{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T05:02:44Z","timestamp":1768712564052,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,7,22]],"date-time":"2022-07-22T00:00:00Z","timestamp":1658448000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Continuous monitoring of soil quality is a challenging task in agricultural activity. To meet this need, scientists have succeeded in developing a quick and inexpensive method to characterize soil properties. Thus, spectroscopy has become a promising method for quantifying soil parameters. However, this method remains sensitive to several factors such as water content (WC). The present study aims to quantify the effect of WC on the estimation of soil texture parameters (sand, silt, and clay) and organic matter (OM) using spectroscopy. Reflectance measurements in the laboratory on 68 soil samples were performed by varying the WC in each sample. The analysis revealed a significant influence of WC on spectra acquired from visible to near infrared (V\/NIR) spectroscopy data and that spectra can be divided into two classes. To quantify the effect of WC, calibration\/validation steps were performed on soil texture parameters and OM with and without taking WC into account. Calibration was performed using the partial least square regression algorithm, and the validation was assessed using four statistical evaluation indices (R2, Nash criterion (Nash), root-mean-square error (RMSE), and BIAS). Results showed a systematic increase in the accuracy of all studied soil particles when the WC is considered. Clay and OM were less influenced, while silt and sand were much more influenced by the WC. The study also highlighted that estimates of soil texture parameters using V\/NIR data achieved relatively higher levels of accuracy (R2 &gt; 0.80 and Nash &gt; 0.80) than OM estimation (R2 = 0.83 and Nash = 0.78).<\/jats:p>","DOI":"10.3390\/rs14153510","type":"journal-article","created":{"date-parts":[[2022,7,25]],"date-time":"2022-07-25T01:42:13Z","timestamp":1658713333000},"page":"3510","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Quantitative Study of the Effect of Water Content on Soil Texture Parameters and Organic Matter Using Proximal Visible\u2014Near Infrared Spectroscopy"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8570-2110","authenticated-orcid":false,"given":"Anas","family":"El Alem","sequence":"first","affiliation":[{"name":"Eau Terre Environnement, INRS, 490 rue de la Couronne, Quebec City, QC G1K 9A9, Canada"}]},{"given":"Amal","family":"Hmaissia","sequence":"additional","affiliation":[{"name":"BioEngine Research Team on Green Process Engineering and Biorefineries, Chemical Engineering Department, Universit\u00e9 Laval, Pavillon Adrien-Pouliot 1065, av. de la M\u00e9decine, Quebec City, QC G1V 0A6, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0018-0761","authenticated-orcid":false,"given":"Karem","family":"Chokmani","sequence":"additional","affiliation":[{"name":"BioEngine Research Team on Green Process Engineering and Biorefineries, Chemical Engineering Department, Universit\u00e9 Laval, Pavillon Adrien-Pouliot 1065, av. de la M\u00e9decine, Quebec City, QC G1V 0A6, Canada"}]},{"given":"Athyna N.","family":"Cambouris","sequence":"additional","affiliation":[{"name":"Agriculture and Agri-Food Canada, Quebec Research and Development Centre, Quebec City, QC G1V 2J3, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,22]]},"reference":[{"key":"ref_1","unstructured":"Brabant, P. (2022, May 15). Activit\u00e9s Humaines et D\u00e9gradation des Terres. Collection Atlas C\u00e9d\u00e9roms. Indicateurs et M\u00e9thodes, Available online: www.cartographie.ird.fr\/degra_PB.html."},{"key":"ref_2","unstructured":"Phogat, V., Tomar, V., and Dahiya, R. (2015). Soil physical properties. Soil Science: An Introduction, Indian Society of Soil Science."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"114553","DOI":"10.1016\/j.geoderma.2020.114553","article-title":"Soil texture prediction using portable X-ray fluorescence spectrometry and visible near-infrared diffuse reflectance spectroscopy","volume":"376","author":"Benedet","year":"2020","journal-title":"Geoderma"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Ball, D.W. (2006). Field Guide to Spectroscopy, SPIE Press.","DOI":"10.1117\/3.682726"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Pinheiro, \u00c9.F., Ceddia, M.B., Clingensmith, C.M., Grunwald, S., and Vasques, G.M. (2017). Prediction of soil physical and chemical properties by visible and near-infrared diffuse reflectance spectroscopy in the central Amazon. Remote Sens., 9.","DOI":"10.3390\/rs9040293"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"751","DOI":"10.2134\/jeq2010.0169","article-title":"Spectroscopic approaches for phosphorus speciation in soils and other environmental systems","volume":"40","author":"Kizewski","year":"2011","journal-title":"J. Environ. Qual."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/j.jaridenv.2007.01.004","article-title":"Applying a field spectroscopy technique for assessing successional trends of biological soil crusts in a semi-arid environment","volume":"70","author":"Zaady","year":"2007","journal-title":"J. Arid. