Baking characteristic, color and rheological properties of frozen pizza
dough under different freezing conditions by using a superheated steam(SHS) oven

A thesis presented
byLingke Meng
Supervisor: Tetusya Araki, Ph. D. Associate Professor

Submitted to the Graduate school Agricultural and Life Sciences, the University ofTokyo in partial fulfillment of the requirement for the degree ofMaster of Agriculture
July, 2016iInternational Program in Agricultural Development Studies (IPADS)© Copyright by Lingke Meng 2016
ii

Acknowledgement
I want to deliver my full gratefulness to all the people who have been sharing withme laughter, depression, sunshine and loneliness, to every encouragement and assistancethat kept pushing me moving forward, to each single minute which has been telling methat this would be the very unique period of life of mine, in this well-organized, graceful,fascinating but also silently stressed city, Tokyo.
It is hard to believe that one day I may forget the time spent here. The very first
moment when I stepped out of the plane from Narita Airport, after which a fat middleaged Japanese man who was the headmaster in the Japanese language school that I
attended before I came Todai, spoke purely Japanese that stressed me so much for it was
nearly the first time I had ever talked in Japanese with a real native-speaker. I will notforget all those architectures, sceneries, neon light and gigantic posters outside of thosebuildings on the walls. They were so strangely exciting for me, meanwhile I was remotely
unsettled for them. On earth, I was merely an inexperienced man who was expecting tosee a bigger world while not knowing what was in front of him, from a remote small town
where people had seldom heard of.
But an unbelievable thought, or better to use the word “dream”, was actuallyrooted in my heart. I came here for the pursuit of a university which was named, Todai,
even though the vice-headmaster in the Japanese language school who had listened to myreason of why I came Japan, only left me with a few words emotionlessly but in a verycertain kind of tongue-“There is no way”.
Not only one time had I been still recalling to the memory on that day, when I wasdressed in suit, standing on the top of Second B Annex, looking down at the green leavesiii

dancing in the wind, while grabbing the bag and documents that were all prepared for thatinterview with Araki sensei with my sweated hand. I was questioning myself, “Would I
had any chance to come again?”
The next time when I stepped into this campus once again, I just felt everything,
everything I experienced had made all worth of it. All the effort, stress, failure and selfquestioning that many people may need to undergo unwillingly, did not beat me down
but had taught me a good lesson-“Never give up”.
With no question the life in Todai has been way better than it was in the Japanese
language school, although I came here still with some uncomfortable disbelief that wasmarked deeply in my mind due to those stressed, not-too-good memories in the past, noneof which deserved to be written here, however. It only turned out that none of my pitiful
worries was necessary.
Araki sensei, in the first place, was so considerate in so many things that you evengave me the permission to do my job-hunting back in my country for over three months.
Without that opportunity, I would have enough reasons to be continually stressed up till
the day I find one. Not to mention your help and concern in other places because it willtake too long to cover them all. Special thanks to the night sensei, Liu san and I sharedthose topics and alcohol just as “can’t-be-closer” friends. It was an amazing night. I think
it will be an unforgettable night for Liu san as well.
Sagara sensei then, who behaves just like my old grandparent, offered me so much
not just help, but also warmness. I was honored being trusted to share your office room’s
key, your snacks in the freezer, your beer and wine (bought only for me because I do not
enjoy the flavor of beer as a matter of fact) and your toilet paper (lol). I was treated soivmany times either in those Izakaya or some other restaurants. And thanks for yourinvitation and payment of the transportation fee for attending the conference, which only
turned out to be my personal trip around Kansai area. I will always remember thoseconversations between us, in which you spent so much time and effort on educating me.
Okada sensei, Kobayashi sensei and Takahashi sensei who have been taking somuch care of IPADS students, thanks for the nice courses inside the paddy field, taking
part in wheat harvesting, wine trip to Nagano and Yamanashi. They have all become partsof my colorful life in Todai.
Thanks for Kouno san and Hikaru san, who helped me very much in my research.
Thanks for your precious time squeezed out from other works. I appreciate all thecooperation offered from Mayekawa Manufacturing Company, your time, support andstaff canteen had been of great help.
I know many people like writing a lot “thanks” to their friends inacknowledgement, but some of them were as if in a tongue like saying goodbye forever.
I do not want to write in that way because I have solid confidence we will meet in the
future, in this smaller and smaller world again, and not only once. Members in our lab
room, Morita san, Jaki, Sasao san, Keren, Xiuming, Xueting, Xilin, Hosoe san, “Mr. goodman”, Malica, Ishiwata san, Matsuki san, Manish, Sato san, Kishida san, Morikuchi san..
Members outside our lab, Nigel, Jade, Naho, Mariko, Mai, Javid, Jason, Mihray, Yimon,
Aung, Nuwan, Mie san, Ichimura san, Kitamura san, Takada san, Hoang. We had so many
good memories, you guys really have colored my life in the lab.
I still remember the very precious email which Araki sensei wrote to me, one of
the sentence was “One best thing you can do in your life, is to keep learning in this longv

run”. When a person really becomes one that does not need to be pushed hard on the backto study, not only for tests, not only for money but more for his real development, one
day he grows up. If I need to tell what I think is the essence in the education I get from
Todai, I think that will answer.
Yes, life is long, or short. One part of my life ends up here with this university
permanently, another part, however, is just going to start off on the way.
Best wishes to everyone, to everything, to the old days and to tomorrow.
Regards,
Lingke Mengvi

Baking characteristic and subsequent properties of frozen pizza dough under
different freezing conditions by using a superheated steam (SHS) ovenLaboratory of International Agro-informatics: Lingke Meng
Supervisor: Tetsuya Araki
A new processing method of utilizing superheated steam (SHS) on one of the mosthighlighted frozen food-frozen pizza product is tested, based on the advantages of using
SHS as a processing medium such as lower energy cost, higher heat transfer coefficientcompared with its counterpart hot air (HA) medium. This research aims to give a better
understanding on the evaluation for the baking characteristic and subsequent quality offrozen pizza, including thawing rate, baking time (till 100 ℃), drying rate, crust colour
and rheological properties. HA is used as the comparison baking medium for comparison
together with SHS throughout the whole research steps.
Materials and methods
Samples ingredients include: Rustica pizza flour (100%), salt (1.74%), sugar (2%),
olive oil (3%), dry yeast (0.5%) and water (58%).
The flow of the research steps follows such an order: 1) mixing (7 min), 2) doughpreparation (divided into 75g per sample, moulding), 3) freezing (-5, -15, -25, -35 and 45 ℃), 4) frozen storage (1, 15, 25 and 35 days), 5) sample transportation, 6) baking (HA
and SHS, 260 ℃), 7) instrumental measurement (color and rheological properties
including creep test, fractural test and TPA test) and 8) data analysis (R programming
language: Student t test, ANOVA and TukeyHSD). An experimental SHS oven, by which
both SHS and HA baking environment are available, is developed and used in thisresearch. In the creep test and the fractural test, the crumbs and crusts of the samples were
tested separately.
Results and discussion
Freezing characteristics
Freezing rate was higher in the samples frozen under lower freezing temperatures.
Nonetheless, throughout the whole research, different freezing temperature did not havesignificant influence on either color or rheological properties in the samples baked by HA

vii

or SHS, except thawing rate due to the temperature difference between frozen pizza
dough and baking medium.
Baking characteristics
Compared with the HA baked samples, the samples baked by SHS showedsignificantly higher thawing rate due to higher heat transfer properties. Apparent
correlation was found between baking time and freezing temperature, whereas suchcorrelation was not found in the SHS baked samples. Higher drying rate of the SHS baked
samples were observed, which was due to higher heat transfer properties and easier vapor
diffusion environment in SHS filled space.
Colour change
Crust colour of the samples baked by SHS had significantly darker, yellower andredder outcomes than the HA baked ones, which was attributed to the accelerated
Maillard reaction due to higher heat transfer properties of SHS.
Rheological properties
In the SHS baked samples, crusts were found to be more viscoelastic than crumbs
whereas this was exactly opposite to the results from the HA baked samples. In fractural
test, no breaking points were found except for the samples frozen under -5 ℃ and 15 daysof frozen storage. This was because of the extremely dried condition inside the samples,indicating that fractural test is suitable for the samples in this research. No significant
difference was found in hardness, cohesiveness or gumminess in comparisons between
the crumbs of the samples baked by HA and SHS.
Conclusions
As a new processing method compared with HA, SHS baking showed the potential to
give frozen pizza products higher thawing rate, less baking time, higher drying rate, quick
browning ability and different viscoelastic properties between crumbs and crusts. The
combined effect of initial condensation, drying rate especially at the top layer of pizza,
crust thickness and water redistribution from crumbs to crusts might have played the mostimportant role which differentiated samples baked by HA and SHS. Different freezing
temperatures from -5 ℃ to -45 ℃ did not seem to cause any significant difference incolour or rheological properties in the samples baked by either HA or SHS.

viii

Chapter 1.
1.1.

Introduction ............................................................................................. 1

Superheated steam (SHS) .............................................................................. 1

1.1.1. Brief introduction to SHS ............................................................................. 1
1.1.2. Advantages and disadvantages ..................................................................... 1
1.1.3. Comparison between steam, saturated steam and SHS ................................ 2
1.1.4. Working principle ......................................................................................... 4
1.1.5. Previous research on SHS ............................................................................ 5

1.2.

1.1.5.1.

Utilization of SHS on food stuffs ......................................................... 5

1.1.5.2.

Drying characteristics of SHS .............................................................. 5

1.1.5.3.

Coloring ability of SHS ........................................................................ 6

1.1.5.4.

Sterilization ability of SHS ................................................................... 7

Frozen pizza products .................................................................................... 7

1.2.1. Chance and challenges for frozen food ........................................................ 7
1.2.2. Over view of global market of pizza ............................................................ 8
1.2.3. Previous studies .......................................................................................... 12
1.2.3.1.

Effects of frozen storage on the quality of wheat flour doughs.......... 12

1.2.3.2.

Experimental pizza crusts with toppings ............................................ 14

1.2.4. Pizza baking methods ................................................................................. 15
1.3.

Objective of this research............................................................................. 16

Chapter 2.

Materials and methods .......................................................................... 17

2.1.

Sample ingredients ....................................................................................... 17

2.2.

Flow chart of research steps ........................................................................ 17

2.3.

Mixing ............................................................................................................ 18

2.4.

Dough preparation ....................................................................................... 20

2.5.

Freezing ......................................................................................................... 21

2.6.

Frozen storage (Appendix 2, additional studies) ....................................... 23

2.7.

Transportation .............................................................................................. 24

2.8.

Baking ............................................................................................................ 24

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2.9.

Colour measurement .................................................................................... 27

2.10. Moisture content measurement ................................................................... 28
2.11. Rheological properties measurement ......................................................... 30
2.11.1.

Sample specimens and devices ............................................................... 30

2.11.2.

Fractural test (Tensile test/large deformation) ....................................... 32

2.11.3.

Creep test (small deformation) ............................................................... 34

2.11.4.

Textual test (TPA test/large deformation) .............................................. 36

2.12. Research design and data analysis .............................................................. 38
2.12.1.

Design of this research ........................................................................... 38

2.13. Data analysis ................................................................................................. 39
Chapter 3.
3.1.

Results .................................................................................................... 40

Freezing characteristics ............................................................................... 40

3.1.1. Freezing rate of samples frozen under different temperature ..................... 40
3.1.2. Super cooling phenomenon ........................................................................ 42
3.1.3. Moisture content after freezing and frozen storage .................................... 43
3.2.

Baking characteristics .................................................................................. 44

3.2.1. Overview of temperature and weight loss curves during baking ............... 44
3.2.2. Thawing rate and baking time comparison between HA and SHS ............ 46
3.2.3. Drying rate comparison between HA and SHS .......................................... 48
3.3.

Colour change ............................................................................................... 51

3.3.1. Lightness values ......................................................................................... 51
3.3.2. a values ....................................................................................................... 52
3.3.3. b values ....................................................................................................... 52
3.3.4. Total colour variance .................................................................................. 53
3.3.5. CIE Lab colour correlation with freezing temperature and baking time .... 54
3.4.

Rheological properties .................................................................................. 55

3.4.1. Creep test .................................................................................................... 55
3.4.2. Fractural test ............................................................................................... 58
3.4.3. TPA test ...................................................................................................... 58

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Chapter 4.
4.1.

Discussion .............................................................................................. 59

Freezing characteristics ............................................................................... 59

4.1.1. Freezing rate and assumption of ice crystallization.................................... 59
4.1.2. Moisture content after freezing................................................................... 60
4.2.

Baking characteristics .................................................................................. 60

4.2.1. Initial condensation (SHS) ......................................................................... 60
4.2.2. Temperature curves for heaters .................................................................. 61
4.2.3. The maximum inner temperature of samples during baking ...................... 61
4.2.4. Thawing rate and baking time .................................................................... 61
4.2.5. Drying rate .................................................................................................. 63
4.3.

Colour change ............................................................................................... 64

4.4.

Rheological properties .................................................................................. 68

4.4.1. Creep test .................................................................................................... 68
4.4.1.1.

Effect of freezing rate in either baking method .................................. 68

4.4.1.2.

Assumptions ....................................................................................... 68

4.4.2. Fractural test ............................................................................................... 71
4.4.3. TPA test ...................................................................................................... 72
Chapter 5.

Conclusion and future work.................................................................. 73

5.1.

Freezing characteristics ............................................................................... 73

5.2.

Baking characteristics .................................................................................. 73

5.3.

Colour ............................................................................................................ 74

5.4.

Rheological properties .................................................................................. 74

5.5.

Super cooled samples ................................................................................... 75

5.6.

An overall wrap up of the conclusion ......................................................... 76

5.7.

Future work .................................................................................................. 76

References ...................................................................................................................... 78
Appendix 1.

Supplemental Tables and Figures ........................................................ 89xi

Appendix 2.

Additional tests (prolonged frozen storage) ........................................ 105

Appendix 3.

Samples frozen under -5 ℃ (in which super cooling happened) ....... 115

Appendix 4.

R programming code examples ........................................................... 118

xii

Chapter 1.
1.1.

Superheated steam (SHS)

1.1.1.

Brief introduction to SHSIntroduction

Superheated steam (SHS), namely the saturated steam that is “super” or “over”
heated, is able to reach higher temperature than its vaporization (boiling) point at theabsolute pressure where the temperature is measured. SHS has a history over 100 years,
but only received serious attention during the past 20-30 years, such as in industrial engine
working and drying area. Superheated steam drying systems begin to gain industrial
acceptance with 15 systems operating in several European countries and recently, two
superheated steam driers have been installed in the United States to dry sugar-beet gulp
(Bruce & Hulkkonen, 1998). However, utilization of SHS is still not well spread yet due
to a lack of knowledge about the process and effects of SHS on product quality (Pronyk,
Cenkowski, & Muir, 2005).
1.1.2.

Advantages and disadvantages
Currently SHS is still utilized mainly in industrial drying process, as it has several

advantages in playing as a drying medium as were pointed out by (Lane & Stern, 1956)(Devente & Heijmans, 2001) (Shitata & Mujumdar, 1994) (Tang & Cenkowski, 2000):
1) Able to recover latent heat that was supplied to SHS, thus reducing cost.
2) When drying food, nutrients inside might be well preserved due to a lack ofoxygen within SHS drying system.
3) Higher drying rate possible.

14) Toxic and organic liquids can be recovered easily by condensation, such as wooddrying.
5) Sterilization, deodorization, blanching, boiling and cooking can be performed
simultaneously.
6) Comparatively safer drying operation available (no fire or explosion hazard
because of oxygen-free environment created).
Note that sterilization is considered as a benefit here, whereas this aspect ofcharacteristic would be adverse for other occasions, for instance in certain varieties offood stuffs that essential microbial reactions are desired.
Aside from advantages, disadvantages were also reported by (Mujumdar &Devahastin , 2008):
1) More complex than hot air method.
2) Initial condensation is hard to avoid.
3) Products that may melt would undergo glass transition.
4) Industrial experience is limited
1.1.3.

