{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T01:53:05Z","timestamp":1782438785774,"version":"3.54.5"},"reference-count":47,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T00:00:00Z","timestamp":1648857600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"German Federal Environment Agency","award":["371 673 208 0"],"award-info":[{"award-number":["371 673 208 0"]}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["VO 1509\/7-1"],"award-info":[{"award-number":["VO 1509\/7-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["LU 583\/19-1"],"award-info":[{"award-number":["LU 583\/19-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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 (\u0394RMSE &lt; 0.4 g\u00b7kg\u22121) and reference SOC uncertainty (\u0394RMSE &lt; 0.3 g\u00b7kg\u22121) to spectral modeling errors were small compared to the difference between the VNIR and MIR spectral ranges (\u0394RMSE ~1.4 g\u00b7kg\u22121 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.<\/jats:p>","DOI":"10.3390\/s22072749","type":"journal-article","created":{"date-parts":[[2022,4,3]],"date-time":"2022-04-03T06:04:01Z","timestamp":1648965841000},"page":"2749","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling"],"prefix":"10.3390","volume":"22","author":[{"given":"Sebastian","family":"Semella","sequence":"first","affiliation":[{"name":"Geoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Hutengs","sequence":"additional","affiliation":[{"name":"Geoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, Germany"},{"name":"Remote Sensing Centre for Earth System Research, Leipzig University, 04103 Leipzig, Germany"},{"name":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Seidel","sequence":"additional","affiliation":[{"name":"Geoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, Germany"},{"name":"Remote Sensing Centre for Earth System Research, Leipzig University, 04103 Leipzig, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1337-252X","authenticated-orcid":false,"given":"Mathias","family":"Ulrich","sequence":"additional","affiliation":[{"name":"Geoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Birgit","family":"Schneider","sequence":"additional","affiliation":[{"name":"Physical Geography, Institute for Geography, Leipzig University, 04103 Leipzig, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Malte","family":"Ortner","sequence":"additional","affiliation":[{"name":"Soil Science, Faculty of Spatial and Environmental Sciences, University of Trier, 54286 Trier, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2721-7333","authenticated-orcid":false,"given":"S\u00f6ren","family":"Thiele-Bruhn","sequence":"additional","affiliation":[{"name":"Soil Science, Faculty of Spatial and Environmental Sciences, University of Trier, 54286 Trier, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8900-6190","authenticated-orcid":false,"given":"Bernard","family":"Ludwig","sequence":"additional","affiliation":[{"name":"Department of Environmental Chemistry, University of Kassel, 37213 Witzenhausen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6048-1163","authenticated-orcid":false,"given":"Michael","family":"Vohland","sequence":"additional","affiliation":[{"name":"Geoinformatics and Remote Sensing, Institute for Geography, Leipzig University, 04103 Leipzig, Germany"},{"name":"Remote Sensing Centre for Earth System Research, Leipzig University, 04103 Leipzig, Germany"},{"name":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Barra, I., Haefele, S.M., Sakrabani, R., and Kebede, F. (2020). Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: Recent advances\u2013A review. TrAC Trends Anal. Chem., 135.","DOI":"10.1016\/j.trac.2020.116166"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Forrester, S.T., Janik, L.J., Soriano-Disla, J.M., Mason, S., Burkitt, L., Moody, P., Gourley, C.J.P., and McLaughlin, M.J. (2015). Use of handheld mid-infrared spectroscopy and partial least-squares regression for the prediction of the phosphorus buffering index in Australian soils. Soil Res., 53.","DOI":"10.1071\/SR14126"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.biosystemseng.2017.06.017","article-title":"Evaluation of the performance of portable visible-infrared instruments for the prediction of soil properties","volume":"161","author":"Janik","year":"2017","journal-title":"Biosyst. