The Pennsylvania State University

The Graduate School

College of Agricultural Sciences

EVALUATION OF ELECTROLYZED WATER FOR CLEAN-IN-PLACE OF

DAIRY PROCESSING EQUIPMENT

A Thesis in

Food Science

by

Yun Yu

2014 Yun Yu

Submitted in Partial Fulfillment

of the Requirements

for the Degree of

Master of Science

May 2014

ii

The thesis of Yun Yu was reviewed and approved* by the following:

Robert F. Roberts

Professor of Food Science

Head of the Department of Food Science

Thesis Advisor

Catherine N. Cutter

Professor of Food Science

Gregory R. Ziegler

Professor of Food Science

Ali Demirci

Professor of Agricultural and Biological Engineering

*Signatures are on file in the Graduate School

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ABSTRACT

Good cleaning and sanitation practices in the dairy industry are essential to

maintaining public health and increasing profitability for producers. Dairy processing

equipment is commonly cleaned using a four-step clean-in-place (CIP) procedure: rinse

with water, wash with an alkaline solution, rinse with water again to remove alkaline

residue, and then rinse with an acid sanitizer. The chemicals used in CIP procedures of

dairy processing equipment are usually handled and stored in concentrated forms, and

may have adverse effects on the environment, and can cause skin or eye burns on contact.

Electrolyzed water is produced via electrolysis of a dilute sodium chloride solution,

which results in a sodium hydroxide solution, called electrolyzed reducing (ER) water

(pH ca. 11.0 and ORP ca. -850 mV), and an acidic solution, called electrolyzed oxidizing

(EO) water (pH ca. 2.5, ORP ca. 1168 mV and 80-100 ppm of chlorine). Thus,

electrolyzed water has the potential to serve as an alternative to CIP chemicals. The

antimicrobial efficacy of acid EO water has been demonstrated. The efficacy of

electrolyzed water used as cleaning and disinfecting agent for on-farm milking systems

also has been demonstrated. The use of acid EO water in CIP applications for dairy

processing systems, especially those involving heat treatment of milk has not been

evaluated.

The purpose of this research was to investigate the efficacy of electrolyzed water

for CIP procedure of dairy processing equipment, specifically a refrigerated milk storage

tank and a tank used for thermal processing of milk. In this work, a pilot scale test

system composed of a 15 liter (4 gallon) stainless steel test vessel was constructed and

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characterized to allow evaluation and optimization of electrolyzed water as CIP agent for

dairy processing equipment. Use of the test system was validated by pilot trials of CIP

cleaning with conventional CIP detergent and sanitizer. Using the same CIP procedure,

electrolyzed water was successfully employed to clean the test vessel after soiling with

milk at refrigerated temperatures (2-4°C). The effectiveness of cleaning was assessed

using a microbiological enrichment method, as well as ATP bioluminescence and

residual protein detection assays. Finally, use electrolyzed water for CIP procedures of

the test vessel soiled by heating milk was evaluated using a response surface model to

optimize temperatures and times for both alkaline ER water and acid EO water

treatments. Parameters for 4-step CIP procedures using electrolyzed water were: wash

with alkaline ER water at 54.6°C for 20.5 min and sanitize with acid EO water at 25°C

for 10 min. The validation study demonstrated that a complete CIP procedure using

electrolyzed water with optimal operational temperatures and time was capable of

returning the surface of the test vessel to a satisfactory clean condition with non-

detectable residual ATP and protein. The study demonstrated the cleaning efficacy and

potential application of using electrolyzed water for CIP procedures in dairy plant. In

contrast to conventional CIP chemicals that are usually prepared by diluting of

concentrated chemicals, electrolyzed water has the advantage of on-site generation, dairy

processing plants, especially small dairy foods manufactures, could benefit by reducing

the risk and cost of storing and handling of concentrated CIP chemicals.

v

TABLE OF CONTENTS

List of Figures ............................................................................................................. viii

List of Tables ............................................................................................................... x

List of Abbreviations ................................................................................................... xi

Acknowledgements ...................................................................................................... xiii

LITERATURE REVIEW ............................................................................ 1 Chapter 1

1.1 MICROORGANISMS IN MILK ................................................................... 2 1.1.1 Pseudomonas fluorescens ..................................................................... 3 1.1.2 Escherichia coli .................................................................................... 3

1.1.3 Enterococcus faecalis ........................................................................... 4 1.2 TANKS USED IN DAIRY PLANT ............................................................... 4

1.2.1 Raw milk silo ........................................................................................ 4

1.2.2 Processing tanks ................................................................................... 5 1.2.3 Fouling in milk process equipment ...................................................... 6

1.3 CLEANING AND SANITATION IN THE DAIRY INDUSTRY ................ 7 1.3.1 Importance of cleaning and sanitation .................................................. 7 1.3.2 Clean-out-of-place (COP) .................................................................... 8

1.3.3 Clean-in-place (CIP) ............................................................................. 9

1.3.4 Key factors influencing cleaning efficiency ......................................... 11 1.4 ASSESSMENT OF CLEANLINESS ............................................................. 17

1.4.1 Visual inspection .................................................................................. 17

1.4.2 Microbiological analysis ...................................................................... 17 1.4.3 ATP bioluminescence method .............................................................. 18

1.4.4 Protein residue detection ...................................................................... 21 1.5 ELECTROLYZED WATER .......................................................................... 22

1.5.1 History .................................................................................................. 22 1.5.2 Generation and Properties .................................................................... 22

1.5.3 Advantages and disadvantages of electrolyzed water: ......................... 24 1.5.4 Application of electrolyzed water in food industry .............................. 26

HYPOTHESIS AND OBJECTIVES .......................................................... 34 Chapter 2

CONSTRUCTION, CHARACTERIZATION AND VALIDATION OF Chapter 3

TEST SYSTEM .................................................................................................... 35

ABSTRACT ......................................................................................................... 35 3.1 INTRODUCTION .......................................................................................... 36

3.2 MATERIALS AND METHODS ................................................................... 38 3.2.1 Construction of test system .................................................................. 38 3.2.2 Characterization of the test system ....................................................... 41

vi

3.2.3 Performance validation of the test system used for CIP ....................... 42 3.2.4 Test for swab sampling variability ....................................................... 46

3.2.5 Statistical analysis ................................................................................ 47 3.3 RESULTS AND DISCUSSION ..................................................................... 49

3.3.1 Characterization of test system ............................................................. 49 3.3.2 Performance validation of the test system used for CIP ....................... 52 3.3.3 Test for swab sampling variability ....................................................... 54

3.4 CONCLUSION............................................................................................... 56

CIP USING ELECTROLYZED WATER FOR A REFRIGERATED Chapter 4

MILK STORAGE TANK ..................................................................................... 58

ABSTRACT ......................................................................................................... 58 4.1 INTRODUCTION .......................................................................................... 59 4.2 MATERIALS AND METHODS ................................................................... 62

4.2.1 Bacterial cultures verification and characterization ............................. 62 4.2.2 Preparation of inoculated milk ............................................................. 64

4.2.3 Generation and characterization of electrolyzed water ........................ 65 4.2.4 Preparation of commercial CIP chemicals ........................................... 66 4.2.5 Preparation of test system ..................................................................... 67

4.2.6 Soiling the system ................................................................................. 67 4.2.7 CIP procedure of electrolyzed water treatment .................................... 68

4.2.8 CIP control treatments .......................................................................... 69 4.2.9 Assessments of cleanliness and data collection .................................... 70

4.2.10 Statistical design and analysis ............................................................ 72 4.3 RESULTS AND DISCUSSION ..................................................................... 72

4.3.1 Inoculum bacterial cultures verification and characterization .............. 72 4.3.2 Chemical properties of electrolyzed water ........................................... 73 4.3.3 Cleanliness assessments ....................................................................... 74

4.3.4 CONCLUSION .................................................................................... 79

CIP USING ELECTROLYZED WATER FOR A HEATED MILK Chapter 5

PROCESSING TANK .......................................................................................... 80

ABSTRACT ......................................................................................................... 80

5.1 INTRODUCTION .......................................................................................... 81 5.2 MATERIALS AND METHODS ................................................................... 83

5.2.1 Preparation of electrolyzed water ......................................................... 83 5.2.2 Experimental design -- response surface model ................................... 84 5.2.3 Soiling and CIP treatments ................................................................... 86 5.2.4 Cleanliness assessments ....................................................................... 87 5.2.5 Other potential factors (Nuisance factor) ............................................. 89

5.2.6 Data analyses and modeling ................................................................. 92 5.2.7 Validation ............................................................................................. 96

5.3 RESULTS AND DISCUSSION ..................................................................... 96

vii

5.3.1 Assessment the importance of nuisance factors ................................... 96 5.3.2 Regression model of RLU3 data after wash and post-rinse ................. 98

5.3.3 Regression model of RLU4 data after sanitizing ................................. 102 5.3.4 Regression model of Protein data ......................................................... 104 5.3.5 Validation ............................................................................................. 106

5.4 CONCLUSION............................................................................................... 109

CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE Chapter 6

RESEARCH ......................................................................................................... 111

REFERENCES: ........................................................................................................... 112

APPENDIX: ................................................................................................................. 120

viii

LIST OF FIGURES

Figure 1-1. Schematic of electrolyzed water generator and produced compounds

(Huang et al., 2008). ............................................................................................. 24

Figure 3-1. Schematic of pilot scale dairy processing test system. ............................. 38

Figure 3-2. Test system. (A) Test vessel (center of the system) with agitator in

place. (B) A modified stainless steel milk can served as reservoir for water

used for CIP cleaning. (C) CIP solution reservoir with coil heat exchanger

connected to a circulating water bath. (D) 360° static spray ball. ....................... 40

Figure 3-3. Flow chart of CIP performance evaluation of test system. CIP

cleaning was conducted at flow rate of 8.3 L/min. ............................................... 43

Figure 3-4. Schematic of test for swab sampling variability. Each rectangle area

represents 50 cm2 (5 cm × 10 cm) inner surface of test vessel. Different

colors represent the sampling for ATP bioluminescence assays after different

steps. Red marked areas were swabbed “after soiling”, green areas were

swabbed “after pre-rinse”, and blue areas were swabed “after sanitizing”. For

one trial, each assessments of ATP bioluminescence assays was conducted in

three replicates. ..................................................................................................... 48

Figure 3-5. Mean volumetric flow rates (L/min) at different VFD pump settings.

The regression equation is: Flow Rate (L/min) = 0.1844 + 0.1918 Pump

Setting. .................................................................................................................. 49

Figure 3-6. Riboflavin coverage test. (A) Riboflavin solution sprayed on test

vessel before rinse. (B) Residual riboflavin remaining after rinsing test

vessel with water at flow rate of 1.8 L/min (pump setting of 10) for 1 min.

(C) Residual riboflavin remaining after rinsing test vessel with water at flow

rate of 3.9 L/min (pump setting of 20) for 7 min. (D) Residual riboflavin

remaining after rinsing test vessel with water at flow rate of 6.0 L/min (pump

setting of 30) for 17 min. (E) Residual riboflavin remaining after rinsing test

vessel with water at flow rate of 8.3 L/min (pump setting of 40) for 1 min. ........ 51

Figure 3-7. Log10 RLU values of after soiling, after pre-rinse, and after sanitizing.

Error bars represent standard deviation of the evaluations of three locations.

Tukey’s comparison was conducted between 9 sets of data. Means that do

not share a letter are significantly different (α = 0.05). ........................................ 55

Figure 4-1. Electrolyzed water generator used in this research.(Model ROX20,

Hoshizaki America Inc.) ....................................................................................... 65

Figure 4-2. Flow chart of CIP procedures of cold milk storage tank using

electrolyzed water. CIP procedures were conducted at flow rate of 8.3 L/min. .. 71

ix

Figure 4-3. Mean populations of cultures during overnight incubation. Error bars

represent standard deviation of the log10 CFU/ml of three replicates.

Tukey’s comparisons were conducted between three sets of data at each

sampling point. Means that do not share a letter are significantly different (α

= 0.05). .................................................................................................................. 73

Figure 5-1. Flow chart for CIP procedure of hot milk processing tank using

electrolyzed water. ................................................................................................ 87

Figure 5-2. Contour plot of versus treatment time and

temperature of ER water wash, generated based on regression model

(Equation 6). ......................................................................................................... 99

Figure 5-3. Surface plot of versus treatment time and

temperature of ER water wash, generated based on regression model

(Equation 6). ......................................................................................................... 100

Figure 5-4. Optimization plot for ln((RLU2-RLU3)/RLU2) versus treatment time

and temperature of ER water wash. The plot suggested the highest

desirability was 0.98, when setting ER water wash temperature at 54.6°C and

time at 20.5 min, and the predicted ln((RLU2-RLU3)/RLU2) = -0.0092,

indicating 99.08% of RLU reduction. ................................................................... 101

Figure 5-5. Optimization plot for “RLU2-RLU4” and “ln((RLU2-RLU3)/RLU2)”.

When setting ER water wash parameters at 53.7°C for 21.6min, setting EO

water sanitizing parameters at 25°C for 10 min, it can be predicted that RLU

reduction achieved 99.08% after ER water treatment, 1.99 × 106 after EO

water treatment, respectively. ............................................................................... 104

Figure 5-6. Means of RLU values comparison between treatments. Error bar

indicates standard deviation of triplicate analysis. Tukey’s comparisons were

conducted between all RLU values. Means that do not share a letter are

significantly different (α = 0.05). (Pos. Ctrl = positive control; EW validation

= electrolyzed water treatment with optimal parameters; Neg. Ctrl = negative

control). ................................................................................................................. 108

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LIST OF TABLES

Table 3-1. Cleanliness assessments made using of ATP and protein measurements

after different steps of standard CIP procedure using commercial chemicals

(*RLU values of zero were assigned as 0.5 for base-10 logarithm

calculation). .......................................................................................................... 53

Table 4-1. Operation temperature and time of four treatments. .................................. 69

Table 4-2. Chemical properties of electrolyzed water of each trial. P-values were

obtained from Tukey’s comparison between treatments. ..................................... 74

Table 4-3. Microbiological data of inoculated milk after soiling and of swab

enrichment test. ..................................................................................................... 75

Table 4-4. Protein residue levels. ................................................................................. 78

Table 5-1. Levels of four independent variables for CIP using electrolyzed water. ... 84

Table 5-2. Box-Behnken response surface design with 27 trails, including 3 center

points (in bold). WashTemp = temperature for ER water wash; WashTime =

time for ER water wash; SaniTemp = Temperature for EO water sanitizing;

SaniTime = Time for EO water sanitizing. ........................................................... 85

Table 5-3. Summary of cleanliness assessments at different sampling points. ........... 88

Table 5-4. P-values of Pearson correlations between variables. Small p-values (<

0.05) indicated the corresponding pair of variables may be related. .................... 97

Table 5-5. Response surface regression: “ln((RLU2-RLU3)/RLU2)” as a function

of ER water treatment temperature and time (WashTemp = temperature of

ER water treatment; WashTime = treatment time of ER water wash). ................ 99

Table 5-6. Regression of “RLU2-RLU4” versus ER water and EO water treatment

factors (WashTemp = temperature of ER water treatment; WashTime =

treatment time of ER water wash; SaniTemp = temperature of EO water

treatment; SaniTime = treatment time of EO water sanitizing). ........................... 103

Table 5-7. Protein detection of validation experiment and control treatments

(where Pos. Ctrl = positive control; EW validation = electrolyzed water

treatment with optimal parameters; Neg. Ctrl = negative control). ...................... 108

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LIST OF ABBREVIATIONS

⁰C degree Celsius

ANOVA analysis of variance

APC aerobic plate count

ATP adenosine triphosphate

BCA bicinchoninic acid

BLAST basic local alignment search tool

CFU colony forming unit

CIP clean in place

COP clean out of place

CPC calcium phosphate-citrate

DNA deoxyribonucleic acid

EO water electrolyzed oxidizing water

ER water electrolyzed reducing water

EW electrolyzed water

GMP good manufacturing practice

HACCP hazard analysis critical control point

HTST high-temperature short-time

ml milliliter

mM millimolar

ORP oxidation reduction potential

PI pre-incubation

PMO pasteurized milk ordinance

ppm parts per million

RLU relative light unit

rRNA ribosomal ribonucleic acid

SPC standard plate count

spp. species

xii

St. Dev. standard deviation

TSA trypticase soy agar

TSB trypticase soy broth

UV ultraviolet

VFD variable-frequency drive

μl microliter

μM micromolar

xiii

ACKNOWLEDGEMENTS

This work was carried out at the Department of Food Science, the Pennsylvania

State University, and funded by a USDA milk safety grant. I would like to express my

appreciation to the department and funding agency for giving me the opportunity and

support needed to pursue a Master of Science degree. This thesis could not have been

completed without the help and support of many people. I would like to take this time to

thank those people.

I owe my deepest gratitude to my advisor Dr. Robert Roberts for giving me the

opportunity to study Food Science under his guidance. Dr. Roberts is a great mentor,

who is always encouraging, supportive, and patient. It was a wonderful learning

experience working with Dr. Roberts. The knowledge, skills, and confidence that I

gained in Dr. Roberts’ lab will be invaluable in my career development. I look forward

to continuing to pursue a Ph.D. degree under Dr. Roberts’ guidance.

I would like to express my appreciation to my committee members Dr. Gregory

Ziegler, Dr. Catherine Cutter, and Dr. Ali Demirci. I would like to thank Dr. Ziegler for

the suggestions on experimental design and statistical analyses. His support helped me

broaden my knowledge in engineering and statistics. I would like to thank Dr. Cutter for

her knowledge and experiences, and for caring about this project. I would also like to

thank Dr. Demirci for bringing up the project, and for his enthusiasm, experiences and

support of this project.

I would like to thank my lab mates, Dr. Emily Furumoto, Dr. Joe Loquasto,

Zhaoyong Ba, and Sarah Brown for the help, suggestions, and support. I would

xiv

especially thank Dr. Emily Furumoto for helping with ordering suppliers for the project.

I also would like to thank undergraduate helpers, especially Jeff Amos, for the help with

my experiments.

I would like to thank faculty, staff and my fellow graduate students. Without their

help, encouragement, and friendship, I would not have been able to complete the graduate

courses and my research, and stay cheered during graduate school.

I would like to thank staff in Berkey Creamery, especially thank to Tom Palchak

for his support and caring, to David Long for helping me with modifying the pilot scale

test system, to Bonnie Ford, Bill Kurtz, and Bob Rosenberry for teaching me the

procedures and tests of cleaning. I also would like to thank Mark Ivkovich from the

Ecolab Inc. and Vivian Saunders from the Charm Inc. for their technique support.

Lastly, I would like to thank my husband Kan Shen, my friends in State College

and my Family in China, for their love and support during the graduate school.

1

Chapter 1

LITERATURE REVIEW

America’s dairy industry is a key economic component of agricultural business

and an important contributor to the nation’s overall economy. This industry includes

small and large dairy farms, dairy foods processors and those corporations involved with

marketing, selling and transporting dairy products. Dairy products are produced in all 50

states and more than 130,000 jobs are created by the dairy industry, including those on

dairy farms, in dairy processing, marketing and transportation, retail stores and other

companies related to the dairy industry (USDA, 2004). Consumers in the United States

spend over 11% of their food expenses on dairy products (Markets, 2006). In

Pennsylvania, according to the Center for Dairy Excellence, the dairy industry generates

more cash receipts than any other agricultural industry in the state. Approximately 40%

of the $3.8 billion in agricultural cash receipts comes from the dairy industry. In

addition, the dairy industry is also a vital economic stimulus to the state and supports

about 40,000 job opportunities (Wolff, 2010).

Dairy products are an ideal growth medium for many microorganisms. The

Centers for Disease Control (CDC) reported 29 outbreaks associated with pasteurized

dairy products between 1998 and 2012 in U.S. (CDC, 2013). Thus, good practices of

cleaning and sanitizing in the dairy industry are essential to decreasing the risk of

outbreaks for public health and increasing profitability for producers.

2

1.1 MICROORGANISMS IN MILK

Milk is a highly perishable food that supports the growth of microorganisms,

which can lead to chemical changes during storage. The nutrients contained in milk, such

as lactose, milk fat, whey proteins, casein, other trace elements and vitamins are

favorable for microbial growth. In addition, the neutral pH value (pH = 6.8) and high

water activity (aw = 0.97 to 1.00) of milk also favor bacterial multiplication (Mostert and

Buys, 2008). Furthermore, some enzymes, produced by bacteria or which originate in the

cow’s udder, can cause chemical degradation of milk components (proteolysis, lipolysis,

etc.) (Bylund, 2003; Robinson, 2002).

Although milk is considered sterile when secreted from healthy cows, it can be

contaminated by microorganisms during the milking process from a variety of different

sources. One of the major sources of bacterial contamination is insufficiently cleaned

and sanitized processing equipment (Robinson, 2002). Microorganisms can also come

from water supplies on the dairy farm, from soil or vegetation near the dairy farm (Rice

and Johnson, 2000), from the exterior of teats or udders, and from the udder canal, in the

case of mastitis (Bylund, 2003; Robinson, 2002).

The numbers and types of microorganisms present in milk differ between farms.

