Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1242876 | Talanta | 2009 | 6 Pages |
Abstract
Discriminate partial least squares analysis of the near infrared spectra allowed to classify soils with and without residues, regardless of the type of tillage or rotation systems used with a prediction rate of 90% in the internal validation and 94% in the external validation. The NIRS calibration model using a modified partial least squares regression allowed to determine the δ13C in soils with or without residues, with multiple correlation coefficients 0.81 and standard error prediction 0.5â° in soils with residues and 0.92 and 0.2â° in soils without residues. The ratio performance deviation for the quantification of δ13C in soil was 2.5 in soil with residues and 3.8 without residues. This indicated that the model was adequate to determine the δ13C of unknown soils in the â16.2â° to â20.4â° range. The development of the NIR calibration permits analytic determinations of the values of δ13C in unknown agricultural soils in less time, employing a non-destructive method, by the application of the fibre optic probe of remote reflectance to the soil sample.
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Mariela Fuentes, Inmaculada González-MartÃn, Jose Miguel Hernández-Hierro, Claudia Hidalgo, Bram Govaerts, Jorge Etchevers, Ken D. Sayre, Luc Dendooven,