Evidence map›Paper›PMID 39130582›Full record

ArticleACS omega2024

Analysis of Macronutrients in Soil Using Impedimetric Multisensor Arrays.

Maria Luisa Braunger, Mario Popolin Neto, Dmitry Kirsanov, Igor Fier, Lucas R Amaral, Flavio M Shimizu, Daniel S Correa, Fernando V Paulovich, Andrey Legin, Osvaldo N Oliveira and 1 more

Abstract read
In one paragraph

Article in ACS omega, 2024. 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

11 authors.

Maria Luisa BraungerInstituto de Física "Gleb Wataghin" (IFGW), Universidade Estadual de Campinas-UNICAMP, Campinas 13083-859, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-6794-5362
Mario Popolin NetoFederal Institute of São Paulo-IFSP, Araraquara 14804-296, São Paulo, Brazil.
Dmitry KirsanovInstitute of Chemistry, Mendeleev Center, St. Petersburg State University, Universitetskaya nab.7/9, St. Petersburg 199034, Russia.
Igor FierQuantum Design Latin America, Campinas 13080-655, São Paulo, Brazil.
Lucas R AmaralSchool of Agricultural Engineering (FEAGRI), University of Campinas-UNICAMP, Campinas 13083-875, São Paulo, Brazil.
Flavio M ShimizuInstituto de Física "Gleb Wataghin" (IFGW), Universidade Estadual de Campinas-UNICAMP, Campinas 13083-859, São Paulo, Brazil.
Daniel S CorreaNanotechnology National Laboratory for Agriculture (LNNA), Embrapa Instrumentação, São Carlos 13560-970, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-5592-0627
Fernando V PaulovichDepartment of Mathematics and Computer Science, Eindhoven University of Technology (TU/e), Eindhoven 5600 MB, The Netherlands.
Andrey LeginInstitute of Chemistry, Mendeleev Center, St. Petersburg State University, Universitetskaya nab.7/9, St. Petersburg 199034, Russia.
Osvaldo N OliveiraSão Carlos Institute of Physics (IFSC), University of São Paulo-USP, São Carlos 13566-590, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-5399-5860
Antonio RiulInstituto de Física "Gleb Wataghin" (IFGW), Universidade Estadual de Campinas-UNICAMP, Campinas 13083-859, São Paulo, Brazil.ORCID https://orcid.org/0000-0002-9760-1851

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The need to increase food production to address the world population growth can only be fulfilled with precision agriculture strategies to increase crop yield with minimal expansion of the cultivated area. One example is site-specific fertilization based on accurate monitoring of soil nutrient levels, which can be made more cost-effective using sensors. This study developed an impedimetric multisensor array using ion-selective membranes to analyze soil samples enriched with macronutrients (N, P, and K), which is compared with another array based on layer-by-layer films. The results obtained from both devices are analyzed with multidimensional projection techniques and machine learning methods, where a decision tree model algorithm chooses the calibrations (best frequencies and sensors). The multicalibration space method indicates that both devices effectively distinguished all soil samples tested, with the ion-selective membrane setup presenting a higher sensitivity to K content. These findings pave the way for more environmentally friendly and efficient agricultural practices, facilitating the mapping of cropping areas for precise fertilizer application and optimized crop yield.

Identifiers

PMID39130582
PMCPMC11307303

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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.