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EFFECT OF PRE AND POST FERMENTATION TREATMENTS ON QUALITY OF RED WINE PREPARATION FROM PUNJAB PURPLE GRAPES Thesis Submitted to the Punjab Agricultural University in partial fulfillment of the requirements for the degree of INTEGRATED MASTER OF SCIENCE (Hons.) in MICROBIOLOGY (Minor Subject: Biochemistry) By Maninderjeet Kaur (L-2008-BS-09-IM) Department of Microbiology College of Basic Sciences and Humanities © PUNJAB AGRICULTURAL UNIVERSITY LUDHIANA – 141 004 2013

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Page 1: EFFECT OF PRE AND POST FERMENTATION TREATMENTS …...where India stands at 12 th position in its production. But, in terms of productivity, India has the highest productivity of 26.2

EFFECT OF PRE AND POST FERMENTATION

TREATMENTS ON QUALITY OF RED WINE

PREPARATION FROM PUNJAB PURPLE GRAPES

Thesis

Submitted to the Punjab Agricultural University

in partial fulfillment of the requirements

for the degree of

INTEGRATED MASTER OF SCIENCE (Hons.) in

MICROBIOLOGY (Minor Subject: Biochemistry)

By

Maninderjeet Kaur (L-2008-BS-09-IM)

Department of Microbiology College of Basic Sciences and Humanities

© PUNJAB AGRICULTURAL UNIVERSITY

LUDHIANA – 141 004

2013

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2

CERTIFICATE I

This is to certify that the thesis entitled, “EFFECT OF PRE AND POST

FERMENTATION TREATMENTS ON QUALITY OF RED WINE PREPARATION

FROM PUNJAB PURPLE GRAPES” submitted for the degree of Integrated Master of

Science (Hons.) in the subject of Microbiology (Minor subject: Biochemistry) of the Punjab

Agricultural University, Ludhiana, is a bonafide research work carried out by Maninderjeet

Kaur (L-2008-BS-09-IM) under my supervision and that no part of this thesis/dissertation

has been submitted for any other degree.

The assistance and help received during the course of investigation have been fully

acknowledged.

_______________________

Dr. G.S Kocher

Major Advisor

Microbiologist

Department of Microbiology

Punjab Agricultural University

Ludhiana-141004

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3

CERTIFICATE II

This is to certify that the thesis entitled, “EFFECT OF PRE AND POST

FERMENTATION TREATMENTS ON QUALITY OF RED WINE PREPARATION

FROM PUNJAB PURPLE GRAPES” submitted by Maninderjeet Kaur (Admn No. L-

2008-BS-09-IM) to the Punjab Agricultural University, Ludhiana, in partial fulfillment of the

requirements for the degree of Integrated Master of Science (Hons.), in the subject of

Microbiology (Minor subject: Biochemistry) has been approved by the Student’s Advisory

Committee along with Head of the Department after an oral examination on the same.

___________________________ ___________________________

(Dr. G.S. Kocher) (Dr. S.K. Soni)

Major Advisor External Examiner

Professor

Deptt. of Microbiology

Panjab University

Chandigarh

___________________________

(Dr. (Mrs.) Parampal Pal Sahota) Head of the Department

___________________________

(Dr. Gursharan Singh) Dean, Postgraduate Studies

Page 4: EFFECT OF PRE AND POST FERMENTATION TREATMENTS …...where India stands at 12 th position in its production. But, in terms of productivity, India has the highest productivity of 26.2

4

ACKNOWLEDGEMENTACKNOWLEDGEMENTACKNOWLEDGEMENTACKNOWLEDGEMENT

I would like to sincerely express my gratitude to all who have supported me through guidance, prayers and

encouragement to successfully complete a work of this kind. I am particularly thankful to the Lord God Lord God Lord God Lord God

AlmightyAlmightyAlmightyAlmighty for His mercy and grace upon my life.

First of all I pay homage to my Major Advisor Dr. G S KocherDr. G S KocherDr. G S KocherDr. G S Kocher, Microbiologist, Department of

Microbiology, Punjab Agricultural University, Ludhiana, who painstakingly edited this work and provided

constructive criticism for writing up this thesis. I really appreciate for his expert guidance, encouragement,

inspiration and advice throughout my research work. This work would not have been possible without her

guidance, support and encouragement. Under his guidance I successfully overcame many difficulties and

learned a lot.

I am also grateful to all the esteemed members of my advisory committee Dr.Dr.Dr.Dr. Maninder AroraManinder AroraManinder AroraManinder Arora,

Senior Food Microbiologist, Department of Microbiology, Dr.SuchDr.SuchDr.SuchDr.Sucheta Sharma, eta Sharma, eta Sharma, eta Sharma, Associate Professor,

Department of Biochemistry, Dr. (Mrs.) Parampal Pal Sahota, Dr. (Mrs.) Parampal Pal Sahota, Dr. (Mrs.) Parampal Pal Sahota, Dr. (Mrs.) Parampal Pal Sahota, Sr. Microbiologist cum Head, Department

of Microbiology, (Dean PG Nominee) for their able guidance, constructive suggestions and continuous

support. I express my sincere thanks to Dr. M I S Gill,Dr. M I S Gill,Dr. M I S Gill,Dr. M I S Gill, Sr. Horticulturist, Department of Fruit Science for

their requisite provision of the fruits they made possible, without which this study would have not been

possible.

I owe a lot to my father S. Amarjit Singh S. Amarjit Singh S. Amarjit Singh S. Amarjit Singh who encouraged and helped me at every stage of my

personal and academic life, and longed to see this achievement come true. I thank my mother Ranjit kaur Ranjit kaur Ranjit kaur Ranjit kaur

for her tender, loving care and compassion. Special thanks to my elder brother Amandeep Singh Amandeep Singh Amandeep Singh Amandeep Singh who make

my life joyful and providing the moral and emotional support I needed to complete my thesis.

As Life is incomplete without friends, so my greatest appreciation goes to my lovely friends

Shiveta Raina, Amandeep Sidhu, Harpreet Kaur, Ritu Didi Shiveta Raina, Amandeep Sidhu, Harpreet Kaur, Ritu Didi Shiveta Raina, Amandeep Sidhu, Harpreet Kaur, Ritu Didi Shiveta Raina, Amandeep Sidhu, Harpreet Kaur, Ritu Didi for supporting me in all my struggles and

frustrations during thesis writing.

My sincerest thanks to Harminder didi Harminder didi Harminder didi Harminder didi for their invaluable help, guidance and constructive ideas

in the laboratory. Thanks to my supportive friends and labmates, Jyoti BalaJyoti BalaJyoti BalaJyoti Bala, Anureet Brar and Pooja Didi Anureet Brar and Pooja Didi Anureet Brar and Pooja Didi Anureet Brar and Pooja Didi

who made the lab a friendly environment for working. I would also like to thanks Kewal Uncle Kewal Uncle Kewal Uncle Kewal Uncle and Ranbir Ranbir Ranbir Ranbir

Bhaji Bhaji Bhaji Bhaji for constantly helping me time to time.

I feel proud to be a part of PAU, Ludhiana where I learnt a lot and spent some unforgettable

moments of my life. I am also thankful to all members of the department.

Last but not least, I duly acknowledge my sincere thanks to all who love and care for me.

Everyone may not have been mentioned but none is forgotten.

_________________ ((((Maninderjeet KaurManinderjeet KaurManinderjeet KaurManinderjeet Kaur))))

Page 5: EFFECT OF PRE AND POST FERMENTATION TREATMENTS …...where India stands at 12 th position in its production. But, in terms of productivity, India has the highest productivity of 26.2

5

Title of the Thesis : Effect of pre and post fermentation treatments on

quality of red wine preparation from Punjab purple

grapes.

Name of the Student : Maninderjeet Kaur and Admission No. L-2008-BS-09-IM

Major Subject : Microbiology

Minor Subject : Biochemistry

Name and Designation : Dr. G.S. Kocher

of Major Advisor Microbiologist

Degree to be Awarded : Integrated Master of Science (Hons.) in Microbiology

Year of award of Degree : 2013

Total pages in Thesis : 69+ Annexure (iv) + Vita

Name of University : Punjab Agricultural University, Ludhiana 141004,

Punjab, India

ABSTRACT

The effect of pre and post fermentative treatments in production of red wine from

Punjab purple variety of grapes was evaluated. The prefermentation was optimized for skin

contact (0.25Kg/L of skin weight, temperature 20oC and incubation time 16 h) and enzymatic

treatment using combination of enzymes i.e. Amylase+pectinase+cellulase at 45oC for 6h that

produced 78.7 % clarification of juice. The latter was fermented by Saccharomyces cerevisae

strain 35 (5% v/v) at 25oC using 150 mg/100ml of DAHP producing 12.1% (v/v) of ethanol.

A 10% (v/v) of spent yeast inoculum was optimized for recycling of two successive fermentation batches producing significantly similar ethanol concentrations after

fermentation. Post fermentative storage of wine (at 15 oC) for 150 days freed the wine from

viable yeast cells but also led to the reduction of phenols along with decrease in % ethanol

levels. The free and total sulphur dioxide in the fresh yeast culture wine was 22.1 ppm and 8.2

ppm, respectively. The qualitative analysis of red wine w.r.t amino acids carried out by TLC

revealed the presence of Histidine/Arginine/Lysine, Threonine, Methionine/Alanine/Valine/

Tyrosine, and Methionine/valine. The prepared wines from Punjab purple under optimized

conditions with fresh and recycled yeast inocula were found to be of standard quality with

mean sensory scores of 65.9±8.01 and 63.3±8.52, respectively at 150 days of storage

compared to 56.2±9.47 of a commercial wine.

Keywords: Punjab purple, red wine, recycling, enzymatic treatment, sensory

___________________________ _______________________

Signature of the Major Advisor Signature of the Student

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6

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lwl AMgUrW dI vweIn 'pMjwb prpl' iksm au~pr KmIrIkrx qoN pihlw Aqy bwAd dy Asr dw mulWkx kIqw igAw [ KmIrIkrx qoN pihlW cmVI sMprk 0.25 iklo/lItr cmVI dy Bwr, qwpmwn 20°C Aqy qwp smW 16 GMty AwSwvwdI sI Aqy ieMzwiemYNitk ielwj ieMzwiem dy imSrx (AmweIlyz+pYktInyz+sYlUlyz) 45°C qwpmwn qy 6 GMty dy iesqymwl sdkw jUs 78.7% q̀k sw& kIqw igAw [ cmVI sMprk vwly dw KmIr sYkromweIisz sYrwivs 35 (5 pRqISq v/v) 25°C qwpmwn qy 150 imlIgRwm pRqI 100/imlI: fIeyAYcpI dw iesqymwl sdkw 12.1 pRqISq vwlI eIQwnol pYdw hoeI [ 10 pRqISq (v/v) KricAw KmIr eInokulm 2 smUh lgwqwr KmIrIkrx dIAW ivDIAW ausy Gxqw dI eIQynol pYdw krn leI AwswvwdI sI [ AMgUrW dI vweIn dy KmIrIkrx qoN bwAd dw BMfwr 15°C qwpmwn qy 150 idnW leI kIqw igAw ijs nwl AMgUrW dI vweIn nUM KmIr sYlW qoN mukq kr id`qw igAw pr nwl dI nwl PInolz Aqy eIQwnol dw pRqISq sqr G`t igAw [ AMgUrW dI vweIn iv`c Awjwd qy swrI slPrfweIAwksweIf dI mwqrw 22.1 pIpIAYm Aqy 8.2 pIpIAYm kRmvwr sI [ lwl AMgUrW dI Srwb dw guxnwqmk ivSlySx AmIno AYisf dy muqwibk tIAYlsI rwhIN kIqw igAw jo ik ihstIfwien/ArjInwien/lweIsIn, QRIEnwien, mIQIEnwien / AYlynwien/vYlylwien/Twieroswien Aqy mIQIEnwien/vYlIn lwl AMgUrW dI vweIn iv`c vYlwien dI hoNd drswauNdw hY [ imQy hlwqW au~pr 'pMjwb prpl' AMgUrW dI vweIn jo ik qwjw qy Krcy hoey ienokUlm qoN iqAwr krky 150 idn dy BMfwr leI r`KI geI sI [ ausdy svwd dy imAwrW au~pr guxv`qw mulWkx ivaupwrk lwl vweIn nwl kIqw igAw [ ijnHW dy guxv`qw AMk 65.9±8.01, 63.3±8.52 Aqy 56.2±9.47 kRmvwr sn [ mu`K Sbd: pMjwb bYNgxI, ieMzymYitk ielwz, lwl AMgUrW dI Srwb, KmIr auTwauxw, dubwrw

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7

CONTENTS

Chapter Topic Page

I. INTRODUCTION 1-3

II. REVIEW OF LITERATURE 4-22

III. MATERIALS AND METHODS 23-33

IV. RESULTS AND DISCUSSION 34-54

V. SUMMARY 55-56

REFERENCES 57-69

ANNEXURE i-iv

VITA

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CHAPTER I

INTRODUCTION

Grapes (Vitis spp.) are economically one of the important fruit species in the world

where India stands at 12th position in its production. But, in terms of productivity, India has

the highest productivity of 26.2 tonnes/ha among the grape producing countries (Anonymous

2010). Though grapes are used for table purposes and ready to serve drinks, the prime use of

grapes is for wine production. Grape wine is perhaps the most common fruit juice alcohol. As

much as 82% of the produce is used for wine preparation worldwide but we in India, utilize

just 2% of the produce for wine (Anonymous 2010). Henceforth, per capita consumption of

wine in India is a meager 7 ml compared to 60 and 50 litres in France and Italy, respectively

(Patil 2008). Because of the commercialization of the product for industry, the process has

received most attention of researchers.

Wine is an alcoholic beverage which is produced by fermentation of grape juice

through activity of Saccharomyces cerevisiae and other naturally occurring yeasts such as

Kloeckera apiculata, Hansenula anomala, Candida stellata, (Heard and Fleet 1986, Combina

et al 2005). Besides ethanol, wine contains a number of phenolics, organic acids, minerals,

vitamins etc. of fruit as well as microbial origin. These are responsible for the typical quality

of a wine (Kunkee and Gosewell 1996). Nowadays, wine is an integral component of the

culture in many countries, a form of entertainment in others, and a drink full of nutraceuticals

and health stimulating properties for others (Bisson et al 2002a). Red wine in particular is

known for antioxidant activities due to its phenols, lowering of blood cholesterol by its

resveratol, anti-inflammatory properties etc. (Duck et al 2008). It has been found that 75% of

these health stimulating phenolics reside in skin and seeds of grapes for which it is very

important that these are extracted in the juice destined for fermentation. This is the reason that

a prefermentation treatment in the form of skin juice contact needs to be standardized for its

time, temperature and associated malo-lactic fermentation (Marais and Rapp 1988, Staden et

al 2005).

Wine is one of the functional fermented foods and has many health benefits. These

include anti-ageing effects of red grape skins, improvement of lung function from

antioxidants in white wine, reduction in coronary heart disease, development of healthier

blood vessels in elderly people, reduction in ulcer –causing bacteria, destruction of cancer

cells by proteins present in red grape skins, prevention of stroke by keeping the arteries clean

owing to polyphenols present in red grape skin, decreasing ovarian cancer risk in women and

making the bones stronger. Many wines are made from fruits having medicinal value and

such wines have many additional benefits (Tapsell et al 2006).

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2

Most well designed population studies have demonstrated a ‘J curve' relationship

between wine consumption and the risk of cardiovascular diseases (Cleophas 1999, Maclure

1993, Marmot 2001). This indicates that people who do not drink alcohol at all and those who

consume more than 30 g/day of alcohol (approx. 2.5 standard drinks) have an increased risk

of death from all causes, higher blood pressure levels, as well as poorer liver function

(Marmot 2001). On the other hand, moderate alcohol intake (1-2 drinks/day) is associated

with a decreased coronary heart disease (CHD) risk in both men and women. One to two

glasses of red wine (with a meal) for men and 1 glass for women may help to fight heart

disease (Snyder 2005).

Indian wine industry is in its infancy and is restricted presently to Maharashtra,

Karnataka and Goa to some extent but is expected to grow by 25-30% between 2009 to 2012

(Patil 2008, Kocher et al 2009, 2011b). The main constraint in growth of wine industry is lack

of suitable varieties and dependence on imported wine producing yeasts. The selection of

suitable grape varieties having potential to make wines of high quality is a continuous type of

work in all the wine producing countries. This is of particular concern in India where varieties

suitable for wine production and adapted to local climatic conditions are lacking. In Punjab,

the only widely grown variety, Perlette is not recommended for wine. Hence, for the past 6

years, 7 grape varieties/hybrids viz., Perlette, Flame Seedless, Porton, Punjab Purple (H-516),

Muscat Hamburg, H-27 and Chasan B have been evaluated. Of these, Punjab Purple has been

recommended by Research Evaluation Committee, PAU for wine preparation at five liter

scale using indigenous strain Saccharomyces cerevisiae strain 35 (Kocher et al 2011b). This

process needs to be scaled up for possible commercialization of the technology.

