{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T17:04:51Z","timestamp":1772643891339,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T00:00:00Z","timestamp":1717113600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Agroscope Research Programme \u201cIndicate-Measuring and Optimising Farm Environmental Impacts\u201d","award":["862695"],"award-info":[{"award-number":["862695"]}]},{"name":"Horizon 2020 European Joint Program (EJP) SOIL project \u201cProbeField\u201d","award":["862695"],"award-info":[{"award-number":["862695"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>One challenge in predicting soil parameters using in situ visible and near infrared spectroscopy is the distortion of the spectra due to soil moisture. External parameter orthogonalization (EPO) is a mathematical method to remove unwanted variability from spectra. We created two different EPO correction matrices based on the difference between spectra collected in situ and, respectively, spectra collected from the same soil samples after drying and sieving and after drying, sieving and finely grinding. Spectra from 134 soil samples recorded with two different spectrometers were split into calibration and validation sets and the two EPO corrections were applied. Clay, organic carbon and total nitrogen content were predicted by partial least squares regression for uncorrected and EPO-corrected spectra using models based on the same type of spectra (\u201cwithin domain\u201d) as well as using laboratory-based models to predict in situ collected spectra (\u201ccross-domain\u201d). Our results show that the within-domain prediction of clay is improved with EPO corrections only for the research grade spectrometer, with no improvement for the other parameters. For the cross-domain predictions, there was a positive effect from both EPO corrections on all parameters. Overall, we also found that in situ collected spectra provided an equally successful prediction as laboratory-based spectra.<\/jats:p>","DOI":"10.3390\/s24113556","type":"journal-article","created":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T11:43:48Z","timestamp":1717155828000},"page":"3556","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Prediction Accuracy of Soil Chemical Parameters by Field- and Laboratory-Obtained vis-NIR Spectra after External Parameter Orthogonalization"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8075-0252","authenticated-orcid":false,"given":"Konrad","family":"Metzger","sequence":"first","affiliation":[{"name":"Field-Crop Systems and Plant Nutrition, Agroscope, Route de Duillier 60, 1260 Nyon, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0000-7491","authenticated-orcid":false,"given":"Frank","family":"Liebisch","sequence":"additional","affiliation":[{"name":"Water Protection and Substance Flows, Agroscope, Reckenholzstrasse 191, 8046 Zurich, Switzerland"}]},{"given":"Juan M.","family":"Herrera","sequence":"additional","affiliation":[{"name":"Cultivation Techniques and Varieties in Arable Farming, Agroscope, Route de Duillier 60, 1260 Nyon, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6926-9337","authenticated-orcid":false,"given":"Thomas","family":"Guillaume","sequence":"additional","affiliation":[{"name":"Field-Crop Systems and Plant Nutrition, Agroscope, Route de Duillier 60, 1260 Nyon, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8583-284X","authenticated-orcid":false,"given":"Luca","family":"Bragazza","sequence":"additional","affiliation":[{"name":"Field-Crop Systems and Plant Nutrition, Agroscope, Route de Duillier 60, 1260 Nyon, Switzerland"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e13481","DOI":"10.1111\/ejss.13481","article-title":"In-field soil spectroscopy in Vis\u2013NIR range for fast and reliable soil analysis: A review","volume":"75","author":"Piccini","year":"2024","journal-title":"Eur. J. Soil Sci."},{"key":"ref_2","unstructured":"Nocita, M., Stevens, A., van Wesemael, B., Aitkenhead, M., Bachmann, M., Barth\u00e8s, B., Ben Dor, E., Brown, D.J., Clairotte, M., and Csorba, A. (2015). Advances in Agronomy, Elsevier."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"116166","DOI":"10.1016\/j.trac.2020.116166","article-title":"Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: Recent advances\u2013A review","volume":"135","author":"Barra","year":"2021","journal-title":"TrAC Trends Anal. Chem."