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"758","DOI":"10.2136\/sssaj2017.02.0066","article-title":"Complete soil texture is accurately predicted by visible near-infrared spectroscopy","volume":"81","author":"Hermansen","year":"2017","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1016\/j.geoderma.2018.10.038","article-title":"Near infrared spectroscopy as an easy and precise method to estimate soil texture","volume":"337","author":"Jaconi","year":"2019","journal-title":"Geoderma"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.geoderma.2015.09.018","article-title":"Laser-induced breakdown spectroscopy to determine soil texture: A fast analytical technique","volume":"263","author":"Romano","year":"2016","journal-title":"Geoderma"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1071\/SR07099","article-title":"Using a legacy soil sample to develop a mid-IR spectral library","volume":"46","author":"Rossel","year":"2008","journal-title":"Soil Res."},{"key":"ref_12","unstructured":"Bach, H., and Mauser, W. (1994, January 8\u201312). Modelling and model verification of the spectral reflectance of soils under varying moisture conditions. Proceedings of the IGARSS\u201994-1994 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1111\/j.1365-2389.2010.01305.x","article-title":"Modelling moisture-induced soil reflectance changes in cultivated sandy soils: A case study in citrus orchards","volume":"61","author":"Somers","year":"2010","journal-title":"Eur. J. Soil Sci."},{"key":"ref_14","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","author":"Minasny","year":"2011","journal-title":"Geoderma"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1111\/ejss.12239","article-title":"Accounting for the effects of water and the environment on proximally sensed vis\u2013NIR soil spectra and their calibrations","volume":"66","author":"Ji","year":"2015","journal-title":"Eur. J. Soil Sci."},{"key":"ref_16","unstructured":"Group, S.C.W. (1998). The Canadian System of Soil Classification."},{"key":"ref_17","first-page":"713","article-title":"Particle size distribution","volume":"2","author":"Kroetsch","year":"2008","journal-title":"Soil Sampl. Methods Anal."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.measurement.2014.04.007","article-title":"A critical review of soil moisture measurement","volume":"54","author":"Lekshmi","year":"2014","journal-title":"Measurement"},{"key":"ref_19","unstructured":"MacQueen, J. (1967, January 1). Some methods for classification and analysis of multivariate observations. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Davis, CA, USA."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Jolliffe, I. (2005). Principal component analysis. Encyclopedia of Statistics in Behavioral Science, John Wiley & Sons, Ltd.","DOI":"10.1002\/0470013192.bsa501"},{"key":"ref_21","unstructured":"Breiman, L., Friedman, J., Stone, C.J., and Olshen, R.A. (1984). Classification and Regression Trees, CRC Press."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1449","DOI":"10.1007\/s10661-011-2053-3","article-title":"Retrieval of total suspended matter (TSM) and chlorophyll-a (Chl-a) concentration from remote-sensing data for drinking water resources","volume":"184","author":"Song","year":"2012","journal-title":"Environ. Monit. Assess."},{"key":"ref_23","unstructured":"Wold, H. (1966). Estimation of principal components and related models by iterative least squares. Multivar. Anal., 391\u2013420."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/S0169-7439(01)00155-1","article-title":"PLS-regression: A basic tool of chemometrics","volume":"58","author":"Wold","year":"2001","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Efron, B., and Tibshirani, R.J. (1994). An Introduction to the Bootstrap, CRC Press.","DOI":"10.1201\/9780429246593"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013). An Introduction to Statistical Learning, Springer.","DOI":"10.1007\/978-1-4614-7138-7"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/0022-1694(70)90255-6","article-title":"River flow forecasting through conceptual models part I\u2014A discussion of principles","volume":"10","author":"Nash","year":"1970","journal-title":"J. Hydrol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1190\/1.1440721","article-title":"Spectral signatures of particulate minerals in the visible and near infrared","volume":"42","author":"Hunt","year":"1977","journal-title":"Geophysics"},{"key":"ref_29","first-page":"9","article-title":"A Study of Effects of MultiCollinearity in the Multivariable Analysis","volume":"4","author":"Yoo","year":"2014","journal-title":"Int. J. Appl. Sci. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.iswcr.2020.04.005","article-title":"The application of proximal visible and near-infrared spectroscopy to estimate soil organic matter on the Triffa Plain of Morocco","volume":"8","author":"Lazaar","year":"2020","journal-title":"Int. Soil Water Conserv. Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/15\/3510\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:54:43Z","timestamp":1760140483000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/15\/3510"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,22]]},"references-count":30,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["rs14153510"],"URL":"https:\/\/doi.org\/10.3390\/rs14153510","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,22]]}}}