USDA Buffer Capacity Study

Fred BreidtADS Technical Meeting, Louisville, KY

Tuesday, April 30th

8:30 – 9:15 AM

USDA Food Science Research UnitLocated in the Food, Bioprocessing and Nutrition Sciences Department at NC State University

• NP306: Improved Processes for the Preservation and Utilization of Vegetables, Including Cucumber, Sweetpotato, Cabbage, and Peppers to Produce Safe, High Quality Products with Reduced Energy Use and Waste

• Dr. Ilenys M. Pérez-Díaz 0.9• Dr. Suzanne D. Johanningsmeier 0.9• Dr. Frederick Breidt, Jr. 0.1• Vacant

• NP108: Intervention Strategies for Controlling Human Pathogens Associated with Fermented and Acidified Vegetables

• Dr. Frederick Breidt, Jr. 0.9• Dr. Suzanne D. Johanningsmeier 0.1• Dr. Ilenys M. Pérez-Díaz 0.1

• Research and support staff, and students • Ms. Sandra Parker (Administrative Support)• Ms. Rong Reynolds • Mr. Robert Price• Mr. Christian Pagan-Medina• Ms. Jennifer Fideler• Ms. Monica Richmond• Mr. Anderson Foster• Nick Marinos• Karen Zhai• Ms. Madyson Longtin

• How do salts affect fermented food safety?• Dupree et al., 2019. J. Food Prot. 82(4):570-578

• Can pathogen survival (or not) be predicted in vegetable fermentations? • Mathematical modeling of the competitive growth of lactic

acid bacteria and bacterial pathogens in fermented foods• Ms. Clara Jones, MS thesis – Spring 2019/publicatons

• How do low acid ingredients influence the pH of acid or acidified foods? • RESEARCH, NOT POLICY, NOT REGULATORY

• BC modeling to identify how ingredients change pH• Manuscript(s) in preparation

NP108: Food Safety Project Under Dr. Jim Lindsay (National. Program Staff, ARS), 5-Year funded project (2016-2021)

TITLE 21--FOOD AND DRUGS

CHAPTER I--FOOD AND DRUG ADMINISTRATIONDEPARTMENT OF HEALTH AND HUMAN SERVICES

[Code of Federal Regulations][Title 21, Volume 2][Revised as of April 1, 2018][CITE: 21CFR114.3]

For the purposes of this part, the following definitions apply.(a) Acid foods means foods that have a natural pH of 4.6 or below.(b) Acidified foods means low-acid foods to which acid(s) or acid food(s) are added; these foods include, but are not limited to, beans, cucumbers, cabbage, artichokes, cauliflower, puddings, peppers, tropical fruits, and fish, singly or in any combination. They have a water activity (aw) greater than 0.85 and have a finished equilibrium pH of 4.6 or below. These foods may be called, or

may purport to be, "pickles" or "pickled ___." Carbonated beverages, jams, jellies, preserves, acid foods (including such foods as standardized and non-standardized food dressings and condiment sauces) that contain small amounts of low-acid food(s) and have a resultant finished equilibrium pH that does not significantly differ from that of the predominant acid or acid food, and foods that

are stored, distributed, and retailed under refrigeration are excluded from the coverage of this part.

Buffer capacity modeling

• Buffers are analogous to a water reservoir to protect against floods or drought

• Weak acids and bases are naturally present in acid/acidified foods• Protect against pH changes at pH values near pK

value

• Many buffers in foods are not clearly identified

• ID buffers in low acid foods from BC curves• Model buffering with monoprotic buffers

• Predict pH changes in acid foods

R-COOH

R-COO- + H+

Weak acid equilibrium

Methods

Acid Titration

BC Curve

Base Titration Titration Curve

Curve FittingMonoproticBuffer Series

pH prediction with mixtures of complex

ingredients

Derivative

Non-linearfitting

Ionic Equilibriamodelling

Table of bufferConcentrations and pK values

Matlab® functions for:

pH prediction: [H+] = CaiKai/(Kai + [H+]) – Cbi[H+]/([H+] + Kbi) + Kw/[H+] + (C2 - C1)Observed BC: β = ∂C(acid or base) / ∂pH (from titration data)BC Model: β = 2.303({CaiKai[H+]/([H+] + Kai)

2}N +Kw/[H+] + [H+]Where:β = buffer capacity or “buffer index”Cai = concentration of each weak acid in solutionKai = the corresponding pKa for each weak acidH+ = proton concentrationKw = Equilibrium constant for water (10-14){}N = one term for each acid in solution∂C(acid or base) = change in the concentration of the acid (HCl) or base (NaOH) in the solution being titrated ∂pH = change in pH due to the addition of acid or base

Reference: Butler and Cogely, 1998. Ionic Equilibrium, Solubility and pH Calculations. John Wiley and Sons, Inc. NY.

