**4. Tests for sensory evaluation of natural beverages and their statistical analysis**

The types of tests that are used in the sensory evaluation of beverages are acceptance tests, discriminative tests, and qualitative tests. In the first two types, can be used the hedonic scale, LAM and JAR, to evaluate attributes. The qualitative tests are used for qualitative descriptive analysis (QDA) as well as to determine the taste profile using the intensity grade scale.

**Figure 1** proposes a sequence of sensory tests that are used in the development of beverages (yellow box). In the tests of acceptance, optimization, substitution of ingredients and in the market study, alternative tests are presented; Through the review of literature in this section, the reader will notice that the sensory tests have different strength to accept or discriminate a

**Figure 1.** Sequence of sensory tests that are used in the development of natural beverages.

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nine points, also can be three, five, or seven points. Acceptance tests are normally conducted with consumers; the number of participants will be based on the level of confidence that is desired for decision making. **Table 2**, presents a list of attributes commonly evaluated in natural drinks and the sensory tests used. You can call the reader's attention to the use of the attributes taste and taste as well as aroma and smell, for this reason, these qualities are pointed out here:

• Taste refers to those feelings that occur inside our mouth, including the tongue and focuses on sweet, salty, sour and bitter taste; lately umami taste has been included for deliciousness. • Aroma refers to a perfume or fragrance very nice, usually is a mixture of pleasant olfactory

• Odor is usually used for unpleasant olfactory sensations and refers to a more specific con-

• The flavor is the combination of aromatic sensations, taste and viscosity. The flavor is a

The scientists can also evaluate the persistence in the mouth of a flavor and refers to the time it takes for the stimulus to disappear from the oral cavity. Generally, it is used in wines, although with the new mixtures of juices and teas it is considered one more attribute to

The cleansing of the palate aims to eliminate a taste in the mouth to give rise to a new sensory experience. As shown in the following table, the most widely used product is unsalted cookies. This product is used to eliminate sweet, spicy, bitter or fatty tastes. Water is the ideal complement to clean the mouth. To evaluate sweet beverages as natural beverages, it is common to use this combination of products, so common that researchers do not report them in

The types of tests that are used in the sensory evaluation of beverages are acceptance tests, discriminative tests, and qualitative tests. In the first two types, can be used the hedonic scale, LAM and JAR, to evaluate attributes. The qualitative tests are used for qualitative descriptive analysis (QDA) as well as to determine the taste profile using the intensity grade scale.

**Figure 1** proposes a sequence of sensory tests that are used in the development of beverages (yellow box). In the tests of acceptance, optimization, substitution of ingredients and in the market study, alternative tests are presented; Through the review of literature in this section, the reader will notice that the sensory tests have different strength to accept or discriminate a

synthesis that makes the brain expresses a general feeling of those combinations.

• The oral sensation refers to the viscosity for example, the body of a drink.

**4. Tests for sensory evaluation of natural beverages and their** 

sensations.

evaluate.

their publications.

**statistical analysis**

cept that aroma.

78 Antioxidants in Foods and Its Applications

**Figure 1.** Sequence of sensory tests that are used in the development of natural beverages.

product; therefore, the choice of each of them will be based on the questions that you wish to answer during the process of developing the drink.

JAR scale can be used with 3 and 9 points to determine the optimal concentration of sweetness in a drink. Some authors compared these scales by analyzing the data obtained through statistical analysis of survival, followed by a regression analysis. Three different ranges of concentration of sucrose were used in orange juice. Optimum sucrose concentration was 8.2% for the nine-point scale and 13.1% for the three-point scale. A later study showed that 70% of subjects preferred the sample with 13.1% of sucrose on the sample with 8.2%. The three points of JAR scale combined with statistical analysis provided a more real optimal level concentra-

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Optimization of drinks is made through the methodology of Box and Wilson called response surface, which is a combination of the experimental design and regression analysis. It is an experimental strategy that allows you to find the optimal values of the independent variables (e.g., sugar level) that maximizes or minimizes the response variable (e.g., flavor). They used this methodology to optimize the ideal sweetness of a fermented beverage of extract of soybean to 11 g of sucrose per 100 mL and obtained predictive models of response with respect

