**6.4 Sensory analysis: pros and contras**

The sensory analysis represents the human response to wine tasting. A sensory panel can provide information about the sensory properties of a product, but significant training is required before the panel becomes a reliable sensory instrument. Astringency is a difficult sensory attribute to evaluate, owing to particular

characteristics of the sensation. Generally, it is evaluated by tasting but can suffer from individual subjectivity. The feeling can take over 15 seconds to develop fully and is known to build in intensity and become increasingly difficult to clear from the mouth over repeated exposures [19, 154]. Carry-over effects can occur. When wines or tannic solutions are evaluated by a well-trained panel using established sensory methodologies, the panel leader can expect to obtain reliable information about the intensity in the perceived astringency of the samples. Screening, selection, training, and panel maintenance are exercises that help the panel attain proficiency before sample evaluation. Classical methodologies widely applied are descriptive and rating sensory analyses. The first helps to distinguish between samples by a qualitative description of their sensory properties [75] and the second permits to scale samples according to the intensity of the perception. However, time-intensity (TI) is a temporal methodology widely used. This method consists of recording one by one the intensity evolution of given attributes [155]. However, TI showed some limitations because it is time-consuming due to the evaluation of only a few attributes at the same time [156]. Furthermore, carry-over effects can overcome when assessing the temporal perception of an attribute [157]. To overcome these drawbacks, Pineau et al. [156] developed a new method called temporal dominance of sensations (TDS), which consists of identifying and rating sensations perceived as dominant until the perception ends. Before the development of this method, a similar experimental approach was successfully used to describe the temporality of sensations in wines [158]. Astringency, a dynamic sensation, takes many seconds to develop after the basic tastes, and the duration depends on the wine. Notwithstanding, TDS can be difficult when panellists had select the dominant attribute and score its intensity, but proper training can overcome this problem [159].

It is also essential to discuss and familiarise with the terms associated with astringency. A vocabulary of 33 terms has been proposed by a combined panel of experienced tasters and winemakers to describe the mouthfeel characteristics of red wines [160]. The check-all-that-apply (CATA) question that consists of a list of subqualities from which the panellists have to select all the options they consider appropriate to that wine has been utilised for the characterisation of the astringency subqualities of Tannat wine [161]. Recently, a sensory method that combines CATA approach and training in astringency subqualities with touch-standards resulted very useful for investigating the astringency characteristics of red wines [24, 25, 162]. In any case, intense training is necessary to distinguish astringency from other tastes, especially bitterness, and to reveal the different qualitative attributes. Fatigue and loss of *stimuli* memory may occur, particularly with panellists who are unfamiliar with astringency, and when too many samples are presented. Training is also expensive and time-consuming. However, it is necessary to investigate the astringency subqualities of red wines. Sensory analysis is of fundamental importance, but in some cases, it is not possible to perform, so the replacement with an analytical instrument able to measure astringency could help in research as well as in the winery.

#### **6.5 Correlation between sensory and analytical analysis**

Because astringency is one of the main attributes for wine quality, winemakers are interested in an analytical and objective method to evaluate it. No method can substitute entirely sensory analysis, but a method that results in a reproducible index has to correlate quite well with it. A statistically significant correlation between the sensorial and analytical methods is necessary.

The gelatin index has represented the almost widely analytical method for estimating astringency in red wine [136]. Besides, it furnished only approximate results [137]. Successively, a positive correlation (R2 = 0.56) between the gelatin index and

**155**

quality of red wines.

*Salivary Protein-Tannin Interaction: The Binding behind Astringency*

time-intensity data was obtained only at a low concentration of polyphenols utilising 29 wines judged by 10 panellists [163]. A method that used the ovalbumin in alternatively to gelatin as a precipitation agent was proposed to determine astringency [137]. Ten wines were tested by 10 expert enologists evaluating the astringency on a scale from 1 to 100. The method resulted in more reproducible than the gelatin index and was positively correlated (R2 = 0.77) with sensory analysis. This method was also used to assess the astringency of Greek wines, and a good correlation was found (R2 = 0.93) [164]. Another predictive model for astringency estimation was based on phenolic compounds and colour analysis of 34 wines by 12 judges on a 9-point intensity scale [165]. Multiple regression generated three possible models to predict astringency from analytical data, the most simple depended on total phenolics and co-pigmented anthocyanins, besides the predicted astringency plotted versus observed astringency resulted in low but acceptable correlation from