In the United States, the maximum allowable standard plate count (SPC) for Grade A raw

milk is < 100,000 CFU/ml before commingling, and < 300,000 CFU/ml for commingled

milk prior to pasteurization (USDHHS, PHS, & FDA, 2011). Typical groups of

microorganisms present in raw milk include psychrotrophic, mesophilic aerobic, and

thermoduric bacteria (Robinson, 2002).

3

1.1.1 Pseudomonas fluorescens

In milk, psychrotrophic microorganisms, which can multiply at refrigerated

temperatures (< 7°C), are often Gram-negative rods. Pseudomonas fluorescens is the

most common psychrotroph occurring in raw milk, and also occurs typically in processed

dairy products as a result of post-pasteurization contamination (Robinson, 2002; Dogan

and Boor, 2003). Contamination with Pseudomonas spp. is a major contributor to shelf-

life reduction. Pseudomonas spp. are known to produce enzymes, such as lipases and

proteases, at refrigerated temperatures, which are heat stable and remain active after

thermal processing. Such enzymes reduce the shelf life of dairy products due to

degradation of milk compounds, leading to off-flavors and odors (Sørhaug and Stepaniak,

1997; Dogan and Boor, 2003).

1.1.2 Escherichia coli

Coliforms are another group of Gram-negative, rod-shaped bacteria often present

in raw milk. Escherichia coli is one specie contained in this group. Although E. coli is

recognized as a fecal-associated microorganism, the presence of E. coli does not provide

direct evidence of fecal contamination (WHO, 1993). Rather, the presence of E. coli

suggests inadequate cleaning of udders prior to milking or unsatisfactory sanitizing

practices. Although most E. coli are non-pathogenic isolates, some pathogenic strains of

E. coli, such as E. coli O157:H7 can cause severe disease in humans.

4

1.1.3 Enterococcus faecalis

Enterococcus spp. including Enterococcus faecalis are a genus of mesophilic

streptococci, which are Gram-positive, non-spore-forming, lactic acid bacteria (Robinson,

2002). E. faecalis is frequently isolated from dairy food products (Gaspar et al., 2009).

Enterococcus spp. is a controversial genus. Some species of Enterococcus spp. are used

as starter cultures or occur as non-starter cultures in food fermentations, such as during

the production of artisan cheeses in Europe. Specific strains of E. faecalis and E. faecium

have been shown to produce bacteriocins that inhibit spoilage or pathogenic bacteria, and

some are known to develop positive sensory characteristics (Giraffa, 2003). However, it

has been shown that some isolates of E. faecalis are potentially pathogenic to humans

(Giraffa et al., 1997).

1.2 TANKS USED IN DAIRY PLANT

A variety of tanks are used in dairy processing facilities. Two major categories

are refrigerated storage tanks (silos) and tanks used to thermally process milk.

1.2.1 Raw milk silo

Since milk is a good growth medium for microorganisms, development of

refrigerated storage was important for maintaining high quality and extending shelf-life

of milk (Robinson, 2002). The milk silo often serves as a storage vessel for received raw

milk, which is held at refrigerated temperature in dairy processing plants. Capacities of

5

raw milk silos range from 3,000 gallons to 70,000 gallons; many processing facilities

have multiple silos, depending upon the capacity of manufacture and the schedule of raw

milk delivery (Bylund, 2003). Most milk silos are located outdoors with double-walled

construction for better insulation. The inside walls usually are made of stainless steel

(grade ss304 or ss316) to reduce fouling and enhance cleanability (Mostert and Buys,

2008). Milk silos are usually equipped with temperature and level indicators. Agitators

are installed near the bottom of silos. After emptying a silo, a thin film of milk may be

adhered to the wall. As such, cleaning should be applied as soon as possible after

emptying because it is more difficult to remove milk residue when it has dried onto the

surface (Bylund, 2003). Because of the size of silos, clean-in-place (CIP) methods

usually are applied.

1.2.2 Processing tanks

Processing tanks, such as yogurt fermentation tanks, tanks for starter culture

preparation, and batch pasteurizers, are used commonly in the dairy industry. Processing

tanks are also made of stainless steel. Although the properties and configurations of

processing tanks vary, most processing tanks are equipped with agitators and temperature

controling and monitoring systems. Heat treatment of milk results in more difficult soil

removal (Bylund, 2003). When milk is heated to 60°C or above, milk proteins,

especially whey proteins, begin to denature. The denatured proteins may bind to the

equipment surface and form aggregates that are difficult to remove (Robinson, 2002).

Milk salts, such as calcium, magnesium, sodium, potassium etc., are equilibrated between

6

a soluble and colloidal phase (Walstra et al., 2006a). When milk is heated above 60°C,

milk salts become less soluble and transform into a colloidal phase. In other words, the

proportion of insoluble calcium phosphate increases (Marriott and Gravani, 2006). In

addition, by combining with denatured proteins, “milk stone” can deposit quickly on

heated surfaces (Walstra et al., 2006a; Marriott and Gravani, 2006).

1.2.3 Fouling in milk process equipment

Soiling in dairy plants occurs when undesired materials deposit on equipment

surfaces, including liquid milk or other dairy product residues,and other foreign matters

such as lubricants or water scale. Dairy soil is a complex material consisting of inorganic

(minerals) and organic compounds (lactose, proteins, and fat). Some compounds, such as

lactose and sodium, are soluble in water and are easy to remove using a water rinse.

Other compounds, including proteins, fat and some mineral salts are less soluble in water.

To remove this type of soil, alkaline detergents or surface-active agents are generally

required (Mostert and Buys, 2008; Bylund, 2003).

The composition of soil complexes deposited on different dairy processing

equipment depends upon product compositions and specific operational conditions.

Stanga (2010) summarized studies that were published by Harper (1972) and Belitz

(1987), and compared the composition of cold milk fouling and hot milk fouling. The

average composition of cold milk soil was 26.6% protein, 38.1% sugar, 29.95% fat and

5.3% minerals; the average composition of hot milk soil was 30.3% protein, trace level of

sugar, 23.1% fat and 46.6% mineral (Stanga, 2010). On cold surfaces, such as raw milk

7

pipelines or raw milk silos, fouling was light and less viscous, and could be cleaned

easily with water (Stanga, 2010). On heated surfaces, the mechanisms of fouling were

different, when compared with cold surfaces. Researchers proposed three fouling

mechanisms that could occur on dairy processing equipment surfaces associated with

heat treatment, including reaction fouling (e.g. whey protein denaturation); crystallization

or precipitation fouling (e.g. the formation of milk stone from proteins and calcium

phosphate); and biological fouling (e.g. attachment of a single microorganism to growth

of biofilms) (Fryer et al., 2011; Fryer and Asteriadou, 2009).

1.3 CLEANING AND SANITATION IN THE DAIRY INDUSTRY

1.3.1 Importance of cleaning and sanitation

Good practices of cleaning and sanitation are important in food manufacturing.

When soil is deposited on the surface of equipment, the performance of processing, and

efficiency of heat exchangers, is reduced. In addition, food residue deposits favor

microbial growth and may lead to food quality and safety issues. Furthermore, cross

contamination between batches can affect the quality of food, or result in contamination

with food allergens. Fryer and Asteriadou (2009) proposed a five-stage model of fouling:

initiation, transportation, attachment, removal, and aging. They indicated that drying or

hardening of the food deposit (aging stage) changes the nature of the deposit and

increases difficulty in cleaning (Fryer and Asteriadou, 2009). Thus, once processing has

8

been completed, cleaning should be begun as soon as possible (Bylund, 2003). There are

two main strategies for cleaning: clean-out-of place (COP) and clean-in-place (CIP).

1.3.2 Clean-out-of-place (COP)

There are some pieces of dairy processing equipment (e.g. parts of separators,

homogenizers, and fillers) need to be cleaned manually using clean-out-of-place (COP)

technology (Mostert and Buys, 2008). Another situation, when heavy deposits have

occurred, COP operation, such as manual scrubbing, may also be required (Mostert and

Buys, 2008).

The procedure for COP is described as follows: a) disconnect or dismantle parts;

b) pre-rinse dismantled parts with warm water (20-40°C) to remove loose fouling; c)

prepare detergent solution with correct concentration (alkaline chlorinated cleansers are

usually used); d) wash pre-rinsed parts with warm detergent (40-60°C) and by manually

brushing or by submerging in COP tanks, in which alkaline cleaning solution is circulated

(i.e. dishwasher); e) post-rinse with water to remove detergent residue; and f) sanitize

parts with hot water or chemical sanitizer (e.g. chlorine sanitizer) by spraying or dipping

(Tamime and Robinson, 1999; Mostert and Buys, 2008; Marriott and Gravani, 2006).

Some limitations must be considered when comparing COP with CIP. Compared

with CIP operations, COP cleaning is more laborious. With manual operations, only

moderate temperatures and mild cleaning solutions can be applied to avoid skin irritation

or burning of employees (Marriott and Gravani, 2006). To assure efficacy and

appropriate methods for COP, well developed standard operating procedures (SOPs) and

9

training, as well as implementation of good manufacturing practices (GMP) are essential

to efficient COP operations (Mostert and Buys, 2008).

1.3.3 Clean-in-place (CIP)

Clean-in-place (CIP) was first developed in the 1960s and is employed frequently

in the dairy industry (Tamime and Robinson, 1999). CIP is defined as cleaning and

sanitizing the entire pipe line, vessel, or other food processing system without

dismantling or opening; by circulating or spraying water or cleaning solutions throughout

the system (Tamime, 2008).

Although the specific CIP program will vary, depending upon the type of

equipment and the nature of the soil, the basic procedures are similar and can be

summarized as follows (Bylund, 2003; Mostert and Buys, 2008; Walstra et al., 2006b):

Recovery of product residues: During this step, the product is drained from the

equipment to facilitate cleaning. To minimize product losses and reduce the load of

sewage, some plants use high quality water to “chase” product out of the equipment.

Pre-rinse with water: After draining the equipment, the next step is to rinse with

water. The purpose of the pre-rinse step is to remove bulk fouling and to loosen any soil

attached to equipment surfaces. Softened water is preferred for the pre-rinsing step to

prevent formation of water scale. A cold pre-rinse is sufficient for removal of light

fouling, such as that deposited in cold milk tanks. A warm temperature is recommended

for removal of thick and fatty fouling such as cream, yogurt or ice cream mix, since a

temperature of at least 32.2°C is needed to melt the fat (Lloyd, 2008). However, it is

10

recommended the temperature not surpass 55°C to avoid denaturation of proteins, which

will make cleaning more difficult. The pre-rinsing step should be conducted until the

water runs clear. An efficient pre-rinsing should remove 90~99% of bulk soil (Bylund,

2003).

Detergent wash cycles and intermediate rinsing with water: Following the pre-

rising step, a wash cycle is applied. This step usually involves circulating alkaline

detergent for a period of time. The alkaline detergent removes most of the attached soil,

including proteins and milk fat. In some systems, after an intermediate rinse with water

to remove all traces of alkaline cleanser, another wash step, employing an acid detergent

is performed. This acid wash step is optional and usually applied once a week for

removal of mineral based soil (e.g. milk stone) from equipment, such as heat exchangers

and other thermal processing equipment.

Sanitizing or disinfection: After post-rinsing with water to remove residual

detergent, the sanitizing step is conducted. The process of sanitizing reduces microbial

contamination to levels considered safe from a public health perspective, by destroying

vegetative cells. There were two methods used for sanitation or disinfection: thermal

disinfection and chemical disinfection. Thermal treatments, such as running hot water

(~85°C) or steam within systems, are applied normally for disinfection of high-

temperature short-time (HTST) pasteurizers. A minimum exposure of equipment surface

to a temperature at 77°C for 5 minutes is required for hot water sanitizing

(USDHS/PHS/FDA, 2011). Chemical sanitizers, such as chlorine, iodophors, quaternary

ammonium compounds and peroxy acid compounds are also commonly used in dairy

plants (Boufford, 2003). Sanitizing could be applied immediately before processing, or

11

at the end of CIP cycles. If a processing system is shut down for more than 4 hours

between shifts, re-sanitizing before manufacturing is recommended (Mauck et al., 2001).

1.3.4 Key factors influencing cleaning efficiency

Sinner (1960) proposed four factors that influence cleaning efficiency: operating

temperature, action or mechanical force, chemistry of detergent and sanitizer, and contact

time (TACT) (Packman et al., 2008). Those four factors interact and must be considered

together. Each of the four factors is described in following sections.

1.3.4.1 Temperature

During cleaning, suitable operating temperatures must be high enough to melt

milk fat to ease removal, but low enough to prevent protein denaturation, which would

make cleaning more difficult (Tamime and Robinson, 1999). In general, the

effectiveness of cleaning is improved as the temperature increases. However, there are

limitations to maximum operating temperatures. COP cleaning or manually cleaning is

usually carried out at less than 60°C for safety reasons (to avoid human injury). When

using enzyme-based detergents, temperature is usually limited to less than 55°C to assure

the enzyme remains active. For heavily fouled surfaces, such as yogurt processing

equipment, CIP procedures might be conducted at higher temperature (85-90°C). When

using chlorinated sanitizer, the operating temperature for sanitizing should be less than

40°C to avoid chlorine volatilization (Tamime and Robinson, 1999).

12

1.3.4.2 Action (mechanical force)

Mechanical forces in CIP procedures include flow rate and flow pressure, which

provide the energy needed for lifting fouling from surface.

For cleaning pipe lines, a sufficient flow rate is essential to provide turbulent flow

for better efficiency of soil removal. Centers for Disease Control and Prevention (CDC)

recommend 1.5 m/s (5 feet/sec) as the minimum flow rate. This means 75 L/min (20

gallon/min) for a 3.8 cm-diameter (1.5 inch) pipe, and 568 L/min (150 gallon/min) for a

10 cm-diameter (4 inch) pipe (CDC, 2012). Bylund (2003) also indicates that flow

velocities of 1.5~3.0 m/s in the pipes provide a turbulent flow.

For CIP cleaning of dairy tanks, simple distribution devices are often applied.

Static spray balls are used to provide a high flow rate and low pressure cleaning liquid;

while rotating devices, such as rotating spray heads and rotating jet heads, enhance the

impact of cleaning liquid by providing higher pressure (Moerman, 2005). In general,

when cleaning a tank, liquid is sprayed on the upper part of the tank, and then falls down

the tank wall in the form of falling film (Bylund, 2003). Coverage is another important

parameter when considering mechanical force. Coverage is classified as direct coverage

or indirect coverage. Direct coverage occurs when the cleaning liquid contacts the

surface to be cleaned directly from the spray device. Indirect coverage results from either

a splash-back effect or falling film effect on tank wall. When cleaning larger tanks,

multiple spray devices might be installed in order to achieve full coverage.

A method used to assess completeness of CIP coverage, the riboflavin-

fluorescence test is commonly used in the dairy and pharmaceutical industries (Tamime,

13

2008). Riboflavin is a water soluble dye that presents bright yellow/green fluorescence

under UV/black light with wave length of 365 nm. To perform this test, a riboflavin

water solution (200 ppm) is sprayed on the surface to be inspected. After delivering

water through a spray device under the flow rate of the CIP cycle for a certain period of

time, the riboflavin residue is inspected with a black light. Any surface that is not

sufficiently rinsed presents fluorescence.

1.3.4.3 Chemicals used in cleaning and sanitizing

In addition to water, which is the solvent and makes up the bulk of the cleaning

compounds, various detergents and sanitizers are employed.

1.3.4.3.1 Alkaline detergents

Sodium hydroxide (NaOH, caustic soda), is typically used in alkaline detergent.

Sodium hydroxide saponifies fat, and converts fat to soap (fatty acid salt), which helps

remove other organic contamination, such as proteins. This is called saponification. In

addition to saponification, alkaline cleansers provide negative ions, which disrupt the

structure, swell, break the soil, and disperse small soil particles into the cleaning solution

due to electrostatic repulsion. Other alkali compounds, including potassium hydroxide

(caustic potash), sodium carbonate (soda ash), sodium silicates, and trisodium phosphate

(TSP), also can serve as ingredients in alkaline detergent (Mauck et al., 2001).

In addition to alkali compounds, surfactants are often employed in alkaline

detergents, and serve as wetting, emulsification and suspension functions, to promote

removal of deposits. Wetting agents function by reducing surface tension and promote

14

penetration of detergent into the soil (Bylund, 2003). Anionic surfactants, such as teepol

(alkyl aryl sulphonate), are high foamers and usually are used as a wetting agent. Other

anionic surfactants, such as sodium triphosphate and complex phosphate compounds,

promote emulsification by absorbing at the oil-water interface, to promote removal of soil

from the surface and maintain soils suspended in cleaning solutions, without re-

deposition or flocculation.

Unlike anionic surfactants, nonionic surfactants are added usually into CIP

cleansers as defoamers, which are usually used at higher temperatures (>40°C). To

prevent precipitation of hard water scale, sequestrants, such as phosphates and EDTA, are

often added to detergent formulations. Sequestrants also help in removal of fouling that

may complex with metallic ions (calcium and magnesium) (Watkinson, 2008).

1.3.4.3.2 Acid detergents

Acid detergents are used for removal of mineral deposits, and to prevent milk

stone formation on dairy processing equipment. Commonly used acids include

phosphoric, nitric, sulfamic and hydrochloric. Sometimes, organic acids, such as

hydroxyacetic acid, citric acid and gluconic acid are also used. An acid rinse is usually

applied once a week, and an “override” cleaning strategy may be employed. In this

strategy, the acid rinse is applied first and then the alkaline detergent is added to

“override” the acid. Override systems save time, water and energy.

1.3.4.3.3 Sanitizers/disinfectants

Chlorine is commonly used in the dairy industry as a sanitizing agent. Chlorine

has a broad antimicrobial activity against bacteria, fungi, and bacteriophage. The main

15

functional compound in chlorine sanitizer solutions is hypochlorous acid (HClO). The

hypochlorite ions kill microorganisms by attacking lipids in cell walls and destroying the

cell membrane structure and enzymes inside the cells. Chlorine compounds also have a

cleaning function and peptize proteins thus enhancing their solubility (Mauck et al.,

2001). Chlorine is stable at higher pH (pH >7), but releases chlorine gas and becomes

toxic and corrosive when the pH falls below 4.0 (Marriott, 1997).

In addition to chlorine, idophores and quaternary ammonium compounds (QACs)

also are used as disinfectants in the dairy industry (Tamime and Robinson, 1999).

Iodophors contain iodine, surfactants and acids, which are more stable and less corrosive

than chlorine. QACs are effective against bacteria, yeasts and molds, and can provide

residual antimicrobial activity in no-rinse applications. Neither iodophors or QACs are

used commonly as CIP sanitizers due to foaming problems (Marriott, 1997).

In addition to a sanitizing function, acid sanitizers also can prevent mineral or

milk stone build up. Those sanitizers include acid-anionic sanitizers, carboxylic acid

sanitizers, and peroxy acid sanitizers.

Acid-anionic sanitizers, containing anionic surfactants and acids, are used as no-

rinse food contact surface sanitizers, which are non-staining and noncorrosive to stainless

steel. This class of sanitizers is less effective against yeasts and molds, when compared

to chlorine. Use of acid-anionic sanitizers is limited in CIP applications due to foaming

issues (Boufford, 2003).

In contrast, carboxylic acid sanitizers, such as sulfonated fatty acids, have lower

foaming characteristics (Boufford, 2003). Carboxylic acid sanitizers are also non-

corrosive to stainless steel. However, carboxylic acid sanitizers may damage plastics and

16

rubber materials at temperatures above 38°C. Both acid-anionic sanitizers and carboxylic

acid sanitizers are active at low pH (pH 2-3, and pH <4, respectively), and may cause

corrosion to stainless steel, when the water is high in chlorine.

When compared with acid-anionic and carboxylic acid sanitizers, peroxy acid

sanitizers have low foam characteristics and a broad range of active pH, up to pH 7.5

(Boufford, 2003). Peroxy acid sanitizers also are less corrosive than chlorine and

idophores. It has been found that peroxy sanitizers are one of the most effective

sanitizers against Listeria and Salmonella (Marriott, 1997). When compared with

organic acids, the antimicrobial effectiveness of peroxy acid sanitizers is improved,

making them more effective against various yeasts and molds.

1.3.4.4 Contact time

Sufficient contact time is essential for effective cleaning. The contact time

required is dependent on the type of equipment, the nature of the soil, and the cleaning

solutions applied. For example, cleaning a pasteurizer requires longer contact time than

cleaning a refrigerated milk storage tank, because the deposit is heavier and includes

heat-denatured protein on the surface of the heat exchanger surfaces of the pasteurizer.

However, the costs of energy for heating and pumping, water and labor also need to be

considered when determining contact time of cleaning programs (Romney, 1990).

17

1.4 ASSESSMENT OF CLEANLINESS

Various methods have been used to evaluate cleanliness in dairy processing

plants, to monitor hygienic conditions, to evaluate cleaning efficiency, and to adjust or

optimize cleaning procedures. Methods for assessments of surface cleanliness include:

visual inspection, microbiological analysis, ATP bioluminescence or protein residue

detection (Asteriadou and Fryer, 2008).

