Influence of Beer Color on Perception of Bitterness a Thesis Submitted To

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Influence of Beer Color on Perception of Bitterness

A Thesis Submitted to the Faculty of Drexel University by Joseph William Spearot in partial fulfillment of the requirements for the degree of Master of Science in Food Science March 2016

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Dedications

To my family and friends. Without your constant encouragement, support, and love I would be lost. iv

Acknowledgements

First and foremost I would like to thank my research mentor, Dr. Jake Lahne, encouraging my research and being an invaluable source of support and knowledge. From IRB approval to quick emails about proper spit cups to helping explain the complexities I cannot thank him enough. Additionally, I would like to thank Nick Rodgers, sensory extraordinaire for

Yards Brewing Company, for his help in setting up, running, and recruiting for the two sensory studies run at Yards. I would also like to thank Frank Winslow and Lena Jonsson of the Quality

Assurance lab of Yards Brewing Company for their help in planning, running, and taking interest in my research. Many thanks go to fellow MS in Food Science students Pradnya Rao, Urvi Shah, and Nidhi Champaneri for their help in setting up and running the sensory study at Drexel.

Additionally, I would like to acknowledge the comments and guidance of my thesis committee including Dr. Steven Wrenn, of the Chemical and Biological Engineering department, and Dr.

Brandy-Joe Milliron, of the College of Nursing and Health Professions. Finally, I’d like to thank all those who took interest in my research, participated in my studies, and helped at any step along the way.

Table of Contents List of Tables ...... vi List of Illustrations ...... vii Abstract ...... viii 1. Introduction ...... 1 2. Literature Review ...... 3 I. Introduction ...... 3 II. Background and the Brewing Process ...... 4 III. Beer in the United States ...... 8 IV. Beer Color ...... 12 i. Malt and Color Extraction ...... 12 ii. Measurement of Color ...... 14 iii. Darkening Techniques ...... 15 V. Beer Bitterness ...... 17 i. Hops and Bitterness Extraction ...... 17 ii. Measurement of Bitterness ...... 20 iii. Perception of Bitterness ...... 22 VI. Sensory Evaluation ...... 25 VII. Relationship between Color and Flavor ...... 28 VIII. Specific Objectives ...... 32 IX. Hypotheses ...... 33 X. Figures and Tables ...... 34 3. Beer Production and The Brewing Process ...... 38 I. Materials and Methods ...... 38 II. Results ...... 41 III. Discussion ...... 42 IV. Figures and Tables ...... 43 4. Biological and Chemical Analyses ...... 46 I. Materials and Methods ...... 46 II. Results ...... 48 III. Discussion ...... 49 IV. Figures and Tables ...... 50 5. Sensory Studies ...... 53 I. Materials and Methods ...... 53 II. Results ...... 56 III. Discussion ...... 58 IV. Figures and Tables ...... 61 6. Conclusions ...... 67 7. References ...... 69 8. Appendix A: Sensory Test Materials ...... 76 9. Appendix B: Raw Chemical Analysis Data ...... 85 10. Appendix C: Raw Sensory Analysis Data ...... 87

List of Tables

Table 1: Summary of Microbiological Testing Results ...... 51 Table 2: Color and Bitterness of Darkening Technique Beers ...... 52 Table 3 Color and Bitterness of Color Perception Testing Beers ...... 52 Table 4: Color Versus Attribute One-Way ANOVA Results ...... 62 Table 5: Expertise Two-Way ANOVA Results ...... 64 Table 6: Summary of Color Perception Discrimination Test ...... 66

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List of Figures

Figure 1: Overview of Brewing ...... 34 Figure 2: Malt Types ...... 35 Figure 3 EBC/SRM Scale ...... 35 Figure 4: Hop Flower Anatomy ...... 36 Figure 5: Compounds Extracted from Hops ...... 36 Figure 6: Isomerization of Alpha Acids ...... 37 Figure 7: G Protein Pathway ...... 37 Figure 8: Specialty Ingredients used during Brewing ...... 43 Figure 9: Overview of Brewing Protocol ...... 44 Figure 10: Final Beer (Color Perception) Products ...... 45 Figure 11: Carbonation Testing Equipment ...... 50 Figure 12: Yeast Microscopy ...... 51 Figure 13: Statistical Results of Color Perception Testing ...... 61 Figure 14: Effect of Beer Color on Bitterness Perception ...... 63 Figure 15: Effect of Expertise on Saltiness and Liking ...... 65 Figure 16: Effect of Color and Expertise on Bitterness ...... 65

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Abstract Influence of Beer Color on Perception of Bitterness Joseph William Spearot Jake Lahne, Ph.D.

