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Volumn , Issue , 2016, Pages 17-31

Quantifying microbial propagation

Author keywords

Beta distribution; Binomial; Microbial propagation; Monte Carlo simulation; Negative binomial; Poisson; Probability; Random variables; Uncertainty; Variability

Indexed keywords


EID: 85014310747     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1016/B978-1-78548-155-0.50002-2     Document Type: Chapter
Times cited : (11)

References (9)
  • 1
    • 84870596030 scopus 로고    scopus 로고
    • Effect of model parameter variability on the uncertainty of refrigerated microbial shelf-life estimates
    • Chotyakul N., Perez Lamela C., Torres J.A. Effect of model parameter variability on the uncertainty of refrigerated microbial shelf-life estimates. Journal of Food Process Engineering 2012, vol. 35(no. 6):829-839.
    • (2012) Journal of Food Process Engineering , vol.35 , Issue.6 , pp. 829-839
    • Chotyakul, N.1    Perez Lamela, C.2    Torres, J.A.3
  • 2
    • 39649105246 scopus 로고    scopus 로고
    • Development and validation of a probabilistic second-order exposure assessment model for Escherichia coli O157:H7 contamination of beef trimmings from Irish meat plants
    • Cummins E., Nally P., Butler F., et al. Development and validation of a probabilistic second-order exposure assessment model for Escherichia coli O157:H7 contamination of beef trimmings from Irish meat plants. Meat Science 2008, vol. 79(no. 1):139-154.
    • (2008) Meat Science , vol.79 , Issue.1 , pp. 139-154
    • Cummins, E.1    Nally, P.2    Butler, F.3
  • 3
    • 84918592927 scopus 로고    scopus 로고
    • Drivers of uncertainty in estimates of foodborne gastroenteritis incidence
    • Glass K., Ford L., Kirk M.D. Drivers of uncertainty in estimates of foodborne gastroenteritis incidence. Foodborne Pathogens and Disease 2014, vol. 11(no. 12):938-944.
    • (2014) Foodborne Pathogens and Disease , vol.11 , Issue.12 , pp. 938-944
    • Glass, K.1    Ford, L.2    Kirk, M.D.3
  • 5
    • 0034631445 scopus 로고    scopus 로고
    • Separation of uncertainty and variability in quantitative microbial risk assessment models
    • Nauta M.J. Separation of uncertainty and variability in quantitative microbial risk assessment models. International Journal of Food Microbiology 2000, vol. 57(no. 1-2):9-18.
    • (2000) International Journal of Food Microbiology , vol.57 , Issue.1-2 , pp. 9-18
    • Nauta, M.J.1
  • 6
    • 33751291827 scopus 로고    scopus 로고
    • Modeling bacterial growth in quantitative microbial risk assessment, Is it possible?
    • Nauta M.J. Modeling bacterial growth in quantitative microbial risk assessment, Is it possible?. International Journal of Food Microbiology 2002, vol. 38:45-54.
    • (2002) International Journal of Food Microbiology , vol.38 , pp. 45-54
    • Nauta, M.J.1
  • 8
    • 77955843466 scopus 로고    scopus 로고
    • Marie Evaluating variability and uncertainty separately in microbial quantitative risk assessment using two R packages
    • Pouillot R., Delignette-Muller L., Marie Evaluating variability and uncertainty separately in microbial quantitative risk assessment using two R packages. International Journal of Food Microbiology 2010, vol. 142(no. 3):330-340.
    • (2010) International Journal of Food Microbiology , vol.142 , Issue.3 , pp. 330-340
    • Pouillot, R.1    Delignette-Muller, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.