University of North Florida
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Stuart Chalk, Ph.D.
Department of Chemistry
University of North Florida
Phone: 1-904-620-1938
Fax: 1-904-620-3535
Email: schalk@unf.edu
Website: @unf

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Biomass

@ ChemSpider@ NIST@ PubChem

Citations 3

"Rapid Determination Of Total Biomass From A Yeast Fermentation Using Sequential Injection"
Analyst 1994 Volume 119, Issue 8 Pages 1807-1812
P. J. Baxter, G. D. Christian and J. Ruzicka

Abstract: Samples were obtained directly from a feed-batch aerobic fermentation of Saccharomyces cerevisiae and were analyzed without pretreatment. A 38 µL sample was pulled into a holding coil via a multiport valve by means of a peristaltic pump. The sample was delivered to a stirred flow cell (volume 1.7 ml) in a water carrier stream (2.2 ml/min) containing 2 ppm of Brijj-35. The signal was recorded by measuring either total transmitted light or light scattered at 90°C. Diagrams of the sequential-injection manifold and flow cell used are given. The sample range for the assay was from 0.2 to at 800 g/l of biomass. RSD (n not given) were 3%. The total assay time was 4 min.
Fermentation broth Nephelometry Turbidimetry Sequential injection Process monitoring Surfactant Valve

"Multivariate Approach For The Simultaneous Determination Of Total Biomass And Glucose From A Yeast Fermentation By Sequential Injection Analysis"
Chem. Anal. 1995 Volume 40, Issue 4 Pages 455-471
Baxter, P.J.;Christian, G.D.;Ruzicka, J.

Abstract: The sequential injection system (diagram given) was incorporated into the circulation line of the fermentation unit. Samples (50 µL) of fermentation liquor were carried to a flow cell (Analyst, 1994, 119, 1807) in Trinder reagent (2 ml/min). The flow and stirring were stopped for 3.5 min, resumed for 20 s to dilute the sample, then stopped again while spectra were recorded from 402-800 nm with 2 nm resolution. The flow cell was then rinsed with 6 mL carrier. The assay time was 8 min. A calibration set of samples in which glucose was determined using a manual Trinder assay, and biomass was determined by the dry weight method, was used to calculate linear partial least squares calibration models. The models had excellent predictive ability for 1 g/kg biomass (average errors 3.68-6.15%). The predictive ability for 10 mg/dl glucose was less good, but identification of pulse spikes in the fermentation broth was possible.
Fermentation broth Spectrophotometry Calibration Chemometrics Sequential injection Simultaneous analysis Partial least squares

"Online And In-situ Monitoring Of Biomass In Submerged Cultivations"
Trends Biotechnol. 1997 Volume 15, Issue 12 Pages 517-522
Lisbeth Olsson and Jens Nielsen

Abstract: Biomass is one of the most important variables in submerged-cultivation processes and, in recent years, many different sensors have been introduced for online or in situ monitoring of this variable. This article provides an overview of the principles behind these sensors and discusses their application in both laboratory and industrial processes. 34 References
Fermentation broth Fluorescence Sensor Review