The response surface methodology was applied to differentiate wines from different harvests by their aroma and taste by Pagliarini et al. [27]. There are few publications on this; however, these two publications illustrate the applications of the methodology in the development of beverages. The difference tests referred to in this section are presented in a comparative manner

On the other hand, when you want to substitute ingredients or compare the attributes of the new beverage against a product already on the market, the difference tests are used. There are two types: when the cause of the difference is asked, focusing on a specific attribute (2AFC and 3AFC) and when it is not asked, focusing on others (duo-trio and triangular). These tests

**Test Samples Presentation sequence Judge instruction**

2AFC Encoded as A or B AB and BA What is the sweetest

AAB ABA BAA BBA

(a) constant reference: R

(b) balanced reference: RA AB, RA BA, RB AB,

ABB, BAB, BBA, BAA, ABA and AAB

Which sample is different from the other two?

(a) select the sample similar to A

(b) select the sample similar to A or B

sample? (for example)

What is the least salty

What is the saltiest

sample?

sample?

BAB ABB

AB, R BA

RB BA

Triangular Encoded with three-digit numbers. Two samples

code. The third sample is different.

Duo-trio A sample is marked as R = reference and the other samples are marked as A or Bs

3AFC Two samples are the same and are marked with

coded in the same way

**Table 3.** Comparison between different sensorial tests.

are the same and are presented with different

three-digit codes. The third sample is the one that has the greatest strength in the attribute and is

to the ideal flavor, sweetness, and generally accepted attitude of purchase.

tion than the nine-point scale.

in the **Table 3**.

In the tests of acceptance with consumers, the hedonic scale is generally used with nine verbal categories, which represent different degrees of taste from "extremely disliked" to "extremely liked." Then the verbal categories converted to numerical values are subjected to statistical analysis. Nicolas et al. [30], wondered if the words and numbers on the hedonic scale of nine points are interchangeable? The answer found after his research was that most consumers respond differentially to scales that use "only words" or "only numbers." The percentage of consumers who give different results for "only words" or "only numbers" varied between 79 and 100%. They conclude that the numerical data derived from these two scales are not interchangeable, and if you want to compare results between them, you should be cautious.

Another scale used in consumer acceptance testing is the scale LAM (labeled affective magnitude) due to its higher discriminative power that the scale of nine points and the spacing of anchor words mainly foods or well-liked beverages [29].

A comparison between the hedonic scale of nine points and the LAM scale was made by Lawless et al. [29] in food acceptance tests and mentions that both scales behave well in the discrimination of products according to consumer tastes and reveal a strong relationship between consumption patterns and acceptance ratings. They suggest that there is no strong superiority of the LAM scale over the nine-point scale and that better scales can help to show differences between new products for the consumer preventing the type II error in which the true differences between the products were not detected.

Jae et al. [22] evaluated two species of Artemis for the elaboration of teas, through the acceptability of color and taste, salinity, bitterness, acidity, and general preference using the LAM scale. The scale ranged from 0 (greatest imaginable dislike) to 15 (greatest imaginable like). They did not find a significant difference for the evaluated attributes, except for taste acceptability and general preference and attribute the difference to the volatile compounds between the two species studied, particularly in the terpenic compounds.

When you want to optimize the level of an attribute in a product or when you want to identify attributes that need improvement, the JAR (Just About Right) scale is used. This implies that the ideal value of the attribute is equal to or very close to the value of the most liked attribute. Therefore, the products qualified as "just right" must be equivalent to the preferred or most liked products. However, the researches that used the JAR scale repeatedly report optimal values of the attributes very different from those of the products currently on the market.

Epler et al. [31] compared the hedonic scale and two types of JAR scale (boxes or lines) to optimize the degree of sweetness in lemonade. The predicted "optimal" level of sweetness for lemonade was determined, as well as differences in taste for formulations with different sugar content (6–14%). The two types of scales yielded similar results in terms of the predicted optimum value (9.2 and 9.4% sucrose), which was significantly lower than the result obtained by the hedonic scale (10.3% sucrose). In the preference test, consumers prefer lemonade with 10.3% sugar over that which contained 9.3%. These results indicate that the hedonic scale is better for predicting sweetness than the JAR scale.

