(620at) A Novel Soft Sensor Approach for Estimating Individual Biomass in Mixed Cultures (Rapid Fire)

Authors: 
Stone, K., Auburn University
Shah, D., Auburn University
He, Q. P., Auburn University
Wang, J., Auburn University

A
novel soft sensor approach for estimating individual biomass in mixed cultures

Kyle
Stone1, Devarshi Shah1, Q. Peter He2, and Jin
Wang1

1Department
of Chemical Engineering, Auburn University, Auburn, AL, 36849, USA

2Department
of Chemical Engineering, Tuskegee University, Tuskegee, AL, 36088, USA
Abstract:

Mixed cultures are ubiquitous in nature but their
applications as biocatalysts in biochemical processes have been very limited.
Until recently the application of mixed culture has been limited to wastewater
treatment, but more diversified applications have started to emerge. For
instance, Norferm Danmark A/S utilized a mixed culture of Methylococcus capsulatus
(Bath) with  heterotrophic bacteria to sustain growth on methane in a process
to convert biomass into single cell protein for animal feed[1],
and co-culture of xylose-fermenting strains have been paired with Saccharomyces
cerevisiae
to ferment lignocellulosic hydrolysate[2],
[3].
Compared to single culture, there are several benefits of mixed culture. For
example, a mixed culture can provide more versatile metabolic machinery due to
a larger pool of collective genes, and tend to be more robust to different
disturbances such as variations in feedstock composition and operation
conditions. The main reason for the limited application of mixed culture
approach is the difficulty associated with modeling, understanding and
controlling of mixed culture.

To understand the metabolomic interactions of a mixed
culture, quantitative analyses that can differentiate the dynamic properties of
the mixed culture from those of monoculture are essential. One of the
challenges in studying a mixed culture is to obtain the biomass concentration
of each organism in the mixed culture. Cell count and fluorescent labelling
have been used for microbial enumeration in mixed culture. But the former is
time consuming and may not be accurate; the latter is also time consuming and
may lack genetic tools and experimental protocols for some microbes. To address
this challenge, we propose an absorbance spectra-based soft sensor to estimate
individual biomass concentration in a mixed culture.

Soft sensor is commonly used in analytical chemistry
and process industry to estimate variables (such as concentration) that are
difficult to measure by using other easily obtainable measurements (such as
absorbance spectra) [4],
[5].
In this work, we propose to use absorbance spectra of the mixed culture broth,
instead of the absorbance at a single wavelength, to estimate the biomass
concentration of each individual strain. The proposed procedure is shown below:

Case studies are carried out to show that the
proposed soft sensor is highly accurate in estimating the individual biomass
concentration from absorbance spectra of the mixed culture.

References:

[1]        H.
Bothe, K. M. Jensen, A. Mergel, J. Larsen, C. Jørgensen, H. Bothe, and L.
Jørgensen, ?Heterotrophic bacteria growing in association with Methylococcus
capsulatus (Bath) in a single cell protein production process,? Appl.
Microbiol. Biotechnol., vol. 59, pp. 33?39, 2002.

[2]        M.
H. Kim, M. Liang, Q. P. He, and J. Wang, ?A novel reactor for systematic
investiagtion of co-culture systems,? Bioresour. Technol., (submitted) 2015.

[3]        M.
H. Kim, M. Liang, Q. P. He, and J. Wang, ?Simultaneous fermentation of glucose
and xylose by co-culture in a novel bioreactor,? in Proceedings of Sun Grant
Initiative 2012 National Conference, 2012, pp. 97?101.

[4]        H.
J. Galicia, Q. P. He, and J. Wang, ?Comparison of the performance of a
reduced-order dynamic PLS soft sensor with different updating schemes for
digester control,? Control. Eng. Pract., vol. 20, pp. 747?760, 2012.

[5]        H.
J. Galicia, Q. P. He, and J. Wang, ?A reduced order soft sensor approach and
its application to a continuous digester,? J. Process. Control., vol. 21, pp.
489?500, 2011.