Monteleone et al. [150] proposed a predictive model by measuring the polyphenol-mucin reactivity in which the capability of polyphenolic extracts to induce astringency was estimated on their ability to develop turbidity in the *in vitro* assay. They found a linear relation between astringency perceived by 30 trained judges and the mucin index for tannic acid model solutions (R2 = 0.993) grape seed

In a study by Kennedy et al. [166], 40 red wines were evaluated by a panel consisting of three winemakers and two enologists for the astringency intensity scored from zero to 10. The aim was to correlate astringency and tannin concentration measured by different analytical methods: absorption at 280 nm, phloroglucinolysis, gel chromatography, and BSA protein precipitation. The analytical method having the strongest correlations with perceived astringency was the protein precipitation one (R2 = 0.82). Protein precipitation represents the method the most similar to the physiological response to astringent *stimuli* and can be used as an *in vitro* tool for understanding how tannin can modulate astringency perception. Generally, it was assumed that the most suitable proteins for evaluating astringency are the salivary PRPs. However, other proteins in whole human saliva were preferentially precipitated by increasing tannin solutions [142]. Successively, the percentage decrease of two salivary proteins after the precipitation with tannins, measured by electrophoresis, represented an indicator of the reactivity of tannin. The saliva precipitation index (SPI) was well correlated with the sensory evaluation of the astringency of 57 red wines (R2 = 0.97) made by 18

The SPI represents a useful tool to assess the physiological response to astringents, measuring the astringency of red wine indirectly. This index evaluated the precipitation of salivary proteins occurring during the tasting of an astringent stimulus. The SPI, analysing the salivary protein pattern by SDS-PAGE electrophoresis, has been improved considering the in-mouth temperature (37°C) for the binding reaction, the choice of resting saliva, and the ratio saliva:wine. The excess of saliva with respect to wine (2:1) in a static environment permits to measure the binding capacity of tannins better [167]. Successively, to reduce the time and solvents, the chip electrophoresis replaced the SDS-PAGE, providing similar results [168]. In the last years, the SPI has been used for different technological practices proving useful information for winemakers and enologists to manage the style and

extracts (R2 = 0.996), and phenolic extracts (R2 = 0.95) [63].

*DOI: http://dx.doi.org/10.5772/intechopen.93611*

a sensory perspective.

trained assessors [167].

**7. The saliva precipitation index (SPI)**

### *Salivary Protein-Tannin Interaction: The Binding behind Astringency DOI: http://dx.doi.org/10.5772/intechopen.93611*

*Chemistry and Biochemistry of Winemaking, Wine Stabilization and Aging*

proper training can overcome this problem [159].

characteristics of the sensation. Generally, it is evaluated by tasting but can suffer from individual subjectivity. The feeling can take over 15 seconds to develop fully and is known to build in intensity and become increasingly difficult to clear from the mouth over repeated exposures [19, 154]. Carry-over effects can occur. When wines or tannic solutions are evaluated by a well-trained panel using established sensory methodologies, the panel leader can expect to obtain reliable information about the intensity in the perceived astringency of the samples. Screening, selection, training, and panel maintenance are exercises that help the panel attain proficiency before sample evaluation. Classical methodologies widely applied are descriptive and rating sensory analyses. The first helps to distinguish between samples by a qualitative description of their sensory properties [75] and the second permits to scale samples according to the intensity of the perception. However, time-intensity (TI) is a temporal methodology widely used. This method consists of recording one by one the intensity evolution of given attributes [155]. However, TI showed some limitations because it is time-consuming due to the evaluation of only a few attributes at the same time [156]. Furthermore, carry-over effects can overcome when assessing the temporal perception of an attribute [157]. To overcome these drawbacks, Pineau et al. [156] developed a new method called temporal dominance of sensations (TDS), which consists of identifying and rating sensations perceived as dominant until the perception ends. Before the development of this method, a similar experimental approach was successfully used to describe the temporality of sensations in wines [158]. Astringency, a dynamic sensation, takes many seconds to develop after the basic tastes, and the duration depends on the wine. Notwithstanding, TDS can be difficult when panellists had select the dominant attribute and score its intensity, but

