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Shelf life estimation of brown pan bread: A consumer approach
Food Quality and Preference 18 (2007) 196–204 www.elsevier.com/locate/foodqual
Shelf life estimation of brown pan bread: A consumer approach Ana Gime´nez a
a,* ,
Paula Varela b, Ana Salvador b, Gasto´n Ares a, Susana Fiszman b, Lorena Garitta c
Seccio´n Evaluacio´n Sensorial, Ca´tedra de Ciencia y Tecnologı´a de Alimentos, Facultad de Quı´mica, Av. General Flores 2124, Montevideo C.P. 11800, Uruguay b Instituto de Agroquı´mica y Tecnologı´a de Alimentos (CSIC), Apartado de Correo 73, Burjassot, Valencia, Spain c Instituto Superior Experimental de Tecnologı´a Alimentaria, H. Irigoyen 931, 6500 Nueve de Julio, Buenos Aires, Argentina Received 25 April 2005; received in revised form 17 August 2005; accepted 28 September 2005 Available online 9 November 2005
Abstract In this study three different approaches—acceptability limit, failure cut-off point methodology, and survival analysis—to estimate the sensory shelf life of brown pan bread elaborated with different enzymes using consumer data were compared. The study was carried out in Spain and Uruguay independently, where four batches of bread were produced, with the same base formulation, one without enzyme, the others with the addition of maltogenic amylase, xylanase, and a mixture of both. The results showed that for Uruguayan consumers the mixture of enzymes provided better results in extending shelf life than the addition of amylase alone. For the Spanish consumers only the addition of amylase provided the desired results, and for consumers of both countries the use of xylanase did not extend the shelf life of bread. Among the methodologies used for the estimation, survival analysis provided the most adequate predictions considering consumer rejection of the product. Hedonic scales do not always reflect consumer behaviour when deciding whether to accept or reject a certain product for its consumption. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Brown pan bread; Enzymes; Shelf life; Survival analysis; Cut-off point methodology; Acceptability
1. Introduction Bread staling is responsible for important economical losses to both the baking industry and the consumer. Although it has been extensively studied, it remains unsolved. Staling is a general term that describes the time-dependent loss in quality of flavour and texture of bread. Bread staling is a complex phenomenon in which multiple mechanisms operate (Gray & Bemiller, 2003). The use of enzymes in the baking industry is mainly concerned with retarding this phenomenon and extending bread sensory quality throughout its shelf life, by acting on major functional flour components (Armero & Collar, 1998; Collar & Armero, 1996). The most useful enzymatic *
Corresponding author. Tel.: +598 2924 5735; fax: +598 2924 1906. E-mail address: [email protected] (A. Gime´nez).
0950-3293/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodqual.2005.09.017
approach to staling rate reduction has been the use of alpha-amylases, which catalyse a small amount of hydrolysis of starch keeping bread freshness for a longer period of time. Non-amylolytic enzymes may also be active in the enzyme supplements although it is unclear whether enzymes that degrade non-starch polysaccharides in bread have any effect on bread staling (Van Eijk & Hille, 1996). Xylanases hydrolyze pentosans present in wheat flour, accelerating the baking of bread by helping to break down polysaccharides in dough (Courtin & Delcour, 2002; Kulp, 1993). While Harada (2000) states that the use of these enzymes extends shelf life of bread by retarding starch retrogradation, Bollaı´n, Agioloni, and Collar (2005) reported that xylanase promotes an increase in bread firmness with storage time. Some synergistic effects of enzymes for dough conditioning and in extension of shelf life have been studied for specific breadmaking processes (Collar, Andreu, &
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Martı´nez-Anaya, 1998; Collar, Martı´nez, Andreu, & Armero, 2000; Haarasilta, Pullinen, Vaiasanen, & TammersaloKarsten, 1989; Qi Si, 1997; Sato, Sato, & Nagashima, 1991). Bollaı´n et al. (2005) have also reported that the joint addition of xylanase and amylase improves bread quality. Food products do not have sensory shelf lives of their own; rather they will depend on the interaction of the food with the consumer. For this reason consumers are the most appropriate tool for determining food product sensory shelf life (Hough, Langohr, Go´mez, & Curia, 2003). Different methodologies could be used to determine the shelf life of a food product, using consumer data. In the failure cut-off point methodology, shelf life is determined as the time when the first significant change in overall acceptability is detected. At this time, consumers detect a change in the sensory characteristics of the product with respect to the fresh product. However, this does not mean that consumers would refuse to consume the product. Sensory shelf life could also be determined as the time required for the overall acceptability scores of the product to fall below a certain predetermined value, for example a value of 6.0 in a 9-point structured hedonic scale (Mun˜oz, Civille, & Carr, 1992). However, this methodology provides little information as to what consumers would normally do when facing the product. In order to estimate sensory shelf life based on consumer rejection of a food product, survival analysis could be applied. This methodology focuses the shelf life risk on the consumers rejection of the product. Survival analysis has been used to estimate shelf life of some baked products (Ga´mbaro, Fiszman, Gime´nez, Varela, & Salvador, 2004; Ga´mbaro, Gime´nez, Varela, Garitta, & Hough, 2005), estimating the product shelf life as the time necessary to reach a fixed percentage of consumer rejection. Comparison of failure criteria among consumers from different countries would help to determine shelf life with a more appropriate perspective (Hough et al., 2002). The objectives of the present work were: (a) To compare shelf life of brown pan bread manufactured with amylase, xylanase and a mixture of both in two different countries, using consumer data. (b) To compare the suitability of different methodologies currently used to estimate sensory shelf life of this type of product: acceptability limit, failure cut-off point methodology, and survival analysis.
2. Materials and methods 2.1. Enzymes Maltogenic amylase from Bacillus stearothermophilus of intermediate thermo stability in granulate form (Novamyl 10000 BG, 10000 MANU/g) and xylanase from Thermomyces lanuginosus in granulate form (Pentopan Mono
197
BG, 2500 FXU/g), both from Novo Nordisk A/S, Denmark. 2.2. Samples The study was carried out independently in Spain and Uruguay. Four batches of bread were manufactured in each country, all having the same formulation but differing on the type of enzyme used. One batch was manufactured without the addition of enzymes (control); one with the addition of amylase, one with xylanase, and a fourth one with a 1:1 mixture of amylase/xylanase. The amounts of enzymes used in each country were selected according to the flour employed in their manufacture. The quantities were: 30 mg/100 g of flour of xylanase in both countries, 30 mg/100 g of flour of maltogenic amylase in Uruguay and 7.5 mg/100 g of flour of amylase in Spain. The addition of maltogenic amylase was based on the measure of native amylolitic activity of flour for each country. The ingredients used for the manufacture of bread were those currently used in each country (mentioned in order of quantity; Spain: water, wheat flour, wheat bran, sugar, vegetal hydrogenated oil, yeast, acetic acid, salt, dried whey, calcium propionate. Uruguay: water, wheat flour, whole wheat flour, wheat bran, corn syrup, gluten, yeast, salt, powdered skimmed milk, vegetable hydrogenated oil, honey, diacetyltartaric acid esters of mono and diglycerides of fatty acids, and calcium propionate). In Uruguay breads were industrially manufactured (Walter M. Doldan y Cia. SA, Montevideo, Uruguay) especially for the experiments; in Spain they were manufactured in a pilot plant at the Instituto de Agroquı´mica y Tecnologı´a de Alimentos, Valencia. In both countries (Spain/Uruguay), the manufacturing process consisted of making a sponge with half the flour, half the water, and yeast, followed by mixing (10 min/ 5 min), intermediate fermenting (2 h at 28 °C, 20 h at 5 °C and 1.5 h at 28 °C/3 h at 26 °C) before being added to the dough. All the ingredients were then mixed (60 rpm, 14 min/60 rpm, 12 min) until optimum dough consistency was reached. The fermented doughs were obtained by bulk fermentation (30 min/1 h), division (600 g/500 g), rounding, resting (10 min/5 min), panning and 1 h fermentation to maximum volume (1 h, 28 °C, 85%RH/1 h, 35 °C, 85%RH). Fermented dough was baked at 180 °C for 20 min (tray oven/continuous industrial oven), breads were then cooled for 2 h, sliced (12 mm slices/20 mm slices), and packaged in polyethylene bags. Breads were stored in a temperature-controlled storage room at 20 °C (in Spain for 0, 4, 7, 10, 13, 16, and 20 days, and in Uruguay for 1, 4, 7, 10, 13, 15 and 17 days). After reaching the desired storage times, breads were frozen at 20 °C and stored at 18 °C, providing samples with different storage times from one batch for each formulation (Gacula & Kubala, 1975). The samples were defrosted at 20 °C for 6 h, for its evaluation.