In this regard, a number of pre-fermentation parameters need to be standardized such

as skin juice contact (as described earlier) and effect of pectinase treatment on the must. The

latter is an important treatment in terms of stability of the must, extraction of skin color and

clarity of the must (Espejo and Armada 2010, Kocher and Pooja 2011). Skin contact time, as

well as temperature at which the treatment is applied could be critical to the composition and

quality of juices and wine as they may be detrimental to wine quality due to increase in the

concentrations of constituents, such as certain phenolic compounds (Marais and Rapp 1988).

Among the prefermentative treatments, supplementation of nitrogen and phosphorous is

another very important fermentation parameter as grape juice is deficient in these salts. In this

regard, availability of Yeast Assimeable Nitrogen (YAN) in the must is very important to

prevent nitrogen stress, which can lead to incomplete fermentation of sugars and the

production of off-flavours in the wine produced, moreover, the nitrogen content of grape

juice affects both yeast cell growth and fermentation rate (Monteiro and Bisson 1992, Ugliano

et al 2007). A considerable research on optimization of fermentation parameters such as

temperature, pH, inoculum size, supplementation of nitrogen and phosphorus has been carried

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3

out in different studies (Erten et al 2006; Asli 2010).

Wines produced after alcoholic fermentation are termed raw/green wines, which are

stored/aged for an extensive period of time for maturation of flavours. This requires

standardization of storage temperature, humidity and light so that organoleptic characteristics

are improved (Jackson and Lombard 1993, Chang et al 2008). This is essential because it has

been found that an increased storage may decrease volatiles (Perez-Prieto et al 2003).

Similarly a very high humidity of 80% may lead to risk of contamination and high light

intensities result in undesirable flavour (Jackson and Lombard 1993, Chang et al 2008).

Keeping in view the paucity of information with regard to different pre and post

fermentation parameters for Punjab purple (Syn H 516) variety of grapes, the present study

was designed to accomplish following objectives-

1. Standardization of pre-fermentation ‘maceration’ process in terms of effective contact

of grape skin with juice.

2. To study the effect of nitrogen and phosphorus supplementation in the ‘must’ and

yeast recycling on quality of wine.

3. Effect of storage on oragnoleptic properties of wine.

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CHAPTER II

REVIEW OF LITERATURE

The recent review of literature on different aspects of wine production from grapes is

presented under the following headings:-

2.1 Wine as a beverage

2.2. Grapes

2.2.1 Chemical characteristics of Grapes

2.2.1.1 Total soluble solids

2.2.1.2 Titrable acidity

2.2.1.3 Volatiles

2.3 Yeast

2.4 Pre-fermentation treatment

2.4.1 Effect of skin contact

2.4.2 Effect of enzymatic treatment

2.5 Ethanol fermentation

2.6 Factors affecting fermentation

2.6.1 Effect of Temperature

2.6.2 Effect of pH

2.6.3 Effect of initial sugar level

2.6.4 Effect of Nitrogen and Phosphorus supplementation

2.7 Post fermentative treatments

2.7.1 Racking

2.7.2 Effect of fining agents

2.7.3 Ageing

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5

2.1 Wine as a Beverage

Wine is one of the world’s most popular alcoholic beverages. It has been produced

and consumed throughout history for cultural, economical, social, religious, and, more

recently, health reasons. Wine produced from grapes is constantly being investigated for its

health benefits. The increased popularity of wine has resulted in an enormous upsurge in

prices of the world’s finest wines, a scarce commodity under the best of circumstances.

According to FAO data (2010), the leading grape producing countries in the world in terms of

production are China (8,651.83 thousand tons), Italy (7,787.80 thousand tons), USA (6,777.73

thousand tons) and Spain (6,107.20 thousand tons) and India’s high productivity in grape has

made it to reach 18th position in the world as far as production (total world production

7,116.25 thousand tons) is concerned.

Wine, a fermented undistilled alcoholic beverage is produced by anaerobic

fermentation of grape sugars to ethanol by the wine yeast (Amerine and Ough 1980, Joshi et

al 2011). The ability to produce palatable effervescent beverage by alcoholic fermentation of

natural fruit juices is a demonstration of inherent ingenuity of man. The nutritional role of

wine is important since its average contribution to total energy intake is estimated to be 10 to

20% in adult males (Macrae et al 1993). During the past few decades, grapes are the main

fruits that have been used for wine production. Traditionally, red wine is produced from grape

varieties that have black or red color and the fermentation is carried out on the skin using

standard wine yeast (Amerine and Ough 1980).

Despite that, several studies have investigated the suitability of other fruits as

substrates for the purpose of wine production (Joshi and Bhutani 1991, Okunowo et al 2005).

Moreover, the non-availability of grapes, which is usually the fruit of choice for wine

production in the tropics, has necessitated the search for alternative fruit source in tropical

countries (Alobo and Offonry 2009). A number of secondary metabolites including

polyphenols (anthocyanins, flavonoids etc.) that are key determinants of wine quality endow

it with antioxidant potential (Chen et al 2009).

The main volatile compounds in wines are secondary products arising from alcoholic

or malolactic fermentation; their presence in young wines, whites, roses and reds, is a quality-

defining factor (Ferrarese 1987, Ribereau-Gayon et al 1982). Wine polysaccharides play an

important role in wine technology, either for their sensory characteristics, their implications

during fermentation or their detrimental role in filtration (Ayestaran et al 2004). Red wine is

characterized by the presence of phenolic compounds that contribute to organoleptic

characteristics such as color, taste, astringency and bitterness and their capacity for aging

(Ribereau-Gayon et al 2006).These compounds occur naturally in grapes of red Vitis vinifera

cultivars and winemakers aim to extract them into the wine through various methods of

maceration. Phenolic compounds are extracted from skin and seeds, and their extraction is

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6

influenced by winemaking procedures. Macerating enzymes may help in phenolic extraction

and, at the same time, may modify the stability, taste and structure of red wines, because it is

not only anthocyanins that are released from skins, but also tannins bound to the cell walls

(Bautista-Ortín et al 2007). The advantage of cryomaceration treatments over maceration at

20 °C was in a significantly lower content of extracted phenols, which are subject to oxidation

and negatively contribute to wine quality (Radeka et al 2008).

Red wine possesses several potentially heart-healthy mechanisms, including a

favorable effect on blood clotting, endothelial function and serum lipids (most notably the

ability to raise levels of HDL “good” cholesterol). The cardio-protective effects observed in

red wine drinkers are thought to be attributed at least in part to moderate alcohol intake, but

especially due to the polyphenolic compounds red wine possesses, most notably, a flavonoid

called resveratrol. Laboratory studies have revealed that resveratrol possesses several cardio-

protective actions as well as cancer-protective effects (Snyder 2005).

The fermentation of wine is known to be a complex process with various ecological

and biochemical processes involving yeast strain (Fleet 2003). The fermentation for the

elaboration of beverage is known to depend on the performance of yeast to convert the sugars

into alcohol and esters. Besides, the different species of yeast that develop during

fermentation determine the characteristic of the flavour and aroma of the final product. Also,

because different fruits have different composition, there is the need for yeast strains to adapt

to different environments, such as sugar composition and concentration of acetic acid (Fleet

2003, Duarte et al 2010). Although, tropical fruits and several yeast strains have been

screened for their suitability in wine production, most studies have either focussed only on the

suitability of the fruits or the yeast strains. Infact, the winemaking process can have a large

influence on the final attributes of a red wine as the winemaker has different tools and

enological practices at his disposal to alter the final properties of the wine (Jackson 2000a).

2.2 Grapes

The majority of grapes grown throughout the world are utilized for winemaking. In

all wine producing countries, wines are made from varieties of the Vitis vinifera grapes.

Different grape varieties are used for the preparation of red wine. But, historically grapevine

(Vitis vinifera L.) is grown mostly for wine making in the world over. However, each grape

variety will result in different wine quality (Tontemsup 1996) due to their unique

characteristics.

Approximately 75,866 square kilometers of the world are dedicated to grapes and

71% of world grape production is used for wine, 27% as fresh fruit, and 2% as dried fruit

(FAO 2010). The area dedicated to vineyards is increasing by about 2% per year. There are no

reliable statistics that break down grape production by variety. It is believed that the most

widely planted variety is ‘Sultana’, also known as Thompson Seedless, with at least

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7

3,600 km2 (880,000 acres) dedicated to it. The second most common variety is Airen. Other

popular varieties include Cabernet Sauvignon, Sauvignon blanc, Cabernet Franc, Merlot,

Grenache, Tempranillo, Riesling and Chardonnay.

In India, Maharashtra ranks first in wine grape cultivation with an area of 8,000 acres,

which formed a proportion of 91.95 per cent in the country’s wine grape area during the year

2007. It is one of the important states growing different varieties of wine grape. Cultivation of

wine grape is extensively carried out in the belts of Nashik, Pune, Sangli, Solapur, Latur,

Buldhana, Osmanabad and Ahmadnagar districts (Kale 2007). In PAU, Punjab Purple, a

colored grape variety was evaluated for red wine production over a period of three years. A

consistent ethanol production of about 10-11% (v/v) with a mean recovery of 62.4 % was

observed. The red wine produced was found to be of standard quality (mean score of 63.5 out

of 80) on the basis of sensory evaluation and had phenolics content of 2496 mg/L which

endows it with a high antioxidant potential (Kocher et al 2011b).

Grape quality is primarily influenced by specific vineyard practices, climate, and

grape varieties (Jackson and Lombard 1993) and thus the potential of the grapes to give a high

quality wine is both evaluated subjectively (e.g. taste, aroma, and visual inspections) and

objectively from compositional analyses of the grapes (Krstic et al 2003). Red winemaking

begins when grapes are harvested and processed at the winery. The grapes for wine

production are harvested at an appropriate stage of maturity whereby particularly important

are the concentrations of sugars and acids, which are major constituents of the juice and have

an important impact on its fermentation properties (Fleet 1998, 2001). For dry or table wines,

grapes of high acidity and moderate sugar content are desirable, while grapes with high sugar

content and moderately low acid are required for sweet or dessert wines.

Grapes contain 0.3%-0.5% of various organic acids, such as tartaric acid and malic

acid, as well as some free sugars and vitamins (Duck et al 2008). Grape juice concentrate is

also used to make wine in many locations that do not or cannot grow grapes (Morris et al

1996). This is because grape juice concentrates can be easily stored, allowing winemakers to

produce wine throughout the year. Grapes are good source of water (82%), carbohydrates

(12–18%), proteins (0.5-0.6%), and fat (0.3–0.4%). Additionally, the grape contains

significant amounts of potassium (0.1-0.2%), vitamin C (0.01–0.02%), and vitamin A (0.001–

0.0015%) and a small amount of calcium (0.01–0.02%) and phosphorus (0.08–0.01%).

The dietary consumption of grape and its products is associated with its medicinal

properties of grape as its constituents are antioxidant, anti-carcinogenic, immunomodulatory,

antidiabetic, anti-atherogenic, neuroprotective, anti-obesity, anti-aging and anti-infection. In

particular, several biological activities of resveratrol (3, 5, 40-trans-trihydroxystilbene), a

major compound extracted from the skin and seeds of grape is a natural phytoalexin

abundantly found in grapes and red wine, which has potent antioxidant property (Yadav et al

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2009).

2.2.1 Chemical Characteristics of Grapes

2.2.1.1 Total soluble solids

Soluble solids can be measured directly from the refractive index and refractometers

are calibrated to give per cent total soluble solids (oBrix) values directly. In regard to the

sugar content, grapes contain glucose and fructose in similar amounts, while sucrose

contributes less than 1% and the starch concentration is practically negligible (Nelson 1985,

Conde et al 2007). However, a few high-sucrose content cultivars have been characterized in

Vitis rotundifolia and hybrids between V. labrusca and V. vinifera (Liu et al 2006). Cultivars

with more fructose than glucose can be harvested earlier due to the greater sweetness of this

sugar compared to glucose. As the fruit becomes mature, the fructose to glucose ratio

increases (Winkler et al 1974). Grape sugar content varies depending on the species, variety,

maturity, and health of the fruit. V. vinifera generally reaches a sugar concentration of 20% or

more at maturity. Immature berries contain very little sugars (2.0 mg/g) such as glucose and

fructose, as the berry matures, the total sugar concentration increases to 150-300 mg/g. Grape

sugar content is critical to yeast growth and metabolism. The concentration of glucose and

fructose on grape surfaces increases during berry ripening (Ribéreau-Gayon et al 2000). Total

sugar content on grape skin represents, on an average, 10 ± 5% of the equivalent content in

juice; however, the concentration of sugars associated with skin varies with the grape variety

(Varandas et al 2004). Wine grapes also tend to be very sweet: they are harvested at the time

when their juice is approximately 24% sugar by weight. By comparison, commercially

produced "100% grape juice", made from table grapes is usually around 15% sugar by weight

(Wine grapes 2010). The concentration of sugars which are major constituents of the juice

also has an important impact on its fermentation properties (Fleet 1998, 2001).

2.2.1.2 Titrable acidity

Grapes contain appreciable amounts of various organic acids. Malic acid may

constitute about half of the total acidity of grapes and wine. The malic acid concentration

decreases when grape mature, especially during hot period. Malic acid is one of the indicators

for determining harvest date. This acid leads to a flat taste into wine and this acid

transformation is necessary for wine with high content of malic acid. Tartaric acid is the other

major grape acid. This acid does not decrease during grape ripening but it is metabolized by

few skin microorganisms (Ough and Amerine 1988). Wines often are cooled near the end of

maturation to enhance early tartrate precipitation and avoid crystal deposition in the bottle

(Boulton et al 1996).

The acidity level is a very important quality factor in both table grapes and those used

for wine production. Consumer acceptance of table grapes and grape juice is strongly

influenced by the sweetness to acid balance (Winkler et al 1974). Acidity also determines the

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suitability of the fruit for wine making. Excessive tartness correlates with low sugar levels

which give poor quality wine (Ruffner 1982). However, in warm climates, grapes with a low

pH and high acidity levels are generally desired for table wines. The brilliance and red

intensity of colored grapes is greater at moderate to high acidity and low pH. With low acidity

and high pH, they tend to be bluish and dull (Winkler et al 1974).

Organic acids are present in small amounts compared to sugars. However, they

contribute significantly to the overall taste (Nelson 1985). In general, organic acids do not

exceed more than 1% of the total juice weight, with tartaric acid usually the most important

acid followed by malic, citric, succinic, and other acids. Organic acids enhance grape flavour

and help to improve mouth-feel of grape (Liu et al 2006).

2.2.1.3 Volatiles

Besides sugars and organic acids, which have been investigated for the last few

decennia, phenolic compounds are extremely important constituents of grapes. Grape is a

phenol-rich and its phenolics are mainly distributed in the skin, stem, leaf and seed of grape,

rather than their juicy middle sections. Total concentration of phenolic compounds is about

2178.8, 374.6, 23.8, and 351.6 mg/g GAE (gallic acid equivalent) in seed, skin, flesh, and

leaf, respectively (Pastrana-Bonilla et al 2003). The compounds mainly include

proanthocyanidins, anthocyanins, flavonols, flavanols, resveratrols and phenolic acids

(Makris et al 2008).

Phenols, which are the principle source of wine color, mouth-feel and taste, make an

important contribution to wine quality (Gawel 1998). The main phenolic compound groups

present in grapes are the anthocyanins and flavan-3-ols. The anthocyanins are the red

pigments responsible for the colour of red grape skins and wine. The two main flavan-3-ol

monomers in grapes and wine are catechin and epicatechin (Gawel et al 2000). The

concentration of grape phenolics increases throughout berry development.

Phytochemicals in grapes are mostly phenolic compounds. According to their

molecular structure, the phenolic compounds are divided into four classes: one phenolic ring

(cinnamic acids and benzoic acids), two phenolic rings (stilbenes), three rings (anthocyanins,

flavonols and flavan-3-ols) and complex ring (ellagic acids) (Hartle et al 2005). Grape skins

contain abundant, widely varied phenolics. These phenolics play an important role in the

sensory properties and nutrition of berries and wines. Many studies demonstrated that these

phenolics could reduce the incidence of serious chronic diseases such as cancer and

cardiovascular diseases, due to their antioxidant abilities (Hartle et al 2005, Pezzuto 2008, Xia

et al 2010, Kocher et al 2011b).

