{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T06:10:44Z","timestamp":1767852644801,"version":"3.49.0"},"reference-count":63,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T00:00:00Z","timestamp":1694044800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Minas Gerais State","award":["08\/2021"],"award-info":[{"award-number":["08\/2021"]}]},{"name":"University of Minas Gerais State","award":["1610132023003"],"award-info":[{"award-number":["1610132023003"]}]},{"name":"UEMG productivity researcher\u2014PQ\/UEMG","award":["08\/2021"],"award-info":[{"award-number":["08\/2021"]}]},{"name":"UEMG productivity researcher\u2014PQ\/UEMG","award":["1610132023003"],"award-info":[{"award-number":["1610132023003"]}]},{"name":"Fundamental Research Funds for Central Non-profit Scientific Institution","award":["08\/2021"],"award-info":[{"award-number":["08\/2021"]}]},{"name":"Fundamental Research Funds for Central Non-profit Scientific Institution","award":["1610132023003"],"award-info":[{"award-number":["1610132023003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The quantification of soil organic matter (SOM) has increased over the years, especially in the Brazilian Cerrado region, one of the most important areas for grain production in the country. In this area, SOM content tends to be low, which directly impacts the physical, chemical and biological quality of soils. Thus, the use of spectroradiometry has been widely evaluated to investigate whether it can be used as a faster, more reliable and cheaper solution to meet the SOM estimation. In this context, the objective of the present paper was to evaluate the performance of a local spectral model for SOM prediction generated through the spiking strategy. The research was developed in the municipality of Passos, Minas Gerais State, located in the Brazilian Cerrado. Soil samples (0\u20130.2 m and 0.2\u20130.4 m depths) were collected in a zigzag pattern and split in calibration of the local models from a test area (90 soil samples) and recalibration and validation from a target area (46 soil samples). After this stage, the SOM contents were determined in a laboratory, and the spectral responses (350\u20132500 nm) of each soil sample were collected. From the target area, 10, 25 and 50% of soil spectra were selected for recalibration of the local models generated for the test area. Although median results were observed in the post-recalibration, due to the type of sample selected and the relative similarity among the spectral curves of both areas, improvement was observed for all statistical indices, especially when using 50% (23) of samples for recalibration of the local models, reaching r2 = 0.43, RMSEP = 2.34 gdm\u22123 and RPIQ = 4.58. These results are important for the SOM estimation in the Brazilian Cerrado considering its importance to the food security and socioeconomic activities. However, considering the lack of similar research in the study area, it is necessary to further investigate the development of spectral models on a local scale and their contribution to improve the identification of SOM spatial variability.<\/jats:p>","DOI":"10.3390\/rs15184397","type":"journal-article","created":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T10:09:50Z","timestamp":1694081390000},"page":"4397","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Estimating Soil Organic Matter (SOM) Using Proximal Remote Sensing: Performance Evaluation of Prediction Models Adjusted at Local Scale in the Brazilian Cerrado"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8042-090X","authenticated-orcid":false,"given":"Everson","family":"Cezar","sequence":"first","affiliation":[{"name":"Department of Agricultural and Earth Sciences, University of Minas Gerais State, Passos 37902-108, MG, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tatiane Amancio","family":"Alberton","sequence":"additional","affiliation":[{"name":"Remote Sensing and Geoprocessing Laboratory, Agronomy Department, State University of Maring\u00e1, Maring\u00e1 87020-900, PR, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evandro Freire","family":"Lemos","sequence":"additional","affiliation":[{"name":"Department of Agricultural and Earth Sciences, University of Minas Gerais State, Passos 37902-108, MG, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1880-4256","authenticated-orcid":false,"given":"Karym Mayara","family":"de Oliveira","sequence":"additional","affiliation":[{"name":"Remote