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When samples reached each of the desired storage times, microbiological analysis (aerobic mesophiles, coliforms, yeasts and molds) were performed in both countries prior to freezing. These analyses showed that samples stored for the longest times in each country were fit for human consumption. 2.3. Consumer study
A regression was carried out considering ‘‘% of acceptance’’ (calculated as the proportion of consumers who accepted the sample, that answered ‘‘yes’’ to the question ‘‘would you normally consume this product?’’) as dependent variable, and consumers ‘‘overall acceptability’’ (averaged over consumers) as explanatory variable. The following equations were tested using linear and non-linear regression: Linear : % of acceptance ¼ a þ b A
People who consumed brown pan bread at least once a week were recruited for each country from the cities of Montevideo, Uruguay and Valencia, Spain. In each country, 50 consumers, ages ranging between 18 and 50, evaluated bread samples. The testing was carried out in four sessions. In each session the consumers received the seven samples corresponding to the seven storage times of each of the four batches, using a balanced complete block design. For each sample they had to score overall acceptability of the product using a 9-box scale labelled on the left with ‘‘dislike very much’’, in the middle with ‘‘indifferent’’ and on the right with ‘‘like very much’’. They also answered the question ‘‘Would you normally consume this product?’’ with a yes or a no (evaluation sheet shown in Fig. 1). It was explained that this meant that if they bought the product or it was served to them, whether they would consume it or not. The testing was carried out in both countries in sensory laboratories that were designed in accordance with ISO 8589:1988.
Exponential: % of acceptance ¼ a þ b cA b Logistic: % of acceptance ¼ a þ 1 þ ecðAdÞ where A is overall consumer acceptability, and a, b, c, d are the regression constants. All these analysis were performed using Genstat 5 Release 3.2 (Lawes Agricultural Trust, Rothamsted).
2.4. Statistical analysis
2.4.1. Failure cut-off point methodology In this methodology shelf life is estimated considering as failure point the first significant difference in overall acceptability. This point could be calculated using the following equation (Hough et al., 2002): rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 MSE S ¼ F Za ð1Þ n where S = minimum tolerable acceptability of stored sample; F = acceptability of fresh sample; Za = one-tailed coordinate of the normal curve for a significance level; MSE = mean square of the error derived from the analysis of variance of the consumer data; n = number of consumers.
A two factor (storage time and type of enzyme) analysis of variance for all samples was performed on the overall acceptability data obtained. Mean rating and Fishers Least Significant Difference for each term were calculated.
2.4.2. Survival analysis Survival analysis methodology was used to estimate the shelf life of the four formulations of brown bread of the two countries using the results obtained from consumers
EVALUATION SHEET INSTRUCTIONS: ♦ You will evaluate 5 samples of BROWN PAN BREAD. ♦ Please try the first sample. ♦ Score the OVERALL ACCEPTABILITY of the sample using the scale and answer the question. ♦ Continue with the other samples. SAMPLE No___
Dislike very much
Indifferent
Like very much
Would you normally consume this product? Yes
No
THANK YOU VERY MUCH
Fig. 1. Evaluation sheet.
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when asked if they would normally consume the samples (Hough et al., 2003). The key concept of this methodology is to focus the shelf life hazard on the consumer rejecting the product. Defining a random variable T as the storage time at which the consumer rejects the sample, the survival function S(t) can be defined as the probability of a consumer accepting a product beyond time t, that is S(t) = P(T > t). Alternatively, the cumulative distribution function F(t) can be defined as the probability of a consumer rejecting a product before time t, that is F(t) = P(T 6 t). Because of the discrete nature of the storage times, T will never be observed exactly, hence the censored nature of the data (Hough et al., 2003). Suppose that consumers are presented with samples stored at times a, b and c. If a consumer rejects the sample at the first storage time observed, then T 6 a and the data is left-censored. If a consumer accepts the sample stored at time a, but rejects the sample stored at time b, then a < T 6 b and the data is interval-censored. Finally, if a consumer accepts all samples, then T > c and the data is right-censored. The likelihood function, which is used to estimate the survival function, is the joint probability of the given observations of the n consumers (Klein & Moeschberger, 1997) Y Y Y L¼ Sðri Þ ð1 Sðli ÞÞ ðSðli Þ Sðri ÞÞ ð2Þ i2R
i2L
i2I
where R is the set of right-censored observations, L is the set of left-censored observations and I is the set of interval-censored observations. A parametric model can be used to estimate the survival function and other quantities of interest. Choosing a lognormal distribution for T (Klein & Moeschberger, 1997; Lindsay, 1998), the rejection function is given by lnðtÞ l SðtÞ ¼ 1 U ð3Þ r where U( Æ ) is the standard normal cumulative distribution function, and l (location parameter) and r (shape parameter) are the models parameters. The parameters of the model are obtained by maximizing the likelihood function (Eq. (2)). The likelihood function is a mathematical expression that describes the joint probability of obtaining the data actually observed on the subjects in the study as a function of the unknown parameters of the model being considered. To estimate l and r for the log-normal distribution, the likelihood function is maximized by replacing S(t) in Eq. (2) with the expression given in Eq. (3). Once the likelihood function has been established for a given model, specialized software can be used to estimate the parameters (l and r) that maximize the likelihood function for the given experimental data. To estimate shelf life, the probability of a consumer rejecting a product (that is, F(t)) must be chosen. Gacula and Singh (1984) mentioned a nominal shelf life value considering 50% rejection, and Cardelli and Labuza (2001)
199
used this criterion in calculating shelf life of coffee. Ga´mbaro et al. (2004), and Ga´mbaro et al. (2005) used 25% rejection to estimate the shelf life of baked products. In the present study, in order to be conservative and assure product quality, shelf life was calculated for F(t) = 25%. This means that if a consumer tries the product at the end of its shelf life, there is a 25% probability that he will reject it. Considering that few consumers will taste the product near the end of its shelf life, and that of the few that do 75% will still find the product acceptable, this value of F(t) = 25% is considered reasonable from a practical point of view. For the Uruguayan and Spanish breads, in order to establish if the enzyme addition influenced rejection times, the following log linear regression model with inclusion of indicator variables was applied (Klein & Moeschberger, 1997) lnðT Þ ¼ l þ r W ¼ b0 þ b1 Z 1 þ r W
ð4Þ
