title: Modeling the inhibitory effects of organic acids on bacteria.
abstract: The inhibitory effect of acids on microbial growth has long been used to preserve foods from spoilage. While much of the effect can be accounted for by pH, it is well known that different organic acids vary considerably in their inhibitory effects. Because organic acids are not members of a homologous series, but vary in the numbers of carboxy groups, hydroxy groups and carbon-carbon double bonds in the molecule, it has typically not been possible to predict the magnitude, or in some cases even the direction, of the change in inhibitory effect upon substituting one acid for another or to predict the net result in food systems containing more than one acid. The objective of this investigation was to attempt to construct a mathematical model that would enable such prediction as a function of the physical and chemical properties of organic acids. Principal Components Analysis (PCA) was applied to 11 properties for each of 17 acids commonly found in food systems; this resulted in four significant principal components (PCs), presumably representing fundamental properties of the acids and indicating each acid's location along each of these four scales. These properties correspond to polar groups, the number of double bonds, molecular size, and solubility in non-polar solvents. Minimum inhibitory concentrations (MICs) for each of eight acids for six test microorganisms were determined at pH 5.25. The MICs for each organism were modeled as a function of the four PCs using partial least squares (PLS) regression. This produced models with high correlations for five of the bacteria (R2 = 0.856, 0.941, 0.968, 0.968 and 0.970) and one with a slightly lower value (R2 = 0.785). Acid susceptible organisms (Bacillus cereus, Bacillus subtilis, and Alicyclobacillus) exhibited a similar response pattern. There appeared to be two separate response patterns for acid resistant organisms; one was exhibited by the two lactobacilli studied and the other by E. coli. Predicting the inhibitory effects of the organic acids as a function of their chemical and physical properties is clearly possible.
authors.affiliation: Department of Food Science and Technology, Cornell University, Geneva, NY 14456, USA.
authors.forename: C P
authors.initials: CP
authors.lastname: Hsiao
authors.forename: K J
authors.initials: KJ
authors.lastname: Siebert
mesh_terms: D001406:Bacillaceae / Q000187:drug effects / Q000254:growth & development; D001409:Bacillus cereus / Q000187:drug effects / Q000254:growth & development; D001412:Bacillus subtilis / Q000187:drug effects / Q000254:growth & development; D001419:Bacteria / Q000187:drug effects* / Q000254:growth & development; D002264:Carboxylic Acids / Q000737:chemistry / Q000494:pharmacology*; D016000:Cluster Analysis; D015169:Colony Count, Microbial; D004926:Escherichia coli / Q000187:drug effects / Q000254:growth & development; D005240:Feasibility Studies; D005544:Forecasting; D007778:Lactobacillus / Q000187:drug effects / Q000254:growth & development; D016018:Least-Squares Analysis; D008826:Microbial Sensitivity Tests; D008954:Models, Biological; D015999:Multivariate Analysis; D009391:Nephelometry and Turbidimetry; D012995:Solubility; D013329:Structure-Activity Relationship
chemical_list: D002264:Carboxylic Acids