The approach:1. Use the derivative of titration curves to generate BC curves2. Fit Fourier series to fit BC curves (linear algebra solution)3. Non-linear curve fitting (Matlab): fit BC model to Fourier series4. Predict pH: Newton’s method to solve high order polynomial

The math…

Validation of buffer capacity model pH prediction in simple mixtures of citric acid and ammonia or acetic acid

and ammonia. The root mean square error (RMSE) and average absolute error (AAE) for the pH prediction

from the buffer capacity model were 0.22 and 0.16, respectively.

Validation of pH prediction

Example titration of lactic acid in water• Add strong acid (3.2 M HCl) or base (3.4 M NaOH) to solution of 20

mM lactic acid

• Record volume added and resulting pH change (Hanna Instr.® titrator)

• Derivative of combined titration curve = BC curve

0 0.5 1 1.52

3

4

5

6

7

3.154 M HCl

3.377 M NaOH

2 3 4 5 6 70

0.005

0.01

0.015

0.02

0.025

0.03

pHVolume added (ml)

pH

Bu

ffer

cap

acit

y

Titration curve Buffer capacity curve

Acid ingredients in a generic ranch dressing formulation

Trim Fourier Series BC model

pK Conc (mM)

1.85 41.98

2.97 43.61

4.41 369.47

4.92 83.07

6.47 32.69

9.66 39.25

11.73 61.16

Parameters Values Units

Acid pHi 3.10 pH

Base pHi 3.06 pH

Pred pH 3.08 pH

Unadj pH 3.05 pH

AdjC -2.48 mM

UB 12.00 pH

LB 2.00 pH

Appx. 2% acetic acidwith pK shift due to added salts

Acetic acid (distilled vinegar)

Bu

ffe

r ca

pac

ity

pH

Buffer with pK shift, 2% NaCl

x

ObservedPredicted

Initial acid titration pH (red) Initial base titration pH (blue)

pK Conc (mM) Buffer Cap.

4.52 429.29 0.247

Buffer capacity of water

BC data and model

Composition and concentration

Low acid Ingredient Compositiona Concentration (%)b

Sugar Assay 99.9 % Sucrose 3.3

Corn Syrup nd 3.3

Liquid Sucrose nd 3.3

Garlic Puree nd 0.6

Mustard Flour nd 0.5

Salted Egg Yolks NaCl 10% 3.5

NaCl Assay 99.7% NaCl 1.7

Garlic PowderDehydrated garlic powder, hot water insoluble solids 10-13%, moisture < 7%

0.6

Onion PowderDehydrated onion powder, hot water insoluble solids 18-20%, moisture < 7%

0.25

Black Pepper (spices?)Dried piper nigrum L, volatile Oil > 3%, moisture < 13%

0.1

Modified StarchModified food starch, moisture 10%

0.4

Propyleneglycol Alginate nd 0.3

Dehydrated Minced Onion nd 0.4

Buttermilk Powder Protein 30%, moisture 5% 1.5

Blue Cheese nd 10

Xanthan GumPolysaccharide xanthan gum powder 1%

0.35

Red Bell Pepper Granules nd 0.4a Product description (nd = not determined)b Concentration (percent) used for titration

Acid Ingredient Compositiona Concentration (%)b

Distilled Vinegar 5% Acetic Acid 5.9

Citric Acid nd 0.15

Monosodium Glutamate Assay 99% 0.5

Phosphoric Acid 75% Phosphoric Acid 0.3

Sodium Benzoate nd 0.09

Potassium Sorbate Assay 99% 0.1

EDTA Assay 99.9%, 1% solution 0.006

a Product description (nd = not determined)b Concentration (percent) used for titration

Low acid ingredients Acid ingredients

Acid ingredients and all ingredientsAcid All

pK Conc (mM) pK Conc (mM)

1.85 41.98 2.00 38.21

2.97 43.61 3.17 59.99

4.41 369.47 4.45 360.57

4.92 83.07 5.15 43.93

6.47 32.69 6.44 43.73

9.66 39.25 9.53 40.28

11.73 61.16 11.29 87.64

0.00

0.03

0.06

0.09

0.12

0.15

0.18

0.21

0.24

1 2 3 4 5 6 7 8 9 10 11 12 13

Bu

ffe

r C

apac

ity

pH

Acid ingredients (triangles), low acid ingredients (squares), and all ingredients (circles)

Buffers from ingredient mixtures

Data from acid ingredient titrations

Salts: The ion concentration is equal to the ingredient concentration.Positive value = anionNegative value = cation (Na+, K+)

Buffers from acids and additives

0

0.01

0.02

0.03

0.04

0.05

0.06

1 2 3 4 5 6 7 8 9 10 11 12

Bu

ffe

r C

apac

ity

pH

Phosphoric acid

Monosodium glutamate

Citric acid

Potassium sorbate

EDTA (10X)