where T is the storage time at which a consumer rejects a sample; b0, b1 are the regression coefficients; Zi is the indicator variable indicating the type of enzyme: Z1 = 1 for control, Z1 = 0 otherwise; Z2 = 1 for amylase, Z2 = 0 otherwise, Z3 = 1 for xylanase, Z3 = 0 otherwise, Z4 = 1 amylase/xylanase; Z4 = 0 otherwise; r is the shape parameter, which does not depend on the indicator variable; W is the error distribution. Calculations were performed using procedures from S-PLUS statistical software (Insightful Corp., Seattle, Washington, USA). A 5% significance level was considered. 3. Results and discussion 3.1. Consumer acceptability Consumers were asked to score bread samples with different storage times on overall acceptability hedonic scales. Figs. 2 and 3 show average scores for Spanish and Uruguayan bread samples, respectively. ANOVA results showed that for both countries, acceptability significantly decreased with storage time (p < 0.001), as expected. For Spanish consumers, control bread overall acceptability decreased during the first week, but then remained constant until the end of the study. For Uruguayan consumers, overall acceptability also decreased during the first week, remained constant till day 13 and then decreased till the end of the tested time for control bread. Furthermore, enzyme addition significantly (p < 0.001) affected consumer acceptability. A significant (p < 0.001) interaction between the two factors (storage time and type of enzyme) was found for both countries. For Spanish consumers, the addition of amylase significantly (p < 0.05) increased overall acceptability from day 13 of storage, amylase/xylanase significantly (p < 0.05) increased acceptability between days 10 and 13 of storage, when compared to control bread, whereas xylanase significantly (p < 0.05)
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200 9.0
Control 8.0
Amylase Xylanase
Acceptability
7.0
Amylase:Xylanase
6.0 5.0 4.0
3.0 2.0 1.0 1
3
5
7
9
11
13
15
17
19
21
Time (days)
Fig. 2. Consumer overall acceptability versus storage time for Spanish breads (mean ± standard deviation).
9.0 Control Amylase
8.0
Xylanase Amylase:Xylanase
7.0
Acceptability
6.0
5.0
4.0
3.0
2.0
1.0 1
3
5
7
9
11
13
15
17
Time (days)
Fig. 3. Consumer overall acceptability versus storage time for Uruguayan breads (mean ± standard deviation).
decreased it from day 10 of storage. For Uruguayans, bread formulated with amylase/xylanase significantly (p < 0.05) increased overall acceptability from day 7, when compared to control bread. The addition of amylase significantly (p < 0.05) increased acceptability from day 10 of storage. However, xylanase did not significantly affect acceptability with respect to control bread. Bread staling, usually associated to an increase in crumb firmness, is responsible for the decrease of consumer acceptance with storage time. These results are in agreement with the
reports that suggest that the use of amylase or amylase/ xylanase decreased the staling rate (Bollaı´n et al., 2005; Dura´n, Barber, & Benedito de Barber, 1995; Martin & Hoseney, 1991). However, Spanish consumers appeared to score low values also for breads supplemented with xylanase alone as previously reported. Acceptability scores could be related to percent consumer rejection. A regression analysis was carried out considering the proportion of consumers who accepted the sample as dependent variable, and consumer overall
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acceptability as explanatory variable. In both countries the logistic regression gave the best fit (r2 = 0.77 and r2 = 0.84 for Uruguayan and Spanish data, respectively). The equations for each country are Uruguay: % of acceptance 0:716 ¼ 0:352 þ 1 þ e1:531ðA5:761Þ 1:6 Spain: % of acceptance ¼ 1:088 1 þ e0:73ðA3:3Þ
ð5Þ ð6Þ
where A = overall acceptability. Consumer rejection percent could then be calculated from these equations as (100% of acceptance). 3.2. Shelf life estimation: comparison of different failure criteria 3.2.1. Acceptability limit Mun˜oz et al. (1992) considered an acceptability score of 6.0 in a 9-point hedonic scale as commercial or quality limit. By using this acceptability score as failure criterion to estimate shelf life with Eq. (5), consumer rejection percent for this score would be 23% for Uruguayan consumers. Performing a linear regression on acceptability scores versus storage time (Gacula, 1975), shelf life could be estimated as the storage time when acceptability reaches a value of 6.0. Table 1 shows estimated shelf life with its confidence intervals for each bread formulation. The use of amylase/xylanase significantly increased shelf life of Uruguayan bread, whereas shelf lives of all other formulations did not show significant differences with respect to the shelf life of the control bread formulation. This acceptability limit was too strict a criterion for Spanish consumers of this product. Consumer rejection percent for a score of 6 calculated applying Eq. (6) would be 11% for Spanish consumers; since this value is too low, this criterion could only be applied to Uruguayan breads. Therefore, consumers in both countries behaved differently. Spanish consumers showed a tendency to decrease their overall acceptability scores while deciding to accept the product. This suggests that shelf life decisions based on an arbitrary acceptability limit might be taken with caution as they do not always reflect consumers decision to accept or reject the product.
Table 1 Shelf life for Uruguayan bread estimated using consumer acceptability score limit of 6.0 Formulation
Shelf life (days) ± 95% confidence intervals
Control Amylase Xylanase Amylase/xylanase
9±3 11 ± 4 8±4 17 ± 4
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3.2.2. Failure cut-off point methodology The sensory failure cut-off point methodology (Hough et al., 2002; Ramı´rez, Hough, & Contarini, 2001) provided high values for the minimum tolerable acceptability, ranging from 6.4 to 6.9 for all samples in both countries. Thus, shelf life of samples would range from 1 to 5 days. As stated earlier, since this methodology reflects the time when consumers noticed the first significant difference in the sensory characteristics of the product with respect to the fresh one, estimated shelf lives were too short. It would be too conservative a criterion to be used by the product manufacturer. Therefore, it is obvious that for the products considered in the present study, this methodology does not apply. 3.2.3. Survival analysis Visual assessment of how parametric models adjust to the non-parametric estimation was used to choose the most adequate model (Hough et al., 2003). For the present data, the following standard distributions were compared: smallest extreme value, normal, logistic, Weibull, log-normal and log-logistic. The log-normal distribution adjusted best for all bread formulations. Therefore, it was chosen to model rejection times for the present data. The maximum likelihood estimates of the parameters of the log-normal distribution for each bread formulation, that is applying Eq. (3) with no indicator variables, is shown in Table 2. The influence of indicator variables is analyzed separately. These parameters can be used to graph percent of consumer rejection versus storage time of each bread formulation as shown in Figs. 4 and 5. These graphs can be used to estimate the shelf lives values (x-axis) with their confidence intervals by entering with a 25% consumer rejection (y-axis), as shown in Table 3. For a 25% of consumer rejection, shelf lives estimated ranged from 5 to 11 days for the different formulations of Spanish bread, and from 8 to 16 days for Uruguayan ones. It is worth pointing out that manufacturers give this type of product a shelf life of 13 days in both countries, regardless of their formulation or manufacturing practices. Consumer rejection percent for control bread at day 13 was 50.3% for Spanish consumers and 42.0% for Uruguayan consumers. Therefore, setting the shelf life of bread to 13 Table 2 Values of log-normal distribution parameters l (location parameter) and r (shape parameter) and their confidence intervals for the failure function for breads of both countries Country
Sample
l ± standard error
r ± standard error
Spain
Control Amylase Xylanase Amylase/xylanase
2.55 ± 0.12 3.00 ± 0.18 2.19 ± 0.16 2.76 ± 0.11
0.69 ± 0.12 0.86 ± 0.18 0.92 ± 0.16 0.55 ± 0.11
Uruguay
Control Amylase Xylanase Amylase/xylanase
2.68 ± 0.10 2.76 ± 0.07 2.79 ± 0.21 3.04 ± 0.11
0.59 ± 0.11 0.41 ± 0.08 1.12 ± 0.24 0.36 ± 0.13
A. Gime´nez et al. / Food Quality and Preference 18 (2007) 196–204
202 90
Control Amylase Xylanase Amylase:Xylanase
80
Consumer rejection (%)
70
60
50
40
30
20
10
0 0
5
10
15
20
Time (days)
Fig. 4. Estimation of consumer rejection percent versus storage time for Spanish breads by survival analysis.