Sensing and Geoprocessing Laboratory, Agronomy Department, State University of Maring\u00e1, Maring\u00e1 87020-900, PR, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2631-8909","authenticated-orcid":false,"given":"Liang","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu\u00eds Guilherme Teixeira","family":"Crusiol","sequence":"additional","affiliation":[{"name":"Embrapa Soja (National Soybean Research Centre\u2013Brazilian Agricultural Research Corporation), Londrina 86001-970, PR, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7661-9166","authenticated-orcid":false,"given":"Marlon","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Federal Institute of Parana, Uni\u00e3o da Vit\u00f3ria 84600-275, PR, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5006-4887","authenticated-orcid":false,"given":"Amanda Silveira","family":"Reis","sequence":"additional","affiliation":[{"name":"Remote Sensing and Geoprocessing Laboratory, Agronomy Department, State University of Maring\u00e1, Maring\u00e1 87020-900, PR, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4854-2661","authenticated-orcid":false,"given":"Marcos Rafael","family":"Nanni","sequence":"additional","affiliation":[{"name":"Remote Sensing and Geoprocessing Laboratory, Agronomy Department, State University of Maring\u00e1, Maring\u00e1 87020-900, PR, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.1365-2389.2010.01338.x","article-title":"Soil organic matters","volume":"62","author":"Powlson","year":"2011","journal-title":"Eur. J. Soil Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.talanta.2016.05.076","article-title":"Application of FTIR-PAS and Raman spectroscopies for the determination of organic matter in farmland soils","volume":"158","author":"Xing","year":"2016","journal-title":"Talanta"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.1016\/j.scitotenv.2018.06.319","article-title":"Rapid identification of soil organic matter level via visible and near-infrared spectroscopy: Effects of two-dimensional correlation coefficient and extreme learning machine","volume":"644","author":"Hong","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1366\/13-07288","article-title":"Visible, Near-Infrared, and Mid-Infrared Spectroscopy Applications for Soil Assessment with Emphasis on Soil Organic Matter Content and Quality: State-of-the-Art and Key Issues","volume":"67","author":"Gholizadeh","year":"2013","journal-title":"Appl. Spectrosc."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1097\/SS.0000000000000132","article-title":"Selection of \u201clocal\u201d models for prediction of soil organic matter using a regional soil Vis-NIR spectral library","volume":"181","author":"Zeng","year":"2016","journal-title":"Soil Sci."},{"key":"ref_6","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."},{"key":"ref_7","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_8","doi-asserted-by":"crossref","first-page":"4305","DOI":"10.3390\/rs6054305","article-title":"Transferability of a Visible and Near-Infrared Model for Soil Organic Matter Estimation in Riparian Landscapes","volume":"6","author":"Liu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1423","DOI":"10.3390\/s21041423","article-title":"An Evaluation of Different NIR-Spectral Pre-Treatments to Derive the Soil Parameters C and N of a Humus-Clay-Rich Soil","volume":"21","author":"Heil","year":"2021","journal-title":"Sensors"},{"key":"ref_10","unstructured":"Meneses, P.R., and Madeira Netto, J.S. (2001). Sensoriamento Remoto\u2014Reflect\u00e2ncia dos Alvos Naturais, EMBRAPA Cerrados."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1590\/S0006-87052003000300012","article-title":"Influ\u00eancia da mat\u00e9ria org\u00e2nica e de formas de ferro na reflect\u00e2ncia de solos tropicais","volume":"62","author":"Epiphanio","year":"2003","journal-title":"Bragantia"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1590\/S0103-84782005000200042","article-title":"Rela\u00e7\u00e3o entre os constituintes do solo e seu comportamento espectral","volume":"35","author":"Dalmolin","year":"2005","journal-title":"Cienc. Rural"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"13","DOI":"10.2478\/v10117-010-0002-9","article-title":"Influence of several soil properties on soil surface reflectance","volume":"29","author":"Cierniewski","year":"2010","journal-title":"Quaest. Geogr."