Abstract
Cultivation of microalgae is a promising long-term, sustainable candidate for biomass and oil for the production of fuel, food, nutraceuticals and other added-value products. Attention has been drawn to the use of computa- tional and experimental validation studies aiming at the optimisation and the control of microalgal oil productiv- ity either through the improvement of the growth mechanism or through the application of metabolic engineering methods to microalgae. Optimisation of such a system can be achieved through the evaluation of or- ganic carbon sources, nutrients and water supply, leading to high oil yield. The main objective of this work is to develop a novel integrated experimental and computational approach, utilising a microalgal strain grown at bench-scale, with the aim to systematically identify the conditions that optimise growth and lipid production, in order to ultimately develop a cost-effective process to improve the system economic viability and overall sus- tainability. To achieve this, a detailed model has been constructed through a multi-parameter quantification methodology taking into account photo-heterotrophic biomass growth. The corresponding growth rate is based on carbon substrate concentration, nitrogen and light availability. The developed model also considers the pH of the medium. Parameter estimation was undertaken using the proposed model in conjunction with an extensive number of experimental data taken at a range of operating conditions. The model was validated and utilised to determine the optimal operating conditions for bench-scale batch lipid oil production.
Original language | English |
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Pages (from-to) | 78-87 |
Journal | Algal Research |
Volume | 23 |
Early online date | 1 Feb 2017 |
DOIs | |
Publication status | Published - 1 Apr 2017 |
Keywords
- Chlamydomonas reinhardtii
- Biofuels
- Kinetic modelling
- Microalgal oil
- Nitrogen starvation
- Acetate utilization