70 Control Amylase Xylanase Amylase:Xylanase
Consumer rejection (%)
60
50
40
30
20
10
0 0
2
4
6
8
10
12
14
16
18
Time (days)
Fig. 5. Estimation of consumer rejection percent versus storage time for Uruguayan breads by survival analysis.
days, without considering their formulation would probably lead to the manufacturer receiving more complaints than expected. As shown in Table 3, shelf life of Uruguayan bread manufactured with amylase/xylanase was significantly longer than control bread. These shelf life estimations are in agreement with those estimated by using as failure criterion an acceptability score of 6.0; however, confidence bands are narrower.
Shelf lives estimated using survival analysis seemed more reasonable for manufacturers than the ones estimated using the failure cut-off point methodology for this type of product. Survival analysis estimates shelf lives based on consumer rejection, which could be related to the number of complaints manufacturers might receive when the product reaches the end of its shelf life. Therefore, shelf lives decisions based on survival analysis might be more appropriate to manufacturers.
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3.2.3.1. Influence of indicator variables. To study the influence of ‘‘the type of enzyme’’ in consumer rejection time distribution for each country, distributions for each formulation were compared to the other three. Results are shown in Table 4. For Uruguayan breads, significant differences were found between the rejection time distributions of bread manufactured with the mixture of enzymes when compared to the other three formulations. For Spanish breads, significant differences were found for rejection time distribution of bread manufactured with amylase versus xylanase, amylase versus control, and xylanase versus amylase/xylanase. Uruguayan bread formulation with amylase/xylanase had lower rejection rates than the other three formulations. Likewise, Spanish bread formulation with amylase had a lower rejection rate than control bread. Using Eqs. (5) and (6), acceptability can be estimated for the corresponding percentage of rejection commonly used in survival analysis, which is 25%. For Uruguay the corresponding acceptability value is 5.9, whereas for Spain the corresponding acceptability value is 5.1. Consumers in each country behave differently. Spanish consumers assign lower
Table 3 Shelf life values estimated for a 25% consumer rejection for breads of both countries Country
Formulation
Shelf life (days) ± 95% confidence interval
Spain
Control Amylase Xylanase Amylase/xylanase
8±2 11 ± 3 5±2 11 ± 2
Control Amylase Xylanase Amylase/xylanase
10 ± 2 12 ± 2 8±3 16 ± 2
Uruguay
Formulation
Rejection time distribution
Spain
Amylase–control Amylase–xylanase Amylase–amylase/xylanase Control–xylanase Control–amylase/xylanase Amylase/xylanase–xylanase
*
NS: no significant difference. * Significant difference (p < 0.05). ** Significant difference (p < 0.01).
4. Conclusions Evaluation of the shelf life of brown pan bread manufactured with different enzymes systems from a consumer standpoint was studied, providing information useful to the manufacturers regarding formulation of this type of product. For Uruguayan consumers the mixture of enzymes provided better results to bread than the addition of amylase alone, extending the shelf life of the product. For Spanish consumers bread formulated with only the addition of amylase provided good results in extending shelf life, and in both countries the use of xylanase did not give the expected results. Of all the methodologies used to estimate the shelf life of bread, survival analysis provided the most adequate predictions considering consumer rejection of the product. Even though hedonic scales could be used to estimate product shelf life, they do not always reflect consumer behaviour when deciding whether to accept or reject a certain product for its consumption. Spanish consumers showed a tendency to decrease their overall acceptability scores while accepting the product to its consumption. In this work shelf lives estimated using the failure cut-off methodology were too conservative as to be used by manufacturers.
The authors are indebted to CYTED (Proyecto XI.16. Subprograma XI: Tratamiento y Conservacio´n de Alimentos) and to the Comisio´n Interministerial de Ciencia y Tecnologı´a for financial support (Project AGL 200309208-C03-02).
Country
Amylase–control Amylase–xylanase Amylase–amylase/xylanase Control–xylanase Control–amylase/xylanase Amylase/xylanase–xylanase
acceptability scores when rejecting the product than Uruguayan consumers; therefore, caution should be taken when making decisions regarding shelf life based on hedonic scores.
Acknowledgements
Table 4 Comparison between different bread formulations by rejection time distribution
Uruguay
203
**
NS NS NS **
NS NS **
NS ** **
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Courtin, C. W., & Delcour, J. A. (2002). Arabinoxylans and endoxylanases in wheat flour bread-making. Journal of Cereal Science, 35, 225–243. Dura´n, E., Barber, B., & Benedito de Barber, C. (1995). Low molecular weight dextrins content in bread crumb as related to bread staling. Proceedings of EuroFood Chem, 2, 324–328. Gacula, M. C. Jr., (1975). The design of experiments for shelf life study. Journal of Food Science, 40, 399–403. Gacula, M. C., Jr., & Kubala, J. J. (1975). Statistical models for shelf-life failures. Journal of Food Science, 40(2), 404–409. Gacula, M. C., Jr., & Singh, J. (1984). Statistical methods in food and consumers research. New York: Academic Press, 505pp. Ga´mbaro, A., Fiszman, S., Gime´nez, A., Varela, P., & Salvador, A. (2004). Consumer acceptability compared with sensory and instrumental measures of white pan bread: sensory shelf-life estimation by survival ana´lisis. Journal of Food Science, 69(9), 401–405. Ga´mbaro, A., Gime´nez, A., Varela, P., Garitta, L., & Hough, G. (2005). Sensory shelf-life estimation of alfajor by survival analysis. Journal of Sensory Studies, 19, 500–509. Gray, J. A., & Bemiller, J. N. (2003). Bread Staling: Molecular basis and control. Comprehensive Reviews in Food Science and Food Safety, 2, 1–21. Haarasilta, S., Pullinen, T., Vaiasanen, S., & TammersaloKarsten, I. (1989). Enzyme product and method of improving the properties of dough and the quality of bread. United States Patent 4,990,343. Harada, O. (2000). Effects of commercial hydrolytic enzyme additives on Canadian short process bread properties and processing characteristics. Cereal Chemistry, 77(1), 70–76. Hough, G., Langohr, K., Go´mez, G., & Curia, A. (2003). Survival analysis applied to sensory shelf life of foods. Journal of Food Science, 68, 359–362.
