Quantification of microbial productivity via multi-angle light scattering and supervised learning
✍ Scribed by Alun Jones; Danielle Young; Janet Taylor; Douglas B. Kell; Jem J. Rowland
- Publisher
- John Wiley and Sons
- Year
- 1998
- Tongue
- English
- Weight
- 266 KB
- Volume
- 59
- Category
- Article
- ISSN
- 0006-3592
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✦ Synopsis
This article describes the use of chemometric methods for prediction of biological parameters of cell suspensions on the basis of their light scattering profiles. Laser light is directed into a vial or flow cell containing media from the suspension. The intensity of the scattered light is recorded at 18 angles. Supervised learning methods are then used to calibrate a model relating the parameter of interest to the intensity values. Using such models opens up the possibility of estimating the biological properties of fermentor broths extremely rapidly (typically every 4 sec), and, using the flow cell, without user interaction. Our work has demonstrated the usefulness of this approach for estimation of yeast cell counts over a wide range of values (10 5 -10 9 cells mL -1 ), although it was less successful in predicting cell viability in such suspensions.