2.3 Yeast

Yeasts occur as natural flora on the surface of grapes. Consequently, grapes are a

primary source of yeasts associated with wine fermentation. During alcoholic fermentation,

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yeasts species and strains within the genera Hanseniaspora, Candida, Metschnikowia, Pichia

and sometimes Kluyveromyces grow during the early stages, but eventually die off due to

toxicity of the increasing concentration of ethanol, leaving Saccharomyces cerevisiae or

Saccharomyces bayanus as the dominant species to complete the fermentation (Fleet and

Heard 1993, Fleet 1998, 2001, Pretorius 2000, Bisson and Block 2002). Saccharomyces

cerevisiae and S. bayanus have become universally accepted as the principal wine yeasts.

Species that have been investigated for wine production thus far include those from the

Candida, Kloeckera, Hanseniaspora, Zygosaccharomyces, Schizosaccharomyces,

Torulaspora, Brettanomyces, Saccharomycodes, Pichia and Williopsis genera (Jolly et al

2006).

S. cerevisiae strains are recognized as GRAS and are normally used in human diets.

The protein content of yeasts rarely exceeds 60%, but yeasts have a reasonable concentration

of essential amino acids such as lysine, tryptophan and threonine. Yeasts are also rich in

vitamins (B group), and their nucleic acid content ranges from 4 to 10%. Yeasts, being larger

than bacteria, their size facilitate their easy isolation and separation. However, the specific

growth rate of yeasts with a generation time of two to five hours is relatively slow, compared

to that of bacteria (Boze et al 1992).

The growth of yeasts that occur naturally in grape juice has been quantitatively

examined during the fermentation of four wines that were inoculated with Saccharomyces

cerevisae. Although S. cerevisae dominated the wine fermentations, there was significant

growth of the natural species Kloeckera apiculata, Candida stellata, Candida colliculosa,

Candida pulcherrima, and Hansenula anomala (Heard and Fleet 1985). The number of

different species, as well as their endurance during alcoholic fermentation, is conditioned by

both the temperature of the must and the temperature during fermentation. These changes

determine the chemical and organoleptic qualities of the wine (Fleet and Heard 1993).

Yeasts are primarily responsible for the alcoholic fermentation of grape juice into

wine (Combina et al 2005). They originate from the flora of grapes and winery equipment and

from added starter cultures, if used (Fleet 2003). Wine fermentation is either performed

conventionally without inoculation or by the addition of selected wine yeast into grape juice.

In conventional wine making, natural (spontaneous) alcoholic fermentation of grape juice is

conducted by a sequence of different yeast species. At the beginning, non- Saccharomyces

yeasts, Kloeckera (teleomorph Hanseniaspora) and Candida in particular, initiate the

alcoholic fermentation of grape juice. These yeasts progressively die off with an increase in

ethanol concentration, and leave more ethanol tolerant Saccharomyces (S.) cerevisiae to

complete the fermentation (Ciani et al 2006, Clemente-Jimenez et al 2005). Infact, the quality

of wine is a direct consequence of the evolution of the micro-flora of the must during

fermentation. Yeasts play a central role in the fermentation process during winemaking.

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Saccharomyces cerevisiae, ‘‘the wine yeast’’, is the most important species involved in the

alcoholic fermentation (Fleet and Heard 1993). The non-Saccharomyces yeasts contribute to

the fermentation since they can reach populations of about up 106–10

7 cells/ml, affecting both

the kinetics of growth and metabolism of Saccharomyces (Lema et al 1996). Hence, the

selection of the good strain having desirable properties is a prerequisite for the quality of wine

production (Degree 1993).

It was found that the production of red wines using selected yeasts under the

conditions tested contributed in improving the physical-chemical parameters of the wines

obtained, reducing some undesirable components in the finished product, like the volatile

acidity, ethyl acetate, methanol and acetaldehyde, when compared to the artisanal wine. The

addition of the yeasts promoted a decrease in the fermentation time, a good alcoholic yield,

demonstrating their dominance in the must, tolerates the sulfite added and the high alcoholic

grade (Dorneles et al 2005).

The diversity and the composition of the yeast also significantly contribute to the

sensory characteristics of wine. The growth of each wine yeast species is characterized by a

specific metabolic activity, which determines concentrations of flavour compounds in the

final wine. However, it must be underlined that, within each species, significant strain

variability has been recorded. The wide use of starter cultures, mainly applied to reduce the

risk of spoilage and unpredictable changes of wine flavour, can ensure a balanced wine

flavour, but it may also cause a loss of characteristic aroma and flavour determinants. Thus,

the beneficial contribution from the yeast increases when starter cultures for winemaking are

selected on the basis of scientifically verified characteristics and are able to complement and

optimize grape quality and individual characteristics (Romano et al 2003).

Yeasts impact on the color and pigment profiles of wines, especially red wines. Such

influences vary with the strain of S. cerevisiae and need to be considered in the portfolio of

properties when selecting yeasts for starter culture development (Medina et al 2005,

Hayasaka et al 2007). The impact of non-Saccharomyces yeasts on wine color is however still

relatively unexplored.

Keeping in view, significant role of yeasts in development of wines, strain selection

has become very important, as not all strains within a species necessarily show the same

desirable characteristics. For example, significant variability is found in the formation of

undesirable biogenic amines amongst strains within some non- Saccharomyces yeast species

(Caruso et al 2002). Innovative oenological traits can be introduced or exchanged by

hybridizing strains belonging to different species but with a sufficient genetic affinity for

them to mate. Interspecific Saccharomyces hybrids were found to be stable, vigorous and

possessing the parental oenological traits in novel and interesting combinations (Raineri and

Pretorius 2000).

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Recently, interspecific hybrid strains between Saccharomyces species have been

described as involved in wine fermentations. Wine yeast hybrids between the species S.

cerevisiae X S.kudriavzevii and S. cerevisiae X S. bayanus as well as a triple hybrid S.

cerevisiae X S.kudriavzevii X S. bayanus were characterized. Several strains selected as

commercial wine yeasts also resulted from Saccharomyces hybrids (Gonzalez et al 2006,

Bradbury et al 2006). Therefore, hybrid strains appear as well adapt to the stress conditions

(Low pH, high sugar concentration and ethanol content) occurring during wine fermentations

(Belloch et al 2008), and their enological characterization confirms their interesting properties

according to the new trends in winemaking (Gonzalez et al 2007).

2.4 Pre-fermentation treatment

2.4.1 Effect of skin contact

Grape skin-contact with juice is an effective technique which can be standardized to

extract additional aroma compounds, such as volatile phenols, flavonoids, terpenes etc. from

grape skins for wine production that enhance the aroma intensity and quality of wines from

cultivars (Hernanz et al 2007). The skin contact technique is thus the most important process

that characterizes the elaboration of rose and red wines. Phenolic compounds from grapes and

wines are also receiving increasing interest because of diverse health benefits attributed to

them (Moreno et al 2007, Parker et al 2007, Katalinic et al 2010). In addition, skin contact

technique frequently displays higher colour intensity and sensitivity to oxidation of white

wines (Cheynier et al 1989, Macheix et al 1991). The total concentrations of free and bound

aroma compounds of the wine increased considerably with the skin contact. The results of the

gas chromatographic data and sensory evaluation showed that skin contact treatment

improved the aroma intensity (particularly terpene-like character) and wine quality

(Cabaroglu and Canbas 2002).

Skin-contact may, however, also result in the extraction of skin compounds

detrimental to wine quality, such as certain phenols and acetamides. The temperature during

skin contact is therefore of critical importance. Harvesting during the night, cooling of the

grapes before or after crushing and skin contact at low temperatures has been found to benefit

the production of wines with higher varietal qualities. Marais and Rapp (1988) reported that

wines produced from juice subjected to low temperature skin-contact are generally of a higher

quality than those wines produced from the free-run juice or juice subjected to skin-contact at

elevated temperatures.

Skin contact by maceration has been used to increase the aroma in white varietal

wines through the extraction of aromatic compounds and nonvolatile sugar-bound glycosidic

conjugates (Selli et al 2003). Further, there is reduction in titrable acidity of the macerated

musts which is due to tartaric acid neutralization by the potassium liberated from the skins

(Ribereau-Gayon et al 2006). It has been found that the composition and organoleptic

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properties of red wine are predominantly affected by maceration and the extraction of grape

derived phenolic components and hence their subsequent reactions in wine (Basha et al 2004,

King et al 2003, Sims and Bates 1994).

2.4.2 Effect of Enzymatic treatment

Amylase, pectinase and cellulase are the common enzymes used for food purposes

such as clarification of juices and beverages, starch and cellulose hydrolysis etc. These

enzymes account for approximately 20% of the world enzyme market (Mantyla et al 1998).

The first enzymes used in enology were pectinases but, recently, enzyme companies have

modified the pectinase preparations (which mainly contain polygalacturonase, pectin esterase

and pectin lyase activities) by adding small amounts of cellulase and hemicellulase in order to

achieve a more complete breakdown of the cells and to enhance color extraction (Parley 1997,

Gil and Valles 2001, Calre et al 2002). Infact, enzymes are used to increase the grape must

yield during pressing, facilitate the settling of musts, and improve clarification and filtration.

The principal enzyme groups used in winemaking are pectinase, cellulase, hemicellulase,

oxidoreductase, protease and β-glycosidase. Evidently, the enzymatic preparations and their

principal and secondary activities are key factors in the results obtained in the products

(Pimenta-Braz et al 1998, Guerin et al 2009). Commercial pectic enzyme preparations are the

extracellularly produced in controlled fermentations by pure, genetically engineered food

grade strains of Aspergillus niger and/or Trichoderma longibrachiatum fungi.

Pectinase enzyme preparations have only been commonly used in wine production

since the early 1970’s, and mostly to improve juice yield from crushed grapes, and to

facilitate clarification of juice. The addition of exogenous pectinase enzymes is beneficial

because although they occur naturally in the fruit, they exist in such small quantities that they

are of little practical value over the short time and under the conditions of the must and juice

handling processes (Felix and Villettaz 1983).

Enzymes used in must treatments are related to skin maceration as an additional and

complementary process. Commercially available enzymes have been widely used in the

oenological industry in wine- producing countries to improve important characteristics of

wines, such as aroma and color. Furthermore, enzymes are used extensively in the fruit-

processing industry and other food sectors (Kashyap et al 2001). The use of pectolytic

enzymes has been shown to be suitable to improve the extraction of colour in red wines

(Revilla and Jose 2003, Bautista-Ortin et al 2005), aroma compounds (Canal-Llauberes 1990,

Castro-Vazquez et al 2002, Cabaroglu et al 2003) and soluble polysaccharides (Ayestaran et

al 2004, Doco et al 2007) from the skins and pulp of the grapes.

Among a number of studies on enzymatic treatment of grape must, a commercial

pectinase from Aspergillus niger containing various polysaccharases has been found to clarify

the white grape juice to an extent of 98-99% and also degrade the grape mash by 25- 30%.

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Grapes of three white cultivars treated with a commercial pectic enzyme preparation have

revealed that pectic enzyme treatment increases the higher alcohols, free hydroxycinnamic

acids and volatile phenols, whereas amounts of most esters, herbaceous alcohols and

hydroxycinnamate derivative esters get reduced. When tasted by an expert panel, differences

were reported in sensory characteristics, with wines from untreated judged of higher quality

than those from treated grapes (Lao et al 1997).

The effect of two commercial pectolytic enzymes using “musts” from sun-dried

grapes of the Pedro Ximenez variety on oenological parameters before and after enzyamatic

treatments with pre-fermentative maceration at room temperature for three hours has been

reported. It was found that resulting wines vary significantly in total soluble solids (OBrix)

and in the final sensorial controls. The enzyme treatment showed no effect on the total content

of polyphenols and other chemical characteristics. A higher qualitative level has been

reported with regard to aroma and gustative quality. The results also demonstrated that total

juice yield improved after enzyme addition together with maceration (Espejo and Armada

2010).

2.5 Ethanol Fermentation

The alcoholic fermentation is the primary fermentation, where yeasts transform

sugars in grape juice (mainly glucose and fructose) into ethanol (the main metabolite of wine)

and carbon dioxide. This process can be conducted either as an indigenous/wild fermentation,

or as an induced /seeded fermentation. With indigenous fermentation, yeasts resident in the

grape juice initiate and complete the fermentation. With seeded fermentation, selected yeast

strains, generally those of Saccharomyces cerevisiae or Saccharomyces bayanus, are

inoculated into the juice at initial populations of 106-107 cells/mL.

One molecule of glucose or fructose yields two molecules each of ethanol and carbon

dioxide. The theoretical conversion of 180 g of sugar into 88 g of carbon dioxide and 92 g of

ethanol means that yield of ethanol is 51.1% on a weight basis. In model fermentation starting

about 22 to 24 % sugar, 95 % of the sugar is converted into ethanol and carbon dioxide, 1% is

converted into cellular material, and the remaining 4% is converted to other end products.

This percentage may vary depending upon inoculum size, fermentation temperature and

nutrient availability (Boulton et al 1996). Fermentations are initiated by the growth of various

species of Candida, Debaryomyces, Hanseniaspora ,Hansenula, Kloeckera, Metschnikowia,

Pichia, Schizosaccharomyces, Torulaspora, and Zygosaccharomyces. Their growth is

generally limited to the first two or three days of fermentation, after which they die off.

Subsequently, the most strongly fermenting and more ethanol tolerant species of

Saccharomyces take over the fermentation.

Saccharomyces cerevisiae is used to ferment grape musts in strictly anaerobic

conditions, subjected to a prefermentative treatment of skin maceration and following a short

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aeration after 48 h of fermentation. It has been reported that the short aeration has no

significant effect on the unsaturation index of the cellular fatty acids, although it increases the

ergosterol/phospholipid ratio. This is reflected by an increase in the growth rate, viability and

fermentative capacity of the yeasts (Fleet and Heard 1993).

The risk of stuck fermentation and the development of several wine faults can also

occur during this stage which can last from 5 to 14 days for primary fermentation and

potentially another 5 to 10 days for a secondary fermentation. Fermentation may be done in

stainless steel tanks, which is common with many white wines like Riesling, in an open

wooden vat, inside a wine barrel and inside the wine bottle itself as in the production of many

sparkling wines (Robinson 2006, Kunze 2004).

Fermentation of the juice was traditionally conducted in large wooden barrels or

concrete tanks, but most modern wineries now use sophisticated stainless steel tanks with

facilities for process management. However, some premium-quality white wines (e.g.

Chardonnay) may be fermented in wooden (oak) barrels. White wines are generally fermented

at 10-18oC for 7-14 days or more, where the lower temperature and slower fermentation rate

favour the retention of desirable volatile flavour compounds (Robinson 2006).On the other

hand, red wines are fermented for about 7 days at 20-30oC, where the higher temperature is

necessary to extract colour from the grape skins. In winemaking the temperature and speed of

fermentation is an important consideration as well as the levels of oxygen present in the must

at the start of the fermentation. There are number of factors which affect yeast fermentation

performance like yeast strain employed, fermentation temperature, media composition, pH,

substrate concentration, mode of substrate feeding, osmotic pressure, ethanol concentration,

membrane composition etc (D’ Amore 1992). Some of these important factors are reviewed

below:-

2.6 Factors affecting fermentation

2.6.1 Effect of Temperature

Temperature is one of the most important factor that strongly affects the fermentation

as it directly affects the microbial ecology of the grape must and the biochemical reactions of

the yeasts. Also the number of different species, as well as their endurance during alcoholic

fermentation, is conditioned by both the temperature of the must and the temperature during

fermentation. These changes determine the chemical and organoleptic qualities of the wine.

Some strains are predominant at low temperatures while others at high ones (Fleet and Heard

1993).

The influence of elevated temperatures from 10 to 25°C at 5°C intervals on yeast

growth and fermentation products have been studied in mixed cultures of Kloeckera

apiculata and Saccharomyces cerevisiae in grape juice. In these experiments carried out at 10

and 15°C, K. apiculata grew and survived longer compared to trials conducted above 20°C. In

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most cases, higher temperatures i.e above 25°C stimulated the production of higher alcohols

but lowered the formation of esters and acetaldehyde (Erten 2006).

Temperature not only affects the fermentation but also the yeast metabolism, and

results in the formation of secondary metabolites such as glycerol, acetic acid, succinic acid,

etc. which determines the chemical composition of the wine (Lafon-Lafourcade 1983). It is

well known that fermentation at 35oC is very restrictive and the effect of higher temperatures

is a premature end of fermentation, which means that fermentation is incomplete and the

ethanol concentration is low (Larue et al 1980).

Temperature can affect the sensitivity of yeast to alcohol concentration, growth rate,

rate of fermentation, viability, length of lag phase, enzyme and membrane function etc.

Because yeast strains differ in response to temperature, the optimum temperature for

vinification can vary widely. A mixed response to fermentation temperature (15- 35°C) on

mixed strain population of Saccharomyces cerevisae has been observed by Torija et al (2001)

whereby alcohol yield was higher at lower temperature while at higher temperature secondary

metabolites were increased.

