RELATIONSHIP BETWEEN INSTRUMENTAL AND SENSORY ANALYSIS OF TEXTURE AND COLOR OF POTATO CHIPS

SANDRA SEGNINI’ and PETR DEJMEK

Department of Food Engineering

AND

RICKARD OSTE

Department of Food Chemistly and Applied Nutrition Lund University, Sweden

Received for Publication June 23, 1999; Accepted for Publication December 1. 1999

ABSTRACT

The instrumental and sensory analysis of the texture and color of commercial potato chips were compared. l l e instrumental measurement was a puncture test with an Intron Universal Testing Machine, and the parameters used were fracture force, deformation and stifiess. The instrumental color quantifica- tion was a computerized video image analysis tachnique, and the color was expressed as L*a*b* values, Sensory evaluation of texture and color was performed by a sensory panel especially trained in evaluating potato chips. The sensory attributes were “hardness”. “chewiness”, “crunchiness ”, and “tender- ness” for texture analysis, and ‘yellow color ”, “burnt aspect ”, “sugar colored aspect ’’ and “transparency ”for color analysis. The factor analysis of the sensory attributes indicated that texture can be divided into two principal components, one represented by “hardness ”, “crunchiness” and “chewiness ”, and the other by “tenderness” alone. The factor analysis of the color can be divided into two principal components, one including “yellow color ’’ and “burnt aspect ”, and the other “sugar colored aspect” and “transparency”. Discriminant analysis showed that “tenderness” and “crunchiness ’’ could predict correctly over 90% of the data. Fracture force correlated well with all of the sensory attributes (R2 > 0.76). and L* with the sensory color attributes (R2 > 0.75,). The “Tenderness” was the individual sensory attribute which had the highest correlation (R2 = 0.95) with fracture force.

i Corresponding author address: S. Segnini, Department of Food Engineering, Kemicentrum, Lund University, P.O.Box 124, S-221 00 Lund, Sweden

Journal of Texture Studies 30 (1999) 677-690. AN Rights Reserved. OCopyright I999 by Food & Nutrition Press, Inc., Trumbull. Connecticut 677

618 S. SEGNINI. P. DEJMEK and R. OSTE

INTRODUCTION

Texture and color are the most important parameters in the definition of the quality of potato chips (Smith 1975; Orr and Janardan 1990; Scanlon ei al. 1994). Their subjective measurements usually do not give any reproducible results due to the complicating factors relating to human perception (Kramer and Szczesniak 1973). Therefore, it is important to find a good objective method that can predict the sensory perception of these parameters (Szczesniak er al. 1963; Andersson er al. 1994).

Potato chip texture is often described in terms of crispness, hardness, crunchiness, etc. (Bourne er al. 1966; Smith 1975). Few studies have been performed to find a useful relationship between sensory and objective analyses of potato chip texture. Bourne er al. (1966) measured potato chip texture using a universal testing machine, and found that the initial slope of the force- deformation curve appeared to increase with increasing crispness, and that the maximum fracture force varied considerably, Katz and Labuza (1981) measured the texture of potato chips using snap and punch tests, but concluded that their analyses did not produce any quantitative information for indicating crispness intensity. They found that potato chips, due to their irregular shape, size, and curvature, produced inconsistent fracturing patterns. Vickers (1987) related sensory and acoustic attributes of potato chip crispness with instrumental analyses, and found that crispness can be predicted by an instrumental test when mechanical and acoustic parameters are measured. Difficulties in relating sensory and objective tests have also been found for the texture of cooked potato (Harada and Paulus 1986; Bohler et al. 1987; Jaswal 1991; Du Pont er al. 1992; Jarvis and Duncan 1992; Truong et al. 1997).

