Skip to main content

Probabilistic modelling of Aspergillus growth

  • Conference paper
Advances in Food Mycology

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 571))

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Alavi, S. H., Puri, V. M., Knabel, S. J., Mohtar, R. H., and Whiting, R. C., 1999, Development and validation of a dynamic growth model for Listeria monocytogenes in fluid whole milk, J. Food Prot. 62:170–176.

    CAS  Google Scholar 

  • Alzamora, S.M., and López-Malo, A., 2002, Microbial behavior modeling as a tool in the design and control of minimally processed foods, in: Engineering and Food for the 21st Century, J. Welti-Chanes, G. V. Barbosa-Canovas, and J. M. Aguilera, eds, CRC Press, Boca Raton, FL, pp. 631–650.

    Google Scholar 

  • Baranyi, J., and Roberts, T. A., 1994, A dynamic approach to predicting bacterial growth in food, Int. J. Food Microbiol. 23:277–294.

    Article  CAS  Google Scholar 

  • Bolton, L. F., and Frank, J. F., 1999, Defining the growth/no growth interface for Listeria monocytogenes in Mexican-style cheese based on salt, pH and moisture content, J. Food Prot. 62:601–609.

    CAS  Google Scholar 

  • Cole, M. B., Franklin, J. G., and Keenan, M. H. J., 1987, Probability of growth of the spoilage yeast Zygosaccharomyces bailii in a model fruit drink system, Food Microbiol. 4:115–119.

    Article  Google Scholar 

  • Cuppers, H. G. M., Oomes, S., and Brul, S., 1997, A model for the combined effects of temperature and salt concentration on growth rate of food spoilage moulds, Appl. Environ. Microbiol. 63:3764–3769.

    CAS  Google Scholar 

  • Gibson, A. M., Baranyi, J., Pitt, J. I., Eyles, M. J., and Roberts, T. A., 1994, Predicting fungal growth: effect of water activity on Aspergillus flavus and related species, Int. J. Food Microbiol. 23:419–431.

    Article  CAS  Google Scholar 

  • Gould, G. W., 1989, Mechanisms of Action of Food Preservation Procedures, Elsevier, London.

    Google Scholar 

  • Hosmer, D. W., and Lemeshow, S., 1989, Applied Logistic Regression, John Wiley and Sons, New York, p. 307.

    Google Scholar 

  • ICMSF (International Commission on the Microbiological Specifications for Foods), 1980, Microbial Ecology of Foods, Vol. 1. Factors Affecting Life and Death of Microorganisms. ICMSF, Academic Press, New York.

    Google Scholar 

  • Lanciotti, R., Sinigaglia, M., Gardini, F., Vannini, L., and Guerzoni, M. E., 2001, Growth/no growth interfaces of Bacillus cereus, Staphylococcus aureus and Salmonella enteritidis in model systems based on water activity, pH, temperature and ethanol concentration, Food Microbiol. 18:659–668.

    Article  CAS  Google Scholar 

  • Leistner, L., 1985, Hurdle technology applied to meat products of shelf stable and intermediate moisture food types, in: Properties of Water in Foods in Relation to Quality and Stability, D. Simatos, and J. L. Multon, ed., Martinus Nihof Publishers, Dordrecht, The Netherlands, pp. 309–329.

    Google Scholar 

  • López-Malo, A., and Palou E., 2000a, Growth/no growth interface of Zygosaccharomyces bailii as a function of temperature, water activity, pH, potassium sorbate and sodium benzoate concentration, Presented at Predictive Modeling in Foods, Leuven, Belgium, September 12–15.

    Google Scholar 

  • López-Malo, A., and Palou E., 2000b, Modeling the growth/no growth interface of Zygosaccharomyces bailii in mango puree, J. Food Sci. 65:516–520.

    Article  Google Scholar 

  • López-Malo, A., Alzamora, S. M., Argaiz, A., 1998, Vanillin and pH synergistic effects on mold growth, J. Food Sci. 63:143–146.

    Article  Google Scholar 

  • López-Malo, A., Guerrero, S., and Alzamora, S. M., 2000, Probabilistic modeling of Saccharomyces cerevisiae inhibition under the effects of water activity, pH and potassium sorbate, J. Food Prot. 63:91–95.

    Google Scholar 

  • López-Malo, A., Palou, E., and Argaiz, A., 1993, Medición de la actividad de agua con un equipo electrónico basado en el punto de rocío, Información Tecnológica. 4(6): 33–37.

    Google Scholar 

  • Masana, M. O., and Baranyi, J., 2000a, Adding new factors to predictive models: the effect on the risk of extrapolation, Food Microbiol. 17:367–374.

    Article  Google Scholar 

  • Masana, M. O., and Baranyi, J., 2000b, Growth/no growth interface of Brochothrix thermosphacta as a function of pH and water activity, Food Microbiol. 17:485–493.

    Article  Google Scholar 

  • McMeekin, T. A., Olley, J., Ross, T., and Ratkowsky, D. A., 1993, Predictive Microbiology: Theory and Application, Research Studies Press, Tauton, UK.