},{"key":"ref_14","first-page":"413","article-title":"Effects of organic matter on the multispectral properties of soils","volume":"79","author":"Baumgardner","year":"1970","journal-title":"Soil Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"421","DOI":"10.2136\/sssaj1973.03615995003700030031x","article-title":"Spectral reflectance of selected Pennsylvania soils","volume":"37","author":"Matews","year":"1973","journal-title":"Soil Sci. Soc. Am. Proc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1282","DOI":"10.2136\/sssaj1980.03615995004400060030x","article-title":"Reflectance technique for predicting soil organic matter","volume":"44","author":"Krishman","year":"1980","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_17","first-page":"1","article-title":"Hyperspectral remote detection as an alternative to correlate data of soil constituents","volume":"16","author":"Chicati","year":"2019","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1782","DOI":"10.3390\/rs13091782","article-title":"Mapping Particle Size and Soil Organic Matter in Tropical Soil Based on Hyperspectral Imaging and Non-Imaging Sensors","volume":"13","author":"Nanni","year":"2021","journal-title":"Remote Sens."},{"key":"ref_19","first-page":"100492","article-title":"Detection of soil organic matter using hyperspectral imaging sensor combined with multivariate regression modeling procedures","volume":"22","author":"Reis","year":"2021","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1376","DOI":"10.3390\/rs13071376","article-title":"Strategies for the Development of Spectral Models for Soil Organic Matter Estimation","volume":"13","author":"Cezar","year":"2021","journal-title":"Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1111\/ejss.12129","article-title":"Assessment of soil organic carbon at local scale with spiked NIR calibrations: Effects of selection and extra-weighting on the spiking subset","volume":"65","author":"Guerrero","year":"2014","journal-title":"Eur. J. Soil Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1080\/00387010.2017.1297958","article-title":"Hyperspectral estimation of soil organic matter based on different spectral preprocessing techniques","volume":"50","author":"Qiao","year":"2017","journal-title":"Spectrosc. Lett."},{"key":"ref_23","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_24","doi-asserted-by":"crossref","first-page":"848","DOI":"10.1111\/j.1365-2389.2012.01495.x","article-title":"Predicting soil properties from the Australian soil visible\u2013near infrared spectroscopic database","volume":"63","author":"Webster","year":"2012","journal-title":"Eur. J. Soil. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1111\/ejss.12165","article-title":"Improving the prediction performance of a large tropical vis-NIR spectroscopic soil library from Brazil by clustering into smaller subsets or use of data mining calibration techniques","volume":"65","author":"Wetterlind","year":"2014","journal-title":"Eur. J. Soil Sci."},{"key":"ref_26","first-page":"589","article-title":"Spectral regionalization of tropical soils in the estimation of soil attributes","volume":"47","author":"Bellinaso","year":"2016","journal-title":"Rev. Ci\u00eanc. Agron."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"113856","DOI":"10.1016\/j.geoderma.2019.07.014","article-title":"Strategies for the efficient estimation of soil organic carbon at the field scale with vis-NIR spectroscopy: Spectral libraries and spiking vs. local calibrations","volume":"354","author":"Seidel","year":"2019","journal-title":"Geoderma"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1111\/ejss.12272","article-title":"Prediction of soil organic matter using a spatially constrained local partial least squares regression and the Chinese vis\u2013NIR spectral library","volume":"66","author":"Shi","year":"2015","journal-title":"Eur. J. Soil Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.geoderma.2010.02.012","article-title":"Increased sample point density in farm soil mapping by local calibration of visible and near infrared prediction models","volume":"156","author":"Wetterlind","year":"2010","journal-title":"Geoderma"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.geoderma.2009.12.021","article-title":"Spiking of NIR regional models using simples from target sites: Effect of model size on prediction accuracy","volume":"158","author":"Guerrero","year":"2010","journal-title":"Geoderma"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e023920","DOI":"10.1590\/1413-7054202145023920","article-title":"Air temperature estimation techniques in Minas Gerais state, Brazil, Cwa and Cwb climate regions according to the K\u00f6ppen-Geiger climate classification system","volume":"45","author":"Monti","year":"2021","journal-title":"Cienc. Agrotecnol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"304","DOI":"10.20873\/jbb.uft.cemaf.v7n2.ferreira","article-title":"Classifica\u00e7\u00e3o clim\u00e1tica para o estado de Minas Gerais segundo as zonas de vida de Holdridge","volume":"7","author":"Ferreira","year":"2019","journal-title":"J. Biotechnol. Biodivers."