Hough, G., Sa´nchez, R. H., Garbarini de Pablo, G., Sa´nchez, R. G., Caldero´n Villaplana, S., Gime´nez, A. M., et al. (2002). Consumer acceptability versus trained sensory panel scores of powdered milk shelf-life defects. Journal of Dairy Science, 85(9), 1–6. ISO (1988). Sensory analysis. General guidance for the design of test rooms. ISO 8589:1988, Geneva, Switzerland. Klein, J. P., & Moeschberger, M. L. (1997). Survival analysis, a self learning text. New York: Springer-Verlag. Kulp, K. (1993). Enzymes as dough improver. In B. S. Kamel & C. E. Stauffer (Eds.), Advances in baking technology (pp. 153–178). London, UK: Blackie Academic & Professional. Lindsay, J. K. (1998). A study of interval censoring in parametric regression models. Lifetime Data Analysis, 4, 329–354. Martin, M. L., & Hoseney, R. C. (1991). A mechanism of bread firming. II. Role of starch hydrolysing enzymes. Cereal Chemistry, 68, 503– 507. Mun˜oz, A. M., Civille, V. G., & Carr, B. T. (1992). Sensory evaluation in quality control. Reinhold USA: Van Mostrand. Qi Si, J. (1997). Synergistic effect of enzymes for breadmaking. Cereal Foods World, 42, 802–807. Ramı´rez, G., Hough, G., & Contarini, A. (2001). Influence of temperature and light exposure on sensory shelf life of a commercial sunflower oil. Journal of Food Quality, 24, 195–204. Sato, N., Sato, M., & Nagashima, A. (1991). Effect of an enzyme preparation containing pentosanasas on the breadmaking quality of flours in relation to changes in pentosan properties. Journal of Cereal Science, 19, 259–272. Van Eijk, J. H., & Hille, J. D. R. (1996). Nonamylolitic enzymes. In R. E. Hebeda & H. Zobel (Eds.), Beked Goods Freshness (pp. 131–150). New York: Marcel Dekker.
Shelf life estimation of brown pan bread: A consumer approach Ana Gime´nez a
a,* ,
Paula Varela b, Ana Salvador b, Gasto´n Ares a, Susana Fiszman b, Lorena Garitta c
Seccio´n Evaluacio´n Sensorial, Ca´tedra de Ciencia y Tecnologı´a de Alimentos, Facultad de Quı´mica, Av. General Flores 2124, Montevideo C.P. 11800, Uruguay b Instituto de Agroquı´mica y Tecnologı´a de Alimentos (CSIC), Apartado de Correo 73, Burjassot, Valencia, Spain c Instituto Superior Experimental de Tecnologı´a Alimentaria, H. Irigoyen 931, 6500 Nueve de Julio, Buenos Aires, Argentina Received 25 April 2005; received in revised form 17 August 2005; accepted 28 September 2005 Available online 9 November 2005
Abstract In this study three different approaches—acceptability limit, failure cut-off point methodology, and survival analysis—to estimate the sensory shelf life of brown pan bread elaborated with different enzymes using consumer data were compared. The study was carried out in Spain and Uruguay independently, where four batches of bread were produced, with the same base formulation, one without enzyme, the others with the addition of maltogenic amylase, xylanase, and a mixture of both. The results showed that for Uruguayan consumers the mixture of enzymes provided better results in extending shelf life than the addition of amylase alone. For the Spanish consumers only the addition of amylase provided the desired results, and for consumers of both countries the use of xylanase did not extend the shelf life of bread. Among the methodologies used for the estimation, survival analysis provided the most adequate predictions considering consumer rejection of the product. Hedonic scales do not always reflect consumer behaviour when deciding whether to accept or reject a certain product for its consumption. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Brown pan bread; Enzymes; Shelf life; Survival analysis; Cut-off point methodology; Acceptability
1. Introduction Bread staling is responsible for important economical losses to both the baking industry and the consumer. Although it has been extensively studied, it remains unsolved. Staling is a general term that describes the time-dependent loss in quality of flavour and texture of bread. Bread staling is a complex phenomenon in which multiple mechanisms operate (Gray & Bemiller, 2003). The use of enzymes in the baking industry is mainly concerned with retarding this phenomenon and extending bread sensory quality throughout its shelf life, by acting on major functional flour components (Armero & Collar, 1998; Collar & Armero, 1996). The most useful enzymatic *
Corresponding author. Tel.: +598 2924 5735; fax: +598 2924 1906. E-mail address: [email protected] (A. Gime´nez).
0950-3293/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodqual.2005.09.017
approach to staling rate reduction has been the use of alpha-amylases, which catalyse a small amount of hydrolysis of starch keeping bread freshness for a longer period of time. Non-amylolytic enzymes may also be active in the enzyme supplements although it is unclear whether enzymes that degrade non-starch polysaccharides in bread have any effect on bread staling (Van Eijk & Hille, 1996). Xylanases hydrolyze pentosans present in wheat flour, accelerating the baking of bread by helping to break down polysaccharides in dough (Courtin & Delcour, 2002; Kulp, 1993). While Harada (2000) states that the use of these enzymes extends shelf life of bread by retarding starch retrogradation, Bollaı´n, Agioloni, and Collar (2005) reported that xylanase promotes an increase in bread firmness with storage time. Some synergistic effects of enzymes for dough conditioning and in extension of shelf life have been studied for specific breadmaking processes (Collar, Andreu, &
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Martı´nez-Anaya, 1998; Collar, Martı´nez, Andreu, & Armero, 2000; Haarasilta, Pullinen, Vaiasanen, & TammersaloKarsten, 1989; Qi Si, 1997; Sato, Sato, & Nagashima, 1991). Bollaı´n et al. (2005) have also reported that the joint addition of xylanase and amylase improves bread quality. Food products do not have sensory shelf lives of their own; rather they will depend on the interaction of the food with the consumer. For this reason consumers are the most appropriate tool for determining food product sensory shelf life (Hough, Langohr, Go´mez, & Curia, 2003). Different methodologies could be used to determine the shelf life of a food product, using consumer data. In the failure cut-off point methodology, shelf life is determined as the time when the first significant change in overall acceptability is detected. At this time, consumers detect a change in the sensory characteristics of the product with respect to the fresh product. However, this does not mean that consumers would refuse to consume the product. Sensory shelf life could also be determined as the time required for the overall acceptability scores of the product to fall below a certain predetermined value, for example a value of 6.0 in a 9-point structured hedonic scale (Mun˜oz, Civille, & Carr, 1992). However, this methodology provides little information as to what consumers would normally do when facing the product. In order to estimate sensory shelf life based on consumer rejection of a food product, survival analysis could be applied. This methodology focuses the shelf life risk on the consumers rejection of the product. Survival analysis has been used to estimate shelf life of some baked products (Ga´mbaro, Fiszman, Gime´nez, Varela, & Salvador, 2004; Ga´mbaro, Gime´nez, Varela, Garitta, & Hough, 2005), estimating the product shelf life as the time necessary to reach a fixed percentage of consumer rejection. Comparison of failure criteria among consumers from different countries would help to determine shelf life with a more appropriate perspective (Hough et al., 2002). The objectives of the present work were: (a) To compare shelf life of brown pan bread manufactured with amylase, xylanase and a mixture of both in two different countries, using consumer data. (b) To compare the suitability of different methodologies currently used to estimate sensory shelf life of this type of product: acceptability limit, failure cut-off point methodology, and survival analysis.