    Google Scholar 

  • McMeekin, T. A., Presser, K., Ratkowsky, D. A., Ross, T., Salter, M., and Tienungoon, S., 2000, Quantifying the hurdle concept by modelling the growth/no growth interface. A review, Int. J. Food Microbiol. 55:93–98.

    Article  CAS  Google Scholar 

  • McMeekin, T. A., Ross, T., and Olley, J., 1992, Application of predictive microbiology to assure the quality and safety of fish and fish products, Int. J. Food Microbiol. 15:13–32.

    Article  CAS  Google Scholar 

  • Montgomery, D. C., 1984, Design and Analysis of Experiments, John Wiley and Sons, New York.

    Google Scholar 

  • Palou, E., and López-Malo, A., 2004, Growth/no-growth interface modeling and emerging technologies, in: Novel Food Processing Technologies, G. V. Barbosa-Canovas, M. S. Tapia, and P. Cano, eds, Marcel Dekker, New York, pp. 629–651.

    Google Scholar 

  • Pitt, J. I., 1989, Food mycology–an emerging discipline, Soc. Appl. Bacteriol. Symp. Suppl. 1989:1S–9S.

    Google Scholar 

  • Pitt, J. I., and Hocking, A. D., 1977, Influence of solute and hydrogen ion concentration on the water relations of some xerophilic fungi, J. Gen. Microbiol. 101:35–40.

    CAS  Google Scholar 

  • Pitt, J. I., and Miscamble, B. F., 1995, Water relations of Aspergillus flavus and closely related species, J. Food Prot. 58:86–90.

    Google Scholar 

  • Presser, K. A., Ross, T., and Ratkowsky, D. A., 1998, Modelling of the growth limits (growth/no-growth) of Escherichia coli as a function of temperature, pH, lactic acid concentration, and water activity, Appl. Environ. Microbiol. 64:1773–1779.

    CAS  Google Scholar 

  • Ratkowsky, D. A., and Ross, T., 1995, Modelling the bacterial growth/no-growth interface, Lett. Appl. Microbiol. 20:29–33.

    Article  CAS  Google Scholar 

  • Ratkowsky, D. A., 1993, Principles of modelling, J. Indust. Microbiol. 12:195–199.

    Article  Google Scholar 

  • Ratkowsky, D. A., Ross, T., McMeekin, T. A., and Olley, J., 1991, Comparison of Arrhenius-type and Belehradek-type models for prediction of bacterial growth in foods, J. Appl. Bacteriol. 71:452–459.

    Google Scholar 

  • Ross, T., and McMeekin, T. A., 1994, Predictive microbiology, Int. J. Food Microbiol. 23:241–264.

    Article  CAS  Google Scholar 

  • Rosso, L., and Robinson, T. P., 2001, Cardinal model to describe the effect of water activity on the growth of moulds, Int. J. Food Microbiol. 63:265–273.

    Article  CAS  Google Scholar 

  • Salter, M. A., Ratkowsky, D. A., Ross, T., and McMeekin, T. A., 2000, Modelling the combined temperature and salt (NaCl) limits for growth of a pathogenic Escherichia coli strain using nonlinear logistic regression, Int. J. Food Microbiol. 61:159–167.

    Article  CAS  Google Scholar 

  • Samson, R. A., 1989, Filamentous fungi in food and feed, Soc. Appl. Bacteriol. Symp. Suppl. 1989:27S–35S.

    Google Scholar 

  • Schaffner, D. W., and Labuza, T. P., 1997, Predictive microbiology: where are we, and where are we going?, Food Technol. 51:95–99.

    Google Scholar 

  • Smith, J. E., and Moss, M.O., 1985, Mycotoxins, Formation, Analysis and Significance, John Wiley and Sons, Chichester, UK.

    Google Scholar 

  • Tienungoon, S., Ratkowsky, D. A., McMeekin, T. A., and Ross, T., 2000, Growth limits of Listeria monocytogenes as a function of temperature, pH, NaCl, and lactic acid, Appl. Environ. Microbiol. 11:4979–4987.

    Article  Google Scholar 

  • Valik, L., Baranyi, J., and Gorner, F., 1999, Predicting fungal growth: the effect of water activity on Penicillium roqueforti, Int. J. Food Microbiol. 47:141–146.

    Article  CAS  Google Scholar 

  • Whiting, R. C., and Call, J. E., 1993, Time of growth model for proteolytic Clostridium botulinum, Food Microbiol. 10:295–301.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer

About this paper

Cite this paper

Palou, E., López-Malo, A. (2006). Probabilistic modelling of Aspergillus growth. In: Hocking, A.D., Pitt, J.I., Samson, R.A., Thrane, U. (eds) Advances in Food Mycology. Advances in Experimental Medicine and Biology, vol 571. Springer, Boston, MA. https://doi.org/10.1007/0-387-28391-9_19

Download citation

Publish with us

Policies and ethics