Color and the surface appearance of potato chips are usually measured by comparison with standard photographs. This technique produces considerable variability due to the influence of the surrounding light, and variation between the objective reaction of different observers, or the reaction of the same observer at different times (Chebey and Walkof 1971; Kent and Porreta 1992). Instrumental measurements of color are based on the Grassman 's laws according to which any color can be exactly reproduced by mixing three primary lights (Clydesdale 1978; Hunt 1991; Kent and Porreta 1992). The relationship between the sensory and instrumental evaluation of potato chip color has not been satisfactorily studied. Isleib (1963) compared the use of the Photovolt 610 reflectance meter with a green tristimulus filter with Coughlin scale values for potato chips color. Coles et al. (1993) developed a "quick crisp method" for estimating potato chip color, and its results were compared with those of the Agtron instrument. The correlation found was relatively good but the authors concluded that the observer tended to overestimate at low vdues and to underestimate at high values.

INSTRUMENTAL AND SENSORY ANALYSIS OF POTATO CHIPS 619

In the present study, the texture and the color of potato chips were evaluated by both sensory and instrumental analyses. The objective of our investigation was to find a relationship between instrumental and sensory analyses of the texture and color of potato chips.

MATERIALS A N D METHODS

Industrially produced potato chips from OLW AB (Sweden) were used as samples. The potato chips called “PPM” , “Naturchip” , “Natur-brinda” , “Natur- gamla”, and “Lantchip” were used in the training section and for the relation- ship between the sensory and instrumental tests. They represented a range of texture and color variability of potato chips. Only the chips called “PPM”, and “Naturchip” were used to define the principal components that describe the sensory perception of texture and color (appearance) attributes.

Instrumental Texture Measurement

The puncture test was performed using an Instron Universal Testing Machine (model 4442, Buckinghamshire, United :Kingdom). The chips were punched by using a pin (5.3 mm diameter) while resting on a 3-point support (distance between the points was 15 mm), Fig. 1, according to Segnini et al. (1999a). The crosshead speed was 50 mm/min. All tests were conducted at ambient temperature and humidity on samples retrieved from a single freshly opened package. Mechanical parameters used were fracture force (Force, N), deformation at fracture (mm), and stifhess (N/mm).

diam 5.3 rnrri

FIG. I . CHIP PUNCTURE TEST

680 S . SEGNINI, P. DEJMEK and R. OSTE

Instrumental Color Quantification

video image analysis technique (Segnini ef al. 1999b). L*a*b* color spaces were quantified on each sample using a computerized

Sensory Analysis

Sensory texture profiles were assessed by 10-12 panel members previously trained in profile methods on chips. The panelists were trained to measure texture and appearance of potato chips by tasting several samples with known properties, in 3 consecutive training sessions each of approximately 30 min. The panel agreed on texture and appearance attributes and their definitions (Table 1). Scores for texture and appearance attributes were based on a 0-10 linear scale, with 0 indicating the lowest and 10 highest score of the attribute. The panelists tested a sample twice, chewing a chip until it was finely divided and melted in the mouth. The panelists were also provided with water and wheat flour wafers to clean their mouth between samples. All sessions were held in a special laboratory for sensory testing (Wasabrod, Sweden).

TABLE 1. SENSORY PANEL ATTRIBUTES FOR TEXTURE AND APPEARANCE OF

POTATO CHIPS

Texture Harahess (?nir&ess): grade the force necessary to bite the chip.

Chewiness (seghet): grades the resistance and energy when chewing the

chip. Tenderness (nrOrher): grades how the chip falls apart in the mouth.

Crunchiness (kmprighet): grades the crispness and the sharp sound when

the chip is bitten.

Yellow Color (pi far@: color of the chips according to the Agtron Appearance and Color instrument.

Sugar coloredqect (sockrrosiigt)): brown color on the surface of the chip

Burnt aspect fir&?): very dark or black color on the surface of the chip.

T r v e n c y (gfmigf): transparent color of the chip.

Statistical Analysis

Statistical analyses were done using Minitab Release 12.2 for Windows (Minitab Inc., USA). All the instrumental tests for texture and color measure-

INSTRUMENTAL AND SENSORY ANALYSIS OF POTATO CHIPS 68 1

ments were performed with 10 replicates, and the mean and standard error were calculated. Analyses of variance were done for sensory and instrumental data with p 10.05. Pearson correlation coefficients were also performed for the sensory and instrumental attributes. Principal component factor analysis with equamax rotation was done for the sensory data. Discriminant analysis was done for the sensory data. Linear multiple regressions were performed to predict the sensory attributes by instrumental parameters.

