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Basic Protocols in Predictive Food Microbiology 2023 ed. [Hardback]

  • Formāts: Hardback, 235 pages, height x width: 254x178 mm, weight: 671 g, 35 Illustrations, color; 13 Illustrations, black and white; XII, 235 p. 48 illus., 35 illus. in color., 1 Hardback
  • Sērija : Methods and Protocols in Food Science
  • Izdošanas datums: 10-Sep-2023
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1071634127
  • ISBN-13: 9781071634127
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  • Hardback
  • Cena: 198,63 €*
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  • Formāts: Hardback, 235 pages, height x width: 254x178 mm, weight: 671 g, 35 Illustrations, color; 13 Illustrations, black and white; XII, 235 p. 48 illus., 35 illus. in color., 1 Hardback
  • Sērija : Methods and Protocols in Food Science
  • Izdošanas datums: 10-Sep-2023
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1071634127
  • ISBN-13: 9781071634127
Citas grāmatas par šo tēmu:
This volume details well-established protocols and procedures being used by laboratories and the industry to study Predictive Microbiology in Foods. Chapters guide readers through methods to design and collect data to generate predictive models, the development of a predictive model, approaches the behavior mainly, and experiments in predictive microbiology. Written in the format of the Methods and Protocols in Food Science series, chapters list necessary materials and methods for readily reproducible protocols.





 Authoritative and cutting-edge, Predictive Food Microbiology aims to be a foundation for future studies and to be a source of inspiration for new investigations in the field.  
Basic Concepts for Predictive Microbiology.- Methods of Inoculation and
Quantification for Collecting Data on Microbial Responses in Foods.- The
influence of food matrices on microbial growth.- Primary Predictive Models of
Microbial Growth.- A protocol for predictive modeling of microbial
inactivation based on experimental data.- Growth/ no-growth microbial models
in food science.- Individual-cell-based Modeling for Microbial Growth and
Inactivation using Time-lapse Microscopy.- Dynamic Models for Predictive
Microbiology.- Mathematical simulation of the bio-protective effect of lactic
acid bacteria on foodborne pathogens.- Acceptable Prediction Zones Method for
Validation of Predictive Models for Foodborne Pathogens.- Predictive Modeling
for Spoilage Microorganisms.- Quantitative PCR Technique for Predictive
Models.