Sensory Evaluation of Aroma Models for Flavor Characterization

1. TM Sensory Evaluation of Aroma Models for Flavor Characterization Keith Cadwallader University of Illinois at Urbana-Champaign Kenneth A. Spencer Award Symposium Kansas City Section of ACS October 27, 2008

2. Overview: • Rationale: why conduct sensory studies? • General approach • Some important considerations • Some common types of model studies • Sensory methods (tools) used in sensory studies • Example of a dose-response study • Example of an addition study • Example of an omission study • Final thoughts

3. Why conduct sensory studies? • Cannot accurately predict the effect (sensory perception) caused by altering the chemical composition of odor mixtures based on only flavor dilution values or odor-activity values (OAVs). • Omission of a compound with a high OAV may not necessarily alter the sensory perception of the overall ‘flavor’ concept.

4. General approach for performing model studies GCO screening of odorants  identification by GC-MS, RIs and odor properties  AEDA, DHDA, GCO-H, post-peak intensity scaling concentrations and OAVs  GC-MS with IS and SIDA methodology  calculation of OAVs from threshold data aroma model construction  selection of appropriate matrix  preliminary testing/adjustments sensory testing of aroma model  dose-response studies (descriptive analysis)  omission studies (n-1) with difference testing and descriptive analysis

5. Some things to consider: • Are all key odorants accounted for? • Are quantitative data accurate? • Is an appropriate matrix available or can it be (re-)created? • What is the objective of study? • Impact (cause-and-effect relationship) of a single odorant • (Re-)creation of an aroma system (model) • Relative impact (or influence) of all aroma components on the aroma system • What is an appropriate experimental approach? • Experimental design options • Sensory methods of analysis

6. Some limitations in methods used to indicate key odorants • Odor-activity values (OAVs) – based on quantitative data (OAV = concentration/odor detection threshold). • Only useful for compounds of known identity • Must have accurate concentration and odor threshold data • Aroma-impact based of GCO data: - (e.g. post-peak) scaling of odorant intensity - flavor dilution factors or CHARM-values (from dilution analysis). • number of odorants detected and the their perceived intensities depend on arbitrarily selected parameters: sample size, isolation method, degree of concentration of aroma extract, etc.

7. Let’s assume we have all relevant or key odorants identified and accurately quantified, and an appropriate matrix is available. What’s next?

8. Need to consider: • Objective and experimental design • Sensory method(s) for evaluation

9. Common types of sensory studies . . .  Dose response studies - Sensory evaluation of a suitable product matrix that has been spiked with an odorant (or group of odorants) to determine if the addition causes an increase in the intensity of a specific flavor attribute.- Suitable technique to evaluate ‘cause and effect’ relationship between odorant and sensory attribute.  Comparison of aroma model to real product (validation) - Use of sensory difference test and/or descriptive analysis  Omission (n – 1) studies • Sensory comparison of the aroma of the complete mixture against the same mixture in which an odorant (or group of odorants) have been omitted. • Suitable for the determination of potential impact of individual (or groups of) odorants on aroma system.

10. Sensory methods used in model studies . . . Conventional Difference Tests • Do not require intensive training of panelists. • Task is easy to understand and perform. • Statistical analysis is straightforward (well established). • Sensitive to small differences provided enough observations (tests) are made. • Not intended to measure direction or degree of difference. • Use difference-from-control test if degree of difference is required.

11. Sensory methods used in model studies Descriptive Analysis • Complement difference tests • provides descriptive terms for attributes and allows quantification of their perceived intensities. • In order to detect small differences between products, the performance level of the panel must be sufficient in terms of reproducibility (precision), discrimination power, and agreement among panelists (improved with training, use of external references and by increased number of panelists). • provides qualitative and quantitative comparisons of the model against the product or the omission mixture.  Terminology (lexicon) should be developed based not only on attributes of product being studied, but also based on attributes of all n-1 combinations (attributes cannot be predicted).