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Hutengs, C., Ludwig, B., Jung, A., Eisele, A., and Vohland, M. (2018). Comparison of Portable and Bench-Top Spectrometers for Mid-Infrared Diffuse Reflectance Measurements of Soils. Sensors, 18.","DOI":"10.3390\/s18040993"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Hutengs, C., Seidel, M., Oertel, F., Ludwig, B., and Vohland, M. (2019). In situ and laboratory soil spectroscopy with portable visible-to-near-infrared and mid-infrared instruments for the assessment of organic carbon in soils. Geoderma, 355.","DOI":"10.1016\/j.geoderma.2019.113900"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Janik, L.J., Soriano-Disla, J.M., and Forrester, S.T. (2020). Feasibility of handheld mid-infrared spectroscopy to predict particle size distribution: Influence of soil field condition and utilisation of existing spectral libraries. Soil Res., 58.","DOI":"10.1071\/SR20097"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1111\/j.1475-2743.2011.00337.x","article-title":"Optical sensing and chemometric analysis of soil organic carbon\u2014a cost effective alternative to conventional laboratory methods?","volume":"27","author":"Holden","year":"2011","journal-title":"Soil Use Manag."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1746","DOI":"10.2136\/sssaj2019.06.0205","article-title":"Application of Mid-Infrared Spectroscopy in Soil Survey","volume":"83","author":"Seybold","year":"2019","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1366\/0003702953963247","article-title":"Examination of Some Misconceptions about Near-Infrared Analysis","volume":"49","author":"Difoggio","year":"1995","journal-title":"Appl. Spectrosc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1366\/0003702971941061","article-title":"Improved Prediction Error Estimates for Multivariate Calibration by Correcting for the Measurement Error in the Reference Values","volume":"51","author":"Faber","year":"1997","journal-title":"Appl. Spectrosc."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"94A","DOI":"10.1366\/0003702001949546","article-title":"Guidelines for Applying Chemometrics to Spectra: Feasibility and Error Propagation","volume":"54","author":"Difoggio","year":"2000","journal-title":"Appl. Spectrosc."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"275","DOI":"10.5194\/soil-5-275-2019","article-title":"Error propagation in spectrometric functions of soil organic carbon","volume":"5","author":"Ellinger","year":"2019","journal-title":"SOIL"},{"key":"ref_13","unstructured":"Kuester, M., Thome, K., Krause, K., Canham, K., and Whittington, E. (2001, January 9\u201313). Comparison of surface reflectance measurements from three ASD FieldSpec FR spectroradiometers and one ASD FieldSpec VNIR spectroradiometer. Proceedings of the IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217), Sydney, NSW, Australia."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.biosystemseng.2018.09.013","article-title":"Developing an intelligent system for the prediction of soil properties with a portable mid-infrared instrument","volume":"177","author":"Soto","year":"2019","journal-title":"Biosyst. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Wehrle, R., Welp, G., and P\u00e4tzold, S. (2021). Total and Hot-Water Extractable Organic Carbon and Nitrogen in Organic Soil Amendments: Their Prediction Using Portable Mid-Infrared Spectroscopy with Support Vector Machines. Agronomy, 11.","DOI":"10.3390\/agronomy11040659"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1366\/0003702914337740","article-title":"On the Effect of Calibration and the Accuracy of NIR Spectroscopy with High Levels of Noise in the Reference Values","volume":"45","author":"Aastveit","year":"1991","journal-title":"Appl. Spectrosc."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Stevens, A., Nocita, M., T\u00f3th, G., Montanarella, L., and van Wesemael, B. (2013). Prediction of Soil Organic Carbon at the European Scale by Visible and Near InfraRed Reflectance Spectroscopy. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0066409"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1002\/(SICI)1099-128X(199705)11:3<181::AID-CEM459>3.0.CO;2-7","article-title":"Propagation of measurement errors for the validation of predictions obtained by principal component regression and partial least squares","volume":"11","author":"Faber","year":"1997","journal-title":"J. Chemometr."