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Updated: May 30, 2026
Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall
Published on: June 10, 2017
Combining multivariate analysis and monosaccharide composition modeling to identify plant cell wall variations by
Andreia M Smith-Moritz1, Mawsheng Chern, Jeemeng Lao
1Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, One Cyclotron Road MS 978-4101, Berkeley, CA 94720, USA. mevega-sanchez@lbl.gov.
Abstract:
We outline a high throughput procedure that improves outlier detection in cell wall screens using FT-NIR spectroscopy of plant leaves. The improvement relies on generating a calibration set from a subset of a mutant population by taking advantage of the Mahalanobis distance outlier scheme to construct a monosaccharide range predictive model using PLS regression. This model was then used to identify specific monosaccharide outliers from the mutant population.
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