RESULTS

The results of the instrumental analysis of the texture and color of PPM and Naturchips are shown in Table 2. Fracture force and stiffness varied significantly among the potato chip samples, but deformation at fracture was not significantly different. The texture of the Naturchips gave a higher fracture force than PPM texture, but their deformation at fracture was similar to PPM. Both types of chips were made from the same potato variety (Saturna), but they were processed in different fryers at different temperalxre curves. Therefore we observed a clear difference in texture, even though the deformation at fracture was similar. The values for color were not significantly different for the two types of samples.

TABLE 2. MEANS AND STANDARD DEVIATION FOR INSTRUMENTALLY MEASURED

TEXTURE AND COLOR PARAMETERS

P'otato chip samples

TEXTURE PARAMETERS (n=20) PPM Naturchip

Fracture force (N) 7 20 f 1 62b

Deformation at fracture (mm) 057fG17'" 0 69 rf: 0 28"

Stiffness (N/mm) 8 14+421" 12 13 f 6 32b

COLOR PARAMETERS (n=12)

L*

a*

b*

' Means in the same row with the same letter are not significantly different @SO 05)

4 16 * 1 45"

84 95 * 2 29"

-5 39 f 1 20"

43 26 k 2 05"

85 74 f 1 62"

-6 46 f 1 05'

43 88 + 3 65"

682 S . SEGNINI, P. DFJMEK and R. OSTE

The means and standard deviation as graded by the trained sensory panel are shown in Table 3. The texture analysis showed a significant difference between the two types of potato chip samples, Naturchips scoring highest in all texture attributes. The color and appearance analysis values were not significant- ly different for both types of samples as for the instrumental results.

TABLE 3. MEANS AND STANDARD DEVIATION FOR TEXTURE AND COLOR PARAMETERS

MEASURED BY SENSORY PANEL

Potato chip samples TEXTURE PARAMETERS (n= 1 8) PPM Naturchip

Hardness 2.53 f 0.98‘ 4.49 * 1.22b- Tenderness 5.71 f 1.67’ 3.49 f 1.15b

Crunchiness 3.38 f 1.20’ 2.89 f 1.44b

Chewiness 1.84 f 0.92’ 2.81 & 1.36b

COLOR PARAMETERS (n= 18)

Yellow color 4.01 k 1.03’ 3.80 k 1.14‘

Burnt aspect 0.89 f 0.76’ 0.95 f 1.03’

Sugar colored aspect 3.02 f 1.27’ 3.16+ 1.17’

Transparency 3.13 k 1.68’ 2.70 f 1.09’

Means in the same row with the same letter are not significantly different (p50.05)

Correlation Analysis

Sensory attributes with significant correlation coefficients among themselves are shown in Table 4. Even though these correlations were significant, their coefficients were low (0.33 <p<O.62) indicating that all of the attributes vary more or less independently. “Hardness” correlated with “tenderness”, “crunchiness”, and “chewiness” (R 20.4), but “tenderness” did not correlate with “crunchiness” and “chewiness”. In the color analysis, the “yellow color” correlated with “sugar colored aspect” (R=0.5), and this also correlated with “burnt aspect” (R=0.381), and “transparency” (R=0.5).

INSTRUMENTAL AND SENSORY ANALYSIS OF POTATO CHIPS 683

TABLE 4. CORRELATION COEFFICIENTS AMONG SENSORY ATTRIBUTES

Eardness Tenderness Crunchiness Chewiness Yellow C. Burnt Sugar C

Tenderness -0 407

Crunchinns 0 625 * Chewiness 0 485 * 0 562

Yellow U. * 0 370 * 0 361

Burnt 0 330 * L * * Sugar C. * L 1: 0538 0505 0382

Transparency * 0 330 * 0 341 * * 0 504

Correlatton coetrc~ents XI 4 are sigruficant at PO 01. coellicient t 0 33 are agntficant at psQ 05. m not agntlicant.

