Modelling mould spoilage in cold-filled ready-to-drink beverages by Aspergillus niger and Penicillium spinulosum

Abstract Mathematical models have been developed to predict the probability of growth of spoilage moulds in response to various preservative systems in ready to drink beverages. A Box-Behnken experimental design included five variables, each at three levels: pH (2·8, 3·3, 3·8), titratable acidity (0·20%, 0·40%, 0·60%), sugar content (8·0, 12·0, 16·0 °Brix), and preservative concentrations (sodium benzoate and potassium sorbate, each 100, 225, 350 ppm). Duplicate samples were inoculated with a mould cocktail consisting of equal proportions of Aspergillus niger and Penicillium spinulosum spores (5·0×10 4 spores/ml). The inoculated samples were plated on malt extract agar after 0, 1, 2, 4, 6, and 8 weeks. Logistic regression was used to create predictive models. The pH, titratable acidity, sugar content, sodium benzoate, and potassium sorbate levels were all found to be significant factors in predicting the probability of mould growth over time. Interactions between pH and sodium benzoate, pH and potassium sorbate, and pH and sugar content were also statistically significant. This logistic model was validated against 14 new conditions and predicted the growth of mould after 8 weeks with over 96% accuracy. Product developers can use these models to predict mould growth in ready to drink beverages.

[1]  E. D. Jackson,et al.  Use of response surface methodology in shelf life extension studies of a bakery product , 1988 .

[2]  N. Mantel.  Why Stepdown Procedures in Variable Selection , 1970 .

[3]  L. Rosso,et al.  Predictive microbiology. , 1994, International journal of food microbiology.

[4]  J Baranyi,et al.  Predicting fungal growth: the effect of water activity on Aspergillus flavus and related species. , 1994, International journal of food microbiology.

[5]  Erich. . Lueck,et al.  Antimicrobial Food Additives: Characteristics, Uses, Effects , 1980 .

[6]  Icmsf.  Soft drinks, fruit juices, concentrates and fruit preserves , 1998 .

[7]  Lothar Leistner,et al.  Principles and applications of hurdle technology , 1995 .

[8]  M W Peck,et al.  Modelling the growth, survival and death of microorganisms in foods: the UK food micromodel approach. , 1994, International journal of food microbiology.

[9]  G. Fleet,et al.  The effect of pH, sodium chloride, sucrose, sorbate and benzoate on the growth of food spoilage yeasts☆ , 1997 .

[10]  R. Pitt.  A Descriptive Model of Mold Growth and Aflatoxin Formation as Affected by Environmental Conditions. , 1993, Journal of food protection.

[11]  T. Eklund.  Inhibition of microbial growth at different pH levels by benzoic and propionic acids and esters of p-hydroxybenzoic acid , 1985 .

[12]  K. Young,et al.  Acetic, lactic and citric acids and pH inhibition of Listeria monocytogenes Scott A and the effect on intracellular pH. , 1993, The Journal of applied bacteriology.

[13]  D. Schaffner,et al.  Mathematical Models for the Effects of pH, Temperature, and Sodium Chloride on the Growth of Bacillus stearothermophilus in Salty Carrots , 1997, Applied and environmental microbiology.

[14]  N. Skovgaard.  Essentials of the microbiology of foods. A textbook for advanced studies , 1997 .

[15]  ED'TESoBLO,et al.  Food "Preservatives." , 1899, The Hospital.

[16]  Grahame W. Gould,et al.  New Methods of Food Preservation , 1994 .

[17]  D W Schaffner,et al.  Modelling bacterial spoilage in cold‐filled ready to drink beverages by Acinetobacter calcoaceticus and Gluconobacter oxydans , 2001, Journal of applied microbiology.

[18]  R. C. Whiting,et al.  Microbial modeling in foods. , 1995, Critical reviews in food science and nutrition.

[19]  M. B. Cole,et al.  Probability of growth of the spoilage yeast Zygosaccharomyces bailii in a model fruit drink system , 1987 .

[20]  I. Booth,et al.  Acidulants and low pH , 2003 .

[21]  G. Edwards,et al.  Antimicrobial Food Additives , 1980 .

[22]  J. Sofos.  Sorbate Food Preservatives , 1989 .

[23]  N. Russell,et al.  Solutes and low water activity , 2003 .

[24]  Donald W. Schaffner,et al.  Comparison of Logistic Regression and Linear Regression in Modeling Percentage Data , 2001, Applied and Environmental Microbiology.

[25]  S. Duffy,et al.  Modeling Yeast Spoilage in Cold-Filled Ready-To-Drink Beverages with Saccharomyces cerevisiae, Zygosaccharomyces bailii, and Candida lipolytica , 2002, Applied and Environmental Microbiology.

[26]  P. Davidson,et al.  Antimicrobials in foods. , 1993 .

[27]  J. I. Pitt,et al.  Further Studies on the Water Relations of Xerophilic Fungi, Including Some Halophiles , 1987 .

[28]  R. C. Whiting,et al.  Differentiation of the Effects of pH and Lactic or Acetic Acid Concentration on the Kinetics of Listeria Monocytogenes Inactivation. , 1993, Journal of food protection.

[29]  S. Duffy,et al.  Simulation and modelling of the effect of small inoculum size on time to spoilage by Bacillus stearothermophilus , 2001 .

[30]  G. J. Banwart,et al.  Basic Food Microbiology , 1979 .