Uso de técnica de espectroscopia NIR no desenvolvimento de softsensor para monitoramento on-line da fermentação alcoólica industrial
Resumo
Automated control and monitoring of bioprocesses are fundamental tools for the modern
biotechnology industry. Chemical introduction, for example, is a biotechnological process
already well established in the sugar and alcohol industry, with high productivity and
robust microorganisms. However, one factor can still be improved: bioprocess monito-
ring. Detailed fermentation monitoring is carried out with at-line and off-line techniques,
such as High Performance Liquid Chromatography (HPLC), which implies a delay to
verify the end of fermentation and/or some disturb. NIR spectroscopy can be used to
monitor bioprocesses, inferring key variables in fermentation in real time, such as resi-
dual sugar concentration. A major difficulty in using this technique is the presence of
intense noise at frequencies, requiring pre-treatment for its use in a soft sensor. The use
of a phenomenological interference model can reduce the noise associated with experi-
mental data, improving the estimation of interference variations using the chemometric
technique. Given these aspects, a methodology was developed for inferring cell concentra-
tion, substrate concentration and product concentration in a prepared fermentation. The
methodology is based on smoothing experimental data from samples using a fermentative
kinetic model. Such data were correlated with NIR spectra to adjust the chemometric
model PLSR (Partial Least Squares Regression) and construct the virtual sensor. Three
fed-batch fermentations were used to construct the detection set and three batches were
used to validate the sensor.
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