3.5. Strengths and limitations of ePBRs for biomass productivity
estimation
This study further supports the convenience of using commercially
available devices such as ePBRs for low cost and low risk assessment of
potential microalgal productivity on any geographical region and to
contribute information on the effect of cultivation variables with high
resolution of site and season specificity. This is especially important
for advancing R&D of microalgal biotechnology in developing countries.
This is mostly because the costs of installation and operation of
raceway ponds, even being the least expensive cultivation systems, might
still represent a barrier to accelerate R&D in developing countries.
Thus, both mathematical modeling [18,36] and
devices for productivity estimation under climate simulated conditions
are generally valuable [23,26] and especially
useful to optimized limited resourced allocated to R&D in developing
counties [2,19,22].
As commented before [23,37] ePBRs proved to be
highly reliable in terms of producing very consistent results with low
variation among independent runs after randomizing the scripts and the
ePBR units.
On the other side, a validation study by Huesemann and colleagues (2017)
suggested that PhenometricsTM ePBRs might
underestimate microalgal biomass productivity up to 44% for C.
sorokiniana (DOE 1412) in Arizona (US) simulated-climate. Similarly,
the optical-density-based biomass productivity and the rate of increase
in cell counts of Picochlorum soloecismus in the ePBRs was also
lower than in custom-built PNNL indoor climate-simulation ponds[23]. It is currently unknown whether ePBRs
generally underestimate microalgal biomass productivity and/or if the
inaccuracy could be strain specific. Although this raises some
uncertainties on the absolute productivity potential of the geographical
sites analyzed in this study, and others, it tends to provide an
optimistic base-line for a comparative estimation. Additionally, it is
important to take into account that these simulations oversimplify the
complexity of outdoors cultivation of microalgae for weather
homogenization around historical annual averages of temperature and
irradiation. Overriding year specific climatic fluctuations might give
reasonably accurate predictions of microalgal biomass productivity in
the long-term. However, weather fluctuations at different time scales
(from hours to years) should be tolerated by selected robust strains to
make both short- and long-term predictions more realistic. Robustness of
selected strains should also prevent and/or tolerate contamination,
predation and/or grazing for more realistic predictive models.
As concluding remarks, this study represents a pioneering work for the
estimation of microalgal biomass productivity in South America. Results
support a high potential of Tropical and Subtropical regions for high
biomass productivities. Fortaleza (Brazil) was identified as one of the
candidate production sites with a predicted annual average biomass
productivity of 23 g · m-2 · d-1,
which is very close to the target estimated by the DOE for economic
feasibility of microalgal biofuels.
This study contributes guidance for comprehensive resource assessment
and techno-economic analyses of the potential of microalgal
biotechnology according to the South American resources and specific
needs.