Abstract
In the present work we wanted to know what happens during time to biomass and lipid productivities of Chlorococcum littorale repeatedly subjected to N-starvation. Experiments were done using repeated cycles of batch-wise N run-out (after 2days N=0). Two different cycles were used: repeated short-starvation (6days of N=0) over a total period of 72days and repeated long-starvation (13days of N=0) over a total period of 75days. Batches (using fresh inocula) were done separately as control. Shorter and longer periods of starvation showed no differences in biomass productivities and PSII quantum yield evolution. The repeated short-starvation-batches showed the same lipid productivities as the control short-starvation batches. Most importantly, the biomass lipid content was the same between control and repeated-batches. Altogether, the results point to C. littorale as a resilient and stable strain, with potential to be used under semi continuous cultivation.
Highlights
Microalgae-based technology has the potential to supply new sustainable products due to its versatility and sustainability (e.g., CO2 neutral and no arable land required) (Ali Bahadar, 2013; Lam and Lee, 2012; Rawat et al, 2013)
The repeated N-starvation experiment was a continuous series of repeated batches that was divided into two phases: 8 cycles of short-starvation (RSS, 7 days of starvation) and 5 cycles of longstarvation (RLS, 13 days of starvation) (Fig. 1)
Between and among each other (Table 1). This result shows two things: 1] the constant biomass productivity throughout repeated batches and that 2] doubling the starvation time showed no effect on subsequent biomass productivity in the cycle
Summary
Microalgae-based technology has the potential to supply new sustainable products due to its versatility (biomass can be simultaneously refined into multiple products) and sustainability (e.g., CO2 neutral and no arable land required) (Ali Bahadar, 2013; Lam and Lee, 2012; Rawat et al, 2013). There are two main approaches to increase microalgal lipid volumetric productivity: process optimization and strain improvement. Process optimization is used to maximize the production of a certain compound using already available strains (Saha et al, 2013). Strain improvement is used to select cells that display an increased baseline production of a certain compound, which can be achieved via breeding and artificial selection (Combe et al, 2015; Fu et al, 2013; Portnoy et al, 2011) and/or mutagenesis (de Jaeger et al, 2014; Doan and Obbard, 2012; Velmurugan et al, 2014). A combination of process optimization and strain improvement could significantly increase productivity and reduce production costs
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