Modeling the formulation pH of elderberry syrup with multiple weak acids.

The objective of this work was to develop methods to assess the influence of the ingredients of an acidified elderberry syrup on product pH. A measure of total ingredient buffering (tBeta) was defined as the area under the buffer capacity curve of a food mixture or ingredient for pH 2-12. Citric acid (1% w/v), elderberry juice (75% v/v), and malic acid (0.75% w/v) had greater buffering (tBeta values of 15.33, 12.00, and 10.95, respectively) than ascorbic acid (0.75%) or lemon juice (3% v/v) (tBeta of 5.74 and 3.30, respectively). All other ingredients, including added spices (≤1% each) and honey (25% w/v), had tBeta values <2. The observed pH for the syrup mixture (pH 2.67) was within 0.11 pH units of the predicted pH based on combined buffer models of the acid and low acid ingredients (pH 2.78) using Matlab software. A total of 16 model syrup formulations containing elderberry juice with mixed acids (malic, acetic, and ascorbic) and having pH values between 3 and 4 were prepared. The pH values of the formulations were compared to predicted values from combined buffer models of the individual ingredients. Regression analysis indicated an excellent fit of the observed and predicted pH data, with a root mean square error of 0.076 pH units. The results indicated that buffer models may be useful for in silico estimates of how the ingredients in acid and acidified foods may influence pH, thus aiding in product development and safety assessments. PRACTICAL APPLICATION: Buffer models using recently developed titration methods for individual acid and low-acid food ingredients can be used to estimate the pH of formulations of these ingredients in silico. The total buffering (tBeta) for ingredients or mixtures, along with ingredient concentrations, may be a useful metric for helping to determine which ingredients will have the greatest impact on pH. Such models can aid product development efforts and safety assessments.