1.4.1 Visual inspection

The Dairy Practices Council (2001) recommends application of visual cleanliness

inspection to surfaces that are difficult to clean in dairy processing systems. Areas

specifically mentioned included “dead ends” in pipelines, valves, and gaskets. A clean

stainless steel surface should be bright, with no residual moisture, scum, or loose

deposits. In addition to visual examination, sour or stale odors can indicate inadequate

cleaning (Asteriadou and Fryer, 2008).

1.4.2 Microbiological analysis

Microbiological analysis to assess surface hygiene can be conducted using

different methods, including the contact plate method, swab-based sampling methods,

and the “rinse-count” methods. The contact plate method samples equipment surface by

pressing an appropriate agar against the surface, followed by incubation to allow bacteria

present on the surface to grow and produce visible colonies that can be counted

18

(Robinson, 2002). The contact plate method is most suitable for sampling flat or slightly

curved surfaces that are smooth and non-porous. Swab-based sampling methods collect

cells by rubbing equipment surfaces with a moistened swab or sponge. Swabbing

methods may not be applied to some areas that are hard to reach by hand. Rinse count

methods can be applied to any surface, and are especially useful on hard-to-reach areas.

In this method, small pieces of equipment can be rinsed with a sterile liquid. The rinse

solution is examined using viable count procedures for general aerobic microorganisms,

coliforms, or other specific groups. Rinse count methods are less sensitive, when

compared to the contact plate methods or swab sampling methods because the sample has

been diluted. In addition to surface sampling, finished product evaluations such as the

standard plate count (SPC) and ongoing shelf-life assessments, also indicate hygienic

conditions of dairy processing equipment.

1.4.3 ATP bioluminescence method

1.4.3.1 ATP in milk

Adenosine-5’-triphosphate (ATP) is a molecule found in all living organisms. In

bovine milk, ATP molecules are associated with bacterial cells, somatic cells, and there

are also free-ATP molecules associated with colloidal calcium phosphate-citrate (CPC)

complex of casein micelles (Richardson et al., 1980). Richardson et al. (1980) indicated

that the primary source of ATP in bovine milk was free ATP. In addition, the

concentration of ATP in bovine milk was not closely related to the bacterial population

19

and somatic cell levels (Richardson et al., 1980; Poulis et al., 1993). Although ATP

molecules present on dairy processing equipment may indicate bacterial contamination.

ATP also indicates the presence of food residues.

1.4.3.2 Mechanism of ATP bioluminescence assay

The ATP bioluminescence assay, based on the luciferin-luciferase system, is

widely used in the food industry for monitoring hygiene (Griffiths, 1996). The luciferin-

luciferase system is a substrate-enzyme complex found in the firefly, Photinus pyralis

(Griffiths, 1993, 1996). In this reaction, luciferin binds with ATP, forming a dianion of

luciferyl-adenylate-AMP, and then the luciferyl-adenylate-AMP complex is oxidized by

O2 and converted to oxyluciferyl-adenylate-AMP, a cyclic dioxetanone. The oxidation

reaction is followed by decarboxylation, loss of AMP, and formation of the biradical

monoanion of oxyluciferin in an excited state. The excited state molecule then rapidly

returns to ground status by releasing energy as a photon of light. The intensity of light

released during the reaction is found to be proportional to the level of ATP. In other

words, the greater the level of ATP presented in a sample, the greater the intensity of

light emitted. Luciferase is the enzyme required for both oxidation and decarboxylation

steps (Campbell, 1988; Rhodes and McElroy, 1958). In this project, a novaLUM

luminometer (Charm Science, Inc. Lawrence, MA) was employed for ATP

bioluminescence detection, which is based on photomultiplier tube technology (Van

Dyke et al., 2002).

20

1.4.3.3 Applications in Food /Dairy Industry

The ATP bioluminescence assay has been applied in the food industry for safety

and quality management. For monitoring hygiene, several researchers have used the ATP

bioluminescence assay to detect overall contamination on a variety of food processing

equipment: meat slicers (Seeger and Griffiths, 1994), breweries (Ogden, 1993), fruit juice

operations (Bautista et al., 1992), milking equipment (Vilar et al., 2008), and milk

transport tankers (Bell et al., 1994). The ATP bioluminescence assay was found to be a

rapid method for monitoring hygienic conditions, providing real-time results when

compared to traditional microbiological methods. Generally, there was a 70% agreement

between passed or failed results when assessing system by the ATP assay and traditional

plate count (Griffiths, 1996). However, several authors also suggested that such a high

correlation was not always expected between ATP bioluminescence and microbiological

methods, because ATP bioluminescence measurements indicate contamination of both

food residues and bacterial cells (Ogden, 1993; Bautista et al., 1992; Bell et al., 1994;

Griffiths, 1993).

1.4.3.4 Advantages and limitations

The advantages of the ATP bioluminescence method, to provide rapid and reliable

assessment of cleanliness to assist in ensuring good manufacturing practice (GMP), has

been discussed extensively and is not controversial (Griffiths, 1993; Robinson, 2002).

However, the limitations of the ATP bioluminescence assay should be considered when it

is used for monitoring hygiene. Temperature can affect the accuracy of the test. The

21

optimum temperature for the ATP bioluminescence assay was found to be 25°C

(Robinson, 2002). The pH of the reaction also was found to be an important factor

(Campbell, 1988, Chollet and Ribault, 2012). In addition, cleansers and sanitizers may

cause enhancement or quenching of the bioluminescence signal. Cleansers and sanitizers

that were examined by Velazquez and Feirtag presented enhancement effects at lower

concentration but quenching effects at higher concentration (Velazquez and Feirtag,

1997).

1.4.4 Protein residue detection

Protein residue detection also can be used to assess cleanliness. One common test

is based on an oxidation reduction reaction (Sapan et al., 1999). After swabbing a

surface, the reagents are released onto the swab. In the reagent mix, cupric ions (Cu2+

)

are converted to cuprous ions (Cu+), after forming a complex with peptide bonds under

alkaline condition. Then the cuprous ions (Cu+) react with bicinchoninic acid (BCA),

forming a purple complex. The higher the level of protein present, the darker the purple

color that develops. Similar to the ATP bioluminescence assay, protein residue tests are

able to be used in the plant and provide results rapidly without incubation. However,

commercially available protein residue tests provide only semi-quantitative

measurements of surface cleanliness. When compared to the ATP bioluminescence

assays, protein residue tests are subject to more error, because of the requirement to

visually estimate color. Although there are limitations to this test, protein residue

22

assessment is used for cleanliness evaluation, especially for detection of proteins that

commonly cause food allergies.

1.5 ELECTROLYZED WATER

1.5.1 History

The phenomenon of water electrolysis was firstly observed in 1789 by a Dutch

merchant, named Adriaan Paets van Troostwijk and his friend, a medical doctor, Johan

Rudolph Deiman (de Levie, 1999; Trasatti, 1999). Troostwijk and Deiman immersed

two thin golden wires that were connected to an electrostatic generator into a glass tube

of water, and observed gas evolution on both wires (de Levie, 1999; Trasatti, 1999). The

idea of using electrolyzed water for decontamination was originally developed in Russian

medical institutions to disinfect surgeon’s hands (Nikitin and Vinnik, 1965). Since the

1980s, electrolyzed water has been approved in Japan for use in disinfecting medical and

dental equipment and for treating wounds (Harada et al., 1983; Shimizu and Hurusawa,

1992). More recently, electrolyzed water has been utilized as a disinfectant in

agriculture, livestock management and food processing (Kondo and Mieno, 1989).

1.5.2 Generation and Properties

Electrolyzed water (EW), also known as electro-chemical activation (ECA) water

is produced via electrolysis of a diluted sodium chloride solution (Huang et al., 2008).

To produce EW/ECA, a sodium chloride (NaCl) solution is pumped into an electrolysis

23

chamber, and then dissociated into sodium (Na+) and chlorine ions (Cl

-); hydrogen (H

+)

and hydroxyl (OH-) ions are also formed at this time (Figure 1-1). In the electrolysis

chamber, the anode and cathode are separated by a semi-permeable membrane. Passing a

current through the electrodes causes the negatively charged ions, including Cl- and OH

-

to migrate towards the anode, where chlorine gas (Cl2), hypochlorite ion (OCl-),

hypochlorous acid (HOCl), hydrochloric acid (HCl) and oxygen gas (O2) are formed.

Meanwhile, positively charged ions, such as Na+ and H

+ migrate to the cathode,

producing sodium hydroxide (NaOH) and hydrogen gas (H2). The acidic solution

produced at the anode side is called anolyte, acidic electrolyzed water (AEW), or

electrolyzed oxidizing (EO) water. The alkaline solution produced on the cathode side, is

called catholyte, alkaline electrolyzed water, basic electrolyzed water (BEW), or

electrolyzed reducing (ER) water (Shimizu and Hurusawa, 1992). The acidic solution

has a low pH (2.3-2.7), is high in oxidation-reduction potential (ORP, above 1100 mV),

contains dissolved oxygen gas and has an available chlorine concentration of 10 to 100

ppm, depending on the type and settings of the electrolyzed water generator.

Characteristics of the alkaline solution include a high pH (10.0-11.5), an ORP of -800 to -

900 mV, and the presence of dissolved hydrogen gas and sodium hydroxide.

24

Figure 1-1. Schematic of electrolyzed water generator and produced compounds (Huang

et al., 2008).

1.5.3 Advantages and disadvantages of electrolyzed water:

One of the advantages of using electrolyzed water as a CIP reagent is its safety.

In contrast with conventional cleansers and sanitizers, usually prepared by diluting from

concentrated chemicals, electrolyzed water can be produced on site, avoiding the need to

store, transport and handle concentrated chemicals. Although the acid EO water has a

low pH, it was not found to cause irritation of skin (Al-Haq et al., 2005). In addition,

using electrolyzed water for CIP procedures also has the potential to reduce the cost of

CIP cleaning (Wang et al., 2012; Al-Haq et al., 2005). Wang et al. (2012) did an on-farm

study and compared the costs of CIP for a milking system using electrolyzed water and

conventional chemicals, and concluded the operational expense of CIP cleaning using

electrolyzed water was 25% less than conventional method.

Anode:

2H2O → 4H+

+ O2 ↑+ 4e-

2NaCl→ Cl2 ↑+ 2 Na+

+ 2e-

Cl2 + H2O → HCl + HOCl

Cathode:

2H2O + 2e- → 2OH

－+ H2↑

2NaCl + 2OH－

→ 2NaOH + Cl-

25

The main disadvantage reported for electrolyzed water is the short shelf life. The

antimicrobial activity of acidic electrolyzed water is rapidly lost due to decomposition of

hypochlorous acid (HOCl) and volatilization of chlorine gas (Cl2). Len et al. (2000)

reported the stability of electrolyzed water could be affected by light, storage

temperature, agitation, packaging conditions (open or closed system), and pH. There was

equilibration of Cl2, HOCl and OCl- dependent on pH. HOCl is the primary bactericide

form of chlorine. When pH was 4.0~5.0, HOCl was at a higher concentration in solution.

HOCl decomposed to H+ and OCl

- when the pH increased, and released Cl2 gas when the

pH decreased (Len et al., 2000). Fabrizio and Cutter (2003) investigated the stability of

electrolyzed water and found the ORP of alkaline ER water was not consistent and

increased after 1-day of storage in sterile Pyrex bottles at both 4°C and 25°C. Thus, the

electrolyzed water used for all experiments in this research, was generated freshly and

stored in polypropylene carboys that closed with lids, at room temperature for no more

than 3 hours.

In addition, acid EO water has been shown to be corrosive to some materials used

in food processing equipment. Work conducted by Ayebah and Hung (2005)

demonstrated stainless steel presented “outstanding corrosion resistance” when immersed

in acid EO water (pH of 2.42, ORP of 1077 mV, and 48.66 ppm of chlorine) at room

temperature (22°C), whereas other materials such as carbon steel, copper, and aluminum

were less resistant to acid EO water. Compared with acid EO water, chlorine water (pH

of 8.72, ORP of 656 mV, and 49.16 ppm of chlorine) and modified EO water by

increasing its pH (pH of 6.12, ORP of 774 mV, and 50.39 ppm of chlorine) were less

26

corrosive. The results indicated that the corrosiveness of acid EO water was due to its

low pH and high ORP.

1.5.4 Application of electrolyzed water in food industry

1.5.4.1 Pure bacterial cultures

The effectiveness of acid EO water has been evaluated in many studies, and

revealed that acid EO water could inactivate various microorganisms, including

Escherichia coli O157:H7 (Fabrizio & Cutter, 2003; Issa-Zacharia, et al. 2010; Kim, et

al. 2000a; Rahman, et al. 2010; Stevenson, et al. 2004; Venkitanarayanan, et al. 1999a),

Listeria monoctogenes (Fabrizio and Cutter, 2003; Kim et al., 2001, 2000b; Rahman et

al., 2010; Venkitanarayanan et al., 1999b), Salmonella Typhimurium (Rahman et al.,

2010; Fabrizio and Cutter, 2003), Salmonella Enteritidis (Venkitanarayanan et al.,

1999b), Staphylococcus aureus (Issa-Zacharia et al., 2010; Rahman et al., 2010), Bacillus

sp. spores (Kim et al., 2000b; Kiura et al., 2002), Clostridium perfringens spores, and

Cryptosporidium parvum oocysts (Venczel et al., 1997).

Venkitanarayanan et al. (1999a) inoculated E. coli O157:H7, S. Enteritidis, and L.

monocytogenes into EO water (~ 80 ppm of free chlorine) at initial populations of 8 log10

CFU/ml. A 5-min treatment at 4°C or 23°C resulted in a reduction of 7 log10 CFU/ml,

and a 10-min treatment at both temperature reduced the population of all three strains to

undetectable levels (Venkitanarayanan et al., 1999a). Kim et al. (2001) investigated the

efficacy of acid EO water in inactivating biofilm forming bacteria on equipment surfaces.

27

A 300-second treatment using acid EO water (pH of 2.6, ORP of 1160 mV and 56 ppm

free chlorine) on stainless steel significantly reduced the number of biofilm-forming

bacteria from 10 log10 CFU/82.5 cm2 to below detectable levels (Kim et al., 2001). When

compared to chlorinated water containing the same concentration of chlorine, acid EO

water was found to be more effective in inactivating bacterial spores or spore formers,

such as Clostridium perfringens spores, Cryptosporidium parvum oocysts (Venczel et al.,

1997), and Bacillus cereus (Kim et al., 2000b).

Neutral EO water has been studied because it is less corrosive than acid EO water.

The disinfectant efficacy of neutral EO water has been examined (Rahman et al., 2010;

Issa-Zacharia et al., 2010). The work conducted by Issa-Zacharia et al. (2010) indicated

neutral EO water (pH of 5.8, ORP of 948 mV, and 21 ppm of free chlorine) was less

efficient as a sanitizer than acid EO water (pH of 2.6, ORP of 1140 mV, and 45 ppm of

free chlorine), but was capable of causing a 5 log10 CFU/ml reduction in pure culture of

Staphylococcus aureus and Escherichia coli after 90s of exposure. The reduced

efficiency of neutral EO water in this study was caused by not only neutral pH but also

lower concentration of free chlorine. In another study, Rahman et al. (2010) reported that

in spite of being lower in chlorine concentration, at least 95% of chlorine in neutral EO

water was in the form of hypochlorous acid, which is effective as a sanitizer.

1.5.4.2 Shell eggs

The application of electrolyzed water in reducing pathogens on egg shells has

been investigated. EO water was found to have the potential to reduce the population of

28

pathogens, including Salmonella spp., E. coli O157 and K12, L. monocytogenes, S.

aureus and Campylobacter jejuni. The efficacy was found to be dependent on the

method of application (Bialka et al., 2004; Park et al., 2005; Russell, 2003). In a study

conducted by Park et al. (2005), inoculated shell eggs were submerged into alkaline ER

water (pH of 11.2, ORP of -940 mV) for 1 min followed by immersion into acid EO (pH

of 2.5, ORP of 1117 mV, 41 ppm total chlorine) water for 1 min. This sequential

treatment achieved 4.39 log10 CFU/egg reductions of L. monocytogenes and 3.66 log10

CFU/egg reductions of S. Enteritidis, which was equivalent to a chlorinated water (200

ppm) wash. The effect of this sequential alkaline-acidic electrolyzed water treatment on

egg quality was also examined by Bialka et al. (2004). Results indicated that acid EO

water treatment did not significantly change albumen height or eggshell strength, but

could affect the cuticle presence and turn eggshells “spotty”. It was found that using an

electrostatic spraying system to apply acid EO water (pH of 2.1, ORP of 1150 mV and

free chlorine of 8 ppm) on inoculated egg shells improved the antimicrobial efficacy. In

this way, pathogenic bacteria, such as S. Typhimurium, S. aureus, L. moncytogenes, and

E.coli were completely eliminated (Russell, 2003).

1.5.4.3 Poultry

Different methods (spraying, immersing, or a combination of both methods) using

acid EO water for reducing pathogenic bacteria on chicken carcasses have been

investigated (Kim et al., 2005; Park et al., 2002; Fabrizio et al., 2002). Park and Huang

(2002) soaked inoculated chicken wings in EO water (pH of 2.57, ORP of 1082 mV, and

29

51.6 ppm free chlorine) with agitation (100 rpm) for 10 min or 30 min at 4°C or 23°C,

and the population of C. jejuni was reduced by ca. 3 log10 CFU/ml by the four treatments.

Fabrizio et al. (2002) reported that acid EO water (pH of 2.6, ORP of 1150 mV, and 39.6

ppm free chlorine) was more effective in reducing bacterial load than chlorine water

(30.9 ppm free chlorine) using an immersion method. These researches revealed that

treatment by immersion of inoculated chicken carcasses into acid EO water was effective

in reducing the population of pathogenic bacteria and preventing recovery of viable cells.

However, treatment with acid EO water by spraying were not effective. Spraying acid

EO water failed to provide a significant reduction in bacterial load, likely due to

insufficient contact time (Kim et al., 2005; Park et al., 2002; Fabrizio et al., 2002). The

work conducted by Kim et al. (2005) indicated that pre-spraying with alkaline ER water

was more effective in removing fecal contamination from chicken carcasses as compared

to 10% trisodium phosphate (TSP), which is used during defeathering to remove a thin

layer of lipids and protect against bacterial growth.

1.5.4.4 Meat

Fabrizio and Cutter (2004 & 2005) examined the effectiveness of using acid EO

water (pH of 2.4, ORP of 1160 mV and 50 ppm free chlorine) as an intervention to

enhance safety of meat products. By spraying acid EO water on fresh pork bellies for

15s, the populations of S. Typhimurium, C. coli, E. coli, and total coliforms were reduced

by 1.67 log10 CFU/cm2, 1.81 log10 CFU/cm

2, 1.13 log10 CFU/cm

2, and about 1 log10

CFU/cm2, respectively. The level of L. monocytogenes was not significantly reduced by

30

the EO water spray treatment. Although the treatment reduced some levels of undesired

bacteria, the authors suggested increased contact time was necessary to improve the

disinfection effectiveness (Fabrizio and Cutter, 2004). In terms of ready-to-eat (RTE)

meat products, frankfurters and ham inoculated with L. monocytogenes (5 log CFU/ml)

were dipped or sprayed with acid EO water (pH of 2.3, ORP of 1154 mV, and 45 ppm

free chlorine) or alkaline ER water (pH of 11.2, ORP of -795 mV) followed by acid EO

water. None of the treatments was able to reduce the bacterial load greater than 1 log10

CFU/g. Although the EO water treatments did not result in bleaching of RTE meat, the

disinfectant strength was not sufficient to meet regulatory requirements (Fabrizio and

Cutter, 2005).

1.5.4.5 Seafood

Acid EO water use in seafood processing has been reported, and the disinfectant

efficacy was not sufficient. Huang et al. (2006a) soaked pathogen-inoculated tilapia in

acid EO water (pH of 2.47, ORP of 1159 mV, and free chlorine of 120 ppm) for 10 min,

and populations of Vibrio parahaemolyticus and E. coli were reduced by 2.6 log10

CFU/cm2 and 0.76 log10 CFU/cm

2, respectively. There were no bacterial cells detected in

acid EO water after soaking, indicating using acid EO water could prevent cross-

contamination during tilapia processing. Ozer and Demirci (2006) investigated EO water

treatment under different conditions (temperature and time), and found that treatment by

soaking inoculated salmon fillet in acid EO water (pH of 2.6, ORP of 1150 mV and 76-90

ppm of free chlorine) at 35 for 64 min reduced populations of L. monocytogenes (1.12

31

log10 CFU/g) and E. coli (1.07 log10 CFU/g). Treatment of salmon fillet with alkaline ER

water prior to this acid EO water treatment did not improve the decontamination rate.

Experiments conducted by Huang et al. (2006b) demonstrated a treatment combining CO

gas with acid EO water containing more than 50 ppm chlorine could extend the shelf life

of tuna fillet from 6 days to 8 days during refrigerated storage.

