Combining multivariate analysis and monosaccharide composition modeling to identify plant cell wall variations by Fourier Transform Near Infrared spectroscopy
1 Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, One Cyclotron Road MS 978-4101, Berkeley, CA 94720, USA
2 Physical Biosciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road MS 978-4101, Berkeley, CA 94720, USA
3 Department of Plant Pathology, University of California, One Shields Ave., Davis, CA 95616
Plant Methods 2011, 7:26 doi:10.1186/1746-4811-7-26Published: 18 August 2011
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.