Lecture 18:
Blending and Sensory Evaluation
of Table Wines
Reading Assignment:
Text, Chapter 10 pages 415-426
Blending Objectives
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Complexity within vintage
Correct a deficiency or excess
Freshen old wine
Age young wine
Fortification
Amelioration
As part of style
Varietal Wine Labeling in California
• Vintage: 95% must be from that vintage
• Varietal: 75% must be from that varietal
• Viticultural appellation: 85% must be
from that growing region
• “Produced and Bottled By”: must control
75% of the fruit
• “Estate Bottled”: 100% must be from
that appellation controlled by the winery
“Controlled by the Winery”
Do or direct all vineyard work- do not
have to own all vineyards
Factors to Consider When Choosing
a Blend
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Acidity
Residual sugar
Alcohol
Appellation
Flavor
Style
What are the most critical components?
The Blending Process
• Bench Tasting to “guesstimate” best
blends
• Make trial blends in small scale
• Period of “marrying”: 3 weeks to 6
months depending upon style
• Re-evaluation of blends
• Determination of final blend
Why Do Blends Need to “Marry”?
To determine if an unexpected problem
develops over time
Types of Unpredictable Changes with
Blending
• Instability
– Protein/polysaccharide haze
– Microbial: bringing microbes and nutrients
together
– Tartrate: bringing tartrate and ions together
• Flavor changes
– Unmasking
– Masking
– Creation of novel characters
Unmasking
A character present in one of the wines becomes
more noticeable in the blend
Dilution of a competing factor that prevents/limits
detection
Character due to a combination of chemicals and
the concentration of those components
increases in the blend
Masking
One flavor is masked by another: seems
to disappear in the blend
Due to dilution
Due to competition for detection
Novel Characters
Chemical reactants brought together
resulting in new aromatic product
Chemicals brought together that are
perceived as something other than the
original aromas
Linearity of Blending Traits
Some aromas are not linear with dilution
– Below or above threshold of detection
– Trait due to mixture of components
– Matrix (acidity) effects
Detection response
Linear vs. Non-Linear Blending
Saturated detection
Linear Range
Threshold of detection
Concentration
Computation of Blend Ratios
• “Pearson’s Square”
• By algebraic equation
• Graphical method for multiple
components
• Software program
Computation of Blending Ratios:
Pearson’s Square
b-m
a
m
b
m-a
a,b represent concentration in wine
m represents desired concentration
Pearson’s Square: Example
Wine “A” is 11% ethanol, Wine “B” is 15 %.
The desired final ethanol concentration is 12%.
15-12 = 3
11%
12%
15%
12-11 = 1
A blend of 3 parts of A (11%) to 1 part of B (15%) will
yield the desired ethanol concentration.
Algebraic Equation
VA + VB = 1
VA = 1 - VB
11VA + 15VB
=
11( 1- VB ) + 15VB =
12(VA + VB )
12((1 – VB) + VB)
11 – 11VB + 15VB = 12 – 12VB + 12VB
4VB = 1
VB = 1/4 = 1 part of VB to 3 parts of VA
Can solve multiple simultaneous equations if needed
Always Check Calculations
3 parts of 11 = 33
1 part of 15 = 15
__________________
4 parts total
= 48
48/4 = 12
Dealing with Multiple Wines
A = 11%; B=15%; C=14%; D=13% and want 12%
ethanol for final blend
11
11
12
15
11
12
14
3(11):1(15)
12
13
2(11):1(14)
Totals: 1(15):1(14):1(13):6(11)
1(11):1(13)
Common Problems with Pearson’s
Square
• Forgetting to have lowest concentration
in upper left
• Both wines exceed or are below the
desired concentration
13
12
15
• Ignoring negative numbers
Dealing with Multiple Components
Frequently, blend decisions are made
considering multiple wines and multiple
components (sugar, ethanol, acidity, etc.). In
this case, graphical methods can be used to
estimate the best overall blend. However,
the ideal value of each component might not
be attainable.
The Sensory Evaluation of
Table Wines
It is important to use
scientifically sound procedures
for the evaluation of wines.
Wine Attributes for Analysis
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Appearance
Odor
Taste
Aroma
Flavor
Sensory Evaluation of Wines
• Descriptive analysis
Descriptive Analysis
• Goal: to describe the aroma and flavor
profile of a wine
• Using panel discussion decide upon
flavor/aroma characters of wine
• Train tasters using standards (wine
spiked with characters of wine)
• Blind tasting to determine if characters
can be reproducibly recognized in wines
Sensory Evaluation of Wines
• Descriptive analysis
• Difference tests
Difference Tests
• Use trained judges
• Determine if two wines are reproducibly
selected as different
• Requires statistical analysis
Difference Tests for Wine Evaluation
• Triangle
• Duo-Trio
The Triangle Test
Tasters are presented with three wines and
asked to determine which wine is different
from the other two.
184 = wine A
184
672 = wine A
359 = wine B
359
672
The Triangle Test
A statistical analysis can then be
used to determine if the number of
times wine 359 was selected as
different is significant or not.
Difference Tests for Wine Evaluation
• Triangle
• Duo-Trio
The Duo-Trio Test
Tasters are provided with a reference and two
sample wines. They are asked to determine which
sample wine is DIFFERENT from the reference.
R
184
R = 352 = Wine B
186 = Wine A
352
The Duo-Trio Test
A statistical analysis can then be used
to determine if the number of times
wine 184 was selected as different is
significant or not.
Sensory Evaluation of Wines
• Descriptive analysis
• Difference tests
• Intensity rating
Intensity Rating Scales
Important to train judges to know what a
term is and what value they will assign
to specific intensities in wines
Can then convert rating into a numerical
score for statistical evaluation
Intensity Scale
Least
Most
Astringent
Astringent
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2
3
4
5
6
7
8
9
10
Taster then rates the wine for the desired trait
1
2
3
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5
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10
Sensory Evaluation of Wines
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Descriptive analysis
Difference tests
Intensity rating
Hedonic tests
Hedonic Evaluation
Uses untrained consumers
Evaluates whether a taster likes a
particular wine or not
Can use an overall evaluation scale
Overall Evaluation Scale
Assign wine to one of the following categories:
1. Like intensely
2. Like moderately
3. Like slightly
4. Neither like nor dislike
5. Dislike slightly
6. Dislike moderately
7. Dislike intensely
Profiling Consumer Definitions of
Quality:
Preference Mapping
J. Yegge & A. C. Noble
Profiling Consumer Preferences
• Over 100 consumers
• 10 different Chardonnay wines
• External (packaging) and Internal (wine)
factors evaluated
• Cluster analysis to look for groupings of
individuals
Consumer Definitions of Quality
1. Do wines differ?
3. Which are liked?
Difference Tests
Preference Tests with
Target Consumers
2. How do they
differ?
Descriptive Analysis
Time Intensity Methods
PREF-MAP
Flavors of preferred
wines?
butter
floral
8
oak
6
Wine D
peach/apricot
4
Wine C
2
citrus
0
caramel
Wine B
spice
Wine G
apple taste
vanilla
sweet
caramel taste
sour
astingency
Yegge & Noble 2001
Internal
Preference Map:
Clusters
Oakier the better
Cluster 3
Fruitier
the better!
B
G
Optimizers
Cluster 2
Cluster 5
I
J
D
C
H
Cluster 4
Cluster 1
E
A1
A2
F
Yegge & Noble 2001
The Big Question:
Can Preference be divorced from
Quality?
Selection of Type of Sensory
Analysis
• What are you trying to determine?
• Judge/taster fatigue
This concludes the
section on PostFermentation
processing of wines.