FN Archimer Export Format
PT J
TI Predicting growth rates and growth boundary of Listeria monocytogenes - An international validation study with focus on processed and ready-to-eat meat and seafood
BT 
AF MEJLHOLM, Ole
   GUNVIG, Annemarie
   BORGGAARD, Claus
   BLOM-HANSSEN, Jesper
   MELLEFONT, Lyndal
   ROSS, Tom
   LEROI, Francoise
   ELSE, Tony
   VISSER, Diana
   DALGAARD, Paw
AS 1:1;2:2;3:2;4:2;5:3;6:3;7:4;8:5;9:5;10:1;
FF 1:;2:;3:;4:;5:;6:;7:PDG-DOP-DCN-BRM-STBM;8:;9:;10:;
C1 Tech Univ Denmark, Natl Food Inst DTU Food, Div Seafood Res, DK-2800 Lyngby, Denmark.
   DMRI, Roskilde, Denmark.
   Univ Tasmania, TIAR, Hobart, Tas, Australia.
   IFREMER, Dept Sci & Tech Alimentaires Marines, Nantes, France.
   PURAC Biochem Bv, Gorinchem, Netherlands.
C2 UNIV TECH DENMARK (DTU AQUA), DENMARK
   DMRI, DENMARK
   UNIV TASMANIA, AUSTRALIA
   IFREMER, FRANCE
   PURAC BIOCHEM BV, NETHERLANDS
SI NANTES
SE PDG-DOP-DCN-BRM-STBM
IN WOS Ifremer jusqu'en 2018
   copubli-europe
   copubli-int-hors-europe
IF 3.143
TC 87
UR https://archimer.ifremer.fr/doc/00011/12218/11422.pdf
LA English
DT Article
DE ;Predictive models;Bias and accuracy factors;Correct prediction percentage;Growth/no-growth predictions;Psi (psi) value
AB The performance of six predictive models for Listeria monocytogenes was evaluated using 1014 growth responses of the pathogen in meat, seafood, poultry and dairy products. The performance of the growth models was closely related to their complexity i.e. the number of environmental parameters they take into account. The most complex model included the effect of nine environmental parameters and it performed better than the other less complex models both for prediction of maximum specific growth rates (mu(max) values) and for the growth boundary of L. monocytogenes. For this model bias and accuracy factors for growth rate predictions were 1.0 and 1.5, respectively, and 89% of the growth/no-growth responses were correctly predicted. The performance of three other models, including the effect of five to seven environmental parameters, was considered acceptable with bias factors of 1.2 to 1.3. These models all included the effect of acetic acid/diacetate and lactic acid, one of the models also included the effect of CO2 and nitrite but none of these models included the effect of smoke components. Less complex models that did not include the effect of acetic acid/diacetate and lactic acid were unable to accurately predict growth responses of L. monocytogenes in the wide range of food evaluated in the present study. When complexity of L monocytogenes growth models matches the complexity of foods of interest. i.e. the number of hurdles to microbial growth, then predicted growth responses of the pathogen can be accurate. The successfully validated models are useful for assessment and management of L monocytogenes in processed and ready-to-eat (RTE) foods. (C) 2010 Elsevier B.V. All rights reserved.
PY 2010
PD JUN
SO International Journal Of Food Microbiology
SN 0168-1605
PU Elsevier Science Bv
VL 141
IS 3
UT 000280343600001
BP 137
EP 150
DI 10.1016/j.ijfoodmicro.2010.04.026
ID 12218
ER

EF