MODELLING THE EFFECT OF TE.l\1PERATURE ON THE GROWING OF SACCHAROMYCES CEREVISIAE CSI-l IN HYDROLYSED

SAGO STARCH BASED MEDIA

NgKim Sai

(37465)

TP Bachelor of Science with Honours (Resource Biotechnology)

S3 2015 N576 2015

416

Pusat Khidmat MakJumat kademi. If. TI M'\L..4.vSU SAR AW,.t \'''C

. Modelling the Effect of Temperature on the Growing of Saccharomyces cerev;s;ae CSI-l

in Hydrolysed Sago Starch Based Media

Ng Kim Sai (37465)

A Thesis submitted in partial fulfilment of the

Requirement for the degree ofBachelor of Science with Honours

(Resource Biotechnology)

Supervisor: A.P. Dr. Cirilo Nolasco Hipolito

Resource Biotechnology

Department of Molecular Biology .'

Faculty of Resource Science and Technology

University Malaysia Sarawak

2015

.... F

ACKNOWLEDGEMENT

I would like to express my gratitude and thanks to my supervisor, Assoc. Prof. Dr. Cirilo

Nolasco Hipolito for the guidance, advice, support and knowledge given through the year

until I completing the study. I learned a lot of new thing throughout the study.

A speciai thanks to the University Malaysia Sarawak for providing the well-equipment

biochemistry laboratory for conducting my study and experiment. I also would tike to thanks

for kak Nurfaezzah Amat lafar who had helped in many ways.

I would like to thank my family for their moral and economic support and always

encouragement me throughout my study i_n UNIMAS. Last but not least, I would like to

thanks to all my friend and fellow classmate for their help, cooperation, assistance and

support throughout the year.

- r

UNIVERSITI MALAYSIA SARA WAK

Grade: ______

Please tick (-y) Final Year Project Report

Masters

PhD

DECLARATION OF ORIGINAL WORK

/.

This declaration is made on the .. .. ... \.1. .......day of.. J.~~~.....20 IS.

Student's Declaration:

I, Ng Kim Sai (37465) from Faculty of Resource Science and Technology hereby declare that the work entitled Modelling the Effect of Temperature on the Growing of Saccharomyces cerevisiae CSI-l in Hydrolysed Sago Starch Based Media is my original work. I have not copied from any other students' work or from any other sources except where due reference or acknowledgement is made explicitly in the text, nor has any part been written for me by another person.

"/0(, ( ~_" Date submitted Ng

Supervisor's Declaration:

I, Cirilo Nolasco Hipolito hereby certifies that the work entitled Modelling the Effect of Temperature on the Growing of Saccharomyces cerevisiae CSI-l in Hydrolysed Sago Starch Based Media was prepared by the above named student, and was submitted to the Faculty of Resource Science and Technology as a ... partial/full fulfilment for the conferment of Bachelor of Science with Honour~, and the aforementioned work, to the best of my knowledge, is the said student's work.

Received for examination by:

11

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iii

Pu:a f<hiumllt 1\ Ilkluma( kliC II'

IVERSfD lALAY. rA SARAWAh

TABLE OF CONTENTS

ACKNOWLEDGEMENT ..................................................................................................................... i

DECLARATION OF ORIGINAL WORK ...... ....... .... .. ..... ... .................. .. ............... ................ .......... ii

TABLE OF CONTENTS.... ... ............... .... ...... .... ... ...... ............... .. .... ..... .. ...... .. ...... ........... .. ................. iv

LIST OF ABBREVIATIONS......... .. ... .. ............... ........... ..... ... ....... ... .......... .. .. .. ...... .... .. ....... .. ............. vi

LIST OF FIGURE .............................................................................................................................. vii

LIST OF TABLE ............................................................................................................................... viii

ABSTRACT ........................................................................................................................................... 1

1.0 INTRODUCTION........................................................................................................................... 2

2.0 LITERATURE REVIEW......... .... .. ......... .... ................... ...... ... .. .............. ........ ......... .. ..... ... ... ..... ... .4

2.1 yeast. ... ........ ............ .... ... .... ... .. .............. ... ..... .. .... .... .. ........ .. ................ .. ........ .. ......... ... .................. 4

