{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:44:59Z","timestamp":1774449899824,"version":"3.50.1"},"reference-count":24,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2023,12,16]],"date-time":"2023-12-16T00:00:00Z","timestamp":1702684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Hunan Province","award":["2023JJ30304"],"award-info":[{"award-number":["2023JJ30304"]}]},{"name":"Natural Science Foundation of Hunan Province","award":["23A0197"],"award-info":[{"award-number":["23A0197"]}]},{"name":"Natural Science Foundation of Hunan Province","award":["2014FY110200"],"award-info":[{"award-number":["2014FY110200"]}]},{"name":"Natural Science Foundation of Hunan Province","award":["kh2302050"],"award-info":[{"award-number":["kh2302050"]}]},{"name":"Scientific Research Program of Hunan Province Department of Education","award":["2023JJ30304"],"award-info":[{"award-number":["2023JJ30304"]}]},{"name":"Scientific Research Program of Hunan Province Department of Education","award":["23A0197"],"award-info":[{"award-number":["23A0197"]}]},{"name":"Scientific Research Program of Hunan Province Department of Education","award":["2014FY110200"],"award-info":[{"award-number":["2014FY110200"]}]},{"name":"Scientific Research Program of Hunan Province Department of Education","award":["kh2302050"],"award-info":[{"award-number":["kh2302050"]}]},{"name":"National Science and Technology Basic Work Special Project","award":["2023JJ30304"],"award-info":[{"award-number":["2023JJ30304"]}]},{"name":"National Science and Technology Basic Work Special Project","award":["23A0197"],"award-info":[{"award-number":["23A0197"]}]},{"name":"National Science and Technology Basic Work Special Project","award":["2014FY110200"],"award-info":[{"award-number":["2014FY110200"]}]},{"name":"National Science and Technology Basic Work Special Project","award":["kh2302050"],"award-info":[{"award-number":["kh2302050"]}]},{"name":"Changsha Soft Science Research Program","award":["2023JJ30304"],"award-info":[{"award-number":["2023JJ30304"]}]},{"name":"Changsha Soft Science Research Program","award":["23A0197"],"award-info":[{"award-number":["23A0197"]}]},{"name":"Changsha Soft Science Research Program","award":["2014FY110200"],"award-info":[{"award-number":["2014FY110200"]}]},{"name":"Changsha Soft Science Research Program","award":["kh2302050"],"award-info":[{"award-number":["kh2302050"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The accurate measurement of soil organic matter (SOM) is vital for maintaining soil quality. We present an innovative model for SOM prediction by integrating spectral and profile features. We use PCA, Lasso, and SCARS methods to extract important spectral features and combine them with profile data. This hybrid approach significantly improves SOM prediction across various models, including Random Forest, ExtraTrees, and XGBoost, boosting the coefficient of determination (R2) by up to 26%. Notably, the ExtraTrees model, enriched with PCA-extracted features, achieves the highest accuracy with an R2 of 0.931 and an RMSE of 0.068. Compared with single-feature models, this approach improves the R2 by 17% and 26% for PCA features of full-band spectra and profile features, respectively. Our findings highlight the potential of feature integration, especially the ExtraTrees model with PCA-extracted features and profile features, as a stable and accurate tool for SOM prediction in extensive study areas.<\/jats:p>","DOI":"10.3390\/s23249868","type":"journal-article","created":{"date-parts":[[2023,12,18]],"date-time":"2023-12-18T11:28:07Z","timestamp":1702898887000},"page":"9868","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Soil Organic Matter Estimation Model Integrating Spectral and Profile Features"],"prefix":"10.3390","volume":"23","author":[{"given":"Shaofang","family":"He","sequence":"first","affiliation":[{"name":"College of Information and Intelligence, Hunan Agricultural University, Changsha 410128, China"}]},{"given":"Siqiao","family":"Tan","sequence":"additional","affiliation":[{"name":"College of Information and Intelligence, Hunan Agricultural University, Changsha 410128, China"}]},{"given":"Luming","family":"Shen","sequence":"additional","affiliation":[{"name":"College of Information and Intelligence, Hunan Agricultural University, Changsha 410128, China"}]},{"given":"Qing","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Resources, Hunan Agricultural University, Changsha 410128, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,16]]},"reference":[{"key":"ref_1","first-page":"327","article-title":"Research progress on prediction of soil organic matter content by mid-infrared spectroscopy","volume":"4","author":"Zhang","year":"2021","journal-title":"Soil Fertil. Sci. China"},{"key":"ref_2","first-page":"3892","article-title":"Determination of soil organic matter content under forest based on different methods","volume":"22","author":"Tao","year":"2022","journal-title":"Sci. Technol. Eng."