Evidence map›Paper›PMID 35274030›Full record

ArticleData in brief2022

Spectral data of tropical soils using dry-chemistry techniques (VNIR, XRF, and LIBS): A dataset for soil fertility prediction.

Tiago Rodrigues Tavares, José Paulo Molin, Lidiane Cristina Nunes, Elton Eduardo Novais Alves, Francisco José Krug, Hudson Wallace Pereira de Carvalho

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Data in brief, 2022. 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
1.6field-weighted citation impact, top 21% of its field
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, 12 citations in OpenAlex.

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

6 authors at 3 institutions in 2 countries.

Tiago Rodrigues TavaresDepartment of Biosystems Engineering, "Luiz de Queiroz" College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, São Paulo 13418900, Brazil.
José Paulo MolinDepartment of Biosystems Engineering, "Luiz de Queiroz" College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, São Paulo 13418900, Brazil.
Lidiane Cristina NunesCenter for Nuclear Energy in Agriculture (CENA), University of São Paulo (USP), Piracicaba, São Paulo 13416000, Brazil.
Elton Eduardo Novais AlvesCESFRA, AgroBioSciences, Mohammed VI Polytechnic University, BenGuerir 43150, Morocco.
Francisco José KrugCenter for Nuclear Energy in Agriculture (CENA), University of São Paulo (USP), Piracicaba, São Paulo 13416000, Brazil.
Hudson Wallace Pereira de CarvalhoCenter for Nuclear Energy in Agriculture (CENA), University of São Paulo (USP), Piracicaba, São Paulo 13416000, Brazil.
Universidade de São Paulo · BRUniversidade Federal de Minas Gerais · BRUniversité Mohammed VI Polytechnique · MA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proximal soil sensing technologies, such as visible and near infrared diffuse reflectance spectroscopy (VNIR), X-ray fluorescence spectroscopy (XRF), and laser-induced breakdown spectroscopy (LIBS), are dry-chemistry techniques that enable rapid and environmentally friendly soil fertility analyses. The application of XRF and LIBS sensors in an individual or combined manner for soil fertility prediction is quite recent, especially in tropical soils. The shared dataset presents spectral data of VNIR, XRF, and LIBS sensors, even as the characterization of key soil fertility attributes (clay, organic matter, cation exchange capacity, pH, base saturation, and exchangeable P, K, Ca, and Mg) of 102 soil samples. The samples were obtained from two Brazilian agricultural areas and have a wide variation of chemical and textural attributes. This is a pioneer dataset of tropical soils, with potential to be reused for comparative studies with other datasets,

Indexed as

Hybrid laboratoryPedometricsPrecision agricultureProximal Soil SensingSoil spectral libraries

Identifiers

PMID35274030
PMCPMC8902611
OpenAlexW4214492526

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.