White wines are often fermented in the range of 10- 20°C. Nevertheless, some

European wineries still prefer fermentation temperatures between 20 and 25°C. As yeast

strains differ in response to temperature, the optimum temperature for vinification can vary

widely (Jackson 2000b). With the effective control of fermentation temperature by the wine

industry, low temperature alcoholic fermentations are becoming more frequent with the aim

to produce white and rose wines with more pronounced aromatic profile. Wines produced at

low temperatures (10-15ºC) are known to develop certain additional characteristics of taste

and aroma (Llauradó et al 2002, Torija et al 2003).

Typically, white wine is fermented between 64-68°F (18-20°C) though a wine maker

may choose to use a higher temperature to bring out some of the complexity of the wine. Red

wine is typically fermented at higher temperatures up to 85°F (29°C). Fermentation at higher

temperatures may have adverse effect on the wine in stunning the yeast to inactivity and even

"boiling off" some of the flavors of the wines. Some winemakers may ferment their red wines

at cooler temperatures, more typical of white wines, in order to bring out more fruit flavors

(Robinson 2006). Further, increasing of fermentation temperature from 15 to 30°C enhances

wine color, reduces herbaceous flavor, increases black current flavor and increases perceived

acidity.

2.6.2 Effect of pH

pH of the fruit wines throughout the period of fermentation ranges from 3.0 to 4.8.

The pH strongly affects the malolactic activity of the cell. The rate of malic acid degradation

is highest at pH 3.2- 3.4. According to Fleet (1998), pH directly affects wine stability. This

may be due to the fact that at a pH close to neutral (7.0) most micro organisms like bacteria

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and molds including some yeasts become more active for fermentation and subsequent

spoilage of wine, whilst a pH of 3.5 eliminates most of the microbes, and favors only few of

the micro organisms for fermentation. Yeasts can grow in a pH range of 4 to 4.5 and molds

can grow from pH 2 to 8.5, but favour low pH (Mountney and Gould 1988).

Yeast cell growth rate and grape juice fermentation rate have been shown to be

dependent on initial Brix and pH as well as on fermentation temperature. Variation between

pH 3.5 and 4.0 caused small but significant fermentation rate changes with more variation at

lower pH. Optimum fermentation rates for grape juice occur between 15 and 20° initial Brix,

and so does optimum yeast growth rate with these media. Temperature interactions with pH

have been demonstrated on rate of fermentation and yeast growth rates. The lower the pH

with increasing temperature, greater effects are observed on rate of fermentation and rate of

yeast growth (Ough 1966).

Grape juice pH largely determines the pH of the wine after fermentation. High wine

pH has a negative impact on wine colour, stability and taste (Somers 1977). Adjustment of pH

with tartaric acid during vinification is routinely applied to protect against such impacts

whereby the aim is generally to bring pH to 3.0-3.3 for white wines and to 3.3-3.5 for red

wines (Godden and Gishen 2005).

pH also plays an important role in aging, clarifying or fining. As the strength of the

relative charge of suspended particles decreases in the wine, the pH of the wine increases. At

high pH, organic protein fining agents may possess a positive charge insufficient to bind to

the negatively charged particulates, thus potentially increasing the turbidity of the wine. This

phenomenon is called "overfining" (Rotter 2008).

The effect of the interaction between pH (2.9-3.5), alcohol concentration (12.5-14.5%

v/v) and wine matrix (Chardonnay, Grenache blend and Cabernet Sauvignon) on malolactic

fermentation (MLF) induced by two commercially available directly inoculated Oenococcus

oeni starter cultures has been reported while wine matrix has greatest impact on the rate of

MLF, it is followed by pH and alcohol; the matrix effect was shown to be significantly

modified by pH and the bacterial culture (Paul and Hoger 2003).

2.6.3 Effect of initial sugar level

Sugar is the main substrate for fermentation of fruits juice into alcohol (Keller 2010);

although, other food nutrients such as protein and fats can be broken down by some micro

organism in some cases where sugar is limited, but as long as sugar is present yeast cells will

continue the process of fermentation until other factors that affect the growth of yeast become

unfavourable (Dickinson 1999). According to Garrison (1993) sugars are the most common

substrate of fermentation to produce ethanol, lactic acid, hydrogen and carbon dioxide.

The concentration of fermentable sugars in grape musts ranges between 125 and 250

g/L (Fleet and Heard 1993). It is likely that the initial concentrations of glucose and fructose

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(main grape sugars) will selectively influence the species and strains of yeast present during

fermentation. Musts with lower concentrations of sugar start to ferment fast and the sugar is

fermented to completion, whereas musts with high sugar content ferment slowly and may be

incomplete. High sugar concentrations inhibit fermentation by high osmotic pressure, which

draws water from the yeast cells in particular (Margalit 1997).

The effect of initial sugar concentration on time of fermentation has also been

observed as higher sugars tend to prolong fermentation (Borzani et al 1993). Higher initial

sugars also possess better retention of ascorbic acid, increase in concentration of total esters

and phenols thus improving the wine quality (Attri 2009).

The various yeast species and strains that develop during the overall fermentative

process metabolize grape juice constituents, principally the sugars, to a wide range of volatile

and non-volatile end-products, which influence and determine the types and concentrations of

many products that contribute to the aroma and flavour characteristics of the wine. Although

sugar is an important substrate of fermentation, higher sugar concentration inhibits the growth

of micro-organisms (FAO 2010). However, Yeasts are fairly tolerant of high concentrations

of sugar and grow well in solutions containing 40% sugar (Steinkraus 1992). At

concentrations higher than this, only a certain group of yeasts – the osmophilic type – can

survive. There are only a few yeasts that can tolerate sugar concentrations of 65-70% and

these grow very slowly in these conditions (Board 1983). High sugar musts can also lead to

higher acetic acid production by yeast during fermentation (Monk and Cowley 1984).

Stuck and sluggish fermentations are more frequently observed in vintages of well

matured grapes with high sugar concentrations (Gafner and Schütz 1996). High osmotic

pressure caused by high sugar concentrations can contribute to stuck fermentations (Kunkee

1991).Yeast strains also differ in their ability to ferment musts containing high levels of sugar

(Salmon et al 1993). Higher inoculation levels of yeast should be used to ferment juice with

high sugar concentrations. Strains of Saccharomyces cerevisiae, such as L2226, have been

recommended in high sugar fermentations as they can be more tolerant to high sugar levels

than other yeast strains (Lallemand 1997).

2.6.4 Effect of Nitrogen and Phosphorus supplementation

The nitrogen content of grape juice affects both yeast cell growth and fermentation

rate. The Yeast Assimilable Nitrogen (YAN) content of grape must regulates the growth and

metabolism of fermentation yeast. Yeast cells are subjected to stress during alcoholic

fermentation by non-optimum YAN availability. It has been found that low YAN is

associated with lagging and incomplete fermentation, and sulfide evolution, whereas excess

of YAN is associated with unbalanced production of some aromatic compounds (Bell and

Henschke 2005). Nitrogen supply strongly influences yeast growth and metabolism during

fermentation (Beltran et al 2005). The concentration and ratio of nitrogenous compounds

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present in grape juice depend on grape variety, harvest time, and vineyard management

factors. Yeast assimilable nitrogen (YAN) includes ammonium and the α-amino nitrogen of

amino acids (excluding proline, which is not used by yeast as a nitrogen source under

anaerobic conditions). Proline and arginine are usually the most abundant nitrogenous

compounds in grape juice (30–65% of total amino acid content) and ammonium makes up ca

40% of grape juice YAN (Beltran et al 2004).

In the preliminary study with a Chardonnay must in combination with a high nitrogen

demanding yeast, Torrea and Henschke (2004) showed that an intermediate concentration of

YAN produced a wine with most preferred sensory attributes. However, they suggested that

more work is needed to determine the optimal YAN concentration of musts of other varieties

in combination with yeast having different demands for YAN. It has been recommended in

other studies also to supplement deficient musts with diammonium phosphate (DAP) at the

start of fermentation to ensure an adequate population of yeast (Bely et al 1990, Ugliano et al

2007, Kocher and Pooja 2011).

Since nitrogen depletion is often the cause of stuck and sluggish fermentations

(Salmon 1996), ammonium salts such as diammonium phosphate (DAP) are frequently added

to grape must fermentations to alleviate nitrogen deficiency. The timed addition of DAP to

grape must significantly affects the amount of ethyl carbamate (EC) produced in wine. This

effect was found to be yeast strain dependent: Pasteur Red produced less EC when DAP was

added at the onset of fermentation, whereas strain 522 produced less EC when DAP was

added during the later stages of fermentation. EC production by strain EC1118 was less

affected by the timing of DAP addition. The metabolically enhanced yeast strains Pasteur

RedEC-, 522EC-, and EC1118EC-, which constitutively express DUR1,2, significantly

reduced the amount of EC produced regardless of the timing of DAP addition (Adams and

Hennie 2010).

Further, fermentation process not only depends upon the quantity of N and P added,

but also on the quality of these supplements. Various nitrogen and phosphorus sources like

ammonium sulphate, diammonium phosphate, potassium dihydrogen phosphate, di potassium

hydrogen phosphate, amino acids, and diammonium hydrogen phosphate have been used to

carry out fermentation efficiently and rapidly. KH2PO4 (46.1g/L) was found to be better

phosphorus source in comparison with K2HPO4 (45.3 g/L) and (NH4)2SO4 (46.1 g/L) was the

best nitrogen source as compared to NaNO3, (NH4)H2PO4, NH4NO3 for the production of red

wine from ‘Siahe sardarsht’ grape variety (Asli 2010).

For a number of fruits, the nitrogen content is insufficient and supplements are made

by the addition of ammonium phosphate or of diammonium phosphate (DAP) before

fermentation. Glutamate is also another preferred nitrogen source because it is utilized

directly for biosynthesis. Glutamine can generate both ammonium ion and glutamate.

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Nitrogen–containing compounds in grape juice may meet one of three fates: (1) Utilized

directly in biosynthesis; (2) converted to a related compound and utilized in biosynthesis; or

(3) degraded releasing nitrogen either as free ammonium ion or as bound nitrogen via a

transamination reaction (Boulton et al 1996).

2.7 Post fermentative treatments

Consumer acceptability is the final goal of wine development. The crude wine

obtained after fermentation contains yeast, protein hazes and residual sugars and does not

have complete quality (sensory) attributes. Hence, it requires post fermentative treatments

(finishing) to make wine potable. In fact, there are five goals of “finishing” a wine: clarity,

stability, compositional adjustment, style development and packaging. It is important,

especially in white wines; that the wine at the point of consumption should not be cloudy or

contain haze or precipitate. This includes clarification, filtration, fining, stabilization, ageing

and blending of wines. It is also important to prevent unwanted microbial growth from

occurring in the wine after primary fermentation is complete as this will affect the flavour and

aroma profile. Saccharomyces autolysis will replenish nutrients in the wine making them

available for other organisms. Saccharomyces does not consume all possible bacterial energy

sources. Many spoilage organisms are obligate aerobes so the wine ‘must’ be protected

against exposure to air once the carbon dioxide blanket generated during fermentation has

dissipated.

Post fermentation treatment of crude wine can be accomplished by different means:

2.7.1 Racking

“Racking" of wine is the process of separating wine from its sediment, or lees, and

transferring the wine into another container using a siphon. Repeated racking produces the

clarity required in wine, especially if it is aged in a barrel. The wine is repeatedly racked to

leave behind less and less precipitate. During the repeated pouring, the wine is also given a

chance to rid itself of the excess carbon dioxide from fermentation. As the CO2 escapes,

oxygen enters the wine with each transfer, helping eventually to age. Besides clarification,

racking also provides suitable conditions for oxygen to dissolve in the wine, at a rate varying

from 2.5 to 5 mg/L. Oxygen eliminates certain unpleasant reduction odors (H2S), as well as

iron (ferric casse) and is also responsible for intensifying color of wine (Amerine and

Roessler 1983).

2.7.2 Effect of fining agents

In winemaking, fining is the process where a substance (fining agent) is added to the

wine to create an adsorbent, enzymatic or ionic bond with the suspended particles, producing

larger molecules that will precipitate out of the wine more readily and rapidly. A variety of

fining agents are commercially available to the wine industry, including proteins and

inorganic ion exchangers. These fining agents are essentially used to control the levels of

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phenolics in wine, but they also have the potential to interact with other wine components,

most often as a side effect. They are therefore expected to influence, at least in part, the

potential for wine protein haze formation. Six common fining agents—casein, egg albumin,

isinglass, chitosan, chitin, and polyvinylpolypyrrolidone (PVPP)— have been analyzed to

assess their effects on wine protein haze-forming potential and on the levels of proteins and

phenolic compounds in a Muscat of Alexandria wine (Chages et al 2012). It was found that

benotonite was not most effective and the fining agents did not significantly affect wine

protein content but removed considerable levels of polyphenols and presented no apparent

effect on protein stabilization of the fined wines. Further, precipitation of combined

particulates is faster at lower temperatures (except for bentonite). However, some fining

agents are less temperature sensitive than others (e.g. isinglass is less temperature sensitive

than gelatin. According to Rotter (2008), wines should be low in dissolved CO2 when fined,

since dissolved CO2 will tend to keep particulates in solution and inhibit settling.

The effect of different fining agents, used at different concentrations, on the

antioxidant status of fined wines was studied by Yildirim (2011).The results demonstrated

that the use of a combination of gelatin and Kieselsol led to the highest total phenol value

(3,491 mg/L GAE) and antioxidant activities (29%) among the tested fining agents. Wines

were mostly negatively affected by the use of egg white as an agent and led to the lowest

value of total phenol (3,038 mg/L GAE) and the lowest rate of antioxidant activity (26%).

Significant differences (p<0.05) were determined between gelatin, egg white, and the control

groups. The results of the grouping of analyzed parameters in n-dimensional space, with

different fining agents at different concentrations, demonstrated the importance of a low

concentration of fining agents for high antioxidant activity and total phenols.

2.7.3 Ageing

The ageing of wine, and its ability to potentially improve wine quality, distinguishes

wine from most other consumable goods. Aged red wines possess significantly different

polyphenolic composition compared with young ones, mainly not only to formation of

polymeric compounds but also because of oxidation, hydrolysis, and other transformations

that may occur in native grape phenolics during aging (Arnous et al 2001).

After fermentation and clearing, wine needs to be aged. Aging can be done by storing

the wine in wooden or the wine bottle. Aging is done in a wooden vat for least six months in

most red wine to add the flavour of the wood to the wine (Wimalsiri et al 1971). Red wines

are commonly matured in oak barrels and this is thought to assist with stabilisation of colour.

The nature of the handling operations of wines in barrels means that they are intermittently

mildly aerated, and this can lead to formation of acetaldehyde bridged polymeric pigments

(Ribereau-Gayon et al 1983). All wines treated with oak showed a trend towards slightly

higher hue values than the unoaked wines.

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In general, wines with a low pH (such as Pinot noir and Sangiovese) have a greater

capability of aging. The white wines with the longest aging potential tend to be those with a

high amount of extract and acidity. The acidity in white wines plays a similar role that tannins

have with red wines in acting as a preservative. The process of making white wines, which

includes little to no skin contact, means that white wines have a significantly lower amount of

phenolic compounds, though barrel fermentation and Oak aging can impart some phenols.

Similarly, the minimal skin contact with rosé wine limits their aging potential (Robinson

2003). With red wines, a high level of flavor compounds, such as phenolics (most notably

tannins); will increase the likelihood that a wine will be able to age. Wines with high levels of

phenols include Cabernet Sauvignon, Nebbiolo and Syrah (Robinson 2006).

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CHAPTER III

MATERIALS AND METHODS

3.1 MATERIALS

3.1.1 Yeast culture

The yeast culture Saccharomyces cerevisae strain 35, used in the present study for

fermentation of grape juice was procured from the Department of Microbiology, Punjab

Agricultural University, Ludhiana. The culture was maintained on Glucose Yeast Extract agar

(GYE agar) slants and stored at 40 C. The yeast was subcultured fortnightly on the same

media:-

Composition of Glucose Yeast Extract agar (gL-1

)

Glucose : 10.0

Peptone : 5.0

Yeast extract : 5.0

Agar : 20

Distilled water (to make volume) : 1000 ml

pH : 5.5

3.1.2 Chemicals used

All chemicals used were of AR/GR grade. Pectinase (1000 units/100mg) and

cellulase (10000 units/100mg) were procured from SISCO research laboratories Pvt. Ltd.

(Mumbai) and Amylase from Novozyme.

3.1.3 Grapes

The grapes used in the present study were of Punjab purple (Syn H516) variety which

were procured from Department of Fruit Science, PAU, Ludhiana (Plate I).

3.2 METHODS

3.2.1 Selection of fruit

Healthy ripened grapes were selected after manual sorting and discarding of defective

bunches. Grape berries were destemmed and then washed with boiled and cooled water and

used for extraction of juice. Juice was extracted aseptically in an electric juicer under hygienic

conditions.

