1. Lecture 18: Blending and Sensory Evaluation of Table Wines

2. Reading Assignment: Text, Chapter 10 pages 415-426

3. Blending Objectives Complexity within vintage Correct a deficiency or excess Freshen old wine Age young wine Fortification Amelioration As part of style

4. 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

5. “Controlled by the Winery” Do or direct all vineyard work- do not have to own all vineyards

6. Factors to Consider When Choosing a Blend Acidity Residual sugar Alcohol Appellation Flavor Style What are the most critical components?

7. 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

8. Why Do Blends Need to “Marry”? To determine if an unexpected problem develops over time

9. 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

10. 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

11. Masking One flavor is masked by another: seems to disappear in the blend Due to dilution Due to competition for detection

12. Novel Characters Chemical reactants brought together resulting in new aromatic product Chemicals brought together that are perceived as something other than the original aromas

13. 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

14. Linear vs. Non-Linear Blending Threshold of detection Saturated detection Linear Range Concentration Detection response

15. Computation of Blend Ratios “Pearson’s Square” By algebraic equation Graphical method for multiple components Software program

16. Computation of Blending Ratios: Pearson’s Square a b m b-m m-a a,b represent concentration in wine m represents desired concentration

17. 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.

18. Algebraic Equation V A + V B = 1 V A = 1 - V B 11V A + 15V B = 12(V A + V B ) 11( 1- V B ) + 15V B = 12((1 – V B ) + V B ) 11 – 11V B + 15V B = 12 – 12V B + 12V B 4V B = 1 V B = 1/4 = 1 part of V B to 3 parts of V A Can solve multiple simultaneous equations if needed

19. Always Check Calculations 3 parts of 11 = 33 1 part of 15 = 15 __________________ 4 parts total = 48 48/4 = 12

20. Dealing with Multiple Wines A = 11%; B=15%; C=14%; D=13% and want 12% ethanol for final blend 12 11 15 11 1314 3(11):1(15)2(11):1(14)1(11):1(13) Totals: 1(15):1(14):1(13):6(11)

21. 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

22. 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.

23. The Sensory Evaluation of Table Wines

24. It is important to use scientifically sound procedures for the evaluation of wines.

25. Wine Attributes for Analysis Appearance Odor Taste Aroma Flavor

26. Sensory Evaluation of Wines Descriptive analysis

27. 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

28. Sensory Evaluation of Wines Descriptive analysis Difference tests

29. Difference Tests Use trained judges Determine if two wines are reproducibly selected as different Requires statistical analysis

30. Difference Tests for Wine Evaluation Triangle Duo-Trio

31. The Triangle Test Tasters are presented with three wines and asked to determine which wine is different from the other two. 184 359672 184 = wine A 672 = wine A 359 = wine B

32. 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.

33. Difference Tests for Wine Evaluation Triangle Duo-Trio

34. 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. R184352 R = 352 = Wine B 186 = Wine A

35. 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.

36. Sensory Evaluation of Wines Descriptive analysis Difference tests Intensity rating

37. 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

38. Intensity Scale Least Most 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

39. Sensory Evaluation of Wines Descriptive analysis Difference tests Intensity rating Hedonic tests

40. Hedonic Evaluation Uses untrained consumers Evaluates whether a taster likes a particular wine or not Can use an overall evaluation scale

41. 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

42. Profiling Consumer Definitions of Quality: Preference Mapping J. Yegge & A. C. Noble

43. 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

44. 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

45. Yegge & Noble 2001

46. Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 A1A2 B D G I C J F H E Internal Preference Map: Clusters Fruitier the better! Oakier the better Yegge & Noble 2001 Optimizers

47. The Big Question: Can Preference be divorced from Quality?

48. Selection of Type of Sensory Analysis What are you trying to determine? Judge/taster fatigue

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