2.1 .1 Ability of Saccharomyces cerevisiae .. ................................. .. .... ........ ............ ..... .. ....... .... ...... .... 4

2.2 Effect of Temperature on the Growth of Saccharomyces cerevisiae ............................................ 5

2.3 Mathematics Modelling ........... ......... ..... ............. ... ......................................................... .... .... ... ... 5

2.3 .1 Primary Model ......................... .. ........ ... ............. .. ..... ...... . ~ .... .. ...... ..... .............................. ... ....... 6

2.3 .2 Secondary Model ..... .. ..................................... ...... .... .. .......... ........................................ ~ ... ........ . 7

2.4 Batch Fermentation .............. ... ......................................... ..... ............................. ................ ........... 8

3.0 MATERIAL AND METHODS ... .. .......................... .. ............................................... .. ............. ... .. 10

3.1 Microorganism and Culture Condition .................................................................... ..... ...... ........ 10

3.2 Inoculum Preparation ............ .. .................................... ... .... ...... .... .... .............................. ... ... .... ... 10

3.3 Fermentation Medium ................................................................................................................. 10

3.4 Temperature Condition on the Growth of S. cerevisiae CSI-1 ................. ..... .. ..... ....... .. ............. 11

3.5 Analytical Procedure .................................................. .. ...................................................... ......... 11

3.5.1 Optical Density, pH, Glucose and Ethanol Concentration ................................................... 11

3.5.2 Dry Cell Weight Detennination ........................................................................................... 12

3.5.3 Viable Cell Count. ................................................................................................................ 13

3.6 Statistically analysis ................................................................................................................. ... 14

lV

3.7 Mathematic Modelling ................................................................................................................ 14

3.7.1 Primary Model ..................................................................................................................... 14

3.7.2 Secondary Model ................................................................................................................. 15

4.0 RESULT AND DISCUSSION...................................................................................................... 16

4.1 Effect of temperature on the growing of S. cerevisiae CSI-1 ..................................................... 16

4.2 Effect of temperature on the cell concentration of S. cerevisiae CSI-1 ...................................... 18

4.3 Specific growth rate of S. cerevisiae CSI-1 under different temperature ................................... 20

4.4 Mathematic model. ...................................................................................................................... 22

4.5 Comparison between cardinal model and experimental data ...................................................... 24

4.6 Effect of temperature on the flow of gases of S. cerevisiae CSI-l. ............................................ 25

4.7 Theoretical ethanol productivity at different temperature conditions ......................................... 26

4.8 Ethanol production based on different temperature conditions ................................................... 28

4.9 Theoretical carbon dioxide productivity at different temperature conditions ............................. 29

4.10 Carbon dioxide production based on different temperature conditions .................................... 30

4.11 Consumption of glucose at different temperature ..................................................................... 31

4.12 pH value at different temperature cond.itions ............................................................................ 33

4.13 Statistically analysis ................................................................. , ........................................... .. ... 34

4.14 Recommendation ...................................................................................................................... 35

5.0 CONCLUSION.............................................................................................................................. 36

REFERENCES .................................................................................................................................... 37

APPENDIX .................."........................................................................................................................ 41

v

I

LIST OF ABBREVIATIONS

~ ,

vi

LIST OF FIGURE

Figure 1: Biomass kinetics of S. cerevisiae CSI-l under different temperature conditions .. .. 16

Figure 2: Kinetic of cell concentration of S. cerevisiae CSI-l under different temperature

conditions . ...... .. ...... .. ....... ........... ..... .... ............. .. ...... ................. ...................... ................... ..... 18

Figure 3: Kinetic of specific growth rate at different temperatures ........ ......... .... ..... ...... ........ 20

Figure 4: Mathematic model that describe that maximum specific growth rate at different

temperature. ........ ........ .. ... ..... .... ..... .............. .. ............... .......... .................. ..... ... ....................... 22

Figure 5: Comparison between cardinal model and experimental data ............. .......... .. ... ... .... 24

Figure 6: Kinetic of flow of gases under different temperature condition . ..................... ....... . 25

Figure 7: Effect of temperature on ethanol production .... ......... .. ............ .................. .... ..... .. ... 28