12. Example of a Dose-Response Study (with sensory descriptive analysis)

13. Farmhouse Cheddar Cheese . . .  Results of gas chromatography-olfactometry (GCO) and Aroma Extract Dilution Analysis (AEDA) indicated 2-isopropyl-3-methoxypyrazine (3-7 ppb) and p-cresol (200 ppb) to be “most likely” responsible for cowy/barny and earthy/bell pepper flavors, respectively. • Additional sensory testing was conducted to measure impact of compounds on perceived intensities of corresponding flavor descriptors (blind study).  Compounds spiked into a bland cheese matrix across concentration found in Farmhouse cheeses.  Evaluation by descriptive sensory panel in a blind study. Suriyaphan, O.; Drake, M.A.; Chen, X.Q.; Cadwallader, K.R. Characteristic aroma components of British Farmhouse Cheddar cheese. J. Agric. Food Chem. 2001, 49, 1382-1387.

14. e.g. Flavor Profile of British Farmhouse Cheddar Cheese description -aromatics associated with barns and stock trailersreference -p-cresol, Band-aid, phenol Bitter Whey Brothy 6 Umami Cooked 4 Cowy/Barny Sweet 2 Sulfur Diacetyl 0 Sour Earthy/Bell Pepper (Aroma) Salty Earthy/Bell Pepper (Flavor) Prickle Free Fatty Acid Nutty Fruity Lactone

15. Farmhouse Cheddar Cheese . . . Linking aroma analysis results to flavor lexicon terms Relationship between p-cresol concentration and “cowy/barny flavor” intensity 3.5 2-isopropyl-3-methoxypyrazine threshold = 0.002 ppb (in water) 3.0 2.5 2.0 Average Flavor Intensity 1.5 Relationship between 2-isopropyl-3-methoxypyrazine 1.0 concentration and “earthy aroma/ flavor” intensity 0.5 0 7 0 65 100 165 300 6 earthy/bell pepper flavor earthy/bell pepper aroma p-Cresol (ppb) 5 4 Average Intensity p-Cresolthreshold = 55 ppb (in water) 3 2 1 0 0 3.5 7 2-isopropyl-3-methoxypyrazine (ppb)

16. Example of an Addition Study (with difference/similarity scaling)

17. Beefy/Brothy Cheddar Cheese . . .  The unambiguous linking of sensory descriptors with causative chemical components permits researchers to precisely relate sensory flavour quality with the chemistry and technology of Cheddar cheese production. • The objective of this study was to identify volatile aroma compounds responsible for the beefy/brothy flavor note in Cheddar cheese.  Potential beefy/brothy compounds identified by GCO.  Compounds spiked into a bland cheese matrix across concentration found in beefy/broth cheese.  Evaluation by similarity-to-control and descriptive sensory analysis. Cadwallader, K.R., Drake, M.A., Carunchia-Whetstine, M.E. and Singh, T.J. 2006. Characterisation of Cheddar cheese flavour by sensory directed instrumental analysis and model studies. In Flavour Science: Recent Trends.Bredie, W.P. and Peterson, M.A. (Eds.), Developments in Food Science 43, Elsevier, New York, pp. 157-160.

20. Example of an Omission Study (with R-index method)

21. Omission studies . . . Four critical steps in omission studies • Choice of target material • Construction of synthetic mixture (model) • Sensory validation of mixture (?) • Choice of experimental approach and sensory method(s) for evaluating model

22. Omission studies . . . Example: Evaluation of key odorants of chipotle peppers Cadwallader, K.R.; Lorjaroenphon, Y.; Kim, H.; Lee, S-Y. Evaluation of key odorants in chipotle pepper by quantitative analysis, calculation of odor-activity values and omission studies. In Recent Highlights in Flavor Chemistry & Biology. Proceedings of the 8th Wartburg Symposium. Hofmann, T., Meyerhof, W. and Schieberle, P. (eds), Deutsche Forschungsanstalt für Lebensmittelchemie, Garching, Germany.