Sodium benzoate

Propylene glycolalginate

Salt

Buffers of low acid ingredients

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

1 2 3 4 5 6 7 8 9 10 11 12

Bu

ffe

r ca

pac

ity

pH

Blue cheese

Mustard Flour

Buttermilk

Egg yolk

Garlic puree

Garlic powder

Minced Onion

Onion powder

Red bell pepper

Spices

Data from low acid ingredient titrations

Sugar Issue…Liquid Sucrose Corn syrup Sugar

pK Conc (mM) pK Conc (mM) pK Conc (mM)

5.61 0.68 10.48 9.13 11.48 25.41

10.12 0.95 11.71 50.41

11.50 25.15

LS CS S

Acid pH 4.35 4.60 6.36

base pH 4.60 4.62 6.04

Pred pH 4.47 4.61 6.20

Unadj pH 10.71 10.89 11.75

Ion (mM) 26.05 59.56 24.41

pK of base is difficult to predict!

Strong base, neutralized with hydrochloric acid?

Combinations of acid and low acid ingredients…

10X salts?

∆ pH = 0.25 ∆ pH = 1.2

BC project summary

• Definition of acidified vs. acid foods• FDA will make the policy decisions!• Science based method

• What can we do with buffer modeling?• Determine pH ranges with variation in ingredient type

and concentration• Predict pH during food fermentations• Determine safety margins for acid/acidified foods • Product development and formulation

• Challenges and future work• pH prediction for mixed solutions with undefined

components• Software development (Matlab -> user friendly software)• What’s up with sugar?

Title: Improved Vegetable Processing Methods to Reduce Environmental Impact,

Enhance Product Quality and Reduce Food Waste.

Researchers: Dr. Fred Breidt (LS), Dr. Suzanne Johanningsmeier, Dr. Ilenys Pérez-Díaz.

Objective 1 (Perez-Diaz): Development of controlled, low-salt vegetable fermentations

free of added preservatives using biofunctional lactic acid bacteria starter cultures to

improve commercial product quality and reduce spoilage and food waste.

Objective 2 (Johanningsmeier): Identify beneficial chemical constituents of vegetables

that facilitate the development of novel, clean-label, health-promoting fermented and

acidified products that retain consumer-preferred appearance, textures, and flavor during

processing, storage and distribution.

Objective 3: Determine the physical and chemical characteristics of sweetpotatogenotypes to optimize commercial food processing methods and enable commercially viable, novel, value-added products that meet consumer preferences…

New NP306 (processing) project proposal in preparation…

2020 and beyond:New NP108 project proposal in late 2019…NOW IS YOUR CHANCE TO INFLUENCE OUR RESEARCH AGENDA!

• Hops as a natural antimicrobial• Beta Tech (Barth-Hass Group)• MS student

• Polylactic acid plastics from waste vegetable fermentation brine• Dr. Bill Orts, USDA/ARS Albany CA. New NP306 project proposal

objective!

• What controls survival of STEC in acid and acidified foods?• Mixed acid effects• Clara Jones MS thesis -> questions…

• Risk Assessment• Dr. Don Schaffner, Rutgers University • Dr. Thomas Oscar, USDA/ARS, Wyndmoor PA• How much Listeria, Salmonella and E. coli is out there?

• ADS research needs?

Webinar hosted by IAFP: “Challenge studies for cold-fill-hold acidified foods” 250+ registered attendees. June 2018.

With:Drs. Barb Ingham Univ. Wissconsin

Elizabeth AndressUniv. Georgia

Other recent food safety work:

Nitrate and Nitrite in pickled vegetables: Food Control 2018 Vol. 90:304-311

Cold Fill Challenge Studies: Food Prot. Trends 2018 Vol. 38(5):322-328

Hot Fill Pasteurization Method: Food Prot. Trends 2018 Vol. 38(4) 258-265.

USDA, FDA, Academia and Industry

http://www.quoteambition.com/best-inspirational-teamwork-quotes-images/

Fred.Breidt@usda.govARS Food Science Research Unit

322 Schaub Hall, Box 7624

NC State Univ., Raleigh, NC 27695-7624

919-513-0186

Acknowledgements:

FDA

• Dr. Don Zink (retired)

• Mike Mignogna and Suzan

Brecher

Industry

• Assn for Dressings and Sauces

• Dr. Ritu Mishra, Clorox Co.

NC State University

• Ms. Madyson Longtin

• Dr. Don Bitzer

USDA/ARS

• Dr. Suzanne Johanningsmeier

• Ms. Summer Connelly-Payton

• Mr. Robert Price

• Dr. Pina Fratamico and Co.

• Dr. Elaine Berry and Co.

• South Korea and China

• Dr. Suh Soohwan (MFDS)

• Dr. Oh Deog Hwan

• Dr. Ding Zhanshen

The microbial world is smiling!