Document Detail

Comparing uncertainty resulting from two-step and global regression procedures applied to microbial growth models.
MedLine Citation:
PMID:  18095435     Owner:  NLM     Status:  MEDLINE    
Two different microbial modeling procedures were compared and validated against independent data for Listeria monocytogenes growth. The most generally used method is two consecutive regressions: growth parameters are estimated from a primary regression of microbial counts, and a secondary regression relates the growth parameters to experimental conditions. A global regression is an alternative method in which the primary and secondary models are combined, giving a direct relationship between experimental factors and microbial counts. The Gompertz equation was the primary model, and a response surface model was the secondary model. Independent data from meat and poultry products were used to validate the modeling procedures. The global regression yielded the lower standard errors of calibration, 0.95 log CFU/ml for aerobic and 1.21 log CFU/ml for anaerobic conditions. The two-step procedure yielded errors of 1.35 log CFU/ml for aerobic and 1.62 log CFU/ ml for anaerobic conditions. For food products, the global regression was more robust than the two-step procedure for 65% of the cases studied. The robustness index for the global regression ranged from 0.27 (performed better than expected) to 2.60. For the two-step method, the robustness index ranged from 0.42 to 3.88. The predictions were overestimated (fail safe) in more than 50% of the cases using the global regression and in more than 70% of the cases using the two-step regression. Overall, the global regression performed better than the two-step procedure for this specific application.
K G Martino; B P Marks
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of food protection     Volume:  70     ISSN:  0362-028X     ISO Abbreviation:  J. Food Prot.     Publication Date:  2007 Dec 
Date Detail:
Created Date:  2007-12-21     Completed Date:  2008-04-01     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7703944     Medline TA:  J Food Prot     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2811-8     Citation Subset:  IM    
Department of Biosystems and Agricultural Engineering, A. W. Farrall Hall, Michigan State University, East Lansing, Michigan 48824, USA.
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MeSH Terms
Bacteria, Aerobic / growth & development
Bacteria, Anaerobic / growth & development
Colony Count, Microbial / methods*
Food Contamination / analysis
Food Microbiology*
Listeria monocytogenes / growth & development*
Meat Products / microbiology
Models, Biological*
Poultry Products / microbiology
Predictive Value of Tests
Regression Analysis
Sensitivity and Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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