Figure 8: Effect of temperature on carbon dioxide production ...... ......... ...... ............ ..... ......... 30

Figure 9: Kinetic of glucose consumption at different temperature ... .. .............. ......... ............ 31

Figure 10: pH value at the different temperature conditions .......... ...... .... .. ... ......... .. ... .. ........ .. 33

Figure 11 : Relationship between DCW and OD ... ... ......................... .... ..... .... .... .. ............ .... ... 41

Figure 12: Relationship between cell number and OD ... ........... .... .. ........ ........ .......... ............. . 41

vii

LIST OF TABLE

Table 1: ANOV A analysis ....................................................................................................... 34

Table 2: Multiple comparison of mean.................................................................................... 42

Table 3: Proportion of variance of cardinal model and experimental data ............................. 43

"

Vlll

I

Modelling the Effect of Temperature on the Growing of Saccharomyces cerevisiae CSI-l in Hydrolysed Sago Starch Based Media

Ng Kim Sai

Resource Biotechnology Program, Department of Molecular Biology Faculty of Resource Science and Technology

University Malaysia Sarawak

ABSTRACT

Yeasts have been widely used in the industry as a way to convert biomass into useful materials through fermentation. Saccharomyces cerevisiae (s. cerevisiae) is well-known yeast around the world. Nowadays, mathematical modelling is widely used to predict the outcome of experiments such as growth kinetic of microbes under different environmental condition. However, not many mathematical modelling has been done to predict the effect of temperature on S. cerevisiae. In this experiment, different temperatures were conducted to test on the growth of S. cerevisiae CSI-1 by using hydrolysed sago starch based media. The maximum specific growth rate for temperature 31,33,35,37, and 39°C at the first 6 h are 0.4527, 0.6675, 0.6634, 0.6021, and 0.5938 respectively. Cardinal model was developed to fit the growth model of S. cerevisiae CSI-l under different temperature.

Keywords: Saccharomyces cerevisiae, sp~cific growth rate, Cardinal model.

ABSTRAK

Yis telah digunakan secara meluas dalam industri sebagai satu cara untuk menukar biomas ke dalam bahan-bahan yang berguna melalui penapaian. Saccharomyces cerevisiae (s. cerevisiae) adalah yis yang terkenal di seluruh dunia. Pada masa kini, pemodelan matematik telah digunakan dengan bijak untuk meramalkan hasil eksperimen seperti kinetik pertumbuhan mikrob di bawah keadaan yang berbeza. Walau bagaimanapun. pemodelan matematik kurang dilakukan untuk meramalkan kesan suhu kepada S. cerevisiae. Dalam eksperimen ini, suhil yang berbeza telah dijalankan untuk menguji pertumbuhan S. cerevisiae CSI-1 dengan menggunakan terhidrolisis media berasaskan kanji sagu. Kadar pertumbuhan spesijik maksimum untuk suhu 31, 33, 35, 37 dan 39 ° C pada mulanya 6 h adalah masing-masing 0.4527, 0.6675, 0.6634, 0.6021, dan 0.5938 .Model kardinal telah dibangunkan untuk muat model pertumbuhan S. cerevisiae CSI-J di bawah suhu yang berbeza.

Kata Icunci: Saccharomyces cerevisiae, kadar pertumbuhan, model Kardinal.

1

1.0 INTRODUCTION

Nowadays, yeast and other types of microorganism have been widely used in the industry

as a way to convert biomass into useful materials through fermentation. Fermentation is the

process whereby the utilization of the substrates by microbiota occurs in the absence of

oxygen. Fermentation is used in various industries such as winemaking as well as baking

of bun and bread (Steinkraus et aI., 1983). Among different types of yeasts,

Saccharomyces cerevisiae (s. cerevisiae) is the well-known yeast around the world.

Various factors such as temperature, pH, and substrate concentration can affect the process

of the fermentation and in tum affect the cost for the fermentation. Fermentation at high

temperature can bring several potential benefits, Jones and Hough (1970) showed that the

productivity of fermentation increases with high temperature under vacuum compared to

low temperature. However, not many is known about the effect of temperature on growth

ofS. cerevisiae CSI-1.