3.2.2 Extraction of juice from Grapes

Healthy ripened grapes were destemmed, washed with boiled and cooled water as in

3.2.1. With the help of electric juicer, extraction of juice was carried out and the juice after

supplementation of KMS (0.01%) was stored in flasks (Fig. 1).

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GRAPES

DESTEM AND WASH

EXTRACTION OF JUICE IN THE JUICER

STORAGE OF GRAPE SKIN AT 4OC

GRAPE JUICE

ADD KMS @0.01%

KEEP IN FLASKS AND STORE AT 4 O

C TILL USE

Fig. 1: Flow diagram for extraction of juice from grapes

3.2.3 Physico-chemical analysis of grape juice

The physico-chemical analysis of Grape juice included the estimation of its TSS, pH,

acidity, Brix acid ratio, ascorbic acid and total phenols.

3.2.4 Preparation of sugar solution

Granulated sucrose (commercial sugar) was procured from the local market. The

stock sugar solution was prepared by dissolving 250g of granulated sucrose in 250ml of water

boiled for 10 min and then allowed to cool at room temperature and used for supplementation

in grape juice to adjust the brix.

3.2.5 Preparation of grape ‘must’ and its ethanolic fermentation

The extracted grape juice was subjected to prefermentative treatment for preparation

of grape ‘must’ before its fermentation by Saccharomyces cerevisae to produce ethanol as:-

3.2.5.1 Pre-fermentation treatment

3.2.5.1.1 Skin treatment

The stored grape juice was subjected to skin treatment to improve the color intensity

and volatiles (Plate II). Response surface methodology (RSM) was adopted in the

experimental design as it emphasizes the modeling and analysis of the problem in which

response of interest is influenced by several variables and the objective is to optimize this

response (Design Expert 8.0). A five-level three-factor Central Composite Rotatable Design

(CCRD) was employed. For the three factors namely temperature, time and skin weight,

CCRD was made up of a full 23 factorial design (eight points) augmented with six replications

of the centre points (all factors at level 0) and six star points (points having one factor at an

axial distance to the centre of ± α, whereas other two factors at level 0) (Table 1). The axial

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Plate I: Punjab purple (Syn H516) grapes

Plate II: Flasks exhibiting different levels of Skin treatment of juice

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distance α was chosen to be 1, and a set of 20 experiments (each with 300ml grape juice) were

carried out:

Total no. of experiments= 2 no. of variables

+ 2 x no. of variables + central points

For three variables:

Total no. of experiments= 23 + 2 x 3 +6 = 20

Five different levels for each experiment in coded form were –α, -1, 0, +1, +α

Where,α = [2] no.of variables/4

= [2]3/4

= 1.682

Table 1: Level of different process variables for skin treatment of Grape juice

Levels Independent

variables -1 0 +1

Temperature (oC) 10 15 20

Time (hr) 1 8.50 16

Skin weight (Kg) 0.25 0.55 0.85

The independent variables were skin weight (X1), time of contact (X2), temperature

(X3).The three independent variables were coded as -1.682 (lowest level) -1, 0, 1 (middle

level) and +1.682 (highest level). The experimental design matrix in coded (X) form and at

the actual level (X) of variables is presented in Table 2.

Table2: Experimental design of process variables and values of experiment data for

optimization of skin treatment of Grape juice

Coded values Uncoded values

Experiment

No.

Temperature

(0C)

Time

(hr)

Skin

weight(Kg)

Temperature

(0C)

Time (hr) Skin weight

(Kg)

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

0

0

0

0

+1

-1

0

+1.682

0

-1.682

+1

-1

+1

+1

-1

0

0

0

0

-1

0

-1.682

+1.682

0

+1

+1

0

0

0

0

+1

-1

-1

-1

+1

0

0

0

0

-1

-1.682

0

0

0

+1

+1

0

0

+1.682

0

-1

+1

+1

-1

-1

0

0

0

0

-1

15.00

15.00

15.00

15.00

20.00

10.00

15.00

23.41

15.00

6.59

20.00

10.00

20.00

20.00

10.00

15.00

15.00

15.00

15.00

10.00

8.50

4.11

21.11

8.50

16.00

16.00

8.50

8.50

8.50

8.50

16.00

1.00

1.00

1.00

16.00

8.50

8.50

8.50

8.50

1.00

0.05

0.55

0.55

0.55

0.85

0.85

0.55

0.55

1.05

0.55

0.25

0.85

0.85

0.25

0.25

0.55

0.55

0.55

0.55

0.25

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A second degree polynomial equation (Eq.1) was provided for the experimental design by the

statistical software (Design Expert Software) so as to estimate the response of the dependent

variable. The response function (y) was related to the coded variables (xi, i=1,2 and 3) by a

second degree polynomial equation as given below:

y=bo+b1x1+b2x2+b3x3+b12x1x2+b13x1x3+b23x2x3+b11x12+b22x2

2+b33x32+ε (1)

The variance for each factor assessed was partitioned into linear, quadratic and interactive

components. The coefficients of the polynomial were represented by bo (constant), b1, b2, b3

(linear effects); b12, b13,b23 (interaction effects); b11,b22,b33 (quadratic effects); and ε (random

error). The significant of all terms in the polynomial functions was assessed statistically using

F-value at probability (P) of 0.05 so as to determine the fitness of the model. The statistical

analysis of the data and three- dimensional (3D) plotting were performed using Design Expert

software ‘DE-8’. The validation of the model was also carried out at 300ml as well as 5L

levels.

3.2.5.1.2 Enzyme treatment

The skin treated juice was subjected to different enzyme treatment i.e. Pectinase

(0.25ml/100ml), Amylase (0.085ml/100ml), Cellulase (0.125ml/100ml), Amylase +

Pectinase, Pectinase + cellulase, Amylase + Cellulase, Amylase + Pectinase + Cellulase (Fig.

2). The temperature of the enzymatic treatment combinations was adjusted 450C for 6h

(Kocher and Pooja 2011).

GRAPE JUICE (300ml in each flask)

ADD ENZYMES INDIVIUALLY AND IN COMBINATIONS ACCORDING TO

SPECIFIED CONCENTRATION I.E. PECTINASE (0.25ML/100ML), AMYLASE

(0.085ML/100ML), CELLULASE (0.125ML/100ML)

KEEP FLASKS AT 450C TEMPERATURE FOR 6h

CENTRIFUGE THE GRAPE JUICE (6000 rpm for 10 minutes)

COLLECT CLARIFIED GRAPE JUICE, HEAT TO 900C

MEASURE OD 550 nm

CALCULATE % DECREASE IN OD 550 nm

Fig. 2: Flow diagram for enzymatic treatment of skin pretreated Grape juice

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At the end of the enzyme treatment, the suspension was centrifuged at 6,000 rpm for 10 min

and the clarified grape juice was heated at 90oC for 5 min to inactivate the enzyme. The

decrease in OD 550 nm (Fig. 2) was then calculated using the following expression:

% decrease in OD = OD Initial

OD Final - OD Initial x 100

3.2.5.2 Preparation of inoculum

The inoculum of S. cerevisae strain 35 was prepared in glucose yeast extract broth for

the fermentation where a loopful of slant culture was inoculated in 250 ml Erlenmeyer flasks

containing 100 ml GYE broth. It was incubated at 100 rpm and at 28±2oC for 24 hrs to raise

seed inoculum. From the seed inoculum, starter culture was prepared. For the purpose 2% of

seed inoculum was inoculum was inoculated in pasteurized Grape juice (diluted 1:1 with

sterile water) and incubated at 28 oC for 24 hrs under shaking (100 rpm) conditions.

3.2.5.3 Alcoholic fermentation of Grape juice

The pretreated grape juice (300 ml) was taken in the 500 ml Erlenmeyer flasks and

chaptalized with sugar syrup to adjust sugar level at 20 oB. The ‘must’ so prepared was

supplemented with different concentrations (50-250 mg/100ml) of Diammonium hydrogen

ortho phosphate (DAHP) to study the effect of N and P supplementation on ethanolic

fermentation inoculated using 5% starter culture (prepared above) and incubated at 25 oC. The

periodic samples of fermenting grape juice were taken, spun at 6000 rpm for 5 minutes and

analyzed for TSS, pH and ethanol content (as per procedure in 3.3) till no further decrease in

oBrix level was noted.

The fermentation efficiency of different experiment treatments was calculated as:

Fermentation efficiency = 100x(%v/v) ethanol lTheoretica

(%v/v) produced ethanol Actual

Theoretical Ethanol % v/v = sugar utilized (g) X 0.64

Sugar utilized=Available sugar- sugar present after fermentation

3.2.5.4 Effect of Recycled yeast

The effect of recycled yeast (yeast obtained from previous lots) was studied on

ethanolic fermentation of subsequent lots at 300ml fermentation level in 500ml Erlenmeyer

flasks. The fermented grape must of previous lot was partially removed after cessation of

fermentation to form 5-20% of the inoculum i.e. 15ml to 60ml to report four different

inoculum levels were used i.e. 5%,10%,15%,20%. The latter was used to inoculate fresh

‘must’ at similar fermentation conditions in duplicate as in 3.2.5.2. Periodic samples were

taken and analyzed for ethanol content, pH and Brix as described earlier. The recycled yeasts

were used upto 2nd level of recycling.

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3.2.6 Post fermentative treatments

3.2.6.1 Siphoning

The flasks/ bottles containing prepared wine were stored at 15 o

C and debris (‘lees’)

was allowed to settle. No settling or fining agent was added. The siphoning (racking) was

repeated after every 15 days till there was no further settling of debris in the bottles. At the

time of each siphoning, 0.01% (v/v) KMS was added to prevent any microbial contamination.

3.2.6.2 Bottling and storage

The cleared wine was stored in glass bottles (washed earlier with boiling water) for

upto 4 months (with decantation treatment every 2 weeks) under refrigerated conditions.

3.2.6.3 Shelf life study

Shelf life of grape wine of variety Punjab purple stored at refrigerated temperature (4

oC) was studied. The refrigerated stored wine was analyzed for total microbial count using

plate count method on GYE media at different periods of time upto 3 months. The clarified

aged wine was tasted and evaluated by a panel of 10 judges on a 80 point scale Modified

Davis Score Card (Annexure, Table I) in comparison to commercial wine (‘Galaxy’ brand of

N.D wines Pvt. Ltd., Nasik).

3.3 Analytical Techniques

3.3.1 pH

The pH of the periodic samples was determined using pocket sized pH meter (Hanna

HI96107).

3.3.2 Total Soluble Solids

Total Soluble Solids (%TSS) in juice was determined by using Erma hand

refractrometer of 0-32 oB and by using Brix Hydrometer (1-10 oB, 0-20 oB). The prism of

refractrometer was cleaned and dried with soft tissue paper. A drop of distilled water at 20 oC

was placed on clean and dry prism and calibrated by reading the zero line of demarcation on

the scale. For Brix determination with Brix hydrometer, the sample (juice/ fermenting juice)

was taken in a measuring cylinder and whole Brix hydrometer was gently dropped in it. The

level of TSS was studied by dipped level of Brix hydrometer.

3.3.3 Titrable Acidity

It was expressed as percent acidity and analyzed using the method of Amerine et al

(1967). Titrable acidity was determined by titrating known amount of juice or wine sample

(5ml) against 0.2 N NaOH using a few drops of 1% phenolphthalein solution as indicator. The

end point was appearance of pink/ Purple color which should persist for 15 seconds.

Titrable Acidity (w/v, %) = taken)sample of (volume 5ml

6 X 0.2 X used NaOH of Volume x 100

3.3.4 Brix-Acid Ratio

Brix- Acid ratio was calculated by dividing TSS value with total acidity of the juice.

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3.3.5 Ethanol estimation

The estimation was performed by the chemical oxidation method of Caputi et al

(1968).

Reagent

1. Potassium dichromate solution: The solution was prepared by dissolving 33.37 g of

K2Cr2O7 in distilled water to which 325 ml of H2SO4 was slowly added by keeping the flask in

a cold water bath and the final volume was made 1L with distilled water. The reagent was

kept in dark colored bottle for overnight, before use.

Procedure

One ml of the fermented wash was added to 500ml distillation flask containing

approximately 20 ml distilled water. The distillate was collected in a 50 ml flask containing

25 ml K2Cr2O7 solution while keeping the condenser tip submerged in the solution

throughout. About 20 ml distillate including the rinsed water from the tip of the condenser

was collected. The distillate containing flask was then kept in a water bath maintained at

62.5oC for 20 min and was cooled to room temperature, thereafter. The final volume of the

flask was raised to 50 ml with distilled water. Five ml of this solution was diluted with five ml

distilled water and used for reading on spectrophotometer (Systronics 106) at 600 nm. The

standard curve of ethanol was prepared by taking 0-20% absolute alcohol (Fig.3).

Fig. 3: Standard curve for ethanol

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 5 10 15 20

Ethanol % (v/v)

Abso

rban

ce a

t 6

00

nm

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3.3.6 Ascorbic acid

The titrametric method using 2,6-dichlorophenol indophenols dye was used to

estimate ascorbic acid (AOVC 1996). Dye factor (i.e. mg of ascorbic acid per ml of dye) was

determined by taking 5 ml standard ascorbic acid solution and 5 ml 0.4% oxalic acid against

dye solution to a pink color. Known weight of crushed sample (10mg) or known volume of

wine (10ml) was taken and 100 ml of volume was made up with 0.4% oxalic acid solution.

The mixture was filtered through Whatman filter paper no. 4. To a measured volume of

aliquot (10ml), 15 ml of oxalic acid (0.4%) was added followed by titration against

standardized dye (0.4%) to a pink end point which should persist for at atleast 15 sec.

Fresh mg of Ascorbic acid/ 100mg = (mg) sample ofht ken x weigAliqout ta

made Volumefactor x dye x Titre x 100

3.3.7 Reducing sugars

Reducing sugars were estimated by the method of Miller (1959). Test tubes

containing 3 ml sample and 3 ml DNS reagent (10 g of 3, 5 dinitrosalicyclic acid, 2.0 g

phenol and 0.5 g sodium sulphite solution were dissolved in 500 ml 1% sodium hydroxide

solution and the volume was made 1000ml by adding additional alkaline solution (filtered and

stored in a dark colored bottle) were heated for 15 min in a boiling water bath. One ml of

Rochelle salt solution (40 g sodium potassium tartarate was dissolved in distlled water and the

volume was made to 100 ml) was added to each test tube and the tubes were allowed to cool

to room temperature. The OD of developed color was measured at 575 nm using Systronics

106 Spectrophotometer. The concentration of reducing sugars (as glucose) was calculated

from the standard curve which was prepared by taking 0.1-0.9 mg/ml of glucose (Fig. 4).

3.3.8 Total phenols

3.3.8.1 Extraction of total phenols

A known volume of juice or wine (1ml) was taken in 100 ml conical flask. To this 10

ml HCl (0.3N) in methanol was added and kept on orbital shaker at 150 rpm for 1 hr. After

shaking, crude extract was filtered through Whatman No. 1 filter paper. The filtrate so

obtained was evaporated to dryness in a boiling water bath. To this residue, hot water was

added and final volume was adjusted to 25 ml with distilled water.

3.3.8.2 Estimation of total phenols

Total phenols were estimated by method of Malik and Singh (1971). To 0.5 ml of the

above extract, 1 ml each of Folin-Ciocalteau reagent (diluted 1:2 with distilled water) and

sodium carbonate reagent (35 grams of sodium carbonate dissolved in 60ml distilled water

and final volume made to 100 ml) was added and then mixed. After 10 min, 2 ml of distilled

water was added and intensity of color was recorded at 620 nm against reagent blank.

The concentration of total phenols was calculated from the standard curve (Fig. 5)

prepared by using Gallic acid (10-100 µg/ml).

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Fig. 4: Standard curve for reducing sugars

Fig. 5: Standard curve for total phenols with Gallic acid as standard

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3.3.9 Estimation of SO2

SO2 (total as well as free) was estimated by Ripper (1898) method, the principle of

which is based on the following equation:-

H2SO3 + I2 + H2O H2SO4 + 2HI

Reagents

Preparation of 0.02 N I2- 0.1 N: - 2.7 g I2 + 40 g KI in 25 ml Distilled Water (DW) and make

volume 1L. Take one part of 0.1N I2 and four parts of DW.

Preparation of 0.02 N Na2S2O3 -0.2N -:50g Na2S2O3..5H2O + 0.1g Na2S2O3 (anhydrous) and

make volume 1L with DW. Take one part of 0.2 N Na2S2O3 and ten parts of DW.

Starch indicator- 1g starch in minimum DW. Make volume 100ml with boiling water. Cool

and add 0.5 ml CCl4.

Sulfuric Acid solution (1+3): 100ml (concentrated) sulfuric acid plus 300ml DW.