2. Materials and methods 2.1. Enzymes Maltogenic amylase from Bacillus stearothermophilus of intermediate thermo stability in granulate form (Novamyl 10000 BG, 10000 MANU/g) and xylanase from Thermomyces lanuginosus in granulate form (Pentopan Mono
197
BG, 2500 FXU/g), both from Novo Nordisk A/S, Denmark. 2.2. Samples The study was carried out independently in Spain and Uruguay. Four batches of bread were manufactured in each country, all having the same formulation but differing on the type of enzyme used. One batch was manufactured without the addition of enzymes (control); one with the addition of amylase, one with xylanase, and a fourth one with a 1:1 mixture of amylase/xylanase. The amounts of enzymes used in each country were selected according to the flour employed in their manufacture. The quantities were: 30 mg/100 g of flour of xylanase in both countries, 30 mg/100 g of flour of maltogenic amylase in Uruguay and 7.5 mg/100 g of flour of amylase in Spain. The addition of maltogenic amylase was based on the measure of native amylolitic activity of flour for each country. The ingredients used for the manufacture of bread were those currently used in each country (mentioned in order of quantity; Spain: water, wheat flour, wheat bran, sugar, vegetal hydrogenated oil, yeast, acetic acid, salt, dried whey, calcium propionate. Uruguay: water, wheat flour, whole wheat flour, wheat bran, corn syrup, gluten, yeast, salt, powdered skimmed milk, vegetable hydrogenated oil, honey, diacetyltartaric acid esters of mono and diglycerides of fatty acids, and calcium propionate). In Uruguay breads were industrially manufactured (Walter M. Doldan y Cia. SA, Montevideo, Uruguay) especially for the experiments; in Spain they were manufactured in a pilot plant at the Instituto de Agroquı´mica y Tecnologı´a de Alimentos, Valencia. In both countries (Spain/Uruguay), the manufacturing process consisted of making a sponge with half the flour, half the water, and yeast, followed by mixing (10 min/ 5 min), intermediate fermenting (2 h at 28 °C, 20 h at 5 °C and 1.5 h at 28 °C/3 h at 26 °C) before being added to the dough. All the ingredients were then mixed (60 rpm, 14 min/60 rpm, 12 min) until optimum dough consistency was reached. The fermented doughs were obtained by bulk fermentation (30 min/1 h), division (600 g/500 g), rounding, resting (10 min/5 min), panning and 1 h fermentation to maximum volume (1 h, 28 °C, 85%RH/1 h, 35 °C, 85%RH). Fermented dough was baked at 180 °C for 20 min (tray oven/continuous industrial oven), breads were then cooled for 2 h, sliced (12 mm slices/20 mm slices), and packaged in polyethylene bags. Breads were stored in a temperature-controlled storage room at 20 °C (in Spain for 0, 4, 7, 10, 13, 16, and 20 days, and in Uruguay for 1, 4, 7, 10, 13, 15 and 17 days). After reaching the desired storage times, breads were frozen at 20 °C and stored at 18 °C, providing samples with different storage times from one batch for each formulation (Gacula & Kubala, 1975). The samples were defrosted at 20 °C for 6 h, for its evaluation.
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When samples reached each of the desired storage times, microbiological analysis (aerobic mesophiles, coliforms, yeasts and molds) were performed in both countries prior to freezing. These analyses showed that samples stored for the longest times in each country were fit for human consumption. 2.3. Consumer study
A regression was carried out considering ‘‘% of acceptance’’ (calculated as the proportion of consumers who accepted the sample, that answered ‘‘yes’’ to the question ‘‘would you normally consume this product?’’) as dependent variable, and consumers ‘‘overall acceptability’’ (averaged over consumers) as explanatory variable. The following equations were tested using linear and non-linear regression: Linear : % of acceptance ¼ a þ b A
People who consumed brown pan bread at least once a week were recruited for each country from the cities of Montevideo, Uruguay and Valencia, Spain. In each country, 50 consumers, ages ranging between 18 and 50, evaluated bread samples. The testing was carried out in four sessions. In each session the consumers received the seven samples corresponding to the seven storage times of each of the four batches, using a balanced complete block design. For each sample they had to score overall acceptability of the product using a 9-box scale labelled on the left with ‘‘dislike very much’’, in the middle with ‘‘indifferent’’ and on the right with ‘‘like very much’’. They also answered the question ‘‘Would you normally consume this product?’’ with a yes or a no (evaluation sheet shown in Fig. 1). It was explained that this meant that if they bought the product or it was served to them, whether they would consume it or not. The testing was carried out in both countries in sensory laboratories that were designed in accordance with ISO 8589:1988.
Exponential: % of acceptance ¼ a þ b cA b Logistic: % of acceptance ¼ a þ 1 þ ecðAdÞ where A is overall consumer acceptability, and a, b, c, d are the regression constants. All these analysis were performed using Genstat 5 Release 3.2 (Lawes Agricultural Trust, Rothamsted).
2.4. Statistical analysis
2.4.1. Failure cut-off point methodology In this methodology shelf life is estimated considering as failure point the first significant difference in overall acceptability. This point could be calculated using the following equation (Hough et al., 2002): rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 MSE S ¼ F Za ð1Þ n where S = minimum tolerable acceptability of stored sample; F = acceptability of fresh sample; Za = one-tailed coordinate of the normal curve for a significance level; MSE = mean square of the error derived from the analysis of variance of the consumer data; n = number of consumers.
A two factor (storage time and type of enzyme) analysis of variance for all samples was performed on the overall acceptability data obtained. Mean rating and Fishers Least Significant Difference for each term were calculated.
2.4.2. Survival analysis Survival analysis methodology was used to estimate the shelf life of the four formulations of brown bread of the two countries using the results obtained from consumers
EVALUATION SHEET INSTRUCTIONS: ♦ You will evaluate 5 samples of BROWN PAN BREAD. ♦ Please try the first sample. ♦ Score the OVERALL ACCEPTABILITY of the sample using the scale and answer the question. ♦ Continue with the other samples. SAMPLE No___
Dislike very much
Indifferent
Like very much
Would you normally consume this product? Yes
No
THANK YOU VERY MUCH
Fig. 1. Evaluation sheet.
