Instrumental assessment of the sensory quality of beer

18 Instrumental assessment of the sensory quality of beer K. J. Siebert, Cornell University, USA DOI: 10.1533/9780857098856.3.547 Abstract: Experiencing beer involves multiple senses. Color, clarity (the lack of turbidity) and foam (volume, duration and cling) are perceived visually. The temperature, carbon dioxide bite and astringency are tactile (chemesthetic) sensations. Various tastes are perceived in the mouth. Odors are perceived, either orthonasally or retronasally, by a huge number of receptor types located in the olfactory epithelium. Instrumental assessments corresponding to some of these, particularly appearance factors, relate well to human perceptions. For others, the nature of human and instrumental responses is quite different. It is interesting to consider which beer sensory perceptions have good instrumental analogs and which leave something to be desired. Key words: chemesthetic sensations, instrumental measurements, olfaction, taste, visual perceptions.

18.1  Introduction 18.1.1  Sensory perceptions Human senses largely follow the psychophysical response curve (Fig. 18.1) (Stevens, 1957). This shows the strength of a stimulus as the abscissa and the intensity of a sensation as the ordinate. At a low level of stimulus, there is no response and changes in stimulus strength in this range are not perceived. At some level (the detection threshold) the stimulus can just be perceived. At a slightly higher level the stimulus can be recognized (the recognition threshold). Above this level the perceived response increases essentially linearly with increasing stimulus strength, although the response slopes vary with the type of stimulus. At some level of stimulus, saturation is reached and higher levels of stimulus cannot be distinguished. Most flavor thresholds of the compounds that have been determined in beer are actually difference thresholds, where substances have been added to a beer to determine the point at which a difference can be detected.

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548  Instrumental assessment of food sensory quality

Response (% of maximum)

100

Saturation

80 60 40

Identification threshold

20

Detection threshold

0 0

1

2

3

4

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log (Stimulus concentration)

Fig. 18.1  Psychophysical response curve showing response as a function of stimulus intensity.

Frequently this has been done using the ASTM E679 Forced-Choice Ascending Concentration Series Method of Limits (American Society for Testing and Materials, 1979). In this approach, a series of triangle tests, each with two controls and one with the added substance in randomized order, are presented to a panelist. The concentration of the added substance increases with subsequent triangles in geometrically increasing steps (often by a factor of two). Panelists are required to identify one sample in each triangle as being different. Some low concentrations of an added substance may be correctly identified by chance; in this case it is likely that the panelist will miss picking the samples with the added substance at some higher concentration. At some concentration a panelist usually begins to correctly identify the samples with the added substance and also picks the additions correctly at all higher levels. A correct pick at a lower concentration with a miss at a higher level is disregarded. An individual’s threshold for a compound is determined as the geometric average of the lowest concentration correctly indicated and the next lower sample. The panel’s best estimated threshold is then computed as the geometric average of the individual thresholds. It is quite normal for individual thresholds for a compound to range over two orders of magnitude (Lawless and Heymann, 1998). Some individuals are typically quite sensitive for a compound, others average and a few quite insensitive. True anosmia (the complete inability to detect a compound) does occur, but rarely. A person who is quite sensitive for one compound is likely to be insensitive for another (there are no super-tasters). The patterns are quite different for different individuals. As a result, sensory testing intended to reflect the general population must be done with a panel of at least modest size rather than by one or a few ‘expert’ tasters.