JAR scale can be used with 3 and 9 points to determine the optimal concentration of sweetness in a drink. Some authors compared these scales by analyzing the data obtained through statistical analysis of survival, followed by a regression analysis. Three different ranges of concentration of sucrose were used in orange juice. Optimum sucrose concentration was 8.2% for the nine-point scale and 13.1% for the three-point scale. A later study showed that 70% of subjects preferred the sample with 13.1% of sucrose on the sample with 8.2%. The three points of JAR scale combined with statistical analysis provided a more real optimal level concentration than the nine-point scale.

Optimization of drinks is made through the methodology of Box and Wilson called response surface, which is a combination of the experimental design and regression analysis. It is an experimental strategy that allows you to find the optimal values of the independent variables (e.g., sugar level) that maximizes or minimizes the response variable (e.g., flavor). They used this methodology to optimize the ideal sweetness of a fermented beverage of extract of soybean to 11 g of sucrose per 100 mL and obtained predictive models of response with respect to the ideal flavor, sweetness, and generally accepted attitude of purchase.

The response surface methodology was applied to differentiate wines from different harvests by their aroma and taste by Pagliarini et al. [27]. There are few publications on this; however, these two publications illustrate the applications of the methodology in the development of beverages. The difference tests referred to in this section are presented in a comparative manner in the **Table 3**.

On the other hand, when you want to substitute ingredients or compare the attributes of the new beverage against a product already on the market, the difference tests are used. There are two types: when the cause of the difference is asked, focusing on a specific attribute (2AFC and 3AFC) and when it is not asked, focusing on others (duo-trio and triangular). These tests


**Table 3.** Comparison between different sensorial tests.

product; therefore, the choice of each of them will be based on the questions that you wish to

In the tests of acceptance with consumers, the hedonic scale is generally used with nine verbal categories, which represent different degrees of taste from "extremely disliked" to "extremely liked." Then the verbal categories converted to numerical values are subjected to statistical analysis. Nicolas et al. [30], wondered if the words and numbers on the hedonic scale of nine points are interchangeable? The answer found after his research was that most consumers respond differentially to scales that use "only words" or "only numbers." The percentage of consumers who give different results for "only words" or "only numbers" varied between 79 and 100%. They conclude that the numerical data derived from these two scales are not interchangeable, and if you want to compare results between them, you should be cautious. Another scale used in consumer acceptance testing is the scale LAM (labeled affective magnitude) due to its higher discriminative power that the scale of nine points and the spacing of

A comparison between the hedonic scale of nine points and the LAM scale was made by Lawless et al. [29] in food acceptance tests and mentions that both scales behave well in the discrimination of products according to consumer tastes and reveal a strong relationship between consumption patterns and acceptance ratings. They suggest that there is no strong superiority of the LAM scale over the nine-point scale and that better scales can help to show differences between new products for the consumer preventing the type II error in which the

Jae et al. [22] evaluated two species of Artemis for the elaboration of teas, through the acceptability of color and taste, salinity, bitterness, acidity, and general preference using the LAM scale. The scale ranged from 0 (greatest imaginable dislike) to 15 (greatest imaginable like). They did not find a significant difference for the evaluated attributes, except for taste acceptability and general preference and attribute the difference to the volatile compounds between

When you want to optimize the level of an attribute in a product or when you want to identify attributes that need improvement, the JAR (Just About Right) scale is used. This implies that the ideal value of the attribute is equal to or very close to the value of the most liked attribute. Therefore, the products qualified as "just right" must be equivalent to the preferred or most liked products. However, the researches that used the JAR scale repeatedly report optimal values of the attributes very different from those of the products currently on the market.

Epler et al. [31] compared the hedonic scale and two types of JAR scale (boxes or lines) to optimize the degree of sweetness in lemonade. The predicted "optimal" level of sweetness for lemonade was determined, as well as differences in taste for formulations with different sugar content (6–14%). The two types of scales yielded similar results in terms of the predicted optimum value (9.2 and 9.4% sucrose), which was significantly lower than the result obtained by the hedonic scale (10.3% sucrose). In the preference test, consumers prefer lemonade with 10.3% sugar over that which contained 9.3%. These results indicate that the hedonic scale is

answer during the process of developing the drink.