1N NaOH- 4 g in 100ml DW

Total SO2

Pipette 20ml of wine into a 250ml Erlenmeyer flask. Add 25 ml of NaOH solution;

mix, stopper and let it stand for 10 min. Add pinch of Na2S2O3 to expel air and then add 5ml

starch indicator solution; add 10ml sulfuric solution (1+3). Titrate rapidly with 0.02 N iodine

solution till end point as bluish color which persists for 30 sec.

SO2 (total) (mg/L or ppm) = (ml) sample of Volume

100032x x N) (0.02 I2 ofNormality x used I2 of Volume

Free SO2

Pipette 50 ml wine a 250ml Erlenmeyer flask. Add pinch of Na2S2O3 to expel air then

add 5ml starch indicator solution; add 5ml sulfuric solution (1+3). Titrate rapidly with 0.02 N

iodine solution till end point as bluish color which persists for 1-2 min. Temperature should

not exceed 20OC.

SO2 (total) (mg/L or ppm) = (ml) sample of Volume

100032x x N) (0.02 I2 ofNormality x used I2 of Volume

3.3.10 Thin layer chromatography (TLC)

TLC of wine was carried out using glass plate (stationary phase) of 5 x 20 cm size.

Slurry was prepared by taking 2g of silica gel with double amount of water and was spread on

plate using glass rod to be of uniform thickness. The plate was activated at 110 oC for 1 h (it

is done to remove the moisture from the plates).Solvent system (Mobile phase) was also

prepared using Butanol: Acetic acid: water :: 40: 20: 10 (v/v/v).Then, solvent was placed into

solvent chamber containing nearly 100 ml in it and covered with filter paper to ensure the

saturation with solvent vapors. After that, spotting was done using capillary tube atleast 1.5

cm above the end of plate (the side we dip in the solvent) and dried the spot immediately.

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After spotting, plate was placed in the chamber (Solvent system) and allowed the

solvent to move on plate till it reached atleast 1-2 cm below from top and plate was then

removed and placed in the oven to remove solvent completely. Then, spots were identified

using ninhydrin reagent (mixture of 0.2% solution of ninhydrin in butanol) and 10% acetic

acid was sprayed for detection as pink color appears after heating at 100-110 0C for 10 to 15

min. Rf values were then calculated using formula as below:

Rf = (cm)solvent by travelledDistance

(cm)spot by travelledDistance

3.3.11 Statistical analysis

Besides the Response Surface Methodology (Design Expert 8.0) adopted for

prefermentation treatment of grape juice, statistical analysis of the fermentation data was

carried out using GSTAT04 and CPCS1 software developed by Department of Math, Stat and

Physics, PAU, Ludhiana (Cheema and Sidhu 2007).

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CHAPTER IV

RESULTS AND DISCUSSION

4.1 Extraction of Grape juice

Healthy fruits of variety Punjab purple (Syn H 516) were selected and juice was

extracted from them. Ten kg of the berries with an initial brix of 16±2.0oB (oBrix depended

upon the maturity stage of the grape fruit), upon juice extraction gave 5.5±0.5 L of brick red

coloured grape juice whereas 1.3 ± 0.1 Kg of grape skin was produced to which 0.01% w/v

KMS was added. The skin was then stored in a deep freezer for further experiments on skin

treatment (Kocher et al 2011a).

4.2 Physiochemical characteristics of grape juice

The physicochemical characteristics of juice were evaluated on the basis of chemical

analysis which is presented in table 3. The analysis revealed TSS (16±2.0), acidity

(0.30±0.06), pH (3.3±0.2), brix acid ratio (58.33 ± 8.33), ascorbic acid (615.38 ± 15.3) and

total phenols (98.49 ± 13.26) mg/100ml in freshly extracted juice.

Table 3: Physico-chemical analysis of Punjab purple juice

Parameters Observations

TSS (oBrix) 16±2.0

Acidity (% w/v) 0.30±0.06

pH 3.3±0.2

Brix-acid ratio 58.33 ± 8.33

Ascorbic acid (mg/100ml) 615.38 ± 15.3

Total phenols (mg/100ml) 98.49 ± 13.26

Since, the parameters like TSS, titrable acidity and brix acid ratio determine the final

sensory quality attributes like appearance, color, aroma, taste, bouquet, body, flavor,

astringency and overall acceptability of the wine, these have been studied by different

research workers prior to fermentation of grape juice. Among the different reports on physico

chemical characteristics of grape juice, Gill and Arora (2009) reported that Punjab Purple had

significantly higher T.S.S. of 17.7%. Topalovic and Mikulic-Petkovse (2010) determined the

sugar content in the grape juice of ‘Cardinal’ cultivar which ranged from 13.1 to 19.4 and its

brix-acid ratio varied between19.4-21.8. Cantos et al (2002) found the content of total

phenolics in range from 115 to 361 mg kg-1

in Dominga and Flame Seedless respectively, of

fresh weight of grapes. Morino-Perez et al (2011) reported 3.18 % acidity, 25.53 oBrix and

3.82 pH in Syrah variety of grapes. Goswami and Ray (2011) found that titratable acidity %

(tartaric acid v/v) and pH was 0.715% and 5.0, respectively in the grape juice concentrate.

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4.3 Pre-fermentation treatment

4.3.1 Skin treatment

The stored grape skin was used for pretreatment of juice so that skin volatiles like

phenols and anthocyanins are extracted into the juice (Lorrain et al 2013). The results of skin

contact treatment conducted by RSM (as explained in materials and methods) are presented in

table 4 as response in the form of Brix, pH, phenols (mg/100ml) and color intensity at OD

620nm (Optical density/ Absorbance is a reflection of color intensity of the juice).

Table 4: Effect of skin treatment on Grape juice from Punjab purple

Uncoded values Responses

Experiment

No.

Skin

weight(Kg)

A

Temperature

(°C)

B

Time

(hr)

C

(°Brix) pH OD

620nm

Phenols

(mg/100ml)

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

0.05

0.55

0.55

0.55

0.85

0.85

0.55

0.55

1.05

0.55

0.25

0.85

0.85

0.25

0.25

0.55

0.55

0.55

0.55

0.25

15.00

15.00

15.00

15.00

20.00

10.00

15.00

23.41

15.00

6.59

20.00

10.00

20.00

20.00

10.00

15.00

15.00

15.00

15.00

10.00

8.50

4.11

21.11

8.50

16.00

16.00

8.50

8.50

8.50

8.50

16.00

1.00

1.00

1.00

16.00

8.50

8.50

8.50

8.50

1.00

14.1

15.5

13

15.5

13

13

14

13.6

16

12.5

13

13

15

14.6

13.3

16

13.1

15.6

16

15.5

3.385

3.459

3.27

3.403

3.306

3.308

3.398

3.393

3.389

3.391

3.487

3.405

3.402

3.405

3.403

3.311

3.487

3.499

3.296

3.483

1.641

1.524

1.367

1.352

1.656

1.381

1.321

1.342

1.943

1.291

1.399

1.812

1.741

1.689

1.221

1.381

1.352

1.353

1.321

1.763

98.41

95.72

98.4

97.4

99.4

98.13

97.1

95.43

109.62

87.66

100.18

96.17

98.08

94.62

92.81

97.12

97.43

97.41

97.14

89.11

*Initial values of brix, pH, OD 620nm and phenols (mg/100ml) were 18°B, 3.5, 1.068, 85.3

respectively.

Maximum phenols (mg/100ml) and color intensity of 109.62 and 1.943 were

observed in combination of 1.05 Kg/L skin weight, temperature 15°C and time 8.5 h but this

combination required very high amount of skin which was not possible from the available

quantity of grapes because the skin produced 0.13 Kg/kg of grapes. Hence, the combination

of 0.25 Kg/L skin weight, temperature 20°C and time 16 h was preferred which was having

2nd

highest phenols i.e. 100.18 mg/100ml, color intensity of 1.399 with 13°Brix and 3.487 pH.

There was significant decrease in Brix with skin treatment which is a negative factor and to

compensate it, juice had to be supplemented with sugar to adjust the brix. The results were

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Table 5: Analysis of variance table for Response 1 (BRIX) [Partial sum of squares]

for response surface quadratic model

Source Sum of

Squares df

Mean

Square

F

Value p-value Prob > F

Model 29.71 9 3.28 77.74 < 0.0001** Significant

A-skin

weight 2.071E-003 1 2.071E-003 0.049 0.8292

B-temp 1.87 1 1.87 44.19 < 0.0001**

C-Time 1.59 1 1.59 37.63 < 0.0001**

AB 0.080 1 0.080 1.89 0.1989

AC 0.045 1 0.045 1.06 0.3264

BC 1.80 1 1.80 42.72 < 0.0001**

A2 4.99 1 4.99 188.02 < 0.0001**

B2 12.79 1 12.79 302.72 < 0.0001**

C2 4.33 1 4.33 102.48 < 0.0001**

Residual 0.42 10 0.042

Lack of Fit 0.089 5 0.018 0.27 0.9128 Not

significant

Pure Error 0.33 5 0.067

Cor Total 29.99 19

R2 0.9859

Adj R-

Squared 0.9732

Pred R-

Squared 0.9708

Adeq

Precision 22.595

** Significant at 5% level

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Table 6: Analysis of variance table for Response 2 (pH) [Partial sum of squares] for

response surface quadratic model

Source Sum of

Squares df

Mean

Square

F

Value p-value Prob > F

Model 0.088 9 9.778E-003 1293.75 <0.0001** Significant

A-skin

weight 3.457E-005 1 3.457E-005 4.57 0.0582

B-temp 4.091E-007 1 4.091E-007 0.054 0.8207

C-Time 0.078 1 0.078 10367.78 <0.0001**

AB 1.051E-004 1 1.051E-004 13.91 0.0039**

AC 1.250E-007 1 1.250E-007 0.017 0.9002

BC 1.361E-004 1 1.361E-004 18.01 0.0017**

A2 5.563E-004 1 5.563E-004 73.60 <0.0001**

B2 2.845E-004 1 2.845E-004 37.65 <0.0001**

C2 3.136E-004 1 3.136E-004 41.50 <0.0001**

Residual 7.558E-005 10 7.558E-005

Lack of Fit 4.225E-005 5 8.449E-006 1.27 0.4006 Not

Significant

Pure Error 3.333E-005 5 6.667E-006

Cor Total 0.088 19

R2 0.9991

Adj R-

Squared 0.9984

Pred R-

Squared 0.9949

Adeq

Precision 119.599

** Significant at 5% level

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Table 7: Analysis of variance table for Response 3 (color intensity, OD 620 nm)

[Partial sum of squares] for response surface quadratic model

Source Sum of

Squares df

Mean

Square

F

Value p-value Prob > F

Model 0.82 9 0.091 90.26 <0.0001** Significant

A-skin

weight 0.077 1 0.077 76.13 <0.0001**

B-temp 0.011 1 0.011 11.22 0.0074**

C-Time 0.27 1 0.27 263.90 <0.0001**

AB 1.250E-003 1 1.250E-003 1.23 0.2925

AC 0.012 1 0.012 12.33 0.0056**

BC 0.045 1 0.045 44.16 <0.0001**

A2 0.33 1 0.33 329.76 <0.0001**

B2 3.721E-003 1 3.721E-003 3.68 0.0842

C2 0.085 1 0.085 83.77 <0.0001**

Residual 0.010 10 1.012E-003

Lack of Fit 7.530E-003 5 1.560E-003 2.90 0.1335 Not

Significant

Pure Error 2.593E-003 5 5.187E-004

Cor Total 0.83 19

R2 0.9878

Adj R-

Squared 0.9769

Pred R-

Squared 0.9195

Adeq

Precision 30.856

** Significant at 5% level

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Table 8: Analysis of variance table for Response 4 (phenols) [Partial sum of squares]

for response surface quadratic model

Source Sum of

Squares df

Mean

Square

F

Value p-value Prob > F

Model 454.16 9 50.46 1007.33 <0.0001** Significant

A-skin

weight 141.20 1 141.20 2818.60 <0.0001**

B-temp 70.95 1 70.95 1416.25 <0.0001**

C-Time 71.55 1 71.55 1428.21 <0.0001**

AB 7.41 1 7.41 147.94 <0.0001**

AC 2.02 1 2.02 40.32 <0.0001**

BC 1.30 1 1.30 25.87 0.0005**

A2 83.99 1 83.99 1676.63 <0.0001**

B2 57.56 1 57.56 1149.04 <0.0001**

C2 1.80 1 1.80 35.89 <0.0001**

Residual 0.50 10 0.050

Lack of Fit 0.37 5 0.074 2.84 0.1380 Not

Significant

Pure Error 0.13 5 0.026

Cor Total 454.66 19

R2 0.9989

Adj R-

Squared 0.9979

Pred R-

Squared 0.9923

Adeq

Precision 137.181

** Significant at 5% level

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analyzed by multiple regression technique. The analysis of variance tables (Tables 5, 6, 7 and

8) for the four responses Brix, pH, color intensity (OD 620nm) and phenols (mg/100ml)

having model F-values of 77.74, 1293.75, 90.26 and 1007.33, respectively. There was only a

0.01% chance that a "Model F-Value" of this large could occur due to noise. Furthur,values of

"Prob > F" were less than 0.0500 in all the four responses thus indicating that the model

terms wenre significant.

The "Lack of Fit F-value" of 0.27, 1.27, 2.90 and 2.84 for Brix, pH, color intensity

and phenols also implied that the Lack of fit is not significant realtive to the pure error in all

the four models (tables 5, 6, 7 and 8). There are also 91.28%, 40.06%, 13.35% and 13.80%

chances that a “Lack of Fit F-value” of this large could occur due to noise. Since, the lack of

fit P value in all the four models was <0.0500 lack of fit non-significant which was desirable

for the model to be fit.

The R- Squared values for four models i.e. Brix, pH, color intensity and phenols were

0.9859, 0.9991, 0.9878 and 0.9989 respectively. The “Pred R-Squared” values of 0.9708,

0.9949, 0.9195 and 0.9923 for brix, pH, color intensity and phenols respectively were in

reasonable agreement with the "Adj R-Squared" of 0.9732, 0.9984 0.9769 and 0.9979

respectively. "Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is

desirable and ratio of four models were 22.595, 119.599, 30.856 and 137.181 respectively,

indicating an adequate signal. Based upon the above measurable statistical parameter it may

be stated that this model can be used to navigate the design space. The same has been plotted

in Fig. 6,7 ,8and 9 respectively.

By applying multiple regression analysis on the experimental data, the following

second order polynomial equations (eqn. 1, 2, 3, 4) were found to represent the effect of

independent variables (Temperature, Time and skin weight) on Brix, pH, color intensity and

phenols.

(1) Brix

Final Equation in Terms of Coded Factors:

+15.73-0.012*A+0.37* B -0.41* C+0.10 * A* B-0.075*A*C-0.47* B*C-0.59*A2-0.94* B2-

0.72*C2 (1a)

Final Equation in Terms of Actual Factors:

+2.52213+6.42566*skinweight+1.27450*temp+0.37032*Time+0.066667*skinweight*temp-

.033333*skinweight*Time-0.012667*temp*Time-6.53034*skinweight2-0.037651*temp2-

0.012752*Time2 (1b)

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Fig.6 (a): Response surface of brix as a function of temperature and skin weight

Fig.6 (b): Response surface of brix as a function of time and skin weight

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Fig.6 (c): Response surface of brix as a function of time and temperature

(2) pH

Final Equation in Terms of Coded Factors:

+3.40+1.591E-003*A +1.731E-004*B-0.091*C +3.625E-003*A*B-1.250E-000*A*C

-4.125E-003*B*C-6.207E-003*A2-4.440E-003 * B2+6.104E-003*C2 (2a)

Final Equation in Terms of Actual Factors:

+3.45550+0.045393*skinweight+4.96792E-003*temp-0.012328*Time+2.41667E-003*

skinweight*temp-5.55556E-005*skinweight*Time-1.10000E-004*temp*Time-0.068970*

skinweight2-1.77582E-004*temp2 +1.08522E-004*Time2 (2b)

Fig.7 (a): Response surface of pH as a function of temperature and skin weight

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Fig.7 (b) : Response surface of pH as a function of time and skin weight

Fig.7 (c) : Response surface of pH as a function of time and temperature

(3) Color intensity

Final Equation in Terms of Coded Factors:

+1.35+0.075*A+0.029*B-0.17 * C+0.013 *A*B+0.040*A*C+0.075 *B*C+0.15*A2-

0.016*B2+0.10*C2 (3a)

Final Equation in Terms of Actual Factors:

+2.21999-1.88233*skinweight+3.50583E-003*temp-0.092352*Time+8.33333E-

003*skinweight*temp+0.017556*skinweight*Time+1.99333E003*temp*Time+1.68955*skin

weight2-6.42195E-004*temp2+1.78453E-003*Time2 (3b)

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Fig.8 (a): Response surface of color intensity as a function of temperature and skin

weight

Fig .8 (b) : Response surface of color intensity as a function of time and skin weight

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Fig.8 (c) : Response surface of color intensity as a function of temperature and time

(4) phenols

Final Equation in Terms of Coded Factors:

+97.29 +3.22*A+2.28*B+2.76*C-0.96*A*B+0.50*A*C+0.40*B*C+2.41*A2-2.00*B2-

0.46*C2 (4a)

Final Equation in Terms of Actual Factors:

+68.09454-11.03548*skinweight+3.11368*temp+0.22341*Time0.64167*skinweight*temp+

0.22333*skinweight*Time+0.010733*temp*Time+26.80028*skinweight2-0.079871*temp2-

8.21629E-003* Time2 (4b)

Fig. 9 (a) : Response surface of phenol as a function of temperature and skin weight

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Fig. 9 (b) : Response surface of phenol as a function of time and skin weight

Fig. 9 (c): Response surface of phenol as a function of time and temperature

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The individual prefermentative parameters have been reported in literature. Among

these, Beer et al (2006) investigated that pre-fermentation maceration, especially at 15°C,

resulted in wines with increased vitisin A content. Pre-fermentation skin contact at 10°C

increased the sensory quality of Pinotage wines compared to the control wine for three

separate vintages (Marais 2003). Pre-fermentation maceration at 10 and 15°C enhanced the

colour and anthocyanin content of red (Heatherbell et al 1997, Watson et al 1997, Reynolds et

al 2001, Gomez-Miguez et al 2006) and rose (Salinas et al 2003, Salinas et al 2005) wines.

