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Applied and Environmental Soil Science
Volume 2012 (2012), Article ID 294121, 14 pages
Research Article

Effects of Subsetting by Carbon Content, Soil Order, and Spectral Classification on Prediction of Soil Total Carbon with Diffuse Reflectance Spectroscopy

1Natural Resources and Environmental Management Department, University of Hawai‘i Mānoa, 1910 East-West Road, Sherman 101, Honolulu, HI 96822, USA
2Biology & Natural Resources Department, Principia College, 1 Maybeck Place, Elsah, IL 62028, USA
3Tropical Plant and Soil Sciences Department, University of Hawai‘i Mānoa, 3190 Maile Way, Honolulu, HI 96822, USA
4Soil and Water Science Department, University of Florida, 2169 McCarty Hall, P.O. Box 110290, Gainesville, FL 32611-0290, USA

Received 15 March 2012; Revised 20 August 2012; Accepted 14 October 2012

Academic Editor: Sabine Chabrillat

Copyright © 2012 Meryl L. McDowell et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [8 citations]

The following is the list of published articles that have cited the current article.

  • Antoine Stevens, Marco Nocita, Gergely Toth, Luca Montanarella, and Bas van Wesemael, “Prediction of Soil Organic Carbon at the European Scale by Visible and Near InfraRed Reflectance Spectroscopy,” Plos One, vol. 8, no. 6, 2013. View at Publisher · View at Google Scholar
  • Tadele Amare, Christian Hergarten, Hans Hurni, Bettina Wolfgramm, Birru Yitaferu, and Yihenew G. Selassie, “Prediction of Soil Organic Carbon for Ethiopian Highlands Using Soil Spectroscopy,” ISRN Soil Science, vol. 2013, pp. 1–11, 2013. View at Publisher · View at Google Scholar
  • S. R. Araújo, J. Wetterlind, J. A. M. Demattê, and B. Stenberg, “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,” European Journal of Soil Science, vol. 65, no. 5, pp. 718–729, 2014. View at Publisher · View at Google Scholar
  • Z. Shi, W. Ji, R. A. Viscarra Rossel, S. Chen, and Y. Zhou, “Prediction of soil organic matter using a spatially constrained local partial least squares regression and the Chinese vis-NIR spectral library,” European Journal of Soil Science, 2015. View at Publisher · View at Google Scholar
  • N.M. Knox, S. Grunwald, M.L. McDowell, G.L. Bruland, D.B. Myers, and W.G. Harris, “Modelling soil carbon fractions with visible near-infrared (VNIR) and mid-infrared (MIR) spectroscopy,” Geoderma, vol. 239-240, pp. 229–239, 2015. View at Publisher · View at Google Scholar
  • Yi Peng, Xiong Xiong, Kabindra Adhikari, Maria Knadel, Sabine Grunwald, and Mogens Humlekrog Greve, “Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra,” PLoS One, vol. 10, no. 11, 2015. View at Publisher · View at Google Scholar
  • Shengxiang Xu, Xuezheng Shi, Meiyan Wang, and Yongcun Zhao, “Effects of Subsetting by Parent Materials on Prediction of Soil Organic Matter Content in a Hilly Area Using Vis-NIR Spectroscopy,” Plos One, vol. 11, no. 3, 2016. View at Publisher · View at Google Scholar
  • Xuezheng Shi, Meiyan Wang, Shengxiang Xu, and Yongcun Zhao, “Rapid determination of carbon, nitrogen, and phosphorus contents of field crops in China using visible and near-infrared reflectance spectroscopy,” Crop Science, vol. 57, no. 1, pp. 475–489, 2017. View at Publisher · View at Google Scholar