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ARS Home Southeast Area Raleigh, North Carolina Food Science and Market Quality and Handling Research Unit Research





- Breidt, Frederick
- Johanningsmeier, Suzanne
- Perez Diaz, Ilenys
- 2021
- 2020
- 2019
- 2018
- 2017
- Publications
- Food Safety, (Animal and Plant Products) (108)

Research Project: Intervention Strategies for Controlling Human Pathogens Associated with Fermented and Acidified Vegetables **Location:
                            Food Science and Market Quality and Handling Research Unit** 2020 Annual Report **Objectives**
                                

1. Determining the safety of low and alternative salt fermentations, produced nationally and internationally. 

2. Develop predictive models for 5-log reduction times for pathogenic Escherichia coli in fermented and acidified vegetable products. 

3. Enhance buffer capacity models for predicting pH changes in acidified foods with low acid ingredients. **Approach**
                                

The experimental approaches that will be use to achieve the objectives will include mathematical modeling, molecular ecology studies, and biochemical analysis of fermentation brines. Specifically, for Objective 1, to determine the effects of salts on pathogen reduction in fermentations, growth and death of bacterial pathogen cocktails (strain mixtures) will be measured in fermentations by conventional bacterial plating methods using automated plating equipment. Log reduction times for pathogens will be calculated using linear or nonlinear (Weibull) models. Biochemical analysis for salts, organic acids and sugars, will be done by titration (for salts), and high performance liquid chromatography (for acids and sugars). A matrix of salt types and concentrations will be tested to determine how salt effects pathogen die-off. For Objective 2, mathematical modeling approaches to determine the reduction in pathogen populations during fermentation will utilize non-linear systems of ordinary differential equations (rate equations) using Matlab computer software. In addition computer simulation models will be developed using the C++ programming language. Data for these models will be obtained from the experiments in Objective 1. Model results will be compared to data generated under a variety of conditions to determine if the models accurately describe the data. To accomplish Objective 3, predicting pH of buffered acidified foods with low acid additives, mathematical models will be based on published ionic equilibria equations for buffered acid and base solutions. Novel methods for numerical solutions to these equations will be implemented with Matlab software. An automated titrator will be used to confirm predicted buffer capacity curve data. To fit data to the models, several optimization algorithms will be used from the Matlab Optimization Toolkit, or independently programmed in Matlab or C++. The knowledge gained will be used to help processors and regulatory agencies assess and assure the safety of acidified and fermented food products. **Progress Report**
                                

Fermented vegetable foods have become increasingly popular, but there has been little information available to aid manufacturers of fermented vegetable products in developing food safety programs that can meet Food Safety Modernization Act (FSMA) and Food and Drug Administration (FDA) Food Code requirements. Under FSMA regulations, a business that manufactures fermented foods may be required to conduct a risk analysis and establish pertinent preventive controls. To fill this knowledge gap, ARS researchers at Raleigh, North Carolina, identified pH as the sole critical control for the manufacture of traditionally fermented vegetable products. This includes a steady and sustained pH decline to < 4.6 for prevention of spore outgrowth and botulism. ARS researchers at Raleigh, North Carolina, linked 5-log reduction times to pH for the principal microbial hazards including Escherichia coli, Salmonella enterica, and Listeria monocytogenes. Additional control points were identified for key processing steps, and included vegetable preparation (cleaning and washing) and salt addition (= 2% is recommended, although lower salt concentrations will work); fermentation time and temperature (e.g. typically 65-72°F for three or more weeks for cabbage fermentations); and refrigerated storage and/or hermetically sealed packaging for shelf-stability. While the parameters for the above control points may differ depending on fermentation type, the controls identified will be beneficial to aid producers in meeting FDA regulatory requirements and establishing production controls for fermented foods, including cucumber pickles, sauerkraut and others.

While it is well known that competition between lactic acid bacteria and bacterial pathogens in vegetable fermentations results in safe fermented products, a mechanistic understanding of bacterial competition is lacking. To help fill this void, ARS researchers at Raleigh, North Carolina, investigated how acid resistance characteristics of disease-causing Escherichia coli (E. coli) strains influenced survival of this pathogen in vegetable fermentations. Surprisingly, ARS researchers at Raleigh, North Carolina, found that the most acid resistant E. coli strains did not survive as well as more acid sensitive strains under some laboratory fermentation conditions. These results are important because they indicate that there are chemical and environmental factors driving changes in microbial ecology during fermentations that are poorly understood and could directly affect fermentation safety. Specifically, the data revealed that metabolic reactions of E. coli that result in pH buffering may be important for controlling E. coli survival in competition with lactic acid bacteria. These results will help guide future research to further define the conditions leading to the safe manufacture of a variety of fermented vegetable products.

