Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling
Soil spectroscopy in the visible-to-near infrared (VNIR) and mid-infrared (MIR) is a cost-effective method to determine the soil organic carbon content (SOC) based on predictive spectral models calibrated to analytical-determined SOC reference data. The degree to which uncertainty in reference data...
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MDPI AG
2022-04-01
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| Online Access: | https://www.mdpi.com/1424-8220/22/7/2749 |
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| author | Sebastian Semella Christopher Hutengs Michael Seidel Mathias Ulrich Birgit Schneider Malte Ortner Sören Thiele-Bruhn Bernard Ludwig Michael Vohland |
| author_facet | Sebastian Semella Christopher Hutengs Michael Seidel Mathias Ulrich Birgit Schneider Malte Ortner Sören Thiele-Bruhn Bernard Ludwig Michael Vohland |
| author_sort | Sebastian Semella |
| collection | DOAJ |
| description | Soil spectroscopy in the visible-to-near infrared (VNIR) and mid-infrared (MIR) is a cost-effective method to determine the soil organic carbon content (SOC) based on predictive spectral models calibrated to analytical-determined SOC reference data. The degree to which uncertainty in reference data and spectral measurements contributes to the estimated accuracy of VNIR and MIR predictions, however, is rarely addressed and remains unclear, in particular for current handheld MIR spectrometers. We thus evaluated the reproducibility of both the spectral reflectance measurements with portable VNIR and MIR spectrometers and the analytical dry combustion SOC reference method, with the aim to assess how varying spectral inputs and reference values impact the calibration and validation of predictive VNIR and MIR models. Soil reflectance spectra and SOC were measured in triplicate, the latter by different laboratories, for a set of 75 finely ground soil samples covering a wide range of parent materials and SOC contents. Predictive partial least-squares regression (PLSR) models were evaluated in a repeated, nested cross-validation approach with systematically varied spectral inputs and reference data, respectively. We found that SOC predictions from both VNIR and MIR spectra were equally highly reproducible on average and similar to the dry combustion method, but MIR spectra were more robust to calibration sample variation. The contributions of spectral variation (ΔRMSE < 0.4 g·kg<sup>−1</sup>) and reference SOC uncertainty (ΔRMSE < 0.3 g·kg<sup>−1</sup>) to spectral modeling errors were small compared to the difference between the VNIR and MIR spectral ranges (ΔRMSE ~1.4 g·kg<sup>−1</sup> in favor of MIR). For reference SOC, uncertainty was limited to the case of biased reference data appearing in either the calibration or validation. Given better predictive accuracy, comparable spectral reproducibility and greater robustness against calibration sample selection, the portable MIR spectrometer was considered overall superior to the VNIR instrument for SOC analysis. Our results further indicate that random errors in SOC reference values are effectively compensated for during model calibration, while biased SOC calibration data propagates errors into model predictions. Reference data uncertainty is thus more likely to negatively impact the estimated validation accuracy in soil spectroscopy studies where archived data, e.g., from soil spectral libraries, are used for model building, but it should be negligible otherwise. |
| first_indexed | 2024-03-09T11:25:26Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T11:25:26Z |
| publishDate | 2022-04-01 |
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| spelling | doaj.art-8f0849e7f4fa42bcba4eff176cdfa7962023-12-01T00:04:51ZengMDPI AGSensors1424-82202022-04-01227274910.3390/s22072749Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon ModelingSebastian Semella0Christopher Hutengs1Michael Seidel2Mathias Ulrich3Birgit Schneider4Malte Ortner5Sören Thiele-Bruhn6Bernard Ludwig7Michael Vohland8Geoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, GermanyGeoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, GermanyGeoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, GermanyGeoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, GermanyPhysical Geography, Institute for Geography, Leipzig University, 04103 Leipzig, GermanySoil Science, Faculty of Spatial and Environmental Sciences, University of Trier, 54286 Trier, GermanySoil Science, Faculty of Spatial and Environmental Sciences, University of Trier, 54286 Trier, GermanyDepartment of Environmental Chemistry, University of Kassel, 37213 Witzenhausen, GermanyGeoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, GermanySoil spectroscopy in the visible-to-near infrared (VNIR) and mid-infrared (MIR) is a cost-effective method to determine the soil organic carbon content (SOC) based on predictive spectral models calibrated to analytical-determined SOC reference data. The degree to which uncertainty in reference data and spectral measurements contributes to the estimated accuracy of VNIR and MIR predictions, however, is rarely addressed and remains unclear, in particular for current handheld MIR spectrometers. We thus evaluated the reproducibility of both the spectral reflectance measurements with portable VNIR and MIR spectrometers and the analytical dry combustion SOC reference method, with the aim to assess how varying spectral inputs and reference values impact the calibration and validation of predictive VNIR and MIR models. Soil reflectance spectra and SOC were measured in triplicate, the latter by different laboratories, for a set of 75 finely ground soil samples covering a wide range of parent materials and SOC contents. Predictive partial least-squares regression (PLSR) models were evaluated in a repeated, nested cross-validation approach with systematically varied spectral inputs and reference data, respectively. We found that SOC predictions from both VNIR and MIR spectra were equally highly reproducible on average and similar to the dry combustion method, but MIR spectra were more robust to calibration sample variation. The contributions of spectral variation (ΔRMSE < 0.4 g·kg<sup>−1</sup>) and reference SOC uncertainty (ΔRMSE < 0.3 g·kg<sup>−1</sup>) to spectral modeling errors were small compared to the difference between the VNIR and MIR spectral ranges (ΔRMSE ~1.4 g·kg<sup>−1</sup> in favor of MIR). For reference SOC, uncertainty was limited to the case of biased reference data appearing in either the calibration or validation. Given better predictive accuracy, comparable spectral reproducibility and greater robustness against calibration sample selection, the portable MIR spectrometer was considered overall superior to the VNIR instrument for SOC analysis. Our results further indicate that random errors in SOC reference values are effectively compensated for during model calibration, while biased SOC calibration data propagates errors into model predictions. Reference data uncertainty is thus more likely to negatively impact the estimated validation accuracy in soil spectroscopy studies where archived data, e.g., from soil spectral libraries, are used for model building, but it should be negligible otherwise.https://www.mdpi.com/1424-8220/22/7/2749visible-to-near infraredmid-infraredportablespectroscopysoil organic carbondry combustion |
| spellingShingle | Sebastian Semella Christopher Hutengs Michael Seidel Mathias Ulrich Birgit Schneider Malte Ortner Sören Thiele-Bruhn Bernard Ludwig Michael Vohland Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling Sensors visible-to-near infrared mid-infrared portable spectroscopy soil organic carbon dry combustion |
| title | Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling |
| title_full | Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling |
| title_fullStr | Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling |
| title_full_unstemmed | Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling |
| title_short | Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling |
| title_sort | accuracy and reproducibility of laboratory diffuse reflectance measurements with portable vnir and mir spectrometers for predictive soil organic carbon modeling |
| topic | visible-to-near infrared mid-infrared portable spectroscopy soil organic carbon dry combustion |
| url | https://www.mdpi.com/1424-8220/22/7/2749 |
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