Abstract
The role water activity, aw, plays in microbial growth by itself or in conjunction with other factors, notably temperature and pH, has been described mathematically by different algebraic models obtained by fitting experimental growth rate vs. aw relationships. Many of these models have one, two, or all three cardinal parameters, namely the minimal, optimal, and maximal aw, in their formulation. Although they all have good fit as judged by statistical criteria, their different mathematical structures have different ramifications concerning the threshold aw for growth initiation, and the growth pattern around and beyond the optimal aw level where it exists. The focus of this review is on the biological implications of the different growth rate vs. aw models inferred exclusively from their mathematical properties, leaving out any statistical fit considerations. It also describes a recently proposed single-parameter model of monotonic or the monotonic part of experimental growth rate vs. aw curves, which can be combined with a decay term to produce a general conceptual model of peaked and monotonic microbial growth rate vs. aw relationships over the entire aw range.
Key points
• Traditional and new growth rate vs. aw models are presented and their implications compared.
• Analogy between aw and the temperature or pH effect on microbial growth rate is reassessed.
• Cardinal parameters alone do not establish a unique growth rate vs. aw relationship.
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References
Barbosa-Canovas GV, Fontana AJ Jr, Schmidt SJ, Labuza TP (eds) (2020) Water activity in foods, 2nd edn. John Wiley & Sons
Baxter CJ, Magan N, Lane B, Wildman HG (1998) Influence of water activity and temperature on in vitro growth of surface cultures of a Phoma sp. and production of the pharmaceutical metabolites, squalestatins S1 and S2. Appl Microbiol Biotechnol 49:328–332
Corradini MG, Peleg M (2007) Shelf life estimation from accelerated storage data. Trends Food Sci Technol 18:37–47
Emborg J, Dalgaard P (2008) Modelling the effect of temperature, carbon dioxide, water activity and pH on growth and histamine formation by Morganella psychrotolerans. Int J Food Microbiol 128:226–233
Feeherry FE, Doona CJ, Taub IA (2003) Effect of water activity on the growth kinetics of Staphylococcus aurus in ground bread crumbs. J Food Sci 68:982–987
Gauvry E, Mathot AG, Couvert O, Leguerinel I, Coroller L (2021) Effects of temperature, pH and water activity on the growth and the sporulation abilities of Bacillus subtilis BSB1. Int J Food Microbiol 337:108915
Gibson AM, Baranyi J, Pitt JI, Eyles MJ, Roberts TA (1994) Predicting fungal growth: the effect of water activity on Aspergillus flavus and related species. Intnl J Food Microbiol 23:419–431
Gotor -Vila A, Teixido N, Sisqulla M, Torrers R, Usall J (2017) Biological characterization of the biocontrol agent Bacillus amyloliquefaciens CPA-8: the effect of temperature, pH and water activity on growth, susceptibility to antibiotics and detection of enterotoxic genes. Curr Micorbiol 74:1089–1099
Han B-Z, Nout RMJ (2000) Effects of temperature, water activity and gas atmosphere on mycelial growth of tempeh fungi Rhizopus microsporus var. microspores and R. microsporus var. oligosporus. World J Microbiol Biotechnol 16:853–858
Kosergen CE, Ramirez-Corona N, Mani-Lopez E, Palou E, Lopez-Malo A (2017) Description of Aspergillus flavus growth under the influence of different factors (water activity, incubation temperature, protein and fat concentration, pH, and cinnamon essential oil concentration) by kinetic, probability of growth, and time-to-detection models. Int J Food Microbiol 240:115–123
Mannaa M, Kim KD (2017) Influene of temperature and water activity on deleterious fungi and mycotoxin production during grain storage. Mycobiology 45:240–254
