Effect of Base and Processing on Flavor Release from Snacks

Chapter 34

Effect of Base and Processing on Flavor Release from Snacks Bonnie M. K i n g and C. A. A. Duineveld

Downloaded by TUFTS UNIV on June 19, 2017 | http://pubs.acs.org Publication Date: September 7, 2000 | doi: 10.1021/bk-2000-0763.ch034

Quest International Nederland BV, P.O. Box 2, 1400 C A Bussum, the Netherlands

Tortilla chips, potato chips and corn-based snacks created by either direct or indirect expansion were evaluated by profiling and timeintensity (TI) evaluations made by a trained panel. In the TI tests both saltiness and a retronasal flavor (paprika, spicy/herbs) were measured for single as well as multiple ingestions. It was shown that processes such as direct expansion can weaken the distinctive base flavor of corn snacks, and that low bulk density snacks require a higher flavor dosage. For both single and multiple ingestions, the retronasal flavor was distinguished from saltiness by lower intensity-related TI parameters. Panelists took longer to swallow when making TI evaluations of retronasal flavor than when evaluating saltiness. The flavor on potato-based as opposed to corn-based snacks lasted longer and was more intense for both descriptors independent of the number of ingestions.

Flavor is applied to snacks either as an oil-based slurry sprayed onto the surface of the product or as a powder that can be dusted onto a product that already has a fatty surface. Potato chips, corn tortillas and numerous types of pasta (corn, potato, wheat or rice based pellets) that obtain their final volume after being fried in vegetable oil are examples of products flavored by dusting. The latter are often referred to as snacks having undergone indirect expansion as opposed to the direct expansion that occurs in the extruder. Directly expanded snacks are usually flavored by slurry. Given that both slurry application and dusting are surface treatments, there might not be chemical evidence for flavor-base interactions in the classical sense. On the other hand, perceptual differences during eating can be attributed to the combined sensation of added flavor and base. Corn bases distort the balance of many savory flavorings. The purpose of the present investigation was to determine which sensory characteristics were most influenced by specific changes in snack base or processing. Flavor formulation and blending are key to producing optimal eating enjoyment,

© 2000 American Chemical Society

Roberts and Taylor; Flavor Release ACS Symposium Series; American Chemical Society: Washington, DC, 2000.

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which is determined to a large extent by flavor release in the mouth. Flavor must not appear immediately and then disappear, leaving a tasteless, chewy mass to be swallowed.

Materials and Methods


Samples A l l samples used in these experiments were prepared by the Quest Snack Department. Samples can be classified according to the scheme given in Figure 1. Samples used in Experiment 1 ( D l , D2, D3, II, 12, 13) were all flavored with the same cheese/ham/bacon flavor. For Experiment 2 there were 18 samples prepared according to a full-factorial design: 3 bases (R, F, T), two cheese/onion flavors and 3 flavor dosages (5%, 6%, 7%). Only samples of type R were used in Experiment 3. The paprika flavor used in this experiment was dosed at 4% and 8%. For Experiments 4 and 5 the samples (flavor dosages) were C (8%), R (6%) and Τ (6%). The paprika flavor used in these experiments was different from the flavor used in Experiment 3. Samples were presented in plastic cups coded with 3-digit numbers. Larger samples (R, F, T) were broken into pieces in order to provide a more homogeneous distribution of flavor. Panelists consumed ad libitum for profiling tests. TI tests, on the other hand, were conducted with weighed portions taken in their entirety as a single ingestion: 2.5 g for Experiment 3 and 1.0 g (respectively 4 times 1.0 g) for Experiments 4 and 5.

Sensory Measurements The Quest Sensory Research paid professional panel (20 women) was used in all experiments. Profiling was done by the audio method previously described (7). Thirteen descriptors were used in Experiment 1 and 18 descriptors in Experiment 2. Profiling tests were replicated twice with an interval of at least 24 h between replications. No more than 4 products were evaluated in the same session. Statistical designs were used to balance serving order, carry-over and session effects. TI measurements were made by using a special transducer system: a squeezable handgrip that transmits hand force via a strain gauge to an amplifier. The device, the method for using it, and panel training in this technique have been described previously (2). For Experiments 3-5 panelists were instructed to empty the contents of the cup into their mouths, click the squeezer on and begin evaluating the descriptor indicated while chewing the sample according to their normal eating habits. Panelists indicated swallowing by pressing the space bar. For the repeated ingestions in



415

1.

