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Visible and near-infrared spectroscopy (vis-NIR, 350\u20132500 nm) and mid-infrared spectroscopy (MIR, 2500\u201325,000 nm) have shown great potential to predict soil properties. However, there is still limited research on using MIR in situ. The aim of this study was to explore the feasibility of in situ MIR for the prediction of soil total nitrogen (TN) and total phosphorus (TP) and to compare its performance with the use of laboratory MIR, as well as the use of in situ and laboratory vis-NIR. A total of 450 samples from 90 soil profiles, along with their in situ and laboratory spectra of MIR and vis-NIR, were collected in a field with ten different tillage and management practices in a typical black soil area of Northeast China. Partial least square regression (PLSR), random forest (RF) and multivariate adaptive regression splines (MARS) were used to generate the calibrations between the spectra and the two properties. The results showed that both MIR and vis-NIR were able to predict the TN whether in laboratory or in situ conditions, but neither of them could predict the TP quantitatively since there was no sensitive band on both spectra regarding the TP. The prediction accuracy of the TN with laboratory spectra was higher than that with in situ spectra, for both vis-NIR and MIR. The optimal prediction accuracy of the TN with laboratory MIR (RMSE = 0.11 g\/kg, RPD = 3.12) was higher than that of laboratory vis-NIR (RMSE = 0.14 g\/kg, RPD = 2.45). The optimal prediction accuracy of in situ MIR (RMSE = 0.20 g\/kg, RPD = 1.80) was lower than that of in situ vis-NIR (RMSE = 0.16 g\/kg, RPD = 2.14). The prediction performance of the spectra followed laboratory MIR &gt; laboratory vis-NIR &gt; in situ vis-NIR &gt; in situ MIR. The performance of in situ MIR was relatively poor, mainly due to the fact that MIR was more influenced by soil moisture. This study verified the feasibility of in situ MIR for soil property prediction and provided an approach for obtaining rapid soil information and a reference for soil research and management in black soil areas.<\/jats:p>","DOI":"10.3390\/rs15082053","type":"journal-article","created":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T02:09:21Z","timestamp":1681351761000},"page":"2053","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Prediction of Soil Properties in a Field in Typical Black Soil Areas Using in situ MIR Spectra and Its Comparison with vis-NIR Spectra"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1821-9746","authenticated-orcid":false,"given":"Jianxin","family":"Yin","sequence":"first","affiliation":[{"name":"College of Land Science and Technology, China Agricultural University, Beijing 100193, China"},{"name":"State Key Laboratory of Resources and Environmental Information System, Beijing 100101, China"},{"name":"Key Laboratory of Agricultural Land Quality, Ministry of Natural Resources, Beijing 100193, China"}]},{"given":"Zhan","family":"Shi","sequence":"additional","affiliation":[{"name":"College of Land Science and Technology, China Agricultural University, Beijing 100193, China"}]},{"given":"Baoguo","family":"Li","sequence":"additional","affiliation":[{"name":"College of Land Science and Technology, China Agricultural University, Beijing 100193, China"}]},{"given":"Fujun","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China"}]},{"given":"Tianyu","family":"Miao","sequence":"additional","affiliation":[{"name":"College of Land Science and Technology, China Agricultural University, Beijing 100193, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3914-5402","authenticated-orcid":false,"given":"Zhou","family":"Shi","sequence":"additional","affiliation":[{"name":"Institute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1245-0482","authenticated-orcid":false,"given":"Songchao","family":"Chen","sequence":"additional","affiliation":[{"name":"ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China"}]},{"given":"Meihua","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Environmental Engineering, Yuzhang Normal University, Nanchang 330103, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4996-3177","authenticated-orcid":false,"given":"Wenjun","family":"Ji","sequence":"additional","affiliation":[{"name":"College of Land Science and Technology, China Agricultural University, Beijing 100193, China"},{"name":"State Key Laboratory of Resources and Environmental Information System, Beijing 100101, China"},{"name":"Key Laboratory of Agricultural Land Quality, Ministry of Natural Resources, Beijing 100193, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1002\/ldr.567","article-title":"Black Soil Degradation by Rainfall Erosion in Jilin, China","volume":"14","author":"Yang","year":"2003","journal-title":"Land Degrad. Dev."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zheng, H., Liu, W., Zheng, J., Luo, Y., Li, R., Wang, H., and Qi, H. (2018). Effect of Long-Term Tillage on Soil Aggregates and Aggregate-Associated Carbon in Black Soil of Northeast China. