Evidence map›Paper›PMID 41882072›Full record

ArticleScientific reports2026

Analyzing the share of amorphous silica in mixtures with different soil minerals using fourier transform infrared spectroscopy and PLSR chemometrics.

Oliver Hunfeld, Ruth H Ellerbrock, Mathias Stein, Carsten W Müller, Jörg Schaller

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

5 authors.

Oliver HunfeldLeibniz Centre for Agricultural Landscape Research (ZALF) , Müncheberg, Germany.
Ruth H EllerbrockLeibniz Centre for Agricultural Landscape Research (ZALF) , Müncheberg, Germany.
Mathias SteinLeibniz Centre for Agricultural Landscape Research (ZALF) , Müncheberg, Germany.
Carsten W MüllerChair of Soil Science Institute of Ecology , Technische Universität Berlin , Berlin, 10587, Germany.
Jörg SchallerLeibniz Centre for Agricultural Landscape Research (ZALF) , Müncheberg, Germany. Joerg.Schaller@zalf.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amorphous silica (ASi) improves key soil functions and crop productivity but is difficult to quantify due to complex mineral mixtures and time-consuming chemical analyses. This study explored the possibility of using Fourier-transform infrared spectroscopy (FTIR) in combination with partial least-squares regression (PLSR) to estimate the ASi content in samples of mineral mixtures. For this purpose, mixtures of different pedogenic minerals (kaolin and montmorillonite) with known ASi content were produced and analysed using FTIR spectroscopy. Based on these data, a PLSR model was used to predict the ASi concentration based on the FTIR spectra. The results show that the model is capable of estimating ASi content in simple mineral mixtures with high accuracy. This suggests that FTIR, combined with PLSR, could be a promising method for the rapid and cost-effective determination of ASi in environmental samples. Future studies should investigate how the method performs with more complex mixtures and natural soil samples, and how factors such as mineral weathering and sample origin influence the accuracy of the prediction.

Indexed as

Amorphous silicaFourier-transform infrared spectroscopyPedogenic mineralsQuantificationSilicon

Identifiers

PMID41882072
PMCPMC13022021

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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.