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Instrumental assessment of the sensory quality of beer  549 Because flavor thresholds can easily range over at least ten orders of magnitude (Meilgaard, 1975), 99% chemical purity is no assurance of sensory purity. To determine thresholds properly it is necessary to determine a threshold, purify a compound in some manner (by activated carbon adsorption, recrystallization, distillation, preparative chromatography, etc.), again determine the threshold, purify by a different method, etc. until a constant threshold is achieved (Meilgaard, 1974). For some purposes the concept of flavor units (FU) is useful. The number of flavor units of a compound present in a sample is: FU =

concentration of the compound present flavor threshold of the compound

[18.1]

So 1.0 flavor unit of a compound should just be perceptible (equal to the detection threshold). With addition thresholds, it is presumed that a sample containing the concentration of a compound equal to the addition threshold would just be discernible for most people. The strength of above threshold perceptions can be gauged by a sensory test format such as magnitude estimation (Lawless and Heymann, 1998). In this approach a panelist assigns a number to the perceived intensity of a stimulus. Often this intensity is expressed relative to a reference sample with a specified numeric value for a rated character. Such anchoring of the scale is a way to produce more similar scale usage and less variability among panelists. With a technique called descriptive analysis (Lawless and Heymann, 1998), during discussion a panel agrees to use a modest number of descriptive terms to describe a set of samples. Samples are then rated for the intensity of each of these attributes. Upon prolonged exposure to a stimulus, people tend to begin ‘tuning it out’. This phenomenon is called ‘adaptation’ (Lawless and Heymann, 1998). Most people will notice a strong odor upon entering a room, but if they stay there for a while the sensation fades. However, if they leave the room for a bit and then return, the odor is once again noticeable. As a result, care must be taken with a sensory panel not to fatigue panelists by overexposing them to stimuli. Human beings are rather imprecise instruments (Lawless and Heymann, 1998). There is a high degree of variability among individuals because of inherent differences in sensitivity to particular compounds. And there is considerable variation within individuals; this is influenced by illness, allergy, recent food consumption and emotional state. 18.1.2  Instrumental measurements Instruments, like humans, do not produce distinguishable responses below some stimulus level; see Fig. 18.2. The level of stimulus that produces a barely significant response is called the critical limit (Lc). This is defined in

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550  Instrumental assessment of food sensory quality

Instrument response

5 4 3

Non-linearity

Insufficient sensitivity

2 Linear range 1 0 0 1 2 3 4 5 6 7 8 9 10 Stimulus intensity

Fig. 18.2  Hypothetical instrumental response curve showing regions of nonsignificant response, linear increase and non-linearity. p(ybl)

Sbl a Xbl

Lc

y

Fig. 18.3  The normally distributed probabilities of response magnitudes for observations of a blank. The critical limit (Lc) is greater than the mean blank result by a multiple of the standard deviation of repeated blank measurements.

terms of multiple measurements of a blank (Currie, 1999). A signal must exceed the mean level of blank responses ( y bl ) by a multiple (kc) of the standard deviation of the blank responses (sbl) to be deemed present (see Fig. 18.3): Lc = y bl + kc sbl

[18.2]

For normally distributed data and a 95% significance level (P ≤ 0.05), kc = 2.13, and the likelihood of a false positive (α risk) is 1 in 20 (Currie, 1999). However, a result less than Lc does not indicate that a stimulus is absent (see Fig. 18.4). For that, a signal must be less than the detection limit (Ld), see Fig. 18.5. Ld = y bl + kd sbl

[18.3]

For normally distributed data and a 95% significance level (P ≤ 0.05), kd = 4.26 and the likelihood of a false negative (β risk) is 1 in 20 (Currie, 1999).

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Instrumental assessment of the sensory quality of beer  551

0.20

Component

Component

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absent

present

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a −6 −5 −4 −3 −2 −1 Xbl

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Lc

Fig. 18.4  A result less than the critical limit has only a 50% probability that a compound is absent (assuming normally distributed data).

0.20

4.26 s

p(y)

p(ybl)

p(yu)

a

b 0.00

−8

−6

−4 Xbl

−2

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Lc

Ld

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4 y

Fig. 18.5  For 95% probability that a compound is absent, a result must be less than the limit of detection (Ld), which is defined as greater than the mean of replicate blank observations plus a higher multiple (4.26 for normally distributed data) times the blank standard deviation.