Comparison between steam, saturated steam and SHS
Commonly for comparison, the counterpart drying or baking medium is hot air,which is same within this research, since hot air (HA) and SHS could be considered as
extreme situation within the inner baking environment (Yoshida & Hyodo, 1963).
Steaming (not saturated), is believed being able to improve the quality of bakery
products such as color and moisture loss. The difference between steam and SHS is thatsteam causes vapor condensation on the surface of the baked material, forming a thin film2

which separates material and baking medium from direct contacting, whereas in SHS
processing, no such vapor condensation happens except for the initial condensation due
to the overlarge temperature difference between materials and SHS. In a sense, steaming
process delays the whole baking process and even delays the crust formation. Additional
moisture absorbs heat from the oven, thereby lowering the surface temperature from thematerials and thus greatly impacts the quality of products (Mahini, Tarzi, & Ardebili,2013).
As was reported by (Lalonde, accessed on 13th, June, 2016), saturated steam isoften more preferable when utilized to obtain better heat transfer capacity, since thetemperature of saturated steam is uniform, no temperature profile can appear between
steam and heating surface. When heating with saturated steam, a thin layer of condensate
also forms on top of the products. The thickness of condensation film is relatively evenover the entire heating surface and the flow equalizes the temperature of the film andprevents the formation of a temperature profile, which helps main the heat transfer
between steam and liquid to a maximum.
Compared with saturated steam, SHS is actually a heat insulator which conducts
heat badly than saturated steam, even though it is hotter and contains more energy. Oneof the superior merits of introducing SHS as the drying system is that a drop in
temperature will not result in condensation of the steam as long as the temperature is still
greater than the saturation temperature at the processing pressure (Pronyk, Cenkowski,
Eng., & Muir, 2004) (Mujumdar & Devahastin , 2008). Also, no condensation exists
except for the initial condensation due to the distinct temperature difference between the
products and SHS at the beginning stage where baking starts.

3

1.1.4.

Working principle
The working principle of SHS drying is sensible heat transferred from superheatedsteam to the products to be dried. During the whole process, SHS stays above its
condensation temperature (depends on the drying system pressure and products
temperature). During drying, SHS plays not only the drying medium but also as a heatsource. Water removed from the product during baking process becomes part of themedium whereas in hot air drying, the moist air must be replaced by fresh air heated tothe desired temperature (Moreira, 2001). During drying, the excess steam, as well as
steam evaporated from the product, can be collected (if possible) and can be used
elsewhere, in other processing part or plant, hence a more efficient usage of energy is
feasible. Emissions during drying, such as polluted or toxic substances, mixed with drying
medium, can be effectively removed through condensation in liquid form and then be
separated and drained. Pollutants that can be collected by condensation, can be burned toclean.

Figure 1-1 Principal scheme of the SHS drying process (Mujumdar & Devahastin ,
2008)

4

1.1.5.

Previous research on SHS

1.1.5.1.

Utilization of SHS on food stuffs

SHS has been proved to be beneficial as a drying medium in many materials,
especially in non-temperature-sensitive materials such as coal (Moreira, 2001) (Li, et al.,2011). It has also been suggested that the future utilization of SHS may not always be in
the form of strictly drying, but also decontamination and product processing. Although
SHS is still mostly utilized in drying processing industrially, some researches had been
conducted on its usage in food stuffs as well. Food such as sugar-beet, pulp, potatoes,
Asian noodles, brewers and distillers’ grain were test as research samples. It was shown
initial condensation was not able to be avoided because of the comparatively cold
temperature of food at the beginning when processing started. Higher steam temperature
was found to lead to decreased drying time and an increase in drying rate. Some qualityof processed products could be beneficially influenced such as an improvements inrecovery, adhesiveness and gumminess of Asian noodles, starch gelatinization and dietaryfiber contents of spent grains. On the other hand, SHS was shown not always beneficial
as a processing medium because some parameters like maximum cutting stress, resistanceto compression and noodle surface firmness of Asian noodles were deleteriously affected(Pronyk C. , Cenkowski, Muir, & Lukow, 2008).
1.1.5.2.

Drying characteristics of SHS

The difference between SHS and HA drying is in diffusion step. In HA drying,diffusion of moisture occurs from inside the product to its surface. In SHS, evaporationof moisture occurs within the material causing cells to expand as moisture turned into
steam which leads to a highly porous dried material (Sehrawat, Nema, & Kaur, 2016).
5

Compared with HA, SHS drying had higher vapor evaporation rate (Chu, Lane, &Conklin, 1953). The drying rate increases as the steam temperature increases for the same
convective heat transfer coefficient. Higher steam temperature also results in more poresand coarser appearance, lower degree of shrinkage, higher modulus of deformation.
Highly dried samples had less gelatinized (Moreira, 2001). Compared with HA drying,initial condensation was detected in SHS drying due to an overlarge temperature
difference between product and SHS. This stage is very important for SHS processing
because it affects drying kinetics (Bourassa, Ramachandran, Paliwal, & Cenkowski,2015). The SHS coming in contact with the product then became cooled and condenses
on the material surface as sensible heat was transferred to the material, which gave a quick
rise in the internal temperature in products (Iyota, Nishimura, Yoshida, & Nomura, 2001).
During the initial condensation, tested samples including sugar-beat, pulp, potatoes,
Asian noodles, brewers and distillers’ grain gained small amount of moisture in the firstfew seconds before the temperature of the products increased to the saturation
temperature (100℃) (Pronyk, Cenkowski, Eng., & Muir, 2004). The condensed water
even permeated into the interior and just after evaporation from the surface began, aregion slightly inward from the surface had higher moisture content than its initial value,in the research tested on potato slices (Iyota, Nishimura, Yoshida, & Nomura, 2001).
1.1.5.3.

Coloring ability of SHS

A color measurement research was conducted by (Iyota, Sakai, & Mamiya, 2013),
sliced bread were baked under hot air (HA) and SHS method, CIE lab parameters were
measured. It showed that in the case of heating with SHS, the value of L* (brightness)decreased more quickly and b* (blue to yellow) had a lower value than the counterpart6

baked with HA. In this research, CIE lab parameters of samples before and after baking
were also measured to check the influence between the two baking method.
Another research of using SHS on the processing of oat groats (Head, Cenkowski,
Arntfield, & Henderson, 2010) found that after processing with SHS, groats were brighter,yellower and redder than the unprocessed groats. Also, Color of oat groats processed withSHS changed significantly (p<0.05) during the initial exposure to SHS, but no majorchanges in the color were noted after around 1 min of SHS processing.
1.1.5.4.

Sterilization ability of SHS

Another research was conducted revealing the microbial decontamination
characteristics of SHS processing method on wheat grain (Hu, Nie, Hu, & Li, 2016).
Different steam temperature, processing time and SHS velocities were used to becompared. It showed that decontamination was efficient at higher SHS velocity, with adistinct decrease in residual levels of bacteria. After SHS treated at 200℃, with 15.0 m3/h
for 80s, approximately 99.9% of total bacteria and 81.8% of Bacillus spp. were reduced.
In this, research, although the velocities of SHS were not measured, the air temperature
was controlled at around 260℃ more baked with baking time much longer than only 80s,
meaning an almost extinction in microorganisms in samples.
1.2.

Frozen pizza products

1.2.1.

Chance and challenges for frozen foodShifts in global economic, social and demographic trends will continue to put

pressure on food supplies, creating new challenges for food manufacturers and consumers.
These changes will significantly reshape the context for food and perceptions fromconsumers. Along with the global populations growing and increasing average incomes,
7diet will change to include more meat and dairy products in countries especially those in
the developing world such as China and India. To ensure all the needs for the diet change
in the emerging market in the future, frozen food could be crucial due to their advantages
for preservation, i.e. long shelf life of the product. So there is a growing desire tounderstand more about the frozen food we eat, including the quality, safety and nutritional
aspects and so on (Board Bia & The Futures Company, 2013).
The commercial production of frozen bakery products mainly began during the1950s, started to gain popularity ever since (Virginia & Tzia, 2007). Despite additionalcosts for freezing, transportation and frozen storage, the use of frozen dough can be
attractive, especially when producing freshly baked products of high add-values atrelatively expensive locations (Asghar, Anjum, Butt, Tariq, & Hussain, 2007). Use offrozen dough permits large scale centralized dough production, distribution and storageof dough in the frozen form and relatively small scale point-of-scale baking(Phimolsiripol, Siripatrawan, Tulyathan, & Cleland, 2008). Frozen dough should have 16
weeks shelf-life if the dough has not been temperature abused during transportation andstorage. As various specialty food products such as frozen pizzas have been developed,
their popularity has increased even further, so that at the present time frozen pizzas andlike products are very important commercially.
1.2.2.

Over view of global market of pizza
An overview report of the situation for global pizza industry was given by (PMQ

Pizza Magzine, 2014). Still concerned as western food, pizza industry in Western Europe,
North America and Latin America occupied the largest market shared globally (SeeFigure 1-2). It was safe to say the pizza restaurant industry had entered the mature stage8

of its life cycle in these regions, especially in the US. Many towns and cities had reachedthe limit of pizza restaurants that their populations could support. That made it harder for
operators to open new stores and for new operators to get into the business.
However, as an emerging market, pizza industrial growth in Asia Pacific regions
was the most remarkable highlight (27%) among all other regions(see Figure 1-3),
leading the global pizza market growth rate. The global diet transition, had brought the
popularity of western food like pasta and pizza to other areas including Asia Pacific,
Middle East, Africa and East Europe. When pizza becomes more and more accepted,
consumers may want to try to make their own pizzas as well. Frozen pizza thus came into
the sight of consumers step by step, offering not only convenience, but also various
flavour by varied toppings, well-preserved nutrients inside, cheaper price and longer
preservation availability.

9Figure 1-2 World pizza market (Billions of dollars) 2014

Figure 1-3 Pizza industry international growth rates 2014
Considering the skill-requiring, time-consuming or other restrained conditions in
the kitchen, the introduction of frozen pizza, including frozen ready-to-eat pizza products
as well as frozen pizza crust and dough, might be beneficial and thus get serious attention.

10

Frozen bakery products including pizzas have a bright prospect in market growth
annually as shown in Figure 1-4 and Figure 1-5.

Figure 1-4 Frozen bakery products market size trend, 2013-2020 (USD Million).
Source: Industry Journals, Related Publications, Company Publications, andMarketsandMarkets Analysis.
Within all frozen prepared foods, frozen pizza has the greatest penetration as muchas 57 percent to American households. Demographically speaking, frozen pizza
consumption is highest among people 18-44 years of age, with consumption dropping in
age levels 45 and up in America. Asian-Americans are less likely to consume frozen pizza
than whites and blacks (Holcomb, 2003).

11

Figure 1-5 World frozen/chilled pizza growth (compound annual growth rate) Period:
2007-2012. Source: Euromonitor International
In all, the simplistic nature of frozen pizza has provided convenience to consumers
for decades. The various options for toppings have allowed frozen pizza to transcend the
traditional image of Italian food and provided the variety that consumers desire.
1.2.3.

Previous studies

1.2.3.1.

Effects of frozen storage on the quality of wheat flour doughs

Several problems arising from the production made from frozen dough have been
described, including 1) gradual loss of dough strength, 2) decrease in the retention
capacity of CO2, 3) longer fermentation time, 4) reduced yeast activity, 5) lowering ofloaf volume, 6) deterioration in the texture of the final product.
The influential factors are containing:
1) The formula ingredients (Salas-Mellado & Chang, 2003) and specifically theeffect of: emulsifiers, shortenings, enzymes or yeast (Ribotta, Leon, & Anon,

12

2001) (Mandala & Sotirakoglou, 2005) (Rosell, Rojas, & Barber, 2001) (Wolt &D' Appolonia, 1984) (Autio & Sinda, 1992). The dough formulation significantly
influence the specific volume and crumb hardness. The type of wheat flour used
for frozen dough production is crucial in imparting desirable baking
characteristics after prolonged frozen storage and the influence of flour type isevident. Supplement of improvers such as gluten and guar-gum improved thespecific volume and form ratio but this was not decisive because excessive use ofhydrocolloids might cause destabilizing or firmer texture of dough due to theinterference with gluten proteins or starch polymers matrix. The problems of
reduced carbon dioxide production or the damage of the gluten network may beovercome by adding improvers. Nevertheless, no one particular improvers resolve
all the issues pertaining to products made from frozen dough.
2) The process parameters such as freezing rate, storage time were announced by (Yi& Kerr, 2009) (Giannou, Kessoglou, & Tzia, 2003) (Giannou & Tzia, 2007)(Salas-Mellado & Chang, 2003). Ice crystal formation and recrystallization, water
redistribution, yeast destruction, damage to gluten network and starch granules
possibly are the direct reasons lead to the change to dough properties (Berglund,
Shelton, & Freeman, 1991) (Varriano-Marston, Hse, & Mahdj, 1980). Doughfrozen at relatively slow freezing rates and stored at higher temperature (-10 ℃ to
-20 ℃), was softer, had higher specific volume and was lighter in color, yet had
greater propensity for staling. In the frozen dough industry, protecting against theeffects of freezing on yeast cellular viability is a main focus of attention. Therefore,
slow cooling in a conventional freezer is the preferred technology instead of13

cryogenics, which gives much more rapid cooling but is supposed to be moredetrimental to the survival of yeast cells in dough pieces (Neyreneuf & Delpuech,1993).
1.2.3.2.

Experimental pizza crusts with toppings

By far the studies on pizza products is still limited, due to its difficulties tostandardize the samples for experimental purposes. Pizza is a flatbread generally topped
with tomato sauce and cheese and baked in an oven. It is commonly topped with aselection of meats, vegetables and condiments. The term was first recorded in the 10th
century, in a Latin manuscript from Gaeta in Central Italy. The modern pizza wasinvented in Naples, Italy, and the dish and its variants have since become popular in many
areas of the world. It will be very difficult and complicated to conduct research on the
pizzas with toppings. A comparison between the doughs cooked by itself and the doughs
cooked with toppings on the top of the crust was asserted by (Mckee, 1997). The toppings
would act as a thermal insulator for the raw dough as heat was driven into the top of pizza.
Whereas, when without toppings, more heat would be driven into the top layer of pizza,
which would result in a tougher crust. Also, toppings are always with at least a certain
moisture vapor permeability which would act as a barrier to the escape of moisture vapor
driven from the top of the pizza during the cooking procedure. On the contrary, when
without toppings, the dough would be drier. On the other hand, the weight of the toppings
also increases the difficulties of researching pizza. In a word, it remains hard to researchon the properties of pizza with toppings before all the influential factors are wellcontrolled.

14

While conducting organoleptic evaluation of pizza products, pizza toppings were
carefully selected by either a thin dressing on the top of crust by tomato sauce but notcovering the crust flavor (Delahaye, Jimenez, & Perez, 2005), or clearly listing theingredients and their proportion inside the toppings (Asghar, Anjum, Butt, Tariq, &Hussain, 2007)
1.2.4.

Pizza baking methods
Historically, pizzas have been baked in deck ovens for a time sufficient to bakethe crust and to bake, heat and melt the ingredients atop the crust. Typically the required
baking time would be around 15 to 25 minutes per pizza (depends on the baking
temperature). This too long waiting time for baking lowered satisfaction of customers.
Likewise, decreased the efficiency and profit for pizzerias (undesirable occupation oftime and space) (Cox, et al., 1995).
One improvement to the art of baking pizzas have been the development of theconveyor oven. Through the use of conveyor ovens, it has been possible to improve theconsistency of baking, ease of operation and utilization of available floor space. For highvolume pizzerias, conveyor ovens have been the industry standard.
Another improvement, air-impingement ovens, are used for baking and cooking
such as pizza crust, tortilla and potato chips, pretzels, crackers, cookies, bread and cakes(Moreira, 2001). Compared with convection ovens, impingement drying methods
generally bake faster and more uniformly, due to its faster air flow speed as was
mentioned in (Pizza Today, 2012).

15

1.3.

Objective of this research
By far, using SHS as baking medium for frozen pizza crust has not been a well-known method and almost there was no previous trials on pizza products in this way.
Based on the unique advantages of SHS processing as was noted above, a new baking
method of utilizing SHS on frozen pizza product is conducted in this research. As apotential processing medium, SHS is still lack of industrial knowledge and experience.
Aside from the advantages, it is also important to investigate on feasibility of the baked
products in this method, such as physical properties, nutritional and healthful aspects,
sensory scores, environmental impact as well as cost and profit.
This research mainly focus on the two major points in order to give a better
understanding of SHS processing on frozen pizza products:
1) Baking characteristics of pizza crust frozen under different temperature andstorage duration by SHS, including thawing rate, baking time and drying rate，color change of SHS baked samples and rheological properties of SHS baked
samples.
2) Comparison of quality of baked samples between HA and SHS baking methods
is simultaneously conducted.

