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-Reference-Cited by-同舟云学术

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

Published:2014-08-05 Issue:5 Volume:65 Page:718-729
ISSN:1351-0754
Container-title:European Journal of Soil Science
language:en
Short-container-title:Eur J Soil Sci

Author:

Araújo S. R.¹,Wetterlind J.²,Demattê J. A. M.¹,Stenberg B.²

Affiliation:

1. Department of Soil Science; University of São Paulo; Av. Pádua Dias 11 13418-260 Piracicaba Brazil

2. Department of Soil and Environment; Swedish University of Agricultural Sciences; Gråbrödragatan 19, PO box 234 532 23 Skara Sweden

Funder

FAPESP (São Paulo Research Foundation)

CNPq (National Council for Scientific and Technological Development)

Swedish Farmers' Foundation for Agricultural Research

Swedish Research Council Formas

Publisher

Wiley

Subject

Soil Science

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/ejss.12165/fullpdf

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3. Near-infrared reflectance spectroscopic analysis of soil C and N;Chang;Soil Science,2002

4. Near-infrared reflectance spectroscopy-principal components regression analyses of soil properties;Chang;Soil Science Society of America Journal,2001

5. Influence of soil moisture on near-infrared reflectance spectroscopic measurement of soil properties;Chang;Soil Science,2005

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