Instruments often have response ranges where the relationship between stimulus and response is essentially linear (Fig. 18.2). Instruments typically do not become saturated at high stimulus levels, but often reach a region where the response is non-linear. The American Society of Brewing Chemists (ASBC), the Institute of Brewing (now the Institute of Brewing and Distilling) and the European Brewing Congress (EBC) have for many years collaboratively tested analytical methods for substances or properties of beer and brewing materials. Methods that have been judged to perform satisfactorily by the ASBC have been published in Methods of Analysis (American Society of Brewing

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552  Instrumental assessment of food sensory quality Chemists, 2009). Some methods have been tested by both ASBC and EBC and accepted as ‘International Methods’. 18.1.3  Univariate and multivariate phenomena A univariate relationship is one where a single response is related to a single compound. An example would be an absorbance measurement at a wavelength where the analyte is the only absorbing substance. Then the relationship is simply between the concentration of the analyte and the absorbance. Another example would be the strength of a sensory response caused by a single compound in a sample. If glucose were the only sweet substance in a beer, then there would be a univariate relationship between glucose concentration and sweetness. In a bivariate relationship, two variables jointly influence a response. Ethyl hexanoate and ethyl octanoate, both apple-flavored esters, jointly produce the apple estery flavor note in beer (Meilgaard, 1982). In multivariate relationships, three or more variables jointly influence a response. Some of these may have a positive effect while others have a negative influence. Positive effects can be simple additivity, where the effects of individual substances are simply added together (e.g. where 0.5 FU of one substance and 0.5 FU of similarly flavored compound would be perceptible), less than perfect additivity (where, for example 0.6 FU of one compound plus 0.6 FU of another would be needed to be perceived) or true synergy, where, for example, 0.4 FU of one compound + 0.5 FU of another would be perceptible. Negative effects are evidenced as inhibition or masking, where the presence of one compound diminishes the response to another. Multivariate responses can occur when multiple compounds jointly impact one response, when a single compound impacts multiple responses, or when multiple compounds impact multiple responses.

18.2  Human and instrumental perceptions of beer appearance Perceptions of beer appearance include color, foam and turbidity. All of these can be observed instrumentally with physical (optical) measurements, and typically these agree well with human perceptions. 18.2.1  Color For many years beer color was thought of as the degree of a brown color, ranging from pale yellow through various shades of brown to nearly black. This was a reasonable assumption until the development of ‘red’ beers; these are not actually red but have a somewhat orange hue. Color observations were originally made with a visual comparator in which a sample was

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Instrumental assessment of the sensory quality of beer  553

Lamp

Monochromator or filter

Sample cell

Transmitted light detector

Fig. 18.6  The optical path for either a photometer or spectrophotometer; the former uses a filter and latter a monochromator to select the wavelength or optical band used.

placed in a tube, compared with reference standards, and expressed as degrees Lovibond. This approach was largely superseded by the use of photometers (colorimeters), see Fig. 18.6, with bandpass filters in the 420–450 nm portion of the visible light spectrum (Beer-10B. Color by Photometric Method, in American Society of Brewing Chemists, 2009). This approach in turn was largely supplanted by the use of a spectrophotometer at a single wavelength of 430 nm (‘Beer-10A. Spectrophotometric Color Method’ in American Society of Brewing Chemists, 2009). More recently, tristimulus instruments or measurements that represent more of the visible spectrum have been employed (Cornell et al., 2002). In both human and instrumental perceptions of color, the strength of the absorbance of a portion of the visible range is observed. In the case of humans, the wavelength range is determined by the concentrations of absorbing compounds present (essentially all the color is derived from malt) while with instruments, the wavelength range is more precisely defined by a monochromator or filter. The correspondence between human and instrumental perception is very good with non-turbid samples. When turbidity is present, it appears to an instrument as if the absorbance is greater than it actually is, because some of the light that does not reach the detector is actually scattered rather than absorbed. A haze-corrected color measurement can be made with an instrument that determines both scattered light and absorbance. Instrumental observations of beer color are considerably more precise (repeatable) than human observations. 18.2.2  Turbidity In the absence of scattered light, a beer appears clear or ‘bright’, although it has some color. Scattered light causes a liquid to appear hazy (turbid). Light scattering results from the presence of suspended particles of colloidal or larger size. It is influenced by the size and shape of suspended particles, the wavelength of light used and the angle at which scattering is observed relative to the incident beam (Siebert, 2009). The optical properties of the suspending liquid can also play a role.