80 Antioxidants in Foods and Its Applications

anchor words mainly foods or well-liked beverages [29].

true differences between the products were not detected.

the two species studied, particularly in the terpenic compounds.

better for predicting sweetness than the JAR scale.

can work with trained judges and consumers, where the latter apply simpler tests and require more participants in order to increase the degree of reliability in the results.

**Acknowledgements**

**Conflict of interest**

**Author details**

Romeo Rojas-Molina<sup>1</sup>

Nuevo León, Mexico

Mexico

**References**

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pone.0109126

Nutrition. 2014;**65**(5):552-557

Dairy and Food Research. 2016;**35**(1):81-84

de C.V. for the facilities given to study his doctorate.

The authors have declared that there is no conflict of interest.

Saúl Saucedo-Pompa1,2, Guillermo Cristian Guadalupe Martínez-Ávila<sup>1</sup>

\*Address all correspondence to: ernesto.sanchezlj@uanl.edu.mx

and Ernesto Javier Sánchez-Alejo1

1 Facultad de Agronomía, Universidad Autónoma de Nuevo León, General Escobedo,

2 Facultad de Ciencias Químicas. Universidad Autónoma de Coahuila, Saltillo, Coahuila,

[1] Rubio-Perez JM, Vidal-Guevara ML, Zafrilla P, Morillas-Ruiz JM. A new antioxidant beverage produced with green tea and apple. International Journal of Food Sciences and

[2] Jaworska G, Grega T, Sady M, Bernaś E, Pogoń K. Quality of apple-whey and apple beverages over 12-month storage period. Journal of Food and Nutrition Research. 2014;**53**(2):

[3] Sushilkumar SM, Sawate AR, Patil BM, Kshirsagar RB, Kulkarni SP. Study on effect of custard apple leaf extract on physico-chemical properties of aonla juice. Asian Journal of

[4] Sharma S, Vaidya D, Rana N. Honey as natural sweetener in lemon ready-to-serve drink. International Journal of Bio-resource and Stress Management. 2016;**7**(2):320-325

[5] Ahmed S, Stepp JR, Orians C, Griffin T, Matyas C. Effects of extreme climate events on tea (*Camellia sinensis*) functional quality validate indigenous farmer knowledge and sensory preferences in tropical China. PLoS One. 2014;**9**(10):e109126. DOI: 10.1371/journal.

Saucedo-Pompa thanks to Jesús Noel Yáñez Reyes and Fitokimica Industrial de México S.A.

,

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\*

These tests are applied with trained judges and with consumers; the statistical method used is Chi-square. Judge fatigue can occur when repeatedly testing the samples and consequently, the adaptation to the stimulus can occur; thus six maximum samples can be evaluated in a session. The interpretation is through the use of statistical tables according to the size of the sample, minimum number of correct answers and the level of significance required. Once the new drink is ready to go on the market, it is necessary to define their sensory properties to establish a flavor profile and define the properties that have to be monitored in the quality control process. Quantitative descriptive analysis (QDA), used for those purposes in this analysis, describes the sensory attributes (no more than seven) of products such as flavor, mouthfeel, aftertaste, and appearances through 10–12 trained judges. The objective of the QDA is to provide a quantitative specification of the sensory attributes of a product as well as to determine the nature and intensity of these.

Beverages are evaluated by the intensity of their attributes crossing the level of intensity found on a vertical line. These distances are converted into numerical values that will be analyzed by means of an ANOVA.

Hruškar et al. [26] evaluated nectars through quantitative descriptive analysis and generated ten descriptive terms related to color, smell, taste, consistency, and overall sensory impression. The analysis of variance showed significant differences in the color intensity, taste sour and sweet intensity, as well as for the overall sensory impression. There were no significant differences in the addition of sugar and acid.

The analysis of main components (PCA) is used to study the positioning of the beverage on the market. It uses the sensory attributes of beverage such as flavor, color, aroma, and body. This descriptive technique allows the study of the sensory attributes quantitatively through the correlation between them and calculates new variables by grouping attributes in such a way that it is possible to observe in a plane the distance between groups of attributes and define which product is better positioned to the consumer and in consequence on the market.
