There is an important need to assess biomass recalcitrance in large populations of both natural and transgenic plants to identify promising candidates for lignocellulosic biofuel production. In order to properly test and optimize parameters for biofuel production, the starting sugar content must be known to calculate percent sugar yield and conversion efficiencies. Pyrolysis molecular beam mass spectrometry (py-MBMS) has been used as a high-throughput method for determination of lignin content and structure and this report demonstrates its applicability for determining glucose, xylose, arabinose, galactose, and mannose content in biomass. Biomass from conifers, hardwoods, and herbaceous species were used to create a 44 sample PLS regression models of py-MBMS spectra based sugar estimates on HPLC sugar content data. The total sugar py-MBMS regression model had a R<sup>2</sup> of 0.91with a 0.17 mg/mg root mean square error of validation indicating accurate estimation of total sugar content for a range of biomass types. Models were validated using 8 independent biomass samples for multiple species, with prediction falling within errors of the HPLC data. With a data collection time of 1.5 minutes per sample py-MBMS serves as a rapid high-throughput method for quantifying sugar content in biomass.

High-throughput method for determining the sugar content in biomass with pyrolysis molecular beam mass spectrometry

249th National Meeting (2015)

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