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554  Instrumental assessment of food sensory quality 90° Detector

Lamp

Lens

Forward scatter detector

Sample cell

Fig. 18.7  The optical path (seen from above) in a turbidimeter. Often there is a bandpass filter in the optical path.

Turbidimeters (Fig. 18.7) typically observe light scattering either at a narrow angle to the incident light beam (usually in the 11–25° degree range) or at 90°. The latter instruments are also called nephelometers. Haze has long been assessed visually using various arrangements, including the shadow box (Gales, 2000), or simply by holding a clear vessel containing beer to view against a light. Recent investigations using omnidirectional lighting have indicated good agreement between the haze visual threshold determined against a black non-reflective background and a turbidimeter employing 90° scattering with white light (essentially the entire visible range). Thresholds measured in this way fell in the range 0.21 to 2.2 nephelometric turbidity units (NTU) (Carrasco and Siebert, 1999; Fleet and Siebert, 2005); this is equivalent to 0.053–0.548 EBC turbidity units or 3.67–38.3 nephelos units. Reduced illumination intensity led to lower thresholds (greater detection sensitivity) up to a point (Fleet and Siebert, 2005). Using a light-colored background rather than the black one resulted in a huge increase in thresholds, corresponding to greatly decreased sensitivity (Fleet and Siebert, 2006). This appears to have been due to the difficulty in seeing scattered white light against a light colored background. Visual perception of haze above the detection threshold using magnitude estimation showed a region of good agreement with a 90° turbidimeter, but diverged at higher particle concentrations (Carrasco and Siebert, 1999); see Fig. 18.8. Humans reached saturation, but the instrumental indication actually increased exponentially, possibly due to multiple scattering. Descriptive analysis was applied to samples containing particles of three different sizes at suprathreshold concentrations, each suspended in three solution colors. The results indicated panelists responded to only two fundamental properties, scattering intensity and homogeneity (Carrasco and Siebert, 1999). The largest particle size used, 10.3 μm diameter, or about the size of a yeast cell, appeared homogeneous at both low and high concentrations, but at intermediate levels appeared ‘lumpy’. It appears that moderate

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Instrumental assessment of the sensory quality of beer  555 1200

350

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Turbidity (NTU)

Visual magnitude estimation

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800 600 400 200

50 0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

0

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

Particle concentration (mg/mL)

Particle concentration (mg/mL)

(a)

(b)

Fig. 18.8  Suspensions of 2.6 μm diameter spherical particles in clear liquid at suprathreshold concentrations were assessed by (a) visual magnitude estimation: results are geometric average results from 18 panelists, and (b) turbidimeter observations. Data from Carrasco and Siebert (1999).

concentrations of relatively large particles are randomly concentrated and dispersed at different locations in a sample. 18.2.3  Foam A number of aspects of beer foam have been described including beer foam height, foam volume, collapse time (or rate) and the amount of foam cling (or ‘lacing’) on a glass. Numerous foam assays have been devised to measure these in various ways (Bamforth, 1985; Evans and Sheehan, 2002). There are two main approaches to foam measurement, pouring from a container (bottle or can) or foaming up degassed beer with CO2. Pour test results are affected by package geometry and the CO2 level of the package. If N2 is used in addition to CO2, this can have a very significant effect on foam bubble size (smaller) and foam duration (longer). Tests in which the beer is removed from the package by piercing through a bottle crown or can bottom rather than by pouring minimize the package effect. And tests where the beer is gently removed from the package and decarbonated before foaming up in some apparatus (e.g. the Rudin method) take away both the effects of the package and the carbonation level. As a result, such approaches should be most informative about the inherent foaming ability of a particular beer. The pour test, on the other hand, is closest to actual consumer practice, but only informative as to the behavior with the particular type of package tested. The Nibem method foams beer into a glass-like beaker after piercing the package. The collapse of the foam is monitored by an instrument that

