NIRS monitoring of Candida utilis biomass

BE596 Research Project – Msc in Bioprocess Engineering (MSBE), DCU Bernard Lawlor Near infrared spectroscopy in off-line biomass monitoring of Candida utilis cultures

Why monitor biomass? ,[object Object],[object Object],[object Object],[object Object]

Project Objective ,[object Object],[object Object]

Biomass Sampling Groups ,[object Object],[object Object],[object Object]

On-line sensor positioning for bioreactors Figure 1 taken from Cervera, A. et al. (2009)

NIRS- How it Works ,[object Object],[object Object],[object Object],[object Object],[object Object]

NIRS - Theory ,[object Object],[object Object],[object Object],[object Object]

NIRS- How it Works ,[object Object],[object Object],[object Object],[object Object],Figure 2 Schematic diagram of a dispersive instrument (Mustafe, A .) 2005

NIRS- How it Works ,[object Object],[object Object],[object Object],[object Object],[object Object],Figure 3. Diagram of a simple interferometer obtained from The National Physics Laboratory. UK.

NIRS- How it Works ,[object Object],[object Object],[object Object],[object Object],[object Object],Figure 4. Diagram of FT-NIRS instrument and transflectance probe. www.ABB.com

Chemometrics ,[object Object],[object Object],[object Object],[object Object]

Chemometrics ,[object Object],[object Object],[object Object]

Cell Culturing ,[object Object],[object Object],[object Object],[object Object],[object Object]

Analysis: Haemocytometer ,[object Object],[object Object],[object Object],[object Object]

Analysis: Dry Cell Weight ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Analysis: Biomass Monitor ,[object Object],[object Object],[object Object],[object Object]

Analysis: NIRS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Experiment Designs ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Calibration Models Construction ,[object Object],[object Object],[object Object],[object Object],[object Object]

Results ,[object Object],[object Object],[object Object],[object Object],[object Object],Figure 5. haemocytometer method results for culture A and B at 21.8 x 106 cells/mL and 27.0 x 106 cells/mL respectively . Figure 6 . Dry Cell Weight methods results for culture A and B at 13.466 g/L and 15.933 g/L respectively.

Results ,[object Object],[object Object],[object Object],[object Object],[object Object],Figure 9. DCW readings against NIRS scans and chemometric analysis with supernatant background. Calibration model produced RMSECV of 7.2 g/L and a % Error value of 93 %. Figure 11. Haemocytometer readings against the NIRS scans and chemometric analysis with supernatant background. Calibration model produced RMSECV of 33.2 x 10 6 cell/ml and a % Error value of 122 %.

Results ,[object Object],[object Object],[object Object],[object Object],Figure 12. Capacitance readings against NIRS scans and chemometric analysis with an air background. Calibration model produced a RMSECV of 1.1 pF/cm and a % Error value of 18.42 %. Figure 13. Capacitance readings against NIRS scans and chemometric analysis with a supernatant background. Calibration model produced a RMSECV of 4.9 pF/cm and a % Error value of 85.1 %.

Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Figure 14. DCW readings against predicted values from NIRS scans with an Air background. Calibration model produced a RMSECV of 4.0 g/L and a % Error value of 57.8 %. Figure 17 Capacitance readings against predicted values from NIRS scans with a supernatant background. The calibration model produced a RMSECV of 1.3 pF/cm and a % Error value of 42.8 %.

Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Figure 20. DCW readings against the predicted values from NIRS scans with supernatant background. The calibration model produced a RMSECV of 1.3 g/L and a % Error value of 52.4 %. Figure 22. Capacitance readings against the predicted values from NIRS scans with a supernatant background. The calibration model produced a RMSECV of 0.7 pF/cm and a % Error value of 48.1 %.

Results ,[object Object],[object Object],[object Object],[object Object],Figure 18 Graph of DCW values against the capacitance readings obtained on the biomass monitor and trendline displaying degree of calibration (R2) Exp 3. Figure 23. Graph of DCW values against the capacitance readings obtained on the biomass monitor and trendline displaying degree of calibration (R2) Exp. 3a.

Results ,[object Object],[object Object],[object Object],Figure 24. Graph of concentration of YPG against NIRS scans with an air background. The calibration model produced a RMSECV of 9.0 % v/v and a % Error value of 17.7 %.

Results ,[object Object],[object Object],[object Object],[object Object],Figure 25. Resupended DCW readings against predicted values from NIRS scans with air background. The calibration model produced a RMSECV of 2.7 g/L and a % Error value of 47.8 %. Figure 26. Resupended DCW readings against predicted values from NIRS scans with water background. The calibration model produced a RMSECV of 2.7 g/L and a % Error value of 47.8 %.

Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object]

Conclusion ,[object Object],[object Object]

Potential future work ,[object Object],[object Object],[object Object]

Bibliography ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Bibliography ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

NIRS monitoring of Candida utilis biomass

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