16Chapter 2.
2.1.

Materials and methods

Sample ingredients
Rustica pizza flour (Nisshin Seifun Group), salt, sugar, olive oil, dry yeast andwater were used as ingredients for making pizza sample in this research (as shown
Figure 2-1). These ingredients follows the basic pizza making method from the researchdone by (Asghar, Anjum, Butt, Tariq, & Hussain, 2007) .

Figure 2-1 Sample ingredients
2.2.

Flow chart of research steps
In Figure 2-2, the flow of the main research steps was listed in a flow chart.

Samples underwent mixing, dough preparation, freezing, frozen storage, transportation,
baking, instrumental measurement and obtained data were analysed. Details for each of
the steps will be depicted in following sections.

17Figure 2-2 Flow chart of the research steps
2.3.

MixingFigure 2-3 Kitchen-aid heavy duty mixer
All ingredients were mixed according to a proportion as listed in the Table 2-1,
by a mixer (Kitchen-aid heavy duty plus stand mixer, see Figure 2-3). The order ofmaterials put in the mixing bow l was 1) flour, 2) yeast melted in 40℃ water, 3) salt, 4)
sugar, 5) olive oil. All the materials was slowly mixed for 1 minute and after the dough18

stuck together the mixing speed was turned to medium-slow for another 6 minutes. The
mixing time of dough could be very significant, as pointed out by (Dobraszczyk &Salmanowidcz, 2008) that dough film rupture could be associated with how well thedough is kneaded. Under or over kneading might lead to easier dough film rupture, which
no longer is able to withstand pressure and thus restricted the growth of gas cells within
dough. There are many sayings about the standard of mixing time, according to what
(Correll, 2011) suggested, mixing time for pizza dough was initially based on the mixing
time for bread dough. However, if so, it would made the mixed pizza dough soft enoughwhile not stiff, which is also one of the desired characters of pizza dough. Soft dough,medium-soft, medium, medium-stiff, stiff were five rankings for mixed pizza doughevaluation and among them medium level which required around 6 to 9 minutes of mixing
was selected in this research. After mixing was completed, the dough was taken off fromthe hook of the mixer and was rested for ten minutes, with an aluminium paper covered
for a short-time pre-proofing.
Table 2-1 Sample ingredients proportion

Proportion/%

Weight in each pieces/g

Flour

100

45.4

Salt

1.74

0.8

Sugar

2

0.9

Olive oil3

1.4

Dry yeast

0.5

0.2

Water

58

26.3

19

Total mass

2.4.

75

Dough preparation
Once the dough was pre-proofed, they were divided into 75 g for each pieces, thenshaped and rounded by a sample mould (with a 100 mm diameter and 10 mm height, cutfrom plastic container),as shown in Figure 2-4.

Figure 2-4 Samples shaped by a simple mould
Sample in which the freezing temperature needed to be measured, was fixed in asample holder which was designed for this research. Three iron needles (シリンジ.ノズ
ル UD 15G*150mm), which were hollow inside, had holes opened right in the middle
from either side. Thermocouples ((Brand RS, K type, PFA twin twisted pair thermocouple
cables, single core strand diameter 0.5 mm, minimum operating temperature: – 75 ℃,
maximum operating temperature: 280 ℃) were then inserted and penetrated out of thepipes through the opened holes, by which three exact points were fixed for recording thetemperature in samples during freezing in the upper, core and lower layers, respectively.

20

The distance of centre point between upper to centre and centre to lower needles in thesample holder were equally 5 mm, as shown in Figure 2-5.

Figure 2-5 Samples with thermocouples inserted in three layers, separately
2.5.

Freezing
Hitachi thermostat chamber, low temperature series EC-33LTP, provided by

Mayekawa manufacturing company (see Figure 2-6), was used in this research forfreezing process. After all samples were ready to freeze, they were put on stainless steel
net, frozen under -5 ℃, -15 ℃, -25 ℃, -35 ℃ and -45 ℃, separately. Initial temperaturesin all samples before freezing were around 25 ℃. During freezing, inner temperature ofsamples were measured using thermocouples (Brand RS, K type, PFA twin twisted pairthermocouple cables) connected to a data logger (midi LOGGER GL220, GRAPHTEC,
see Figure 2-7).

21

Figure 2-6 Hitachi thermostat chamber, low temperature series (EC-33LTP)

Figure 2-7 Graphtec data logger
The temperature of upper, centre and bottom layers in all samples were measured
and freezing was stopped when the centre temperature in samples reached down to thefreezing air temperature. In order to capture a better freezing performance also prevent
too much moisture content loss, surface of samples were slightly covered withpreservative film while not sealed too well, so that cold air generated from the refrigerator
was ensured to have a good contact with samples (see Figure 2-8). After freezing processcompleted, samples were packaged by zip-loc.

22

Figure 2-8 Research samples freezing process
2.6.

Frozen storage (Appendix 2, additional studies)
After the core temperature had reached down to the desired temperature,samples were kept frozen in storage refrigerator (SANYO, MDF-U536D). Groups ofsamples were separated in terms of 1 day, 15 days, 25 days and 35 days frozen storage,
under temperatures same with their freezing temperatures, respectively. Among them, 1
day frozen samples were triplicated, whereas due to availability, samples frozen for 15days, 25 days and 35 days were not repeated, thus 3 samples each for all 5 different
freezing temperature (-5 ℃, -15 ℃, -25 ℃, -35 ℃, -45 ℃), under 1 day frozen storage. 1
sample each for 5 different freezing temperature under 15 days, 25 days and 35 days
frozen storage was used for additional studies which was introduced in Appendix 2.
Samples frozen under -5 ℃ were frozen up to 15 days due to its difficulty to maintainthe comparatively higher freezing temperature. Frozen dough should have 16 weeks
shelf-life if the dough has not been temperature abused during transportation andstorage (Phimolsiripol, Siripatrawan, Tulyathan, & Cleland, 2008). However, due to the23availability in the schedule, samples were only remained as long as 35 days frozen
storage to see if there had any significant difference generalised by frozen storage
duration.
2.7.

Transportation

Figure 2-9 Cooler box containing dry ice for frozen sample transportation.
When frozen samples reached the desired storage date, they were taken out fromthe storage refrigerator, transferred to a cooler box (I-BEAM, IJSSEL, Figure 2-9). Dry
ice were used to prevent temperature rise inside. Samples were posted from Mayekawa
manufacturing company to the University of Tokyo. Because the usage of dry ice,
temperature of samples descended further from their original frozen temperature. Hence,
samples were waited to recover to their original frozen temperature before baking started.
2.8.

BakingBaking experiment was conducted using an oven developed that was able togenerate superheated steam (see Figure 2-10.) Pipes connecting faucet and the oven24

allowed tap water flew into the heater and was boiled. Boiling of water kept until water
turned into saturated steam and then was superheated via the super heater (as shown in
Figure 2-11). To achieve superheated steam, a preheating was necessary. The temperatureof superheated steam in this research was 105 ℃.

Figure 2-10 Superheated steam oven
An electric scale (Shimadzu UW4200H) was put on top of the oven, while
separated from the oven by a heat protection space, where an electric fan was also used
for heat dissipation. This was very important because the very sensitive electric scale
could be severely influenced by heat from the oven and thus led to inaccurate data.
Heaters were installed both in upper and lower layer in the oven and heat-durable
thermocouples were tied around heaters to check their temperature. Anotherthermocouple was used to check the air surrounding the sample holder. During preheating,temperature of heaters was adjusted so as to ensure the air temperature surrounding the25

samples to be approximately same and stable for each trials. In this research, surrounding
air temperature was adjusted to around 260 ℃ for both hot air (HA) and superheatedsteam (SHS) baking methods, since HA and SHS could be considered as extreme
situations within the inner baking environment (Yoshida & Hyodo, 1963).
Samples that were baked were inserted with thermocouples approximately into
core part in the samples. Thus it was able to measure the inside temperature of samples
during baking. To avoid samples under or over baking, according to the baking curves
shown later in the results section, baking were stopped immediately when innertemperature reached up to 100 ℃, which was a threshold because temperature of samples
would not rise above it. During baking, weight and temperature of samples were measured
simultaneously.
After baking was completed, samples were allowed to cool down till the innertemperature was down to room temperature before wrapped with preservative films toprevent moisture loss. Three samples frozen under each temperature under 1 day frozen
storage were baked in this research. Samples frozen over 15, 25 and 35 days were nottriplicated due to the availability, however (see Appendix 2).

26

Figure 2-11 SHS oven working principles
2.9.

Colour measurement

Figure 2-12 Handy spectrophotometer
Colour of samples was measured using a handy spectrophotometer NF-333(Nippon Denshoku, Ind.Co.Ltd) as shown in Figure 2-12 and colour was presented in

27

CIE Lab colour space shown in Figure 2-13. L (lightness from 0 to 100), a (+ red, - green)
and b (+ yellow, - green) were recorded. Three places near the center area of the sample(see Figure 2-15) were measured.

Figure 2-13 The CIE Lab colour space(http://dba.med.sc.edu/price/irf/Adobe_tg/models/cielab.html)
After L, a, b values were recorded, Delta E (total colour variance before and after
baking) was calculated, using Equation 2-3-1(2-1)
where L1, a1, b1 stand for L, a, b values of samples before baking; L2, a2, b2 values standfor CIE Lab values of baked samples.
2.10.

Moisture content measurement

28

Three cylindrical small samples (diameter 6 mm, height 10 mm) taken from the
middle part of the samples by cork borer, were dried by a drying oven (F0-60W, Japan,
see Figure 2-14) under 105 ℃ over 24 h. Samples moisture content M [%] was measured
by dry basis method (Singh & Heldman, 2014) through Equation 2-2(2-2)
where Ww is the wet base weight, Wd is the dry base weight.

Figure 2-14 Drying oven F0-60W, Japan

29

2.11.

Rheological properties measurement

2.11.1.

Sample specimens and devices

Figure 2-15 Specimens taken from baked samples
As baked sample had been cooled down to room temperature, three places aroundthe centre area in the sample were taken by cork borer (Kenis, cork borer, size = 3,
diameter = 6mm) as shown in Figure 2-15. Crusts and crumbs of samples were taken andmeasured separately based on visual textural difference (Westerlund, Theander, & Aman,
1989), as it still remains hard to set a precise definition of the spatial domain comprising
crust due to the difficulty to define a boundry during the gradual change in crust properties(Vanin, Lucas, & Trystram, 2009). Before rheological properties measured, thickness30

[mm] of crusts were measured with the build-in thickness measuring function of the creep
meter.

Figure 2-16 Creep meter
A creep meter (RE2-33005C, YAMADEN corp., Japan) was used for rheologicalproperties of samples (see Figure 2-16). A schematic graph of creep meter was listed (seeFigure 2-17) (Morita, et al., 2015). This experimental instrument system was constituted
from viscoelastic measurement part, thickness measurement gauge of specimen, data
recorder and a control and operating computer.
As shown in Figure 2-17, when samples were compressed by a plunger during
the up and down movement of the sample holding stage according to a certain speed, theload cell sensed and recorded the corresponding force. In this research, two large
deformation test (fractural test, textural test) and a small deformation test (creep test) was
conducted and they were explained in the following sections, respectively.

31

Figure 2-17 Schematic of creep meter working principles
2.11.2.

Fractural test (Tensile test/large deformation)
A dedicated software for the creep meter (Ver. 2.3 (BAS-3305)) was employed toanalyse the mechanical properties of crumbs and crusts from baked samples. In fractural
test, breaking force [N], the force recorded at the breaking point in the curve, was used as
the parameter to evaluate samples physical properties through fractural test. Plunger
diameter was 53 [mm].
During fractural test, the compression was conducted up to 100% distortion rate
in a speed of 5 mm/s. Force-strain curve was obtained (as shown in Figure 2-18) with aload cell (200N maximum) in 10 times the voltage magnification (20N), where therupture force was taken as the maximum force peak height required to break the sample.

Figure 2-18 Typical fractural test curve

32Aside from the direct results in fractural test, four stages in fractural curve wereshown. The first stage (stage Ⅰ, strain rate around 0%~5%) was the short moment whensample surface got touched by the plunger and sometimes an unconstant deformation
occurred which might be due to the uneven surface contact between the sample andplunger. In the second stage in the fractural curve, there was a near-linear line area (stage
Ⅱ, strain rate around 5%~10%). Linear viscoelasticity is when the function is separable
in both creep response and load and is usually applicable only for small deformations.
The third stage (stage Ⅲ, strain rate around 10%~30%) was the stage where
sample reached to the breaking point, which was called the yield point in tensile test. A
breaking point detected at the broken down moment in breaking curves were shown in
Figure 2-18. In tensile test the breaking point referred to the yield point, before which thematerial deformed elastically and would return to the original shape once the stress wasremoved, while after which the material deformed plastically. Thus the breaking point
determined the limitation of the force applied to the material without non-reversible
deformation.
The fourth stage (stage Ⅳ, strain rate around 30%~75%) was the final stage wherecompressed samples reached to the maximum recorded force, after which the stress was
stopped and removed, giving a sudden drop in the curve and further decrease of therecorded force.

33

2.11.3.

Creep test (small deformation)
According to the stage Ⅱ in fractural test mentioned above, the material was only

viscoelastic within a very small range of deformation (5%~10%), where it showed a nearlinear curve, indicating characteristics of Newtonian material within that range. Thus the
creep test load was obtained from each of the fractural test curves of samples at the endpoint from where the near-linear line turned non-linear. All operations were automaticallycontrolled by the dedicated software (Ver.1.6 (CAS-3305)). Plunger diameter was 53[mm].

Figure 2-19 Four element Maxwell and Voigt model
In this research, a four element (instantaneous elasticity in E0 [pa], delayedelasticity E1 [pa], delayed viscosity η1 [pa/s] and permanent viscosity ηN [pa/s]) Maxwell
and Voigt model creep test was conducted. A spring and a dashpot were consisted torepresent the elastic and the viscous part, respectively, as shown in Figure 2-19. Figure
2-20 showed typical creep test curves triplicated from one sample frozen under -5 degree
and was kept frozen for 15 days. In response to a sudden deformation of the model, thespring was immediately extended, while the dashpot remained initially motionless (Stage34

1). But the extended spring would be applying a steady force on the dashpot in an attempt
to recoil. This caused the dashpot began to move in the direction of the spring force at a
speed governed by the spring force and the spring kept a constant length all the way. Aslong as the force remained, the deformation remained to be in a linear style perpetually(Stage 2). After sudden release of the applied force (in this research set at 60 s), the spring
began to recoil with the moving dashpot, elasticity deformation was restored while
viscosity deformation remained permanently (Stage 3 and Stage 4). The total operation
time was kept 120 s for all trials.

Figure 2-20 Typical creep test curve
Four elements in creep test can be calculated by Equation 2-3,

(2-3)
where ε is deformation, σx is the loaded stress, t stands for time, exp stands for exponent
retardation time constant. The exponent can be obtained by constructing a semi-log plot35

of the retarding exponential approach between the end of curve which represented elastic
recovery and the permanent curve which represented permanent viscosity (ηN). The semilog plot will result in a straight line whose slope will give the time constant (Figura &Teixeira, 2007).
2.11.4.

Textual test (TPA test/large deformation)
During a TPA test samples are compressed twice using a texture analyzer toprovide insight into how samples behave when chewed. The TPA test is often called the"two bite test" because the texture analyzer mimics the biting action in the mouth. A twobite TPA test was conducted and parameters such as hardness, cohesiveness andgumminess were determined and calculated automatically by the dedicated software(Ver.2.3 (TAS-3305)). Plunger diameter was 53 [mm]. In general, many food products
are permanently deformed beyond the point of plastic deformation in strains of greaterthan 50% (Texture Technologies, accessed on 13th, June, 2016), thus 50% strain
deformation was chosen as the standard. The maximum force was 20N.

Figure 2-21 Typical TPA test curve
A textural test curve was shown in Figure 2-21. The mountain curve of area A1
represented the first bite and area A2 was the second bite. Hardness [N] values were36

translated from maximum force point values, cohesiveness [-] values were calculated by
Equation 2-4.

(2-4)
where A1 is dimension within the first deformation area, A2 stands for the dimension forseconddeformationarea.