Modelling is an important tool for improving bioprocess as it can guide the

operation of the bioreactor. Modelling provides information to control the overall process

performance in various phenomena within the fennentation system (Mitchell et at. , 2003).

However, less mathematical modelling has been done to predict the effect of temperature

on S. cerevisiae. The growth of S. cerevisiae CSI-1 during bioconversion process is

complicated (Lin & . Tanaka, 2006). Hence, it is .important to develop a model to

understand the growth of S. cerevisiae CSI-1. Sago starch is a feedstock for food and

beverage industries. Upon enzymatic hydrolysis process as an efficient process to produce

sugars, hydrolyzed sago starch is more cost effective than sugar. Therefore, the hydrolysed

sago starch (HSS) is selected as the media for fermentation. HSS is fermented by S.

cerevisiae CSI-I type strain converting it into ethanol under different temperature

conditions in batch fermentation.

2

The purpose of this study was to monitor the growth of S. cerevisiae eSI-I under

different temperatures with the help of specific growth rate equation and cardinal model.

Therefore, the hypothesis to be tested is wherever the growth of S. cerevisiae eSI-I at

different temperatures is the same, or the growth of S. cerevisiae eSI-l is affected by the

temperature.

In this experiment, fermentation at different temperatures was conducted to

evaluate the growth of S. cerevisiae eSI-l by using hydrolysed sago starc!) based media.

The HSS was prepared with a concentration of 100 giL of sago starch. Filtration method

and centrifugation method was carrying out to remove the fibre content. The effect of

temperatures of 31, 33, 35, 37, and 39 °e had been tested on the growth of S. cerevisiae

CSI-l in a batch fennenter. Samples were withdrawn very 2 hours from the batch

fermenter. The growth rate of S. cerevisiae eSI-l was calculated using the direct method

by counting

consumption and

dioxide.

the cell

ethanol

using

pro

haemocytometer,

duction were calc

optical

ulated'

density,

from the

and

produ

Dew.

ction of carbon

Glucose

The objective:

1. Study the effect of temperature on the growth of S. cerevisiae eSI-l in HSS based

media.

2. Develop cardinal model to monitor , the growth of S. cerevisiae eSI-l at different

temperatures.

3

2.0 LITERATURE REVIEW

2.1 Yeast

Yeast is a simple, unicellular eukaryote which has become a preferred used model system

in biological research. According to Schneiter (2004), yeast is popular for food and

beverage production by fermentation process. There are many valuable food ingredients

and processing aids are now derived mainly from yeast. Besides that, yeast can also be

applied in food preservation through fermentation processes.

Yeast had also been recognised as the most common microorganism for ethanol

fermentation. According to Schneiter (2004), yeast contains several characteristics like

cheap and easy to be cultivated, has relatively short generation time, detailed genetic

knowledge, and convenience of genetic manipulation. Among different species of yeasts,

Saccharomyces cerevisiae, and Saccharomyces bayanus var. uvarum are the most

important species used in the fermentation-process (Pretorius, 2000; Querol & Fleet, 2006).

2.1.1 Ability of Saccharomyces cerevisiae

Saccharomyces cerevisiae is a well-known ethanol producer, and it is widely used in

industrial application. Among other yeast species, S. cerevisiae can degrade carbohydrate

hexose such as glucose into alcohol and lactic acid under anaerobic condition.

S. cerevisiae is known as Crabtree-positive ,yeast that can accumulate ethanol even

in the presence of oxygen. On the other hand, Candida albicans and Kluyveromyces lactis

are known as Crabtree-negative yeasts can degrade sugar to carbon dioxide (Piskur et aI.,

2006). In a research done by Thomson et al. (2005), Saccharomyces genus contains an

alcohol dehydrogenases enzyme that is encoded by ADH 1 and ADH 2 gene. ADH 1

converts sugar into alcohol while ADH 2 catalyses the reverse reaction, and ADH 2 is only

produced when the sugar level drops.

4

· u :: K1li lat J\1akJuma Aka m:> UNIVERSITI MALAYSIA SARAWAK

According to Goddard (2008), temperature plays an important role in the presence

and imposition of our daily activity and industrial applications. The yeast grows well at

temperature 25 and 30 °e, but it shows a decrease in the growth at 35 °e (Torija et al.,

2002). While in the study done by Aldiguier et al. (2004), they had proven that the 30 °e

showed the benefit for the growth of S. cerevisiae.

