Quantitative reflectance spectroscopy offers an alternative to traditional analytical methods for the determination of the chemical composition of a sample. The objective of this study was to develop a set of spectroscopic calibrations to determine the chemical composition (nutrients, carbon, and fiber constituents, determined using standard wet lab methods) of dried conifer foliage samples (N = 72), and to compare the predictive ability of calibrations based on three different spectral regions: visible and shortwave near infrared (VIS-sNIR, 400- to 1100-nm wavelengths), near infrared (NIR, 1100- to 2500-nm wavelengths), and mid infrared (MIR, 2500- to 25 000-nm wavelengths). To date, most quantitative reflectance spectroscopy has been based on the VIS-sNIR-NIR, and the ability of MIR calibrations to predict the composition of tree foliage has not been tested. VIS-sNIR calibrations were clearly inferior to those based on longer wavelengths. For 8 of 11 analytes, the MIR calibrations had the lowest standard error of cross-validation, but in most cases the difference in accuracy between NIR and MIR calibrations was small, and against an independent validation set, there was no clear evidence that either spectral region was superior. Although quantitative MIR spectroscopy is at a more primitive state of development than NIR spectroscopy, these results demonstrate that the mid infrared has considerable promise for quantitative analytical work.
ASJC Scopus subject areas
- Global and Planetary Change