Soil parameter quantification by NIRS as a Chemometric challenge at ‘Chimiométrie 2006’

By J. Pierna, P. Dardenne. 2008

48 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Artificial Intelligence, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/05731dbfcad9c743a9d02cad0598e69c9f734691

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. José Alexandre Mello Demattê

In Artificial Intelligence

1. José Alexandre Mello Demattê
2. Bo Stenberg
3. Suzana Romeiro Araújo
4. Johanna Wetterlind

In Environmental Engineering

1. José Alexandre Mello Demattê

Citations in the corpus

• 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 (2014, result): “Viscarra Rossel & Behrens (2010) also found SVM to be about equal to PLSR, while Pierna & Dardenne (2008) found that SVM was superior to PLSR for predicting total N, total C and CEC in a validation set of 207 soils from a calibration set of 618 cultivated Belgian soils.”