In general, beer is composed of malted barley, hops, water, and yeast. The color of beer derives in large part from malted barley, which also provides sugars for alcoholic fermentation by yeast. Meanwhile, bitterness in beer derives almost entirely from the main flavoring agent: hops, which also give the product fruity, woody, herbal, and spicy flavor notes. Thus, flavor and color in beer – particularly bitter taste – are not connected. Nevertheless, the idea that beer color predicts flavor intensity is common among consumers. This is probably due to sociohistorical factors. For example, in the 19th century companies like Miller and Anheuser-Busch began to, and still do, dominate the brewing market with German-style lagers with low alcohol, low bitterness, and light colors. Perhaps because of this there is a common misconception that a dark- colored beer will be more bitter than a lighter beer. The current research was designed to investigate whether this common misperception will result in measurable differences in consumer sensory perception. All of the research below was approved by the Drexel University

IRB. First, a discrimination study on methods for creating dark color in beers was completed to determine whether these adjuncts created perceptible differences in beers when consumers were blind to color. Three batches of beer from the same recipe were brewed; one batch was darkened with black malt (~4% total grain bill w/w), one was darkened with Sinamar®, a malt-based dye

(120 mL per 19 L beer), and the third was uncolored. A series of triangle tests (n = 24) was carried out between the samples with color concealed; in addition, bitterness (IBU) and color

(SRM) were quantified instrumentally. Tests confirmed that the only difference between samples ix was color. From these results, Sinamar® was chosen as a darkening method for the main test; a triple batch of the same recipe was brewed, split into three, and colored to three levels: yellow

(SRM = 13.0), brown (SRM = 30.7), and black (SRM = 55.1). A second set of triangles tests (n

= 21) found no differences between these beers. A consumer sensory test (n = 85) collected data on these beers’ flavors with color unobscured. Data were analyzed using repeated-measures

ANOVA, with consumers as between-variables and beer-color as within-variables. This analysis showed that consumers rated the yellow beer samples as significantly (F (2, 164) = 5.15; p <

0.05) more bitter than the black beer samples, although the same samples are not readily discriminable when color is obscured. This is evidence of a significant color/taste interaction in beers. The direction of this interaction, however, was unexpected: this may be due to the rise in popularity of India Pale Ale styles; these are light, yellow beers with intense hop bitterness. To examine this hypothesis further, posthoc investigation of demographic trends in color-bitterness interactions were explored and are presented here.

Chapter 1: Introduction

Despite beer color and hop bitterness (or any specific flavor attribute) being unrelated, there is a misconception that color or color intensity will equate with bitterness. In general beer is composed of malted barley, hops, water, and yeast. While barley is the main source of sugars in brewing, additional sources such as oats, rice, corn, and sugar extracts are commonly used. Barley is responsible for the toasted and caramel- like sweetness when used in high concentrations. These grains are the main source of color in the beer. Chemical compounds, such as melanoidins, are extracted during the brewing process and additional browning can form due to Maillard reactions. The roast intensity of malt will determine the color contribution. Base malt will contribute little to no yellow color whereas black malt can contribute deep brown or black color.

Although hops contribute a majority of flavor to beer, these malts will also contribute to the flavor profile of the beer. Chemical compounds in hops, namely iso- alpha acids, are responsible for the characteristic bitterness of many beers. The compounds are extracted and formed during the boiling step of brewing. Hops may also contribute herbal, earthy, spicy, and citrus flavors to the beer. Beyond flavors hop compounds contribute to beer stability and have bacteriostatic activity (Hardwick, 1995).

Over time styles of beer, particularly levels of bitterness, have adapted to consumers palates. Brewers can independently choose different types or levels of both hops to influence bitterness and malt types to effect color.

Beyond being one of the most popular beverages worldwide today, beer has had a long history of economic, cultural, social, and scientific importance (Nelson, 2005). Over 2 the past 30 years the craft beer revolution in the United States and around the world has produced beers with unique flavors and ingredients. Large commercial breweries did not become prevalent in the United States until the influx of German immigrants in the mid-

19th century. During this time companies like Anheuser-Busch and Miller rose to, and still currently, control a monopoly on the beer market. Lager styles of beer became popular for their light flavors and thirst quenching characteristics (Ogle, 2006). Lager beers are characterized as being light bodied, very pale yellow in color, a neutral taste with little to no hop bitterness, and some residual sweetness. They are meant to be what is called “sessionable” today, or suitable for a long drinking session, due to their light bodied, low calorie and alcohol, and low hop bitterness characteristics (BJCP, 2008).