A cell-based model for the competitive growth of lactic acid bacteria and bacterial pathogens in vegetable fermentations has been developed in Matlab. This model has been developed by ARS researchers at Raleigh, North Carolina, as a computer simulation based on mechanistic principles for cell growth and division, rather than traditional growth modeling based on cell population growth and death rates. A novel feature of the model is the prediction of pH based on acid production by the cells undergoing fermentation, taking into account the buffering of the fermentation medium itself. An advantage of the cell-based mechanistic modeling is that bacterial competition and pH changes in fermentation systems are not dependent on the specific conditions of the experiments or defined by fitted curves. Using curve fitting methods for these variables limits the utility of the models to only the system studied. Further development of these models may lead to practical use of pH as a measure of fermentation safety because these models link pH directly to acid concentrations, which has been difficult for mixed acid fermentations.

The pH of most acid food products depends on undefined and complex buffering of all ingredients but is critically important for regulatory purposes and food safety. ARS researchers at Raleigh, North Carolina, have developed a new method for modeling the pH of complex food ingredients. ARS researchers at Raleigh, North Carolina, used the method for defining the buffering and pH of individual ingredients and ingredient mixtures in salad dressing products. Ingredients of salad dressings were titrated individually and in combination at concentrations typical of dressing products. Buffer data were then used to predict pH. The research showed that most ingredients in salad dressings had little buffering compared to the vinegar typically used in dressing formulations, meaning that very little pH change would occur due to adding the ingredient to the dressing. ARS researchers at Raleigh, North Carolina, found that sugars showed significant buffering at high pH values due to very weakly acidic hydroxyl groups on sugar molecules. These chemical groups would not affect product pH under conditions typical of foods. Application of buffer models and data for dressing ingredients may help manufacturers with new product formulation and determining pH stability and safety of dressing products. This work will also aid regulatory agencies in assessing the impact of ingredients in salad dressings on final product pH for regulatory purposes. **Accomplishments**
                                

1. Development of buffer capacity models for acid and acidified foods. Acid foods are primarily composed of acidic food ingredients but often have small amounts of spices and other high pH ingredients to improve flavor, texture or other properties of the final products. Acidified foods, on the other hand are primarily composed mostly of high pH ingredients (like cucumbers) that are made acidic by adding vinegar. Defining these two product types, which are regulated differently for safety considerations by FDA, has been difficult. ARS researchers at Raleigh, North Carolina, have developed buffer models and modeling methods that can be used to define the pH impact of all the ingredients in different types of acid or acidified foods. The method works even if the chemical compositions of the food ingredients are not known or not chemically defined. The buffer capacity models have been adapted by the salad dressing industry and by FDA to help differentiate between acid and acidified foods based on pH changes with ingredient addition. These models represent a novel scientific advance with broad application to the safety of acid and acidified foods, including: 1) predicting pH of products based on ingredient mixtures; 2) estimating pH stability; and 3) predicting pH changes in vegetable and other food fermentations as acids accumulate. **Review Publications**
                            *Longtin, M., Price, R.E., Mishra, R., Breidt, F. 2020. Modeling the buffer capacity of ingredients in salad dressing products. Journal of Food Science. 85(4):910-917. https://doi.org/10.1111/1750-3841.15018.*
                                *Price, R.E., Longtin, M., Conley Payton, S., Osborne, J.A., Johanningsmeier, S.D., Bitzer, D., Breidt, F. 2020. Modeling buffer capacity and pH in acid and acidified foods. Journal of Food Science. 85(4):918-925. https://doi.org/10.1111/1750-3841.15091.*
                                *Jones, C.M., Price, R.E., Breidt, F. 2020. Escherichia coli O157:H7 stationary phase acid resistance and assessment of survival in a model vegetable fermentation system. Journal of Food Protection. 83(5):745-753. https://doi.org/10.4315/JFP-19-463.*
                                *Snyder, A., Breidt, F., Andress, E.L., Ingham, B.H. 2020. Manufacture of traditionally fermented vegetable products: Best practice for small businesses and retail food establishments. Food Protection Trends. 40(4):251-263.*
                                *Lu, Z., Perez Diaz, I.M., Hayes, J., Breidt, F. 2020. Bacteriophages infecting gram-negative bacteria in a commercial cucumber fermentation. Frontiers in Microbiology. 11:1306. https://doi.org/10.3389/fmicb.2020.01306.*


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