},{"key":"ref_3","first-page":"1278","article-title":"Hyperspectral estimation of soil organic matter content based on continuous wavelet transformation","volume":"42","author":"Yumiti","year":"2022","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_4","first-page":"833","article-title":"Construction of soil organic matter rapid detection model based on hyperspectral","volume":"52","author":"Li","year":"2021","journal-title":"J. Shandong Agric. Univ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"104452","DOI":"10.1016\/j.catena.2020.104452","article-title":"Prediction of tropical volcanic soil organic carbon stocks by visible-near- and mid-infrared spectroscopy","volume":"189","author":"Allo","year":"2020","journal-title":"Catena"},{"key":"ref_6","first-page":"564","article-title":"Hyperspectral inversion of soil organic matter content in the three-rivers source region","volume":"52","author":"Zhou","year":"2021","journal-title":"Chin. J. Soil Sci."},{"key":"ref_7","first-page":"4128","article-title":"Hyperspectral estimation of soil organic matter content in Yinchuan plain, China based on PCA sensitive band screening and SVM modeling","volume":"40","author":"Shang","year":"2021","journal-title":"Chin. J. Ecol."},{"key":"ref_8","first-page":"331","article-title":"Soil organic matter content in dryland farmland in northeast China with hyperspectral reflectance based on CWT-SCARS","volume":"53","author":"Gou","year":"2022","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_9","first-page":"361","article-title":"Estimation of soil organic matter content based on characteristic variable selection and regression methods","volume":"39","author":"Liu","year":"2019","journal-title":"Acta Opt. Sin."},{"key":"ref_10","first-page":"2862","article-title":"Extracting characteristic wavelength of soil nutrients based on multi-classifier fusion","volume":"39","author":"Li","year":"2019","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_11","first-page":"95","article-title":"Wavelength variable selection methods for estimation of soil organic matter content using hyperspectral technique","volume":"32","author":"Yu","year":"2016","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_12","unstructured":"Hao, X.X. (2017). Change Characteristic of Soil Organic Matter in Mollisol Profile under Different Ecosystem. [Ph.D. Thesis, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences]."},{"key":"ref_13","first-page":"2696","article-title":"Distribution characteristics and influence factors of organic matter content in cultivated soil in different horizons in hilly areas","volume":"29","author":"Zhang","year":"2020","journal-title":"Resour. Environ. Yangtze Basin"},{"key":"ref_14","first-page":"1864","article-title":"Characteristic of soil profile and nutrient change of fragrant taro typical region in Shaoguan","volume":"31","author":"Gao","year":"2018","journal-title":"Southwest China J. Agric. Sci."},{"key":"ref_15","first-page":"74","article-title":"Composition and distribution characteristics of organic matter in soil profiles of Yancheng flats","volume":"13","author":"Jia","year":"2015","journal-title":"Wetl. Sci."},{"key":"ref_16","first-page":"2556","article-title":"Prediction of soil organic matter based PCA-MLR and PCA-BPN algorithm using field VNIR spectroscopy in coastal soils of southern Laizhou bay","volume":"38","author":"Xu","year":"2018","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_17","first-page":"13","article-title":"The progress and prospect of soil organic matter mapping based on remote sensing technology","volume":"31","author":"Yan","year":"2019","journal-title":"China Agric. Inform."},{"key":"ref_18","first-page":"1170","article-title":"Some thoughts on deep learning enabling cartography","volume":"50","author":"Ai","year":"2021","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_19","first-page":"767","article-title":"Inversion of desert soil organic matter content using visible-infrared spectrum in southern Xinjiang","volume":"49","author":"Li","year":"2018","journal-title":"Chin. J. Soil Sci."},{"key":"ref_20","first-page":"22","article-title":"A review of hyperspectral multivariate information extraction models for soils","volume":"2","author":"Zhang","year":"2018","journal-title":"Soil Fertil. Sci. China"},{"key":"ref_21","first-page":"156","article-title":"Estimation of desert soil organic matter through hyperspectral based on fractional-order derivatives and SVMDA-RF","volume":"51","author":"Zhang","year":"2020","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_22","first-page":"1261","article-title":"Spatial prediction of topsoil organic matter of arable land by different models at the regional scale","volume":"52","author":"Ma","year":"2021","journal-title":"Chin. J. Soil Sci."},{"key":"ref_23","first-page":"1905","article-title":"Hyperspectral estimation model of soil organic matter content using generative adversarial networks","volume":"41","author":"He","year":"2021","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_24","first-page":"6638","article-title":"CatBoost: Unbiased boosting with categorical features","volume":"2018","author":"Prokhorenkova","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/24\/9868\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:40:04Z","timestamp":1760132404000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/24\/9868"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,16]]},"references-count":24,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["s23249868"],"URL":"https:\/\/doi.org\/10.3390\/s23249868","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,16]]}}}