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556  Instrumental assessment of food sensory quality observes the time taken for a conductivity probe that senses the top of the foam column to sink by 10, 20 or 30 mm (Wackerbauer and Greif, 1980). In the Rudin method (Rudin, 1957), beer is removed from the package with minimal foaming, allowed to degas spontaneously overnight in a covered beaker, and a measured volume of beer is placed in the apparatus. CO2 at regulated pressure and flow rate is admitted through a sintered glass frit to foam up the beer to a certain height. The time taken for drainage of a fixed volume of beer from the foam is observed with a stopwatch. Pour tests typically involve either pouring by hand or with an apparatus that tilts a package to pour the beer into a glass or glass-like beaker. The time taken for the foam to collapse is measured with a stopwatch. There is inherent difficulty in carrying out pour tests reproducibly. With tests that assess foam cling, the foam, once generated, is allowed to collapse completely and the amount of foam adhering to the vessel walls is measured in some manner (by comparison with standard photographs or optically). The fact that many foam methods have been described in the literature likely attests to the fact that none is completely satisfactory. One of the difficulties is that the foam level observed at the side of a vessel is different from that in the center.

18.3  Human and instrumental perceptions of beer flavor Flavor includes perceptions made in at least three ways. The main senses involved are taste, olfaction and chemesthesis. 18.3.1  Olfaction Olfaction occurs either during inhalation of gas from above a beer, which draws odorant substances past the olfactory epithelium (called orthonasal olfaction) or during exhalation of gas after having ingested beer (retronasal olfaction). In the latter case gas from the lungs or stomach passes by the olfactory epithelium from the back of the nose. There are hundreds of different olfactory receptor types (Hasin-Brumshtein et al., 2009), each of which responds to different degrees to individual chemicals. It has been estimated that humans are capable of recognizing thousands of different compounds (Zozulya et al., 2001). The gas being sensed with any real food or beverage contains multiple compounds. The brain receives many responses in parallel and combines these to produce a pattern that, through experience, we may learn to identify as belonging to a beer, a particular beer brand or a beer style. Because olfaction responds to large numbers of compounds, two general instrumental approaches have been employed. One of these is the use of gas chromatography (GC), which is suitable because odorants must, by definition, be volatile. GC separates compounds in the time dimension for

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Instrumental assessment of the sensory quality of beer  557 separate detection, often by a rather non-specific detector (e.g. flame ionization). This approach converts a multivariate phenomenon into a sequential univariate one (intensity as a function of time), where the size (height or area) of a GC peak (when a peak is due to a single compound) indicates the concentration of a compound and its sensory intensity if it is present above its flavor threshold. The second approach is to use multiple different sensors in parallel that are exposed to the headspace gas above a sample. Because the approach of multiple sensors operating in parallel is conceptually similar to the way olfaction operates, this approach has been dubbed the ‘electronic nose’ or ‘e-nose’. Olfaction is difficult to represent instrumentally because commonly employed detectors respond very differently to odorant chemicals than the olfactory epithelium. The flame ionization detector (FID) has widely been used in GC studies of organic compounds because it is sensitive, stable and responds to most organic compounds. With an FID, compounds exiting the GC column are passed through a hydrogen–air flame. As they are burned, ions are generated and the ion current between two electrodes is sensed. Many of the compounds causing large peaks in an FID chromatogram of a sample such as beer have no effect on flavor because their flavor thresholds are much higher than the concentrations at which they occur in beer. Often the compounds actually responsible for flavor produce small peaks that are obscured in the chromatogram by larger ones. Some GC studies have been carried out using a mass spectrometer (MS) as the detector. When MS with selected ion monitoring is employed, the detector is in effect tuned to respond to a particular compound or compound class. This presupposes that the flavor compounds of interest and their mass spectra are known, which is often not the case. Limitations of GC are the need for adequate separation and sufficient detection sensitivity (Siebert, 2011). GC-GC, where a peak from one column is switched to a dissimilar column to be further separated, can improve resolution. A detector that is highly specific for an element (e.g. nitrogen or sulfur) can measure compounds of interest without physically separating them. This is also the case with simultaneous observation of multiple different signals (like full spectrum MS); this provides data that can be de-convoluted to measure compounds whose peaks underlie other compounds. An approach that produces a response similar to human sensory perception is gas chromatography-olfactometry (GCO), where the compound separation is carried out by GC but the detection is done with a human nose (Murakami et al., 2003). Strictly speaking, however, this is not entirely an instrumental method. In an e-nose, a detector array is exposed to headspace gas from a sample (see Fig. 18.9). Several types of detector arrays have been employed (Deisingh et al., 2004). These include metal oxide semiconductor field-effect transistors (MOSFET), conducting polymers, quartz crystal microbalances,

