Quantification of microbial productivity via multi-angle light scattering and supervised learning |
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Authors: | Jones A Young D Taylor J Kell D B Rowland J J |
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Affiliation: | Institute of Biological Sciences, University of Wales, ABERYSTWYTH, Ceredigion SY23 3DD, Wales, United Kingdom. auj/diy/jjt95/dbk/jjr@aber.ac.uk |
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Abstract: | 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. |
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