Using acid EO water as disinfectant in seafood processing facilities has been

reported. To investigate the disinfectant effect of acid EO water on seafood processing

surfaces, Liu and Su (2006) reported that treatment with acid EO water containing 50

ppm of free chlorine for 5 min significantly reduced the load of L. monocytogenes on

various seafood processing surfaces, including a stainless steel sheet (reduction of 3.73

log10 CFU/25cm2, 2.33 log10 CFU/25cm

2 with food residue), ceramic tile (reduction of

4.24 log10 CFU/25cm2, 2.33 log10 CFU/25cm

2with food residue), and floor tile (reduction

of 5.12 log10 CFU/25cm2, 1.52 log10 CFU/25cm

2with food residue). Treatment by

immersion in acid EO water containing 40 ppm free chlorine reduced L. monocytogenes

on seafood processing gloves as well, providing 1.60 to 2.41 log10 CFU/cm2 reduction on

reusable gloves, and 2.54 to 3.87 log10 CFU/cm2 reductions on disposable.

1.5.4.6 Milking system

The feasibility of using electrolyzed water as cleaning and sanitizing agent for

CIP of milking system has been investigated. Walker et al. (2005a) conducted trials

using response surface design to evaluate the cleaning efficacy of electrolyzed water in

cleaning for coupons of five materials commonly used in milking systems: stainless steel

32

sanitary pipe, PVC milk hose, rubber liners, rubber gasket, and polysulfone plastic. The

cleanliness of material coupons was evaluated using ATP bioluminescence assays and

aerobic plate counts. Operational parameters, namely time and temperature combinations

of alkaline ER water and acid EO water, were determined based on liner regression

analyses. The results indicated the potential of electrolyzed water as a cleaning and

sanitizing agent for CIP cleaning of milking system. Furthermore, the effectiveness of

using electrolyzed water for CIP cleaning of a pilot scale milking system after soiling

with inoculated raw milk was also investigated (Walker et al., 2005b). The cleaning

efficacy of electrolyzed water treatments was evaluated using ATP bioluminescence

assays and a microbial enrichment method. Treatment with electrolyzed water for 7.5

min for both the alkaline wash and acid sanitize steps at a starting solution temperature of

60°C showed equivalent cleaning efficacy, when compared with a conventional cleaning

treatment.

However, both work done by Walker et. al. used the same temperature for both

steps of the CIP process, i.e. the alkaline wash with ER water and acid sanitizing with

acid EO water, which is not typical of CIP operations in the dairy industry. Alkaline

wash steps are usually conducted at higher temperature (50~72°C) for better efficacy of

cleaning; while the acid sanitizing step using chlorine sanitizer is usually conducted at

temperatures less than 40°C to avoid chlorine volatilization (Mauck et al., 2001; Tamime

and Robinson, 1999).

The operating temperatures for CIP cleaning with electrolyzed water for a pilot

scale milking system were further optimized by Dev et al. (2014), using response surface

modeling. In this work, cleanliness was assessed using the ATP bioluminescence

33

method. A set of operational temperatures was optimized: 58.8°C and 37.9°C for

alkaline ER water and acid EO water treatments respectively. This optimal CIP

procedure using electrolyzed water for cleaning of the pilot scale milking system was

able result in a clean surface with 100% RLU reduction

Another on-farm study conducted by Wang and Demirci compared cleaning

performance of conventional CIP solutions and electrolyzed water (Wang, et al., 2012).

In this on-farm study, after cleaning the milking system using electrolyzed water, 9 areas

of pipeline inner surface near tri-clamps along with gaskets were sampled for cleanliness

evaluation, using ATP bioluminescence assays and microbial enrichment method. The

authors suggested that electrolyzed water achieved the same or better cleaning efficacy in

CIP cleaning of cold milking system, when compared to conventional CIP solutions.

Although a few studies have been done using electrolyzed water as cleaning and

sanitizing solutions for CIP of system soiled with cold milk, the cleaning efficacy of

electrolyzed water for CIP of dairy processing system in dairy plant, especially when the

soil has been heated has not been investigated. Heat treatment during manufacturing

increases the difficult of cleaning, due to protein denaturation and mineral deposition

(milk stone formation).

In this study, the potential of using alkaline ER water and acid EO water as CIP

reagents for cleaning, by CIP, of surfaces soiled with cold milk or surfaces soiled during

heating of milk was evaluated. Comparison of the results of this work with conventional

CIP procedures using commercial cleanser and sanitizer will provide valuable in future

about the potential application of electrolyzed water for CIP procedures in dairy plant.

34

Chapter 2

HYPOTHESIS AND OBJECTIVES

Hypothesis:

Electrolyzed water can be used as an effective cleanser and sanitizer for CIP cleaning of

milk processing equipment.

To address this hypothesis, research was undertaken with the following objectives:

1. Construction of a pilot scale test system to allow evaluation and optimization of

electrolyzed water as CIP agent for dairy processing equipment (Chapter 3).

2. Determination of the efficacy of electrolyzed water as a CIP solution for cleaning a

refrigerated milk storage tank using a pilot scale test system (Chapter 4).

3. Optimization, using response surface model, of a CIP procedure with electrolyzed

water, for cleaning a processing equipment used to heat milk (Chapter 5).

35

Chapter 3

CONSTRUCTION, CHARACTERIZATION AND VALIDATION

OF TEST SYSTEM

ABSTRACT

Clean-in-place (CIP) is commonly used in the dairy industry for cleaning and

sanitation of dairy processing equipment. Optimization of CIP procedures has gained

importance, because of a desire to reducing operational costs and environmental impact.

Electrolyzed water is a set of alkaline and acidic solutions, which have been considered

as potential alternatives for CIP detergent and sanitizer. The goal of this research was to

develop a pilot scale test system to mimic soiling of tanks used to store refrigerated milk

and to thermally process milk, to evaluate efficacy of CIP procedures, and to further

optimize CIP procedures using electrolyzed water. The primary tank in the pilot scale

test system was a 15 liter (4 gallon) stainless steel vessel, equipped with a 360° static

spray ball delivering of CIP liquid. The test system was characterized, in terms of flow

rate, and the minimal flow rate providing full tank coverage was determined. Preliminary

trials using a standard CIP procedure and conventional detergent and sanitizer were

conducted, for cleaning the test vessel after being used to heat milk. The efficacy of the

standard CIP procedure was assessed with ATP bioluminescence assays and protein

residue detection assays. Results showed demonstrated the test vessel was completely

cleaned by conventional CIP procedure, which validated the suitability of the system for

evaluation and optimization of CIP procedures with other cleaning compounds.

36

3.1 INTRODUCTION

Dairy processing equipment is complex and requires frequent cleaning and

sanitizing. Cleaning and sanitizing play an essential role in the dairy industry in ensuring

quality products by preventing microbial contamination and by avoiding reduced

processing equipment performance due to fouling. Most dairy processing equipment is

cleaned using a highly automated technique, namely clean-in-place (CIP), which is a

method of cleaning the internal surface of pipe lines or processing equipment by jetting,

spraying or circulating cleaning solutions without opening or disassembly of the

equipment (Romney, 1990). CIP cleaning includes four steps: rinsing with water to

remove bulk dairy food residue; washing with alkaline detergents to remove proteins and

fat more firmly attached to equipment surfaces; rinsing with water again to remove

residue cleanser and dissolved soil; and finally rinsing with sanitizer to reduce bacterial

contamination (Lloyd, 2008).

Electrolyzed water is a set of alkaline and acid solutions, produced via electrolysis

of a dilute (0.1%) sodium chloride solution. This process results in an alkaline

electrolyzed reducing (ER) water containing sodium hydroxide (pH ca. 11.0 and ORP ca.

-850 mV) and acid electrolyzed oxidizing (EO) water containing 10-100 ppm chlorine

(pH ca. 2.5, ORP ca. 1168 mV) (Huang et al., 2008; Al-Haq et al., 2005). In contrast to

conventional CIP chemicals, which are usual stored and handled in concentrated forms,

electrolyzed water can be produced onsite, and offers an attractive alternative to

conventional cleaning and sanitizing solutions. As described in Chapter 1, using

electrolyzed water for CIP cleaning provides the possibility of reducing manufacturing

37

costs by reducing the cost of handling and storing concentrated cleaning and sanitizing

chemicals.

CIP procedures are well established and widely used not only in the dairy industry

but also in the beverage and pharmaceutical industries. Optimization of CIP procedures

and improving efficiency of cleaning have become more important in recent years (Fryer

et al., 2011). Cleaning and sanitizing generates large amounts of water containing

cleaning chemicals, which presents an environmental impact issue (Vourch et al., 2008).

In addition, costs of manufacturing could be reduced by reducing cleaning costs related to

energy, labor and purchase of cleaning chemicals. However, cleaning protocols are

commonly overdesigned and semi-empirical, because: (1) manufacturers need to ensure

the safety and quality of food rather than take a risk to narrow the margin of cleanliness

criteria; (2) assessments of cleanliness are normally conducted at the end of cleaning, and

online measurements during cleaning processing are usually missing; (3) it is difficult to

compare cleaning efficiency of removal of different types of soils (Fryer and Asteriadou,

2009; Fryer et al., 2011).

In this work, a pilot scale test system was constructed: (i) to mimic soiling in

different types of tanks used in dairy processing plants, (ii) to allow the assessment of

cleanliness at any time during CIP cleaning, and (iii) to evaluate cleaning efficiency and

to optimize CIP procedures using electrolyzed water.

38

3.2 MATERIALS AND METHODS

3.2.1 Construction of test system

A pilot-scale dairy processing system was designed and constructed for testing the

efficacy of cleaning and sanitizing (Figure 3-1).

Figure 3-1. Schematic of pilot scale dairy processing test system.

Test vessel. A 15-liter (4-gallon) stainless steel vessel equipped with a

heating/cooling jacket, which allowed temperature control during soiling, served as the

base for the test system (Figure 3-2A). For mimicking a refrigerated milk silo, chilled

water (4°C) was circulated within the jacket to maintain the refrigerated temperatures

during soiling. For mimicking thermal processing, hot water (75°C to 80 °C) was

circulated through the jacket during soiling. The bottom of the test vessel has a cone

shape to allow complete drainage. To measure temperature of test vessel during soiling

39

and cleaning, a temperature probe was installed at the bottom of the 15-liter (4-gallon)

test vessel. The temperature probe was also connected to an AJ-310 microprocessor-

based circular chart recorder (Anderson Instrument Co., Fultonville, NY) for temperature

monitoring and recording. A customized stainless steel lid equipped with a gasket to seal

the tank was held in place by four clamp fasteners during soiling and cleaning. To allow

agitation during soiling, a 1.5-inch fitting welded on to the lid served as the entrance for

the shaft of the agitator. The fitting was covered when the agitator was not in use. Thus,

the test vessel could be sealed to maintain temperature, to prevent against evaporation

during heated soiling, and to avoid leakage during cleaning.

Water tank and CIP tank. A stainless steel milk can welded with a 0.5-inch fitting

served as water reservoir for storing water for the pre-rinse and post-rinse steps during

CIP processes (Figure 3-2B). Similarly, an 11.4 L (12-quart) stainless steel pot welded

with a 0.5-inch fitting served as the reservoir for CIP solutions during washing and

sanitizing operations (Figure 3-2C). In order to maintain temperatures of CIP solutions

during cleaning, a coil heat exchanger with external diameter of 0.64 cm (¼ inch)

(constructed by Swagelok Co., Pittsburgh, PA) connected to a circulating water bath

(Thermo Fisher Scientific Inc., Pittsburgh, PA) was immersed into CIP solution reservoir.

During CIP cleaning, the water bath was pre-set at a temperature of about 10% higher

than the specified operating temperature to compensate for heat loss due to CIP fluid

circulation.

40

Figure 3-2. Test system. (A) Test vessel (center of the system) with agitator in place. (B)

A modified stainless steel milk can served as reservoir for water used for CIP cleaning.

(C) CIP solution reservoir with coil heat exchanger connected to a circulating water bath.

(D) 360° static spray ball.

Liquid delivery system. A 360° static spray ball (Model 149588, Sani-Matic Inc.,

Madison, WI) was installed at the top of the 15-liter (4-gallon) test vessel, attached in the

center of the lid, was used to deliver CIP liquids (Figure 3-2D). Liquid used for CIP

cleaning was delivered to the 15-liter (4-gallon) test vessel by a variable frequency drive

B A

C

D A

41

(VFD) pump (Fluid-o-Tech, Plantsville, CT), which allowed control of flow rate during

cleaning. The test vessel, CIP tanks and VFD pump (Model AT13-18-56CB, World

Wide Electric Corp., Pittsford, NY) were connected via 3-way or 2-way valves, and

sanitary stainless steel pipes with diameter of ½" (1.27 cm), which provided different

flow paths and allowed circulation or rinse-to-drain.

3.2.2 Characterization of the test system

3.2.2.1 Volumetric flow rate measurement

To characterize the performance of the VFD pump, the flow rate was evaluated at

each pump speed setting. Water was pumped from the rinse tank, and collected for 1 min

at each pump speed setting. The volume of collected water was measured using a

graduated cylinder. The flow rate (L/min) of each pump speed setting was measured in

triplicate.

3.2.2.2 Evaluation of spray ball coverage

Coverage tests were conducted using a riboflavin solution to assure the system

was capable of delivering water or CIP solutions to the entire internal surface of the

vessel. Riboflavin emits fluorescence under UV light at a wavelength of 365 nm

(Bowser, 2005). For the coverage tests, a riboflavin in water solution (200 ppm, Sigma-

Aldrich Co. LLC, Saint Louis, MO) was sprayed on the internal surface of the test vessel

using a spray bottle. The test vessel was then rinsed with room temperature (ca. 22°C)

42

tap water using the 360° static spray ball at different flow rates (established using the

VFD pump). Tests were conducted at flow rates of 1.8, 3.9, 6.0, 8.3, and 10.0 L/min.

The residual riboflavin remaining on the surface of the test vessel was evaluated visually

using a UV light (model 8CC-MIG-BLB, K&H Industries, Inc., Hamburg, NY). The

first inspection of residual riboflavin was conducted after rinse for 1 min at each pre-set

flow rate. After the first inspection, the residual riboflavin was inspected visually under

the UV light after every 2- min of rinsing.

3.2.3 Performance validation of the test system used for CIP

To validate the suitability of the test system for evaluation and optimization of

CIP procedures, a standard CIP procedure using commercial cleanser and sanitizer was

performed (Figure 3-3).

3.2.3.1 Pre-cleaning

Before each experiment, the test system was cleaned manually and thoroughly,

according to “Sanitation Standard Operating Procedure” used by Penn State Berkey

Creamery (Votano et al., 2007), using a commercial detergent and sanitizer to return the

vessel to a presumably clean condition. To perform pre-cleaning, the internal surface of

the test vessel was sprayed with tap water at ambient temperature (ca. 22°C), followed by

brushing with warm (45~50°C) chlorinated alkaline detergent, HC-10®

solution (ca. 16

g/l, Ecolab USA Inc., St. Paul, MN). This step was followed by another rinse with tap

43

water at room temperature (ca. 22°C) to remove the residue of alkaline solution and cool

down the test vessel. Finally, the test vessel was brushed with a chlorinated sanitizer,

XY-12® solution (ca. 100 ppm of available chlorine, Ecolab USA Inc.) at room

temperature (ca. 22°C).

Figure 3-3. Flow chart of CIP performance evaluation of test system. CIP cleaning was

conducted at flow rate of 8.3 L/min.

3.2.3.2 Soiling

After returning the test vessel to a presumably clean condition, 11.4 liters (3

gallons) of HTST pasteurized whole milk, purchased from Penn State Berkey Creamery,

was poured into the vessel. Hot water at ca. 77°C was circulated through the jacket for

soiling the test vessel under heated conditions. Milk was heated from 4°C to 74°C, which

44

took ca. 15 min, and then the temperature of the milk was kept at 74 ± 1°C for another 15

min. Thus, the total soiling time was about 30 min. An agitator (Stir-Pak, Laboratory

Stirrer, Model 4554, Cole-Parmer Co., Vernon Hills, IL) with a 316 stainless steel 3-

blade propeller (8.9 cm diameter, Cole-Parmer Co.) and a 316 stainless steel shaft (1.0

cm diameter × ca. 60 cm length, Cole-Parmer Co.) was employed to ensure the tank was

heated and soiled evenly.

3.2.3.3 Four-step conventional CIP

A CIP procedure was conducted at a flow rate of 8.3 L/min, as determined by the

coverage tests. Before CIP cleaning, milk was drained from the test vessel. Next, the test

vessel was sprayed with tap water via the spray ball for 3 min at ambient temperature (ca.

22°C) using the rinse-to-drain flow path as a pre-rinse step. After pre-rinsing a

commercial chlorinated alkaline detergent, namely Principal® (3200-4000 ppm, Ecolab

USA Inc.), was circulated within the system for 15 min at 63°C. Following the alkaline

wash, the system was post-rinsed with tap water for 3 min at ambient temperature (ca.

22°C) using the rinse-to-drain flow path as well. Finally, the test vessel was sanitized

with the commercial sanitizer, XY-12® (ca. 100 ppm of available chlorine, Ecolab USA

Inc.), by circulating through the system for 3 min at room temperature (ca. 22°C). Tap

water for both pre-rinse and post-rinse steps was not reused. Therefore, for each rinse

step, ca. 24.9 L water was needed. In contrast, about 11 L detergent or sanitizer was used

for each circulating step.

45

3.2.3.4 Assessment of cleanliness

Cleanliness of the inner surface of the test vessel was assessed at several points

during the procedure: after pre-cleaning as a background check; after soiling to determine

the initial condition of the vessel; after pre-rinse; after post-rinse to evaluate the effect of

the alkaline wash; and after sanitizing to evaluate the effect of acidic sanitizing. Direct

surface sampling using two swabbing methods was applied for cleanliness assessments:

an ATP bioluminescence assay and a protein residue detection assay.

3.2.3.4.1 Detection of residual ATP

For each ATP bioluminescence analysis, 5 cm × 10 cm of the tank surface was

swabbed using PocketSwab Plus swabs (Charm Science, Inc. Lawrence, MA) for ca. 15

sec, vertically and horizontally, in an overlapping pattern according to manufacturer’s

instructions. After the sample was collected, the swab was twisted down to break the

metal foil seal, releasing the buffering agent and to dissolve the luciferin/luciferase tablet.

The buffering agent also contains compounds that help releasing ATP from cells. Once

the ATP was exposed to the luciferein and luciferease complex, light was produced

(Griffiths, 1996). The intensity of light given off was detected using a novaLUM palm-

sized luminometer (Charm Science, Inc.), which provides a measure of relative light units

(RLU). According to the manufacturer, the amount of ATP is proportional to RLU. An

RLU of zero (0) indicates an acceptably clean stainless steel surface (Griffiths, 1993).

3.2.3.4.2 Detection of residual protein

Protein is a major component of milk soil. To detect residual protein, an area of 5

cm × 10 cm of the inner surface was swabbed for ca. 15 sec using a Pro-Clean Rapid

46

Protein Residue Test Swabs (Hygiena llc., Camarillo, CA), vertically and horizontally in

an overlapping pattern. After swabbing, the reagent contained in the snap vial was

released to react with protein on the swab, which causes a color change from green to a

purplish-violet color (Sapan et al., 1999). Color was evaluated 10 min after releasing the

reagent. Cleanliness assessment using this protein detection method provides only

categorical data. A green color after reaction indicates an acceptable cleanliness with

protein residue of less than 20 µg. Colors of gray, light purple and dark purple indicate

protein residue levels of 20~40 µg, 40~100 µg and > 100 µg.

3.2.4 Test for swab sampling variability

For the swab-sampling methods, each 5 cm × 10 cm inner surface could be

swabbed only once during any given trial. Thus, cleanliness evaluations after different

steps had to be assessed at different locations. Consequently, the locations for swab-

sampling might be a “nuisance factor” leading to variability in evaluations of cleanliness,

specifically for the ATP bioluminescence assay. To avoid this situation, swab-sampling

were assessed at the same height of the inner surface area of the test vessel. In addition, a

separate experiment was conducted to assess the variability of cleanliness at various

positions in the test vessel.

To conduct this experiment, the test vessel was pre-cleaned and soiled with milk

at high temperature (ca. 74°C) for 15 min using the same procedures as described above.

After draining the milk out of the test vessel, in order to enhance the difficulty of

cleaning, the system was allowed to dry for 15 min before sampling for ATP

47

bioluminescence analyses, and the RLU data was marked as “after soiling”. Three

randomly picked areas of 50 cm2

(5 cm × 10 cm) at different positions were swabbed for

each cleanliness assessment. Sampling and assessment of cleanliness took ca. 15 min.

Thus, after 30 min following draining, the test vessel was rinsed with tap water at flow

rate of 8.3 L/min for 3 min at room temperature (ca. 22°C). Then, another cleanliness

assessment was performed again using the ATP bioluminescence method, and marked as

“after pre-rinsing”. Lastly, instead of using a commercial sanitizer, sanitizing with acid

electrolyzed oxidizing (EO) water was applied for 2 min at room temperature.

Cleanliness of three areas was determined using the same procedure for ATP

bioluminescence analyses and marked as “after sanitizing” (Figure 3-4). This experiment

was replicated in three times.

3.2.5 Statistical analysis

The ATP bioluminescence data (RLU values) were converted to base 10

logarithms. Since log10 (0) is undefined, the RLU values of zero were assigned a value of

0.5 for logarithmic calculation. Statistical analyses were performed using Minitab

software version 16 (Minitab Inc., State College, PA). Analysis of variance (ANOVA)

test using Tukey’s comparison was performed for comparing the means of log10 RLU

after different CIP steps. Means were consider significantly different at a level of 0.05 (α

= 0.05).

