Estimating the soil clay content and organic matter by means of different calibration methods of vis-NIR diffuse reflectance spectroscopy

By Said Nawar, Henning Buddenbaum, Joachim Hill, Jacek Kozak, Abdul Mounem Mouazen. 2016

269 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Artificial Intelligence, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/705dca24cac5227e324786aa990d07a39ad92b12

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. W. P. Filho
2. R. S. Dalmolin
3. Sabine Grunwald
4. André Carnieletto Dotto
5. A. T. Caten

In Artificial Intelligence

1. W. P. Filho
2. R. S. Dalmolin
3. Sabine Grunwald
4. André Carnieletto Dotto
5. A. T. Caten

In Environmental Engineering

1. W. P. Filho
2. R. S. Dalmolin
3. Sabine Grunwald
4. André Carnieletto Dotto
5. A. T. Caten
6. Budiman Minasny

Citations in the corpus

• Two preprocessing techniques to reduce model covariables in soil property predictions by Vis-NIR spectroscopy (2017, methodology): “SVM and PLSR have already shown good results in soil properties predictions (Araújo et al., 2014; Conforti et al., 2015; Knox et al., 2015; Kuang et al., 2015; Nawar et al., 2016; Stevens et al., 2010; Terra et al., 2015).”