Factor analysis was done separately for the texture and color analysis (Table 5) . In both cases, the attributes could be represented by two factors. Texture attributes could describe 8 1.1 % of the data variance. The texture results showed two principal components, which are shown clearly in Fig. 2. The first component was represented by “hardness”, “crunchiness” and “chewiness” , explaining 50.6% of the variance in the data. The second component was represented by “tenderness’’ only.

Color and appearance attributes could describe 73.1 % of the data variance by two factors. Figure 3 shows the loading plot between the first and the second factor. The first component was represented by “yellow color” and “burnt aspect”, explaining 38.1 % of the data variance, and the second component corresponded to “sugar colored aspect” and “transparency” attributes.

Discriminant analysis was used to classify the observations and to investigate how the variables contribute to group separations. The analysis for color attributes showed that all of the variables were not significant (p > 0. l), which means that these variables could not discriminate the color of the potato chip samples used. This result corresponds to those from analysis of variance. where the sensory color attributes were not significantly different for the two types of potato chip samples. The sensory color attributes could not explain the data variance very well.

684

1 ,o -

b 0,5 - 0 m LL

L1

pr 0 0.0 - 0

m

JJ3 -

S. SEGNINI. P. DEJMEK and R. OSTE

Equarnax rotation Tenderness

Chewines

Crunchiness

I I I I I I I I I I

TABLE 5 . ROTATED FACTOR LOADINGS OF THE SENSORY ATTRIBUTES

Factor’

Attribute F1 FZ Hardness 0.76

Tenderness 0.97

Crunchiness 0.88

Chewiness 0.85

Variance 2.03 1.22

% CPVA’ 50.6 81.1

Yellow C. 0.71

Burnt 0.83

sugar c. 0.67

Transparency 0.94

Variance 1.52 1.40

% CPVA’ 38.1 73.1

’ Loadings > 0.6

* Cumulative proportion of variance accounted.

INSTRUMENTAL AND SENSORY ANALYSIS OF POTATO CHIPS 685

’?O]] Equamaw rotation

L

s LL 0 . 5 - V m

U c 0 u 0) cn

0,o -

I I I I I 0.0 0 2 0.4 0.6 0.8

First Factor

Sugar colomd

Yellow Color

FIG. 3. LOADING PLOT OF SENSORY COLOR (APPEARANCE) ATTRIBUTES

Discriminant analysis of the sensory texture attributes showed that using all texture attributes could correctly identify 94.5% of the data, with only 3 misclassified observations (Table 6, Eq. 1). A similar result was obtained when only two variables were included in the discriminant function. “Tenderness” and “crunchiness” could predict correctly 90.9% of the data, with only 5 misclassi- fied observations (Table 6 , Eq. 2). “Crunchiness” correlated with “hardness” and “chewiness” , and it was in the first principal component of texture, together with “hardness” and “chewiness”. Therefore Eq. 2 (Table 6 ) can be used, in practice, to discriminate the texture of potato chip samples.

TABLE 6 . DISCRIMINANT ANALYSIS FOR SENSORY ATTRIBUTES OF TEXTURE

Discriminant functions

1 ~ -0 PI9flardness) t I . 143(Tendemess)-O, 6lcS(Crunchiness)-O 693((7hewiness)

I = I . 1 O29(Tendemess)-I. I21 4(Cmnchiness)

Eq I

Eq. 2

Predicted proportion=0.945, Misclassified observations-3

Predicted proportion-0 909, Misclassified observations=5

686 S. SEGNINI, P. DETMEK and R. OSTE

Analyzing the correlation coefficients among the instrumental results, texture attributes were not significantly correlated among themselves (p > 0.05), while in the color attributes, L* was significantly correlated with a*(R=-0.-745) and b* (R =-0.381). Stiffness, which is a texture attribute, correlated significant- ly with b*, a color measure (R=-0.455), indicating a relationship between texture and color of potato chips.