Gumminess[N]valuesweredeterminedbyhardness*cohesiveness.
As a matter of fact, the textural test curve is a generalisation of all the threerheological tests in this research. It gave a food mastication process imitation by using
creep test, a very small deformation happened momentarily when food was bitten,
fractural test, a large deformation which completed the first bite, giving a maximum
compression to the food that broke it down and another large deformation till the otherone bite. The three tests were combined within one plot in order to give a better vision of
the mastication process by using instrumental experiment, as shown in Figure 2-22.

Figure 2-22 Typical force vs time curve measured during two bites(1) Small deformation shortly after first touch(2) Large deformation until first bite completed37

(3) Large deformation until send bite completed

2.12.

Research design and data analysis

2.12.1.

Design of this research

Figure 2-23 Tree diagram of research design
Figure 2-23 showed the design of this research. Among all the research steps, 1
day frozen samples were triplicated for each of the five groups of samples frozen under
different temperature, from -5 ℃, -15 ℃, -25 ℃, -35 ℃, -45 ℃, and three specimens takenfrom each baked samples thus 9 data for each sample (colour and rheological properties
measurement). Although samples kept frozen for over 15 days, 25 days and 35 days were38

not triplicated in this research due to the availability, it was still expected to show sometendency and assumptions for future work.
2.13.

Data analysis
R programming language was used in this research for both data analysis andgraphing, together with Excel for some further handling of graphs. Packages were
downloaded from CRAN (The Comprehensive R Archive Network, accessed on 13th,
June, 2016),including data restructuring and aggregating package reshape2, data splitting
package plyr, graphing packages such as ggplot2, grid, gridExtra, scatterplot3d,
lattice, data reading package xlsx and correlation coefficient graphing package corrplot.
Statistical significant difference was worked out by ANOVA test if there wereover two compared objectives. Student t test was used when there were only two set ofdata compared. If significant difference was found within multiple datasets by ANOVA
test, TUKEY HSD (honestly significant difference) test was used for advanced pairwise
comparison (Kono, Kawamura, Yamagami, Araki, & Sagara, 2015). Throughout thisresearch, 95% confidence interval was chosen in ANOVA test, pairwise TUKEY-HSD
test and Student t test, while 99% confidence interval was selected in finding the crosscorrelation coefficient in the results.

39

Chapter 3.

Results

3.1.

Freezing characteristics

3.1.1.

Freezing rate of samples frozen under different temperature

Figure 3-1 Freezing temperature curve of sample centre temperature under different
freezing temperature
The plots which recorded the temperature change of upper, center and lower layersof samples frozen under five different temperature (-5, -15, -25, -35, -45 ℃) duringfreezing were included in the Appendix 1 (Figure A1-1, Figure A1-2, Figure A1-3,
Figure A1-4, Figure A1-5). Figure 3-1 showed an overview of the five freezing
temperature curves of center temperature in samples change during freezing process.
Initial temperature of all samples started from around 25 ℃. The freezing curves
went down drastically when the temperature was above 0 ℃, while showing a distinct
40

change of the shape in each of the curves between the temperature ranges from around 1 ℃ to -4 ℃. It was supposed that most of the ice crystallization happened within thisrange. This results corresponded with the statement from (Giannou, Kessoglou, & Tzia,
2003) Freezing normally starts at −1 ℃ to −3 °C and as the temperature drops more of
the water in food becomes frozen.
After a slowing down period which was required to remove the latent heat insamples, each of the freezing curves started to go down again till it reached the same
temperature with the freezing air in the freezer.

Figure 3-2 Magnified freezing temperature curve between 0 and -5 ℃ region
Freezing rate [℃/min] was calculated from the result of how fast each curves
passed through the freezing zone (see Figure 3-2). FA stood for the exact point where thespecified freezing curve started to change the direction from which it originally was going,by drawing a tangent line. It referred to the freezing point for the sample. FB was the exact
point from where the freezing curve restarted to go down in a linear way. Freezing rate41

was thus calculated as the slope of the line between FA and FB, as shown in Equation 31.

(3-1)
where ΔT and Δt referred to the temperature and time difference between the two points.
Table 3-1
Freezing Rate [℃/min]
-5℃

0.95

-15℃

0.14

-25℃

0.28

-35℃

0.49

-45℃

0.50

As a result, the lower the freezing temperature, the higher the freezing rate was,as shown in Table 3-1.
3.1.2.

Super cooling phenomenon
However, samples frozen under -5 ℃ showed an exceptional higher freezing rate

among all freezing rates calculated above. In this research, the freezing rate of samples inwhich super cooling phenomenon happened was calculated by how fast the temperaturerose suddenly from lowest point till the point it restarted to drop again in the freezing
temperature curve.

42Super cooling is unpredictable and will cause a general confuse as a matter of fact.
In this research, super cooling broke the trend that lower freezing temperature had higher
freezing rate, because the formation of ice crystal was completed so soon that the freezing
rate even doubled the freezing rates of samples that were frozen under -45 ℃. For
convenience sake, in this research samples frozen under -5 ℃ were discussed separatelyfrom the other four groups of samples (see details in Appendix 3).
3.1.3.

Moisture content after freezing and frozen storage
During freezing, a certain amount of moisture was lost in samples. In 1 day frozen

samples, positive correlation was found between moisture content [%] in samples andfreezing rate(r= 0.86, p value < 0.01, r2=0.74), indicating that lower freezing rate andmore exposure time to the refrigerating air lead to more water loss in samples, see Table
3-2. Samples frozen under -5 ℃ had the lowest moisture content (64.7±0.4%) and samples
frozen under -45 ℃ had the most moisture content (71.1±0.5%).
Table 3-2 Sample moisture content [%] (1 day frozen storage)
Freezing Temperature/℃
Samples
-5
Crumb

-15

-25

-35

-45

64.7±0.4b 68.1±0.8a 68.5±0.1a 70.0±0.4c 71.1±0.5d

a,b,c:Means in the same column by the same lowercase superscript letters are not significantly different(p<0.05)

43

3.2.

Baking characteristics

3.2.1.

Overview of temperature and weight loss curves during baking
Figure 3-3 and Figure 3-4 showed the weight loss curve of samples, temperatureof heaters and surrounding air and inner temperature within samples during baking by
HA and SHS.

Figure 3-3 1 day frozen samples baking performance by HA method.
Note: In the legend column on the right side of graph, names of variables were assigned to be classified easily for graphing anddata analysis in R programming language. N, stands for no SHS used, 1 is 1 day, T means temperature, W means weight, M means
minus. N1TM45 thus indicates the inner temperature of samples frozen under -45 ℃ under 1 day frozen storage, baked without
SHS. Upper, air and lower referred to upper heater, surrounding air and lower heater.

44

Figure 3-4 1 day frozen samples baking performance by SHS method.
Note: In the legend column on the right side of graph, names of variables were assigned to be classified easily for graphing anddata analysis in R programming language. S, stands for SHS used, 1 is 1 day, T means temperature, W means weight, M means
minus. S1TM45 thus indicates the inner temperature of samples frozen under -45 ℃ under 1 day frozen storage, baked with SHS.
Upper, air and lower referred to upper heater, surrounding air and lower heater.

Upper part of either graph is weight loss curve of samples during baking. From
weight loss curve it showed that almost all samples had a similar weight loss speed,
especially in the HA baking method. In all SHS baked samples, there was a rise in theweight loss curve within a short time in the initial baking period.
Middle part of either graph stands for the temperature curves for upper and lower
heaters in the oven and temperature of the air surrounding baked samples. Upper heaterand lower heater were adjusted to around 350 ℃ and 290 ℃ respectively in order to allow
temperature of the surrounding air to be kept around 260 ℃, for both baking methods.
When SHS was added into the system, the inside temperature became less stable thanbarely HA. Even though, the surrounding air temperature (green line) around samples still45

maintained as most stable as possible throughout the whole baking process, offering
samples the same surrounding air temperature with HA.
Lower part of either graph is the inner temperature of samples curve from samples
initial frozen temperature till completely baked. The maximum baking temperature insamples would not get over 100 ℃, which gave a same result as found in other research(Le-bail, et al., 2011). In order to avoid samples being under or over baked, while innertemperature of samples reached up to 100 ℃, baking was stopped immediately and thus
all the subsequent properties were measured of samples that the core temperature reachedexactly up to 100 ℃.
3.2.2.

Thawing rate and baking time comparison between HA and SHS

Figure 3-5 Centre temperature curve comparison of samples during baking
Figure 3-5 gave a better vision at the comparison of center temperature in samples
change during baking between the two baking methods. Baking time was calculated by46

the time period from initial temperature in samples till it reached up to 100 ℃. Thawing
speed [℃/min] was calculated through Equation 3-1(3-1)
where ΔT and Δt are the temperature and time difference between the starting point attime 0 and the point when the curve reaches 0 ℃.
Significant difference was found between samples baking time and freezing rate,
indicating lower freezing temperature, longer baking time in HA baked samples. In SHS
baked samples, no such significant different or correlation was found.
HA baking method tended to give higher thawing rate to samples that were frozen
with higher freezing rate (lower freezing temperature) (correlation coefficient: 0.79, p <0.01, as shown in Table 3-7), significant difference was found, too. However, in SHS
baked samples, no such correlation was found or significant difference was found.
Compared with HA baking method, SHS gave a significantly faster frozen sample
thawing rate and less baking time till samples are fully baked, as shown in Table 3-4.
Also, negative correlation (r = -0.67, p < 0.01) was between thawing rate andbaking time in SHS baked samples, i.e. faster thawing rate, shorter baking time. No suchcorrelations was found in HA baked samples. This indicated a more consistent baking
temperature characteristic from thawing stage till fully baked samples when using SHS
as the baking medium.

47

Table 3-3 Baking time comparison between HA and SHS
Freezing Temperature/℃

BakingSamplesmethod

-5

-15

-25

-35

-45

HA

9.5±0.6c,A 11.6±2.1b,A 11.9±1.1ab,A 12.2±1.2ab,A 13.8±2.0a,ASHS

7.0±0.2c,B

Crumb
8.6±1.7a,B

9.8±1.4a,B

8.4±0.6ac,B

9.6±1.8a,B

a,b,c:Means in the same column by the same lowercase superscript letters are not different(p<0.05)
A,B,C:Numbers followed by the same uppercase superscript letters in the same column have no difference(p<0.05)

Table 3-4 Thawing rate comparison between HA and SHS
Freezing Temperature/℃

BakingSamplesmethod

-5

-15

-25

-35

-45

HA

6.6±0.4ab,A5.0±1.2a,A

6.9±1.2b,A8.4±0.9b,A10.8±2.1c,ASHS

3.9±0.5a,B

17.5±9.9b,B 13.7±4.2ab,B 37.7±14.0c,B 15.1±4.1b,B

Crunb

a,b,c:Means in the same column by the same lowercase superscript letters are not different(p<0.05)
A,B,C:Numbers followed by the same uppercase superscript letters in the same column have no difference(p<0.05)

3.2.3.

Drying rate comparison between HA and SHS
Initial condensation was mentioned in some previous studies such as (Devente &Heijmans, 2001) and an overview by (Mujumdar & Devahastin , 2008). It was reflectedin the weight loss curves. As shown in Figure 3-6 of the weight loss comparison between
the two baking methods, as soon as the baking process started, samples baked by SHS
gave an immediate rise in weight, which indicated the initial condensation of SHS on thesurface of the samples due to a comparatively huge temperature difference that cooled
down SHS in the surrounding air.

48

Figure 3-6 Weight loss curve comparison of samples during baking

Table 3-5 Drying rate during baking of 1 day frozen samples
Drying rate/% during baking
Freezing Temperature/℃
Samples
-5

-15

-25

-35

-45

HA

2.8

8.4

5.9

8.5

8.5

SHS

8.8

10.1

12.4

12.1

14.7

Crumbs49

Table 3-6 correlation and p values between freezing rate, thawing rate and baking time

Table 3-6 showed the correlation and related p values between freezing rate,
thawing rate and baking time. HA baked samples showed a positive correlation between
thawing rate and freezing rate (r = 0.79, p<0.01), while SHS baked samples showed anegative correlation between thawing rate and baking time (r = -0.67, p<0.01).

50

3.3.

Colour change

3.3.1.

Lightness values
Colour is probably one of the most important parameter for food stuffs because it

is always firstly evaluated by consumers (Pronyk C. , Cenkowski, Muir, & Lukow, 2008).
Table 3-7 showed CIE Lab values for 1 day frozen samples. Samples frozen under
different freezing temperature showed almost no significant difference.
Table 3-7 Raw sample CIE Lab values before baking (1 day frozen storage)
Freezing Temperature/℃

Raw samples after
freezing

-5

-15

-25

-35

-45

L1

85.2±0.8b 88.9±1.6a 87.5±1.9a

87.3±1.5a 87.5±1.6aa1

4.0±0.6b

3.1±0.5ab1

14.5±1.0b 12.9±1.3a 13.5±0.9ab 14.4±1.1b 13.4±1.0ab

2.9±0.4a

2.9±0.4a

3.0±0.7aa,b,c:Means in the same column by the same lowercase superscript letters are not significantly different(p<0.05)

Table 3-8 listed L (lightness) values by HA and SHS baking method. Comparedwith HA, SHS gave samples lower L values in samples frozen under all freezing
temperature. HA baked samples had no significant difference in L values under different
freezing temperatures, whereas significant difference was found in SHS baked samples
frozen between -25 ℃ and -35 ℃.

51

Table 3-8 L2 of samples baked by two different method
Freezing Temperature/℃

BakingSamplesmethod

-5

-15

HA

80.9±2.0a,A

82.5±4.5a,ASHS

77.8±1.3c,B 61.9±5.4ab,B 54.9±6.1a,B 65.7±5.9b,B 60.8±7.7ab,B

-25

-35

82.2±1.7a,A 81.4±2.6a,A-45
81.3±2.3a,ACrust

a,b,c:Means in the same column by the same lowercase superscript letters are not significantly different(p<0.05)

3.3.2.

a values
Table 3-9 listed a2 (- green, + yellow) values by HA and SHS baking method.

Compared with HA, SHS gave samples larger a2 values, indicating a yellower outcome.
HA baked samples had no significant difference in a values under different freezing
temperatures, whereas significant difference was found in SHS baked samples frozen 35 ℃ compared with other sample groups.
Table 3-9 a2 of samples baked by two different method
Freezing Temperature/℃
Samples Baking method
-5

-15

-25

-35

-45

HA

3.0±0.4ab,A2.6±0.8a,A

2.7±1.2ab,A2.5±1.1a,A

4.5±2.4b,ASHS

4.1±1.0c,B

18.9±2.9a,B 19.1±0.9a,B 12.5±4.6b,B 16.0±3.1a,B

Crust

a,b,c:Means in the same column by the same lowercase superscript letters are not different(p<0.05)
A,B,C:Numbers followed by the same uppercase superscript letters in the same column have no difference(p<0.05)

3.3.3.

b values
Table 3-10 listed b2 (- blue, + red) values by HA and SHS baking method.

Compared with HA, SHS gave samples larger b2 values, indicating a redder outcome. In
HA baked samples, significant higher b values was found in samples frozen under -45 ℃
compared with samples frozen under -15 ℃. In SHS baked samples, whereas significant

52lower values was found in SHS baked samples frozen -35 ℃ compared with samples
frozen under -15 ℃.
Table 3-10 b2 of samples baked by two different method
BakingFreezing Temperature/℃

method-5HA14.6±0.5ab,A 13.0±1.0a,A 12.1±1.9a,ASHS

17.6±2.1c,B

Samples
-15

-25

-35

-45

13.9±1.5ab,A 16.7±4.8b,A

Crust
35.0±3.4a,B

32.4±3.9ab,B 28.2±5.1b,B

30.9±1.9ab,B

a,b,c:Means in the same column by the same lowercase superscript letters are not different(p<0.05)
A,B,C:Numbers followed by the same uppercase superscript letters in the same column have no difference(p<0.05)

3.3.4.