2.2 Effect of Temperature on the Growth of Saccharomyces cerevisiae

Developments of different Saccharomyces strains are affected by the temperature of

fermentation. The temperature can affect the sensitivity of yeast that in tum affects the

alcohol concentration, growth rate, and rate of fermentation, length of the lag phase,

viability, enzyme, and membrane function. In research done by Sener et al. (2007), the

production of ethanol and other fermentation by-products are related to temperature. Sener

et al. (2007) also showed that the S. cerevisiae (Zymaflore VLt) and S. cerevisiae

(Uvaferm eM) at 25°e have higher fermentation rate than 18°C. Lin et al. (2012)

showed that the cell growth and ethanol production decline at 50°C. However, less is

known about the growth of S. cerevisiae eSI-l on different temperature. Hence, a

mathematical model should be developed to study the effect of temperature on the growth

ofS. cerevisiae eSI-l.

2.3 Mathematics Modelling

Mathematical model has been used to predict and study the growth of microbes, especially

in the field of food science and medicine. The model can control the overall process

performance by predicts how various phenomena affect the bioprocess within the

fermentation system (Mitchell et al., 2003). Mitchell et al. (2003) concluded in a research

that the use of a mathematical model in the design and operation of SDF bioreactor can

maximize the economic performance of SSF process.

5

Wilson et al. (2002) used a mathematical modelling to study the growth of the

organisms in many types of food. They found that the growth prediction by the model was

faster than the observed growth. A study done by Trontel et al. (2010) had proven that

mathematical modelling and optimization of the temperature in bioprocess of Lactobacillus

amylovorus DSM 20531 T can produce economically attractive lactic acid. However, no

research has been done so far to model the effect of temperature on the growth of S.

cerevisiae CSI-l. The attractiveness of the research is focused mainly on modelling the

effect of the temperature using sago starch as substrate for the media. It is well known as

stated above that there are diverse phenomena that affect the metabolism of the

microorganism. Hence, the effect of the temperature on S. cerevisiae CSI-l was done using

sago starch. Sago starch is the substrate by excellence in Malaysia since sago palm is

abundant in our country.

2.3.1 Primary Model

Primary model is used to study the evolution such as growth, inactivation or survival of

microorganism in various times. There are different types of primary models; the static

model is a model that is only valid under static environment condition while the dynamic

model can deal with time-varying environment factor (Wilson et al., 2002). Grijispeerdt

and Vanrolleghem (1999) stated that the Baranyi model is structurally identifiable to

provide sufficiently,good quality of bacterial growth data. However, the Baranyi model is

difficult and complex to be used to describe the growth of yeast.

According to Zwietering et al. (1990), the modified Gompertz equation is simple,

easy to use and to describe the data of the growth of Lactobacillus plantarum more

statistically compared to other types of models. The growth of yeast in batch fermentation

shows a lag pbase followed by exponential phase, stationary phase and finally dead phase.

Therefore, the Gompertz equation is modified to include the specific growth rate, lag time

6

and the maximum value reached (Zwietering et al., 1991). In recent research carried out by

Arroyo-Lopez et al. (2009) and by Salvado et al. (2011b), the Gompertz equation was

chosen as the primary model to study the growth rate of S. cerevisiae.

However, since the experiment design to exclude the lag phase, the modified

Gompertz equation is not suitable for this experiment. According to Gupthar, Bhattacharya

and Basu (2000), the maximum specific growth rate can be calculated using a more simple

rate equation.

2.3.2 Secondary Model

According to Wilson et al. (2002), the primary model parameter on environmental

influence such as temperature, pH, organic acid, and different substrate concentration can

be study by secondary model. One of the popular secondary models is response surface

(RS). RS has been applied to estimate the growth of yeast under combined effect of

different environmental variables such .as pH, temperature, and sugar concentration

(Arroyo-Lopez et al., 2009). However, RS model is not suitable because it is complicated

and time-consuming.

