Modelling of Starch Production by Microalgal Biomass under Multi-nutrient Limitation

摘要

Microalgal biomass is considered to be a sustainable and renewable feedstock for biofuel production. These photosynthetic organisms naturally accumulate carbohydrates - mainly in the form of starch - that can be used as raw substrates for sugar-based biofuels like bioethanol or biobutanol. Several studies have shown that carbohydrate content in microalgae strains is positively influenced under stressed cultivation conditions such as single or multi-nutrient limitation. An efficient approach towards improving carbohydrate productivities by means of a cultivation strategy is the development of robust dynamic models able to describe the main elements involved during microalgae cultivation. However, there have been very limited efforts in the literature regarding the modelling of microalgae-based carbohydrates. The aim of this work is thus to develop a predictive multi-parameter model for the optimization of microalgal carbohydrate production under multi-nutrient limitation. The proposed model takes into account the intracellular carbon flows between two main cellular compartments: a functional pool of carbon biomass and a storage pool comprising of starch (carbohydrates) and lipids. The model was fitted against experimental datasets generated from lab-scale cultivation involving growth of Chlamydomonas reinhardtii CCAP 11/32C in standard Tris-Acetate-Phosphate (TAP) media under different concentration regimes. Parameter fitting was carried out through an in-house developed optimization algorithm followed by model validation. The model can be used to predict three carbon-based cellular pools - starch, lipids, and biomass - as well as nutrient consumption, factors which help in establishing optimal cultivation strategies.