Evidence map›Paper›PMID 40619784›Full record

ArticlePlant, cell & environment2025

Non-Invasive Phenotyping of Sugar Beet and Maize Roots Using Field-Scale Spectral Electrical Impedance Tomography.

Valentin Michels, Maximilian Weigand, Lena Lärm, Onno Muller, Andreas Kemna

Abstract read
In one paragraph

Article in Plant, cell & environment, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Valentin MichelsInstitute of Geosciences, Geophysics Section, University of Bonn, Bonn, Germany.ORCID 0009-0005-4339-4905
Maximilian WeigandInstitute of Geosciences, Geophysics Section, University of Bonn, Bonn, Germany.ORCID 0000-0003-0510-1938
Lena LärmInstitute of Bio- and Geosciences, Agrosphere (IBG-3), Forschungszentrum Jülich, Jülich, Germany.ORCID 0000-0002-0633-4293
Onno MullerInstitute of Bio- and Geosciences, Plant Sciences (IBG-2), Forschungszentrum Jülich, Jülich, Germany.ORCID 0000-0002-0473-5632
Andreas KemnaInstitute of Geosciences, Geophysics Section, University of Bonn, Bonn, Germany.ORCID 0000-0002-3709-1378

Funding

This study was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC 2070 - 390732324 - PhenoRob within the project 'Structural and functional field root sensing using tomographic and endoscopic electrical impedance tomography'.
6 · The paper itself

Abstract

Root systems are essential for plant water and nutrient uptake, but are difficult to characterize in-situ due to their inaccessibility. Spectral electrical impedance tomography (sEIT) is a non-invasive geoelectrical method that has shown potential to quantify root traits at the laboratory scale. However, field applications remain scarce due to technical limitations and challenges in separating soil and root polarization signatures. This study explores the use of sEIT for in-situ phenotyping of sugar beet and maize root systems. We conducted multi-frequency sEIT measurements at varying crop growth stages to derive the subsurface complex resistivity distribution. Spectral analysis revealed high-frequency polarization peaks for both species. Additionally, sugar beets exhibited an additional low-frequency peak late-season, which we attribute to the development of large storage parenchyma. For sugar beet, the high root-to-soil volume fraction allowed a direct correlation of electrical parameters to root biomass density. For maize, the superimposed soil polarization necessitated an alternative approach: We introduce an electrical root index (

Indexed as

Beta vulgarisPlant RootsTomographyZea maysBiomassElectric ImpedancePhenotypeSoilSoilagrogeophysicsinduced polarizationmaizeroot phenotypingspectral electrical impedance tomographysugar beet

Identifiers

PMID40619784
PMCPMC12415421

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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.