|Buffer Capacity Modeling|
Longtin M, Price RE, Mishra R, Breidt F. 2020. Modeling the buffer capacity of ingredients in salad dressing products. J Food Sci. 85(4):910-917 doi:10.1111/1750-3841.15018
Price RE, Longtin M, Conley-Payton S, Osborne JA, Johanningsmeier SD, Bitzer D, Breidt F. 2020. Modeling buffer capacity and pH in acid and acidified foods. 85(4)918-J Food Sci. 85(4)918-925 doi: 10.1111/1750-3841.15091
Buffer capacity models have been developed that can be used to determine pH changes with the addition of acids or low acid ingredients to foods. Details of the modeling methods are described by Price et al., (2020). These methods have been used to define buffering and pH changes with the addition of low acid ingredients in salad dressings (Longtin et al., 2020).
An example of the BC modeling method for 3.6% acetic acid is shown in the graph below. The commercial vinegar solution was titrated with 1.22 N HCl, then 1.3 N NaOH. The buffer capacity curve (purple circles), which is the derivative of the combined titration curves (Panel A) was trimmed (blue circles) to result in a BC curve with symmetrical ends, followed by linear gap filling (black circles). The vertical red and blue lines represent the initial pH of the acid and base titrations (respectively). A trigonometric regression (Panel B, black curve) was then used to the BC data line. Panel C shows: the BC model fit (black curve); the BC of water (red curve); the pH calculated from the predicted buffer (black X on the X-axis), and the mean initial pH measurement of the solution being titrated (red circle on the X-axis); the pK (pH value) and BC (β) value for the predicted buffer is represented by the black vertical line.
The model data can be used to predict pH changes when ingredients are added to solutions for which buffering is already measured. Tables buffering for selected salad dressing ingredients are published (Longtin et al., 2020), although additional ingredients may be included. Use of the software currently requires Matlab (Mathworks, Inc.) software with the Matlab Optimization toolbox. The software is available for download here. Please contact Dr. Fred Breidt (firstname.lastname@example.org) for assistance and further details and software download and availability.