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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.
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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
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
Linear vs. Non-Linear Blending Saturated detection Detection response 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 = 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 11 11 11 12 12 12 15 14 13 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 12 15
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.
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 = wine A 672 = wine A 359 = wine B 184 359 672
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 184 352 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 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 MappingJ. 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? 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?
Internal Preference Map: Clusters Oakier the better Cluster 3 Fruitier the better! B G Optimizers Cluster 2 Cluster 5 D C I J 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 Post-Fermentation processing of wines.