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Ahmadi, A., Emami, M., Daccache, A., and He, L. (2021). Soil Properties Prediction for Precision Agriculture Using Visible and Near-Infrared Spectroscopy: A Systematic Review and Meta-Analysis. Agronomy, 11.","DOI":"10.3390\/agronomy11030433"},{"key":"ref_5","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_6","doi-asserted-by":"crossref","first-page":"e13271","DOI":"10.1111\/ejss.13271","article-title":"Diffuse reflectance spectroscopy for estimating soil properties: A technology for the 21st century","volume":"73","author":"Behrens","year":"2022","journal-title":"Eur. J. Soil Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"364","DOI":"10.2136\/sssaj1995.03615995005900020014x","article-title":"Near-infrared analysis as a rapid method to simultaneously evaluate several soil properties","volume":"59","author":"Banin","year":"1995","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.geoderma.2013.09.021","article-title":"Best practices for obtaining and processing field visible and near infrared (VNIR) spectra of topsoils","volume":"214\u2013215","author":"Gras","year":"2014","journal-title":"Geoderma"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.geoderma.2015.07.007","article-title":"Prediction of soil organic carbon stock using visible and near infrared reflectance spectroscopy (VNIRS) in the field","volume":"261","author":"Cambou","year":"2016","journal-title":"Geoderma"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"108350","DOI":"10.1016\/j.compag.2023.108350","article-title":"Estimation of soil organic matter by in situ Vis-NIR spectroscopy using an automatically optimized hybrid model of convolutional neural network and long short-term memory network","volume":"214","author":"Wang","year":"2023","journal-title":"Comput. Electron. Agric."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"993","DOI":"10.2136\/sssaj2016.08.0253","article-title":"Depth-Specific Prediction of Soil Properties In Situ using vis-NIR Spectroscopy","volume":"81","author":"Zhang","year":"2017","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"e12952","DOI":"10.1111\/sum.12952","article-title":"The use of visible and near-infrared spectroscopy for in situ characterization of agricultural soil fertility: A proposition of best practice by comparing scanning positions and spectrometers","volume":"40","author":"Metzger","year":"2024","journal-title":"Soil Use Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1080\/05704928.2022.2128365","article-title":"Mathematical techniques to remove moisture effects from visible\u2013near-infrared\u2013shortwave-infrared soil spectra\u2014Rev","volume":"58","author":"Knadel","year":"2022","journal-title":"Spectrosc. Rev."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0065-2113(02)75005-0","article-title":"Quantitative remote sensing of soil properties","volume":"Volume 75","year":"2002","journal-title":"Advances in Agronomy"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.geoderma.2011.09.008","article-title":"Removing the effect of soil moisture from NIR diffuse reflectance spectra for the prediction of soil organic carbon","volume":"167\u2013168","author":"Minasny","year":"2011","journal-title":"Geoderma"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.compag.2009.10.006","article-title":"On-the-go VisNIR: Potential and limitations for mapping soil clay and organic carbon","volume":"70","author":"Bricklemyer","year":"2010","journal-title":"Comput. Electron. Agric."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.biosystemseng.2022.10.011","article-title":"Assessing a VisNIR penetrometer system for in-situ estimation of soil organic carbon under variable soil moisture conditions","volume":"224","author":"Murad","year":"2022","journal-title":"Biosyst. Eng."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Ji, W., Zhou, S., Jingyi, H., and Shuo, L. (2014). In situ measurement of some soil properties in paddy soil using visible and near-infrared spectroscopy. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0105708"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Yin, J., Shi, Z., Li, B., Sun, F., Miao, T., Shi, Z., Chen, S., Yang, M., and Ji, W. (2023). Prediction of Soil Properties in a Field in Typical Black Soil Areas Using in situ MIR Spectra and Its Comparison with vis-NIR Spectra. Remote Sens., 15.","DOI":"10.3390\/rs15082053"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"113900","DOI":"10.1016\/j.geoderma.2019.113900","article-title":"In situ and laboratory soil spectroscopy with portable visible-to-near-infrared and mid-infrared instruments for the assessment of organic carbon in soils","volume":"355","author":"Hutengs","year":"2019","journal-title":"Geoderma"},{"key":"ref_21","unstructured":"Safanelli, J.L., Hengl, T., Sanderman, J., and Parente, L. (2021). Open Soil Spectral Library (Training Data and Calibration Models), Zenodo."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.earscirev.2016.01.012","article-title":"A global spectral library to characterize the world\u2019s soil","volume":"155","author":"Behrens","year":"2016","journal-title":"Earth-Sci. Rev."