title: Combining multivariate analysis and monosaccharide composition modeling to identify plant cell wall variations by Fourier Transform Near Infrared spectroscopy.
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.
authors.affiliation: Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, One Cyclotron Road MS 978-4101, Berkeley, CA 94720, USA. mevega-sanchez@lbl.gov.
authors.forename: Andreia M
authors.initials: AM
authors.lastname: Smith-Moritz
authors.forename: Mawsheng
authors.initials: M
authors.lastname: Chern
authors.forename: Jeemeng
authors.initials: J
authors.lastname: Lao
authors.forename: Wing Hoi
authors.initials: WH
authors.lastname: Sze-To
authors.forename: Joshua L
authors.initials: JL
authors.lastname: Heazlewood
authors.forename: Pamela C
authors.initials: PC
authors.lastname: Ronald
authors.forename: Miguel E
authors.initials: ME
authors.lastname: Vega-Sánchez