Journal
JOURNAL OF NEAR INFRARED SPECTROSCOPY
Volume 16, Issue 3, Pages 265-273Publisher
N I R PUBLICATIONS
DOI: 10.1255/jnirs.786
Keywords
PLS regression; cross-model validation; band assignment; extended multiplicative scatter correction; fatty acids; interpretive spectroscopy
Categories
Ask authors/readers for more resources
In this paper, we present an approach for incorporating chemical band assignment information in regression models between spectra and constituents. It is shown how the matrices in this L-shaped data structure can be combined and give direct information of the relationships between theoretical chemical band assignment, spectral wavelengths and the responses. The chosen application is NIR spectroscopic measurements of canoLa seeds. Variable selection based on partial least squares regression using jack-knifing within a cross-modet validation (CMV) framework is applied for removing non-retevant spectral regions. Extended multiplicative scatter correction was applied as a spectral pre-treatment to remove physical scatter effects in the spectra. The results show a high degree of correspondence between the objectively found wavelength bands from CIVIVand the reported chemical interpretation found in the Literature.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available