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558  Instrumental assessment of food sensory quality Sensor array

Sample

Air pump

Vent

Interface

PC

Fig. 18.9  In an electronic nose, the headspace above a liquid or solid is sampled and passed by a sensor array in which each sensor responds somewhat differently. The response data is acquired by a computer and processed using pattern recognition or in some cases a calibration to measure an analyte.

and surface acoustic wave (SAW) sensors. In each case different sensors in the array are modified (for example by different coatings) in order to produce somewhat different responses to a stimulus. E-noses have many fewer types of sensor than the olfactory epithelium and in many cases do not have adequate sensitivity to measure compounds at or below their flavor thresholds. Of necessity e-noses employ computers and multivariate analysis (Siebert, 2001) to process the data. Commonly used approaches are principal components analysis (PCA) and pattern recognition techniques for characterizing samples by raw material cultivar (Bailey et al., 1995; Tomlinson et al., 1995; Weber and Poling, 1997), beer type or brand (Tomlinson et al., 1995), or to detect off-flavors or stale flavors (McKellar et al., 2002; Weber and Poling, 1997). In some cases e-noses have been used to detect or measure particular compounds (Bailey et al., 1995; Weber and Poling, 1997). Fairly often the multivariate procedure used with the e-nose has been an artificial neural network (ANN) either to classify samples in some way or to predict a compound concentration or flavor sensation (Weber and Poling, 1997). This approach can model non-linear relationships using multiple nodes and layers to feed in inputs in different ways. One of the problems with ANN is that the analyst has no idea how it has operated (which individual sensors were used and in what manner) to produce a result. That severely limits what can be learned. Seasholtz and Kowalski (1993) suggested one should apply the principle of Occam’s razor to the use of multivariate procedures: that no more complicated method should be used than

