Journal
JOURNAL OF FOOD SCIENCE
Volume 65, Issue 3, Pages 516-520Publisher
WILEY
DOI: 10.1111/j.1365-2621.2000.tb16039.x
Keywords
logistic regression; mango; predictive microbiology; probabilistic modeling; Zygosaccharomyces bailii
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Probabilistic microbial modeling using logistic regression was used to predict critical temperatures to inhibit for at least 35 d Zygosaccharomyces bailii growth in a pH 3.5 mango puree formulated with 1000 ppm of potassium sorbate (KS) or sodium benzoate (NaB) at selected a(w) (0.99, 0.98, or 0.97), The probability of growth was calculated, thereby ascertaining the set conditions and critical temperatures required inhibiting yeast growth for different storage times, Using the logistic model, with a growth probability of 0.05, critical temperatures were higher for KS than for NaB. Use of KS to inhibit Z. bailii growth enabled for mango puree 30 d of storage at 6.4 degrees C.
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