},{"key":"ref_33","unstructured":"CPRM (2006). Mapa Geodiversidades do Brasil: Escala 1:2,500,000: Legenda Expandida."},{"key":"ref_34","unstructured":"World Reference Base for Soil Resources (2014). International Soil Classification System for Naming Soils and Creating Legends for Soil Maps, FAO. [3rd ed.]."},{"key":"ref_35","unstructured":"Instituto Agron\u00f4mico de Campinas IAC (2009). M\u00e9todos de An\u00e1lise Qu\u00edmica, Mineral\u00f3gica e F\u00edsica de Solos do Instituto Agron\u00f4mico de Campinas, Boletim 106."},{"key":"ref_36","unstructured":"Empresa Brasileira de Pesquisa Agropecu\u00e1ria\u2014EMBRAPA (2017). Manual de M\u00e9todos de An\u00e1lise de Solo, Embrapa. [3rd ed.]. Revista e Ampliada."},{"key":"ref_37","unstructured":"Labsphere, Inc. (1996). Reflectance Calibration Laboratory. Handling Guidelines, Labsphere, Inc. Reflectance Calibration Laboratory."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2400","DOI":"10.1080\/00103624.2022.2071926","article-title":"Relationship Between Vegetation Indices, Nutrients Content, and the Biomass Production of Brachiaria (Brachiaria ruziziensis)","volume":"53","author":"Rodrigues","year":"2022","journal-title":"Commun. Soil Sci. Plan."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"682","DOI":"10.1080\/03650340.2017.1373185","article-title":"Partial least squares regression (PLSR) associated with spectral response to predict soil attributes in transitional lithologies","volume":"64","author":"Nanni","year":"2017","journal-title":"Arch. Agron. Soil Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"e00558","DOI":"10.1016\/j.geodrs.2022.e00558","article-title":"Evaluation of Vis-NIR preprocessing combined with PLS regression for estimation soil organic carbon, cation exchange capacity and clay from eastern Croatia","volume":"30","author":"Milos","year":"2022","journal-title":"Geoderma Reg."},{"key":"ref_41","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_42","doi-asserted-by":"crossref","first-page":"115263","DOI":"10.1016\/j.geoderma.2021.115263","article-title":"A regional-scale hyperspectral prediction model of soil organic carbon considering geomorphic features","volume":"403","author":"Bao","year":"2021","journal-title":"Geoderma"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.indcrop.2016.07.008","article-title":"Methods for estimating leaf nitrogen concentration of winter oilseed rape (Brassica napus L.) using in situ leaf spectroscopy","volume":"91","author":"Li","year":"2016","journal-title":"Ind. Crops Prod."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"637","DOI":"10.2136\/sssaj2014.09.0390","article-title":"Estimating a soil quality index with VNIR reflectance spectroscopy","volume":"2","author":"Veum","year":"2015","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1368","DOI":"10.3390\/rs14061368","article-title":"Estimating Forest Soil Properties for Humus Assessment\u2014Is Vis-NIR the Way to Go?","volume":"14","author":"Thomas","year":"2022","journal-title":"Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.geoderma.2019.01.021","article-title":"Organic matter and sand estimates by spectroradiometry: Strategies for the development of models with applicability at a local scale","volume":"340","author":"Cezar","year":"2019","journal-title":"Geoderma"},{"key":"ref_47","unstructured":"Naes, T., Isaksson, T., Fearn, T., and Davies, T. (2004). A User-Friendly Guide to Multivariate Calibration and Classification, Nir Publication."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"237","DOI":"10.4141\/cjss-2015-004","article-title":"Spiking regional VIS-NIR calibration models with local samples to predict soil organic carbon in two High Arctic polar deserts using a Vis-NIR probe","volume":"95","author":"Guy","year":"2015","journal-title":"Can. J. Soil Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1016\/j.still.2015.07.008","article-title":"Do we really need large spectral libraries for local scale SOC assessment with NIR spectroscopy?","volume":"155","author":"Guerrero","year":"2016","journal-title":"Soil Till. Res."