Modeling the buffer capacity of ingredients in salad dressing products

Abstract

The pH of most acid food products depends on undefined and complex buffering of ingredients but is critically important for regulatory purposes and food safety. Our objective was to define the buffer capacity (BC) of ingredients in salad dressing products. Ingredients of salad dressings were titrated individually and in combination using concentrations typical of dressing products. Titration curves from pH 2 to 12 were generated with sodium hydroxide and hydrochloric acid, which were then used to generate BC curves. A matrix of concentration and pK values for a series of monoprotic buffers approximated the pH of each ingredient. Some buffer series required anion or cation corrections for accurate pH prediction, possibly due to the presence of salts of acid or bases. Most buffers had BC values less than 10-fold the BC of acetic acid (0.25 β) typically in dressing formulations and had little influence on the final product pH of the dressings tested. Unexpectedly, we found that sugars in dressing formulations, including sucrose or corn syrup, exhibited buffering at pH values greater than 11 (0.035 β and 0.059 β, respectively), which was likely due to weakly acidic hydroxyl groups on the sugar molecules. However, the concentration and pK for buffers above pH 11 or below pH 2 were difficult to quantify due to the BC of water. The BC data may help to quantify the effects of salad dressing ingredients on the final product pH and benefit regulatory agencies and manufacturers in assessing product pH and safety.

Modeling buffer capacity and pH in acid and acidified foods

“…4), we found that α = 0.5 resulted in a BC model for pH 2 to 12 that had model results similar to observed BC data. By default, we used 15 sine–cosine paired terms, which were sufficient to approximate most BC curves generated for acid and low‐acid food ingredients (Longtin et al., 2020). The trigonometric regression results for the acetic acid BC data are shown in Figure 4B (black line).…”

“…We include data on pH prediction with sodium and calcium (monovalent and divalent cations) chloride, under a variety of pH conditions, to be relevant to food matrices, including recently developed calcium‐based vegetable fermentations (MccFeeters & Perez‐Diaz, 2010). A companion paper (Longtin, Price, Mishra, & Breidt, 2020) reports data from BC models for a variety of acid and low‐acid ingredients in salad‐dressing products. Once the BC of an acid or low‐acid ingredient is known, the magnitude of pH changes due to the addition of that ingredient to acid or acidified foods may be estimated.…”

Modeling the formulation pH of elderberry syrup with multiple weak acids

“…Recently, buffer models have been used to characterize how acid and low‐acid salad dressing ingredients influence product pH (Longtin et al., 2020). Buffer models have also been used to link pH with fermentation acid concentrations during vegetable fermentations, and to help quantify the pH impact of the malolactic reaction of lactic acid bacteria (Breidt & Skinner, 2022).…”

“…Food ingredient buffering can be estimated by using a titration method to generate buffer capacity (BC) curves over a pH range of 2–12 (Longtin et al., 2020) where there is little or no buffering from water. Outside of this pH range, buffering is essentially the same for aqueous food products, due to the symmetrical increase in buffering of water at the low and high extremes of the pH scale (Butler & Cogley, 1998).…”

“…The concentration of low‐acid ingredients in acidified foods affects the pH due to the cumulative effects of buffering of these ingredients. Ingredients with little or no buffering in the pH range of acidified foods such as starches or sugars (Longtin et al., 2020) may thus have little or no impact on the final equilibrium pH other than dilution of the concentration of buffering ingredients even at high concentrations (25% or greater for some added sugars). Salts may also influence pH due to ionic strength effects on the p K values of buffers.…”