Cardinal model, a model, developed by Rosso et al. in 1993, can be used to predict

the specific growth rate of the microorganism in relation to the temperature. According to

Rosso et al. (I993), the cardinal model is better than other models such as Ratkowsky

complete model, Hinshelwood model, and Zwietering model. Cardinal model has

examined the result of different water activity on the growth of moulds, and it showed a

good concordance between the observed and predicted result (Rosso & Robinson, 2001).

Shafi and Price (2001) used the cardinal model in their research to estimate the seed

gennination with different temperature. In a study done by Salvado et al. (2011 a, 2011 b),

7

cardinal temperature model was chosen with inflection (CTMI) because it is simple and

direct to use during biological interpretation of the result.

2.4 Batch Fermentation

There are many types of bioreactor that are used for industrial purposes. Many studies

were focused on continuous ethanol production using immobilized yeast cell in various

type of bioreactors. The most common bioreactors are the fluidized-bed bioreactor;

continuous-flow stirred tank bioreactor, and packed-bed bioreactor (Najafpour, Younesi, &

Syahidah Ismail, 2004; Bravo & Gonzalez, 2007). Fermentation can be performed as a

batch process where each filling of the nutrient gives a bath of end product. It also can be

carried out as a continuous process where the nutrients are added, and the product is

removed continuously over a fixed period.

Batch fermentation is a method in which fermentation is carried out in an anaerobic

condition as all the processes are done iq a closed system. The sterile closed system can

ensure the growth of the desired organism. According to Scragg (1991), batch fermentation

is operated under optimum condition of temperature, pH, and redox potential because the

performance can be improved by compare to the previous batch runs. Other than that, the

batch fermentation system does not necessarily need to contain the entire nutrient to

sustain the growth of S. cerevisiae. Besides that, contamination does not bring a serious

effect on the femlentation process that occurs in a batch fermenter unless it takes place

during the lag phase of fermentation. According to Caylak and Varder (1998), batch

fermentation required less control and less cost.

S. cerevisiae is used extensively in a batch fermentation to produce ethanol and

other by-products through fermentation for the production of beverage and biofuels.

According to Mendes et al. (2004), batch fermentation is widely used in the production of

8

ethanol. During batch fermentation, the rate of ethanol production increases for a short

period until it reaches a maximum peak and then declines progressively as ethanol

accumulates in the bioreactor. Ozligen et al. (1991) proved that the accumulation of

ethanol in a fermenter can inhibit the specific growth rate, specific ethanol production rate,

cell viability and substrate consumption of S. cerevisiae. Hence, it is impo,rtant to develop

a model to predict the effect of different temperature on the growth ofS. cerevisiae CSI -1.

"

3.0 MATERIAL AND METHODS

3.1 Microorganism and Culture Condition

Saccharomyces cerevisiae CSI-1 yeast strain (Cirilo-Shimazaki-Ishizaki, Japan) was

obtained from FRST laboratory and used in this research. The strain was grown on 20 giL

glucose (Com Products, Malaysia), 5 giL yeast extract (Oxoid, England) at 38.5 °C for 6 h.

Subculture was carried out for every two weeks.

3.2 Inoculum Preparation

S. cerevisiae CSJ-J from the culture was inoculated into 250 ml of Erlenmeyer flask with

200 ml of growth medium that contains 40 giL glucose and 5 giL yeast extract. The pre­

culture was incubated in 38.5 °C incubator for 16 h. The pre-culture was centrifuged at

2500 x g (5000 rpm), 28°C for 3 min. The cell pellet was then used as the inoculum and

put into the fermenter.

3.3 Fermentation Medium

Hydrolysed sago starch (HSS) was produced using an enzymatic method to hydrolyse sago

starch (Nolasco-Hipolito et al., 2012). Sago starch (Herdsen Sago Mill, Malaysia) was

suspended and dissolved in distilled water to reach the final concentrtion of 200 giL (20%

w/v dry basis). The pH of the suspension was adjusted to 6.5 . Then, 0.5 J..lI Termamyl SC

(Science Techniqs, Malaysia) per gram of starch was added for liquefaction of the starch at

90-95 °C and agitated at 200 rpm for 2 h. The saccharification was performed by adding

0.6 J..lI AMG (Science Technics, Malaysia) per gram of starch at pH 4.5 and agitated at 200

rpm with 60-63 °C for 24h.