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Instrumental assessment of the sensory quality of beer  559 is needed to solve a problem. They recommend the use of ANN with multiple layers and nodes as the method of last resort. 18.3.2  Taste The five tastes (bitter, salty, sour, sweet and umami) are well characterized (Lawless and Heymann, 1998). Different types of taste buds in the tongue perceive the tastes. Beers usually have noticeable bitterness resulting from the isoalpha acids derived from the hop alpha acids during kettle boiling. Isoalpha acids have a characteristic sharp (or clean) bitterness. Some beers have minor salty or sweet notes. Beers appear to lack umami (savory) flavor. Most beers have limited sourness, but lambics and gueuzes (Belgian sour styles) have a lot of this character. The bitter aspect of beers is reasonably well measured by UV spectrophotometry after extracting isoalpha acids (and some closely related hopderived compounds) from acidified beer with isooctane (‘Beer-23A. Bitterness Units (BU)’ in American Society of Brewing Chemists, 2009); this is an International Method, (where 1 BU is approximately equal to 1 mg/L isoalpha acids). The sweet character in some beers is either from residual amounts of simple sugars remaining after fermentation or, in some cases, from ‘priming’ sugar added to the beer shortly before packaging, mainly for in bottle ‘conditioning’ (generating CO2 by the action of yeast). Sweetness in beer is closely associated with the levels of monosaccharides and disaccharides; these can be measured by HPLC using a refractive index detector (‘Wort-14B. Fermentable Saccharides by HPLC’ in American Society of Brewing Chemists, 2009). Individual sugars differ in their perceived sweetness (fructose is noticeably sweeter than either glucose or sucrose). Saltiness is associated with the sodium ion (Chandrashekar et al., 2006); its concentration in beer can be determined by atomic absorption spectroscopy (‘Beer-36. Sodium by Atomic Absorption Spectroscopy’ in American Society of Brewing Chemists, 2009). Sourness is largely a function of pH, with lower pHs perceived as more sour. Low pH in beer is closely related to the concentrations of relatively strongly ionized organic acids, particularly acetic and lactic acids; beer total acidity can be determined either by titration using a pH meter (‘Beer-8A. Total Acidity by Potentiometric Titration’ in American Society of Brewing Chemists, 2009) or by indicator titration (‘Beer-8B. Total Acidity by Titration of Diluted Beer with Phenolphthalein as Indicator’ in American Society of Brewing Chemists, 2009). An equivalent approach for taste to the e-nose is the ‘electronic tongue’ (Deisingh et al., 2004). This is an array of sensors that are immersed in a liquid (see Fig. 18.10). Because taste is conceptually simpler than olfaction (in terms of the number of characterized qualities), one approach to the electronic tongue is to construct the device to produce responses equivalent to each of the five tastes. In practice, however, electronic tongues have

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560  Instrumental assessment of food sensory quality Sensor array

Liquid sample

Pump

Waste

Interface

PC

Fig. 18.10  In an electronic tongue, a liquid is sampled and passed by a sensor array in which each sensor responds somewhat differently. The response data is acquired by a computer and processed using pattern recognition or a calibration to measure an analyte.

usually been designed on similar conceptual lines to the e-nose. That is, arrays with considerably more than five sensors are used and multivariate analysis is used to map to the five tastes. The measurement principles used have included electrochemical (potentiometric, voltammetric, ampero­ metric, impedimetric and conductimeric), optical, mass, and enzymatic sensors (also called biosensors) (Escuder-Gilabert and Peris, 2010). In beer, electronic tongues have been applied to relate to taste panel responses (Rudnitskaya et al., 2009), to predict bitterness and alcoholic strength (Arrieta et al., 2010), and to relate to basic beer parameters (Polshin et al., 2010). 18.3.3  Chemesthetic sensations Chemesthetic perceptions are actually tactile or pain sensations produced by the trigeminal nerve, which wraps around the throat and extends into the mouth. Among the impressions sensed in this way are hot and cold temperature, mouthfeel, CO2 bite and astringency. Beer is normally served cool or even chilled, and this is perceived by chemesthesis. Smoothness is a general mouthfeel sense, probably resulting from a number of compounds acting in concert. Some beers (particularly very dark ales or lagers) produce an astringent sensation. Saliva contains proline-rich proteins (PRPs), which normally provide lubrication of oral surfaces. When polyphenols are ingested, they cross-link the PRPs, precipitating them and removing the lubrication they provide (Bajec and Pickering, 2008); this results in the astringent sensation. Acids intensify the PRP–polyphenol interaction and

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Instrumental assessment of the sensory quality of beer  561 Oscillator circuit

Frequency counter

Flow cell

PC

Pump

Sample

Waste

Fig. 18.11  Membrane sensor: when a liquid sample is passed by a quartz crystal coated with a lipid, non-polar compounds in the liquid adsorb onto the lipid. This changes the resonant frequency of the crystal in proportion to the mass adsorbed.

