Monitoring polyhydroxyalkanoate production from wastes with at-line near-infrared spectroscopy

Ciprietti, Giulia (2020) Monitoring polyhydroxyalkanoate production from wastes with at-line near-infrared spectroscopy. [Laurea magistrale], Università di Bologna, Corso di Studio in Ingegneria chimica e di processo [LM-DM270], Documento full-text non disponibile
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Bio-relate polymers are showing to have an increasing and important role to moving forward a more sustainable society, given the currently problems related to common plastic disposal. Among these ”green” most promising polymers, polyhydroxyalkanoates (PHA) are aliphatic polyesters synthesized by bacteria and stored as intracellular granules, completely bio-based and bio-degradable. In this study, poly(3-hydroxybutyrate), P(3HB) was produced by a mixed microbial culture fed with a fermented confectionary’s wastewater. The two stages production process was monitored at-line by NIR spectroscopy to develop a quantitative model for predict intracellular PHA content (%), one of the most important parameters in the production process. NIR spectral data were used for the development of calibration models through partial least squares (PLS) regression. The models were subjected to cross-validation and external test set validation and proved to be suitable for predicting the parameter under study. With the selected model intracellular PHA content was predicted with a root mean square error of prediction (RMSEP) of 3,10% and a coefficient of determination (R2) of 0,92. The present study’s results confirm that NIR spectra actually contain information regarding intracellular chemical compounds and the applicability of NIR spectroscopy as powerful tool in PHA production process monitoring.

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Ciprietti, Giulia
Relatore della tesi
Corso di studio
Ingegneria di processo
Ordinamento Cds
Parole chiave
Polyhydroxyalkanoates,Mixed Microbial Culture,Bioreactor Monitoring,Near-Infrared Spectroscopy,Multivariate Analysis.
Data di discussione della Tesi
13 Marzo 2020

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