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In Silico Models on Algal Cultivation and Processing: An Approach for Engineered Optimization
Abstract
In modern system-level metabolic engineering, genome-wide metabolic reconstructions are used as a systems-based framework for integrating and analyzing large “omics” data sets as well as for assessing cell design molecular and bioinformatics approach “in silico”. Microalgae growth processes are based on the concurrent interaction of micronutrients (Mg, Fe, Zn, etc.), macronutrients (N, C, P), and environmental parameters (temperature and light). Blackbox models or macroscopic models give the reliable interrelationship amidst the growth kinetics of microalgae and its potential of lipid and starch accumulation in response to any of the growth restraining factors. This chapter provides an insight into the different in silico models for the growth and cultivation of microalgae. Various factors such as light intensity/distribution, the temperature during cultivation, and nutrient concentration are considered. The chapter also summarises the role of different photobioreactors (PBRs) in optimising algae-based products using genome-scale models.
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