},{"key":"ref_19","unstructured":"(2005). Geologie von Rheinland-Pfalz, Landesamt f\u00fcr Geologie und Bergbau Rheinland-Pfalz; Schweizerbart."},{"key":"ref_20","unstructured":"Wagner, W.H., Kremb-Wagner, F., Koziol, M., and Negendank, J.F.W. (2012). Trier und Umgebung: Geologie der S\u00fcd- und Westeifel, des S\u00fcdwest-Hunsr\u00fcck, der Unteren Saar Sowie der Maarvulkanismus und die Junge Umwelt- und Klimageschichte, Borntraeger."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"113","DOI":"10.5194\/soil-8-113-2022","article-title":"Content of soil organic carbon and labile fractions depend on local combinations of mineral-phase characteristics","volume":"8","author":"Ortner","year":"2022","journal-title":"SOIL"},{"key":"ref_22","unstructured":"(1996). Soil Quality-Determination of Organic and Total Carbon after Dry Combustion (Elementary Analysis) (Standard No. DIN ISO 10694)."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1080\/07352680902776556","article-title":"Evaluation of Different Soil Carbon Determination Methods","volume":"28","author":"Chatterjee","year":"2009","journal-title":"Crit. Rev. Plant Sci."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Kuhn, M., and Johnson, K. (2013). Applied Predictive Modeling, Springer.","DOI":"10.1007\/978-1-4614-6849-3"},{"key":"ref_25","unstructured":"R Core Team (2020). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_26","unstructured":"Liland, K., Mevik, R., Wehrens, R., and Hiemstra, P. (2021, September 30). pls: Partial Least Squares and Principal Component Regression. R Package Version 2.8-0. Available online: https:\/\/CRAN.R-project.org\/package=pls."},{"key":"ref_27","unstructured":"Stevens, A., Ramirez-Lopez, L., and Guillaume, H. (2020, October 31). prospectr: Miscellaneous Functions for Processing and Sample Selection of Spectroscopic Data. R Package Version 0.2.1. Available online: https:\/\/CRAN.R-project.org\/package=prospectr."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1002\/jpln.200620701","article-title":"Expanded measurement uncertainty of soil parameters derived from proficiency-testing data","volume":"170","author":"Munzert","year":"2007","journal-title":"J. Plant Nutr. Soil Sc."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Ross, D.S., Bailey, S.W., Briggs, R.D., Curry, J., Fernandez, I.J., Fredriksen, G., Goodale, C.L., Hazlett, P.W., Heine, P.R., and Johnson, C.E. (2015). Inter-laboratory variation in the chemical analysis of acidic forest soil reference samples from eastern North America. Ecosphere, 6.","DOI":"10.1890\/ES14-00209.1"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1255\/jnirs.1031","article-title":"Optimising Sample Preparation and near Infrared Spectra Measurements of Soil Samples to Calibrate Organic Carbon and Total Nitrogen Content","volume":"20","author":"Miltz","year":"2012","journal-title":"J. Near Infrared Spec."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1896","DOI":"10.2136\/sssaj2008.0213","article-title":"Near-Infrared Reflectance Spectroscopy Prediction of Soil Properties: Effects of Sample Cups and Preparation","volume":"73","author":"Nduwamungu","year":"2015","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1111\/j.1365-2389.2011.01401.x","article-title":"Sample preparation and selection for qualitative and quantitative analyses of soil organic carbon with mid-infrared reflectance spectroscopy","volume":"62","author":"Stumpe","year":"2011","journal-title":"Eur. J. Soil Sci."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Le Guillou, F., Wetterlind, W., Viscarra Rossel, R.A., Hicks, W., Grundy, M., and Tuomi, S. (2015). How does grinding affect the mid-infrared spectra of soil and their multivariate calibrations to texture and organic carbon?. Soil Res., 53.","DOI":"10.1071\/SR15019"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"S277","DOI":"10.1016\/S0269-7491(01)00259-7","article-title":"The potential of diffuse reflectance spectroscopy for the determination of carbon inventories in soils","volume":"116","author":"Reeves","year":"2002","journal-title":"Environ. Pollut."