It is also essential to discuss and familiarise with the terms associated with astringency. A vocabulary of 33 terms has been proposed by a combined panel of experienced tasters and winemakers to describe the mouthfeel characteristics of red wines [160]. The check-all-that-apply (CATA) question that consists of a list of subqualities from which the panellists have to select all the options they consider appropriate to that wine has been utilised for the characterisation of the astringency subqualities of Tannat wine [161]. Recently, a sensory method that combines CATA approach and training in astringency subqualities with touch-standards resulted very useful for investigating the astringency characteristics of red wines [24, 25, 162]. In any case, intense training is necessary to distinguish astringency from other tastes, especially bitterness, and to reveal the different qualitative attributes. Fatigue and loss of *stimuli* memory may occur, particularly with panellists who are unfamiliar with astringency, and when too many samples are presented. Training is also expensive and time-consuming. However, it is necessary to investigate the astringency subqualities of red wines. Sensory analysis is of fundamental importance, but in some cases, it is not possible to perform, so the replacement with an analytical instrument

able to measure astringency could help in research as well as in the winery.

Because astringency is one of the main attributes for wine quality, winemakers are interested in an analytical and objective method to evaluate it. No method can substitute entirely sensory analysis, but a method that results in a reproducible index has to correlate quite well with it. A statistically significant correlation

The gelatin index has represented the almost widely analytical method for estimating astringency in red wine [136]. Besides, it furnished only approximate results [137]. Successively, a positive correlation (R2 = 0.56) between the gelatin index and

**6.5 Correlation between sensory and analytical analysis**

between the sensorial and analytical methods is necessary.

**154**

time-intensity data was obtained only at a low concentration of polyphenols utilising 29 wines judged by 10 panellists [163]. A method that used the ovalbumin in alternatively to gelatin as a precipitation agent was proposed to determine astringency [137]. Ten wines were tested by 10 expert enologists evaluating the astringency on a scale from 1 to 100. The method resulted in more reproducible than the gelatin index and was positively correlated (R2 = 0.77) with sensory analysis. This method was also used to assess the astringency of Greek wines, and a good correlation was found (R2 = 0.93) [164]. Another predictive model for astringency estimation was based on phenolic compounds and colour analysis of 34 wines by 12 judges on a 9-point intensity scale [165]. Multiple regression generated three possible models to predict astringency from analytical data, the most simple depended on total phenolics and co-pigmented anthocyanins, besides the predicted astringency plotted versus observed astringency resulted in low but acceptable correlation from a sensory perspective.

Monteleone et al. [150] proposed a predictive model by measuring the polyphenol-mucin reactivity in which the capability of polyphenolic extracts to induce astringency was estimated on their ability to develop turbidity in the *in vitro* assay. They found a linear relation between astringency perceived by 30 trained judges and the mucin index for tannic acid model solutions (R2 = 0.993) grape seed extracts (R2 = 0.996), and phenolic extracts (R2 = 0.95) [63].

In a study by Kennedy et al. [166], 40 red wines were evaluated by a panel consisting of three winemakers and two enologists for the astringency intensity scored from zero to 10. The aim was to correlate astringency and tannin concentration measured by different analytical methods: absorption at 280 nm, phloroglucinolysis, gel chromatography, and BSA protein precipitation. The analytical method having the strongest correlations with perceived astringency was the protein precipitation one (R2 = 0.82). Protein precipitation represents the method the most similar to the physiological response to astringent *stimuli* and can be used as an *in vitro* tool for understanding how tannin can modulate astringency perception. Generally, it was assumed that the most suitable proteins for evaluating astringency are the salivary PRPs. However, other proteins in whole human saliva were preferentially precipitated by increasing tannin solutions [142]. Successively, the percentage decrease of two salivary proteins after the precipitation with tannins, measured by electrophoresis, represented an indicator of the reactivity of tannin. The saliva precipitation index (SPI) was well correlated with the sensory evaluation of the astringency of 57 red wines (R2 = 0.97) made by 18 trained assessors [167].
