000 03137nam a22004935i 4500
001 978-1-4614-5520-2
003 DE-He213
005 20140220082820.0
007 cr nn 008mamaa
008 121211s2013 xxu| s |||| 0|eng d
020 _a9781461455202
_9978-1-4614-5520-2
024 7 _a10.1007/978-1-4614-5520-2
_2doi
050 4 _aTP248.65.F66
072 7 _aTDCT
_2bicssc
072 7 _aTEC012000
_2bisacsh
082 0 4 _a641.3
_223
082 0 4 _a664
_223
100 1 _aPerez-Rodriguez, Fernando.
_eauthor.
245 1 0 _aPredictive Microbiology in Foods
_h[electronic resource] /
_cby Fernando Perez-Rodriguez, Antonio Valero.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aVI, 128 p. 21 illus., 11 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Food, Health, and Nutrition ;
_v5
505 0 _a1. Predictive Microbiology in Foods.- 2. Experimental Design and Data Generation -- 3. Predictive Models: Foundation, Types and Development -- 4. Other Models and Modeling Approaches -- 5. Software and Data Bases: Use and Application -- 6. Application of Predictive Models in Quantitative Risk Assessment and Risk Management -- 7. Future Trends and Perspectives.   .
520 _aPredictive microbiology is a recent area within food microbiology, which studies the responses of microorganisms in foods to environmental factors (e.g., temperature, pH) through mathematical functions. These functions enable scientists to predict the behavior of pathogens and spoilage microorganisms under different combinations of factors. The main goal of predictive models in food science is to assure both food safety and food quality.   Predictive models in foods have developed significantly in the last  20 years due to the emergence of powerful computational resources and sophisticated statistical packages. This book presents the concepts, models, most significant advances, and future trends in predictive microbiology. It will discuss the history and basic concepts of predictive microbiology. The most frequently used models will be explained, and the most significant software and databases (e.g., Combase, Sym’Previus) will be reviewed.  Quantitative Risk Assessment, which uses predictive modeling to account for the transmission of foodborne pathogens across the food chain, will also be covered.
650 0 _aChemistry.
650 0 _aMicrobiology.
650 0 _aFood science.
650 1 4 _aChemistry.
650 2 4 _aFood Science.
650 2 4 _aMicrobiology.
650 2 4 _aApplied Microbiology.
700 1 _aValero, Antonio.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461455196
830 0 _aSpringerBriefs in Food, Health, and Nutrition ;
_v5
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-5520-2
912 _aZDB-2-CMS
999 _c95432
_d95432