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Open Access Methodology

Combining multivariate analysis and monosaccharide composition modeling to identify plant cell wall variations by Fourier Transform Near Infrared spectroscopy

Andreia M Smith-Moritz12, Mawsheng Chern13, Jeemeng Lao13, Wing Hoi Sze-To13, Joshua L Heazlewood12, Pamela C Ronald123 and Miguel E Vega-Sánchez13*

Author Affiliations

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

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Plant Methods 2011, 7:26  doi:10.1186/1746-4811-7-26

Published: 18 August 2011

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.

Keywords:
near infrared spectroscopy; cell wall; hemicellulose; multivariate analysis; mutant screen; pls modeling