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when asked if they would normally consume the samples (Hough et al., 2003). The key concept of this methodology is to focus the shelf life hazard on the consumer rejecting the product. Defining a random variable T as the storage time at which the consumer rejects the sample, the survival function S(t) can be defined as the probability of a consumer accepting a product beyond time t, that is S(t) = P(T > t). Alternatively, the cumulative distribution function F(t) can be defined as the probability of a consumer rejecting a product before time t, that is F(t) = P(T 6 t). Because of the discrete nature of the storage times, T will never be observed exactly, hence the censored nature of the data (Hough et al., 2003). Suppose that consumers are presented with samples stored at times a, b and c. If a consumer rejects the sample at the first storage time observed, then T 6 a and the data is left-censored. If a consumer accepts the sample stored at time a, but rejects the sample stored at time b, then a < T 6 b and the data is interval-censored. Finally, if a consumer accepts all samples, then T > c and the data is right-censored. The likelihood function, which is used to estimate the survival function, is the joint probability of the given observations of the n consumers (Klein & Moeschberger, 1997) Y Y Y L¼ Sðri Þ ð1 Sðli ÞÞ ðSðli Þ Sðri ÞÞ ð2Þ i2R
i2L
i2I
where R is the set of right-censored observations, L is the set of left-censored observations and I is the set of interval-censored observations. A parametric model can be used to estimate the survival function and other quantities of interest. Choosing a lognormal distribution for T (Klein & Moeschberger, 1997; Lindsay, 1998), the rejection function is given by lnðtÞ l SðtÞ ¼ 1 U ð3Þ r where U( Æ ) is the standard normal cumulative distribution function, and l (location parameter) and r (shape parameter) are the models parameters. The parameters of the model are obtained by maximizing the likelihood function (Eq. (2)). The likelihood function is a mathematical expression that describes the joint probability of obtaining the data actually observed on the subjects in the study as a function of the unknown parameters of the model being considered. To estimate l and r for the log-normal distribution, the likelihood function is maximized by replacing S(t) in Eq. (2) with the expression given in Eq. (3). Once the likelihood function has been established for a given model, specialized software can be used to estimate the parameters (l and r) that maximize the likelihood function for the given experimental data. To estimate shelf life, the probability of a consumer rejecting a product (that is, F(t)) must be chosen. Gacula and Singh (1984) mentioned a nominal shelf life value considering 50% rejection, and Cardelli and Labuza (2001)
199
used this criterion in calculating shelf life of coffee. Ga´mbaro et al. (2004), and Ga´mbaro et al. (2005) used 25% rejection to estimate the shelf life of baked products. In the present study, in order to be conservative and assure product quality, shelf life was calculated for F(t) = 25%. This means that if a consumer tries the product at the end of its shelf life, there is a 25% probability that he will reject it. Considering that few consumers will taste the product near the end of its shelf life, and that of the few that do 75% will still find the product acceptable, this value of F(t) = 25% is considered reasonable from a practical point of view. For the Uruguayan and Spanish breads, in order to establish if the enzyme addition influenced rejection times, the following log linear regression model with inclusion of indicator variables was applied (Klein & Moeschberger, 1997) lnðT Þ ¼ l þ r W ¼ b0 þ b1 Z 1 þ r W
ð4Þ
where T is the storage time at which a consumer rejects a sample; b0, b1 are the regression coefficients; Zi is the indicator variable indicating the type of enzyme: Z1 = 1 for control, Z1 = 0 otherwise; Z2 = 1 for amylase, Z2 = 0 otherwise, Z3 = 1 for xylanase, Z3 = 0 otherwise, Z4 = 1 amylase/xylanase; Z4 = 0 otherwise; r is the shape parameter, which does not depend on the indicator variable; W is the error distribution. Calculations were performed using procedures from S-PLUS statistical software (Insightful Corp., Seattle, Washington, USA). A 5% significance level was considered. 3. Results and discussion 3.1. Consumer acceptability Consumers were asked to score bread samples with different storage times on overall acceptability hedonic scales. Figs. 2 and 3 show average scores for Spanish and Uruguayan bread samples, respectively. ANOVA results showed that for both countries, acceptability significantly decreased with storage time (p < 0.001), as expected. For Spanish consumers, control bread overall acceptability decreased during the first week, but then remained constant until the end of the study. For Uruguayan consumers, overall acceptability also decreased during the first week, remained constant till day 13 and then decreased till the end of the tested time for control bread. Furthermore, enzyme addition significantly (p < 0.001) affected consumer acceptability. A significant (p < 0.001) interaction between the two factors (storage time and type of enzyme) was found for both countries. For Spanish consumers, the addition of amylase significantly (p < 0.05) increased overall acceptability from day 13 of storage, amylase/xylanase significantly (p < 0.05) increased acceptability between days 10 and 13 of storage, when compared to control bread, whereas xylanase significantly (p < 0.05)
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200 9.0
Control 8.0
Amylase Xylanase
Acceptability
7.0
Amylase:Xylanase
6.0 5.0 4.0
3.0 2.0 1.0 1
3
5
7
9
11
13
15
17
19
21
Time (days)
Fig. 2. Consumer overall acceptability versus storage time for Spanish breads (mean ± standard deviation).
9.0 Control Amylase
8.0
Xylanase Amylase:Xylanase
7.0
Acceptability
6.0
5.0
4.0
3.0
2.0
1.0 1
3
5
7
9
11
13
15
17
Time (days)
Fig. 3. Consumer overall acceptability versus storage time for Uruguayan breads (mean ± standard deviation).
decreased it from day 10 of storage. For Uruguayans, bread formulated with amylase/xylanase significantly (p < 0.05) increased overall acceptability from day 7, when compared to control bread. The addition of amylase significantly (p < 0.05) increased acceptability from day 10 of storage. However, xylanase did not significantly affect acceptability with respect to control bread. Bread staling, usually associated to an increase in crumb firmness, is responsible for the decrease of consumer acceptance with storage time. These results are in agreement with the
reports that suggest that the use of amylase or amylase/ xylanase decreased the staling rate (Bollaı´n et al., 2005; Dura´n, Barber, & Benedito de Barber, 1995; Martin & Hoseney, 1991). However, Spanish consumers appeared to score low values also for breads supplemented with xylanase alone as previously reported. Acceptability scores could be related to percent consumer rejection. A regression analysis was carried out considering the proportion of consumers who accepted the sample as dependent variable, and consumer overall
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acceptability as explanatory variable. In both countries the logistic regression gave the best fit (r2 = 0.77 and r2 = 0.84 for Uruguayan and Spanish data, respectively). The equations for each country are Uruguay: % of acceptance 0:716 ¼ 0:352 þ 1 þ e1:531ðA5:761Þ 1:6 Spain: % of acceptance ¼ 1:088 1 þ e0:73ðA3:3Þ
ð5Þ ð6Þ
where A = overall acceptability. Consumer rejection percent could then be calculated from these equations as (100% of acceptance). 3.2. Shelf life estimation: comparison of different failure criteria 3.2.1. Acceptability limit Mun˜oz et al. (1992) considered an acceptability score of 6.0 in a 9-point hedonic scale as commercial or quality limit. By using this acceptability score as failure criterion to estimate shelf life with Eq. (5), consumer rejection percent for this score would be 23% for Uruguayan consumers. Performing a linear regression on acceptability scores versus storage time (Gacula, 1975), shelf life could be estimated as the storage time when acceptability reaches a value of 6.0. Table 1 shows estimated shelf life with its confidence intervals for each bread formulation. The use of amylase/xylanase significantly increased shelf life of Uruguayan bread, whereas shelf lives of all other formulations did not show significant differences with respect to the shelf life of the control bread formulation. This acceptability limit was too strict a criterion for Spanish consumers of this product. Consumer rejection percent for a score of 6 calculated applying Eq. (6) would be 11% for Spanish consumers; since this value is too low, this criterion could only be applied to Uruguayan breads. Therefore, consumers in both countries behaved differently. Spanish consumers showed a tendency to decrease their overall acceptability scores while deciding to accept the product. This suggests that shelf life decisions based on an arbitrary acceptability limit might be taken with caution as they do not always reflect consumers decision to accept or reject the product.
