Development and validation of an extended predictive model for the effect of pH and water activity on the growth kinetics of Geobacillus stearothermophilus in plant-based milk alternatives

被引：8

作者：

Misiou, Ourania ^{[1
]}

Kasiouras, Georgios ^{[1
]}

Koutsoumanis, Konstantinos ^{[1
]}

机构：

[1] Aristotle Univ Thessaloniki, Fac Agr, Dept Food Sci & Technol, Lab Food Microbiol & Hyg, Thessaloniki 54124, Greece

来源：

FOOD RESEARCH INTERNATIONAL | 2021年 / 145卷

基金：

欧盟地平线“2020”;

关键词：

Geobacillus stearothermophilus; Plant-based milk alternatives; Food spoilage; Growth model; Water activity; pH; BACILLUS-STEAROTHERMOPHILUS; THERMOPHILIC BACILLI; HEAT-RESISTANCE; PERFORMANCE EVALUATION; MICROBIAL SPOILAGE; STRAIN VARIABILITY; BACTERIAL-GROWTH; SPORE FORMERS; TEMPERATURE; FOOD;

D O I：

10.1016/j.foodres.2021.110407

中图分类号：

TS2 [食品工业];

学科分类号：

0832 ;

摘要：

The cardinal model for the effect of temperature on Geobacillus stearothermophilus ATCC 7953 growth developed by Kakagianni, Gougouli, & Koutsoumanis, 2016 was expanded for the effect of pH and water activity (a(w)). The effect of pH (range: 5.7-8.5) and a(w) (range: 0.985-0.999) on G. stearothermophilus growth rate was studied in tryptone soy broth (TSB) using the Bioscreen C method and further modelled using a Cardinal Model (CM). The estimated values for the cardinal parameters pH(min), pH(opt), pH(max), a(wmin), and a(wopt) were 5.65 +/- 0.14, 6.74 +/- 0.03, 8.71 +/- 0.03, 0.984 +/- 0.007 and 0.998 +/- 0.001, respectively. The growth behaviour of G. stearothermophilus was investigated in 7 commercial non-refrigerated plant-based milk alternatives under static conditions (62 degrees C) and the estimated maximum specific growth rates were used to determine the optimum growth rate for each product. The developed model was validated against observed growth of G. stearothermophilus in the 7 products during storage at non-isothermal conditions (testing 4 different temperature profiles). The validation results showed a good performance of the model with overall Bias factor (B-f) = 1.06 and Accuracy factor (A(f)) = 1.12. The developed model can be used as an effective tool by the food industry in predicting spoilage of plant-based milk alternatives during distribution and storage at retail and domestic levels.

引用

页数：11

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