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Two preprocessing techniques to reduce model covariables in soil property predictions by Vis-NIR spectroscopy

Two preprocessing techniques to reduce model covariables in soil property predictions by Vis-NIR... http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Soil and Tillage Research CrossRef

Two preprocessing techniques to reduce model covariables in soil property predictions by Vis-NIR spectroscopy

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Publisher
CrossRef
Copyright
© 2017 Elsevier B.V. All rights reserved.
ISSN
0167-1987
DOI
10.1016/j.still.2017.05.008
Publisher site
See Article on Publisher Site

Abstract

Journal

Soil and Tillage Research – CrossRef

Published: Sep 1, 2017

References

  • A Comparison of Support Vector Machines and Partial Least Squares Regression on Spectral Data
    Üstün
  • The soil management assessment framework: a quantitative soil quality evaluation method
    Andrews
  • 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
    Araújo