Miles DW, Ross T, Olley J, McMeekin TA (1997) Development and evaluation of a predictive model for the effect of temperature and water activity on the growth rate of Vibrio parahaemolyticus. Int J Food Microbiol 38:133–142
Neumeyer K, Ross T, McMeekin TA (1997) Development of a predictive model to describe the effects of temperature and water activity on the growth of spoilage pseudomonads. Int J Food Microbiol 38:45–54
Nyhan L, Begley M, Mutel A, Qu Y, Johnson N, Callanan M (2018) Predicting the combinatorial effects of water activity, pH and organic acids on Listeria growth in media and complex food matrices. Food Micorobiol 74:75–85
Parra R, Magan N (2004) Modelling the effect of temperature and water activity on growth of Aspergillus niger strains and applications for food spoilage moulds. J Appl Microbiol 97:429–438
Peleg M (2021) A New Look at Models of the Combined Effect of temperature, pH, water activity or other factors on microbial growth rate. Food Eng Rev (In press, available online)
Peleg M, Corradini MG (2011) Microbial growth curves - what the models tell us and what they cannot. Crit Rev Food Sci Nutr 51:917–945
Rockland LB, Beuchat LR (Eds) (1987) Water activity: theory and applications to food Marcel-Decker NY New York
Romero SM, Patriarca A, Fernández Pinto V, Vaamonde G (2007) Effect of water activity and temperature on growth of ochratoxigenic strains of Aspergillus carbonarius isolated from Argentinean dried vine fruits. Intnl J Food Micorbiol 115:140–143
Ross T, Ratkowski DA, Mellefont LA, McMeekin TA (2003) Modelling the effects of temperature, water activity, pH and lactic acid concentration on the growth rate of Escherichia coli. Int J Food Microbiol 82:33–43
Rosso L, Lobry JR, Bajard S, Flandrois JP (1995) Convenient model to describe the combined effects of temperature and pH on microbial growth. Appl Environ Microbiol 61:610–616
Rosso L, Robinson TP (2001) A cardinal model to describe the effect of water activity on the growth of moulds. Int J Food Microbiol 63:265–273
Samapundo S, Devlighere F, Geerared AH, De Meulenaer B, Van Impe JF, Debevere J (2007) Modelling of the individual and combined effects of water activity and temperature on the radial growth of Aspergillus flavus and A. parasiticus on corn. Food Microbiol 24:517–529
Sautour M, Soare Mansur C, Bensoussan M, Dantingy P (2002) Comparisn of the effect of temperature and water activity on growth rate of food spoilage moulds. J Ind Microbiol Biotechnol 28:311–315
Stevenson A, Cray JA, Williams JP, Santos R, Sahay R, Neuenkirchen N, McClure CD, Grant IR, Houghton JDR, Quinn JP, Timson DJ, Patil SV, Singhal RS, Anto’n J, Dijksterhuis J, Hocking AD, Lievens B, Rangel DEN, Voytek MA, Gunde-Cimerman N, Oren A, Timmis KN, McGenity TJ, Hallsworth JE (2015) Is there a common water-activity limit for the three domains of life? ISME J 9:1333–1351
Taub IA, Feeherry FE, Ross EW, Kustin K, Doona CJ (2003) A quasi–chemical kinetics model for growth and death of Staphylococcus aureus in intermediate moisture bread. J Food Sci 68:2530–2537
Valik L, Baranyi J, Goener F (1999) Predicting fungal growth: the effect of water activity on Penicillium roqueforti. Int J Food Microbiol 47:141–146
Wijtzes T, Rombouts FM, Kant-Muermans MLT, van’t Riet K, Zwietering MH (2001) Development and validation of a combined temperature, water activity, pH model for bacterial growth rate of Lactobacillus curvatus. Int J Food Microbiol 63:57–64
Zwietering MH, De Wit JC, Notermans S (1996) Application of predictive microbiology to estimate the number of Bacillus cereus in pasteurised milk at the point of consumption. Int J Food Microbiol 30:55–70
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Peleg, M. Models of the water activity effect on microbial growth rate and initiation. Appl Microbiol Biotechnol 106, 1375–1382 (2022). https://doi.org/10.1007/s00253-022-11792-7
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DOI: https://doi.org/10.1007/s00253-022-11792-7