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1002\/saj2.20194","article-title":"Fine grinding is needed to maintain the high accuracy of MIR spectroscopy for soil property estimation","volume":"85","author":"Wijewardane","year":"2020","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Da Fonseca, A.A., Pasquini, C., Costa, D.C., and Soares, E.M.B. (2022). Effect of the sample measurement representativeness on soil carbon determination using near-infrared compact spectrophotometers. Geoderma, 409.","DOI":"10.1016\/j.geoderma.2021.115636"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.geoderma.2014.01.013","article-title":"Determination of soil properties with visible to near- and mid-infrared spectroscopy: Effects of spectral variable selection","volume":"223\u2013225","author":"Vohland","year":"2014","journal-title":"Geoderma"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Stenberg, B., Viscarra Rossel, R.A., Mouazen, A.M., and Wetterlind, J. (2010). Visible and Near Infrared Spectroscopy in Soil Science, Elsevier.","DOI":"10.1016\/S0065-2113(10)07005-7"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1080\/05704928.2013.811081","article-title":"The perfomance of visible, near-, and mid-infrared reflectance spectroscopy for prediction of soil physical, chemical, and biological properties","volume":"49","author":"Janik","year":"2014","journal-title":"Appl. Spectrosc. Rev."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.geoderma.2009.04.005","article-title":"Near-versus mid-infrared diffuse reflectance spectroscopy for soil analysis emphasising carbon and laboratory versus on-site analysis: Where are we and what needs to be done?","volume":"158","author":"Reeves","year":"2010","journal-title":"Geoderma"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Greenberg, I., Seidel, M., Vohland, M., Koch, H.J., and Ludwig, B. (2022). Performance of in situ vs. laboratory mid-infrared soil spectroscopy using local and regional calibration strategies. Geoderma, 409.","DOI":"10.1016\/j.geoderma.2021.115614"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Hutengs, C., Eisenhauer, N., Sch\u00e4dler, M., Lochner, A., Seidel, M., and Vohland, M. (2021). VNIR and MIR spectroscopy of PLFA-derived soil microbial properties and associated physicochemical soil characteristics in an experimental plant diversity gradient. Soil Biol. Biochem., 160.","DOI":"10.1016\/j.soilbio.2021.108319"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1398","DOI":"10.1016\/j.soilbio.2011.02.019","article-title":"Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils\u2014Critical review and research perspectives","volume":"43","author":"McBratney","year":"2011","journal-title":"Soil Biol. Biochem."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Angelopoulou, T., Balafoutis, A., Zalidis, G., and Bochtis, D. (2020). From Laboratory to Proximal Sensing Spectroscopy for Soil Organic Carbon Estimation\u2014A Review. Sustainability, 12.","DOI":"10.3390\/su12020443"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Vohland, M., Ludwig, B., Seidel, M., and Hutengs, C. (2022). Quantification of soil organic carbon at regional scale: Benefits of fusing vis-NIR and MIR diffuse reflectance data are greater for in situ than for laboratory-based modelling approaches. Geoderma, 405.","DOI":"10.1016\/j.geoderma.2021.115426"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.geoderma.2005.03.007","article-title":"Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties","volume":"131","author":"Walvoort","year":"2006","journal-title":"Geoderma"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Hong, Y., Munnaf, M.A., Guerrero, A., Chen, S., Liu, Y., Shi, Z., and Mouazen, A.M. (2022). Fusion of visible-to-near-infrared and mid-infrared spectroscopy to estimate soil organic carbon. Soil Till. Res., 217.","DOI":"10.1016\/j.still.2021.105284"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/7\/2749\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:49:05Z","timestamp":1760136545000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/7\/2749"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,2]]},"references-count":47,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["s22072749"],"URL":"https:\/\/doi.org\/10.3390\/s22072749","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,2]]}}}