期刊
CELLULOSE
卷 20, 期 4, 页码 1629-1637出版社
SPRINGER
DOI: 10.1007/s10570-013-9935-1
关键词
Miscanthus; FT-NIR; Composition; PLS regression; Chemometrics
资金
- Energy Biosciences Institute
Fourier transform near infrared spectroscopy was applied to ball-milled and dried whole plant Miscanthus x giganteus samples in combination with partial least square regression analysis for prediction of main constituents of the biomass. The developed models with 172 calibration samples had an R-2 in the range of 0.96-0.99. For the first time, the acetyl content was modeled for Miscanthus. An independent calibration set of 58 samples revealed a low root mean square error of prediction of 0.414 % for extractives, 0.485 % for glucan, 0.249 % for xylan, 0.061 % for arabinan, 0.050 % for acetyl, 0.198 % for Klason lignin, 0.226 % for total ash and 0.133 % for ash after extraction, an indication of a high level of accuracy. The results showed major improvement over previously reported models, which was attributed to the smaller particle size used. The models are a valuable tool for the fast monitoring of the composition of M. x giganteus in e.g. plant breeding studies.
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