Classification of samples used in Experiments 1-5.


416

Experiment 5, panelists were prompted on the screen every 30 s. Recording was stopped after 101 s for single ingestion experiments and after 161 s for the repeated ingestion test. Different descriptors for the same product were evaluated in different sessions, usually separated by 2 days. TI tests were replicated three times with an interval of at least 48 h between replications. Statistical designs were used to balance serving order, carry-over and session effects.


Data Processing Genstat 5 (1998 PC/Windows 95, release 4.1 Fourth Edition: Lawes Agricultural Trust, I A C R Rothamsted, U K ) was used to perform all calculations and statistical analyses. Profiling tests Profiling descriptors were fitted by variance components models using Restricted Maximum Likelihood (REML). The R E M L model for a given descriptor comprised the sum of terms for the following effects: Score = product + panelist + panelist.product + session(panelist) + error, where panelist.product is the interaction between panelist and product, and session(panelist) is sessions nested in panelists. Random effects were: panelist ~ N(0,«* ), panelist.product ~ N ( 0 , ^ ) and session(panelist) - N ( 0 , « l ) 2

2

panelist

p a n e l i s t p r o d u c t

2

session(panelist)

TI tests Raw data from TI tests were filtered in order to remove digitation noise while keeping all other features intact. A nine point Epanechnikov kernel smoother was used as filter (3). Seven parameters were abstracted from single-ingestion TI filtered curves: area under the curve, Imax (highest intensity over complete curve), Tmax (average time where intensity is 95% of maximum), durmax (duration of intensity >90% of maximum), Tdur (earliest time after maximum at which intensity equals only 5% of Imax), Iswal (intensity at swallowing), Tswal (time at swallowing). Figure 2 shows additional parameters extracted from the multiple-ingestion curves to give a total of 26 parameters used for Experiment 5. In order to stabilize the variance, logarithmic transformations of the parameters were used in all calculations. The R E M L model for a given TI parameter comprised the sum of terms for the following effects: TI parameter = product + panelist + panelist.product + session(panelist) + error, with random effects panelist ~ N(0,«* ), panelist.product ~ N ( 0 , « l ) and session(panelist) ~ N ( 0 , ^ ). 2

panelist

2

2

panelistproduct

session(panelist)

When comparing descriptors, the R E M L model comprised the sum of terms for the following effects: TI parameter = product + descriptor + product.descriptor + panelist + panelistproduct + session(panelist) + panelist.descriptor + error, with random effects panelist ~ N(0,«* ), panelist.product ~ N ( 0 , « l ), session(panelist) ~ N ( 0 , ^ ) and panelist.descriptor ~ N(0,«* 2

2

panelist

2

panelistproduct

2

session(panelist)

panelist.descriptor) ·

Non-significant effects were removed from the analysis.




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Intensity

418 Data from Experiments 4 and 5 were combined so that both descriptors and ingestion methods (variable indicated by "type") could be compared. The R E M L model comprised the sum of terms for the following effects: TI parameter = product + descriptor + type + product.descriptor + product.type + type.descriptor + panelist + panelist.product + session(panelist) + panelist.descriptor + panelist.type + error, with random effects panelist ~ N(0,«* ), panelist.product ~ N ( 0 , « l ), session(panelist) ~ N ( 0 , ^ ) , panelist.descriptor ~ N(0,«* 2

2

panelist

panelistproduct

2

session(panelist)

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panelist.type ~ N ( 0 , « l model.

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).

