Thesis Defence

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Thesis defence for MSc

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Sensory, chemical and consumer analysis of Brettanomyces

spoilage in South African wines

Janita BothaThesis defence

17 February 2009

Research Team:

M Muller, W J du Toit, A J de Villiers & A G J Tredoux

Project background

FermentationMalo-lactic Fermentation

Barrel Aging

Bottle

Saccharomyces cerevisiae

Oenococcus oeni

Other LAB

Brettanomyces/

Dekkera

Ethanol

CO2

Lactic acid

Diacetyl

Furfural

Guaiacol

Eugenol

Etc

Brett-related spoilage compounds

+

user
Ek weet ek het al nog met ELKE presentation hier slide gebruik, maar dit is 'n maklike manier om almal weer op dieselfde (Brett) bladsy te kry as waar hulle was

Sensory studies about Brett

Chatonnet et al. (1992): Linked 4-ethylphenol and 4-ethylguaiacol to

BrettanomycesDetection thresholds of 4-EP and 4-EGCommonly quoted study

Licker et al. (1999): Linked isovaleric acid to Brettanomyces

Hesford & Schneider (2004): Linked 4-ethylcatechol to Brettanomyces

Recent sensory studies

Curtin et al. (2008):Detection thresholds of 4-EP, 4-EG and 4-ECProfiling of certain combinationsConsumer analysisRecommend further studies

Romano et al. (2009):Found further strong links between 4-EP and

isovaleric acid Investigated effect of isovaleric acid on

detection thresholds of 4-EP and 4-EG

Isovaleric acid?

4-ethylcatechol?

Research Aims

Determine the sensory

detection thresholds of 8 Brett-related compounds

To determine the sensory profiles of 4 Brett-related

compounds

To determine the sensory interactions of 4 Brett-

related compounds

To determine the consumer preference of 4 Brett-related

compounds

Chapter 1

Chapter 2

Chapter 3

To investigate realationships between 8

Brett-related compounds in selected South African

wines

Chapter 4

Research Chapter 1:Detection Thresholds

Materials and Methods

Method based on ASTM E 679 – 04

3-Alternative Forced Choice (3-AFC)

3 glasses of wine presented, 1 contains the Brett compound

8 levels of 8 compounds tested

Difference known, judges therefore

trained

Materials and Methods

Concentration increases with a constant MF factor on log scale

Two calculation methods investigated: ASTM and median

0

400

800

1200

1600

2000

1 2 3 4 5 6 7 8 9 10

Level

Co

nc

en

tra

tio

n (

μg

/L)

Results: 4-ethylphenol

LLLL

ASTM

Median

UL

UL

0

50

100

150

200

250

300

350

400

Median ASTMCalculation method

Con

cent

ratio

n (μ

g/L)

Level 5

Level 2

Level 4

Level 3

Level 1

Outlier

Larger range

Results: 4-ethylcatechol

LLLL

ASTMMedian

UL

UL

0

200

400

600

800

1000

1200

Median ASTMCalculation method

Con

cent

ratio

n (μ

g/L)

Level 3

Level 4

Level 5

Level 6

Level 7

Level 8

True rangeSimplified

range

Conclusions

Concept of “detection threshold” is limited and obscures information

The use of a detection threshold range more accurate

Range provided by median more informative about population

Research Chapter 2: Singular Profiling

Materials and Methods:Central composite design

Com

poun

d 1

Compound 2

Compound 3Singular profiling exploration step

before compounds can be tested in

combination

Materials and Methods: Singular profiling

4-EP

4-EG

4-EC

Isovaleric acid

0 2 431 5

DTValues

determined used as guide

Levels pre-screened to

confirm suitability for use in new

medium

Example of linear results: 4-EP

0

10

20

30

40

50

60

70

0 2 4 6 8 10 12 14Level of 4-ethylphenol

Inte

nsi

ty o

f d

escr

ipto

r

Elastoplast

Leather

Berry-like

Sick-sweet

Mirroring

Following

Example of linear results: 4-EP

0

10

20

30

40

50

60

70

0 2 4 6 8 10 12 14Level of 4-ethylphenol

Inte

nsi

ty o

f d

escr

ipto

r

Elastoplast

Leather

Berry-like

Sick-sweet

Example of Discriminant Analysis: 4-EP

0000

0

000

0

0

1

1

1

1

11 1

1

11

2 2

2

22

2

2

2

2

2

33

3

L3

3

3

3

3 3

3

444

4

444

4

44

5

5

55

5

5

5

5

5

5

5

4

3

21

0

-6

-4

-2

0

2

4

6

-6 -4 -2 0 2 4 6

F1 (78.64 %)

F2

(19.

88 %

)

012345Centroids

Level

Example of PCA: 4-EP

5

5

55

5

5

5

5

5

5

4

4

4

4

44

4

4

4

4

33

3

3

3

3

3

33

3

2

2

2

22

2

2

2

2

2

1

1

1

1

1 11

1

1

1

00000

0000

0

Elastoplast

Leather

Sick-sweet

Berry-like

-1.5

-0.5

0.5

1.5

-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8

F1 (86.81 %)

F2

(8.9

0 %

)Similar pattern in univariate results

Overall results

4-EP 4-EG 4-EC Isovaleric acid

Elastoplast Leather Medicinal Smoky Savoury Pungent

Sick-sweetBerry-like

Not in literature

Clove-like??

