Field Evaluation of a Portable Multi-Sensor Soil Carbon Analyzer: Performance, Precision, and Limitations Under Real-World Conditions

Soil organic carbon (SOC) monitoring is central to carbon farming Monitoring, Reporting, and Verification (MRV), yet high laboratory costs and sparse sampling limit its scalability. We present the first independent field validation of the Stenon FarmLab multi-sensor probe across 100 temperate European arable-soil samples, benchmarking its default outputs and a simple pH-corrected model against three laboratory reference methods: acid-treated TOC, temperature-differentiated TOC (SoliTOC), and total carbon dry combustion. Uncorrected FarmLab algorithms systematically overestimated SOC by +0.20% to +0.27% (SD = 0.25–0.28%), while pH adjustment reduced bias to +0.11% and tightened precision to SD = 0.23%. Volumetric moisture had no significant effect on measurement error (r = −0.14, p = 0.16). Bland–Altman and Deming regression demonstrated improved agreement after pH correction, but formal equivalence testing (accuracy, precision, concordance) showed that no in-field model fully matched laboratory standards—the pH-corrected variant passed accuracy and concordance evaluation yet failed the precision criterion (p = 0.0087). At ~EUR 3–4 per measurement versus ~EUR 44 for lab analysis, FarmLab facilitates dense spatial sampling. We recommend a hybrid monitoring strategy combining routine, pH-corrected in-field mapping with laboratory-based recalibrations alongside expanded calibration libraries, integrated bulk density measurement, and adaptive machine learning to achieve both high-resolution and certification-grade rigor.

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Publication Details

Journal
Soil Systems
Published
2025-06-27
DOI
https://doi.org/10.3390/soilsystems9030067
Citations
1
Primary Topic
Soil Geostatistics and Mapping
Type
article
Field-Weighted Citation Impact
0.80

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article

Field Evaluation of a Portable Multi-Sensor Soil Carbon Analyzer: Performance, Precision, and Limitations Under Real-World Conditions

Christian Ahl, Claus Vielhauer, Andreas Gattinger, Eva-Maria L. Minarsch et al.
1 citations
Soil Systems
Soil Geostatistics and Mapping
0.80
article

Field Evaluation of a Portable Multi-Sensor Soil Carbon Analyzer: Performance, Precision, and Limitations Under Real-World Conditions

Christian Ahl, Claus Vielhauer, Andreas Gattinger, Eva-Maria L. Minarsch, J. C. Brown, Lukas Kohl, Abdullah Öztürk, Wiebke Niether
article en
1 citations

Abstract

Soil organic carbon (SOC) monitoring is central to carbon farming Monitoring, Reporting, and Verification (MRV), yet high laboratory costs and sparse sampling limit its scalability. We present the first independent field validation of the Stenon FarmLab multi-sensor probe across 100 temperate European arable-soil samples, benchmarking its default outputs and a simple pH-corrected model against three laboratory reference methods: acid-treated TOC, temperature-differentiated TOC (SoliTOC), and total carbon dry combustion. Uncorrected FarmLab algorithms systematically overestimated SOC by +0.20% to +0.27% (SD = 0.25–0.28%), while pH adjustment reduced bias to +0.11% and tightened precision to SD = 0.23%. Volumetric moisture had no significant effect on measurement error (r = −0.14, p = 0.16). Bland–Altman and Deming regression demonstrated improved agreement after pH correction, but formal equivalence testing (accuracy, precision, concordance) showed that no in-field model fully matched laboratory standards—the pH-corrected variant passed accuracy and concordance evaluation yet failed the precision criterion (p = 0.0087). At ~EUR 3–4 per measurement versus ~EUR 44 for lab analysis, FarmLab facilitates dense spatial sampling. We recommend a hybrid monitoring strategy combining routine, pH-corrected in-field mapping with laboratory-based recalibrations alongside expanded calibration libraries, integrated bulk density measurement, and adaptive machine learning to achieve both high-resolution and certification-grade rigor.

Soil SystemsVol. 9(3)
Justus-Liebig-Universität Gießen (DE), Technische Universität Berlin (DE), University of Göttingen (DE)
European Commission
Openalex Percentile: Top 28%
Soil Geostatistics and Mapping
0.80
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