10

.-_._. --_.._-----------­

3.4 Temperature Condition on the Growth of S. cerevisiae CSI-1

Batch fermentation was perfonned in a 3 L bioreactor (Biott, Japan). The working volume

was fixed at 2 L of broth. The fennentation was perfonned at different temperature as

follow: 31 33, 35, 37 and 39°C with HSS media. The optical density, temperature,

agitation, and the carbon dioxide were monitored online by the computer. The agitation

rate was fixed at 100 rpm. For this experiment, the HSS media were set at 100 giL and

yeast extract was set at 5 giL to be used as carbon and nitrogen sources respectively.

3.5 Analytical Procedure

During the fermentation process, 10 ml of broth sample was removed every 2 hours to

determine the 00, cell count and dry cell weight. Sample was centrifuged at 5000 rpm for

10 minutes to remove the cell. The supernatant was filtered through 0.45 ~m of filter paper

and was reserved at 4 °C for further analysis. The flow of gas is monitor online by

computer.

3.5.1 Optical Density, pH, Glucose and Ethanol Concentration

Optical Density (OD) value was detennined via a turbidimeter build-up with a laser sensor

at wavelength 0[780 run (ASAR Instruments, Japan). pH value of the sample was checked

using pH probe every 4 hours. The glucose and ethanol concentration was calculated from

the flow ofgases which monitored online by computer. ..

11

3.5.2 Dry Cell Weight Determination

A standard curve describing the relationship of dry cell weight (DCW) and

spectrophotometric OD reading was done (refer appendix A). The OD reading was

recorded while DCW was weighted to obtain the correlation of both parameters by a graph.

Dew is one of the most common measurements that are used to determine the

biomass concentration in grams per litre. DCW was determined using centrifugation

method. Around 10ml sample was centrifuged at 3000xg, for 10 min. The cell pellet was

then washed with 0.2 M HCI and the supernatant was discarded. The cell pellet was then

dried in oven at 90°C for 6 hours. The weight of centrifuged tube and dried cell was

measured using analytical balance. Dry cell weight (DCW) determination was carried out

by using the equation 1:

DCW (giL) = [A (9)+ 8 (9)]-[A (g)] X 103 Equation 1 V (L)

Where

A= Weight of centrifuge tube (g)

B= Weight of centrifuge tube + weight of dry cell pellet

V= Volume of sample (L)

12

i

3.5.3 Viable Cell Count

A standard curve describing the relationship of cell count and spectrophotometric OD

reading was weighted to obtain the correlation of both parameters by a graph.

Viable Cell count (VCC) of S. cerevisiae CSI-l was determined using the

methylene blue - haemocytometer method. Samples were taken from the batch fermenter

and mixed with 0.1 % methylene blue. 50 ~l of sample was mixed with 50 ~l of methylene

blue and then fill the haemocytometer by capillary diffusion. According to Painting and

Kirsop (1990), viable yeast cell generally are able to resist the methylene blue dye while

the non-viable yeast cell are not able to resist the blue stain. Therefore the viable yeast cell

was appeared colourless while non-viable yeast was appeared blue in colour. The cell

concentration was calculated using the following equation 2:

vee (c;~l) = (x)(2)(10,000)(bdf) Equation 2

Where

VCC= Viable cell (cell/ml)

2= I volume of broth + 1 volume of blue methylene

10,000= 1/ (haemocytometer volume)

bdf= broth dilution factor

=average counting

13

3.6 Statistically analysis

Since the experiments involve 5 different temperatures and perfonned in triplicate, then,

the data was analysis using analysis of variance (ANOV A) followed by Tukey post-hoc

analysis in order to find out if there is any different between the mean of the growth of the

yeast at various temperature.

3.7 Mathematic Modelling

3.7.1 Primary Model

In (it) /.l=-_o­Equation 3Tt - To

Jl Specific growth rate (h- 1)

Xl Cell dry weight at specific time (gil)

Xo Cell dry weight at initial time (gll)-

Tl Time for Xl (h)

To Time for Xo (h)

1 ~