Evidence map›Paper›PMID 33025222›Full record

ArticleEnvironmental monitoring and assessment2020

Near-infrared spectroscopy for the prediction of rare earth elements in soils from the largest uranium-phosphate deposit in Brazil using PLS, iPLS, and iSPA-PLS models.

Angelo Jamil Maia, Yuri Jacques Agra Bezerra da Silva, Clístenes Williams Araújo do Nascimento, Germano Veras, Maria Eugenia Ortiz Escobar, Cleyton Saialy Medeiros Cunha, Ygor Jacques Agra Bezerra da Silva, Rennan Cabral Nascimento, Lavínia Hannah de Souza Pereira

Abstract read
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Article in Environmental monitoring and assessment, 2020. 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
1.5field-weighted citation impact, top 13% 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, 18 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

9 authors at 4 institutions in 1 country.

Angelo Jamil MaiaAgronomy Department, Federal Rural University of Pernambuco (UFRPE), Dom Manuel de Medeiros street, s/n - Dois Irmãos, Recife, PE, 52171-900, Brazil.
Yuri Jacques Agra Bezerra da SilvaAgronomy Department, Federal University of Piaui (UFPI), Planalto Horizonte, Bom Jesus, PI, 64900-000, Brazil. yurijacques@ufpi.edu.br.ORCID http://orcid.org/0000-0001-6865-7146
Clístenes Williams Araújo do NascimentoAgronomy Department, Federal Rural University of Pernambuco (UFRPE), Dom Manuel de Medeiros street, s/n - Dois Irmãos, Recife, PE, 52171-900, Brazil.
Germano VerasChemistry Department, State University of Paraiba, Baraúnas St. 351, Campina Grande, PB, 58429-500, Brazil.
Maria Eugenia Ortiz EscobarSoil Science Department, Federal University of Ceará (UFC), Av. Mister Hull, s/n, Campus do Pici, Fortaleza, CE 60455-760, Brazil.
Cleyton Saialy Medeiros CunhaSoil Science Department, Federal University of Ceará (UFC), Av. Mister Hull, s/n, Campus do Pici, Fortaleza, CE 60455-760, Brazil.
Ygor Jacques Agra Bezerra da SilvaAgronomy Department, Federal Rural University of Pernambuco (UFRPE), Dom Manuel de Medeiros street, s/n - Dois Irmãos, Recife, PE, 52171-900, Brazil.
Rennan Cabral NascimentoAgronomy Department, Federal Rural University of Pernambuco (UFRPE), Dom Manuel de Medeiros street, s/n - Dois Irmãos, Recife, PE, 52171-900, Brazil.
Lavínia Hannah de Souza PereiraChemistry Department, State University of Paraiba, Baraúnas St. 351, Campina Grande, PB, 58429-500, Brazil.
Universidade Federal Rural de Pernambuco · BRUniversidade Estadual da Paraíba · BRUniversidade Federal do Ceará · BRUniversidade Federal do Piauí · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The largest uranium-phosphate deposit in Brazil also contains considerable levels of rare earth elements (REEs), which allows for the co-mining of these three ores. The most common methods for REE determination are time-consuming and demand complex sample preparation and use of hazardous reagents. Thus, the development of a safer and faster method to predict REEs in soil could aid in the assessment of these elements. We investigated the efficiency of near-infrared (NIR) spectroscopy to predict REEs in the soil of the uranium-phosphate deposit of Itataia, Brazil. We collected 50 composite topsoil samples in a well-distributed sampling grid along the deposit. The NIR measures in the soils ranged from 750 to 2500 nm. Three partial least squares regressions (PLSR) were selected to calibrate the spectra: full-spectrum partial least squares (PLS), interval partial least squares (iPLS), and successive projections algorithms for interval selection in partial least squares (iSPA-PLS). The concentrations of REEs were measured by inductively coupled plasma optical emission spectroscopy (ICP-OES). In addition to raw spectral data, we also used spectral pretreatments to investigate the effects on prediction results: multiplicative scatter correction (MSC), Savitzky-Golay derivatives (SG), and standard normal variate transformation (SNV). Positive results were obtained in PLS for La and ΣLREE using MSC pretreatment and in iSPA-PLS for Nd and Ce using raw data. The accuracy of the measurements was related to the REE concentration in soil; i.e., elements with higher concentrations tended to present more accurate results. The results obtained here aim to contribute to the development of NIR spectroscopy techniques as a tool for mapping the concentrations of REEs in topsoil.

Indexed as

UraniumBrazilEnvironmental MonitoringLeast-Squares AnalysisPhosphatesSoilSpectroscopy, Near-InfraredPhosphatesSoilUraniumChemometricsGeomappingNIRSoil contaminationSpectral pretreatment

Identifiers

PMID33025222
OpenAlexW3092194749

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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.