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0199523"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1016\/j.envsci.2010.07.004","article-title":"Soil Loss and Conservation in the Black Soil Region of Northeast China: A Retrospective Study","volume":"13","author":"Xu","year":"2010","journal-title":"Environ. Sci. Policy"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"134173","DOI":"10.1016\/j.jclepro.2022.134173","article-title":"Study of Soil Nitrogen Cycling Processes Based on the 15N Isotope Tracking Technique in the Black Soil Areas","volume":"375","author":"Zhang","year":"2022","journal-title":"J. Clean. Prod."},{"key":"ref_5","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":"Rossel","year":"2006","journal-title":"Geoderma"},{"key":"ref_6","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_7","doi-asserted-by":"crossref","first-page":"115159","DOI":"10.1016\/j.geoderma.2021.115159","article-title":"Evaluating Validation Strategies on the Performance of Soil Property Prediction from Regional to Continental Spectral Data","volume":"400","author":"Chen","year":"2021","journal-title":"Geoderma"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1071\/EA97158","article-title":"Soil Chemical Analytical Accuracy and Costs: Implications from Precision Agriculture","volume":"38","author":"Rossel","year":"1998","journal-title":"Aust. J. Exp. Agric."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1071\/EA97144","article-title":"Can Mid Infrared Diffuse Reflectance Analysis Replace Soil Extractions?","volume":"38","author":"Janik","year":"1998","journal-title":"Aust. J. Exp. Agric."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/bs.agron.2015.02.002","article-title":"Soil Spectroscopy: An Alternative to Wet Chemistry for Soil Monitoring","volume":"132","author":"Nocita","year":"2015","journal-title":"Adv. Agron."},{"key":"ref_11","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_12","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1016\/j.geoderma.2018.11.048","article-title":"Pedometrics Timeline","volume":"338","author":"McBratney","year":"2019","journal-title":"Geoderma"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"116029","DOI":"10.1016\/j.geoderma.2022.116029","article-title":"Bridging the Gap between Soil Spectroscopy and Traditional Laboratory: Insights for Routine Implementation","volume":"425","author":"Poppiel","year":"2022","journal-title":"Geoderma"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"105791","DOI":"10.1016\/j.catena.2021.105791","article-title":"Clay Content Mapping and Uncertainty Estimation Using Weighted Model Averaging","volume":"209","author":"Zhao","year":"2022","journal-title":"Catena"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"104938","DOI":"10.1016\/j.catena.2020.104938","article-title":"Predicting Soil Physical and Chemical Properties Using Vis-NIR in Australian Cotton Areas","volume":"196","author":"Zhao","year":"2021","journal-title":"Catena"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"105990","DOI":"10.1016\/j.compag.2021.105990","article-title":"Soil Exchangeable Cations Estimation Using Vis-NIR Spectroscopy in Different Depths: Effects of Multiple Calibration Models and Spiking","volume":"182","author":"Zhao","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"ref_17","unstructured":"Williams, P., and Norris, K. (1987). Near-Infrared Technology in the Agricultural and Food Industries, American Association of Cereal Chemists, Inc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1071\/SR9950621","article-title":"Characterization and Analysis of Soils Using Mid-Infrared Partial Least-Squares. 1. Correlations with XRF-Determined Major-Element Composition","volume":"33","author":"Janik","year":"1995","journal-title":"Soil Res."},{"key":"ref_19","unstructured":"Rossel, R.V., Walvoort, D.J.J., and MacBratney, A.B. (2001, January 18\u201320). Proximal Sensing of Soil PH and Lime Requirement by Mid Infrared Diffuse Reflectance Spectroscopy. Proceedings of the Third European Conference on Precision Agriculture (3 ECPA), Montpellier, France."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1080\/05704928.2013.811081","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":"2014","journal-title":"Appl. Spectrosc. Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1097\/01.ss.0000187377.84391.54","article-title":"Comparison of near Infrared and Mid Infrared Diffuse Reflectance Spectroscopy for Field-Scale Measurement of Soil Fertility Parameters","volume":"171","author":"McCarty","year":"2006","journal-title":"Soil Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.geoderma.2015.04.017","article-title":"Spectral Libraries for Quantitative Analyses of Tropical Brazilian Soils: Comparing Vis\u2013NIR and Mid-IR Reflectance Data","volume":"255","author":"Terra","year":"2015","journal-title":"Geoderma"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.geoderma.2010.04.008","article-title":"Effects of Soil Sample Pretreatments and Standardised Rewetting as Interacted with Sand Classes on Vis-NIR Predictions of Clay and Soil Organic Carbon","volume":"158","author":"Stenberg","year":"2010","journal-title":"Geoderma"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.biosystemseng.2016.06.005","article-title":"Assessment of Soil Properties in Situ Using a Prototype Portable MIR Spectrometer in Two Agricultural Fields","volume":"152","author":"Ji","year":"2016","journal-title":"Biosyst. Eng."