23. Omission studies . . . Predominant Odorants in chipotle peppers by GCO* A total of 41 odorants were detected by GCO (post-peak intensity scaling, 7 pt scale) of DSE-SAFE aroma extracts from the three dried chipotle pepper samples  16 compounds had high odor intensities  4.0 2- and 3-methylbutanal, 2-ethyl-3,5-dimethylpyrazine, 2-isobutyl-3-methoxypyrazine, 2-(3)-methylbutanoic acid, -damascenone, guaiacol, o-cresol, 4-hydroxy-2,5-dimethyl-3(2H)-furanone, octanoic acid, p-cresol, sotolon, syringol, coumarin, phenyacetic acid and vanillin  7 additional odorants had odor intensities  3 * Cadwallader, K.R.; Gnadt, T.A.; Jasso, L. Aroma components of chipotle peppers. In Hispanic Foods: Chemistry and Flavor (Tunick, M.H., González de Mejia, E., eds.); American Chemical Society: Washington, D.C., 2006, 57-66

24. Concentrations and Odor-Activity Values (>100) OAV conc. (ng/g) no. odorant Threshold (ng/mL) 27 sotolon 376 0.001 376000 10 2-ethyl-3,5-dimethylpyrazine 626 0.04 15640 3 3-methylbutanal 3069 0.2 15350 7 1-octen-3-one 75 0.005 15000 17 -damascenone 22 0.002 11000 11 2-isobutyl-3-methoxypyrazine 38 0.005 7600 8 dimethyltrisulfide 33 0.01 3300 5 ethyl 2-methylbutanoate 9 0.006 1500 13 2-methylpropanoic acid 52620 50 1052 18 guaiacol 2541 3 847 12 linalool 1688 6 281 4 2,3-butanedione 979 4 245 2 2-methylbutanal 465 3.7 126 16 2- and 3-methylbutanoic acid 5736 50 115 9 acetic acid 2253000 22000 102

25. Concentrations and Odor-Activity Values (<100) conc. (ng/g) Threshold (ng/mL) no. odorant OAV 30 skatole 291 3 97 1 methylpropanal 83 1 83 22 4-ethylguaiacol 2181 50 44 25 p-cresol 2167 55 39 32 vanillin 907 25 36 6 hexanal 167 4.5 37 23 4-hydroxyl-2,5-dimethyl-3(2H)-furanone 790 31 25 20 4-methylguaiacol 1914 90 21 15 phenylacetaldehyde 75 4 19 14 butanoic acid 3604 240 15 19 2-phenylethanol 14330 1000 14 29 coumarin 258 25 10 26 m-cresol 5300 680 8 28 syringol 10340 1850 6 21 o-cresol 2845 650 4 31 phenylacetic acid 14000 10000 >1 24 octanoic acid 1497 3000 <1

26. Composition of Matrix Applied in the Sensory Experiments composition amount 0.1 M citrate buffer (pH 4.8) 10 mL base 1.7 g soybean oil 0.3 ga base composition Ratio cellulose (Sigma, St. Louis, MO, USA) 2.6a sucrose (Sigma) 2.1a natural capsaicin (Aldrich, St. Louis, MO, USA) 722.4 μg/g (dry basis)b a Based on dietary fiber (2.6), sugars (2.1) and total fat (0.9) in 100 g of jalapeno pepper (wet basis) (NutritionData, 2006). b Based on analysis of capsaicin and dihydrocapsaicin in chipotle pepper using method of Thomas et al. (1998).

27. Chipotle aroma . . . Omission studies – some additional considerations  Eliminating successively (n - 1) all possible components of the mixture- may not reveal much because of antagonistic effects  Eliminating groups of compounds of the model- e.g. where each group is composed of odorants with similar odor qualities or same chemical class

28. Odorant groups* for omission studies earthy(2-ethyl-3,5-dimethylpyrazine and 2-isobutyl-3-methoxypyrazine) smoky (guaiacol, 4-methylguaiacol, o-cresol, 4-ethylguaiacol, p-cresol, m-cresol, syringol, coumarin) sweet aromatics(2,3-butanedione, HDMF, sotolon and vanillin) floral/fruity(ethyl 2-methylbutanoate, linalool, phenylacetaldehyde, -damascenone, 2-phenylethanol, phenylacetic acid) malty (methylpropanal, 2- and 3-methylbutanal) sour/sweaty(acetic, 2-methylproanoic, butanoic, 2/3-methylbutanoic and octanoic acids) sulfurous(dimethyltrisulfide) green/plant-like(hexanal, 1-octen-3-one) * Terms decided upon by descriptive sensory panel