Total colour variance
Table 3-11 listed ΔE* values (calculated through Equation 2-1) by HA and SHS

baking method. Compared with HA, SHS gave samples larger ΔE* values, indicating
more total colour variance. HA baked samples had no significant difference in ΔE* values
under different freezing temperatures, whereas significant lower ΔE* values was foundin samples frozen under -35 ℃ baked by SHS.
Table 3-11 ΔE* of samples baked by two different method
Freezing Temperature/℃

BakingSamplesmethod

-5

-15

-25

-35

-45

HA

4.6±2.1a,A

6.9±5.7a,A

5.9±3.0a,A

6.3±2.1a,A

8.8±3.9a,ASHS

8.1±2.5a,B 38.6±5.4b,B 41.4±5.2b,B 27.7±8.2c,B 35.6±8.2b,B

Crust

a,b,c:Means in the same column by the same lowercase superscript letters are not different(p<0.05)
A,B,C:Numbers followed by the same uppercase superscript letters in the same column have no difference(p<0.05)

53

3.3.5.

CIE Lab colour correlation with freezing temperature and baking time
Table 3-12 listed Pearson’ correlation coefficients for colour values from HA

baked sample crusts with freezing temperature and baking time. Only correlation
coefficients that had p values less than 0.01 were listed in the Table. It showed that a2,b2and ΔE* had positive correlations with baking time. No correlation was found between
freezing temperature and colour of samples in HA baked pizza crusts.
Table 3-12 Pearson product correlation coefficients of colour values at various freezing
rate and baking time (HA baked sample crusts)
Processing variables
Freezing temperature

Baking time

HA crusts
Correlation coefficient p values Correlation coefficient p values
Crust thickness
L2
a2

0.72

p < 0.01

b2

0.58

p < 0.01

ΔE*

0.41

p < 0.01

Only p values less than 0.01 correlations were listed

Table 3-13 listed Pearson’s correlation coefficients between colour values andfreezing temperature and baking time of SHS baked sample crusts. Freezing temperature
showed negative correlations with a, b and total colour variance values. Baking time had
negative correlation with L values, while positive correlations with a and total colour
variance values. Aside from these correlations, thickness of SHS baked samples crusts
was also found to have positive correlation with baking time.

54

Table 3-13 Pearson product correlation coefficients of colour values at various freezing
temperature and baking time (SHS baked sample crusts)
Processing variables
Freezing rate

Baking time

SHS crusts
Correlation coefficient p values Correlation coefficient p values
Crust thickness

0.47

p < 0.01

L2

-0.55

p < 0.01

0.47

p < 0.01

0.45

p < 0.01

a2

-0.63

p < 0.01

b2

-0.56

p < 0.01

ΔE*

-0.59

p < 0.01

Only p values less than 0.01 correlations were listed

3.4.

Rheological properties
In bar plots listed below, legends on x-axis describing each of the bars were named

as follows:
N: HA/No steam
S: SHS0, 1, 2, 3, 4 referred to the freezing temperature of specified samples in such an order: -5 ℃,-15 ℃, -25 ℃, -35 ℃, -45 ℃.
a,b,c: (HA baked samples) Means in samples by the same lowercase superscript letters are not different(p<0.05)
A,B,C: (SHS baked samples) Means in samples by the same lowercase superscript letters are not different(p<0.05)

3.4.1.

Creep test

Firstly, the effect of freezing temperature was checked on samples baked by both HA
and SHS. Analysis of Variance (ANOVA) test was run through R programming
language. Significant difference were found in delayed elasticity E1 in SHS baked55

sample crumbs and delayed viscosity V1 in sample crumbs in both baking methods, as
shown in Figure 3-7 and Figure 3-8.

Figure 3-7 Delayed elasticity E1 values of crumbs and crusts (1 day frozen samples)

56

Figure 3-8 Delayed elasticity V1 values of crumbs and crusts (1 day frozen samples)No significant difference were found in instantaneous elasticity E0 or permanentviscosity VN in sample crumbs or crusts in either baking method. More information was
listed in Appendix 1 (Figure A1-6).
Secondly, difference between samples baked by HA and SHS was checked
through Student t.test, as shown in the Appendix 1 (Table A1-1). From the significant
difference found, SHS baked sample crumbs showed less viscoelasticity than HA baked
samples crusts, whereas SHS baked samples crusts had larger viscoelasticity values than
HA baked samples crusts.
Also difference between samples crumbs and crusts was checked through Student
t.test in both baking methods, as shown in the Appendix 1 (Figure A1-2). From thesignificant difference found, in HA baked samples, crumbs had larger viscoelasticity thancrusts had; whereas in SHS baked samples, crumbs had less viscoelasticity than crusts
had.
57

3.4.2.

Fractural test
There was no breaking point found in fractural test curves in all samples, thus

instead of breaking force, maximum force was obtained from fractural test curves of all
samples (see Figure 2-18). There was no significant difference found in the recorded
maximum force in samples frozen under different freezing temperature, or samples baked
by HA or SHS. More information was listed in the Appendix 1 (Figure A1-8).
3.4.3.

TPA test
No significant difference was found in hardness, cohesiveness or gumminessvalues of samples frozen under different freezing temperature in either HA or SHS baking
method.
Also, no significant difference was found in the comparison in hardness,cohesiveness or gumminess of samples baked by the two baking methods. Detailed
information was shown in the Appendix 1 (Figure A1-9, Figure A1-10, Figure A1-11).

58

Chapter 4.

Discussion

4.1.

Freezing characteristics

4.1.1.

Freezing rate and assumption of ice crystallization
As the results shown in Table 3-1, the lower the freezing temperature, the higher

the freezing rate was. The freezing curve in Figure 3-1 showed clear freezing
characteristic of pizza dough, wherein latent heat and sensible heat should be taken into
account. Latent and sensible heat are types of energy released or absorbed in theatmosphere. Latent heat is related to changes in phase between liquids, gases, andsolids. Sensible heat is related to changes in temperature of a gas or object with no change
in phase.
In this research, lower freezing temperature caused more sensible heat between
freezing air and samples, thus the freezing curve went down more rapidly. Latent heat ofsamples frozen under lower temperature was removed faster, indicating a faster phasetransition or faster ice crystallization. According to research done by (Bevilacqua &Zaritzky, 1980), the size of ice crystals depends on the freezing rate. The faster thefreezing rate, the smaller size of ice crystals were detected.
Liquids inside pizza dough frozen by crystallization, formation of crystalline
solid from the uniform liquid. This was a first-order thermodynamic phase transition,
which meant that, as long as solid and liquid coexisted, the temperature of the wholesystem remained very nearly equal to the melting point due to slow removal of heat whenin contact with air, which was a poor heat conductor. Because of the latent heat of fusion,
the freezing was greatly slowed down and the temperature would not drop anymore once59the freezing starts but would continue dropping once it finished. Crystallization consistedof two major events, nucleation and crystal growth. Nucleation was the step wherein themolecules started to gather into clusters, on the nanometer scale, arranging in a definedand periodic manner that defined the crystal structure. The crystal growth was thesubsequent growth of the nuclei that succeeded in achieving the critical cluster size
4.1.2.

Moisture content after freezing
Significant difference was found in moisture content of samples frozen under

different temperature. Samples frozen under higher freezing temperature tended to had
lower water content. This was due to the removed moisture from samples to the air by therefrigeration coils. Moisture left the surface of the samples and produces areas of visible
damage known as freezer burn (Fellows, 1997). Picture was shown in the Appendix 2(Figure A2-1).
4.2.

Baking characteristics

4.2.1.

Initial condensation (SHS)
In weight loss curves of SHS baked samples, there was a rapid rise in the

beginning stage of baking, see Figure 3-4. This was called initial condensation and was
mentioned in many researches (Bourassa, Ramachandran, Paliwal, & Cenkowski, 2015)(Mujumdar & Devahastin , 2008) (Devente & Heijmans, 2001) (Pronyk, Cenkowski, &Muir, 2005). The initial condensation was very unique to SHS as a processing medium.
It occurred when a material at a temperature lower than the saturation temperature was
exposed to SHS. SHS coming in contact with the material then became cooled andcondensed on the material. The condensation was proved to have happened in thisresearch according to the sudden rise in the weight loss curves of SHS baked samples in60

Figure 3-4. Along with the increase of weight of samples, the momentary surface
moisture content might also have increased, as proved to have happened in potato samples
in research done by (Iyota, Nishimura, Yoshida, & Nomura, 2001). When the material
surface temperature increased to the saturation temperature, condensation period wasover and restoration period began. During restoration, the initial condensation evaporated
and the moisture content of the material returned to its origin, as shown in Figure 3-6.
4.2.2.

Temperature curves for heaters
Sudden drop in the temperature curves for heaters were detected in both baking

methods, as is shown in Figure 3-3 and 3-4. This was due to the open of oven led to an
abrupt colder air inside, which at once cooled down the surface of the heaters. However,this operation was unable to be omitted.
4.2.3.

The maximum inner temperature of samples during baking
From Figure 3-3 and Figure 3-4, all samples maximum inner temperature would

not transcend 100 ℃ in either baking method. This phenomenon was due to the highpercentage of moisture content inside samples. As shown in Table 3-2, the averagemoisture content in most samples were over 65%.
This result corresponded with many researches for bakery products such as (Lebail, et al., 2011) (Acar & Gokmen, 2009) (Mogol & Gokmen, 2014). During baking,inner temperature of samples rapidly rose to around 100 ℃ or near the boiling point ofwater according to the local atmospheric pressure and remained that temperature forcertain time.
4.2.4.

Thawing rate and baking time61

From the results shown in Table 3-5 and Table 3-7, thawing rate of HA baked
samples had positive correlation with freezing rate. Samples frozen under -45 ℃ had
significant higher thawing rate than samples frozen under -15 ℃. This might be due tothe more distinct sensible heat difference between -45 ℃ samples and the baking medium.
SHS baked samples did not have such correlations, significant higher thawing rate
was found in -35 ℃ frozen samples compared with -15 ℃ frozen samples. However, forsamples frozen under -45 ℃, the thawing rate was once again slower. The inaccurate
position where the thermocouple sensor was inserted might be the reason. Compared with
HA baked samples, it showed significant higher thawing rate in samples frozen under all
temperatures, this was due to higher heat transfer properties in SHS than in HA at same
temperature (Sehrawat, Nema, & Kaur, 2016). Initial condensation might also contributeto this result due to the condensation heat transfer which was confirmed in anotherresearch (Iyota, Nishimura, Yoshida, & Nomura, 2001). During the stage where SHS
condensed on the surface of samples, instead of air, condensed water played importantrole of heat transfer. In free convection, heat transfer coefficient of air is 5 to 25 [W/m2*k],whereas water would be up to 20 to 100 [W/m2*k] (Singh & Heldman, 2014). Sensible
heat transfer might have caused a faster thawing rate in this occasion.
In HA baked samples, lower freezing temperature frozen samples had longer
baking time, as shown in Table 3-4 and Figure 3-7. This is easy to understand because
lower temperature frozen samples had larger temperature difference before arriving at
100 ℃ and thus would generally take more time till fully baked. However, no suchcorrelation or significant difference was found in SHS baked samples. This result showeda more complicated baking method compared to its counterpart HA baking method, as62

also was indicated in (Asghar, Anjum, Butt, Tariq, & Hussain, 2007). Currently theknowledge and experience of SHS is still limited. On the other hand, in SHS baked
samples, thawing rate had negative correlation with baking time. This showed a moreconsistent baking temperature change compared with HA, i.e. samples had fastercompleted thawing had faster speed of reaching to 100 ℃.
4.2.5.

Drying rate
Nowadays SHS was still mainly used as drying medium, especially worked

effectively in turbines due to its superior large amount of energy and specialty of avoiding
droplets (Lalonde, accessed on 13th, June, 2016). The rate of evaporation of moisturepresent in a food material was given by Equation 4-1(4-1)
N: Evaporation rate [kg water m-2 h-1]
q: Heat transferred per unit area [Wm-2]
ʎ: Latent heat of evaporation of water [J kg-1]
h: Heat transfer coefficient [Wm-2]
Tsurface: Surface temperature of drying material [K]Tmedium: Superheated steam temperature [K]Due to initial condensation, more time was required to dry SHS baked sample (seeFigure 3-6). Although drying of the samples was slowed down by initial condensation,
final baked samples by SHS still showed drier outcomes than HA baked ones (see Table
3-6). This was due to air-free environment in SHS baking method. Water vapour had noresistance to diffuse in such an environment compared with HA baking environment

63

(Sehrawat, Nema, & Kaur, 2016). Also, as the surface reached the dew point temperature,steam accelerated the temperature rise and water loss, especially for a relatively long
baking time (Vanin, Lucas, & Trystram, 2009).
4.3.

Colour change
In SHS baked samples, L2 and a2 values were significantly lower in samples

frozen under -25 ℃, than samples frozen under -35 ℃, while a2 values was significantly
lower in samples frozen under -35 ℃. This was due to the longer baking time in samples
frozen under -25 ℃ and shorter baking time in samples frozen under -35 ℃. Same results
were given in sliced bread experiment (Jimenez, Vilanova, & Hernandez, 2001).
Compared with HA baked samples, SHS baked samples had significantly (p<0.05)
lower L values, while higher in a, b total colour variance values. This result indicatedaccelerated surface browning by the combined effect of Maillard reaction andcaramelisation (Kocadagli & Gokmen, 2016), between which the Maillard reaction took
more part in colouring than caramelisation did (Deman, 1990). Previous research had
found that the value of L2 decreased more quickly by SHS than HA in the baking processof sliced bread (Iyota, Sakai, & Mamiya, 2013)by using in-situ colour measurement.
Conventional baking process contained two main stages, namely 1) development
stage, 2) drying and colouring stage (Manley, 2000). In the development stage, doughtemperature began to increase, causing some physical changes in dough such as fat
melting, gluten softening and starch gelatinization. After certain level of thermal load,
both moisture and temperature conditions became favourable for browning reactions in
the latter stage. In drying and colouring stage, colour of samples crust was tanned through
Maillard reaction, which essentially took place in food products containing high levels of64sugar and protein or amino acids. The rate of the reaction is proportional to the heattreatment severity, particularly when a low water activity (Ames, Bates, & Mcdoulall,1993)was reached. The presence of melanoidins, brown nitrogen-containing highmolecular weight pigments, responded for the characteristic colour of roasted foods suchas coffee, cocoa, bread and malt. Melanoidins can also be formed by sugar caramelization
without participation of amino groups (Bastons, Monaro, SIguemoto, & Sefora, 2012).
In this research, baking temperature was controlled to be around 260 ℃ in either
baking method. Comparatively larger amount of moisture loss to crust of samples baked
by SHS might be the reason why the crust colour was more severely tanned.
The crust and crumb came from the same original dough, but their final properties
differed according to a distinct local heat-moisture treatment. As soon as the dough wasplaced inside the oven, water evaporated from the warmer region, absorbing latent heatof vaporisation and the surface layers started drying, resulting in a much lower watercontent than at the centre part (Vanin, Lucas, & Trystram, 2009). Beneath this drying
region, water vapour diffused through the interconnected pores towards the surface. A
concomitant liquid water gradient was formed from the core to the surface. As the
diffusive flow of liquid water from the core was less rapid than evaporation flow at thesurface, a drying zone was developed that slowly increased in thickness and formed thecrust (Wagner, Lucas, Ray, & Trystram, 2007). Compared with crumb, the heating rateof crust was higher (see Appendix 1, Figure A1-3). Also, the addition of steam reduced
the water loss at the onset of baking, as shown in Figure 3-6. However, as the surface
reached the dew point temperature, steam accelerated temperature rise and water loss for65

long baking time, which differentiated with HA baked crust, showing a more tanned
colour.

Figure 4-1 3D plot colour distribution of samples baked by HA and SHS
Figure 4-1 and Figure 4-2 gave the intuitive vision of the appearance comparisonof crust colour between HA and SHS baked samples. L, a and b values of samples baked
SHS are apparently distributed in a wider range in the colour space, indicating larger total
colour change (ΔE*) values with darker, yellower and redder outcomes, even withincomparatively shorter baking time.

66

Figure 4-2 Appearance of samples baked by HA and SHS

67

4.4.

Rheological properties

4.4.1.

Creep test

4.4.1.1.

Effect of freezing rate in either baking method

Different freezing rate did not have significant effect on viscoelastic properties ofsamples.
Although significant difference was found in delayed elasticity E1 in SHS baked crumbs
and delayed viscosity V1 in crumbs of samples in both baking methods, as shown in
Figure 3-9 and Figure 3-10, baking time seemed to have more influence on thisconsequence instead of freezing rate. Samples frozen under -45 ℃ and -25 ℃ tookapproximately same longer baking time compared with samples frozen under -15 ℃,
which led to the significant lower viscoelastic properties. This result was also true in V1
values of HA baked sample crumbs, in which samples frozen under -45 ℃ took significant
longer baking time and thus rendered significant lower V1 values compared with samples
frozen under -15 ℃. On the other hand, compared with samples frozen under -15 ℃,
samples frozen under -35 ℃ which had similar baking time, showed no significant
difference in all four-element viscoelastic parameters. It further proved the conclusionthat compared with baking time, freezing rate did not seem to cause significant differencein creep test results.
4.4.1.2.