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Non significant terms were eliminated from the

77 curve averaging The following procedure was used to produce TI curves averaged over sessions and panelists in the figures. The raw data (TI curve) were integrated to create monotonie increasing curves. The integrated curves were divided into (unequal) time segments using increments equal to 2% of the maximum found for this curve. (This procedure is similar to one proposed by Overbosch (4); however, problems related to double peaks and plateaus are avoided by using the integrated curves.) A n average value of log (time) per segment was determined according to the following R E M L model: Time = product + panelist + panelist.product + session(panelist) + error, with random effects panelist ~ N(0,«* ), panelist.product ~ N ( 0 , ^ ) and session(panelist) ~ N ( 0 , ^ ). The series of points thus obtained form an average integrated TI curve. The normal representation of a TI curve is the first derivative of this curve. In order to carry out numeric differentiation, the integrated TI curve was first fitted by M splines. (The spline and fitting method were chosen to ensure a monotonie increasing curve.) The area under each differentiated TI curve (which equals 1) was multiplied by the antilog of the average log (area) determined by the R E M L analysis. 2

2

panelist

p a n e l i s t p r o d u c t

2

session(panelist)

Results and Discussion

Experiment 1 The P C A biplot in Figure 3 shows the effect of processing on the different corn bases in terms of flavor perception. Samples II, 12,13 are made from pasta-type corn pellets that expand when fried in hot vegetable oil. They retain the corn flavor associated with their base, and they pick up a fatty, oily taste during processing. Direct expansion in the extruder acts as a steam distillation that weakens the taste of the corn base. The directly-expanded samples ( D l , D2, D3) therefore have more of the cheesy flavor and less of the corn flavor than the indirectly-expanded corn pellets (samples II, 12,13). Low bulk density snacks require a much higher flavor dosage in order to be perceived in the same way as their higher bulk density counterparts. The



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420 isolation of sample D3 in this figure can be explained by the fact that, as a low bulk density product, it scored very low on all of the flavor attributes.


Experiment 2 When a biplot for P C A results from Experiment 2 was produced based on all the descriptors used to evaluate the samples, the first dimension accounted for 95% of the variation in the data; the second dimension accounted for 3%. This one-dimensional separation of the samples was explained by base flavor. Eliminating the base-related descriptors (corn, corn aftertaste, potato, potato aftertaste) produced the biplot shown in Figure 4. There is still a very large distinction between corn-based products on the right and potato-based products on the left along the first dimension. Interestingly, the choice of flavor, independent of base, creates the same order of difference in the samples as varying the flavor dosages between 5% and 7%. A closer examination of products R and F showed no support for modifying flavor type or dosage to compensate for the higher fatty-taste associated with the F structure. In both Figures 3 and 4 the descriptors spicy (a retronasal sensation) and salty (one of the basic tastes) are orthogonal to the descriptors responsible for major product separation. For this reason it was possible to conduct TI experiments on all samples using both of these descriptors.

Experiment 3 As a rule of thumb, snack flavors are usually prepared so that there is 1.8% salt on the finished product. Experiment 3 was designed to investigate by TI the effect of flavor dosage without such a correction. The average TI curves shown in Figure 5 indicate that all the intensity-related parameters for both descriptors are indeed directly proportional to the dosage. The R E M L analysis per descriptor indicated that the 8% dosage was significantly greater than the 4% dosage for log (area), log (Imax) and log (Iswal) obtained on both descriptors. For salty the higher dosage also had a significantly larger log (Tdur). There was no significant dosage-related difference in log (durmax), log (Tmax) or log (Tswal). Conducting the R E M L analysis per TI parameter over the two descriptors and two products showed that panelists swallowed later when evaluating the retronasal descriptor paprika than when evaluating saltiness. This difference was larger at lower dosage, as shown in the biplot for this experiment (Figure 6).

Experiments 4 and 5 In both single and multiple ingestion TI tests using the products C, Τ and R, flavor perception was most intense and longest lasting on the potato base, product R. The average TI curves for Experiment 4 (Figure 7) show an increase in intensity-



4. PCA ofpanel profiling REML scores from Experiment 2 without 4 base descriptors (corn, corn aftertaste, potato, potato aftertaste). Flavor dosage (5%, 6%, 7%) is indicated within the sample symbol.




