View graph of relations

Different methods for spectral preprocessing were compared in relation to the ability to distinguish between fungal isolates and growth stages for Penicillium camemberti grown on cheese substrate. The best classification results were obtained by temperature- and wavelength-extended multivariate signal correction (TWEMSC) preprocessing, whereby three patterns of variation in near-infrared (NIR) log(1/R) spectra of fungal colonies could be separated mathematically: (1) physical light scattering and its wavelength dependency, (2) differences in light absorption of water due to varying sample temperature, etc., and (3) differences in light absorption between different fungal isolates. With this preprocessing, discriminant partial least squares (PLS) regression yielded 100% correct classification of three isolates, both within the cross-validated calibration set and in two independent test sets of samples.
Original languageEnglish
JournalApplied Spectroscopy
Publication date2005
Volume59
Issue1
Pages56-68
ISSN0003-7028
StatePublished

Keywords

  • NIR, diffuse reflectance, preprocessing, water structure, EMSC, near infrared, P. camemberti, temperature-calibrated EMSC, extended multiplicative signal correction, temperature, light scattering
Download as:
Download as PDF
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
Word

ID: 2675576