The use of RSM for optimization of phenolic compounds extraction from cactus pear

(Opuntia ficus-indica) skin has been reported with time of extraction (h), concentration of

ethanol (%v/v) and temperature (oC) as variables (Jorge et al 2013).

4.3.2 Effect of enzymatic treatment on Grape “must” from Punjab purple

Pre-fermentation treatment with pectinase and combination of enzymes viz. Amylase,

Cellulase and Pectinase results in increase in juice recovery and clarity in grape juice (Vaidya

et al 2009). The combination of three enzymes i.e. pectinase (0.25ml/100ml), cellulase (0.125

ml/100ml) and amylase (0.085 ml/100ml) at 45 oC for 6h revealed the best clarity of the grape

juice as 78.7 % which was significantly higher than the individual enzyme and combination

of two other enzymes (Table 9) (Plate III).

Table 9: Effect of enzymatic treatment on Grape “must” from Punjab purple

Enzymes used % clarification (Mean ± SD)

Control 10.0± 1.26

Amylase 41.65±1.06

Cellulase 40.75±1.62

Pectinase 42.5±2.26

Amylase+pectinase 46.5±1.41

Pectinase+cellulose 63.4±1.27

Amylase+cellulose 57.45±0.91

Amylase+pectinase+cellulose 78.7±1.13

Enzymes degrade the polysaccharide gel formed in different fruit pulps and thus

reduce their viscosity and also improve the juice filtration (Qin et al 2005). Earlier, Rai et al

(2004) observed that at constant time and temperature, the clarity increases with increasing

enzyme concentration but at constant temperature and enzymatic concentration, the juice

clarity varies nonlinearly with the duration of treatment.

Earlier, Espedo and Armada (2010) observed decrease in juice turbidity by pectinase

treatment of grape juice from Pedro Ximenez Variety of grapes. They also standardized

increased juice yield by enzyme addition along with dynamic maceration. Mojsov et al (2011)

reported increase in clarity of wine filterability, settling of solids and wine quality when grape

mashes of Smederevka were treated with different pectolytic enzyme preparation. Such effects

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of pectinase enzyme treatment have been reported in other fruit juices.

Elsewhere, Norjana and Noor Aziah (2011) reported that the juice yield was

increased by 35% using 0.1% pectinase concentration for 3 h of incubation in Durain fruit

(Durio zibethinus Murr) juice. Karangwa et al (2010) optimized conditions for carrot-orange

juice as 0.06% (w/v) of enzyme concentration, 3.6 pH, 49ºC temperature and 91 min of

reaction time. The enzymatic treatment in Kiwifruits studied by Vaidya et al (2009) reported

enhanced juice recovery by 78.46% as compared to control (58.44%). In his study, they used

combination of enzymes (Pectinase 0.025g/kg, amylase 0.025g/kg and Mash enzyme

0.05g/kg for 2 h at 50°C) for clarification of Kiwifruits.

4.4 Ethanol fermentation of pretreated grape juice

A combined source of Nitrogen and Phosphorus viz. Di-ammonium Hydrogen ortho

Phosphate (DAHP) was supplemented (50-250mg/100 ml) in the “must” of grape juice for

optimization under standardized conditions of 20°B, 25°C and fermented by S.cerevisae

strain 35 (Plate IV) inoculum size of (5% v/v).

4.4.1 Effect of DAHP supplementation

The effect of DAHP supplementation (50-250 mg/100ml) on ethanolic fermentation

of Grape juice by S.cerevisae strain 35 was studied. DAHP increases the activity of yeast by

providing the required nitrogen and phosphorus which accelerates the fermentation process

and increases the ethanol production (Ugliano et al 2007). Results presented in table 10 (also

see Table II, Annexure) reveal 150mg/100ml as the optimized concentration of DAHP for

maximum ethanol production from grape juice with a fermentation efficiency of 94.5%

compared to 85.93% in control. The brix values were not zero as the same was measured by

refractrometer in which the produced ethanol interferes (www.moundtop.com).

For a number of fruits, the nitrogen content is insufficient and supplements are made

by the addition of ammonium phosphate or of diammonium phosphate (DAP) before

fermentation. KH2PO4 (46.1g/L) was found to be better phosphorus source in comparison

with K2HPO4 (45.3 g/L) and (NH4)2SO4 (46.1 g/L) was the best nitrogen source as compared

to NaNO3, (NH4)H2PO4, NH4NO3 for the production of red wine from ‘Siahe sardarsht’ grape

variety (Asli 2010). It was observed that higher concentrations of DAHP i.e 400 and 500 mg/

100ml juice produce less ethanol due to reduction in cellular activity of yeast. Ghosh et al

(2010) also found that higher DAHP concentrations produce less ethanol as compared to less

concentration as with higher concentration of nitrogen, cellular activity of yeast gets inhibited

and ethanol production is affected. They also reported that DAHP was better nitrogen source

than urea for fermentation carried out by S.cerevisae. It has been suggested that nitrogen

management is also critical for wine flavour and style and practice of supplementation of

nitrogen, particularly DAHP (a combined source of N & P) has started in wineries (Ugliano et

al 2007).

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Plate III: Enzyme (Pectinase + Amylase + cellulase) treatment of grape juice,

A-treated juice

B- Untreated juice

Plate IV: Phase contrast microscopic image (45X) of Saccharomyces

cerevisiae strain 35.

A B

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Table 10: Effect of di-ammonium hydrogen ortho phosphate (DAHP) concentration on ethanol fermentation of Grape juice.

%Eth-Ethanol (%) v/v ; R.S – reducing sugars % Cultural Conditions:

Actual ethanol produced Scale of fermentation : 300 ml

**Fermentation Efficiency % (v/v) = --------------------------------- × 100 Brix : 20°B

Theoretical ethanol produced Temperature : 25°C

Theoretical Ethanol % (v/v) = available sugar × 0.64 Inoculum size : 5% v/v

DAHP concentration (mg/100ml)

Control (0 ) 50 100 150 200 250 Time

(days)

pH Brix (R.S

mg/100ml) %Eth pH

Brix

(R.S) %Eth. pH

Brix

(R.S) %Eth pH

Brix

(R.S) %Eth pH

Brix

(R.S) %Eth pH

Brix

(R.S) %Eth

1 3.5 16 (13.1) 0.1 3.4 16.5

(15.0) 1.1 3.4

17

(15.4) 1.0 3.3

17.5

(14.4) 1.4 3.2

17

(16) 0.96 3.4

16.5

(14.74) 0.55

2 3.4 9 (7.8) 6.8 3.3 10.5

(8.5) 6.45 3.0

10

(7.4) 6.75 3.2

8.25

(6.5) 7.5 3.1

11

(9.4) 6.35 3.3

11.5

(9.1) 6.46

3 3.0 2 (0.42) 11.0 3.1 4.5

(0.80) 11.35 3.0

3.5

(0.45) 11.65 3.0

0

(0.3) 12.1 3.1

5

(0.7) 10.8 3.1

5.5

(0.83) 10.4

**F.E 85.93 88.67 91.0 94.5 84.3 81.2

CD ethanol

(5%)

Fermentation time – 0.379

DAHP conc. – 0.536

49

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The scale up studies on grape wine at 5L scale validated under the optimized

conditions presented an ethanol production of 12.13±0.25% v/v having total phenols of

111.046 mg/100ml and total ascorbic acid content of 686.23±6.7 mg/100ml. A pictorial

representation of the preparation of red wine from Punjab purple grapes is also presented in

Plate V.

4.5 Effect of recycled yeast

The wort from the first experimental batch where the fermentation had just completed

was used as inoculum (2x108cells/ml) of recycled yeast. Four levels of inoculum sizes i.e. 5,

10, 15 and 20% v/v with direct microscopic counts of 3x109 to 1.2x1010cells/ml were used in

triplicate. The recycling was repeated for upto 2 subsequent lots and fermentation efficiencies

were compared. The results present in Table 11 (also see Table III, Annexure) revealed

increase in ethanol produced with 10% (v/v) inoculum while higher inoculum sizes reported

lower ethanol levels represented 10% (v/v) inoculum (from previous lot) produce statistically

similar ethanol production which is attributed to the fact that higher biomass requires more

sugars for its growth. The same was also reflected in the fermentation efficiencies of different

levels. However, the lots, the first recycled lot (Lot 1) reflected a decrease in ethanol from

fresh inoculum but second lot (Lot 2) produced statistically similar ethanol levels as that of

fresh inoculum lot.

There was no decrease in number of fermentation days for ethanol production,

however, the residual sugars decreased after successive lots. Earlier, Puri et al (2012) also

reported 20% inoculum level for recycling sugarcane fermentation batches. Strehaiano and

Gowa (1983) observed 10% inoculum concentration and Yadav et al 1997 reported 30%

inoculum level as optimum for improved ethanol production and high fermentation efficiency.

The lower efficiencies observed in our studies may be attributed to sustain the initial high

inoculum levels. However, the present study suggests that recycled yeast (10%v/v) is suitable

for wine preparation as the final ethanol concentration of the successive lots is same as that of

fresh yeast inoculum lot.

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Juice

extraction

Enzymatic treatment

(45ºC,6h and pectinase

(0.25ml/100ml), cellulase (0.125

ml/100ml) and amylase (0.085

ml/100ml)

Optimization

of DAHP and

recylced

inoculum

Grapes

(Punjab purple Syn H516)

0.15% DAHP

(w/v) and 10%

yeast recycled

inoculum

Ethanolic fermentation

Decantation

and storage

Grape wine

Skin treatment

(0.25Kg/L,20oC,16h)

Plate V: Pictorial Diagram for preparation of red wine (Punjab purple,Syn H-516).

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Table 11: Effect of recycling of yeast on ethanol fermentation of Grape juice.

*Initial number of cells- 2x108 cells/ml Culture conditions:-

%Eth-Ethanol (%) v/v ; R.S – reducing sugars %

Actual ethanol produced Scale of fermentation : 300 ml

**Fermentation Efficiency % (v/v) = -------------------------------------- × 100 Initial Brix : 20°B

Theoretical ethanol produced Temperature : 25°C

Theoretical Ethanol % (v/v) = available sugar × 0.64 Inoculum size : 5%v/v (fresh)

Inoculum level (% v/v)

5 10 15 20

Time

(days) pH Brix (R.S)

%Eth

(F.E) pH Brix (R.S)

%Eth

(F.E) pH Brix (R.S)

%Eth

(F.E) pH

Brix

(R.S)

(F.E)

%Eth

1 3.5 12(10.8) 2.55 3.45 10.5(8.75) 4.6 3.5 11(8.51) 3.2 3.4 9.5(6.1) 3.47

2 3.45 6.75(3.65) 5.1 3.4 3.25(1.9) 8 3.4 4(2.15) 5.6 3.35 3.25(1.45) 4.95

FRESH

LOT

3 3.35 3.25(1.35) 8.92

(69.68) 3.45 2.25(0.43)

9.54

(74.53) 3.4 3.75(1.65)

8.76

(68.43) 3.3 3(1.09)

9.5

(74.21)

1 3.5 13.5(11.77) 3.95 3.5 12(10.55) 4.7 3.5 8(5.56) 5.3 3.5 6(4.56) 5.5

2 3.45 7.75(5.74) 5.45 3.35 5.5(3.93) 6.3 3.35 5(3.81) 5.65 3.5 4(2.50) 6.5

LOT 1

3 3.35 4.25(1.12) 8.4

(65.62) 3.25 3.5(1.11)

8.14

(63.59) 3.25 3.25(0.95)

7.36

(57.5) 3.35 3(0.40)

8.3

(64.84)

1 3.5 10(8.69) 3.25 3.5 11(9.76) 3.25 3.5 9.5(7.4) 2.50 3.5 10.5(7.43) 2.86

2 3.45 5(1.85) 5.55 3.25 5(1.76) 6.50 3.35 4.5(1.68) 4.60 3.35 4(1.47) 4.95

LOT 2

3 3.35 3(0.71) 9.67

(75.54) 3.2 2(0.44)

9.97

(77.89) 3.3 2.5(0.53)

8.53

(66.64) 3.25 3.5(0.57)

6.85

(53.51)

F.E.

(%) 70.28 ±4.98 71.9 ± 7.48 64.18 ± 5.84 64.18 ± 10.36

CD

(5%) Ethanol -0.338

51

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4.6 Post fermentation treatment

4.6.1 Storage study

The grape wine prepared under the optimized fermentation conditions of Brix (20°B),

temperature (25°C), 5% (v/v) inoculum size of fresh and 10% (v/v) recycled yeast and DAHP

(0.15%) supplementation was subjected to settling for 7 days at refrigerated conditions (4°C)

in glass bottles. Afterwards, the bottles were stored at 15°C and every 15 days upto 6 months,

the process of racking was repeated. During this course, various physiochemical and

microbiological parameters were observed which are presented in table 12 (also see Tables IV

and V, Annexure).

Table 12: Effect of storage time on microbiological and physicochemical properties of

Wine var. Punjab purple

Parameters

% ethanol (v/v) pH Total phenols*

(mg/100ml)

Total yeast count

(cfu/ml)

Storage

Time

(days)

Fresh

yeast

inoculum

With

recycled

yeast

inoculum

Fresh

yeast

inoculum

With

recycled

yeast

inoculum

Fresh

yeast

inoculum

With

recycled

yeast

inoculum

Fresh

yeast

inoculum

With

recycled

yeast

inoculum

0 12.10 9.97 3.4 3.5 222.6 207.1 6.2X106 7.3X10

6

15 11.63 9.86 3.4 3.4 210.9 201.4 1.1X101 2.1X10

1

30 11.49 9.64 3.4 3.4 206.2 180.6 0.1X101 0.3X101

45 11.22 9.53 3.4 3.4 187.4 175.9 0.0 0.0

60 10.89 9.36 3.3 3.4 145.8 155.7 0.0 0.0

75 10.71 9.19 3.3 3.3 138.8 141.4 0.0 0.0

90 10.66 9.10 3.3 3.3 106.6 127.2 0.0 0.0

120 10.45 8.99 3.3 3.3 102.4 112.9 0.0 0.0

150 10.42 8.91 3.3 3.3 100.2 110.4 0.0 0.0

CD

(5%)

CD (days)-0.508

CD (inoculum)-

0.239

NS CD (days)-8.25

CD (inoculum)- NS

-

*% decrease in phenols in fresh yeast inoculum wine- 55%

*% decrease in phenols in recycled yeast inoculum wine- 47%

Total SO2 = 22.1 ppm

Free SO2 = 8.2 ppm

The results revealed that fresh yeast used as inoculum was significantly better than

recycled yeast though a significant decrease in % ethanol was observed in both inoculums.

Moreover, the decrease in ethanol became constant after about 15 days of storage till 150 days

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upto which storage studies were carried out. pH showed no change in both the treatments. The

decrease in total phenols was significant with storage and total phenols decreased (from fresh

wine) to 55 and 47% in fresh and recycled yeast inoculum, respectively. Zafriella et al (2003)

reported upto 90% decrease of anthocyanins with no change in flavonol content of red wines

during storage. It was also observed that the decrease in phenols stabilized after 90-120 days

of storage. Similar trends have been reported in white and merlot wines. While Kallithraka et

al (2009) observed a decrease in total phenols upto 6 months, Ivanova et al (2009) reported a

continuous decrease of phenols upto 16 months of storage that they studied. Another

important observation was the absence of viable yeast cells after 30 days of storage in the

racked wine suggesting that yeast tends to settle quickly during storage (Table 12).

