Evidence map›Paper›PMID 35218184›Full record

ReviewJournal of experimental botany2022

Advances in field-based high-throughput photosynthetic phenotyping.

Peng Fu, Christopher M Montes, Matthew H Siebers, Nuria Gomez-Casanovas, Justin M McGrath, Elizabeth A Ainsworth, Carl J Bernacchi

Abstract readReview
In one paragraph

Review in Journal of experimental botany, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Photosynthetic Responses to Rising COGlobal change biology · 2026
    Review
  2. Article
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  5. Hyperspectral phenotyping and GWAS identify novel QTLs for soybean photosynthetic rate.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Article
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  15. Article
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  17. Review
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  19. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Peng FuCarl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, IL, USA.ORCID 0000-0003-1568-1518
Christopher M MontesDepartment of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.ORCID 0000-0002-7295-3092
Matthew H SiebersDepartment of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.ORCID 0000-0002-5200-0913
Nuria Gomez-CasanovasDepartment of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.ORCID 0000-0003-4784-3585
Justin M McGrathDepartment of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.ORCID 0000-0002-7025-3906
Elizabeth A AinsworthCarl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, IL, USA.
Carl J BernacchiCarl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, IL, USA.ORCID 0000-0002-2397-425X

Funding

Bill and Melinda Gates FoundationForeign, Commonwealth & Development Office OPP1172157Foundation for Food and Agriculture ResearchUSDA Agricultural Research Service, Arizona State University, Tempe, AZ ASU092762
6 · The paper itself

Abstract

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.

Indexed as

EcosystemPhotosynthesisGenotypePhenotypeField phenotypingfood securitygas exchangephotosynthesisplant breedingremote sensing

Identifiers

PMID35218184
PMCPMC9126737

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.