},{"key":"ref_25","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_26","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_27","unstructured":"IUSS Working Group WRB (2022). World Reference Base for Soil Resources. International Soil Classification System for Naming Soils and Creating Legends for Soil Maps, International Union of Soil Sciences (IUSS). [4th ed.]."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1366\/0003702854248656","article-title":"Linearization and Scatter-Correction for near-Infrared Reflectance Spectra of Meat","volume":"39","author":"Geladi","year":"1985","journal-title":"Appl. Spectrosc."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1016\/j.trac.2009.07.007","article-title":"Review of the Most Common Pre-Processing Techniques for near-Infrared Spectra","volume":"28","author":"Rinnan","year":"2009","journal-title":"TrAC Trends Anal. Chem."},{"key":"ref_30","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\u2013Critical Review and Research Perspectives","volume":"43","author":"McBratney","year":"2011","journal-title":"Soil Biol. Biochem."},{"key":"ref_31","unstructured":"Wold, S., Martens, H., and Wold, H. (1983). Matrix Pencils, Springer."},{"key":"ref_32","unstructured":"Wold, S., Johansson, E., and Cocchi, M. (1993). 3D QSAR in Drug Design: Theory, Methods and Applications, Kluwer ESCOM Science Publisher."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"116102","DOI":"10.1016\/j.geoderma.2022.116102","article-title":"Data Mining of Urban Soil Spectral Library for Estimating Organic Carbon","volume":"426","author":"Hong","year":"2022","journal-title":"Geoderma"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.chemolab.2009.09.005","article-title":"A Bootstrap-VIP Approach for Selecting Wavelength Intervals in Spectral Imaging Applications","volume":"100","author":"Gosselin","year":"2010","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"e3226","DOI":"10.1002\/cem.3226","article-title":"Comparison of Variable Selection Methods in Partial Least Squares Regression","volume":"34","author":"Mehmood","year":"2020","journal-title":"J. Chemom."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.chemolab.2012.07.010","article-title":"A Review of Variable Selection Methods in Partial Least Squares Regression","volume":"118","author":"Mehmood","year":"2012","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1080\/10618600.1996.10474713","article-title":"R: A Language for Data Analysis and Graphics","volume":"5","author":"Ihaka","year":"1996","journal-title":"J. Comput. Graph. Stat."},{"key":"ref_38","first-page":"1","article-title":"Multivariate Adaptive Regression Splines","volume":"19","author":"Friedman","year":"1991","journal-title":"Ann. Stat."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_40","first-page":"31","article-title":"Survey of Boosting and Bagging","volume":"36","author":"Shen","year":"2000","journal-title":"Comput. Eng. Appl."},{"key":"ref_41","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_42","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1111\/j.1365-2486.2008.01743.x","article-title":"Soil Carbon Sequestrations by Nitrogen Fertilizer Application, Straw Return and No-Tillage in China\u2019s Cropland","volume":"15","author":"Lu","year":"2009","journal-title":"Glob. Chang. Biol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1038\/nature13809","article-title":"Productivity Limits and Potentials of the Principles of Conservation Agriculture","volume":"517","author":"Pittelkow","year":"2015","journal-title":"Nature"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Yan, Y., Ji, W., Li, B., Wang, G., Hu, B., Zhang, C., and Mouazen, A.M. (2022). Effects of Long-Term Straw Return and Environmental Factors on the Spatiotemporal Variability of Soil Organic Matter in the Black Soil Region: A Case Study. Agronomy, 12.","DOI":"10.3390\/agronomy12102532"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/S0167-1987(02)00018-1","article-title":"Soil Organic Matter Stratification Ratio as an Indicator of Soil Quality","volume":"66","author":"Franzluebbers","year":"2002","journal-title":"Soil Tillage Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"115614","DOI":"10.1016\/j.geoderma.2021.115614","article-title":"Performance of in Situ vs Laboratory Mid-Infrared Soil Spectroscopy Using Local and Regional Calibration Strategies","volume":"409","author":"Greenberg","year":"2022","journal-title":"Geoderma"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1111\/ejss.12320","article-title":"Simultaneous Assessment of Key Properties of Arid Soil by Combined PXRF and V Is\u2013NIR Data","volume":"67","author":"Weindorf","year":"2016","journal-title":"Eur. J. Soil Sci."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Chen, S., Hu, B., Ji, W., Li, S., Hong, Y., Xu, H., Wang, N., Xue, J., and Zhang, X. (2022). Global Soil Salinity Prediction by Open Soil Vis-NIR Spectral Library. Remote Sens., 14.","DOI":"10.3390\/rs14215627"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"53","DOI":"10.4141\/cjss10029","article-title":"Predicting Soil Organic Carbon and Total Nitrogen Using Mid- and near-Infrared Spectra for Brookston Clay Loam Soil in Southwestern Ontario, Canada","volume":"91","author":"Xie","year":"2011","journal-title":"Can. J. Soil. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2307","DOI":"10.1080\/00103620600819461","article-title":"Can near or Mid-Infrared Diffuse Reflectance Spectroscopy Be Used to Determine Soil Carbon Pools?","volume":"37","author":"Reeves","year":"2006","journal-title":"Commun. Soil Sci. Plant Anal."