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. © 2011 Smith-Moritz et al; licensee BioMed Central Ltd.
CITATION STYLE
Smith-Moritz, A. M., Chern, M., Lao, J., Sze-To, W. H., Heazlewood, J. L., Ronald, P. C., & Vega-Sánchez, M. E. (2011). Combining multivariate analysis and monosaccharide composition modeling to identify plant cell wall variations by Fourier Transform Near Infrared spectroscopy. Plant Methods, 7(1). https://doi.org/10.1186/1746-4811-7-26
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