Modeling microbial growth and dynamics
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| 003 | CHVBK | ||
| 005 | 20210128100622.0 | ||
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| 008 | 210128e20151101xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00253-015-6877-6 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00253-015-6877-6 | ||
| 245 | 0 | 0 | |a Modeling microbial growth and dynamics |h [Elektronische Daten] |c [Daniel Esser, Johan Leveau, Katrin Meyer] |
| 520 | 3 | |a Modeling has become an important tool for widening our understanding of microbial growth in the context of applied microbiology and related to such processes as safe food production, wastewater treatment, bioremediation, or microbe-mediated mining. Various modeling techniques, such as primary, secondary and tertiary mathematical models, phenomenological models, mechanistic or kinetic models, reactive transport models, Bayesian network models, artificial neural networks, as well as agent-, individual-, and particle-based models have been applied to model microbial growth and activity in many applied fields. In this mini-review, we summarize the basic concepts of these models using examples and applications from food safety and wastewater treatment systems. We further review recent developments in other applied fields focusing on models that explicitly include spatial relationships. Using these examples, we point out the conceptual similarities across fields of application and encourage the combined use of different modeling techniques in hybrid models as well as their cross-disciplinary exchange. For instance, pattern-oriented modeling has its origin in ecology but may be employed to parameterize microbial growth models when experimental data are scarce. Models could also be used as virtual laboratories to optimize experimental design analogous to the virtual ecologist approach. Future microbial growth models will likely become more complex to benefit from the rich toolbox that is now available to microbial growth modelers. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2015 | ||
| 690 | 7 | |a Model |2 nationallicence | |
| 690 | 7 | |a Bacteria |2 nationallicence | |
| 690 | 7 | |a Predictive microbiology |2 nationallicence | |
| 690 | 7 | |a Wastewater |2 nationallicence | |
| 690 | 7 | |a Food safety |2 nationallicence | |
| 700 | 1 | |a Esser |D Daniel |u Department of Ecosystem Modelling, University of Göttingen, Büsgenweg 4, 37077, Göttingen, Germany |4 aut | |
| 700 | 1 | |a Leveau |D Johan |u Department of Plant Pathology, University of California, 95616-8751, Davis, CA, USA |4 aut | |
| 700 | 1 | |a Meyer |D Katrin |u Department of Ecosystem Modelling, University of Göttingen, Büsgenweg 4, 37077, Göttingen, Germany |4 aut | |
| 773 | 0 | |t Applied Microbiology and Biotechnology |d Springer Berlin Heidelberg |g 99/21(2015-11-01), 8831-8846 |x 0175-7598 |q 99:21<8831 |1 2015 |2 99 |o 253 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00253-015-6877-6 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a review-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00253-015-6877-6 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Esser |D Daniel |u Department of Ecosystem Modelling, University of Göttingen, Büsgenweg 4, 37077, Göttingen, Germany |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Leveau |D Johan |u Department of Plant Pathology, University of California, 95616-8751, Davis, CA, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Meyer |D Katrin |u Department of Ecosystem Modelling, University of Göttingen, Büsgenweg 4, 37077, Göttingen, Germany |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Applied Microbiology and Biotechnology |d Springer Berlin Heidelberg |g 99/21(2015-11-01), 8831-8846 |x 0175-7598 |q 99:21<8831 |1 2015 |2 99 |o 253 | ||