lecture 18: blending and sensory evaluation of table wines

Lecture 18:

Blending and Sensory Evaluation of Table Wines

Reading Assignment:

Text, Chapter 10 pages 415-426

Blending Objectives

• 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

• 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

MaskingOne 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

Linear vs. Non-Linear Blending

Threshold of detection

Saturated detection

Linear Range

Concentration

Det

ectio

n re

spon

se

Computation of Blend Ratios

• “Pearson’s Square”

• By algebraic equation

• Graphical method for multiple components

• Software program

Computation of Blending Ratios: Pearson’s Square

a

b

m

b-m

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%.

11%

15%

12%

15-12 = 3

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 = 12(VA + VB )

11( 1- VB ) + 15VB = 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

12 12 12

11

15

11 11

1314

3(11):1(15) 2(11):1(14) 1(11):1(13)

Totals: 1(15):1(14):1(13):6(11)

Common Problems with Pearson’s Square

• Forgetting to have lowest concentration in upper left

• Both wines exceed or are below the desired concentration

• Ignoring negative numbers

13

15

12

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

• 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

359 672

184 = wine A

672 = wine A

359 = wine B

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 184 352

R = 352 = Wine B

186 = Wine A

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

1 2 3 4 5 6 7 8 9 10

Taster then rates the wine for the desired trait

1 2 3 4 5 6 7 8 9 10

Sensory Evaluation of Wines

• 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 ScaleAssign 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

1. Do wines differ?

Difference Tests

2. How do they differ?

Descriptive Analysis

Time Intensity Methods

3. Which are liked? Preference Tests with Target Consumers

PREF-MAP

Flavors of preferred wines?

Consumer Definitions of Quality

0

2

4

6

8butter

oak

caramel

spice

vanilla

caramel taste

astingencysour

sweet

apple taste

citrus

peach/apricot

floral

Wine B

Wine G

Wine D

Wine C

Yegge & Noble 2001

Cluster 1

Cluster 2

Cluster 3

Cluster 4

Cluster 5

A1 A2

B

D

G

I CJ

F

H

E

Internal Internal Preference Map: Preference Map: ClustersClusters Fruitier

the better!

Oakier the better

Yegge & Noble 2001

Optimizers

The Big Question:

Can Preference be divorced from Can Preference be divorced from Quality?Quality?

Selection of Type of Sensory Analysis

• What are you trying to determine?

• Judge/taster fatigue

This concludes the section on Post-Fermentation processing of wines.