Validation of a polynomial regression model: the thermal inactivation of Bacillus subtilis spores in milk
1Department of Biotechnology, Faculty of Engineering, Kansai University, Suita, Osaka, Japan. jagann10@yahoo.com
Aims:
The predicted survival of Bacillus subtilis 168 spores from a polynomial regression equation was validated in milk.
Methods And Results:
Bias factor suggested as an index of model performance was used to validate the polynomial model predictions in ultrahigh temperature (UHT) treated and sterilized whole and skim milk. Model predictions were fail safe, predicting higher D-values (decimal reduction times) in buffer than actually noted in milk.
Conclusions:
The D-values for spores were lower in milk as compared with those predicted in potassium phosphate buffer contrary to the popular expectation of better spore survival in complex food systems. The Bias factor, a quantitative measure of the model performance, indicated that on average the model predictions exceed the observations by 40% in the case of whole milk and by 60% in the case of skim milk.
Significance And Impact Of The Study:
The present work is an attempt to ascertain the extent of reliability that one can safely place in polynomial model predictions, without compromising on the safety or palatability of foods where it is eventually intended to be applied. The work has also highlighted the differences in the thermal inactivation pattern of spores in buffer and in milk with a possible influence of the various constituents of milk. The work will assist the dairy industry to better design thermal processes to ensure longer shelf life of dairy foods.
Insights
Polynomial models accurately predict Bacillus subtilis 168 spore survival in milk, showing lower D-values than buffer. This validation ensures food safety and optimizes thermal processing for dairy products.
Area of Science:
- Food microbiology
- Thermal processing validation
- Mathematical modeling in food science
Background:
- Predictive models for microbial inactivation are crucial for food safety.
- Bacillus subtilis spores are common contaminants in dairy products.
- Understanding spore thermal resistance in different food matrices is essential for process design.
Purpose of the Study:
- To validate polynomial regression model predictions for Bacillus subtilis 168 spore survival in milk.
- To assess the reliability of these models for designing thermal processes in the dairy industry.
- To compare spore inactivation in milk with predictions made in a buffer solution.
Main Methods:
- Utilized a polynomial regression equation to predict spore survival.
- Validated model predictions by comparing them with experimental data in whole and skim milk.
- Employed the Bias factor as an index for model performance evaluation.
Main Results:
- Model predictions for D-values (decimal reduction times) were consistently higher than observed values in milk, indicating a fail-safe approach.
- Spore D-values were found to be lower in milk compared to potassium phosphate buffer.
- The Bias factor showed that model predictions exceeded observations by 40% in whole milk and 60% in skim milk.
Conclusions:
- Polynomial models provide a reliable, fail-safe estimation of spore inactivation in milk.
- The thermal inactivation of Bacillus subtilis spores differs between buffer and milk, influenced by milk composition.
- These findings aid the dairy industry in optimizing thermal processing for enhanced food safety and shelf-life.
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