The free and total sulphur dioxide in the stored wine was also analyzed. The wine

from fresh yeast culture was having 22.1 ppm of total SO2 and 8.2 ppm of free SO2 at 150

days of storage which is less than the recommended value of 150-400 and 25-40 ppm

respectively for red wines (www.morewine.com; www.eco-consult.net). Sims and Morris

(1984) reported that sulfur dioxide levels higher than 25 ppm free SO2 severely bleached the

color of red muscadine wine and lessened browning in high pH wine only. High SO2 levels

also lessened browning of wine stored at 20°C, but not at higher storage temperatures.

4.6.2 Thin Layer chromatography (TLC)

The qualitative analysis of wine w.r.t amino acids carried out by TLC is presented in

table 13. The spots were observed at a distance of 2.5 cm, 4.7cm, 7.6 and 9.9 showing Rf

values of 0.16, 0.30, 0.46 and 0.63, respectively as distance travelled by the solvent was 15cm

(Plate VI). The standard amino acids were also run on thin layer chromatograms and

compared with the spots of wine thin layer chromatograms. Based on the comparison and the

literature (tera.chem.ut.ee; www.reachdevices.com) the Rf values were designated to the

presence of histidine, arginine, lysine, threonine, methionine, alanine, valine, tyrosine,

methionine, valine in red wine (Table 13).

Table 13: Qualitative analysis of Amino acids by Thin Layer chromatography (TLC).

Distance travelled by

spot Rf value* Amino acid**

2.5 0.16 Histidine/ Arginine/Lysine

4.7 0.30 Threonine

7.6 0.46 Methionine/Alanine/Valine/Tyrosine

9.9 0.63 Methionine/Valine

Distance travelled by the solvent-15 cm *Rf = Distance travelled by spot

Distance travelled by solvent

**The ‘/’ indicates similar Rf values of amino acids

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4.7 Sensory analysis of wine

The red wine samples were subjected to sensory analysis to find out the acceptability

among the tasting panelists. The results of sensory evaluation of 150 days old red wine are

presented in table 14 (also see Tables VI, Annexure). The wines prepared from Punjab purple

under optimized conditions with fresh and recycled yeast inoculums were found to be of

standard quality with mean score of 65.9±8.01 and 63.3±8.52, respectively at 150 days of

storage whereas commercial wine (‘Galaxy’ brand of N.D wines Pvt. Ltd., Nasik) was also

found to be of standard quality but with a lesser mean score value of 56.2±9.47 (Table 14).

Hence, red wine prepared from fresh yeast inoculum was significantly better than commercial

wine whereas the red wines prepared from recycled yeast inoculum and fresh yeast inoculum

were insignificantly different from each other.

In literature, Kocher et al (2009) studied the sensory characteristics of Grape wines

(white and red wines both) prepared from five different grape varieties/hybrids and reported

species specific variation in sensory characteristics of grape wines. Soni et al (2009) observed

that matured Amla wine was better than unmatured wine in terms of its sensory attributes.

They also reported that Amla wine matured in oak wood barrel had higher quantity of

desirable components including ethyl acetate and phenolics etc. and was better in its sensory

characteristics than the wine stored in glass bottles.

Table 14: Sensory evaluation of grape wine (var. Punjab purple) at 150 days of storage

Types of red wine Sensory

analysis

(characters)

Maximum

points Commercial Fresh yeast

inoculum

Recycled yeast

inoculum

Appearance 16 12.2±3.73 13.8±2.27 13±2.04

Taste 24 15.8±2.48 17.9±3.44 17.6±2.28

Aroma 24 16.2±4.48 19.8±3.34 18.3±4.53

Total acidity 8 7.0±1.61 7.8±0.6 7.8±0.6

Overall feel 8 5.0±1.34 6.6±0.9 6.6±0.9

Total 80 56.2±9.47 65.9±8.01 63.3±8.52

CD (5%) 4.076

* The above scoring is mean + standard deviation of evaluation by 10 panelists.

Ratings:

Superior (68-80)

Standard (52-68)

Below standard (36-52)

Unacceptable/ Spoiled (4-36)

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PLATE VI: Thin Layer Chromatogram of amino acids in red wine. A: Distance

travelled by solvent=15cm; B= Histidine/ Arginine/ Lysine - 2.5cm; C=Threonine -

4.7cm; D=Methionine/ Alanine/ Valine/ Tyrosine - 7.6cm; E=Methionine/ Valine - 9.9cm

A

B

C

D

E

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CHAPTER V

SUMMARY

Grapes are the foremost substrates used worldwide for wine production. However,

there are no wineries in this part of the country, though central and south Indian states like

Maharashtra, Karnataka have some of them. Further, grape production in Punjab is declining

and there are no wine varieties cultivated in Punjab. The Departments of Microbiology and

Fruit science have been evaluating different grape cultivars/ varieties for their wine potential

for the past about 5 years. In this regard, one variety, Punjab purple (syn H516) has been

identified and a laboratory scale technology standardized for red wine production for it.

However, a number of pre-fermentative and post fermentative parameters still need to be

optimized. Hence, the present study was conducted to study the effect of pre- and post

fermentation treatments on quality of red wine preparation from Punjab purple grapes.

Initially, physico-chemical characteristics of juice in terms of TSS (16±2.0°B), acidity

(0.30±0.06 %, w/v), pH (3.3±0.2), brix-acid ratio (58.33 ± 8.33), ascorbic acid (615.38 ± 15.3

mg/ 100 ml) and total phenols (98.49 ± 13.26 mg/100ml) in freshly extracted juice were

analyzed from the destemmed and crushed berries.

In the present study, an important prefermentative treatment i.e. skin contact of juice

was optimized w.r.t. Temperature, Time and Skin weight by applying Central Composite

Rotatable Design (CCRD) under Response surface methodology (RSM) using Statistical

software “Design Expert software 8.0”.The response provided in terms of pH, Brix, color

intensity and phenols (mg/100ml) revealed a combination of 20oC temperature, 16 hr skin

contact time and 0.25 Kg/L skin weight having phenols 100.18 mg/100ml, color intensity

1.399 at OD620nm with 13OBrix and 3.487 pH as optimum. The juice pretreated under these

optimized conditions was subjected to enzymatic treatment with pectinase (0.25ml/100ml),

cellulase (0.125 ml/100ml) and amylase (0.085 ml/100ml) individually and also in

combinations of enzymes i.e. Amylase+pectinase, Pectinase+cellulase, Amylase+cellulase,

Amylase+pectinase+cellulase at 45 oC for 6h. The treatment with combination of three

enzymes giving 78.7 % clarification was significantly higher than the individual enzymes and

treatments having combination of enzymes. Hence, the dual pretreatment of juice

standardized for its skin contact and enzymatic treatment was used for fermentation.

The ethanol fermentation of pretreated grape juice was carried out at already

standardized conditions of 20oB, 25

oC temperature and inoculum size of 5% (v/v) for the

optimization of DAHP supplementation (50-250 mg/100ml) by S.cerevisae strain 35. The

effect of DAHP supplementation at the rate of 150mg/100ml produced significantly higher

ethanol of 12.10% (v/v) as compared to untreated control 11.0% (v/v) from grape juice with

fermentation efficiencies of 94.5% and 85.93%, respectively. The red wine so produced from

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Punjab purple was also scaled upto 5L producing 12.13% (v/v) ethanol that also validated the

results obtained at flask level.

Thereafter, experiments were also conducted to study the effect of recycling of yeast

inoculum from previous fermentation lots so that the process may be economized in terms of

fermentation time. The worts from experimental batches where the fermentation had just

completed were used as inoculum (2x108 cells/ml) of recycled yeast. Four levels of inoculum

sizes i.e. 5, 10, 15 and 20% (v/v) with direct microscopic counts of 3x109 to 1.2x10

10 cells/ml

were used and the recycling was repeated for upto two lots. The successive lots of 5 and 10%

inoculum levels represented insignificant changes in final ethanol produced i.e. 9.67 and 9.97

(v/v), respectively but with increase in inoculum size, the overall ethanol production

decreased. The same was also reflected in the fermentation efficiencies in the combined

fermentation efficiencies of three lots of different inoculum levels. Also, there was no

reduction in fermentation time with variable inoculum levels.

The red wine prepared under the optimized fermentation conditions of Brix (20°B),

temperature (25°C), inoculum size 5% (v/v) for fresh and 10% (v/v) for recycled yeast and

150 mg/100ml DAHP supplementation was subjected to settling for 7 days at refrigerated

(4°C) conditions in glass bottles. Afterwards, the bottles were stored at 15°C±5°C and every

15 days for upto 3 months, the process of racking was repeated. The wine (post storage)

prepared from fresh yeast was found to be significantly better than recycled yeast, though the

decrease in % ethanol was also significant. The decrease in total phenols was also significant

with storage as total phenols decreased to 55 and 47% of the initial values in fresh and

recycled yeast, respectively. The free and total sulphur dioxide in the stored wine was also

analyzed. The wine from fresh yeast culture was having 22.1 ppm of total SO2 and 8.2 ppm of

free SO2 at 150 days of storage which is less than the recommended values of 150-400 and

25-40 ppm, respectively for red wines. The qualitative analysis of wine w.r.t amino acids

carried out by TLC revealed the presence of Histidine/Arginine/Lysine, Threonine,

Methionine/Alanine/Valine/Tyrosine, Methionine/valine in red wine.

The prepared wine was subjected to the sensory analysis at 150 days of storage vis-a-

vis commercial wine (‘Galaxy’ brand of N.D wines Pvt. Ltd., Nasik). The red wines prepared

from Punjab purple under optimized conditions with fresh inoculum and recycled yeast

inoculum were found to be of standard quality with mean scores of 65.9±8.01 and 63.3±8.52,

respectively whereas commercial wine was found to be of standard quality but with a lesser

mean sensory score of 56.2±9.47. Thus, the present study successfully optimized the

prefermentation conditions in term of skin contact (0.25 Kg/L), enzymatic treatment

(Amylase+pectinase+cellulase :: 25+50+25 units/ 100 ml). The addition of DAHP

(150mg/100ml) improved the fermentation efficiency and the prepared red wine was found to

be superior than the commercial red wine tested.

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57

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Table I: Modified Davis Score Card for Sensory analysis of wine

Wine sample_____________ Name of Panelist_________________

Fruit variety_____________ Date of analysis _________________

Ethanol (w/v) _____________ Titrable acidity __________________

Characteristic Weight Score points

Excellent

(4)

Good

(3)

Average

(2)

Mediocre

(1)

Poor

(0)

Visual

Appearance (clarity, no

suspended material)

2

Colour (pale green & purple rosy

desirable;& off colours

undesirable )

2

Taste

Astringency (pickery feel) 1

Body (full i.e high alcohol

desirable) 1

Sweetness/bitterness (Very sweet

and very bitter undesirable) 1

Sourness (vinegar undesirable) 1

Flavour ( mouth feel when wine

kept in mouth for few seconds) 2

Olfactory

Aroma (wine odour derived from

guava), shouldn’t be too earthy,

stemmy or moldy

3

Bouquet (odour developed

during fermentation, processing

or aging)

Yeasty &burning undesirable

3

Total acidity (titrable) 2

General quality (Overall feel) 2

Total score (Out of 80)

Ratings: Superior- (68-80); Standard- (52-68); Below standard-(36-52);

Unacceptable/ Spoiled(4-36)

ANNEXURES

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ii

TABLE II: Analysis of Factorial Experiment in CRD for DAHP (Table 10, Results and Discussion)

No. of reps.= 2 No. of factors= 2

TREAT. COMBINATION MEANS

1 .10000000 6.8000000 11.000000 1.1000000 6.6500000

6 11.350000 1.0750000 6.3500000 11.650000 1.4000000

11 7.5000000 12.100000 .96000000 6.9500000 10.800000

16 .55000000 6.7000000 10.400000

FACTOR MEANS

1 6.1666670 6.6791670 6.0600000

2 .71166680 6.7000000 11.150000 1.0166670 6.9499990 11.283330

ANOVA TABLE

SOURCE d.f. M.S. F-Ratio CD(5%) C.V.

A 2 1.3149620 6.71 .379451

B 5 129.69810 662.08 .536625

AB 10 .42424320 2.17 NS

Error 18 .19589570 7.02

TABLE III: Analysis of Factorial Experiment in CRD for Recycling (Table 10, Results and Discussion)

No. of reps.= 2 No. of factors= 3

TREAT. COMBINATION MEANS

1 2.5000000 4.4500000 3.3500000 3.6850000 3.8600000

6 4.5000000 5.1500000 5.6000000 3.3500000 3.4000000

11 2.6000000 2.8100000 4.9500000 7.9000000 5.7000000

16 4.9800000 5.5500000 6.5000000 5.7500000 6.7500000

21 5.6550000 6.4500000 4.4500000 4.9750000 8.9600000

26 9.6399990 8.8099990 9.6000000 8.2999990 8.2400000

31 7.3100000 8.2000010 9.7700000 9.9850010 8.4950000

36 6.7450000

FACTOR MEANS

1 4.0494440 4.9322220 6.8266660 8.5161110

2 5.2837500 5.9791670 6.9804170

3 6.0600000 6.3162500 5.8670830

ANOVA TABLE

SOURCE d.f. M.S. F-Ratio CD(5%) C.V.

A 3 71.596100 2563.07 .112944

B 2 17.459150 625.02 .978126E-01

AB 6 9.4375170 337.85 .195625

C 2 1.2186690 43.63 .978126E-01

AC 6 1.0220740 36.59 .195625

BC 4 1.2968350 46.43 .169416

ABC 12 2.8804780 103.12 .338833

Error 36 .27933760E-01 2.75

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iii

TABLE IV: Analysis of Factorial Experiment in CRD for storage phenols

(Table 12, Results and Discussion)

No. of reps.= 2 No. of factors= 2

TREAT. COMBINATION MEANS

1 222.60000 207.90000 210.90000 201.40000 206.20000

6 180.60000 187.40000 175.90000 145.80000 155.70000

11 138.80000 141.40000 106.60000 127.20000 102.40000

16 112.90000 100.20000 110.40000

FACTOR MEANS

1 215.25000 206.15000 193.40000 181.65000 150.75000

140.10000 116.90000 107.65000 105.30000

2 157.87780 157.04440

ANOVA TABLE

SOURCE d.f. M.S. F-Ratio CD(5%) C.V.

A 8 7390.2420 239.39 8.25056

B 1 6.3402780 .21 NS

AB 8 228.87930 7.41 11.6681

Error 18 30.871530 3.53

TABLE V: Analysis of Factorial Experiment in CRD for storage ethanol (Table 12, Results and Discussion)

No. of reps.= 2 No. of factors= 2

TREAT. COMBINATION MEANS

1 12.100000 9.9700000 11.630000 9.8600000 11.485000

6 9.6450000 11.220000 9.5300000 10.715000 9.3600010

11 10.710000 9.1900010 10.660000 9.1000000 10.450000

16 8.9900000 10.420000 8.9100000

FACTOR MEANS

1 11.035000 10.745000 10.565000 10.375000 10.037500

9.9500010 9.8800000 9.7200000 9.6650000

2 11.043330 9.3950000

ANOVA TABLE

SOURCE d.f. M.S. F-Ratio CD(5%) C.V.

A 8 .93148800 7.96 .508123

B 1 24.453450 208.84 .239532

AB 8 .56233640E-01 .48 NS

Error 18 .11709260 3.35

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TABLE VI: Analysis of Factorial Experiment in CRD for sensory evaluation (Table 14, Results and Discussion)

No. OF REP = 3 No. OF TREATMENTS = 6

TREATMENT MEANS

1 13.000 2 17.100 3 18.100 4 7.533 5 6.067

6 61.800

ANOVA TABLE

SOURCE d.f. M.S. F-Ratio F-TABLE(5%)

Treatments 5 1293.3930 246.55 3.11

Error 12 5.2460120

G.M.= 20.600 C.V.= 11.12 CD(5%) = 4.076

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v

VITA

Name of the student : Maninderjeet Kaur

Father’s name : S. Amarjit Singh

Mother’s name : Smt. Ranjit Kaur

Nationality : Indian

Date of birth : 29.11.1991

Permanent home address : Ward No. 1, Street No.9, House no. 1760,

Mansa-151505, Punjab.

EDUCATIONAL QUALIFICATION

Master’s degree : Integrated Master of Science (Hons.) in

Microbiology

University and year of award : Punjab Agricultural University, Ludhiana

(2013)

OCPA : 8.03/10.00

Title of Master’s Thesis : Effect of pre and post fermentation

treatments on quality of red wine preparation

from Punjab purple grapes.