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Clingensmith, C.M., and Grunwald, S. (2022). Predicting Soil Properties and Interpreting Vis-NIR Models from across Continental United States. Sensors, 22.","DOI":"10.3390\/s22093187"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4155390","DOI":"10.1155\/2023\/4155390","article-title":"A Spectral Transfer Function to Harmonize Existing Soil Spectral Libraries Generated by Different Protocols","volume":"2023","author":"Francos","year":"2023","journal-title":"Appl. Environ. Soil Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/S0169-7439(03)00051-0","article-title":"EPO\u2013PLS external parameter orthogonalisation of PLS application to temperature-independent measurement of sugar content of intact fruits","volume":"66","author":"Roger","year":"2003","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Wadoux, A.M.J.-C., Malone, B., Minasny, B., Fajardo, M., and McBratney, A.B. (2021). Soil Spectral Inference with R: Analysing Digital Soil Spectra Using the R Programming Environment, Springer International Publishing.","DOI":"10.1007\/978-3-030-64896-1"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.geoderma.2015.06.002","article-title":"Predicting clay content on field-moist intact tropical soils using a dried, ground VisNIR library with external parameter orthogonalization","volume":"259\u2013260","author":"Ackerson","year":"2015","journal-title":"Geoderma"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.geoderma.2018.09.015","article-title":"External parameter orthogonalisation of Eastern European VisNIR-DRS soil spectra","volume":"337","author":"Chakraborty","year":"2019","journal-title":"Geoderma"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Veum, K.S., Parker, P.A., Sudduth, K.A., and Holan, S.H. (2018). Predicting Profile Soil Properties with Reflectance Spectra via Bayesian Covariate-Assisted External Parameter Orthogonalization. Sensors, 18.","DOI":"10.3390\/s18113869"},{"key":"ref_30","unstructured":"(2024, May 02). NF ISO 14235. Available online: https:\/\/www.boutique.afnor.org\/fr-fr\/norme\/nf-iso-14235\/qualite-du-sol-dosage-du-carbone-organique-par-oxydation-sulfochromique\/fa040485\/14434."},{"key":"ref_31","unstructured":"(2024, May 02). NF ISO 13878. Available online: https:\/\/www.boutique.afnor.org\/en-gb\/standard\/nf-iso-13878\/soil-quality-determination-of-total-nitrogen-content-by-dry-combustion-elem\/fa040644\/14435."},{"key":"ref_32","unstructured":"Gee, G.W., and Bauder, J.W. (1986). Methods of Soil Analysis, American Society of Agronomy."},{"key":"ref_33","first-page":"112","article-title":"Reflectance measurements of soils in the laboratory: Standards and protocols","volume":"245\u2013246","author":"Ong","year":"2015","journal-title":"Geoderma"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Karyotis, K., Chabrillat, S., and Dor, E.B. (2023, January 16\u201321). P4005: The IEEE SA Standard and Protocol Scheme for Soil Spectral Measurement in Both Laboratory and Field. Proceedings of the IGARSS 2023\u20132023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA.","DOI":"10.1109\/IGARSS52108.2023.10282263"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"114171","DOI":"10.1016\/j.geoderma.2020.114171","article-title":"Mid-infrared spectroscopy as an alternative to laboratory extraction for the determination of lime requirement in tillage soils","volume":"364","author":"Metzger","year":"2020","journal-title":"Geoderma"},{"key":"ref_36","unstructured":"Stevens, A., and Ramirez-Lopez, L. (2024, May 02). An Introduction to the Prospectr Package. Available online: https:\/\/cran.r-project.org\/web\/packages\/prospectr\/vignettes\/prospectr.html."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and differentiation of data by simplified least squares procedures","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1366\/0003702894202201","article-title":"Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra","volume":"43","author":"Barnes","year":"1989","journal-title":"Appl. Spectrosc."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Wadoux, A.M.J.-C., Malone, B., Minasny, B., Fajardo, M., and McBratney, A.B. (2021). Soil Spectral Inference with R: Analysing Digital Soil Spectra using the R Programming Environment, Springer International Publishing.","DOI":"10.1007\/978-3-030-64896-1"},{"key":"ref_40","unstructured":"R Core Team (2023). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. 4.3.2."