Abstract: Methods and materials for measuring the composition of plant biomass and predicting the efficiency of conversion of such biomass to various end products under various processing conditions are disclosed. For example, methods and materials for identifying plant material having higher levels of accessible carbohydrate, as well as materials and methods for processing plant material having higher levels of accessible carbohydrate are disclosed. Also disclosed are computer-implemented methods and systems that provide improved economic efficiencies to biorefineries.

Abstract: The present invention is directed to a method of using a near-infrared (NIR) model to predict the amount of accessible carbohydrate material in a feedstock sample. The NIR model is generated by subjecting a set of biomass calibration feedstock samples to near infrared spectroscopy which produces NIR spectroscopic data, measuring the chemical compositions of each said calibration feedstock sample by wet chemical techniques, and measuring the total amount of monosaccharides and disaccharides solubilized by each said calibration feedstock sample after processing under a defined pretreatment condition or defined enzyme load condition. The method is then applied to NIR spectral data obtained from a test feedstock sample to predict the amount of accessible carbohydrate material in the test feedstock sample.

Abstract: Methods and materials for measuring the composition of plant biomass and predicting the efficiency of conversion of such biomass to various end products under various processing conditions are disclosed. For example, methods and materials for identifying plant material having higher levels of accessible carbohydrate, as well as materials and methods for processing plant material having higher levels of accessible carbohydrate are disclosed. Also disclosed are computer-implemented methods and systems that provide improved economic efficiencies to biorefineries.