Assumptions

In viscoelasticity comparison between HA and SHS, all significant difference
found was in samples baked within a shorter baking time (8.6±1.7 min, 8.4±0.6 min).
This result shorter baking time, more difference in rheological properties between the two
medium baked samples. This results corresponded with the other research results reported68

by (Head, Cenkowski, Arntfield, & Henderson, 2010) that colour of oat processed withSHS changed significantly (p<0.05) during the initial exposure to SHS, but no majorchanges in the colour of oat groats were noted after about 1 min of SHS processing. It
would be valid to assume that the initial condensation might have been the mostinfluential factor behind these outcomes.
According to the significant difference, compared with HA baked samples, SHS
baked samples were found to have lower delayed elasticity, lower delayed viscosity andlower permanent viscosity values in crumbs, whereas had higher instantaneous elasticity
and higher delayed viscosity values in crusts. On the other hand, in HA baked samples,
crumbs tended to be more viscoelastic than crusts whereas this result did not agree withSHS baked samples, in which crusts showed more viscoelastic behaviour than crumbs.
Starch gelatinisation might have great influence on these outcomes. The degree ofgelatinisation (DSG) was shown to be directly affected by water (Burt & Russell, 1983),(Le-Meste, Huang, Panama, Anderson, & Lentz, 1992) (Jenkins & Donal, 1998) (Fessas& Schiraldi, 2000) (Cup, Abecassis, & Guilbert, 2003) and the heating rate (Donavan,1979) (Bloksma, 1980), which again differentiated crumb and crust in one baked sample.
As shown in the Appendix 1 (Figure A1-11), according to previous studies, the distinct
higher heating rate in crust layer than in crumb even under different baking temperatures,
as well as a much higher water loss rate, both of which contributed to the postpone of
starch gelatinisation happening in crust layer. This might favour low level ofviscoelasticity (Vanin, Lucas, & Trystram, 2009).
However, the introduction of initial condensation which not only delayed thedrying rate but on the contrary increased crust layer moisture content, both of which might69

have favoured starch gelatinisation on the surface of baked samples and thus gave an
increase in viscoelasticity in crusts. Depending on the porosity of the material thecondensed moisture has the ability to permeate into the interior of the material (Bourassa,
Ramachandran, Paliwal, & Cenkowski, 2015). Another study done by (Iyota, Nishimura,
Yoshida, & Nomura, 2001) reported there was slight moisture increase in the surface ofpotato shortly after the start of baking, other researches also had shown small amounts ofmoisture increase in the first few seconds of processing in superheated steam due to theinitial condensation in sugar-beet, pulp, potatoes, Asian noodles, brewer and distiller’s
grain (Pronyk, Cenkowski, Eng., & Muir, 2004). Although after the temperature of doughsurface reached up to the dew point, drying rate was accelerated and rendered a dryer
outer layer than inside, water redistribution from crumb to crust might be the main reason
that humidified the crust whereas dried the crumb. In the research done by (Baik &Chinachoti, 2000), they detected the result that during storage, bread crumb moisture
content and water activity decreased significantly when stored with crust, whereas whenstored without crust, the water content and water activity remained relatively unchanged.
On the other hand, case hardening might also contribute to the water redistribution
from crumb to crust in SHS baked samples. Case-hardening is particularly common withfoods that contain dissolved sugars and other solutes in high concentration, as pointed outby (Potter & Hotchkiss, 2012). It occurs when there is high surface temperature andunbalanced drying of the piece so that a dry skin forms quickly before most of the internalmoisture has had opportunity to migrate to the surface.
Case hardening may cause sealing of the surface of food. This can be explained
from various ways water may escape from a product during drying period. Some of the70

water moves via cell walls or through membranes by molecular diffusion. Again, water
may be heated to vapour within a food piece and escape as water vapour molecules freeof solute. Water in foods rises in the voids, cracks and pores of various diameters down
to minute capillary size from inside to food surface. Capillary water carries sugars, salts
and other materials in solution to the surface of food during dehydration. Then at thesurface, water is evaporated and the solutes are deposited, which elevated the osmaticpressure in the upper layer of samples, accelerated the water transportation from inside tooutside. Although in this research, the exact moisture content in crust of samples was notmeasured, extremely dried and hardened surface layer of samples baked by SHS was
obtained immediately after baking completed, whereas after cooling was finished, thesurface regained viscoelasticity and tenderness. Another point which differentiated HAand SHS baked samples is the crus thickness (see Appendix 1, Figure A1-4). Comparedwith HA baked samples, SHS baked samples had thicker crusts formed during baking due
to the higher drying speed the outer layer of samples, which separated the crumb and crust,
substantially contributed to the organoleptic perception of the final product. Significant
thicker crust bake by SHS compared with HA were found to be those under longer baking
time.
4.4.2.

Fractural test
No breaking point was found in crumbs or crusts in samples in either baking

method. Instead of breaking force which should have been measured at the exact breaking
point, maximum force was obtained from all samples in this test and there showed nosignificant difference within all comparisons. This might indicate that the samples in thisresearch were not s for performing fractural test.

71

4.4.3.

TPA test
According to the results of parameters selected in this research, hardness,cohesiveness or gumminess were not found to have significant difference in thecomparison in different freezing rate or comparison between two baking methods incrumbs of samples. Due to the difficulty to conduct TPA test on crusts, comparison
between crumbs and crusts in both baking methods were not available to discuss in thisresearch. However, based on the cross-correlation plot in the Appendix 1(Figure A1-5,
Figure A1-6, Figure A1-7, Figure A1-8) in both HA and crumbs of SHS baked samples,
hardness values had positive correlation coefficient (p<0.01) with all viscoelastic
parameters values. Thus an assumption that the TPA test results might show the same inthe comparison between crumbs and crusts of HA and SHS baked sample is given. Further
research is necessary toward this assumption.

72

Chapter 5.
5.1.

Conclusion and future work

Freezing characteristics
Freezing rate was higher in samples frozen under lower freezing temperatures.

Large temperature difference might have favoured the faster speed for removing latent
heat during phase transition, in which ice crystal formed. Different exposure time to thefreezing air during freezing caused a moisture difference in frozen samples.
5.2.

Baking characteristics
Initial condensation had been a unique phenomenon in SHS baking, a weightincrease proved this phenomenon in this research. During baking, inner temperature insamples did not transcend 100 ℃ due to the phase transition.
Compared with HA baked samples, samples baked by SHS showed significant
higher thawing rate in samples frozen under all temperatures, this was due to higher heattransfer properties in SHS than in HA at same temperature. Initial condensation mightalso contribute to this result.
Some apparent correlation was found in HA baked samples such as the longer the
lower the freezing temperature, the longer the baking time. However, this did not work
the same in SHS baked samples, revealing a more complicated baking method comparedwith HA. The knowledge and experience in SHS is still limited.
Although the results for drying rate of samples were not obtained over three times
in this research, according to the existing outcome, compared with HA baked samples,
SHS baked sampled showed moisture content loss. This might be due to the higher heat73

transfer rate and easier diffusion environment for water vapour in SHS filled oven. Also,
initial condensation might also have influence on this outcome.
5.3.

ColourCompared with HA, SHS baked samples had lower L values, larger a, b and total

colour variance ΔE* values, indicating darker, yellower and redder outcomes. Colour
significant difference between HA and SHS was found in samples frozen under all
freezing temperature. On the other hand, different freezing temperature did not havesignificant influence on crust colour of baked samples by either baking method.
From Pearson’s correlation coefficient results, in SHS baking method, samples
frozen under higher freezing temperature had yellower and redder crust colour and moretotal colour variance. The longer the baking time, the darker and yellower crust colour it
would be and thus more total colour variance. Also longer baking time gave SHS baked
samples thicker crust.
5.4.

Rheological properties
Compared with baking time, freezing rate did not seem to cause significant

difference in creep test results. In viscoelasticity comparison between HA and SHS, allsignificant difference found was in samples baked within a shorter baking time (8.6±1.7min, 8.4±0.6 min). On the other hand, in HA baked samples, crumbs tended to be moreviscoelastic than crusts whereas in SHS baked samples, crusts showed more viscoelastic
behaviour than crumbs. A combined effect of starch gelatinisation, initial condensation,
crust thickness and water redistribution from crumb to crust which might have been74

caused by case hardening during the cooling down period might have contributed to thisresult.
In fractural tests, no breaking point was found in crumbs or crusts of samples ineither baking method. Instead of breaking force which should have been measured at theexact breaking point, maximum force was obtained from all samples in this test and there
showed no significant difference within all comparisons. This might indicate that the
samples in this research were not suitable for performing fractural test.
TPA test was only conducted on crumbs of samples due to its difficulty to conduct
on the thin crust layer. No difference was found in comparison between samples that werefrozen under different temperature, nor in comparison between HA and SHS baked
crumbs of samples. However, due to the apparent cross-correlation coefficient between
TPA test results and creep test results in crumbs in either baking method, it was assumed
that hardness and gumminess might also show a positive correlation, while cohesivenessa negative correlation with viscoelastic properties of crusts.
5.5.

Super cooled samples
Although the freezing temperature was the lowest (-5 ℃) of all in this research,super cooling rendered the batch of samples highest freezing rate and possibly small andhomogenous fine ice crystals, which differed these samples significantly different fromsamples those were frozen under high freezing temperature, especially in rheologicalproperties. Micro-structure of samples frozen under -5 ℃ should be the reason why they
were differentiated in this research from other samples. Further observation of thesemicro-structure is necessary.

75

5.6.

An overall wrap up of the conclusion
Compared with HA baked samples, SHS baked samples showed higher thawing

rate, less baking time and higher drying rate; SHS baked samples had darker, yellower
and redder crust colour; SHS baked samples were more viscoelastic in crusts, than in
crumbs. Fractural test might not be suitable for measuring the samples in this research.
TPA test results of samples crumbs including hardness, cohesiveness and gumminesswere not found to be significantly affected by using different baking method.
Initial condensation, drying rate especially at the top layer of pizza crusts crust
thickness and water redistribution from crumbs to crusts might have played the mostimportant roles which differentiated HA and SHS baked products. Different freezing
temperature from -15 ℃ till -45 ℃ did not seem to produce different outcomes in colour
or rheological properties of frozen pizza, except for thawing rate due to the temperature
difference between frozen pizza dough and baking medium.
5.7.

Future work

1. In this research, using SHS as the baking medium conferred higher thawing rate,
less baking time and higher drying rate on frozen pizza dough. SHS was used fromthe starting point of baking till baking completed. It is also important to know the
optimum steaming time, velocity and pressure of steam for finding out the
optimization SHS utilization on frozen pizza processing in further studies.
2. As was noted in the introduction part in this research, SHS had advantages likelower energy consumption, sterilization and so on. Further studies should also be
focusing on calculating the energy cost and saved in SHS system and observationsof the elimination of microorganisms.
76

3. More investigations should be taken to examine the sensory score of products
baked by SHS, in both consumers panel and experts panel. A thin layer of tomato
source toppings can be used, but note to not cover the original flavour of the crust(Delahaye, Jimenez, & Perez, 2005). Industrial survey in pizza processing
factories, pizzerias, delivery-shops should be conducted to get more attitude andideas on the feasibility of spreading SHS as a frozen pizza processing medium. It
is significant to link instrumental measurement results with sensory evaluations
scores in order to decide the pros and cons of utilization of SHS as a baking
medium on frozen pizza products.
4. In order to capture the baking characteristics of frozen samples under different
freezing conditions, samples in this research did not undergo enough fermentation
except for a short time pre-proofing before freezing. Considering the capability ofeliminating the microbial inside the samples by SHS, it is assumed that SHS baked
frozen samples might have lower extent of oven spring compared with HA baked
samples. Further studies is necessary to confirm this assumption and theassociated impact.
5. Due to the availability, frozen samples had to experience a further cooling process
by dry ice during transportation from Mayekawa Manufacturing Company till the
University of Tokyo. The effect of dry ice on samples remains unknown.
Extremely low temperature is detrimental to the vitality of yeast cells and ovenspring might be negatively affected.
6. More accurate method for inserting thermocouples inside the samples formeasuring the inner temperature during baking, should be developed in further
studies.

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88Appendix 1. Supplemental Tables and Figures

Figure A1- 1 -5℃ sample freezing curve of upper, center and lower layers

89Figure A1- 2 -15℃ sample freezing curve of upper, center and lower layers

Figure A1- 3 -25℃ sample freezing curve of upper, center and lower layers

90

Figure A1- 4 -35℃ sample freezing curve of upper, center and lower layers

Figure A1- 5 -45℃ sample freezing curve of upper, centre and lower layers

91Viscoelastic properties
In bar plots listed below, legends on x-axis describing each of the bars were named asfollows:
N: HA/No steam
S: SHS0, 1, 2, 3, 4 referred to the freezing temperature of specified samples in such an order: -5 ℃,-15 ℃, -25 ℃, -35 ℃, -45 ℃.
a,b,c (HA baked): Means in samples by same baking method by the same lowercase superscript letters are not different (p<0.05)
A, B, C (SHS baked): Means in samples by same baking method by the same lowercase superscript letters are not different (p<0.05)

Figure A1- 6 Instantaneous elasticity E0 values of crumbs and crusts (1 day frozen
samples)92

Figure A1- 7 Permanent viscosity VN values of crumbs and crusts (1 day frozen
samples)Figure A1- 8 Breaking force values of crumbs and crusts (1 day frozen samples)93

Figure A1- 9 Hardness values of crumbs (1 day frozen samples)

Figure A1- 10 Cohesiveness values of crumbs (1 day frozen samples)94Figure A1- 11 Gumminess values of crumbs (1 day frozen samples)

Table A1- 1 Comparison of baked sample properties between HA and SHS baked
samples (1 day frozen)
Freezing Temperature/℃

Instrumental
Samples
data

-5

-15

-25

-35

-45

Crumb

***

0.99

0.19

0.1

0.49

Crust

0.29

0.16

0.9

*

0.4

Crumb

***

0.09

0.08

*

*

Crust

0.13

0.73

0.87

0.43

0.36

E0

E1

95

Crumb

***

0.07

0.08

*

0.07

Crust

*

*

0.8

0.36

0.32

Crumb

***

*

0.1

*

0.16

Crust

*

0.78

0.23

0.29

0.45

Hardness

Crumb

***

0.19

0.29

0.87

0.34

Cohesiveness

Crumb

**

0.14

0.08

0.54

0.07

Gumminess

Crumb

*

0.46

0.49

0.89

0.76

Crust thickness

crust

0.247

0.4

***

0.24

*

L2

crust

**

***

***

***

***

a2

crust

**

***

***

***

***

b2

crust

**

***

***

***

***

ΔE*

crust

**

***

***

***

***

V1

VN

*,** and ***: Significant difference at p<0.05,p<0.01 and p<0.001 level, respectively

96

Table A1- 2 Comparison of baked sample properties between crumbs and crusts (1 day
frozen)Freezing Temperature/℃
Samples

Baking method
-5

-15

-25

-35

-45

HA

0.83

0.36

0.12

0.94

0.17

SHS

0.1

0.34

0.06

**

**

HA

*

0.74

**

**

0.1

SHS

0.08

0.36

0.41

0.7

0.19

HA

***

***

**

**

0.11

SHS

**

0.63

0.41

0.68

0.2

HA

0.18

0.13

0.56

**

0.38

SHS

0.28

0.57

0.68

0.48

0.18

E0

E1

V1

VN

*,** and ***: Significant difference at p<0.05,p<0.01 and p<0.001 level, respectively

97

Table A1- 3 Heating rates for different cereal products and baking conditions at bread surface and core (reviewed by (Vanin,
Lucas, & Trystram, 2009))

Product

Bread

Mass ofSurfaces

Position ofOven airHeating

dough/batter

exposedtemperaturetemperature

rate

(g)

to heatin(°C)(°C/min)transferdough/batterTop

Top surface

185

7.7

200

bottomReference(Wagner et al.,2008a and Wagner

Bottom2.6
et al., 2008b)

surface

Centre

Bread

341

All

Top surface

2.4

203

11.3

(Zanoni et al.,
1993)

Bottom9.5

surface at
1 cm
beneathThe top

2.6

surface

Bread

–

All

Top surface

210

10.3*

(Thorvaldsson, &Skjöldebrand,

Mid-width

3.9*
1996)

Centre

Pan

–

–

–

–

Surface

1.8*

220

8.8

bread

Francala

14.4

98(Dogan, 2002)

Product

Bread

Mass ofSurfaces

Position ofOven airHeating

dough/batter

exposedtemperaturetemperature

rate

(g)

to heatin(°C)(°C/min)transferdough/batterAll

Top surface

225

6.7

1.5 L

Reference(Thorvaldsson, &Skjöldebrand,

Bottom4.4
1998)

surface

Bread

760

All

Side

235

7.4

Wannan, 1976)

surface

Centre–BiscuitAll

Centre(Marston &

2.8

300

75.0**(Chevallier et al.,(400 g/kg

2002)

dry air)300

61.7**(20 g/kg
dry air)240

44.7**(200 g/kg
dry air)180

19.6**(20 g/kg
dry air)

Sponge400–600

Top

Top surface

cake

200

0.5

(Lostie et al.,
2002)“–” Refers to missing information. *Data from reheated samples. **With different relative air humidity. Bold and italic values
emphasizes high surfaces values.

