Validation of bacterial growth inhibition models based on molecular properties of organic acids.
Organic acids occur naturally in foods and have been used in many food products as preservatives because they inhibit the growth of most microorganisms. The acids commonly found in foods differ greatly in both their structure and inhibitory effects for different bacteria. A way to represent relationships between different acids was previously described in which principal components analysis (PCA) was applied to 11 physical and chemical properties of 17 organic acids, to arrive at principal properties. These were used for development of regression models that related the minimum inhibitory concentrations (MICs) of organic acids to their principal properties. Separate MIC models were constructed for six different bacteria. The objective of the present study was to test the predictive capabilities of the organism models using different organic acids from the ones used to construct the original models. MIC predictions were made for three acids for each of the six bacteria for which models were previously constructed. MIC determinations for these acids were then carried out and compared with the predictions; these were in good agreement, thus validating the models. The new data were combined with that obtained previously to produce similar, but slightly stronger models. These had R(2) values between 0.861 and 0.992.
Nakai
Silvia A
SA
The National Food Laboratory, Dublin, CA 94568, USA.
Siebert
Karl J
KJ
D000143:Acids / Q000494:pharmacology*; D001407:Bacillus / Q000187:drug effects / Q000254:growth & development; D001419:Bacteria / Q000187:drug effects* / Q000254:growth & development; D015169:Colony Count, Microbial; D004926:Escherichia coli / Q000187:drug effects / Q000254:growth & development; D005516:Food Microbiology; D006863:Hydrogen-Ion Concentration; D007778:Lactobacillus / Q000187:drug effects / Q000254:growth & development; D008826:Microbial Sensitivity Tests; D008954:Models, Biological; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis
D000143:Acids