48

Figure 3-4. Schematic of test for swab sampling variability. Each rectangle area

represents 50 cm2 (5 cm × 10 cm) inner surface of test vessel. Different colors represent

the sampling for ATP bioluminescence assays after different steps. Red marked areas

were swabbed “after soiling”, green areas were swabbed “after pre-rinse”, and blue areas

were swabed “after sanitizing”. For one trial, each assessments of ATP bioluminescence

assays was conducted in three replicates.

49

3.3 RESULTS AND DISCUSSION

3.3.1 Characterization of test system

3.3.1.1 Volumetric flow rate measurement

The volumetric flow rates at 9 pump speed settings were measured. Figure 3-5

shows volumetric flow rate as a function of pump speed setting. Standard deviation was

obtained from three replicates. The volumetric flow rate increased as the speed of VFD

pump was increased. The regression equation indicates that an increase of 10 unit of

VFD pump speed setting lead to an increase of 1.9 (L/min) in flow rate (R2 = 99.8%).

0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0

0

5

1 0

1 5

2 0

V F D p u m p se t tin g

me

an

flo

w r

ate

(L

/min

)

Figure 3-5. Mean volumetric flow rates (L/min) at different VFD pump settings. The

regression equation is: Flow Rate (L/min) = 0.1844 + 0.1918 Pump Setting.

50

3.3.1.2 Coverage test

Spraying riboflavin solution on the inner surface of the test vessel resulted in

uniform fluorescence under UV light. After rinsing with water at each pump speed

setting, the pattern of residual riboflavin revealed the coverage of the 360° static spray

ball (Figure 3-6). At a pump speed setting of 10 (1.8 L/min), ca. half of the inner wall of

the test vessel was rinsed. The spray ball failed to provide full coverage of the test-tank

at pump speed settings of 10 (1.8 L/min), 20 (3.9 L/min), or 30 (6.0 L/min). In fact, even

after rinsing the test vessel with water for 17 min at a setting of 30 (6.0 L/min), there was

still some riboflavin remaining on the upper wall of the test vessel. However, at pump

speed settings of 40 (8.3 L/min) and 50 (10.0 L/min), water was able to contact and wet

an internal surfaces thoroughly after a 3 min rinsing. The coverage test along with

volumetric flow rate measurements revealed the lowest flow rate providing full coverage

was 8.3 L/min (pump speed setting of 40). Hence, a flow rate of 8.3 L/min was chosen

for CIP procedures for the entire project.

51

Figure 3-6. Riboflavin coverage test. (A) Riboflavin solution sprayed on test vessel

before rinse. (B) Residual riboflavin remaining after rinsing test vessel with water at

flow rate of 1.8 L/min (pump setting of 10) for 1 min. (C) Residual riboflavin remaining

after rinsing test vessel with water at flow rate of 3.9 L/min (pump setting of 20) for 7

min. (D) Residual riboflavin remaining after rinsing test vessel with water at flow rate of

6.0 L/min (pump setting of 30) for 17 min. (E) Residual riboflavin remaining after

rinsing test vessel with water at flow rate of 8.3 L/min (pump setting of 40) for 1 min.

The European Hygienic Engineering & Design Group (EHEDG) recommends the

flow rates for tank cleaning using static spray ball should be 30-50 liters per minute per

meter of tank circumference (Fliessbach, 2013). The circumference of the test vessel

used in this study was 0.718 meter, with diameter of 0.229 meter (9 inch). To meet the

EHEDG recommendation, the flow rates should achieve 21.5-35.9 liter per minute,

A B

C D E

52

beyond the capacity of the VFD pump. Thus, according to EHEDG, the flow rate was

insufficient. However, it has been reported that this situation is not uncommon when

cleaning tanks using a static spray ball (Packman et al., 2008). Since complete coverage

of the tank surface was demonstrated, the system was considered suitable for this study.

3.3.2 Performance validation of the test system used for CIP

The purpose of evaluating the effectiveness of conventional CIP procedure using

commercial chemicals of the test vessel after soiling with whole milk after heating was to

validate the test system was suitable for evaluation and optimization of CIP procedures

using electrolyzed water.

Results of ATP bioluminescence assays, the RLU values and log10 RLU are

presented in Table 3-1. The ATP levels, which are proportioned to RLU values, are

significantly higher “after soiling” and “after pre-rinse” than the residual ATP levels of

“after post-rinse” and “after sanitizing” (p-value = 0.000). The ATP levels detected

“after soiling” were not statistically different from those detected “after pre-rinsing” (p-

value = 0.461). The slightly increase of ATP level observed is likely due to loosening of

the soil by water rinsing. These results demonstrated the test vessel was returned to a

satisfactorily clean condition after alkaline wash with commercial chemicals and post-

rinse with water, indicating the standard procedure using conventional CIP chemicals

succeeded in cleaning for the test vessel after soiling with hot milk.

53

Table 3-1. Cleanliness assessments made using ATP and protein measurements after

different steps of standard CIP procedure using commercial chemicals (*RLU values of

zero were assigned as 0.5 for base-10 logarithm calculation).

Step Replicate RLU*1

Log10

RLU Protein (μg) 2

Cleanliness

assessment

After soiling

1 328,785 5.52 > 100 Fail

2 239,806 5.38 40-100 Fail

3 450,775 5.65 > 100 Fail

After pre-rinse

1 455,831 5.66 > 100 Fail

2 596,649 5.78 > 100 Fail

3 667,585 5.82 > 100 Fail

After post-rinse

1 0 -0.30 < 20 Pass

2 0 -0.30 < 20 Pass

3 0 -0.30 < 20 Pass

After sanitizing

1 0 -0.30 < 20 Pass

2 0 -0.30 < 20 Pass

3 0 -0.30 < 20 Pass

1 RLU = relative light units. An RLU of 0 is considered clean.

2 A residue protein level of < 20 μg is considered clean.

Protein detection results are also summarized in Table 3-1. Cleanliness

assessments in terms of residual protein failed “after soiling” and “after pre-rinse”. In

contrast, “after post-rinse” and “after sanitizing”, the protein levels were less than 20 μg

per 50 cm2 sampling area, which indicated an acceptable cleanliness. Results revealed

pre-rinse with only water was insufficient to remove most residual proteins from the

surface of the test vessel soiled with milk at high temperature (ca. 74°C). After heat-

treatment, the milk proteins were likely denatured, making them more difficult to remove

(Stanga, 2010). Washing the test vessel with commercial alkaline chlorinated cleanser

was able to remove residual protein and denatured proteins to an undetectable level (<20

μg). Results of residual protein analyses agreed with the cleanliness assessments made

54

using the ATP bioluminescence assay. This observation again verified the CIP

procedure, using a commercial cleanser and sanitizer, was able to return the test vessel to

a cleaning condition after soiling with whole milk at high temperature. This experiment

confirmed the test system was suitable for further study of CIP procedures.

3.3.3 Test for swab sampling variability

The purposes of this experiment were to determine whether swab sampling

location was a factor leading to variance in cleanliness, as measured by RLU values, and

to determine if this approach could led to systematic errors between trials.

To determine the impact of sampling location on variance of RLU readings, three

areas of the test vessel internal surface were swabbed for ATP bioluminescence analyses

at each cleanliness assessment (after soiling, after pre-rinse or after sanitizing). Means

and standard deviations of RLU values are presented in Figure 3-7. The small standard

deviations obtained indicated the variability of cleanliness at different positions of the test

vessel was small, and the test vessel was evenly soiled and rinsed. Thus, location of

sampling was not a factor leading to variance in cleanliness assessment.

This experiment was conducted in triplicate. ANOVA using Tukey’s comparison

revealed that log10 RLU values were not significantly different between trials. Results

revealed the repeatability of trials using the test system was acceptable (Figure 3-7).

55

Figure 3-7. Log10 RLU values obtained after soiling, after pre-rinse, and after sanitizing.

Error bars represent standard deviation of the evaluations of three locations. Tukey’s

comparison was conducted between 9 sets of data. Means that do not share a letter are

significantly different (α = 0.05).

When comparing the log10 RLU values between steps (after soiling, after pre-

rinse, and after sanitizing), there were no statistically significant differences in general.

The log10 RLU values of “after pre-rinse” were slightly higher than the log10 RLU values

of “after soiling”. This observation may be attributed to the loosening of attached soil

deposits by pre-rinsing with water. The mechanism proposed by Bird and Fryer (1991)

showed that the deposit swelled and formed a gel by a chemical reaction and mass

transfer process, making it more removable.

AB AB AB A A AB AB B AB

0.000

1.000

2.000

3.000

4.000

5.000

6.000

7.000

Trial #1 Trial #2 Trial #3

Log1

0 R

LU

After soiling

After pre-rinse

After sanitizing

56

Comparing the cleanliness “after soiling” with “after sanitizing” (Figure 3-7), the

log10 RLU values were slightly, but not significantly decreased. This result also indicated

that the ATP analysis was not quenched in the presence of acid electrolyzed water (EW).

3.4 CONCLUSION

In this work, a pilot scale test system was constructed for soiling and CIP cleaning

of dairy processing equipment. The test system was designed for optimization of CIP

procedures by controlling soiling conditions, such as soiling temperature; and controlling

CIP parameters, such as flow rate, temperature and time. The pilot scale test system was

characterized with regards to flow rate and coverage. A flow rate of 8.3 L/min was

determined to assure adequate coverage of the test vessel and was used throughout the

thesis project.

Additional tests showed the test vessel was able to be soiled and sprayed evenly;

indicating sampling location was not a factor leading to variance of RLU values. The

repeatability of cleanliness assessments after soiling or CIP procedure also was

determined as acceptable. Results of this experiment also suggested rinsing with acid EO

water did not significantly decrease ATP load on the inner surface of the test vessel. In

other words, acid EO water did not have a quenching effect on ATP in the

bioluminescence assay.

In addition, use of the test system was validated by successful cleaning using a

standard CIP procedure with conventional CIP detergent and sanitizer for the test vessel

57

after soiling with whole milk heated to high temperature (77°C). The results indicate that

the test system was suitable for evaluation and optimization of CIP procedures.

58

Chapter 4

CIP USING ELECTROLYZED WATER FOR A REFRIGERATED

MILK STORAGE TANK

ABSTRACT

Electrolyzed water (EW) is a set of alkaline and acid solutions, namely

electrolyzed reducing (ER) water (pH ca 11.0 and ORP ca. -850 mV) and electrolyzed

oxidizing (EO) water (pH ca. 2.5, ORP ca. 1168 mV and 80-100 ppm of chlorine).

Electrolyzed water has the potential to serve as an alternative to clean-in-place (CIP)

chemicals. Compared to conventional CIP detergents and sanitizers, which are prepared

by dilution of concentrated chemicals, electrolyzed water is safer and more

environmental friendly. In this research, CIP procedures using electrolyzed water for

cleaning of a pilot sale cold milk storage tank were evaluated. Cleanliness was assessed

using ATP bioluminescence analysis, protein residue detection and a microbiological

enrichment assay. After soiling with milk inoculated with Pseudomonas fluorescens,

Enterococcus faecalis and Escherichia coli at refrigerated temperature, to mimic a raw

milk silo, the stainless steel vessel was successfully cleaned using a 4-step CIP procedure

employing electrolyzed water. The procedure included a wash step of using alkaline ER

water for 15 min at 40 °C and sanitizing step of using acid EO water for 1 min at 25 °C.

59

4.1 INTRODUCTION

After being received from the dairy farm, milk is often stored in a refrigerated raw

milk silo at the dairy plant to maintain high milk quality and extend the shelf-life, by

delaying multiplication of microorganisms and inhibiting enzyme activity (Robinson,

2002). The U.S. Department of Health and Human Services (USDHS) Grade “A”

Pasteurized Milk Ordinance (2011) requires that raw milk silos or other storage tanks

should be cleaned immediately after being emptied. Regardless, raw milk silos or storage

tanks must be emptied and cleaned at least every 72 hours.

Because of the size of many raw milk storage tanks (3,000 to 70,000 gallons), CIP

technology is commonly used for cleaning and sanitation. CIP procedures in the dairy

industry are commonly conducted in 4 steps, rinse – wash – rinse – sanitize. The CIP

procedure for cleaning of raw milk silos or storage tanks suggested by the Dairy Practices

Councils (DPC) are summarized as follow: pre-rinse with water at temperature range

from ambient to 43.3°C to remove and loosen milk fouling; wash with chlorinated

alkaline detergent for 15 min at 62.8°C to remove attached milk fouling, such as fat

globules and proteins; post-rinse with cold water to remove residual detergent; and finally

rinse with a sanitizer for destruction of microorganisms and to retard bacterial growth

(Mauck et al., 2001).

Use of electrolyzed water (EW) as a cleaning and sanitizing agent has gained the

attention of the food industry (Huang et al., 2008; Al-Haq et al., 2005). Electrolyzed

water is produced via electrolysis of a dilute sodium chloride solution into sodium and

chlorine ions. A semi-permeable membrane installed between the anode and cathode

60

electrodes separates ions with different charges. An acidic solution is generated on the

anode side. This material is called acidic electrolyzed water (AEW), or electrolyzed

oxidizing (EO) water, and is characterized by having a low pH (2.3-2.7), a high

oxidation-reduction potential (ORP, >1100 mV), and a free chlorine content of 10 to 100

ppm, depending on the types and settings of the electrolyzed water generator. An

alkaline solution is generated on the cathode side. This solution is called basic

electrolyzed water (BEW) or electrolyzed reducing (ER) water, and is characterized

by a high pH (10-13), and low ORP (-800 to – 900 mV). The major component of ER

water is sodium hydroxide (Len et al., 2000; Hricova et al., 2008).

Use of acid EO water as a disinfectant for food processing, for example to reduce

microbial contamination on processing utensils (cutting board, gloves) or food products

(sea food, meat, poultry, shell eggs, fruit and vegetables), has been well investigated

(Monnin et al., 2012; Liu and Su, 2006; Ozer and Demirci, 2006; Fabrizio and Cutter,

2004; Fabrizio et al., 2002; Bialka et al., 2004; Izumi, 1999). In addition, since sodium

hydroxide (caustic soda) has been a typical ingredient in alkaline detergents, it seems

feasible to use ER water as an alkaline detergent for cleaning. Compared with

conventional CIP cleaning, where cleaning and sanitizing solutions are commonly

prepared by dilution of concentrated chemicals, using electrolyzed water for CIP reagents

could avoid purchase, storage and handling of concentrated chemicals. This advantage

improves the operating environment in terms of safety and may also reduce the cost of

production.

Walker et al. (2005a) evaluated the efficacy of alkaline ER water and acid EO

water in cleaning of coupons of five materials used in milking systems. Furthermore, the

61

effectiveness of using both electrolyzed water solutions for removal of milk residue (ATP

reduction) and reducing bacterial level of a pilot scale milking system were also

investigated (Walker et al., 2005b). Both the laboratory and pilot studies suggested that

electrolyzed water had potential as a cleanser and disinfectant for CIP cleaning of

milking systems. The operating temperatures of CIP procedures using electrolyzed water

for a pilot scale milking system were further optimized (Dev et al., 2014). A set of wash

temperature (58.8°C) and sanitizing temperature (37.9°C) were determined and achieved

100% ATP reduction. An on-farm study using electrolyzed water for CIP of a milking

system revealed that electrolyzed water achieved the same or better cleaning efficacy as a

conventional CIP procedure using commercial chemicals of a milking system using

(Wang et al., 2012).

To our knowledge, application of electrolyzed water for CIP procedures of

processing equipment in dairy plants has not been investigated. The purpose of this work

was to evaluate cleaning efficacy of electrolyzed water as a cleanser and sanitizer in CIP

procedures for refrigerated milk storage tanks, using a pilot scale test system.

62

4.2 MATERIALS AND METHODS

4.2.1 Bacterial cultures verification and characterization

In order to mimic raw milk silo soiling, milk used for soiling was inoculated with

a cocktail of three common raw milk cultures (Pseudomonas fluorescens, Enterococcus

faecalis ATCC 51299, and Escherichia coli ATCC 25922). These cultures were obtained

as stock cultures from the Department of Agricultural and Biological Engineering, The

Pennsylvania State University. To activate bacterial cells, each culture was streaked on

trypticase soy agar (TSA), and incubated aerobically for 24 hours at their optimum

growth temperatures: P. fluorescens was incubated at 32°C, while E. faecalis and E. coli

were incubated at 37°C. Individual colonies of each culture were picked and inoculated

into 10 ml of sterile trypticase soy broth (TSB) (Difco; Becton Dickinson and Company,

Sparks, MD), then incubated for 24 h at their optimum temperatures prior to stock culture

preparation.

In order to verify the cultures were the actual species, 16S ribosomal RNA gene

sequence analysis was conducted. To obtain DNA for sequencing, bacteria liquid PCR

(polymerase chain reaction) was conducted, which involved longer initial denaturation

step (5 min) comparing to regular PCR (2 min denaturation), to allow amplification of the

target DNA fragment by PCR directly from liquid culture. Two universal primers for

16S rRNA, which were adopted from sequencing primers developed by the 454 Life

Sciences (Roche Titanium-compatible), were employed for the PCR reactions (Integrated

DNA Technologies, Inc., Coralville, IA):

Test8F (5’-CCAATCCCCTGTGTGCCTTCGCAGTC-3’)

63

Test518R (5’-CCATCTCATCCCTGCGTGTCTCCGAC-3’)

The 25-μl PCR amplification mixtures consisted of 5 μl culture broth (~109

CFU/ml), 5 μl of 5× Colorless GoTaq Reaction Buffer (Promega, Madison, WI) with

MgCl2 (1.5 mM of final concentration), 200 μM of deoxynucleotide triphosphate

(dNTPs, Promega), 0.5 units of GoTaq DNA Polymarase (Promega), and 5 μM of each

primer (Integrated DNA technologies Coralville, IA). The PCR reactions were

performed with a Master-cycler gradient machine (Eppendorf, Hamburg, Germany). The

cycling consisted of an initial denaturation step for 5 min at 95°C, followed by 32

amplification cycles (denaturation for 30 sec at 94°C, annealing for 45 sec at 58°C, and

extension for 1 min at 72°C), and then a final extension step for 5 min at 72°C.

Electrophoresis of PCR amplicons was performed using a horizontal 1% agarose

gel at 110 V for 90 min. Bands were visualized on a UV trans-illuminator after staining

in an ethidium bromide solution (10 mg/ml) for 1 h. The target DNA bands were

extracted from the agarose gel and purified using a QIAquick gel extraction kit (Qiagen,

Valencia, CA) following the manufacturer’s instructions.

Purified PCR amplicons were sequenced in both the forward and reverse

directions using universal 16S rRNA PCR primers mentioned above. Sequencing was

conducted at the Huck Institute Genomic Core Facility of The Pennsylvania State

University. Sequencing was accomplished on an ABI 3730XL DNA analyzer with 3’

BigDye-labeled dideoxynucleotide triphosphate (v 3.1 dye terminators; Applied

Biosystems, Foster City, CA) and ABI sequence analysis software (version 5.1.1). The

16s rRNA gene sequences were identified using nucleotide BLAST (Basic Local

Alignment Search Tool, http://blast.ncbi.nlm.nih.gov/Blast.cgi) (Altschul et al., 1990).

64

To determine the incubation time required to obtain cell concentrations of ca. 109

CFU/ml, the population of viable bacterial cells were assessed using aerobic plate count

(APC) after incubation for 16 h, 20 h, and 24 h, respectively. These assessments were

repeated three times. To compare the difference of cell concentrations at each incubation

point, one-way ANOVA and Tukey’s comparison were applied (Minitab 16, Minitab

Inc., State College, PA, USA). Incubation for 24 h was determined to yield about 109

CFU/ml cells for each culture. For long-term storage, stock culture of each organism

were prepared by mixing 0.5 ml of each cultures with 0.5 ml of 20% glycerol in sterile

screw cap microcentrifuge tube, and freezing at -80°C.

4.2.2 Preparation of inoculated milk

Three bacterial cultures were grown separately as described above. For each

culture, cells from 10 ml of culture were harvested by centrifugation (Model Sorval ST

16 centrifuge, Thermo Scientific, Ashville, NC) at 5,000 g for 10 min at room

temperature. After discarding the supernatant, the bacterial cell pellet was re-suspended

in ca. 2 ml pasteurized whole milk by vortexing. To mimic raw milk, this suspension

was used to inoculate 11.4 liters (3 gallons) of HTST pasteurized whole milk. The final

concentration of bacterial cells was ca. 3×106 CFU/ml. Note that all three test organisms

were added to the milk.

65

4.2.3 Generation and characterization of electrolyzed water

Electrolyzed water generator (Model ROX20, Hoshizaki America Inc., Peachtree

City, GA) was employed to generate electrolyzed water (Figure 4-1). A continuous

stream of deionized water and a 12% sodium chloride solution were fed into the

electrolytic chamber at room temperature to yield a dilute sodium chloride solution with a

concentration of approximate 0.1%. A pressure-reducing valve was installed on the

deionized water supply line to ensure the water pressure was ca. 17 psi, resulting in a

flow rate of 1.9 L/min (0.5 gallon/min) of each output as recommended by the

manufacture (Hoshizaki America Inc.). The operating amperage and voltage were set at

18 amp and 10 volts; respectively. To stabilize the quality of electrolyzed water, the

water electrolyzer was allowed to operate for 10 min before beginning collection. The

alkaline and acid electrolyzed water were prepared prior to each use, and stored

separately in 5-gallon polypropylene carboys that closed with lids, at room temperature

for no more than 3 h.

