122 related articles for article (PubMed ID: 25500394)
1. Software for predictive microbiology and risk assessment: a description and comparison of tools presented at the ICPMF8 Software Fair.
Tenenhaus-Aziza F; Ellouze M
Food Microbiol; 2015 Feb; 45(Pt B):290-9. PubMed ID: 25500394
[TBL] [Abstract][Full Text] [Related]
2. 'MicroHibro': A software tool for predictive microbiology and microbial risk assessment in foods.
González SC; Possas A; Carrasco E; Valero A; Bolívar A; Posada-Izquierdo GD; García-Gimeno RM; Zurera G; Pérez-Rodríguez F
Int J Food Microbiol; 2019 Feb; 290():226-236. PubMed ID: 30368088
[TBL] [Abstract][Full Text] [Related]
3. Application of predictive modelling techniques in industry: from food design up to risk assessment.
Membré JM; Lambert RJ
Int J Food Microbiol; 2008 Nov; 128(1):10-5. PubMed ID: 18701182
[TBL] [Abstract][Full Text] [Related]
4. Food engineering and predictive microbiology: on the necessity to combine biological and physical kinetics.
Mafart P
Int J Food Microbiol; 2005 Apr; 100(1-3):239-51. PubMed ID: 15854709
[TBL] [Abstract][Full Text] [Related]
5. Special issue on 10th international conference of predictive modelling in foods: Towards a new paradigm in predictive microbiology.
Pérez-Rodríguez F; Carrasco E; Pradhan AK; Sant'Ana AS; Valdramidis VP; Valero A
Int J Food Microbiol; 2019 Feb; 291():65-66. PubMed ID: 30463031
[No Abstract] [Full Text] [Related]
6. Quantitative risk assessment from farm to fork and beyond: a global Bayesian approach concerning food-borne diseases.
Albert I; Grenier E; Denis JB; Rousseau J
Risk Anal; 2008 Apr; 28(2):557-71. PubMed ID: 18419669
[TBL] [Abstract][Full Text] [Related]
7. Predicting mycotoxins in foods: a review.
Garcia D; Ramos AJ; Sanchis V; Marín S
Food Microbiol; 2009 Dec; 26(8):757-69. PubMed ID: 19835759
[TBL] [Abstract][Full Text] [Related]
8. Predictive microbiology models vs. modeling microbial growth within Listeria monocytogenes risk assessment: what parameters matter and why.
Pouillot R; Lubran MB
Food Microbiol; 2011 Jun; 28(4):720-6. PubMed ID: 21511132
[TBL] [Abstract][Full Text] [Related]
9. [Predictive microbiology. Toward an operational tool to help our appraisal].
Jolivet P
Ann Pharm Fr; 2000 Dec; 58(6 Suppl):475-81. PubMed ID: 11148386
[TBL] [Abstract][Full Text] [Related]
10. Lessons from the organization of a proficiency testing program in food microbiology by interlaboratory comparison: analytical methods in use, impact of methods on bacterial counts and measurement uncertainty of bacterial counts.
Augustin JC; Carlier V
Food Microbiol; 2006 Feb; 23(1):1-38. PubMed ID: 16942983
[TBL] [Abstract][Full Text] [Related]
11. [Predictive microbiology and risk assessment].
Hildebrandt G; Kleer J
Dtsch Tierarztl Wochenschr; 2004 May; 111(5):195-200. PubMed ID: 15233338
[TBL] [Abstract][Full Text] [Related]
12. [Application of predictive microbiology in fungi growth and mycotoxin production].
Wang W; Yu H; Li F
Wei Sheng Yan Jiu; 2009 Nov; 38(6):753-6. PubMed ID: 20047240
[TBL] [Abstract][Full Text] [Related]
13. Information systems in food safety management.
McMeekin TA; Baranyi J; Bowman J; Dalgaard P; Kirk M; Ross T; Schmid S; Zwietering MH
Int J Food Microbiol; 2006 Dec; 112(3):181-94. PubMed ID: 16934895
[TBL] [Abstract][Full Text] [Related]
14. Letter to the editor of the International Journal of Food Microbiology on software to calculate food safety.
Peleg M
Int J Food Microbiol; 2007 Aug; 118(1):97-8. PubMed ID: 17588700
[No Abstract] [Full Text] [Related]
15. Mathematical modelling methodologies in predictive food microbiology: a SWOT analysis.
Ferrer J; Prats C; López D; Vives-Rego J
Int J Food Microbiol; 2009 Aug; 134(1-2):2-8. PubMed ID: 19217180
[TBL] [Abstract][Full Text] [Related]
16. A risk assessment approach applied to the growth of Erwinia carotovora in vegetable juice for variable temperature conditions.
Shorten PR; Soboleva TK; Pleasants AB; Membré JM
Int J Food Microbiol; 2006 May; 109(1-2):60-70. PubMed ID: 16507324
[TBL] [Abstract][Full Text] [Related]
17. Highlights from the 8th International Conference on Predictive Modelling in Food (ICPMF8).
Ellouze M; Tenenhaus-Aziza F; Carlin F
Food Microbiol; 2015 Feb; 45(Pt B):160-1. PubMed ID: 25500380
[No Abstract] [Full Text] [Related]
18. Bioinactivation: Software for modelling dynamic microbial inactivation.
Garre A; Fernández PS; Lindqvist R; Egea JA
Food Res Int; 2017 Mar; 93():66-74. PubMed ID: 28290281
[TBL] [Abstract][Full Text] [Related]
19. Combined physico-chemical and water transfer modelling to predict bacterial growth during food processes.
Lebert I; Dussap CG; Lebert A
Int J Food Microbiol; 2005 Jul; 102(3):305-22. PubMed ID: 16014298
[TBL] [Abstract][Full Text] [Related]
20. Modelling microbial growth in structured foods: towards a unified approach.
Wilson PD; Brocklehurst TF; Arino S; Thuault D; Jakobsen M; Lange M; Farkas J; Wimpenny JW; Van Impe JF
Int J Food Microbiol; 2002 Mar; 73(2-3):275-89. PubMed ID: 11934035
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