More detail obtained about the contributions of the respective compounds

Research Chapter 3:Combination Profiling

Materials and Methods:Design

Com

poun

d 1

Compound 2

Compound 3

Samples

Materials and Methods: Samples

24444444

424422444424242442242224444224424242224244222422422222225333133335333133

33533313

333533313333

Isovaleric acid4-EC4-EG4-EP 1 Centre Sample

8 Star Samples

16 Cube Samples

Results: Interaction

Elastoplast: 4-EP*4-EG*4-EC4-EP*4-EG*ISOV

Medicinal:4-EG cause increase4-EC and isovaleric acid cause decrease

Pungent:ISOV*4-EG4-EP cause increase

All four compounds affect intensity of Elastoplast descriptor

Compounds have different effects at different levels

Intensity affected by other compounds present

“Sweaty leather” aroma attributed to Brett?

PCA vs PARAFAC: sensory data

Judges

Sam

ples

Attributes

Sam

ples

Attributes

Judge 1 Judge 2 Judge n

PCA: Analysis of (unfolded) 2-way data

PARAFAC: Analysis of data cube

Effects of judges not ignored Often simplified by finding mean over judges

PCA vs PARAFAC

1st factor calculated

Subsequent orthogonal factors

calculated

1st factor calculatedSubsequent factors

calculated in sucessive directions

of variance

Factors recalculated untill they converge

PCA

PARAFAC

Less noise modelled

Biplot (axes F1 and F2: 67.45 %)

5333

4444

4442

4424

4422

42444242

4224

4222

3533

33533335

3333

33313313

3133

24442442

2424

2422

2244

2242

22242222

1333

Medicinal

Savoury

Pungent

Elastoplast

Sick-sweet

Berry-like

-4

-3

-2

-1

0

1

2

3

4

-5 -4 -3 -2 -1 0 1 2 3 4 5 6

F1 (37.92 %)

F2

(2

9.5

3 %

)

PCA of profiles

Biplot (axes F1 and F2: 67.45 %)

5333

4444

4442

4424

4422

42444242

4224

4222

3533

33533335

3333

33313313

3133

24442442

2424

2422

2244

2242

22242222

1333

Medicinal

Savoury

Pungent

Elastoplast

Sick-sweet

Berry-like

-4

-3

-2

-1

0

1

2

3

4

-5 -4 -3 -2 -1 0 1 2 3 4 5 6

F1 (37.92 %)

F2

(2

9.5

3 %

)

Detection threshold change

PARAFAC – factor 1 vs 2

Berry-like

ElastoplastMedicinal

Pungent

Sick-sweetSavoury

Factor 1: ElastoplastFactor 2: Berry-like

PARAFAC – factor 2 vs 3

Pungent

Berry-like

Sick-sweet

SavouryMedicinal

Elastoplast

Factor 3: Pungent, Medicinal, SavouryPungent related to group with highest levels of 4-EP

Conclusions: Combination profiling

Elastoplast

Berry-like

PungentMedicinalSavoury

Sick-sweet

Hierachy of descriptors:

Results of PARAFAC complementary to PCA and univariate results

4-EP related to pungency

Consumer analysis

Some “Brett” wine liked better than the control

Difference found in terms of wine knowledge

Results not conclusive

Research methodology: Test “fuzzy” concepts

Research Chapter 4:Chemical Analyses

Materials and methods

Set of 32 South African winesWines known to be spoiltWines on the marketQuestionable wines

GC-MS4-ethylphenol, 4-ethylguaiacol, isovaleric acid, isobutyric

acid, acetic acid, 4-vinylphenol and 4-vinylguaiacol

HPLC-MS-MS4-ethylcatechol

Cultivar and mildly spoilt wines

Biplot (axes F1 and F2: 85.20 %)

B6

B4

C6

M3

B3

S6S4

C4

M2

P6P5

P2

B2

4-EC

4-VG

4-EP4-EG

Isovaleric acidIsobutyric acid

Acetic acid

4-VP

-5

0

5

-7 -2 3 8 13

F1 (62.71 %)

F2

(22.

50 %

)

Pinotage?

Same enzymatic pathways

Conclusions: Chemical analyses

First South African study to analyse 4-ethylcatechol

Strong correlations between ethylphenols and isovaleric/isobutyric acid

Sample set too small to draw valid conclusions regarding cultivar

Recommended that larger study be undertaken to investigate this aspect further

Conclusions

Conclusions

Threshold value limiting concept, range more appropriate

Focus should shift to ranges

More research should be done for detection threshold methodology

All four compounds tested interact, especially in terms of the most NB descriptors

All four compounds should therefore be included in future sensorystudies

Conclusions cont.

Consumer analysis not conclusive

Use better testing methodologies

Use of central composite design limiting but necessary for investigating interactions

Further studies with a more “complete” design

Future research

4-ethylcatechol should be tested in future studies concerning Brettanomyces

Help clear up discrepancies

Study indicates direction of future research

Acknowledgements

Adriaan Oelofse & Jan Bester

Thomas Skov – Parafac

Prof van Aarde – Statistics help

Marietjie Stander – Chemical analyses

Distell

Friends & Family

Heavenly Father

Conclusions

Discriminant analyses and Linear LSD’s have similar results

Same underlying function

PCA complement linear statistics by means of providing insight into relationships

Overall – techniques complement one another

More detail about the profile of “Brett character” (Smoky/Savoury)

Materials and Methods: Samples

24444444

424422444424242442242224444224424242224244222422422222225333133335333133

33533313

333533313333

Isovaleric acid4-EC4-EG4-EP