology coupled with advanced statistical techniques are expanding remote sensing tools to finer spatial scales and increasing the number and complexity of phenotypes that can be extracted. In this review, we outline the photosynthetic phenotypes of interest to the plant science community and describe the advances in high-throughput techniques to characterize photosynthesis at spatial scales useful to infer treatment or genotypic variation in field-based experiments or breeding trials. We will accomplish this objective by presenting six lessons learned thus far through the development and application of proximal/remote sensing-based measurements and the accompanying statistical analyses. We will conclude by outlining what we perceive as the current limitations, bottlenecks, and opportunities facing HTP of photosynthesis. Oxford University Press 2022-02-26 /pmc/articles/PMC9126737/ /pubmed/35218184 http://dx.doi.org/10.1093/jxb/erac077 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Experimental Biology. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Papers Fu, Peng Montes, Christopher M Siebers, Matthew H Gomez-Casanovas, Nuria McGrath, Justin M Ainsworth, Elizabeth A Bernacchi, Carl J Advances in field-based high-throughput photosynthetic phenotyping |
title | Advances in field-based high-throughput photosynthetic phenotyping |
title_full | Advances in field-based high-throughput photosynthetic phenotyping |
title_fullStr | Advances in field-based high-throughput photosynthetic phenotyping |
title_full_unstemmed | Advances in field-based high-throughput photosynthetic phenotyping |
title_short | Advances in field-based high-throughput photosynthetic phenotyping |
title_sort | advances in field-based high-throughput photosynthetic phenotyping |
topic | Review Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9126737/ https://www.ncbi.nlm.nih.gov/pubmed/35218184 http://dx.doi.org/10.1093/jxb/erac077 |
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