COMPUTER-ASSISTED FERMENTATION DESIGN OF COMPLEX MACROALGAE BIOMASS INTO BIOETHANOL

Increase the energy return on investment is a major target for biorefinery development. The composition of feedstock biomass and the selection of fermenting microorganisms are critical factors in biorefinery energy efficiency. Feedstock biomass composition is constrained by local supply materials, but microorganism selection affords considerable flexibility. Once biomass feedstock is identified, biorefinery designers need to select optimal fermenting organisms to transform the feedstock biomass into target products. While fermentation by microorganism communities can increase the range of digested biomass compounds and can be more resistant to infections, it has intrinsic problems in the context of species competition, process design and modeling — issues related to insufficient process control. Using a serial fermentation approach, we offset some of these issues to allow maximal process control, while benefiting from organism diversity to maximize feedstock conversion rates. Here, we describe the application of BioLEGO, a freely available web-based application that enables computer-assisted a single and two-step multiorganism fermentation process design to ferment complex macroalgae from Ulva and Kappaphycus families into bioethanol. BioLEGO is based on a modular modeling approach, enabling the generation of different fermentation configurations consisting of independent organism modules. We show that two-step fermentation of complex marine biomass reduces by 32% the total energy wastes of the process in comparison with a single step fermentation performed today. This findings are important for the further improvements of energy return on interment of biorefineries.