Evaluating pXRF accuracy for predicting soil fertility: effects of moisture and soil properties.

Joao Antonangelo, Somsubhra Chakraborty, Deepanjan Mridha, Shikha Singh, Surendra Singh

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.

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

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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.

Joao AntonangeloDepartment of Crop and Soil Sciences, Washington State University, Pullman, WA, USA. joao.antonangelo@wsu.edu.ORCID http://orcid.org/0000-0001-7329-1150

Somsubhra ChakrabortyAgricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, India.ORCID http://orcid.org/0000-0003-1913-3973

Deepanjan MridhaDepartment of Crop and Soil Sciences, Washington State University, Pullman, WA, USA.ORCID http://orcid.org/0000-0001-6269-3875

Shikha SinghDepartment of Crop and Soil Sciences, Washington State University, Lind, WA, USA.ORCID http://orcid.org/0000-0001-6442-8215

Surendra SinghDepartment of Crop and Soil Sciences, Washington State University, Lind, WA, USA.ORCID http://orcid.org/0000-0002-0920-5665

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Portable X-ray fluorescence (pXRF) has emerged as a rapid, cost-effective tool for assessing soil fertility in precision agriculture. While the influence of soil moisture on pXRF elemental detection has been widely studied, its specific impact on nutrient prediction accuracy, particularly when combined with key soil properties, remains less well quantified. This study investigates how moisture conditions affect pXRF-based detection of soil nutrients and evaluates whether integrating soil properties enhances prediction accuracy. Using stepwise multiple linear regression (SMLR), available macronutrients and micronutrients were modeled from pXRF data under dry soil (DS), field moisture (FM), saturated paste (SP), and after the removal of excess water (AREW) from SP. At both DS and SP, pXRF yielded strong predictions for macronutrients, with R

Indexed as

Portable X-ray fluorescence (pXRF)Precision agricultureSoil moisture effectsSoil nutrient predictionSoil properties

Identifiers

PMID42286186

DOI10.1038/s41598-026-58282-8

PMCPMC13518830

What OpenQuestion holds

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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.