Reflectance spectroscopy of fresh whole leaves for the estimation of chemical concentration

https://doi.org/10.1016/0034-4257(92)90133-5Get rights and content

Abstract

In an effort to further develop the methods needed to remotely sense the biochemical content of plant canopies, we report the results of an experiment to relate the concentrations of chlorophyll, protein, starch, sugar, amaranthin, and water in fresh whole leaves to their reflectance at wavelengths throughout the visible and near infrared. This is an analysis of laboratory data from a previously reported experiment (Curran et al., 1991) in which 163 freshly excised leaves of the plant Amaranthus tricolor were measured for reflectance and biochemical content. Stepwise regression was used to generate an equation for the estimation of chemical concentration from derivative reflectance in selected wavelengths. The reduction of instrument noise through Fourier filtering and a sample control procedure to minimize spectral overlap had little effect on the correlation between derivative reflectance in selected wavelengths and chemical concentration but did enable absorption features attributable to sugar and protein to be detected. However, the minimization of spectral overlap did increase the number of wavelengths attributable to known absorption features that were selected by stepwise procedures. Using only derivative reflectance in wavelengths that were attributable to absorption by the chemical of interest, the coefficients of determination (R2) between estimated and measured concentrations of chlorophyll, amaranthin, starch, and water were 0.82 or above, with root-mean square errors that were 12.5% of the median or less.

References (36)

  • C.D Elvidge

    Vegetation reflectance features in AVIRIS data

  • C.D Elvidge

    Visible and near infrared reflectance characteristics of dry plant materials

    Int. J. Remote Sens.

    (1990)
  • V.F Flack et al.

    Frequency of selecting noise variables in subset regression analysis: A simulation study

    Am. Stat.

    (1987)
  • P Gaus et al.

    Smoothing and differentiation of spectroscopic curves using spline functions

    Appl. Spectrosc.

    (1984)
  • F.G Giesbrecht et al.

    The use of trigonometric polynomials to approximate visible and near infrared spectra of agricultural products

    Appl. Spectrosc.

    (1981)
  • W Hruschka

    Data analysis: wavelength selection and methods

  • R.A Johnson et al.

    Applied Multivariate Statistical Analysis

    (1982)
  • O.H Lowry et al.

    Protein measurement with the Folin-phenol reagent

    J. Biol. Chem.

    (1950)
  • Cited by (0)

    This research was undertaken at NASA/Ames Research Center, California and was partially funded by NASA's Earth Sciences Applications Division while P.J.C. held a Senior NRC Research Associateship under a grant from the NASA's Life Sciences Division, B. A. M. held a NRC Research Associateship under a grant from the NASA's Life Sciences Division, and S. E. P. held a NASA Space Biology Internship.

    Processing the large data set reported here was made possible by the laboratory and computing assistance of Xoan Trinh of San Jose State University and Laure Nishioka, Oliver Lin, Saumya Sutaria, Punam Bansal, Pierson Chiou, and Luu Nuygen of NASA's SHARP and Space Biology Studentship Programs.

    1

    We are indebted to Don Card of the University of Utah for his critique of the manuscript.

    View full text