High-Throughput Screening of Biomass for Identification of Key Biofuel Traits Using Vibrational Spectroscopy

Eucalypts, such as Corymbia and Eucalyptus species, are suitable biofuel feedstocks, partially due to their ability to grow in a wide range of climates and on marginal land unfit for agriculture.  Characteristics like these have led to eucalypts being the most widely planted hardwood across the globe.  In order to efficiently screen large sample sets of eucalypt species grown in various environments or transgenic trees, analytical tools that circumvent laborious standard methodology are necessary.  The use of analytical techniques such as Raman, mid-infrared, and near-infrared spectroscopy can provide abundant qualitative and quantitative information for evaluating the suitability of plants for biofuels.  We have employed a marriage of analytical spectroscopy with standard methods, such as sulfuric acid hydrolysis and pyrolysis molecular beam mass spectrometry, to produce multivariate models capable of accurately predicting key biomass traits such as cellulose and lignin content, the syringyl:guaiacyl lignin monomer ratio, and the sugar yield following enzymatic saccharification.  Through the use of these predictive models, we have screened over 500 different eucalypt species to isolate which may be best suited for further biofuel research.