Figure 4-1. Electrolyzed water generator used in this research.(Model ROX20, Hoshizaki

America Inc.)

66

The characteristics of alkaline and acid solutions were determined before each

use. Characterization included determination of the pH of both alkaline and acidic

solutions using a pH meter (SevenEasy pH meter S20, Mettler Toledo, Columbus, OH)

along with a pH probe (Model InLab 413, Mettler Toledo); ORP of both solutions were

measured using with a combination redox/ORP electrode (Model 9678BNWP, Thermo

Scientific Inc., Beverly, MA) connecting with a pH/ORP meter (Model InLab 413,

Mettler Toledo); the total and free chlorine concentrations of the acidic solution were

evaluated using a digital titrator (Model 16900, Hach Inc., Loveland, CO), equipped with

a N,N- diethyl-p-phenylenediamine-ferrous ethylene diammonium sulfate (DPD-FEAS)

titration cartridge (Hach, Inc.); the OH- concentration of the alkaline solution was

calculated from the pH values. The electrolyzed water was heated in a stainless steel pot

over a gas range prior to use to 42°C, which was slightly higher than the treatment

temperature to compensate for heat loss during liquid transfer.

4.2.4 Preparation of commercial CIP chemicals

Conventional CIP procedures using a commercial cleanser and sanitizer were

employed as a positive control. For the alkaline wash step, Principal®

(3.2~4 ml/L,

Ecolab USA Inc., St. Paul, MN) was used as cleanser. Principal® is a chlorinated alkaline

detergent commonly used for dairy processing equipment. For the sanitizing step, XY-

12®, a sodium hypochlorite sanitizer was used (1.2 ml/L, Ecolab USA Inc.). The

concentrations of both solutions were determined using a titration kit (Ecolab USA Inc.)

following the manufacture’s instruction, to ensure that the concentrations of working

67

solutions were 3200~4000 ppm for Principal® solution, and 100 ppm available chlorine

contained in XY-12® solution. The Principal

® working solution was heated in a stainless

steel pot over a gas range prior to use to 67°C, which was also slightly higher than the

temperature used for positive treatment to compensate for heat loss during liquid transfer.

4.2.5 Preparation of test system

Before each experiment, the test system was cleaned manually and thoroughly,

according to “Sanitation Standard Operating Procedure” used by the Penn State Berkey

Creamery (Votano et al., 2007), as described in Chapter 3.

4.2.6 Soiling the system

To mimic soiling of a raw milk silo, the test vessel was soiled by holding 3

gallons of inoculated milk for 18 h at refrigerated temperatures (2 ~ 4 °C). The cooling

media, sweet water, was circulated through the heating/cooling jacket of the test system

during soiling to maintain the vessel temperature at 1.4 ~ 2.2°C. After soiling, inoculated

milk was drained from the system and 10 ml of milk sample was collected during

draining for aerobic plate count (APC) analyses to determine the population of viable

bacterial cells after soiling.

68

4.2.7 CIP procedure using electrolyzed water treatment

Operating parameters for both treatments are summarized in Table 4-1. For the 4-step

CIP procedure for cleaning of the test system soiled with cold milk, the test vessel was

first pre-rinsed with water for 1 min at ambient temperature (ca. 22°C). After pre-rinsing

with water, the test vessel was treated with alkaline ER water. Two treatments using

electrolyzed water were evaluated: “EW short” with a 5-min ER water wash and “EW

long” with a 15-min ER water wash. Pre-heated (40°C) alkaline electrolyzed water was

circulated on the inner surface of the test vessel by spraying. The temperature of the

alkaline electrolyzed water (40±1°C) was maintained by a coil heat exchanger connected

with a circulating water bath (Thermo Fisher Scientific Inc.). The alkaline electrolyzed

water was drained from the test vessel at the end of the alkaline wash step. The next step

was to post-rinse with tap water for 1 min at ambient temperature (ca. 22°C). Finally, the

test vessel was sanitized by circulating acidic electrolyzed water for 1 min at 25°C, using

the same flow path as that for the alkaline wash step described above. The system was

drained at the end of the sanitizing step. The flow rate was set at 8.3 L/min for the entire

CIP procedure. Each treatment was conducted in triplicate.

69

Table 4-1. Operation temperature and time of four treatments.

Treatments

Wash Sanitizing

Chemical Temp.

(°C)

Time

(min)

Chemical Temp.

(°C)

Time

(min)

Pos Ctrl1 Principal

® 63 15 XY-12

® 25 1

EW Long2 ER water 40 15 EO water 25 1

EW Short3

ER water 40 5 EO water 25 1

Neg Ctrl4

water 40 15 water 25 1

1 Pos Ctrl = Positive control (As recommended by the Berkey Creamery)

2 EW Long = electrolyzed water treatment with longer wash time (15 min, chosen

according to preliminary experiments that remove most soil after rinsing with water).

3 EW Short = electrolyzed water treatment with shorter wash time (5 min)

4 Neg. Ctrl = negative control

4.2.8 CIP control treatments

As a negative control, the system was “cleaned and sanitized” using only water.

As a positive control, the system was cleaned using commercial chemicals following a

conventional CIP procedure. Both negative and positive controls were replicated three

times. The test vessel was soiled, cleaned and sampled for cleanliness assessment by the

same strategies as those for the electrolyzed water.

For the negative control treatment, the test vessel was pre-rinsed with water for 1

min at room temperature (ca. 22°C) after soiling. Then, a “wash step” was conducted by

circulating pre-heated water through the system for 15 min at 40°C. After a 1-minute

post-rinse with water at room temperature (ca. 22°C), the water was circulated through

the system for 1 min at 25°C as the sanitizing step of negative control.

70

For the positive control treatment, the vessel was pre-rinsed with water as

described above for the electrolyzed water. Then, a chlorinated alkaline detergent,

Principal® (3200-4000 ppm, Ecolab USA Inc.), was circulated through the system for 15

min at 63°C, as prescribed by manufacturer. After the Principal®

solution was drained

out of test vessel; another post-rinse with water was conducted for 1 min at room

temperature. Finally, the test system was sanitized by circulating a chlorine sanitizer,

XY-12® (ca. 100 ppm of available chlorine, Ecolab USA Inc.), through the system for 1

min at room temperature. The system was drained before evaluation of cleanliness.

4.2.9 Assessments of cleanliness and data collection

Cleanliness of the inner surface of the test vessel was inspected at several steps

during the cleaning cycle. To ensure the experiment started with a clean test vessel with

RLU = 0 and less than 20 µg per 50 cm2 of protein, cleanliness was assessed after manual

pre-cleaning. During each trial, assessments of cleanliness were conducted after soiling

and draining, after pre-rinse, after alkaline wash and post-rinse, and then after sanitizing

(Figure 4-2). Direct surface sampling using three swabbing methods was employed: ATP

bioluminescence analysis, protein residue detection, and microbiological enrichment

assay. The ATP bioluminescence analysis and protein residue detection were the same as

the methods described in Chapter 3.

71

Figure 4-2. Flow chart of CIP procedures of cold milk storage tank using electrolyzed

water. CIP procedures were conducted at flow rate of 8.3 L/min.

To evaluate the cleanliness in terms of microbial load, 50 cm2 (5 cm × 10 cm) of

surface was carefully swabbed vertically and horizontally in an overlapping pattern using

a sterile calcium alginate swab (Amd Ritmed Inc., Tonawanda, NY) pre-moisturized with

sterile TSB (Difco; Becton Dickinson and Company). After swabbing, the alginate swab

was placed in 10 ml of sterile TSB (Difco; Becton Dickinson and Company) and incubated

for 48 hours at 30°C. The presence of turbidity in the enrichment broth was considered

evidence of viable microorganisms.

72

4.2.10 Statistical design and analysis

One-way ANOVA and Tukey’s comparison were employed using Minitab 16

(Minitab Inc., State College, PA, USA), to compare means of RLU value of each

assessment between treatments. Statistical significance was set at 0.05 (α = 0.05).

4.3 RESULTS AND DISCUSSION

4.3.1 Inoculum bacterial cultures verification and characterization

The identity of the cultures (P. fluorescens, E. faecalis ATCC 51299, and E. coli

ATCC 25922) was verified to the species level using BLAST of 16s rRNA gene

sequence. BLAST results yield 99%~100% identities to their corresponding strains with

sequence lengths of 437~518 bases and 0% gaps (Figure A-1 to A-3).

After growth in 10 ml of TSB for 24 hours at optimum temperatures, viable cell

counts of P. fluorescens, E. faecalis, and E.coli were 9.04 ± 0.07 log10 CFU/ml, 9.46 ±

0.09 log10 CFU/ml, and 9.11 ± 0.03 log10 CFU/ml, respectively (Figure 4-3). Cell

concentrations of E. faecalis were higher than the other two organisms during the

incubation. P. fluorescens had the lowest concentrations. Differences in cell

concentrations of different cultures were likely due to the different initial inoculation

levels and different growth rates. However, the population of all three organisms was ca.

9 log10 CFU/ml after 24-hour of incubation.

73

Figure 4-3. Mean populations of cultures during overnight incubation. Error bars

represent standard deviation of the log10 CFU/ml of three replicates. Tukey’s

comparisons were conducted between three sets of data at each sampling point. Means

that do not share a letter are significantly different (α = 0.05).

4.3.2 Chemical properties of electrolyzed water

Chemical properties of electrolyzed water are listed in Table 4-2. There was no

significant difference in the chemical properties between treatments of EW short and EW

long (p-values are also listed in Table 4-2). Correlations between RLU values and

corresponding chemical concentrations also were evaluated. The results suggested no

correlation between RLU values “after post-rinse” and OH- concentration; or between

RLU values “after sanitizing” and chlorine concentration. Statistical analyses of the

chemical properties of the electrolyzed water analyzed indicated a consistent

composition.

B B' B" A

A' A"

C

C'

B"

7.5

8

8.5

9

9.5

10

16 20 24

log 1

0 C

FU/m

l

Incubation time (h)

Escherichia coli

Enterococcus faecalis

Pseudomonas fluorescens

74

Table 4-2. Chemical properties of electrolyzed water of each trial. P-values were

obtained from Tukey’s comparison between treatments.

Treatment Trials

EO Water1 ER water

2

pH

ORP

(mV)

Total

[Cl-]

(ppm)

Free

[Cl-]

(ppm)

pH

ORP

(mV)

[OH-]

(ppm)

EW Short3

1 2.45 1157 76.7 70.6 11.58 -851 64.7

2 2.35 1178 93.7 90.0 11.76 -880 97.9

3 2.40 1173 83.3 78.6 11.61 -877 69.3

Average 2.40 1169 84.6 79.7 11.65 -869 77.3

St.Dev. 0.04 8.96 7.00 7.96 0.08 13.02 14.69

EW Long4

1 2.33 1170 94.5 93.6 11.65 -877 76.0

2 2.48 1159 68.7 67.1 11.63 -874 72.6

3 2.33 1170 84.7 83.9 11.69 -885 83.3

Average 2.38 1166 82.6 81.5 11.66 -879 77.3

St.Dev. 0.07 5.19 10.63 10.95 0.02 4.64 4.48

p-value 0.75 0.70 0.84 0.86 0.92 0.39 1.00

1 EO Water = electrolyzed oxidizing water

2 ER Water = electrolyzed reducing water

3 EW Short = electrolyzed water treatment with shorter wash time (5 min)

4 EW Long = electrolyzed water treatment with longer wash time (15 min)

4.3.3 Cleanliness assessments

4.3.3.1 Microbiological analyses results

Results of microbiological analyses are presented in Table 4-3. The viable cell

population of the bacterial cocktail in milk was 6.5 ± 0.09 log CFU/ml, after soiling for

18 h at refrigerated temperature (1.4~2.2°C). There was no significant difference in

viable cell population between the treatments (p-value = 0.238). In terms of the surface

swab enrichment tests, only one swab tested negative after “pre-rinse” with water. In

75

general, swabs tested positive “after soiling” and “after pre-rinse”. In contrast, no

positive enrichment results were observed “after wash and post-rinse” or “after

sanitizing”. Regarding microbiological data, rinsing the test system soiled with cold milk

with only water was able to reduce the bacterial population to undetectable levels. In

other words, the soiling of cold milk storage tank, such as that of a milk silo, was

considered light soiling that is easy to remove (Robinson, 2002).

Table 4-3. Microbiological data of inoculated milk after soiling and of swab

enrichment test.

Treatment Trials

APC1

(log

CFU/ml)

After

Soiling2

After

Pre-rinse2

After

Post-rinse2

After

Sanitizing2

Pos. Ctrl3

1 6.453 + + - -

2 6.452 + - - -

3 6.434 + + - -

EW Long4

1 6.491 + + - -

2 6.562 + + - -

3 6.412 + + - -

EW Short5

1 6.574 + + - -

2 6.686 + + - -

3 6.472 + + - -

Neg. Ctrl6

1 6.658 + + - -

2 6.547 + + - -

3 6.472 + + - -

1 Aerobic plate count of inoculated milk after soiling at refrigerated

temperature overnight

2 Indicates turbidity (+) or no turbidity (-) after the enrichment step.

3 Pos. Ctrl = positive control

4 EW Long = electrolyzed water treatment with longer wash time (15 min)

5 EW Short = electrolyzed water treatment with shorter wash time (5 min)

6 Neg. Ctrl = negative control

76

4.3.3.2 ATP bioluminescence assay results

Results of cleanliness assessments based on ATP bioluminescence assays are

presented in Figure 4-4. After soiling, ANOVA using Tukey’s comparison showed no

significant difference for RLU values between the four treatments (p-value = 0.452),

indicating the soiling procedure was repeatable. The RLU values for each of the four

treatments are significantly higher after soiling than the RLU values of the other

conditions (p-value = 0.000). In other words, after a pre-rinse with water, most of the

fouling was removed, as was expected. It has been suggested that a sufficient pre-rinse

should remove 90~99% of fouling (Bylund, 2003). If, as suggested by the manufacturer

of the ATP swabs (Charm Sciences, Inc.), an RLU=0 indicates a clean surface, both the

EW long treatment and positive control returned the test vessel to clean conditions after

alkaline wash and post-rinse. Although the efficacy of the EW long treatment or positive

control was better, the EW short treatment returned the test vessel to a clean state after

the complete four-step CIP cleaning. In contrast, the negative control, cleaned only with

water, did not return the tank surface to acceptable conditions, eliminating the effect of

mechanical force or flow rate.

77

Figure 4-4. Means of RLU values comparison between treatments. Error bar

indicates standard deviation of triplicate analysis. Tukey’s comparisons were conducted

between all RLU values. Means that do not share a letter are significantly different (α =

0.05). (Pos. Ctrl = positive control; EW Long = electrolyzed water treatment with 15-

min wash time; EW Short = electrolyzed water treatment with 5-min wash time; Neg.

Ctrl = negative control)

4.3.3.3 Protein detection results

Results of cleanliness based on protein residue levels are presented in Table 4-4.

The protein residue detection verified fouling on the surface of the test vessel after

soiling. Results revealed that most residual protein on the surface of test system was

removed by the pre-rinse step. After an alkaline wash with ER water or a commercial

detergent, the protein level on the inner surface of the test vessel was so low as to be

a

b

d d

a

b

d d

a

b

c

d

a

b b

b

1

10

100

1000

10000

100000

1000000

After Soiling After Pre-rinse After Post-rinse After Sanitizing

RLU

Pos ctrl

EW long

EW short

Neg ctrl

78

undetectable (< 20 μg per 50 cm2). In contrast, the negative control treatment was less

effective, exhibiting detectable protein residue after both the wash and post-rinse steps.

As expected the results also indicated that swabbing for protein detection was less

sensitive than ATP bioluminescence assay.

Table 4-4. Protein residue levels.

Protein

(ug/ 50 cm2)

Trials After

Soiling

After

Pre-rinse

After

Post-rinse

After

Sanitizing

Pos. Ctrl1

1 > 100 20 ~ 40 0 ~ 20 0 ~ 20

2 > 100 20 ~ 40 0 ~ 20 0 ~ 20

3 > 100 20 ~ 40 0 ~ 20 0 ~ 20

EW Long2

1 > 100 20 ~ 40 0 ~ 20 0 ~ 20

2 > 100 20 ~ 40 0 ~ 20 0 ~ 20

3 > 100 20 ~ 40 0 ~ 20 0 ~ 20

EW Short3

1 > 100 20 ~ 40 0 ~ 20 0 ~ 20

2 > 100 20 ~ 40 0 ~ 20 0 ~ 20

3 > 100 20 ~ 40 0 ~ 20 0 ~ 20

Neg. Ctrl4

1 > 100 20 ~ 40 20 ~ 40 0 ~ 20

2 > 100 20 ~ 40 20 ~ 40 0 ~ 20

3 > 100 20 ~ 40 20 ~ 40 0 ~ 20

1 Pos. Ctrl = positive control

2 EW Long = electrolyzed water treatment with longer wash time (15 min)

3 EW Short = electrolyzed water treatment with shorter wash time (5 min)

4 Neg. Ctrl = negative control

79

4.3.4 CONCLUSION

In this research, two treatments, “EW long” (15-min wash) and “EW short” (5-

min wash), using electrolyzed water as cleanser and sanitizer for CIP of refrigerated milk

storage tank were evaluated. Both treatments were able to return the test vessel to

acceptably clean conditions after the complete 4-step CIP procedure. The effectiveness

of EW long treatment (15-min wash) was comparable to conventional CIP procedure

using a commercial cleanser and sanitizer. Furthermore, the alkaline wash step using ER

water was conducted at lower temperature (40°C) than the conventional operating

temperature (63°C), which indicated that using electrolyzed water as CIP solutions has

the potential to save energy cost and reduce production costs, although the efficacy of

conventional CIP treatment at low temperature was not measured.

80

Chapter 5

CIP USING ELECTROLYZED WATER FOR A HEATED MILK

PROCESSING TANK

ABSTRACT

Electrolyzed water is produce by electrolysis of a weak sodium chloride solution

into alkaline electrolyzed reduction (ER) water and acid electrolyzed oxidization (EO)

water. Previous studies revealed the disinfectant effect of acid EO water on various food

products and cleaning. The potential application in CIP procedure of using alkaline ER

water and acid EO water for cleaning of milking system was also demonstrated. The CIP

application of electrolyzed water on dairy processing plants has not been reported in

literature. In this research, CIP procedures using electrolyzed water were optimized for

cleaning a pilot scale test vessel soiled by thermally processing milk. Cleanliness was

assessed using an ATP bioluminescence assays and protein residue detection. A set of

optimal CIP operational parameters was obtained from regression analyses of a response

surface model. The optimal conditions were alkaline wash with ER water at 54.6°C for

20.5 min and acid sanitize with EO water at 25°C for 10 min. The complete 4-step CIP

procedure using electrolyzed water with optimal parameter combination was validated

and was able to return the test vessel into clean conditions.

81

5.1 INTRODUCTION

Cleaning and sanitizing plays a very important role in dairy foods production.

Not only because of concern about food safety and public health, but also because the

fouling deposits on equipment surface can reduce processing, for example by decreasing

the heat transfer rate of heat exchangers. Design of cleaning procedures depends on

several factors, including characteristics of soil, types of materials to be cleaned,

limitation of cleaning settings in terms of maximum flow rate, temperature, time, and the

degree of cleanliness demanded (Tamime and Robinson, 1999). Soil on dairy processing

equipment used in heat treatment is relatively difficult to remove, requiring more

aggressive cleaning procedures and/or cleaning reagents than is required to clean other

types of dairy processing equipment. A well designed and optimized cleaning procedure

should be able to return equipment to a satisfactory state with a minimum cost, energy

consumption and environmental impact.

Clean-in-Place (CIP) techniques are widely used in the dairy industry. A typical

CIP cycle for cleaning of dairy processing equipment used for heat treatment usually

includes four steps: pre-rinse with cold or warm (43.3°C) water to remove the bulk of the

dairy food residue; then wash with alkaline cleanser at high temperature (62.8°C);

followed by a cold water rinse; and finally by sanitizing, generally with an acid sanitizer

to disinfect the equipment surface (Mauck et al., 2001). The chemicals used to prepare

CIP techniques and sanitizing solutions are usually diluted from concentrated stock

chemicals.

82

Use of electrolyzed water (EW) as a cleaning and sanitizing agent has recently

gained the attention of the food industry (Huang et al., 2008; Al-Haq et al., 2005).

Electrolyzed water is generated by passing a 0.1% sodium chloride solution stream into

an electrolyzer equipped with two electrodes, separated by a semi-permeable membrane.

Positively and negatively charged ions move towards the opposite electrodes, producing

alkaline electrolyzed reducing (ER) water and acid electrolyzed oxidizing (EO) water.

