Presentation on theme: "Sensory Evaluation of Aroma Models for Flavor Characterization Keith Cadwallader University of Illinois at Urbana-Champaign TM Kenneth A. Spencer Award."— Presentation transcript:
Sensory Evaluation of Aroma Models for Flavor Characterization Keith Cadwallader University of Illinois at Urbana-Champaign TM Kenneth A. Spencer Award Symposium Kansas City Section of ACS October 27, 2008
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 omission study Final thoughts Example of an addition study
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.
GCO screening of odorants General approach for performing model studies AEDA, DHDA, GCO-H, post-peak intensity scaling identification by GC-MS, RIs and odor properties concentrations and OAVs calculation of OAVs from threshold data GC-MS with IS and SIDA methodology aroma model construction preliminary testing/adjustments selection of appropriate matrix sensory testing of aroma model omission studies (n-1) with difference testing and descriptive analysis dose-response studies (descriptive analysis)
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
Some limitations in methods used to indicate key odorants Odor-activity values (OAVs) – based on quantitative data (OAV = concentration/odor detection threshold). Aroma-impact based of GCO data: - (e.g. post-peak) scaling of odorant intensity - flavor dilution factors or CHARM-values (from dilution analysis). Only useful for compounds of known identity Must have accurate concentration and odor threshold data 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.
Let’s assume we have all relevant or key odorants identified and accurately quantified, and an appropriate matrix is available. What’s next?
Need to consider: Objective and experimental design Sensory method(s) for evaluation
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. 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. Common types of sensory studies... Comparison of aroma model to real product (validation) - Use of sensory difference test and/or descriptive analysis
Sensory methods used in model studies... Conventional Difference Tests Do not require intensive training of panelists. Statistical analysis is straightforward (well established). Task is easy to understand and perform. 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.
Sensory methods used in model studies provides qualitative and quantitative comparisons of the model against the product or the omission mixture. 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). Descriptive Analysis Complement difference tests 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).
Example of a Dose-Response Study (with sensory descriptive analysis)
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.
Linking aroma analysis results to flavor lexicon terms Relationship between p-cresol concentration and “cowy/barny flavor” intensity 0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 065100165300 p-Cresol (ppb) Average Flavor Intensity 2-isopropyl-3-methoxypyrazine (ppb) Average Intensity 0 1 2 3 4 5 6 7 03.57 earthy/bell pepper flavor earthy/bell pepper aroma Relationship between 2-isopropyl-3-methoxypyrazine concentration and “earthy aroma/ flavor” intensity p-Cresol threshold = 55 ppb (in water) 2-isopropyl-3-methoxypyrazine threshold = 0.002 ppb (in water) Farmhouse Cheddar Cheese...
Example of an Addition Study (with difference/similarity scaling)
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. 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. Potential beefy/brothy compounds identified by GCO.
Differentiating odorants detected in beefy/brothy Cheddar cheeses Compound Odor Description FD Factor RI a AEDA b DHDA c FFAPDB-5NdNd B1 d B2 d NB1B2 2-Methyl-3-furanthiol (MFT) 1312873Vitamin, meaty nd39 3-(Methythio) Propanal 1455907Potato92187 525 2-Methyl-(3- methyldithio) furan 16821170Vitamin, meaty ndn.d. 525 Maltol19981175Burnt sugarnd99 Furaneol TM (HDMF) 20351058Burnt sugar97292187525 Homofuraneol20901160Burnt sugar393nd11 Bis-(2-methyl-3-furyl) disulfide 21321542Vitamin, meaty Ndnd 115 a Retention index. b Flavor dilution factor determined by aroma extract dilution analysis. c Flavor dilution factor determined by dynamic headspace dilution analysis. d N indicates control (not brothy) cheese, B1 and B2 refer to beefy/brothy cheeses.
Sensory Analysis of Beefy/Brothy Model Cheeses Combination Aroma Description (Intensity) a Overall Similarity Score b No spikeNot beefy/brothy c 0 MFT (2 ng/g) + Furaneol (10 g/g) Beefy/brothy (2)8 MFT (4 ng/g) + Furaneol (20 ug/g)Beefy/brothy (3) Burnt sugar/fruity (3) 7 MFT (2 ng/g) + Furaneol (10 g/g) + Methional (80 g/g) Beefy/brothy (2)9 MFT (4 ng/g) + Furaneol (20 g/g) + Methional (80 g/g) Beefy/brothy (3)7 a Average aroma intensity on a 15-point universal scale (nine trained panelists). b Similarity to typical beefy/brothy Cheddar cheese (10-point scale). c Cheese received the following aroma/ flavour scores: diacetyl=2, whey=4, cooked=3.5, milkfat=3.5, salty=4, sour=3, sweet=1.5.
Example of an Omission Study (with R-index method)
Four critical steps in omission studies Choice of target material Sensory validation of mixture (?) Construction of synthetic mixture (model) Choice of experimental approach and sensory method(s) for evaluating model 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.
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 7 additional odorants had odor intensities 3 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 * 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 Omission studies...
Composition of Matrix Applied in the Sensory Experiments 722.4 μg/g (dry basis) b natural capsaicin (Aldrich, St. Louis, MO, USA) 2.1 a sucrose (Sigma) 2.6 a cellulose (Sigma, St. Louis, MO, USA) Ratiobase composition g a 0.3soybean oil g1.7base mL100.1 M citrate buffer (pH 4.8) amountcomposition 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).
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 Chipotle aroma...
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) Odorant groups* for omission studies * Terms decided upon by descriptive sensory panel
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.
R-index Values for Omission Test 41.4green/plant-like (6, 7) 44.8sulfurous (8) 48.3sour/sweaty (9, 13, 14, 16, 24) 55.2malty (1, 2, 3) 62.1floral/fruity (5, 12, 15, 17, 19, 31) 62.1sweet aromatics (4, 23, 27, 32) *69.0 smoky (18, 20, 21, 22, 25, 26, 28, 29) * 79.3 earthy (10, 11) R-index b odorant group omitted a 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).
Synergistic and Antagonistic Effects Some Final Thoughts Synergistic effects are mainly observed for subthreshold concentrations, i.e. a decrease in detection threshold occurs 1. But models are build from odorants at suprathreshold concentrations - in this region antagonistic effects seem to be most common 2. In general, human subjects are unable to identify individual odorants when the mixture contains greater than four odorants in total 3. This helps explain why omission of one or more odorants from a complex odor mixture often is not distinguished from the intact (complete) mixture. 1Laska, M.; Hudson, R. A comparison of the detection thresholds of odour mixtures. Chem. Senses 1991, 16, 651-662. 2Grosch, 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.
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 odorants of 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 to determine 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. Characteristic aroma components of rennet casein. J. Agric. Food Chem. 2003, 51, 6797-6801.