Multiscale Analysis and Spatio-temporal Modeling of Deconstruction of Lignocellulosic Biomass – BIOMOD

The conversion of lignocellulose into products such as biofuels and bio-based molecules can be a solution to concerns over growing energy demand and contribute to climate change mitigation. However, lignocellulosic biomass (LB) is naturally recalcitrant to enzymatic deconstruction. The recalcitrance hinders cost-effective conversion of LB into biofuels, chemicals and polymers. Extensive research for understanding the parameters underlying LB recalcitrance has led to the identification of several chemical and physical parameters. Nevertheless, uncovering universal parameters remains largely elusive as the identified parameters are confined to LB species and/or pretreatment type. Furthermore, the cellular and tissular scales structural parameters governing LB recalcitrance have not been investigated yet. Goal of BIOMOD project is to develop an original combination of confocal time-lapse imaging of LB samples during enzymatic hydrolysis, 4D (space + time) image processing, and spatio-temporal modelling to identify universal key structural parameters at cellular and tissular scales correlated with hydrolysis yield. The image processing and quantification pipeline will be integrated in an open-source software platform with a web-based graphical user interface.