The alkaline ER water contains sodium hydroxide and has a pH of about 11.5 and an

oxidation-reduction potential (ORP) of – 850 mV. The acid EO water has a low pH (2.3-

2.7), high ORP (>1100 mV), and a free chlorine content of 80 to 100 ppm, depending on

the type and settings of the electrolyzer. Because of its chemical properties, electrolyzed

water may be suitable for serving as a cleaning and sanitizing reagent (Huang et al.,

2008; Al-Haq et al., 2005). Using electrolyzed water for CIP procedures generated on

site for cleaning would avoid the need to purchase, store and handle concentrated

chemicals, resulting in potential cost savings and a safer manufactory environment.

The efficacy of acid EO water in reducing microbial contamination has been

investigated (Monnin et al., 2012; Liu and Su, 2006; Ozer and Demirci, 2006; Fabrizio

and Cutter, 2004; Fabrizio et al., 2002; Bialka et al., 2004; Izumi, 1999). Acid EO water

was able to achieve 1 to 7 log reduction of bacterial load on food products or food

processing surfaces (Hricova et al., 2008). Use of alkaline ER water and acid EO water

as CIP reagents on dairy farms has also been investigated. Walker et al. (2005a; b)

evaluated the effectiveness of using both electrolyzed water solutions for removal of milk

residue and bacterial contamination in laboratory and pilot scale studies. Results

suggested that electrolyzed water could serve as a CIP reagent. Dev et al. (2014)

83

optimized the CIP procedure using electrolyzed water for cleaning of pilot scale milking

system in terms of temperatures of the ER water wash and EO water sanitizing steps

regard to achieve 100% ATP reduction. In addition, the on-farm study conducted by

Wang et al. (2012) indicated that electrolyzed water resulted in the same or better

cleaning efficacy then a conventional CIP procedure employing conventional detergents

and sanitizers.

The application of electrolyzed water for CIP procedures of processing equipment

in dairy foods plant has not been reported in the literature. No information was found

related to cleaning of equipment used to heat-treat milk and milk products, soil which is

relatively difficult to remove due to protein denaturation and mineral deposition. The

objective of this work was to investigate the cleaning capability of electrolyzed water for

CIP cleaning and sanitizing of a pilot-scale stainless steel test vessel used to heat-treat

milk. Response surface modeling was employed to optimize the settings of a CIP process

using electrolyzed water. Variables included temperatures and treatment times for both

alkaline ER water and acid EO water treatments.

5.2 MATERIALS AND METHODS

5.2.1 Preparation of electrolyzed water

Electrolyzed water (EW) was generated immediately prior to each trial using an

ROX20 water electrolyzer (Hoshizaki America Inc., Peachtree City, GA) as described in

Chapter 4. Chemical properties of electrolyzed water, such as pH, ORP and chlorine

84

concentration were determined as described in Chapter 4. Concentration of hydroxide

ions [OH-] was calculated from the pH value of alkaline ER water as well using the

equation-1 below:

∵ [OH-] [H

+] =

∴ [OH-] = – -- Equation 1

5.2.2 Experimental design -- response surface model

A Box-Behnken response surface model was employed to determine the optimal

combination of four operational parameters. Specifically the temperatures and times for

both the ERW wash and the EOW sanitizing steps (Table 5-1) were evaluated. A Box-

Behnken design was chosen to minimize the number of trials, and also to avoid using

extreme parameters. The Box-Behnken design with four variables consisted of 27 trials

including 3 replicates of the center points (Table 5-2). The parameter range for each

factor was selected according to previous studies and conventional CIP procedures. The

design, including a randomized running order, was generated using Minitab 16 (Minitab

Inc., State College, PA).

Table 5-1. Levels of four independent variables for CIP using electrolyzed water.

Coded levels

Independent variables Unit -1 0 +1

Temperature for ER water wash °C 40 55 70

Treatment time for ER water wash min 5 15 25

Temperature for EO water sanitizing °C 25 35 45

Treatment time for EO water sanitizing min 1 5.5 10

85

Table 5-2. Box-Behnken response surface design with 27 trails, including 3 center points

(in bold). WashTemp = temperature for ER water wash; WashTime = time for ER water

wash; SaniTemp = Temperature for EO water sanitizing; SaniTime = Time for EO water

sanitizing.

Standard

Order

Run

Order

WashTemp

(°C)

WashTime

(min)

SaniTemp

(°C)

SaniTime

(min)

1 2 40 5 35 5.5

2 10 70 5 35 5.5

3 26 40 25 35 5.5

4 6 70 25 35 5.5

5 18 55 15 25 1

6 13 55 15 45 1

7 7 55 15 25 10

8 21 55 15 45 10

9 3 40 15 35 1

10 17 70 15 35 1

11 20 40 15 35 10

12 14 70 15 35 10

13 15 55 5 25 5.5

14 19 55 25 25 5.5

15 5 55 5 45 5.5

16 11 55 25 45 5.5

17 4 40 15 25 5.5

18 12 70 15 25 5.5

19 24 40 15 45 5.5

20 16 70 15 45 5.5

21 22 55 5 35 1

22 1 55 25 35 1

23 9 55 5 35 10

24 25 55 25 35 10

25 27 55 15 35 5.5

26 8 55 15 35 5.5

27 23 55 15 35 5.5

86

5.2.3 Soiling and CIP treatments

This study was conducted using the pilot scale test system described in Chapter 3.

To ensure a presumably clean condition before soiling, the test vessel was pre-cleaned

manually using HC-10®

and XY-12® (Ecolab USA Inc., St. Paul, MN, USA) as the

detergent and sanitizer as described in Chapter 3 and Chapter 4. Then, the test vessel was

soiled with pasteurized whole milk (Penn State Berkey Creamery, University Park, PA)

and heated as described in Chapter 3. The milk was heated to 74°C under agitation and

then held at 74 ± 1°C for 15 min. After soiling, the heated milk was drained from the

system.

After draining, a four-step CIP cleaning protocol was conducted at flow rate of

8.3 L/min. Steps in the process were pre-rinse, alkaline wash, post-rinse and sanitizing.

The pre-rinse and post-rinse steps were conducted for 3 min at ambient temperature (~

22°C) using tap water. The alkaline wash and sanitizing steps using alkaline ER water

and acid EO water were conducted using the different temperature and time combinations

specified by the response surface model.

Two control treatments also were evaluated in triplicate. These controls included

the same pre-rinse and post-rinse procedures as those used in the electrolyzed water

treatments. For the negative control treatment, tap water was used instead of detergent

and sanitizer. The operating parameters for the negative control were these parameters of

the center point, to be specific; the test vessel was washed with water for 15 min at 55°C,

and sanitized for 5.5 min at 35°C with water. For the positive control treatment, a

commercial detergent and sanitizer were employed. The operating parameters for the

87

positive control were determined from the manufacturer’s suggestion; specifically, wash

with Principal® (3200-4000 ppm, Ecolab USA Inc.) for 15 min at 62.8°C, and sanitize

with XY-12® (ca. 100 ppm of available chlorine, Ecolab USA Inc.) for 3 min at 25°C.

5.2.4 Cleanliness assessments

The cleanliness of the system was assessed after draining, and after different CIP

steps: after pre-rinse, after alkaline wash and post-rinse, and after sanitizing as described

in chapter 3 and 4 (Figure 5-1).

Figure 5-1. Flow chart for CIP procedure of hot milk processing tank using electrolyzed

water.

88

For each trial, cleanliness of the inner surface of the test vessel was assessed using

ATP bioluminescence method and the protein residue detection method. An area of 50

cm2 (5 cm × 10 cm) was swabbed for each cleanliness assessment. The detailed

procedures for swabbing sampling and cleanliness assessment were elaborated in Chapter

3. Table 5-3 contains a summary of the RLU value and protein residue level determined

after each assessment. “RLU0” and “Protein0” represent the responses of cleanliness after

pre-cleaning. These assessments were taken to ensure each trial started with a clean tank

i.e. an RLU = 0 and undetectable protein residues. The measurements for “RLU1” and

“Protein1” were taken immediately after soiling and draining; those for “RLU2” and

“Protein2” were taken immediately after pre-rinse with water and prior to the ER wash

step; those for “RLU3” and “Protein3” were taken after ER water wash and post-rinse

step; those for “RLU4” and “Protein4” were taken after the EO water sanitizing step (at

the end of CIP cleaning).

Table 5-3. Summary of cleanliness assessments at different sampling points.

Sampling point Name of responses

After pre-clean Assessment0 RLU0 Protein0

After soiling Assessment1 RLU1 Protein1

After pre-rinse Assessment2 RLU2 Protein2

After alkaline wash and post-rinse Assessment3 RLU3 Protein3

After sanitizing Assessment4 RLU4 Protein4

89

5.2.5 Other potential factors (Nuisance factor)

Besides the four factors of primary interest (wash temperature, wash time,

sanitizing temperature, and sanitizing time), there were several other factors that may

affect the measured responses as well. Those factors were termed nuisance factors. Data

for potential nuisance factors were monitored and recorded. The nuisance factors are

described below:

5.2.5.1 Different batches of electrolyzed water

Since the shelf-life of electrolyzed water is short, fresh electrolyzed water was

generated prior to each trial. Although electrolyzed water was generated using the same

unit as mentioned in Chapter 3 and Chapter 4 (ROX20, Hoshizaki America Inc.,

Peachtree City, GA). The chemical properties, such as pH, ORP, and hydroxide ions or

chlorine concentrations, varied slightly, within certain ranges. As mentioned above, the

chemical properties of both alkaline ER water and acid EO water were tested and

recorded for further statistical analyses.

5.2.5.2 Day effect

It took 2.5 to 3 hours to complete one trial, so the 27 trials were conducted on

different days. In this case, day was a potential nuisance factor. To be specific, the

temperature and humidity of the pilot plant environment varied on different days. After

soiling and before cleaning, the test vessel was opened for assessing cleanliness. During

90

the time required for assessment, drying and hardening of milk deposits could occur

because the inner surface of the test vessel was hot. This drying and hardening process

was described by Fryer (2009) as “ageing”, the last stage of the fouling processes, in

which the properties of deposit might change. The ambient temperature and humidity

might also influence the ageing process. In an attempt to account for this issue, the

ambient temperature and humidity for each test day were monitored and recorded.

5.2.5.3 Different batches of milk used for soiling

Because the course of the study was longer than the shelf-life of milk used for

soiling, use of more than one batch of milk could not be avoided. Thus, differences in

milk composition between batches, such as fat content and total solids content, might

influence fouling. To address this nuisance factor, a record of code date of each batch of

milk was kept for further tracking.

Even when using the same batch of milk, trials conducted on different days were

actually using milk of different ages. Thus, quality of milk could change slightly during

the storage. To determine the influence of age of milk, the days between trial running

day and milk expiration day (code date) was calculated and recorded for further statistical

analyses.

91

5.2.5.4 Heating conditions during soiling

As described above, soiling of the test vessel with milk under heated conditions

could be divided into two stages. In the 1st stage - whole milk was added to the test

vessel and heated from 4°C to 74°C, by circulating hot water through the jacket of the

test vessel. During the 2nd

stage, once a temperature of 74°C was achieved, injection of

hot water was stopped, and the test vessel was held for another 15 min at 73~75°C. The

steam status varied on different days, which influenced the rate of temperature increase

and thus the time of soiling. In other words, it took a longer time for heating milk to

74°C when the steam pressure was lower, so the test vessel was soiled for a longer time.

To deal with this variation, the heating time was recorded for further analyses. Thus, the

actual soiling time should be heat time (1st stage) + 15 min (2

nd stage).

During the 2nd

stage of soiling, the temperature of milk dropped slightly due to

loss of heat. The highest temperature during soiling (Th), and the final temperature at the

end point of soiling (Tf) were recorded. To deal with this temperature gradient, a

logarithmic mean temperature (TLMT), was considered the actual effective temperature of

2nd

stage soiling, and was calculated using the following equation (Dev et al., 2014):

TLMT =

-- Equation 2

To summarize, several nuisance factors were considered; namely the chemical

properties of electrolyzed water (pH, ORP, concentration of hydroxide ions,

concentration of total and free chlorine), ambient temperature, ambient humidity, milk

code date, days before milk expiration date, heating time, and TLMT. In order to

92

determine which nuisance factors were important enough to be included in the models for

statistical analyses, correlations between nuisance factors and measured responses were

evaluated using Minitab 16 (Minitab Inc., State College, PA).

5.2.6 Data analyses and modeling

Although the operating temperatures of CIP procedures could be controlled using

a coil heat exchanger and monitored by temperature probe, the actual measured operating

temperatures diverged slightly from the target temperatures called for in the response

surface design. For data analyses and modeling, the actual temperature and time of the

ER water wash and EO water sanitizing were used, rather than the target values set by the

response surface design.

5.2.6.1 Regression modeling and optimization of RLU3 data after wash and

post-rinse

Measurements of RLU3 (assessment of cleanliness) were taken immediately after

the alkaline ER water wash and post-rinse with water. Hence, only the temperature and

time of the alkaline ER water wash step was included in the model associated with RLU3.

Thus the predict variables of the model were “WashTemp” and “WashTime”. In order to

determine the effect of ER water and eliminate variance due to levels of fouling, the

percent reduction in RLU from before the alkaline wash step to after the wash and post-

rinse steps was calculated using the equation:

-- Equation 3

93

Percentage reduction RLU would take on a value between 0 and 100%,

representing the proportion of ATP residue removed by the ER wash and post-rinse steps.

In order to improve the residual behavior of response surface regression, natural

logarithms transformations were made. Thus, the response used for regression modeling

and optimization was

-- Equation 4

The goal of the optimization was to determine a temperature and time

combination of the ER water treatment required to achieve a 100% RLU reduction or to

achieve

= 0. Regression modeling and optimization were conducted

using the response surface tools in Minitab 16 (Minitab Inc., State College, PA, USA).

5.2.6.2 Regression modeling and optimization of RLU4 data after sanitizing

Measurements of RLU4 (assessment following complete the CIP protocol) were

taken immediately after acid EO water sanitizing. There were four predict variables in

this model: “WashTemp” represented temperature of the ER water wash step;

“WashTime” represented the treatment time of the ER water wash; “SaniTemp”

represented the temperature used for EO water sanitizing; and “SaniTime” represented

treatment time used for EO water sanitizing. Considering the initial RLU variation,

reduction in RLU from after pre-rinse (RLU2) to after acid EO water sanitizing (RLU4)

was employed as the model response (RLU2-RLU4).

94

According to preliminary experiments, RLU4 readings were likely to be 0 after

the sanitizing step, which was desired. However, not all RLU4 values of 0 represented

equal cleaning efficacy, because (1) the RLU values at the beginning of the process were

different among trials; (2) of limitations in by the sensitivity of ATP analyzer, the actual

RLU values might slightly vary but result in an RLU reading of 0. Thus, the RLU

reduction (RLU2-RLU4) can only be observed to be as high as the initial RLU values,

although a certain combination of the factor levels may have the capability to remove

more milk residue than was present. To address this situation, data were analyzed using a

normal response surface model, along with censoring-type regression model.

In the censoring-type regression model, if the observed “RLU4” value is larger

than zero, which means the observed “RLU2 - RLU4” value were actual RLU reduction,

the designated censor indicator is “0” indicating uncensored. If the observed “RLU4”

value equals zero, which means the observed response of “RLU2 – RLU4” may be less

than the actual RLU reduction, the designated censor indicator is “1” to indicate the

response was censored.

Regression modeling applied to evaluate the effects of the 4 CIP factors described

earlier (“WashTemp”, “WashTime”, “SaniTemp”, and “SaniTime”) on the response RLU

reduction (“RLU2 – RLU4). The response optimization was conducted using predicted

“RLU2 – RLU4” values obtained from the regression model. Both analyses were

conducted using Minitab 16 (Minitab Inc., State College, PA, USA).

95

5.2.6.3 Regression modeling of protein data

Assessment of milk residue in terms of protein was treated as a categorical

variable, because the protein residue was measured by visual inspection of color changes

in protein swabs. As described in Chapter 2, after sampling and testing, swab colors of

green (score 1), gray (score 2), light purple (score 3) and dark purple (score 4) indicated

protein residue levels of < 20 µg, 20~40 µg, 40~100 µg and > 100 µg, respectively.

Since protein measurements actually represent the amount of protein residue, which is

continuous variable, the protein measurements (scores of 1~4) could be considered as

ordinal variables. The goal of CIP with electrolyzed water was to reduce the milk soil

in terms of protein residue to undetectable level (< 20 µg or green color of swab). A

cumulative logistic regression model was employed to estimate the probability of

obtaining a certain level of protein residue. The response of the model was

= αj + β𝑥i -- Equation 5

where π stands for the probability of obtaining protein detection score at or below value j,

e.g. when j =1, π stands for the probability of protein detection score of 1 with the

amount of protein < 20 µg; when j =2, π stands for the probability of protein detection

scores of 1 and 2, with the amount of protein < 40 µg; The data analyses and regression

modeling were conducted using Minitab 16 (Minitab Inc., State College, PA, USA).

96

5.2.7 Validation

The CIP procedure using electrolyzed water with optimal parameters, namely

temperature and time for wash and sanitizing steps was evaluated. The evaluation was

conducted following the same soiling and cleaning steps elaborated in Figure 5-1.

Cleanliness was assessed using ATP bioluminescence assay and protein residue

detection. The cleaning efficacy of optimal CIP procedures was compared with the

treatment using commercial CIP chemicals (positive control) and the treatment using

only water (negative control). Each treatment was conducted in triplicate. RLU values

obtained from ATP bioluminescence assays were converted in logarithms. To compared

log10(RLU) values between treatments, one-way ANOVA and Tukey’s comparison were

conducted using Minitab 16 (Minitab Inc., State College, PA, USA) at confidence level

of 95% (α = 0.05).

5.3 RESULTS AND DISCUSSION

5.3.1 Assessment the importance of nuisance factors

To determine if the nuisance factors were important enough to be included in

regression models, any possible correlations between variables including nuisance factors

and response variables were identified. The outputs of analyses for correlation are

displayed in Appendix (Figure A-4 to A-7). Matrix plots of variables were also

constructed to confirm the information about correlation between variables. The

presence of a linear pattern in a plot suggested the corresponding pair of variables are

97

correlated (Figure A-8 to A-11). Table 5-4 listed the pairs of variables that had relatively

high correlations (p-value = 0.000 ~ 0.052). The Pearson correlation (r) with a range of -

1 to 1 indicates the correlation between a pair of variables: Pearson correlation value

close to -1 or 1 indicates strong linear relationship between variables. Although some

nuisance factors were found to be related to each other with Pearson correlations close to

1 or -1, correlation analyses suggested that none of the nuisance factors are correlated

with the responses (RLU values or protein scores). Thus, it was not necessary to include

any nuisance factors within the regression models.

Table 5-4. P-values of Pearson correlations between variables. Pearson correlation value

close to -1 or 1 indicated the corresponding pair of variables may be related.

Variable 1 Variable 2

Pearson

correlation (r)

p-value of

correlation

RLU1 RLU2 0.600 0.001

ambient temperature code date 0.591 0.002

TLMT* ambient temperature 0.537 0.007

TLMT ambient humidity 0.410 0.052

ORP of acid EO water pH of acid EO water 0.289 0.000

[Total Cl] of EO water pH of EO water -0.885 0.000

[Total Cl] of EO water pH of ER water 0.491 0.009

[Free Cl] of EO water pH of EO water -0.848 0.000

[OH-] of ER water pH of ER water 0.995 0.000

[Free Cl] of EO water [Total Cl] of EO water 0.974 0.000

[Total Cl] of EO water ORP of acid EO water 0.657 0.000

[OH-] of ER water [Total Cl] of EO water 0.503 0.008

* TLMT refers to logarithmic mean temperature during soiling.

Additional data in Appendix A4-A11.

98

5.3.2 Regression model of RLU3 data after wash and post-rinse

Response surface regression analysis for the response

is presented

in Table 5-5. The ER water treatment time was significant at a 95% confidence level (p-

value < 0.05). The ER water treatment temperature and interaction of ER water treatment

time and temperature were significant at the confidence level of 90% (p-value < 0.1).

The coefficient of ER water treatment temperature and time are positive, which indicated

that at higher temperatures and longer times ER water treatment was more effective at

removing ATP contained in the milk residue. To better visualize the model, contour plot

and surface plot were employed (Figure 5-2 and 5-3). The contour plot indicated that,

with certain settings of temperature and time of ER water treatment, a greater than 98.5%

RLU reduction could be achieved (

> -0.02). The regression

model of

is shown in Equation 6:

[ ]

[ ] [

]

-- Equation 6

The low R2 of the model, 48.12%, might be due to the variation of initial RLU values,

however the lack-of-fit test statistic (p-value = 0.721) suggested the model fits well.

99

Table 5-5. Response surface regression: “

” as a function of ER water

treatment temperature and time (WashTemp = temperature of ER water treatment;

WashTime = treatment time of ER water wash).

