Analysis of forest foliage spectra using a multivariate mixture model

Christine A. Hlavka, David L. Peterson, Lee F. Johnson, Barry Ganapol

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Wet chemical measurements and near infrared spectra of dry ground leaf samples were analysed to test a multivariate regression technique for estimating component spectra. The technique is based on a linear mixture model for log(1/R) pseudoabsorbance derived from diffuse reflectance measurements. The resulting unmixed spectra for carbohydrates, lignin and protein resemble the spectra of extracted plant carbohydrates, lignin and protein. The unmixed protein spectrum has prominent absorption peaks at wavelengths that have been associated with nitrogen bonds. It therefore appears feasible to incorporate the linear mixture model in whole leaf models of photon absorption and scattering so that effects of varying nitrogen and carbon concentration on leaf reflectance may be simulated.

Original languageEnglish (US)
Pages (from-to)167-173
Number of pages7
JournalJournal of Near Infrared Spectroscopy
Issue number3
StatePublished - 1997


  • Cellulose
  • Leaf chemistry
  • Least squares regression
  • Lignin
  • Linear mixture model
  • Protein
  • Spectral deconvolution
  • Spectral reconstruction

ASJC Scopus subject areas

  • Spectroscopy


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