29. Omission studies . . . Omission studies – methodology • Subjects were provided with mixtures (signals) marked with 3-digit codes and the complete model (noise) coded as R. A randomized complete block design was used to randomize the samples across subjects. • Subjects were instructed to gently squeeze each sample container, evaluate the odor and rank the samples on how different they were from R, with 1 = least different to 9 = most different. Subjects were allowed to reevaluate samples ad libitum. Subjects were instructed to wait at least 10 seconds between evaluations to minimize adaptation effects. • A response matrix was constructed for the entire panel to calculate the R-indices. O’Mahony, M. Understanding discrimination tests: A user friendly treatment of response bias, rating and ranking R-index tests and their relationship to signal detection. J. Sensory Stud. 1992, 7, 1-47.

30. Omission studies . . .

31. R-index Values for Omission Test odorant group omitteda R-indexb 79.3 earthy (10, 11) * 69.0 * smoky (18, 20, 21, 22, 25, 26, 28, 29) sweet aromatics (4, 23, 27, 32) 62.1 floral/fruity (5, 12, 15, 17, 19, 31) 62.1 malty (1, 2, 3) 55.2 sour/sweaty (9, 13, 14, 16, 24) 48.3 sulfurous (8) 44.8 green/plant-like (6, 7) 41.4 a Numbers in parentheses indicate odorant numbers omitted. Description of each group was determined by consensus opinion of the trained sensory descriptive panel. b R-index of each model is calculated by using John Brown computations (O’Mahony, 1992) against control (complete model) (n=29; female=21 and male=8). *Significantly different from control at α=0.05 (critical value, expressed in percentage; R-Index = 50% for two-tailed test, α=0.05, n=29 is 17.37).

32. Some Final Thoughts • Synergistic and Antagonistic Effects Synergistic effects are mainly observed for subthreshold concentrations,i.e. a decrease in detection threshold occurs1. But models are build from odorants at suprathreshold concentrations - in this region antagonistic effects seem to be most common2. In general, human subjects are unable to identify individual odorants whenthe mixture contains greater than four odorants in total3. This helps explain why omission of one or more odorants from a complex odor mixture oftenis not distinguished from the intact (complete) mixture. • Laska, M.; Hudson, R. A comparison of the detection thresholds of odour mixtures. Chem.Senses 1991, 16, 651-662. • Grosch, W. Evaluation of the key odorants of foods by dilution experiments, aroma • models and omission. Chem. Senses 2001, 26, 533-545. • 3. Liang, D.G. Perceptual odour interactions and objective mixture analyses. Food Qual. Pref.1994, 5, 75-80.

33. Additional References: Brown, J. Recognition assessed by rating and ranking. Brit. J. Phychol. 1974, 65, 13-22 Czerny, M.; Mayer, F.; Grosch, W. Sensory study on the character impact odorantsof roasted arabica coffee. J. Agric. Food Chem. 1999, 47, 695-699. Drake, M.A.; Miracle, R.E.; Caudle, A.D. ; Cadwallader, K.R. Relating sensory and instrumental analyses. In Sensory-Directed Flavor Analysis. Marsili, R. (Ed.), CRC Press/Taylor & Francis Group, LLC, Boca Raton, FL, 2007, pp. 23-54. Engel, E.; Nicklaus, S.; Salles, C.; Le Quere, J.-L. Relevance of omission tests todetermine flavour-active compounds in food: application to cheese taste. Food Qual.Pref. 2002, 13, 505-513. Karagul-Yuceer, Y.; Vlahovich, K.N.; Drake, M.A.; Cadwallader, K.R. Characteristicaroma components of rennet casein. J. Agric. Food Chem. 2003, 51, 6797-6801.