{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T06:18:51Z","timestamp":1774505931238,"version":"3.50.1"},"reference-count":105,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,11,24]],"date-time":"2021-11-24T00:00:00Z","timestamp":1637712000000},"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>Quantifying the organic carbon content of soil over large areas is essential for characterising the soil and the effects of its management. However, analytical methods can be laborious and costly. Reflectance spectroscopy is a well-established and widespread method for estimating the chemical-element content of soils. The aim of this study was to estimate the soil organic carbon (SOC) content using hyperspectral remote sensing. The data were from soils from two localities in the semi-arid region of Brazil. The spectral reflectance factors of the collected soil samples were recorded at wavelengths ranging from 350\u20132500 nm. Pre-processing techniques were employed, including normalisation, Savitzky\u2013Golay smoothing and first-order derivative analysis. The data (n = 65) were examined both jointly and by soil class, and subdivided into calibration and validation to independently assess the performance of the linear methods. Two multivariate models were calibrated using the SOC content estimated in the laboratory by principal component regression (PCR) and partial least squares regression (PLSR). The study showed significant success in predicting the SOC with transformed and untransformed data, yielding acceptable-to-excellent predictions (with the performance-to-deviation ratio ranging from 1.40\u20133.38). In general, the spectral reflectance factors of the soils decreased with the increasing levels of SOC. PLSR was considered more robust than PCR, whose wavelengths from 354 to 380 nm, 1685, 1718, 1757, 1840, 1876, 1880, 2018, 2037, 2042, and 2057 nm showed outstanding absorption characteristics between the predicted models. The results found here are of significant practical value for estimating SOC in Neosols and Cambisols in the semi-arid region of Brazil using VIS-NIR-SWIR spectroscopy.<\/jats:p>","DOI":"10.3390\/rs13234752","type":"journal-article","created":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T01:45:02Z","timestamp":1638323102000},"page":"4752","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Soil Organic Carbon Content Prediction Using Soil-Reflected Spectra: A Comparison of Two Regression Methods"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3099-550X","authenticated-orcid":false,"given":"Sharon Gomes","family":"Ribeiro","sequence":"first","affiliation":[{"name":"Soil Science Graduate Program, Federal University of Ceara, Fortaleza 60455-760, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1480-0944","authenticated-orcid":false,"given":"Adunias dos Santos","family":"Teixeira","sequence":"additional","affiliation":[{"name":"Department of Agricultural Engineering, Federal University of Ceara,  Fortaleza 60455-760, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1150-1498","authenticated-orcid":false,"given":"Marcio Regys Rabelo","family":"de Oliveira","sequence":"additional","affiliation":[{"name":"Agricultural Engineering Graduate Program, Federal University of Ceara, Fortaleza 60455-760, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4682-4756","authenticated-orcid":false,"given":"Mirian Cristina Gomes","family":"Costa","sequence":"additional","affiliation":[{"name":"Department of Soil Science, Federal University of Ceara, Fortaleza 60455-760, Brazil"}]},{"given":"Isabel Cristina da Silva","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"Department of Agricultural Engineering, Federal University of Ceara,  Fortaleza 60455-760, Brazil"}]},{"given":"Luis Clenio Jario","family":"Moreira","sequence":"additional","affiliation":[{"name":"Department of Agronomy, Federal Institute of Education, Science and Technology of Ceara, Limoeiro do Norte 62930-000, Brazil"}]},{"given":"Fernando Bezerra","family":"Lopes","sequence":"additional","affiliation":[{"name":"Department of Agricultural Engineering, Federal University of Ceara,  Fortaleza 60455-760, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1945","DOI":"10.2136\/sssaj2004.1945","article-title":"The Soil Management Assessment Framework: A Quantitative Soil Quality Evaluation Method","volume":"68","author":"Andrews","year":"2004","journal-title":"Soil Sci. 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