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.2136\/sssaj2018.03.0099","article-title":"Transferability of Vis-NIR models for Soil Organic Carbon Estimation between Two Study Areas by using Spiking","volume":"82","author":"Hong","year":"2018","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_51","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 atributes by NIR spectroscopy","volume":"29","author":"Ahumada","year":"2010","journal-title":"TrAC Trend Anal. Chem."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1590\/0103-9016-2013-0365","article-title":"Morphological Interpretation of Reflectance Spectrum (MIRS) using libraries looking towards soil classification","volume":"71","author":"Bellinaso","year":"2014","journal-title":"Sci. Agric."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"72","DOI":"10.52945\/rac.v34i1.1048","article-title":"Avan\u00e7os na observa\u00e7\u00e3o e no conhecimento do solo via o sensoriamento pr\u00f3ximo","volume":"34","author":"Dalmolin","year":"2021","journal-title":"Agropecu\u00e1ria Catarin."},{"key":"ref_54","first-page":"679","article-title":"VIS-NIR-SWIR na avalia\u00e7\u00e3o de solos ao longo de uma topossequ\u00eancia em Piracicaba (SP)","volume":"46","author":"Fiorio","year":"2015","journal-title":"Ver. Cienc. Agron."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1590\/18069657rbcs20160519","article-title":"Surface Spectroscopy of Oxisols, Entisols and Inceptisol and Relationships with Selected Soil Properties","volume":"42","author":"Poppiel","year":"2018","journal-title":"Rev. Bras. Cienc. Solo"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1080\/05704928.2019.1683569","article-title":"Evaluation of the use of spectroradiometry for the determination of soil exchangeable ions after the application of mining coproducts","volume":"55","author":"Rodrigues","year":"2019","journal-title":"Appl. Spectrosc. Rev."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.compag.2018.06.042","article-title":"Optimal sample selection for measurement of soil organic carbon using online Vis-NIR spectroscopy","volume":"151","author":"Nawar","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.geoderma.2009.12.025","article-title":"Using data mining to model and interpret soil diffuse reflectance spectra","volume":"158","author":"Behrens","year":"2010","journal-title":"Geoderma"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1002\/ldr.3250","article-title":"Soil organic matter and texture estimation from visible\u2013near infrared\u2013shortwave infrared spectra in areas of land cover changes using correlated component regression","volume":"30","author":"Vlassova","year":"2019","journal-title":"Land Degrad. Dev."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.catena.2016.12.014","article-title":"Predictive performance of mobile vis-near infrared spectroscopy for key soil properties at different geographical scales by using spiking and data mining techniques","volume":"151","author":"Nawar","year":"2017","journal-title":"Catena"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.geoderma.2012.08.035","article-title":"Distance and similarity-search metrics for use with soil vis\u2013NIR spectra","volume":"199","author":"Behrens","year":"2013","journal-title":"Geoderma"},{"key":"ref_62","first-page":"139","article-title":"Carbon sequestration rates in no-tillage soils under intensive cropping systems in tropical agroecozones","volume":"13","author":"Bouzina","year":"2006","journal-title":"Edafologia"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"15748","DOI":"10.3390\/rs71115748","article-title":"Mapping the spectral soil quality index (SSQI) using airborne imaging spectroscopy","volume":"7","author":"Zaady","year":"2015","journal-title":"Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/18\/4397\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:46:37Z","timestamp":1760129197000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/18\/4397"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,7]]},"references-count":63,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2023,9]]}},"alternative-id":["rs15184397"],"URL":"https:\/\/doi.org\/10.3390\/rs15184397","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,7]]}}}