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1002\/saj2.20067","article-title":"Robustness of Visible Near-Infrared and Mid-Infrared Spectroscopic Models to Changes in the Quantity and Quality of Crop Residues in Soil","volume":"84","author":"Greenberg","year":"2020","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_52","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","author":"Vohland","year":"2014","journal-title":"Geoderma"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1111\/ejss.12729","article-title":"Multi-Sensor Fusion for the Determination of Several Soil Properties in the Yangtze River Delta, China","volume":"70","author":"Xu","year":"2019","journal-title":"Eur. J. Soil Sci."},{"key":"ref_54","first-page":"77","article-title":"Infrared Spectroscopy Prediction of Organic Carbon and Total Nitrogen in Soil and Particulate Organic Matter from Diverse Canadian Agricultural Regions","volume":"98","author":"Zhang","year":"2017","journal-title":"Can. J. Soil. Sci."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"108319","DOI":"10.1016\/j.soilbio.2021.108319","article-title":"VNIR and MIR Spectroscopy of PLFA-Derived Soil Microbial Properties and Associated Soil Physicochemical Characteristics in an Experimental Plant Diversity Gradient","volume":"160","author":"Hutengs","year":"2021","journal-title":"Soil Biol. Biochem."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/S0016-7061(98)00023-8","article-title":"Laboratory Evaluation of a Proximal Sensing Technique for Simultaneous Measurement of Soil Clay and Water Content","volume":"85","author":"McBratney","year":"1998","journal-title":"Geoderma"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.geoderma.2006.03.026","article-title":"Mid-and near-Infrared Spectroscopic Assessment of Soil Compositional Parameters and Structural Indices in Two Ferralsols","volume":"136","author":"Madari","year":"2006","journal-title":"Geoderma"},{"key":"ref_58","first-page":"3","article-title":"Spectroscopy of Rocks and Minerals, and Principles of Spectroscopy","volume":"3","author":"Clark","year":"1999","journal-title":"Man. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0065-2113(02)75005-0","article-title":"Quantitative Remote Sensing of Soil Properties","volume":"75","year":"2002","journal-title":"Adv. Agron."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1016\/j.geoderma.2010.06.013","article-title":"Integration of Mid-Infrared Spectroscopy and Geostatistics in the Assessment of Soil Spatial Variability at Landscape Level","volume":"158","author":"Cobo","year":"2010","journal-title":"Geoderma"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"e09050","DOI":"10.1016\/j.heliyon.2022.e09050","article-title":"Performance of Mid Infrared Spectroscopy to Predict Nutrients for Agricultural Soils in Selected Areas of Ethiopia","volume":"8","author":"Lelago","year":"2022","journal-title":"Heliyon"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"722","DOI":"10.2136\/sssaj2017.10.0361","article-title":"Predicting Physical and Chemical Properties of US Soils with a Mid-Infrared Reflectance Spectral Library","volume":"82","author":"Wijewardane","year":"2018","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/0034-4257(92)90099-6","article-title":"Infrared (8\u201314 \u03bcm) Remote Sensing of Soil Particle Size","volume":"42","author":"Salisbury","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_64","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_65","first-page":"19","article-title":"Experimental Study on Total Nitrogen Concentration in Soil by VNIR Reflectance Spectrum","volume":"21","author":"Xu","year":"2005","journal-title":"Geogr. Geo-Inf. Sci."},{"key":"ref_66","first-page":"256","article-title":"Determination for total nitrogen content in black soil using hyperspectral data","volume":"26","author":"Lu","year":"2010","journal-title":"Trans. CSAE"},{"key":"ref_67","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_68","doi-asserted-by":"crossref","first-page":"101","DOI":"10.5194\/soil-4-101-2018","article-title":"Proximal Sensing for Soil Carbon Accounting","volume":"4","author":"England","year":"2018","journal-title":"Soil"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/bs.agron.2021.02.001","article-title":"Current Sensor Technologies for in Situ and On-Line Measurement of Soil Nitrogen for Variable Rate Fertilization: A Review","volume":"168","author":"Guerrero","year":"2021","journal-title":"Adv. Agron."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"116103","DOI":"10.1016\/j.geoderma.2022.116103","article-title":"Soil Moisture Effects on Predictive VNIR and MIR Modeling of Soil Organic Carbon and Clay Content","volume":"427","author":"Seidel","year":"2022","journal-title":"Geoderma"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2053\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:15:13Z","timestamp":1760123713000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2053"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,13]]},"references-count":70,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["rs15082053"],"URL":"https:\/\/doi.org\/10.3390\/rs15082053","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,13]]}}}