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Wadoux, A.M.J.C., Malone, B., Minasny, B., Fajardo, P.M., and McBratney, A. (2021). Soil Spectral Inference with R, Springer.","DOI":"10.1007\/978-3-030-64896-1"},{"key":"ref_42","unstructured":"Esbensen, K.H., and Swarbrick, B. (2018). Multivariate Data Analysis: An Introduction to Multivariate Analysis, Process Analytical Technology and Quality by Design, Camo. [6th ed.]."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1002\/cem.1225","article-title":"Repeated double cross validation","volume":"23","author":"Filzmoser","year":"2009","journal-title":"J. Chemom."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Varmuza, K., and Filzmoser, P. (2016). Introduction to Multivariate Statistical Analysis in Chemometrics, CRC Press.","DOI":"10.1201\/9781420059496"},{"key":"ref_45","unstructured":"Filzmoser, P., and Varmuza, K. (2024, May 02). Chemometrics: Multivariate Statistical Analysis in Chemometrics. Available online: https:\/\/cran.r-project.org\/web\/packages\/chemometrics\/index.html."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1016\/j.trac.2010.05.006","article-title":"Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy","volume":"29","author":"Palagos","year":"2010","journal-title":"TrAC Trends Anal. Chem."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1198\/016214502753479392","article-title":"Statistical methods in assessing agreement: Models, issues, and tools","volume":"97","author":"Lin","year":"2002","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_48","first-page":"139","article-title":"The Performance of Visible, Near-, and Mid-Infrared Reflectance Spectroscopy for Prediction of Soil Physical, Chemical, and Biological Properties","volume":"49","author":"Janik","year":"2013","journal-title":"Appl. Spectrosc. Rev."},{"key":"ref_49","unstructured":"Stenberg, B., Viscarra Rossel, R.A., Mouazen, A.M., and Wetterlind, J. (2010). Advances in Agronomy, Academic Press."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1542","DOI":"10.2136\/sssaj2018.11.0413","article-title":"Accuracy of Estimating Soil Properties with Mid-Infrared Spectroscopy: Implications of Different Chemometric Approaches and Software Packages Related to Calibration Sample Size","volume":"83","author":"Ludwig","year":"2019","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"100024","DOI":"10.1016\/j.soisec.2021.100024","article-title":"Comparison of soil organic carbon stocks predicted using visible and near infrared reflectance (VNIR) spectra acquired in situ vs. on sieved dried samples: Synthesis of different studies","volume":"5","author":"Cambou","year":"2021","journal-title":"Soil Secur."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"105196","DOI":"10.1016\/j.still.2021.105196","article-title":"Comparing the effect of different sample conditions and spectral libraries on the prediction accuracy of soil properties from near- and mid-infrared spectra at the field-scale","volume":"215","author":"Breure","year":"2022","journal-title":"Soil Tillage Res"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"722","DOI":"10.2136\/sssaj2002.7220","article-title":"Moisture Effects on Soil Reflectance","volume":"66","author":"Lobell","year":"2002","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.geoderma.2014.01.011","article-title":"VisNIR spectra of dried ground soils predict properties of soils scanned moist and intact","volume":"221\u2013222","author":"Ge","year":"2014","journal-title":"Geoderma"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"115877","DOI":"10.1016\/j.geoderma.2022.115877","article-title":"Developing a generalized vis-NIR prediction model of soil moisture content using external parameter orthogonalization to reduce the effect of soil type","volume":"419","author":"Liu","year":"2022","journal-title":"Geoderma"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"480","DOI":"10.2136\/sssaj2001.652480x","article-title":"Near-infrared reflectance spectroscopy\u2013principal components regression analyses of soil properties","volume":"65","author":"Chang","year":"2001","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"105225","DOI":"10.1016\/j.still.2021.105225","article-title":"Minimising the effect of moisture on soil property prediction accuracy using external parameter orthogonalization","volume":"215","author":"Mirzaei","year":"2022","journal-title":"Soil Tillage Res."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/11\/3556\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:51:50Z","timestamp":1760107910000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/11\/3556"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,31]]},"references-count":57,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["s24113556"],"URL":"https:\/\/doi.org\/10.3390\/s24113556","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,31]]}}}