Table 1 Shelf life for Uruguayan bread estimated using consumer acceptability score limit of 6.0 Formulation
Shelf life (days) ± 95% confidence intervals
Control Amylase Xylanase Amylase/xylanase
9±3 11 ± 4 8±4 17 ± 4
201
3.2.2. Failure cut-off point methodology The sensory failure cut-off point methodology (Hough et al., 2002; Ramı´rez, Hough, & Contarini, 2001) provided high values for the minimum tolerable acceptability, ranging from 6.4 to 6.9 for all samples in both countries. Thus, shelf life of samples would range from 1 to 5 days. As stated earlier, since this methodology reflects the time when consumers noticed the first significant difference in the sensory characteristics of the product with respect to the fresh one, estimated shelf lives were too short. It would be too conservative a criterion to be used by the product manufacturer. Therefore, it is obvious that for the products considered in the present study, this methodology does not apply. 3.2.3. Survival analysis Visual assessment of how parametric models adjust to the non-parametric estimation was used to choose the most adequate model (Hough et al., 2003). For the present data, the following standard distributions were compared: smallest extreme value, normal, logistic, Weibull, log-normal and log-logistic. The log-normal distribution adjusted best for all bread formulations. Therefore, it was chosen to model rejection times for the present data. The maximum likelihood estimates of the parameters of the log-normal distribution for each bread formulation, that is applying Eq. (3) with no indicator variables, is shown in Table 2. The influence of indicator variables is analyzed separately. These parameters can be used to graph percent of consumer rejection versus storage time of each bread formulation as shown in Figs. 4 and 5. These graphs can be used to estimate the shelf lives values (x-axis) with their confidence intervals by entering with a 25% consumer rejection (y-axis), as shown in Table 3. For a 25% of consumer rejection, shelf lives estimated ranged from 5 to 11 days for the different formulations of Spanish bread, and from 8 to 16 days for Uruguayan ones. It is worth pointing out that manufacturers give this type of product a shelf life of 13 days in both countries, regardless of their formulation or manufacturing practices. Consumer rejection percent for control bread at day 13 was 50.3% for Spanish consumers and 42.0% for Uruguayan consumers. Therefore, setting the shelf life of bread to 13 Table 2 Values of log-normal distribution parameters l (location parameter) and r (shape parameter) and their confidence intervals for the failure function for breads of both countries Country
Sample
l ± standard error
r ± standard error
Spain
Control Amylase Xylanase Amylase/xylanase
2.55 ± 0.12 3.00 ± 0.18 2.19 ± 0.16 2.76 ± 0.11
0.69 ± 0.12 0.86 ± 0.18 0.92 ± 0.16 0.55 ± 0.11
Uruguay
Control Amylase Xylanase Amylase/xylanase
2.68 ± 0.10 2.76 ± 0.07 2.79 ± 0.21 3.04 ± 0.11
0.59 ± 0.11 0.41 ± 0.08 1.12 ± 0.24 0.36 ± 0.13
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202 90
Control Amylase Xylanase Amylase:Xylanase
80
Consumer rejection (%)
70
60
50
40
30
20
10
0 0
5
10
15
20
Time (days)
Fig. 4. Estimation of consumer rejection percent versus storage time for Spanish breads by survival analysis.
70 Control Amylase Xylanase Amylase:Xylanase
Consumer rejection (%)
60
50
40
30
20
10
0 0
2
4
6
8
10
12
14
16
18
Time (days)
Fig. 5. Estimation of consumer rejection percent versus storage time for Uruguayan breads by survival analysis.
days, without considering their formulation would probably lead to the manufacturer receiving more complaints than expected. As shown in Table 3, shelf life of Uruguayan bread manufactured with amylase/xylanase was significantly longer than control bread. These shelf life estimations are in agreement with those estimated by using as failure criterion an acceptability score of 6.0; however, confidence bands are narrower.
Shelf lives estimated using survival analysis seemed more reasonable for manufacturers than the ones estimated using the failure cut-off point methodology for this type of product. Survival analysis estimates shelf lives based on consumer rejection, which could be related to the number of complaints manufacturers might receive when the product reaches the end of its shelf life. Therefore, shelf lives decisions based on survival analysis might be more appropriate to manufacturers.
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3.2.3.1. Influence of indicator variables. To study the influence of ‘‘the type of enzyme’’ in consumer rejection time distribution for each country, distributions for each formulation were compared to the other three. Results are shown in Table 4. For Uruguayan breads, significant differences were found between the rejection time distributions of bread manufactured with the mixture of enzymes when compared to the other three formulations. For Spanish breads, significant differences were found for rejection time distribution of bread manufactured with amylase versus xylanase, amylase versus control, and xylanase versus amylase/xylanase. Uruguayan bread formulation with amylase/xylanase had lower rejection rates than the other three formulations. Likewise, Spanish bread formulation with amylase had a lower rejection rate than control bread. Using Eqs. (5) and (6), acceptability can be estimated for the corresponding percentage of rejection commonly used in survival analysis, which is 25%. For Uruguay the corresponding acceptability value is 5.9, whereas for Spain the corresponding acceptability value is 5.1. Consumers in each country behave differently. Spanish consumers assign lower
Table 3 Shelf life values estimated for a 25% consumer rejection for breads of both countries Country
Formulation
Shelf life (days) ± 95% confidence interval
Spain
Control Amylase Xylanase Amylase/xylanase
8±2 11 ± 3 5±2 11 ± 2
Control Amylase Xylanase Amylase/xylanase
10 ± 2 12 ± 2 8±3 16 ± 2
Uruguay
Formulation
Rejection time distribution
Spain
Amylase–control Amylase–xylanase Amylase–amylase/xylanase Control–xylanase Control–amylase/xylanase Amylase/xylanase–xylanase
*
NS: no significant difference. * Significant difference (p < 0.05). ** Significant difference (p < 0.01).
4. Conclusions Evaluation of the shelf life of brown pan bread manufactured with different enzymes systems from a consumer standpoint was studied, providing information useful to the manufacturers regarding formulation of this type of product. For Uruguayan consumers the mixture of enzymes provided better results to bread than the addition of amylase alone, extending the shelf life of the product. For Spanish consumers bread formulated with only the addition of amylase provided good results in extending shelf life, and in both countries the use of xylanase did not give the expected results. Of all the methodologies used to estimate the shelf life of bread, survival analysis provided the most adequate predictions considering consumer rejection of the product. Even though hedonic scales could be used to estimate product shelf life, they do not always reflect consumer behaviour when deciding whether to accept or reject a certain product for its consumption. Spanish consumers showed a tendency to decrease their overall acceptability scores while accepting the product to its consumption. In this work shelf lives estimated using the failure cut-off methodology were too conservative as to be used by manufacturers.
The authors are indebted to CYTED (Proyecto XI.16. Subprograma XI: Tratamiento y Conservacio´n de Alimentos) and to the Comisio´n Interministerial de Ciencia y Tecnologı´a for financial support (Project AGL 200309208-C03-02).
Country
Amylase–control Amylase–xylanase Amylase–amylase/xylanase Control–xylanase Control–amylase/xylanase Amylase/xylanase–xylanase
acceptability scores when rejecting the product than Uruguayan consumers; therefore, caution should be taken when making decisions regarding shelf life based on hedonic scores.
Acknowledgements
Table 4 Comparison between different bread formulations by rejection time distribution
Uruguay
203
**
NS NS NS **
NS NS **
NS ** **
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