99Table A1- 4 Sample crust thickness (after baking, 1 day frozen)
Freezing Temperature/℃
Samples
-5
HA

-15

-25

1.6±0.2a,A 1.8±0.2a,A 1.8±0.2a,A

-35

-45

1.8±0.5a,A

1.9±0.4a,A

Crust
SHS 1.5±0.3d,A 2.0±0.3c,A 2.5±0.4b,B 2.1±0.3ac,A 2.4±0.3ab,B
a,b,c:Means in the same column by the same lowercase superscript letters are not different(p<0.05)
A,B,C:Numbers followed by the same uppercase superscript letters in the same column have no difference(p<0.05)

100Table A1- 5 Cross- correlation coefficient (1 day frozen, HA baked crumbs)

101

Table A1- 6 Cross- correlation coefficient (1 day frozen, SHS baked crumbs)

102

Table A1- 7 Cross- correlation coefficient (1 day frozen, HA baked crusts)

103

Table A1- 8 Cross- correlation coefficient (1 day frozen, SHS baked crusts)

104

Appendix 2. Additional tests (prolonged frozen
storage)
Aside from samples frozen for 1 day, there were also trials on longer frozen
storage from 15 days, 25 days till 35 days, each of which contained one sample. The
research materials, methods and steps followed exactly the same with former research
and were explained in Chapter 2.2.4.
Appendix 2.1. Moisture content after frozen storage
Longer frozen storage till 35 days did not give samples significant difference inmoisture content, whereas samples frozen under -5 ℃ over 15 days gave significant(p<0.05)moisture content difference (49.3±1.1) from 1 day frozen samples (64.7±0.4). It
indicated samples frozen under -5 ℃ over 15 days were very much dried, even close to
the extent of fully dried samples moisture content (44.2±0.6).
Table A2- 1 Moisture content of raw samples after different lengths of frozen storage
Freezing Temperature/℃

Frozen storage duration/days
1

15

25

35

-5

64.7±0.4c,A49.3±1.1c,B

NA

NA

-15

68.1±0.8a,A 69.1±0.6ab,A67.8±0.6a,A

68.1±0.2c,A-25

68.5±0.1a,A

68.1±0.6b,A68.3±0.7a,A

69.2±0.2a,A-35

70.0±0.4b,A70.1±0.3a,A

69.1±0.4ab,A 70.0±0.2ab,A-4571.1±0.5d,A70.5±0.3a,A70.8±0.3b,A71.0±0.9b,Aa,b,c:Means in the same column by the same lowercase superscript letters are not different(p<0.05)
A,B,C:Numbers followed by the same uppercase superscript letters in the same row have no difference(p<0.05)

105Freezer burn was observed in sample frozen under-5 ℃ for 15 days frozen storage.
Due to overlarge amount of moisture left the sample, visible damage was produced on
the surface of sample, as shown in Figure A2-1. The serious wrinkled crust surface
indicated the dried condition of the crust.
The extreme dried condition of samples frozen under -5 ℃ for 15 days frozen
storage could be attributed to the freeze-thaw cycle that drew water out of the gluten
matrix. Internal damage to starch granules due to ice recrystallization was noted duringfrozen storage and freeze-thaw cycles (Berglund, Shelton, & Freeman, 1991). Starch thatwas physically damaged would allow penetration of water into cracks or fractures on thesurface or outer edge of the granule. (Tipples, 1969) found that damaged starch caused alinear increase in water absorption by flour since the damaged starch acts like a spongein the presence of water. Increased damage to starch granules may be the reason to explain
the water redistribution.
As more water was drew from the gluten matrix, the water was apparently
concentrated in large pools recognised as ice. Subliming of the ice is the reason whichcaused the overlarge moisture loss.

106

Figure A2- 1 Freezer burnt sample (-5 ℃, 15 days frozen)

Appendix 2.2. Rheological properties analysis
In bar plots listed below, legends on x-axis describing each of the bars were named asfollows:
A, B, C, D refers to the days of frozen storage for specified samples in the following order: 1 day, 15 days, 25 days and 35 days.
N: HA/No steam
S: SHS0, 1, 2, 3, 4 refers to the freezing temperature for specified samples in the following order: -5 ℃,-15 ℃, -25 ℃, -35 ℃ and -45 ℃.

Appendix 2.3. Creep test
Creep test values for crumbs and crusts were shown in Figure A2-2, Figure A23, Figure A2-4 and Figure A2-5, respectively.
Negative correlation was found between viscoelastic properties and baking time
(p<0.01) in crumbs. Frozen storage was not found to have significant correlations withviscoelasticity in samples. However, almost all significant difference were found withinsamples that were frozen under comparatively higher freezing rate, in either baking
method. This might be deterioration in samples after prolonged frozen storage. As
indicated by (Berglund, Shelton, & Freeman, 1991) (Varriano-Marston, Hse, & Mahdj,

107

1980). Faster freezing rates could have yielded some deterioration of the dough matrix
by ice recrystallization and therefore altered the rheological and gas-retaining propertiesof gluten network, which directly was related with the viscoelastic properties.
Viscoelastic properties of crusts (35 days frozen) showed significant higher
values, whereas no such difference was observed in HA baked sample crusts. Ice
recrystallization, water redistribution from crumb to crust and case hardening might be
the reason. During prolonged frozen storage, ice crystal melted and reformed, with theaddition of water drew from gluten network, the total moisture redistribution from crumb
to crust during cooling process caused the higher viscoelasticity in crust while lower
viscoelasticity in crumb.
Likewise, individual difference should be considered because in additional studies,
baked samples were not triplicated.

108

Figure A2- 2 Crumbs and crusts E0 values baking by HA and SHS under various
freezing treatments

109

Figure A2- 3 Crumbs and crusts E1 values baking by HA and SHS under various
freezing treatments

Figure A2- 4 Crumbs and crusts V1 values baking by HA and SHS under various
freezing treatments

110

Figure A2- 5 Crumbs and crusts VN values baking by HA and SHS under various
freezing treatments

Figure A2- 6 Crumbs and crusts breaking force values baking by HA and SHS undervarious freezing treatments

111

Almost no significant difference was found under various treatments, except for
samples frozen under -5 ℃, 15 days frozen storage, as shown in Figure A2-6. Breaking
points were found in both crumbs and crusts in either baking method, which gave thedistinctly lower breaking force compared with others, see Figure A2-7.
A crispy texture is associated with low moisture content and water activity, whenstarch and gluten matrix are in a glassy state making cells walls more prone to fracture(Stroke & Donald, 2000). This result further proved that fractural test might not be an
appropriate way on testing pizza dough due to the wet condition of samples in theprevious research, since only samples that were in a near fully dried condition weredetected with breaking points.

Figure A2- 7 Fractural curve comparison (samples frozen under -5 ℃, 1 day and 15
days frozen, SHS baked)
Appendix 2.4. TPA test (hardness)
Significantly (p<0.05) increased hardness in sample crumbs was found in samples
frozen under higher freezing rates (-35 ℃ and -45 ℃) during prolonged frozen storage, ineither baking method, as shown in Figure A2-8. The increase of dough hardness alongwith prolonged frozen storage was also found in other researches (Salas-Mellado &Chang, 2003) (Yi & Kerr, 2009) (Berglund, Shelton, & Freeman, 1991). Amylose

112

recrystallization plays an important role in the initial crumb hardness and in the firststages of staling (Hug-Iten, Escher, & Conde-Petit, 2003) (Barcenas & Rosell, 2006).
Microscopic studies showed that there is a phase separation between amylose andamylopectin during baking, which leads to an accumulation of amylose inside the starch
granules (Hug-Iten, Handschin, Conde-petit, & Escher, 1999). Along with prolonged
frozen storage, ice crystallization causes damage to the starch granule, which allows theleaching of intracellular amylose, increasing the interaction between the intra- and intergranular amylose and the formation of a network of amylose that increases crumb
hardness. Almost no significant difference found in the hardness comparison between HA
and SHS baked samples.

Figure A2- 8 Crumbs and crusts hardness values baking by HA and SHS under various
freezing treatments
Appendix 2.5. Assumption from additional studies

113

Similar results were obtained in the additional studies with some previous
researches. Along with prolonged frozen duration, samples frozen under higher freezing
rates seemed to have increased viscoelasticity especially in the sample crusts baked by
SHS. Combined effect of ice recrystallization, case hardening and water redistribution
might be the reason that differentiate the two baking methods. Fractural test might not beappropriate for the analysis of samples at the breaking point for the materials used in thisresearch. Hardness of samples increased with longer frozen storage. Using SHS did not
make significant difference on the hardness of samples compared with HA method.

114

Appendix 3. Samples frozen under -5 ℃ (in which
super cooling happened)
Samples frozen under -5 ℃ were discussed separately because super coolingphenomenon was observed.
Appendix 3.1. Freezing rate
As shown in Table 3-1, samples frozen under -5 ℃ was found to have the highest
freezing rate compared with other groups of samples. In spite of the second law ofthermodynamics, crystallization of pure liquids usually begins at a lower temperature thanthe melting point, due to high activation energy of homogeneous nucleation. The creationof a nucleus implies the formation of an interface at the boundaries of the new phase.
Some energy is expended to form this interface, based on the surface energy of each phase.
If a hypothetical nucleus is too small, the energy that would be released by forming its
volume is not enough to create its surface, and nucleation does not proceed. Freezing does
not start until the temperature is low enough to provide enough energy to form stable
nuclei. In presence of irregularities on the surface of the containing vessel, solid or
gaseous impurities, pre-formed solid crystals, or other nucleators, heterogeneous
nucleation may occur, where some energy is released by the partial destruction of theprevious interface, raising the super cooling point to be near or equal to the melting point.
The melting point of water at 1 atmosphere of pressure is very close to 0 °C (32 °F,
273.15 K), and in the presence of nucleating substances the freezing point of water isclose to the melting point, but in the absence of nucleators water can super cool to −40 °C(−40 °F, 233 K) before freezing (Lundheim, 2002) (Franks, 2003).

115

Appendix 3.2. Moisture content after freezing
Samples frozen under -5 ℃ had the lowest moisture content (64.7±0.4%)
compared with other groups of samples, as shown in Table 3-2. This was due to the longer
total freezing time than groups of samples.
Appendix 3.3. Thawing rate and baking timeThawing rate and baking time were both significantly lower or less than samples
frozen under -45 ℃. This indicated that the difference in starting temperature or thedifference in sensible heat the baking period contributed more than different freezing rate.
Appendix 3.4. Drying rate
Although weight loss of samples before and after baking was not measured overthree times, based on the results, it is still assumed that less baking time caused the lower
drying rate of samples frozen under -5 ℃.
Appendix 3.5. Colour results
In spite of less baking time, HA baked samples showed no significant differencein L, a, b values compared with other groups of samples. However, in SHS baked
samples, the comparatively baking time must have conferred more influence on
samples colour values because samples frozen under -5 ℃ were less browned comparedwith other groups of samples (see Table 3-9, Table 3-10, Table 3-11 and Table 3-12).
The severity of Maillard reaction could be considered to be much more in SHS
environment than in HA.

116

Appendix 3.6. Rheological tests results
In either baking method, crumbs and crusts of samples frozen under -5 ℃ showedalmost no significant difference in viscoelasticity with samples frozen under -35 ℃ or 45 ℃, whereas significant difference was found within the comparison between supercooled samples and samples frozen under -15 ℃.
This results suggested that rheological properties for super cooled samples weresimilar to those frozen under conventionally lower freezing temperatures. This might bedue to their comparatively similar microstructure or ice crystal size (Kobayashi,
Kimizuka, & Watanabe, 2015).
No significant difference was found in fractural test or TPA test between supercooled samples and other groups of samples.
Appendix 3.7. Conclusion
Although the freezing temperature was lowest (-5 ℃) of all in this research, supercooling rendered the batch of samples highest freezing rate and possibly small andhomogenous fine ice crystals, which differed these samples significantly different fromsamples those were frozen under high freezing temperature, especially in rheologicalproperties. Micro-structure of samples frozen under -5 ℃ should be the reason why they
were differentiated in this research from other samples. Further observation of thesemicro-structure is necessary.

117

Appendix 4. R programming code examples
Appendix 4.1. Personal defined settings
N: HA/No steam
S: SHS5, 15, 25, 35, 45: Specified samples frozen under -5, -15, -25, -35, -45 ℃, respectively
Crumb: Crumbs of samples
A: Data analysis

Appendix 4.2. 1 day samples ANOVA and TukeyHSD tests codes (comparison examplesof CIE Lab L values, samples frozen under difference freezing rate)
setwd("C:/Users/LINGKE/Desktop/R/Research/1 day samples")N5crumb1 <- read.csv("N5crumb1A.csv")
N15crumb1 <- read.csv("N15crumb1A.csv")
N25crumb1 <- read.csv("N25crumb1A.csv")
N35crumb1 <- read.csv("N35crumb1A.csv")
N45crumb1 <- read.csv("N45crumb1A.csv")
S5crumb1 <- read.csv("S5crumb1A.csv")
S15crumb1 <- read.csv("S15crumb1A.csv")
S25crumb1 <- read.csv("S25crumb1A.csv")
S35crumb1 <- read.csv("S35crumb1A.csv")
S45crumb1 <- read.csv("S45crumb1A.csv")
N5crumb1.L <- N5crumb1$L
N15crumb1.L <- N15crumb1$L
N25crumb1.L <- N25crumb1$L
N35crumb1.L <- N35crumb1$L
N45crumb1.L <- N45crumb1$L118

S5crumb1.L <- S5crumb1$L
S15crumb1.L <- S15crumb1$L
S25crumb1.L <- S25crumb1$L
S35crumb1.L <- S35crumb1$L
S45crumb1.L <- S45crumb1$L
df.Ncrumb.L<data.frame(N5crumb1.L,N15crumb1.L,N25crumb1.L,N35crumb1.L,N45crumb1.L)
df.Ncrumb.L <- stack(df.Ncrumb.L)
Anova.Ncrumb.L <- aov(df.Ncrumb.L$values~df.Ncrumb.L$ind)
summary(Anova.Ncrumb.L)
TukeyHSD(Anova.Ncrumb.L)
df.Scrumb.L<data.frame(S5crumb1.L,S15crumb1.L,S25crumb1.L,S35crumb1.L,S45crumb1.L)
df.Scrumb.L <- stack(df.Scrumb.L)
Anova.Scrumb.L <- aov(df.Scrumb.L$values~df.Scrumb.L$ind)
summary(Anova.Scrumb.L)
TukeyHSD(Anova.Scrumb.L)

