experimental work has been presented to confirm this [107]. In fact, in earlier
studies, Barstow et al. [162] reported temperature differences of up to 3 °C
across the bioreactor. The model was used to investigate the predicted effects on
the performance of the laboratory scale bioreactor of variations in the inlet air
flowrate, the overall heat transfer coefficient from the drum to the surrounding
air, the inlet air relative humidity, and the inlet air flowrate. This model highlighted the importance of evaporation and the airflow rate in temperature control. In addition, through an analysis of the model, in which both the growth
rate and the maximum biomass concentration were functions of moisture content and temperature, Sargantanis et al. [107] determined the optimal temporal
profiles of substrate bed temperature and moisture content. Regarding temperature, optimum performance was predicted to be obtained with a temporal
bed temperature profile in the shape of a rectangular hyperbola, with the
temperature increasing from 33 °C to 38.8 °C during the first 15 h of the
fermentation, and then a negligible increase after that. Regarding moisture
content, optimum performance was predicted for a steady increase from 56.5%
to 64% moisture over the first 25 h of the fermentation and then a negligible
increase in moisture content after that. Such an analysis could be important in
the design of on-line control strategies. However, they only identified the
optimum profiles for the bed temperature and moisture content, the values of
which depend on the operating conditions. They did not use their model to
explore how the operating conditions should be manipulated in order to ensure
that these optimum profiles would actually be obtained.
5.5.4
Evaluation of Mixed Aerated Bioreactors
The gas-solid fluidized bed gives the best heat transfer performance of all SSF
bioreactors. However, relatively little information is available about design and
operation. Any increases in productivity over other bioreactor types must also
be weighed against the increased operating costs associated with the relatively
high aeration rates needed to achieve fluidization. The stirred-bed design of
Durand and Chereau [2] has been successfully demonstrated at a scales of 25
tonnes of moist substrate. It will probably remain the bioreactor of choice for
those SSF processes in which mixing can be tolerated. Rocking drum bioreactors, on the other hand, have only been used on the laboratory scale, and
there is no information about their performance on the large scale.
6
Approaches to Scale-Up of SSF Bioreactors
There has been a significant advance in our understanding of scale-up of SSF
bioreactors since the largely qualitative review on this topic by Lonsane et al. in
1992 [165]. These advances have been achieved by applying mass and energy
balances to describe the operation of SSF bioreactors. This work is still in
progress. There are not yet any reports describing how such quantitative approaches have been used in the design of a commercial scale SSF bioreactor.
Biochemical Engineering Aspects of Solid State Bioprocessing
117
studies, Barstow et al. [162] reported temperature differences of up to 3 °C
across the bioreactor. The model was used to investigate the predicted effects on
the performance of the laboratory scale bioreactor of variations in the inlet air
flowrate, the overall heat transfer coefficient from the drum to the surrounding
air, the inlet air relative humidity, and the inlet air flowrate. This model highlighted the importance of evaporation and the airflow rate in temperature control. In addition, through an analysis of the model, in which both the growth
rate and the maximum biomass concentration were functions of moisture content and temperature, Sargantanis et al. [107] determined the optimal temporal
profiles of substrate bed temperature and moisture content. Regarding temperature, optimum performance was predicted to be obtained with a temporal
bed temperature profile in the shape of a rectangular hyperbola, with the
temperature increasing from 33 °C to 38.8 °C during the first 15 h of the
fermentation, and then a negligible increase after that. Regarding moisture
content, optimum performance was predicted for a steady increase from 56.5%
to 64% moisture over the first 25 h of the fermentation and then a negligible
increase in moisture content after that. Such an analysis could be important in
the design of on-line control strategies. However, they only identified the
optimum profiles for the bed temperature and moisture content, the values of
which depend on the operating conditions. They did not use their model to
explore how the operating conditions should be manipulated in order to ensure
that these optimum profiles would actually be obtained.
5.5.4
Evaluation of Mixed Aerated Bioreactors
The gas-solid fluidized bed gives the best heat transfer performance of all SSF
bioreactors. However, relatively little information is available about design and
operation. Any increases in productivity over other bioreactor types must also
be weighed against the increased operating costs associated with the relatively
high aeration rates needed to achieve fluidization. The stirred-bed design of
Durand and Chereau [2] has been successfully demonstrated at a scales of 25
tonnes of moist substrate. It will probably remain the bioreactor of choice for
those SSF processes in which mixing can be tolerated. Rocking drum bioreactors, on the other hand, have only been used on the laboratory scale, and
there is no information about their performance on the large scale.
6
Approaches to Scale-Up of SSF Bioreactors
There has been a significant advance in our understanding of scale-up of SSF
bioreactors since the largely qualitative review on this topic by Lonsane et al. in
1992 [165]. These advances have been achieved by applying mass and energy
balances to describe the operation of SSF bioreactors. This work is still in
progress. There are not yet any reports describing how such quantitative approaches have been used in the design of a commercial scale SSF bioreactor.
Biochemical Engineering Aspects of Solid State Bioprocessing
117