Term Coefficient P-value

constant -0.603766 0.011

WashTemp 0.013945 0.068

WashTime 0.020466 0.011

WashTemp × WashTemp -0.000085 0.195

WashTime × WashTime -0.000199 0.128

WashTemp × WashTime -0.000222 0.068

WashTemp (°C)

Wa

sh

Tim

e (

min

)

656055504540

25

20

15

10

5

>

–

–

–

–

–

–

–

–

–

–

<

-0.039 -0.027

-0.027 -0.015

-0.015

-0.135

-0.135 -0.123

-0.123 -0.111

-0.111 -0.099

-0.099 -0.087

-0.087 -0.075

-0.075 -0.063

-0.063 -0.051

-0.051 -0.039

ln((RLU2-RLU3)/RLU2)

Figure 5-2. Contour plot of

versus treatment time and temperature of ER

water wash, generated based on regression model (Equation 6).

100

24

18-0.12

-0.08

12

-0.04

40

0.00

50 660

70

ln((RLU2-RLU3)/RLU2)

WashTime (min)

WashTemp (°C)

Figure 5-3. Surface plot of

versus treatment time and temperature of ER

water wash, generated based on regression model (Equation 6).

Figure 5-4 presents the optimization of ER water treatment temperature and time

to achieve a

target of 0. Results of optimization indicate that, when the

wash temperature was 54.6°C and the time was 20.5 min, the response

was predicted to be -0.0092, which was the maximum, but was still lower than the target

of 0. The corresponding RLU percentage reduction

would be 99.08%. The

absolute RLU3 value was predicted for better interpretation of the cleanliness. To predict

the RLU3 value, the mean RLU2 value of 33 trials (27 trials of response surface model, 6

trials of control treatments) was used, which was 462,105. Thus, when CIP cleaning with

ER water for 20.5 min at 54.6°C, after the post-rinse steps, 99.08% of ATP was removed

101

and the predicted RLU3 value is 4251, which indicated the surface was not clean.

Therefore, it can be concluded that the additional rinse with acid EO water step was

necessary to completely clean the system using electrolyzed water.

Figure 5-4. Optimization plot for

versus treatment time and temperature of

ER water wash. The plot suggested the highest desirability was 0.98, when setting ER

water wash temperature at 54.6°C and time at 20.5 min, and the predicted

= -0.0092, indicating 99.08% ( of RLU reduction.

102

5.3.3 Regression model of RLU4 data after sanitizing

Table 5-6 presents results of regression analysis of “RLU2-RLU4” (representing

ATP reduction after cleaning and sanitizing). The factors of temperature and time of ER

water treatment, and the factor of time for acid EO water treatment were significant at a

90% confidence level (p-value < 0.1). Acid EO water treatment temperature was not

significant (p-value = 0.24). The positive coefficients indicated that the cleaning

procedure had better performance at higher temperatures and longer treatment times. The

regression model used for calculating predicted “RLU2 – RLU4” values was:

-- Equation 7

Equation 7 was used for predict value. In the response optimizer

function of Minitab 16 (Minitab Inc., State College, PA, USA), the variables of

“

” and predicted “ ”, were selected to determine an

optimum combination of parameters for best efficacy of CIP cleaning using electrolyzed

water for the test vessel soiled with heated milk. An optimum combination of four

factors was determined to achieve the target value of 0 for “

” and to

achieve a maximum value of “RLU2 – RLU4”. The optimum condition is presented in

Figure 5-5, which suggested that for CIP procedure using electrolyzed water -washing the

103

test vessel with ER water for 22 min at 53.7°C, and then sanitizing the with acid EO

water for 10 min at 25°C after rinse with water-could achieve a desired RLU reduction of

2×106, which is larger than any observed RLU reductions between RLU2 and RLU4. It

may be concluded that it is possible to remove all ATP residue by the CIP procedure

using this optimum combination of electrolyzed water treatment parameters.

Converting the predicted “

” value (–0.0092) to percentage

reduction of RLU3, predicts that 99.08% of ATP residue could be removed by treatment

with ER water for 22 min at 53.1°C. This observation agreed with the conclusion of

response regression modeling and optimization of “

” in section 5.3.2.

Table 5-6. Regression of “RLU2-RLU4” versus ER water and EO water treatment

factors (WashTemp = temperature of ER water treatment; WashTime = treatment

time of ER water wash; SaniTemp = temperature of EO water treatment; SaniTime =

treatment time of EO water sanitizing).

Term Coefficient P-value

constant -2743012 0.062

WashTemp 33653.6 0.085

WashTime 155015 0.047

SaniTemp 31156.4 0.243

SaniTime 381579 0.035

WashTemp*WashTime -2309.31 0.101

SaniTemp*SaniTime -9372.32 0.066

104

Figure 5-5. Optimization plot for “RLU2-RLU4” and “ln((RLU2-RLU3)/RLU2)”. When

setting ER water wash parameters at 53.7°C for 21.6min, setting EO water sanitizing

parameters at 25°C for 10 min, it can be predicted that RLU reduction achieved 99.08%

( after ER water treatment, 1.99 × 106 after EO water treatment, respectively.

5.3.4 Regression model of Protein data

Protein residue detection provided additional confirmation for the response

modeling results. Protein3 was measured after ER water wash and post-rinse. The

regression model presented below:

105

[ ] [ ]

-- Equation 8

In this model, is the constant coefficient of the regression model used to predict the

probability of observing residual protein levels at or below value j (j = 1, 2, 3, or 4):

If j=1, then , which is the constant coefficient for predicting the

probability of observing green in protein residue detecting (residue protein level ≤ 20 μg

per 50 cm2 of surface);

, which is the constant coefficient for predicting the

probability of observing green and gray in protein residue detecting (residue protein

level ≤ 40 μg per 50 cm2 of surface).

When using Equation 8 to predict the probability of observing green in residual

protein assay after cleaning with ER water at 54.6°C for 20.5 min, which are optimal

parameters obtained according RLU data as described above, plug in parameters

( , WashTemp = 54.6°C, WashTime = 20.5 min) into the Equation 8 above.

This leaded to a

-1.707. Thus, the probability of observing green in protein

residue detection would be 15.35%, obtained from the equations below:

P(Y = 1) = π =

= 15.35%

-- Equation 9

106

The analysis of Protein3 indicated that, after rinsing with cold water for 3 min,

wash with ER water for 20.5 min at 54.6°C, and rinse with cold water again for 3 min,

the probability of reduce protein residue of inner tank surface less than 20 µg per 50 cm2

was low (15.35%). This observation was further confirmation that the cleaning with only

ER water was not sufficient to return the test vessel to an acceptably clean condition, and

that the acid EO water sanitizing step was necessary.

Protein4 was measured after sanitizing. There were 25 observations of green out

of 27 trials. A similar cumulative logistic regression was attempted, but the regression

model was found not to be reliable. However, the high frequency (92.6%) observations

of green in protein detection test, suggests that CIP procedures conducted with

electrolyzed water at the optimum combinations of parameters obtained according RLU

response modeling was able reduce residual proteins to an acceptable cleaning condition.

5.3.5 Validation

The CIP procedure using electrolyzed water with optimal parameters was

validated, and its cleaning efficacy was compared to treatments using commercial CIP

chemicals (positive control) and using tap water (negative control). The RLU values and

protein residue measurements are presented in Figure 5-6 and Tables 5-7. The negative

control procedure using water failed to remove all milk soil, in terms of both ATP and

protein residues. The results eliminated the effect of mechanical force or flow rate, and

further indicated the effectiveness of electrolyzed water as CIP reagents. Both

electrolyzed water and positive treatments returned the test vessel to clean conditions

107

after the complete four-step CIP procedures. However, after the alkaline wash step with

ER water at 53.3°C for 21 min and post-rinse with water for 3 min at room temperature,

the RLU reduction achieved 97.5%, and low level of protein residue was detected. While

the positive control, using conventional CIP procedure with commercial cleaning

chemicals, achieved a 100% reduction of RLU values after alkaline wash and post-rinse

step, and the protein residue was reduced to undetectable levels. Thus, the commercial

chemicals employed worked better than the electrolyzed water. This may result from the

low alkalinity (12-216 ppm) (Abramowitz and Arnold, 2002) of ER water with <100 ppm

of hydroxide ions concentration ([OH-]). In contrast, the working solution of the

commercial CIP detergent (Principal®, Ecolab USA Inc.) contains ca. 585 ppm of sodium

hydroxide and 117 ppm of sodium hypochlorite. In addition, The Dairy Practice Council

(DPC, 2001) recommended an alkalinity of 1500~1800 ppm of alkaline detergent that

used for CIP procedures of storage tank. However, both a complete 4-step electrolyzed

water treatment and the positive control treatment were able to return the inner surface of

the test vessel to acceptable cleanliness with 0 RLU value and undetectable protein

residue levels.

108

Figure 5-6. Means of RLU values comparison between validation experiment and control

treatments. Error bar indicates standard deviation of triplicate analysis. Tukey’s

comparisons were conducted between all RLU values. Means that do not share a letter

are significantly different (α = 0.05). (Pos. Ctrl = positive control; EW validation =

electrolyzed water treatment with optimal parameters; Neg. Ctrl = negative control).

Table 5-7. Protein detection of validation experiment and control treatments (where Pos.

Ctrl = positive control; EW validation = electrolyzed water treatment with optimal

parameters; Neg. Ctrl = negative control).

Treatment Trials Protein1

(ug/ 50 cm2)

Protein2

(ug/ 50 cm2)

Protein3

(ug/ 50 cm2)

Protein4

(ug/ 50 cm2)

Pos. Ctrl. 1 > 100 > 100 0 ~ 20 0 ~ 20

2 40~60 > 100 0 ~ 20 0 ~ 20

3 > 100 > 100 0 ~ 20 0 ~ 20

EW

validation 1 > 100 > 100 0 ~ 20 0 ~ 20

2 > 100 > 100 20 ~ 40 0 ~ 20

3 > 100 > 100 20 ~ 40 0 ~ 20

Neg. Ctrl. 1 > 100 > 100 > 100 40~60

2 40~60 > 100 40~60 20 ~ 40

3 40~60 > 100 > 100 20 ~ 40

a a

d d

a a

c

d

a a

ab b

1

10

100

1,000

10,000

100,000

1,000,000

After Soiling After Pre-rinse After Post-rinse After Sanitizing

RLU

Pos ctrl

EW validation

Neg ctrl

109

5.4 CONCLUSION

Optimum parameters, in terms of temperature and time of alkaline ER water and

acid EO water within a 4-step CIP procedure for the pilot scale dairy processing tank,

were determined using response surface modeling.

The response surface regression model was applied to the RLU data both before

and after an EO water sanitizing step (RLU3 and RLU4). Using the RLU3 data, several

regression models of the response surface design were employed. The model with

response of

exhibited the best fit of the models that were evaluated. The

low R2 (48.12%) and adjusted R

2 (35.76%) might due to the variance of RLU

measurements. The model indicated that both ER water treatment temperature and time

were statistically significant at 90% confidence level (p-valueWashTemp = 0.011, p-

valueWashTime = 0.068). The optimum setting of ER water treatment obtained from the

model (54.6°C for 20.5 min), was expected to reduce 99.17% of ATP during first three

steps of CIP (pre-rinse with water – ER water wash – post-rinse with water).

The regression model of RLU4 data suggested that the ER water treatment

temperature and time, and EO water treatment time were statistically significant at a

confidence level of 90% (p-valueWashTemp = 0.085, p-valueWashTime = 0.047, p-valueSaniTime

= 0.035). The optimization result suggested similar settings for ER water treatment

(53.1°C for 22 min), and the settings for EO water treatment (25°C for 10 min). CIP

procedure using electrolyzed water with the optimum settings was predicted to reduce

RLU values by 2 ×106.

110

A cumulative logistic regression model was applied for protein data. The

regression model suggested that ER water treatment alone was not sufficient to remove

all protein residues. The 4-step CIP procedure using electrolyzed water at optimum

settings-wash with ER water at 54.6°C for 20.5 min and sanitize with EO water at 25°C

for 10 min was capable of reducing the protein residue to undetectable level.

A four step CIP procedure using electrolyzed water provided similar cleaning

capability to a conventional CIP procedure. However, direct comparison between CIP

procedures using electrolyzed water and conventional cleaning and sanitizing reagent

suggested that the ER water was less effective than commercial alkaline detergent in

removal of soil from surface fouled by heat treatment. The cleaning efficacy of ER water

might be improved by increasing sodium hydroxide concentration or adding other

cleaning ingredients such as surfactants as wetting/dispersing agents.

111

Chapter 6

CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE

RESEARCH

This study demonstrated that using electrolyzed water (EW) was successful in

removal of soil from the surface of a test vessel soiled with cold milk i.e. mimicking milk

refrigerated storage tanks. By using optimum temperatures and times of a CIP procedure,

electrolyzed water was also found to be capable of cleaning the surface of a test vessel

that was used to heat milk, but was less effective when compared to commercial CIP

detergent and sanitizers. For future research, it would be interesting to improve the

cleaning efficacy of electrolyzed water, especially alkaline ER water, by adding some

surfactant, such as teepol (alkyl aryl sulphonate) or sodium triphosphate, which can serve

as wetting agent.

During the study, corrosion was observed on some surfaces when using acid EO

water as a sanitizer. This observation may occur because chlorine is not stable at low pH

(2.3~2.7) and chlorine gas (Cl2) is released, which is corrosive to many metals, including

stainless steel. To address this drawback, two potential solutions could be considered: (1)

using neutral electrolyzed water with less corrosive characteristics (pH = 7 to 8, ORP =

750 mV, 50-500 ppm of free chlorine, depending on water electrolyzer), which can be

produced by mixing acid EO water with alkaline ER water after electrolysis, or by using

a single electrolysis chamber without semi-permeate membrane; (2) adding corrosion

inhibitors, such as silicates to the acid EO water to prevent corrosion.

112

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APPENDIX:

Figure A-1: 16s rRNA Gene sequence alignment of Pseudomonas fluorescens using BLAST

121

Figure A-2: 16s rRNA Gene sequence alignment of Enterococcus faecalis using BLAST

Figure A-3:16s rRNA Gene sequence alignment of Escherichia coli using BLAST

122

Correlations: RLU3, RLU4, pH (H), pH(OH), ORP (H) (mV), ORP (OH) (mV, ... RLU3 RLU4 pH (H) pH(OH)

RLU4 0.157

0.433

pH (H) 0.016 -0.011

0.937 0.958

pH(OH) 0.080 -0.245 -0.322

0.690 0.217 0.102

ORP (H) (mV) 0.123 -0.181 -0.679 0.523

0.540 0.366 0.000 0.005

ORP (OH) (mV) -0.086 -0.096 0.289 -0.216

0.671 0.634 0.144 0.278

Total Cl (ppm) 0.047 0.010 -0.885 0.491

0.815 0.961 0.000 0.009

Free Cl (ppm) 0.064 0.035 -0.848 0.437

0.752 0.862 0.000 0.023

[OH] (ppm) 0.069 -0.231 -0.333 0.995

0.731 0.247 0.089 0.000

ORP (H) (mV) ORP (OH) (mV) Total Cl (ppm) Free Cl (ppm)

ORP (OH) (mV) -0.130

0.517

Total Cl (ppm) 0.657 -0.279

0.000 0.158

Free Cl (ppm) 0.618 -0.203 0.974

0.001 0.310 0.000

[OH] (ppm) 0.517 -0.221 0.503 0.444

0.006 0.269 0.008 0.020

Cell Contents: Pearson correlation

P-Value

Figure A-4: Correlations between RLU3, RLU4, and chemistry properties of electrolyzed water (pH

values, ORP of both solutions, total and free chlorine concentration of EO water, hydroxide ion

concentration of ER water). The highlighted Pearson correlations that were closed to 1 or -1 indicated

relatively strong correlation of the corresponding pair of variables.

123

Correlations: RLU1, RLU2, RLU3, RLU4, code date, days before , amb-temp, ... RLU1 RLU2 RLU3

RLU2 0.600

0.001

RLU3 0.150 -0.098

0.454 0.628

RLU4 0.159 -0.250 0.157

0.429 0.208 0.433

code date 0.107 -0.072 -0.210

0.595 0.723 0.293

days before expi -0.055 0.238 -0.028

0.785 0.232 0.890

amb-temp 0.053 -0.212 0.277

0.807 0.320 0.190

amb_hum -0.053 0.145 0.346

0.811 0.510 0.106

HtTime (min) 0.015 -0.155 0.050

0.959 0.598 0.866

HtTemp(LMT) 0.002 -0.152 0.159

0.994 0.449 0.427

RLU4 code date days before expi

code date 0.173

0.387

days before expi -0.030 -0.088

0.880 0.662

amb-temp 0.161 0.591 -0.087

0.453 0.002 0.687

amb_hum -0.215 -0.144 0.484

0.324 0.511 0.019

HtTime (min) -0.079 -0.168 -0.144

0.789 0.565 0.624

HtTemp(LMT) -0.058 0.181 -0.189

0.773 0.367 0.346

amb-temp amb_hum HtTime (min)

amb_hum 0.149

0.531

HtTime (min) 0.347 0.207

0.245 0.478

HtTemp(LMT) 0.537 0.410 0.411

0.007 0.052 0.144

Cell Contents: Pearson correlation

P-Value

Figure A-5: Correlations between RLU1, RLU2, RLU3, RLU4 and other nuisance factors. The data

showed no strong correlations between responses and nuisance factors.

124

Correlations: Protein3, Protein4, pH (H), pH(OH), ORP (H) (mV), ... Protein3 Protein4 pH (H) pH(OH)

Protein4 0.347

0.077

pH (H) -0.181 0.308

0.367 0.118

pH(OH) 0.104 -0.156 -0.322

0.605 0.436 0.102

ORP (H) (mV) 0.116 -0.473 -0.679 0.523

0.566 0.013 0.000 0.005

ORP (OH) (mV) -0.296 -0.075 0.289 -0.216

0.134 0.710 0.144 0.278

Total Cl (ppm) 0.138 -0.183 -0.885 0.491

0.493 0.360 0.000 0.009

Free Cl (ppm) 0.136 -0.204 -0.848 0.437

0.498 0.307 0.000 0.023

[OH] (ppm) 0.104 -0.166 -0.333 0.995

0.606 0.409 0.089 0.000

ORP (H) (mV) ORP (OH) (mV) Total Cl (ppm) Free Cl (ppm)

ORP (OH) (mV) -0.130

0.517

Total Cl (ppm) 0.657 -0.279

0.000 0.158

Free Cl (ppm) 0.618 -0.203 0.974

0.001 0.310 0.000

[OH] (ppm) 0.517 -0.221 0.503 0.444

0.006 0.269 0.008 0.020

Cell Contents: Pearson correlation

P-Value

Figure A-7: Correlations between Protein3, Protein4, and chemistry properties of electrolyzed water

(pH values, ORP of both solutions, total and free chlorine concentration of EO water, hydroxide ion

concentration of ER water). The highlighted Pearson correlations that were closed to 1 or -1

indicated relatively strong correlation of the corresponding pair of variables.

125

Correlations: Protein1, Protein2, Protein3, Protein4, code date, ... Protein1 Protein2 Protein3

Protein2 *

*

Protein3 0.060 *

0.767 *

Protein4 0.143 * 0.347

0.477 * 0.077

code date -0.372 * -0.210

0.056 * 0.293

days before expi 0.055 * 0.108

0.786 * 0.592

amb-temp -0.354 * 0.144

0.090 * 0.501

amb_hum -0.234 * 0.029

0.282 * 0.894

HtTime (min) -0.269 * 0.279

0.352 * 0.334

HtTemp(LMT) -0.327 * 0.156

0.096 * 0.438

Protein4 code date days before expi

code date -0.289

0.144

days before expi 0.383 -0.088

0.049 0.662

amb-temp -0.128 0.591 -0.087

0.552 0.002 0.687

amb_hum 0.219 -0.144 0.484

0.315 0.511 0.019

HtTime (min) -0.250 -0.168 -0.144

0.388 0.565 0.624

HtTemp(LMT) -0.174 0.181 -0.189

0.385 0.367 0.346

amb-temp amb_hum HtTime (min)

amb_hum 0.149

0.531

HtTime (min) 0.347 0.207

0.245 0.478

HtTemp(LMT) 0.537 0.410 0.411

0.007 0.052 0.144

Cell Contents: Pearson correlation

P-Value

* NOTE * All values in column are identical.

Figure A-8: Correlations between Protein1, Protein2, Protein3, Protein4, and other nuisance

factors. The data showed no strong correlations between responses and nuisance factors.

126

Figure A-9: Matrix plot of RLU3, RLU4, and chemistry properties of electrolyzed water (pH values,

ORP of both solutions, total and free chlorine concentration of EO water, hydroxide ion concentration

of ER water). Linear pattern of plot that was circled indicated that the corresponding pair of variables

was correlated.

127

Figure A-10: Matrix plot of RLU1, RLU2, RLU3, RLU4 and other nuisance factors. Linear pattern

of plot indicated that the corresponding pair of variables was correlated.

128

Figure A-11: Matrix plot of Protein3, Protein4, and chemistry properties of electrolyzed water (pH

values, ORP of both solutions, total and free chlorine concentration of EO water, hydroxide ion

concentration of ER water). Linear pattern of plot that was circled indicated that the corresponding

pair of variables was correlated.

129

Figure A-12: Matrix plot of Protein1, Protein2, Protein3, Protein4, and other nuisance factors.

Linear pattern of plot that was circled indicated that the corresponding pair of variables was

correlated.