enhance astringency (Siebert and Chassy, 2003). So acids contribute to both sour taste and astringency. It is known that acids alone in water also produce astringency. This was recently shown to be due to the intensification of interaction of polyphenols already present in saliva with PRPs (Siebert et al., 2011). Some instruments designed to be equivalent to humans for chemesthetic sensations have been developed. Mainly these have employed lipid-coated quartz crystal microbalances (see Fig. 18.11). This approach has been used to assess body, smoothness and astringency in beer (Kaneda et al., 2005). When a liquid is passed by the sensor, non-polar materials are adsorbed onto the lipid, increasing the mass of the crystal, which in turn changes the resonant frequency in proportion to the adsorbed mass.

18.4  Overall perception of beer flavor When humans experience a product such as beer, the multiple flavor sensations detected by olfaction, taste and chemesthesis are combined in the brain in a manner akin to PCA. Only the three or four most prominent features are seized upon unless a conscious effort is made to steer attention to particular individual characteristics (Laing and Jinks, 1996). One major difference between analytical measurements and sensory perceptions is that the former are often univariate, while the latter are frequently multivariate. Analytical measurements often originate in the size of a chromatographic peak, which is presumed to represent the concentration of a single compound. In spectrophotometry an absorbance at a particular wavelength is often taken to result from a single compound or class

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562  Instrumental assessment of food sensory quality of closely related compounds, either directly or after use of a reagent to develop a color (chromophore). Visual perceptions and instrumental observations of visual phenomena often perceive essentially the same phenomena and relate well even when the phenomenon actually is caused by multiple factors. For example, the color of beer is the combined effect of all the substances that absorb light in a portion of the visible range. Beer haze mainly results from interactions between proline-rich proteins and polyphenols that are affected by the beer pH and alcohol content. Beer foam is largely a result of proteins (different from those involved in haze) that interact with hop-derived bitter compounds and is also influenced by pH and ethanol content, among other factors. However, since haze and foam are directly measured, their multivariate nature is not apparent. Studies of various beer properties are frequently made by carrying out sensory observations and chemical (or physical) analysis on the same set of beers. Univariate or multivariate regression is then typically applied to produce relations where the chemical analysis results are presumed to be independent variables and the sensory results are presumed to be dependent variables. In other words, researchers frequently assume that the analytical variables cause the sensory results. In this situation the actual independent variables are the raw materials and the manner of producing the beers. Both the sensory and analytical observations are actually dependent variables. As a result, any apparent relationships cannot demonstrate cause and effect but rather only associations. This may still be useful information as it can guide further experimentation to prove or disprove causation. To prove that a compound is flavor-active, it is necessary to show that the substance is present in beer at or above its flavor threshold or that, together with similarly flavored substance(s), two or more substances are jointly perceptible at the concentrations at which they occur in beer (Siebert, 1988).

18.5  Future trends Some evolutionary improvements in instrument response in terms of sensitivity and stability are likely to occur; this would lead to better precision and accuracy. However, since many improvements in this area have already occurred, remaining improvements will likely be small. One such area, the use of digital rather than analog electronics, has enabled more signal averaging and digital smoothing, which reduces noise. Knowledge of the compounds responsible for particular flavors is certain to improve. Many measurements will be moved on-line or in-line. This gives faster response than grab sampling by laboratory personnel and provides continuous information. It also offers the possibility of on-line control for critical parameters such as alcohol, calories, original gravity and CO2 content.

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Instrumental assessment of the sensory quality of beer  563 Instruments developed relatively recently will undoubtedly improve and mature. To some extent this will be so for the e-nose, but probably even more so for the electronic tongue and chemesthesis sensors. There may be some developments in which sensory properties are predicted from observations of substances that cause a phenomenon. For example, haze at some time point could perhaps be predicted from the concentrations of haze-active (HA) proteins and HA polyphenols.

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