Evidence map›Paper›PMID 39696591›Full record

ArticlePlant methods2024

In-vivo Raman microspectroscopy reveals differential nitrate concentration in different developmental zones in Arabidopsis roots.

Alma Fernández González, Ze Tian Fang, Dipankar Sen, Brian Henrich, Yukihiro Nagashima, Alexei V Sokolov, Sakiko Okumoto, Aart J Verhoef

Abstract read
In one paragraph

Article in Plant methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

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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

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Alma Fernández González *Department of Soil and Crop Sciences, Texas A&M University and Texas A&M AgriLife Research, College Station, TX, USA.
Ze Tian Fang *Department of Soil and Crop Sciences, Texas A&M University and Texas A&M AgriLife Research, College Station, TX, USA.
Dipankar Sen *Institute of Quantum Science and Engineering, Texas A&M University, College Station, TX, USA.
Brian HenrichDepartment of Soil and Crop Sciences, Texas A&M University and Texas A&M AgriLife Research, College Station, TX, USA.
Yukihiro NagashimaDepartment of Horticultural Sciences, Texas A&M University and Texas A&M AgriLife Research, College Station, TX, USA.
Alexei V SokolovInstitute of Quantum Science and Engineering, Texas A&M University, College Station, TX, USA.
Sakiko OkumotoDepartment of Soil and Crop Sciences, Texas A&M University and Texas A&M AgriLife Research, College Station, TX, USA. Sakiko.Okumoto@ag.tamu.edu.
Aart J VerhoefDepartment of Soil and Crop Sciences, Texas A&M University and Texas A&M AgriLife Research, College Station, TX, USA. Aart.Verhoef@ag.tamu.edu.

Funding

Texas A and M University AgriLife ResearchTexas A and M University X-Grant Program and startup fundsU.S. Department of Energy SC BER Grant # FWP-ERW7011Welch Foundation A-1547
6 · The paper itself

Abstract

backgroundNitrate (NO

resultsAs a proof of concept, we have used Raman microspectroscopy for in-vivo mapping of nitrate content in roots of Arabidopsis seedlings grown on agar media with different nitrate concentrations. Our results revealed that the root nitrate concentration increases gradually from the meristematic zone (~ 250 µm from the root cap) to the maturation zone (~ 3 mm from the root cap) in roots grown under typical growth conditions used for Arabidopsis, a trend that has not been previously reported. This trend was observed for plants grown in agar media with different nitrate concentrations (0.5-10 mM). These results were validated through destructive measurement of nitrate concentration.

conclusionsWe present a methodology based on Raman microspectroscopy for in-vivo label-free mapping of nitrate within small root tissue volumes in Arabidopsis. Measurements are done in-situ without additional sample preparation. Our measurements revealed nitrate concentration changes from lower to higher concentration from tip to mature root tissue. Accumulation of nitrate in the maturation zone tissue shows a saturation behavior. The presented Raman-based approach allows for in-situ non-destructive measurements of Raman-active compounds.

Indexed as

Arabidopsis thalianaIn-situ non-destructive measurementIn-vivo mappingNitrate uptake and storageRaman spectroscopy and microscopyRoot imaging

Identifiers

PMID39696591
PMCPMC11657419

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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.