Evidence map›Paper›PMID 39217189›Full record

ArticleScientific reports2024

Assessing soil CO

Fernando Saragosa Rossi, João Lucas Della-Silva, Larissa Pereira Ribeiro Teodoro, Paulo Eduardo Teodoro, Dthenifer Cordeiro Santana, Fábio Henrique Rojo Baio, Wendel Bueno Morinigo, Luís Guilherme Teixeira Crusiol, Newton La Scala, Carlos Antonio da Silva

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. COChemical science · 2025
    Article
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

10 authors.

Fernando Saragosa RossiPPG-Ciência do Solo, State University of São Paulo (UNESP), Jaboticabal, 15385-000, Brazil.
João Lucas Della-SilvaPPG-Bionorte, State University of Mato Grosso (UNEMAT), Sinop, 78550-000, Brazil.
Larissa Pereira Ribeiro TeodoroFederal University of Mato Grosso do Sul (UFMS), Chapadão do Sul, 79560-000, Brazil.
Paulo Eduardo TeodoroFederal University of Mato Grosso do Sul (UFMS), Chapadão do Sul, 79560-000, Brazil. eduteodoro@hotmail.com.
Dthenifer Cordeiro SantanaFederal University of Mato Grosso do Sul (UFMS), Chapadão do Sul, 79560-000, Brazil.
Fábio Henrique Rojo BaioFederal University of Mato Grosso do Sul (UFMS), Chapadão do Sul, 79560-000, Brazil.
Wendel Bueno MorinigoPPGCAM, Federal University of Mato Grosso (UFMT), Sinop, 78555000, Brazil.
Luís Guilherme Teixeira CrusiolNational Soybean Research Center (Embrapa Soja), Brazilian Agricultural Research Corporation, Londrina, 86001-970, Brazil.
Newton La ScalaPPG-Ciência do Solo, State University of São Paulo (UNESP), Jaboticabal, 15385-000, Brazil.
Carlos Antonio da SilvaDepartment of Geography, State University of Mato Grosso (UNEMAT), Sinop, Mato Grosso, 78555000, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Eucalyptus species play an important role in the global carbon cycle, especially in reducing the greenhouse effect as well as storing atmospheric CO₂. Thus, assessing the amount of CO₂ released by the soil in forest areas can generate important information for environmental monitoring. This study aims to verify the relation between soil carbon dioxide (CO₂) flux (FCO₂), spectral bands, and vegetation indices (VIs) derived from a UAV-based multispectral camera over an area of eucalyptus species. Multispectral imageries (green, red-edge, and near-infrared) from the Parrot Sequoia sensor, derived vegetation indices, and the FCO₂ data from a LI-COR 8100 analyzer, combined with soil moisture and temperature data, were collected and related. The vegetation indices ATSAVI (Adjusted Transformed Soil-Adjusted VI), GSAVI (Green Soil Adjusted Vegetation Index), and SAVI (Soil-Adjusted Vegetation Index), which use soil correction factors, exhibited a strong negative correlation with FCO₂ for the species E. camaldulensis, E. saligna, and E. urophylla species. A Multivariate Analysis of Variance showed significance (p < 0.01) for the species factor, which indicates that there are differences when considering all variables simultaneously. The results achieved in this study show a specific correlation between the data of soil CO₂ emission and the eucalypt species, providing a distinction of values between the species in the statistical data.

Indexed as

Carbon DioxideEucalyptusSoilEnvironmental MonitoringForestsRemote Sensing TechnologyCarbon DioxideSoil

Identifiers

PMID39217189
PMCPMC11365961

What OpenQuestion holds

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Registered trials

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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.