Evidence map›Paper›PMID 40462115›Full record

ArticlePlant methods2025

Leaf spectroscopy as a tool for predicting the presence of isoprene emissions and terpene storage in central Amazon forest trees.

Michelle Robin, Flavia Machado Durgante, Caroline Lorenci Mallmann, Hilana Louise Hadlich, Christine Römermann, Lucas de Souza Falcão, Caroline Dutra Lacerda, Sérgio Duvoisin, Florian Wittmann, Maria Teresa Fernandez Piedade and 2 more

Abstract read
In one paragraph

Article in Plant methods, 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

12 authors.

Michelle RobinBiogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany. mcarneiro@bgc-jena.mpg.de.ORCID http://orcid.org/0000-0003-2280-9436
Flavia Machado DurganteDepartment of Wetlands Ecology, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Caroline Lorenci MallmannDepartment of Geosciences, Federal University of Santa Maria, Santa Maria, Brazil.
Hilana Louise HadlichDepartment of Botany, National Institute of Amazonian Research, Manaus, Brazil.
Christine RömermannInstitute for Ecology and Evolution, Friedrich-Schiller University, Jena, Germany.
Lucas de Souza FalcãoDepartment of Chemistry, University of Amazonas State, Manaus, Brazil.
Caroline Dutra LacerdaDepartment of Chemistry, University of Amazonas State, Manaus, Brazil.
Sérgio DuvoisinDepartment of Chemistry, University of Amazonas State, Manaus, Brazil.
Florian WittmannDepartment of Wetlands Ecology, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Maria Teresa Fernandez PiedadeDepartment of Botany, National Institute of Amazonian Research, Manaus, Brazil.
Jochen SchöngartDepartment of Botany, National Institute of Amazonian Research, Manaus, Brazil.
Eliane Gomes AlvesBiogeochemical Processes Department, Max Planck Institute for Biogeochemistry, Jena, Germany. egomes@bgc-jena.mpg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVolatile isoprenoids (VIs), such as isoprene, monoterpenes, and sesquiterpenes, participate in various forest-atmosphere processes ranging from plant cell regulation to atmospheric particle formation. The Amazon Forest is the greatest and most diverse source of VI emissions, but the lack of leaf-level studies and the logistical challenges of measuring in such remote and highly biodiverse sites bring high levels of uncertainty to modeled emission estimates. Studies indicate that leaf spectroscopy is an effective tool for estimating leaf morphological, physiological, and chemical traits, being a promising tool for more easily assessing VI emissions from vegetation. In this study, we tested the ability of leaf reflectance spectroscopy to predict the presence of VI emissions and storage in central Amazon Forest trees. We measured leaf-level isoprene emission capacity (E

resultsWe found that dry leaf hyperspectral reflectance data, and fresh leaf reflectance measured at selected wavelengths (616, 694, and 1155 nm), predicted the presence of isoprene emissions with accuracies of 0.67 and 0.72, respectively. Meanwhile, fresh leaf hyperspectral reflectance data predicted monoterpene and sesquiterpene storage with accuracies of 0.65 and 0.67, respectively.

conclusionsOur results indicate the possibility of using spectral readings from botanical collections or field inventories to orient sampling efforts toward potential isoprene-emitting or terpene-storing trees, or to identify key spectral features (most informative selected wavelengths) for potential future incorporation into remote sensing models. The use of spectral tools for detecting potential isoprene-emitting and terpene-storing species can help to improve current VI emission datasets, reduce modeling emission uncertainties, and contribute to a better understanding of the roles of VIs within forest-atmosphere interactions, atmospheric chemistry, and the carbon cycle.

Indexed as

BVOCsMonoterpenesSesquiterpenesSpectroscopyVolatile isoprenoids

Identifiers

PMID40462115
PMCPMC12135534

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.