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related TI parameters going from C to Τ to R for both descriptors. The R E M L analysis per descriptor indicated no significant differences between C and Τ for any parameter on either spicy/herbs or salty. R was significantly larger than C for log (area) and log (Imax) on spicy/herbs, and R was significantly larger than both C and Τ for these parameters when salty was evaluated. The only significant time-related TI parameter was log (Tdur): R lasted longer than C for the retronasal spicy/herbs. When the R E M L analysis was conducted per TI parameter over the two descriptors and three products it was evident that the salty curves had a larger area, a larger maximum intensity, and they lasted longer than the spicy/herbs curves. Salty curves also had a larger intensity at swallowing, but swallowing occurred faster, as was seen in Experiment 3. These differences in descriptors and products are summarized in the biplot shown in Figure 8. Repeated ingestion of the same products (R, T, C : Experiment 5) reversed the order of increasing intensity parameters for the two corn-based samples, i.e., Τ was perceived as less intense than C. There was insufficient evidence from these tests to prove a faster build-up of flavor in the mouth for the low bulk density C because none of the TI parameters was able to show significant differences between the four ingestions. The biplot for intensity-related TI parameters (Figure 9) shows product separation along the first dimension with T, C, R positioned in order of increasing intensity. The second dimension separates the two descriptors. These descriptors are no longer clearly separated in the biplot for time-related TI parameters shown in Figure 10, although product separation does follow along a diagonal from the 3 to 1 quadrant. In a R E M L analysis for log (Imax) over all data collected in Experiments 4 and 5 it was shown that R > (C, T) with no significant difference between the two cornbased products. Imax for a single ingestion was greater than for any of the multiple ingestions, the latter being not significantly different going from first ingestion to fourth. The salty evaluations were always more intense than the spicy/herbs evaluations. The corresponding R E M L analysis for log (Tmax) in which only the first of the multiple ingestion maxima was used, showed that Τ products reached their maximum intensity faster than R products. The fact that the first maximum of the multiple ingestions occurred sooner than for the single ingestion might be an artifact of the test if panelists felt rushed or stressed by the multiple ingestion procedure The R E M L analysis for log (Tmax) on these combined data also showed a significant difference between the two descriptors: the retronasal sensation reached its maximum 1.7 s before the basic salty taste. (This difference was not significant in either of the single ingestion tests.) Cliff and Noble (5), reporting TI measurements of sweetness (basic taste) and fruitiness (retronasal) in model solutions of glucose/peach essence, found that Tmax for sweetness was 3.8 s shorter than Tmax for fruitiness. They speculated that retronasal perception was aided by the convection and turbulence that occurred during expectoration since sweetness was perceived before expectoration and fruitiness afterward. The same order of perception was found in a later study (6) for binary and tertiary mixtures using sweeteners, although it was only significant for binary systems. rd


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If the difference between Tmax for retronasal as opposed to basic tastes is not simply an artifact of peak size, procedural differences may explain why Noble's group found longer times to reach a retronasal maximum. Panelists in the current study were free to swallow whenever they chose. The fact that panelists swallowed later when evaluating the retronasal flavor might indicate that they required more time to recognize this flavor. No expectoration was allowed in the current study. Other experimental differences in these studies are the nature of the samples (liquid as opposed to solid), and the nature of the basic taste (sweetness versus saltiness). Additional testing of various flavors and products is necessary in order to understand the temporal perception of retronasal as opposed to basic tastes.

Acknowledgements Appreciation is expressed to Laith Wahbi, Rob Walraven and Walter van Damme from Quest Snacks. Paul Arents, Susanne Schroff and Seeta Soekhai are thanked for their help in collecting and processing these data.

References 1. 2. 3. 4. 5. 6.

King, B . M . Lebensm.-Wiss. u.-Technol. 1994, 27, 450-456. King, B . M . ; Moreau, N. J. Inst. Brew. 1996, 102, 419-425. Härdie, W. Applied Nonparametric Regression; Econometric Society Monographs No. 19; Cambridge University Press: Cambridge, 1991; pp 24-36. Overbosch P.; van den Enden J.C. and Keur B . M . Chem. Senses. 1986, 11, 331-338. Cliff, M.; Noble, A . C . J. Food Sci. 1990, 55, 450-454. Matysiak, N . L . ; Noble, A . C . J. Food Sci. 1991, 56, 823-826.


Effect of Base and Processing on Flavor Release from Snacks

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