Biomedical Engineering Reference
In-Depth Information
comprehensive evaluation of select species from an integrated perspective would be
of greatest benefit to commercial operations. Although Serrano's quote (Serrano,
2010) that, “We are still like the Wright Brothers, putting pieces of wood and paper
together” is in a different context, it is apt here. The rigor of microalgal biofuel
research, coupled with its interdisciplinary nature, suggests that a comprehensive
modeling strategy, one that accounts for numerous culture and harvest parameters
and optimizes industrial processes from a perspective of cost, would be of great
value. Simulation models that incorporate elements of nutrient systems, ideal culture
conditions, and harvest of multiple products such as fuels and high-value nutraceu-
ticals and/or recombinant proteins would be instrumental in the development of a
viable bio-economy. Brown (2009) pointed out that as mass cultivation of algae for
biofuels per se may not sustain microalgal technology, attention should be paid to
non-fuel products and co-products as well. These co-products include carotenoids,
phycolbiliproteins, astaxanthin, and eicosapentaenoic acid; additionally, algal bio-
mass waste could be used as fertilizer (Donovan and Stowe, 2009).
Various processes are involved in this modeling activity. As Malcata (2010)
observed, modeling exercises, instead of empirical approaches, should have biologi-
cal meaning for which specific experimental data should be obtained on the optimum
versus enhanced growth, metabolic cycles, assimilation efficiencies, that is, con-
version of substrate into reserves, accumulation, and product sysnthesis/excretion.
Scott et al. (2010) commented that there is an inadequacy of established background
knowledge in this area, and there is a need to integrate biology and engineering.
The central theme rests on the predictive aspects of modeling that enable one
to determine the exact quantities of the envisaged end product together with co-
products. To estimate the actual quantities, we require appropriate input data regard-
ing culture conditions, harvest efficiencies, and yield of co-products, as outlined
above. The effective price for the microalgae-derived biofuels can be calculated by
optimizing the cost functional involving several variables under appropriately for-
mulated constraints. Results obtained from all stages of the process constitute the
vital parameters in the mathematical model. As the process is dynamic in charac-
ter, time delays do occur in a natural way, and these delays account for the process
lead-time. We need to estimate these time delays, maintaining the stability of the
corresponding delay-free systems. Division rates of the reaction mechanisms play
a vital role in the process of restoring and/or maintaining the stability of the pro-
cesses. Simulations based on realistic data will grossly help in the validation of these
models. Thoroughly validated models are utilized for predicting the optimal cost of
biofuel under conditions where lipid yields are maximum.
Williams and Laurens (2010) argued that a fundamental change in the approaches
to production is needed, and that “biofuel-only” options may not be economically
viable. They showed that 30% to 50% of primary production is lost in the produc-
tion of protein and lipid, and that if lipid production is increased, then production
of other valuable co-products is reduced. These authors argue that the availabil-
ity of nutrients such as phosphorus and nitrogen, delivery of CO
2
, and the energy
costs associated with sterilization and recycling of spent culture water
and removal
of biological contaminants, pathogens, and predators would escalate production of
microalgal biomass and could be “show-stoppers.”
Search WWH ::
Custom Search