Appendix 4.3. 1 day frozen samples Student t test (comparison examples between
samples by HA and SHS)
119

t.test(N5crumb1.L,S5crumb1.L)t.test(N15crumb1.L,S15crumb1.L)t.test(N25crumb1.L,S25crumb1.L)t.test(N35crumb1.L,S35crumb1.L)t.test(N45crumb1.L,S45crumb1.L)
Appendix 4.4. 1 day samples cross-correlation (package “corrplot” required)setwd("C:/Users/LINGKE/Desktop/R/Research/1 day samples")require(corrplot)
Ncrumb.correlation.coefficient <- read.csv("1 day HA crumb.csv")
Ncrust.correlation.coefficient <- read.csv("1 day HA crust.csv")
Scrumb.correlation.coefficient <- read.csv("1 day SHS crumb.csv")
Scrust.correlation.coefficient <- read.csv("1 day SHS crust.csv")
cor.mtest <- function(mat, conf.level = 0.95){
mat <- as.matrix(mat)n <- ncol(mat)p.mat <- lowCI.mat <- uppCI.mat <- matrix(NA, n, n)diag(p.mat) <- 0diag(lowCI.mat) <- diag(uppCI.mat) <- 1
for(i in 1:(n-1)){
for(j in (i+1):n){tmp <- cor.test(mat[,i], mat[,j], conf.level = conf.level)p.mat[i,j] <- p.mat[j,i] <- tmp$p.value
lowCI.mat[i,j] <- lowCI.mat[j,i] <- tmp$conf.int[1]uppCI.mat[i,j] <- uppCI.mat[j,i] <- tmp$conf.int[2]}}return(list(p.mat, lowCI.mat, uppCI.mat))}120

res1 <- cor.mtest(Ncrumb.correlation.coefficient,0.95)
res2 <- cor.mtest(Ncrumb.correlation.coefficient,0.99)
p.Ncrumb.correlation.coefficient <- cor(Ncrumb.correlation.coefficient)
corrplot(p.Ncrumb.correlation.coefficient,addrect = 2,title = "Ncrumb coefficientcorrelation",method="number" ,mar = c(1,1,1,1))
p.Ncrust.correlation.coefficient <- cor(Ncrust.correlation.coefficient)
corrplot(p.Ncrust.correlation.coefficient,method = "number",addrect = 2,title = "Ncrustcoefficient correlation",mar = c(1,1,1,1))
p.Scrumb.correlation.coefficient <- cor(Scrumb.correlation.coefficient)
corrplot(p.Scrumb.correlation.coefficient,method = "number",addrect = 2,title = "Scrumbcoefficient correlation",mar = c(1,1,1,1))
p.Scrust.correlation.coefficient <- cor(Scrust.correlation.coefficient)
corrplot(p.Scrust.correlation.coefficient,method = "number",addrect = 2,title = "Scrustcoefficient correlation",mar = c(1,1,1,1))

Appendix 4.5. Centre temperature curve of samples during freezing (package“ggplot2”, “grid”, “gridExtra”, “lattice”, “reshape2” required)require(ggplot2)
require(grid)
require(gridExtra)
require(lattice)require(reshape2)
getwd()
setwd("C:/Users/LINGKE/Desktop/R/Research")
sampleholder.freezing.curve <- read.csv("Freezing curve generalisation with sample
holder.csv")

121

time.sampleholder <- sampleholder.freezing.curve$Time
STM5 <- sampleholder.freezing.curve$Minus5
STM15 <- sampleholder.freezing.curve$Minus15
STM25 <- sampleholder.freezing.curve$Minus25
STM35 <- sampleholder.freezing.curve$Minus35
STM45 <- sampleholder.freezing.curve$Minus45
Sdata <- data.frame(time.sampleholder,STM5,STM15,STM25,STM35,STM45)
Sdata <- melt(Sdata,id.vars = "time.sampleholder", value.name = "Temperature")
Sdata
plot.sampleholder <- ggplot(Sdata,aes(x=time.sampleholder,y=Temperature,color=variable))+geom_line()+geom_point()+theme_bw()+ggtitle("Sample centre
freezing curve with sample holder")+theme(plot.title=element_text(size =20))+xlab("Time/min")+ylab("Temperature/celsius
degree")+scale_x_continuous(breaks = round(seq(min(Sdata$time.sampleholder),max(Sdata$time.sampleholder), by = 10),1)) +scale_y_continuous(breaks =round(seq(min(Sdata$Temperature), max(Sdata$Temperature), by =5),1))+annotate("text",x=150,y=-11,label="Freezing time=36 min\nFreezing rate=0.14
celsius degree/min",size=5)+annotate("text",x=150,y=-23,label="Freezing time=18
min\nFreezing rate=0.28 celsius degree/min",size=5)+annotate("text",x=150,y=33,label="Freezing time=10 min\nFreezing rate=0.49 celsius
degree/min",size=5)+annotate("text",x=150,y=-43,label="Freezing rate=0.50 celsius

122degree/min",size=5)+annotate("text",x=150,y=-2,label="Freezing time=2
min\nFreezing rate=0.95 celsius
degree/min",size=5)+theme(legend.text=element_text(size=15))+annotate("text",x=95,y=5,label="where ice crystalling happens(0~-5 celsius
degree)",size=5)+geom_segment(col="black",x=70,y=4.7,xend=60,yend=0,arrow =arrow(length =unit(0.5,"cm")))+geom_segment(col="black",x=135,y=6,xend=87,yend=-3.9,arrow = arrow(length =unit(0.5,"cm")))+annotate("text",x=150,y=-6,label="supercooling",size=5)+theme(text=element_text(size = 20))
plot.sampleholder <- plot.sampleholder+scale_x_continuous(breaks =round(seq(min(Sdata$time.sampleholder), max(Sdata$time.sampleholder), by = 10),1))+scale_y_continuous(breaks = round(seq(min(Sdata$Temperature),max(Sdata$Temperature), by = 5),1))
plot.sampleholder

Appendix 4.6. Baking characteristics of samples by SHS (package “ggplot2”, “grid”,“gridExtra”, “lattice”, “reshape2” required)require(ggplot2)
require(grid)
require(gridExtra)
require(lattice)require(reshape2)

123

getwd()setwd("C:/Users/LINGKE/DESKTOP/R/Research")
S1curve <- read.csv("S1baking performance.csv")
S1curve.samples <- read.csv("S1 baking performance samples.csv")
S1curvestr(S1curve)
xS1 <- S1curve$Time.S1.
xS1 <- round(xS1*(1/60),2)
xS1
xS2 <- S1curve.samples$Time.S2.
xS2 <- round(xS2*(1/60),2)
xS2
S1TM45 <- S1curve.samples$S1TM45
S1TM35 <- S1curve.samples$S1TM35
S1TM25 <- S1curve.samples$S1TM25
S1TM15 <- S1curve.samples$S1TM15
S1TM5 <- S1curve.samples$S1TM5
S1WM45 <- S1curve$S1WM45
S1WM35 <- S1curve$S1WM35
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S1WM25 <- S1curve$S1WM25
S1WM15 <- S1curve$S1WM15
S1WM5 <- S1curve$S1WM5
S.Upper <- S1curve$Upper.heater.S.
S.Air <- S1curve$Surrounding.air.S.
S.Lower <- S1curve$Lower.heater.S.
S1df1 <- data.frame(xS1,S.Upper,S.Air,S.Lower)
S1df2 <- data.frame(xS2,S1TM45,S1TM35,S1TM25,S1TM15,S1TM5)
S1df3 <- data.frame(xS1,S1WM45,S1WM35,S1WM25,S1WM15,S1WM5)
S1dfa <- melt(data=S1df1,id.vars="xS1",value.name = "Heater.T")
S1dfb <- melt(data=S1df2,id.vars="xS2",value.name = "Sample.T")
S1dfc <- melt(data=S1df3,id.vars="xS1",value.name = "Sample.W")
WS1 <- qplot(x=xS1,y=Sample.W,data=S1dfc,col=variable,xlab="",ylab = "Sample
weight/g",main="Baking performance of samples under 1 day frozen storage by SHS")
WS1 <- WS1+theme_bw()+theme(plot.margin=unit(c(0.7,0.5,0,0.4),"cm"))+theme(axis.title.y=element_text(size=15))+theme(axis.title.x=element_text(size=15))+geom_line()+geom_point()+theme(axis.text.x=element_blank())+geom_point()+theme(plot.title=element_text(size=20))+theme(text=element_text(size=20))
PS1 <- qplot(x=xS1,y=Heater.T,data=S1dfa,col=variable,geom = "line",xlab = "",ylab ="Heater T/C")

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PS1 <PS1+theme_bw()+theme(axis.text.x=element_blank())+theme(axis.title.y=element_text(size=15))+geom_point()+theme(plot.title=element_text(size=30))+theme(plot.margin=
unit(c(-0.9,-0.2,0,0.2),"cm"))+theme(text=element_text(size=20))
TS1 <- qplot(x=xS2,y=Sample.T,data=S1dfb,col=variable,xlab="Time/min",ylab ="Sample T/C")
TS1 <- TS1+theme_bw()+theme(plot.margin=unit(c(-0.9,0.3,0,0.2),"cm"))+theme(axis.title.y=element_text(size=15))+theme(axis.title.x=element_text(size=15))+geom_line()+geom_point()+theme(text=element_text(size=20))+scale_x_continuous(limits = c(0,15))
grid.arrange(WS1,PS1,TS1)

Appendix 4.7. 3D scatterplot of CIE Lab colour space (package “scatterplot3d”
required)
require("scatterplot3d")
getwd()
setwd("C:/Users/LINGKE/DESKTOP/R/Research")
Ncolor <- read.csv("Ncolor.csv")
LN <- Ncolor$Delta.L
aN <- Ncolor$Delta.abN <- Ncolor$Delta.b126

Scolor <- read.csv("Scolor.csv")
LS <- Scolor$Delta.L
aS <- Scolor$Delta.abS <- Scolor$Delta.b
xlimN <- range(0,50)
ylimN <- range(0,25)
zlimN <- range(40,LN)
zlimS <- range(40,LS)par(mfrow=c(1,2))
scatterplot3d(bN,aN,LN,pch=19,highlight.3d = FALSE,xlim=xlimN,ylim = ylimN,zlim= zlimN,main = "HA baked sample \ncolor distribution",cex.axis = 1.5)
scatterplot3d(bS,aS,LS,pch=19,highlight.3d = FALSE,xlim=xlimN,ylim = ylimN,zlim= zlimN,main = "SHS baked sample \ncolor distribution",cex.axis = 1.5)

Appendix 4.8. Rheological properties graphics (instantaneous elasticity/E0, package“ggplot2”, “grid”, “gridExtra”, :lattice”, “reshape2”, “matrixStats” required )require(ggplot2)
require(grid)
require(gridExtra)
require(lattice)127require(reshape2)
require(matrixStats)
setwd("C:/Users/LINGKE/Desktop/R/Research/1 day samples")N5crumb1 <- read.csv("N5crumb1A.csv")
N15crumb1 <- read.csv("N15crumb1A.csv")
N25crumb1 <- read.csv("N25crumb1A.csv")
N35crumb1 <- read.csv("N35crumb1A.csv")
N45crumb1 <- read.csv("N45crumb1A.csv")
S5crumb1 <- read.csv("S5crumb1A.csv")
S15crumb1 <- read.csv("S15crumb1A.csv")
S25crumb1 <- read.csv("S25crumb1A.csv")
S35crumb1 <- read.csv("S35crumb1A.csv")
S45crumb1 <- read.csv("S45crumb1A.csv")
N5crust1 <- read.csv("N5crust1A.csv")
N15crust1 <- read.csv("N15crust1A.csv")
N25crust1 <- read.csv("N25crust1A.csv")
N35crust1 <- read.csv("N35crust1A.csv")
N45crust1 <- read.csv("N45crust1A.csv")

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S5crust1 <- read.csv("S5crust1A.csv")
S15crust1 <- read.csv("S15crust1A.csv")
S25crust1 <- read.csv("S25crust1A.csv")
S35crust1 <- read.csv("S35crust1A.csv")
S45crust1 <- read.csv("S45crust1A.csv")
N5crumb1.E0 <- N5crumb1$E0
N15crumb1.E0 <- N15crumb1$E0
N25crumb1.E0 <- N25crumb1$E0
N35crumb1.E0 <- N35crumb1$E0
N45crumb1.E0 <- N45crumb1$E0
S5crumb1.E0 <- S5crumb1$E0
S15crumb1.E0 <- S15crumb1$E0
S25crumb1.E0 <- S25crumb1$E0
S35crumb1.E0 <- S35crumb1$E0
S45crumb1.E0 <- S45crumb1$E0
N5crust1.E0 <- N5crust1$E0
N15crust1.E0 <- N15crust1$E0
N25crust1.E0 <- N25crust1$E0
N35crust1.E0 <- N35crust1$E0129

N45crust1.E0 <- N45crust1$E0
S5crust1.E0 <- S5crust1$E0
S15crust1.E0 <- S15crust1$E0
S25crust1.E0 <- S25crust1$E0
S35crust1.E0 <- S35crust1$E0
S45crust1.E0 <- S45crust1$E0
df.crumb.E0 <data.frame(N5crumb1.E0,S5crumb1.E0,N15crumb1.E0,S15crumb1.E0,N25crumb1.E0,
S25crumb1.E0,N35crumb1.E0,S35crumb1.E0,N45crumb1.E0,S45crumb1.E0)
mean.df.crumb.E0 <- colMeans(df.crumb.E0)
mean.df.crumb.E0 <- as.matrix(mean.df.crumb.E0)
sd.df.crumb.E0 <- as.matrix(df.crumb.E0)
sd.df.crumb.E0 <- colSds(sd.df.crumb.E0)
column.crumb.E0 <- c("N0","S0","N1","S1","N2","S2","N3","S3","N4","S4")Baking.method <- gl(2,1,10,labels = c("HA","SHS"))d.crumb.E0 <data.frame(column.crumb.E0,Baking.method,mean.df.crumb.E0,sd.df.crumb.E0)
d.crumb.E0130

p.crumb.E0 <ggplot(d.crumb.E0,aes(x=column.crumb.E0,y=mean.df.crumb.E0,fill=Baking.method))+
geom_bar(stat = "identity",position = position_dodge(1))+
theme_bw()+
ylab(expression(paste(E[0], " /pa")))+
ggtitle(expression(paste(E[0], " of crumbs")))+
theme(axis.title.x=element_text(size=30))+
theme(axis.title.y=element_text(size=30))+
theme(plot.title=element_text(size=30))+
scale_fill_manual(values=c("grey","black"))+geom_errorbar(aes(ymin=mean.df.crumb.E0-sd.df.crumb.E0,
ymax=mean.df.crumb.E0+sd.df.crumb.E0),position=position_dodge(width=.9),color="darkblue")+theme(legend.position="top")+annotate("text",x=6,y=85000,label="
1 day frozen",size=7)+theme(axis.title.x=element_blank())+theme(text=element_text(size=20))
print(p.crumb.E0)131df.crust.E0 <data.frame(N5crust1.E0,S5crust1.E0,N15crust1.E0,S15crust1.E0,N25crust1.E0,S25crus
t1.E0,N35crust1.E0,S35crust1.E0,N45crust1.E0,S45crust1.E0)
mean.df.crust.E0 <- colMeans(df.crust.E0)
mean.df.crust.E0 <- as.matrix(mean.df.crust.E0)
sd.df.crust.E0 <- as.matrix(df.crust.E0)
sd.df.crust.E0 <- colSds(sd.df.crust.E0)
column.crust.E0 <- c("N0","S0","N1","S1","N2","S2","N3","S3","N4","S4")Baking.method <- gl(2,1,10,labels = c("HA","SHS"))d.crust.E0 <data.frame(column.crust.E0,Baking.method,mean.df.crust.E0,sd.df.crust.E0)
p.crust.E0 <ggplot(d.crust.E0,aes(x=column.crust.E0,y=mean.df.crust.E0,fill=Baking.method))+geom_bar(stat = "identity",position = position_dodge(1))+
theme_bw()+xlab("Tested samples")+ylab(expression(paste(E[0], " /pa")))+
ggtitle(expression(paste(E[0], " of crusts")))+
theme(axis.title.x=element_text(size=30))+
theme(axis.title.y=element_text(size=30))+132

theme(plot.title=element_text(size=30))+
scale_fill_manual(values=c("grey","black"))+geom_errorbar(aes(ymin=mean.df.crust.E0-sd.df.crust.E0,
ymax=mean.df.crust.E0+sd.df.crust.E0),position=position_dodge(width=.9),color="darkblue")+theme(legend.position="top")+annotate("text",x=6,y=85000,label="
1 day frozen ",size=7)+theme(text=element_text(size=20))
print(p.crust.E0)
grid.arrange(p.crumb.E0,p.crust.E0)133