Correlation between sensory and instrumental data was investigated using all the potato chip samples. Fracture force was the instrumental attribute that correlated well with all of the sensory texture attributes (R >0.76). Deformation at fracture did not significantly correlate with any of the sensory attributes (p >0.05), and stiffness correlated with “chewiness” (R=0.775) and “transpar- ency” (R =-0.794). Here, we observed another relationship between texture and color. In the color analysis, L* showed a high correlation between “yellow color”, “burnt” and “sugar colored aspect” (R >0.79), and a* correlated highly with “burnt aspect” (R=0.785). The b* attribute did not significantly correlate with any of the sensory parameters (pB0.05).

It appears that the sensory attributes could be predicted by the instrumental parameters. Fracture force seems to be a good predictor for all of the sensory texture attributes, and L* could predict most of the sensory color attributes.

Linear Multiple Regressions

Linear multiple regression analysis was performed to predict the sensory attributes by the instrumental parameters. Regression equations are presented in Table 7. All of them were significant (pCO.05) and had R220.6. The best predicted attributes were “tenderness” (R2=0.95), which corresponded to the second principal component of the sensory texture, and “burnt aspect”(RZ=0.80) which was one of the first components of sensory color. “Chewiness” could be predicted by fracture force (R2=0.58) or stiffness (R2=0.60) but when a multiple regression analysis was done using both predictors, the resulting equation was not significant.

Difficulties in relating sensory and instrumental measurements of food texture have been summarized by Szczesniak (1987). Recent studies still showed these difficulties. Reyes-Vega el al. (1998) studied the texture of corn tortillas, and found that the puncture test using a cylindrical (flat-end) punch did not show a good correlation with the sensory attributes even though this test could be used to differentiate brands, but peak force from the puncture test with a spherical punch showed a good correlation with tearing by hand, and sensory hardness (0.86 and 0.96, respectively). Also, TPA parameters showed correlations with some sensory attributes as moisture, springiness, stickiness, and grittiness (r > 0.8). Vickers and Christensen (1980) studied the sensory/instrumental relationship of different crisp foods, and found sensory firmness correlating

INSTRUMENTAL AND SENSORY ANALYSIS OF POTATO CHIPS 687

TABLE 7 . REGRESSION EQUATIONS FOR SENSORY AND INSTRUMENTAL PARAMETERS’

Equation R f

Hardness = 0 45 + 0.514(Force) 0 59

Tenderness = 8.41 - 0.674(Force) 0.95

Crunchiness = 1.22 + 0.509(Force) 0.68

Chewiness = 1.21 + 0.186(Force) or

Chewiness = 1.42 + 0.0999(Stifiess)

0.58

0.60

Yellow Color = 39.1 - 0.416 (L*) 0.63

Burnt = 87.4 - 1.07(L*) - 0.797(a*) 0.80

Sugar Colored = 29.8 - 0.3 13 (L*) 0.63

’ AU ofthe equations are sigruficant @CO.OS).

reasonably well (R=0.5-0.7) with peak force, and ’Young’s modulus. They also concluded that crispness was more closely related to acoustical qualities than oral tactile qualities.

CONCLUSIONS

Sensory attributes of potato chips were divided into two principal components for texture and color analyses. Texture attributes were “hardness”, “crunchiness” and “chewiness” (factor I), and “tenderness” (factor 2), which explained 8 1.1 % of the data variance. These texture attributes were highly correlated with fracture force (R > 0.76). Discriminant analysis showed that chips could be differentiated by ”tenderness” and “crunchiness”. The principal components of color were “yellow color” and “burnt aspect” (factor l), and “sugar colored aspect” and “transparency” (factor 2), which explained 73.1 % of the data variance. These color attributes were highly correlated with the L* value (R > 0.79). Fracture force was highly correlated with all of the sensory

688 S. SEGNINI. P. DEJMEK and R. OSTE

texture attributes, and L* with the sensory color attributes. The sensory attribute best predicted from the instrumental measurements was “tenderness”, which correlated with fracture force (R2> 0.95).

The results indicate that instrumental techniques for texture and color measurements can be used to estimate the sensory attributes of potato chips, which offers the possibility to predict the quality of chips during processing.

ACKNOWLEDGMENTS

The authors wish to acknowledge fmancial support from OLW Chips AB (Sweden), Procordia Food AB (Sweden), and the Swedish Board for Technical Development.

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