Budweiser, a light flavored American lager, still controls the market being 18% of total beer sold within the US (Satran, 2012). This dominance, and the only relatively new recent expansion of craft beer, has led to many misconceptions and bias about beer. This includes the belief that a darker beer will be more bitter while a lighter yellow beer will be less bitter. There may be an additional population of consumers who believe the opposite, that a dark beer is less bitter and sweeter while a lighter yellow beer is more bitter. Differences in how beer is perceived is a complex topic that must take into account historical trends, current beer styles or trends, and consumers beer drinking experience and liking of beer. As discussed above, malt is largely responsible for beer color and hops for bitterness (Ogle, 2006). Therefore, color and bitterness are not related.

This research will review the current state on knowledge on beer color, bitterness, and perception of flavors while also examining historical and socioeconomic trends. At the same time a detailed study will be used to determine how consumers relate color to 3 bitterness. To do so, chemical analysis and sensory evaluation techniques were utilized to determine how consumers perceive beer samples. Experimentally, three beers of varying colors (yellow, brown, and black) were presented to a series of testing participants to determine how color affects perception of bitterness. Before this a series of tests were completed to determine appropriate darkening method and to ensure that color was the only different variable between beers. While additional investigation is always necessary, this research should not only comment on beer, but the idea that perception of food products can often have more of an effect than reality.

Chapter 2: Literature Review

Introduction

Throughout this review background on brewing, the source of color and bitterness in beer, historical trends in brewing, and how color influences flavor perception will be detailed. While dark malts may contribute slight bitterness, the majority of bitterness in beer is derived from hops, while color is derived from the malt. Thus, there is not necessarily a connection between color and hop bitterness. However, there is a common misconception that beer color is directly related to flavor (specifically bitterness) or flavor intensity. These beliefs are likely due to historical trends and a general lack of education on beer and the brewing process. Historically, paler (more yellow) beers with lower bitterness levels have been considered more desirable than dark beers. This research will review the current state of knowledge on beer color and bitterness while providing background for the current research that follows. 4

Background and the Brewing Process

According to Nelson (2005) beer, after water and tea, is the third most popular beverage in the world overall. He also notes that it is the most widely consumed alcoholic beverage and is considered to be one of the oldest fermented beverages alongside wine and mead. Brewing has been noted as early as the Neolithic period where it had strong influence on culture and religion. Beer was drunk and offered to the gods ritually throughout early civilizations and played an important role in everyday life and nutrition

(Nelson, 2005). According to Meussdoerffer (2009) fermented beverages may have been one of the major sources of human development and survival. Beer offered an alternative source of hydration, as opposed to the regularly infected water sources, and contained many essential nutrients (Meussdoerffer, 2009). Early documentation (including hieroglyphics and ancient texts.) stressed beer’s importance in society. The first evidence of beer in Egypt is dated from 3500 BC. Monasteries, as sources of innovation and research, also used beer for economic and nutritional support (Meussdoerffer, 2009).

Brewing as a profession can be traced back to the time of Charlemagne, and throughout the 11th and 12th centuries the presence of “brassatores,” brewers, in major cities was considered normal (Meussdoerffer, 2009). As scientific discoveries led to a better understanding of the brewing process they led to the development of efficient brewing equipment and processing during the 18th and 19th centuries. In fact, research with beer developed the pH scale (Sørensen, 1909), the statistical student’s t-test (Box, 1987), and the process of pasteurization (Pasteur, 1879). While 79% of the world’s beer was produced in Europe at the turn of the 20th century, only 34% of the beer produced today is of European origin (Meussdoerffer, 2009). Beer and brewing have spread around the 5 world, and this once ancient drink is still extremely important in the lives of many people today.

Although it is difficult to define “beer” in an all-encompassing manner, the U.S.

Department of the Treasury, Alcohol, and Tobacco Tax and Trade Bureau (TTB), in Title

27, Chapter 1, Subchapter A, Part 25, Subpart B of the Code of Federal Regulations

(CFR) defines:

“Beer, ale, porter, stout, and other similar fermented beverages (including saké

and similar products) of any name or description containing one-half of one

percent or more of alcohol by volume, brewed or produced from malt, wholly or

in part, or from any substitute for malt.” (TTB, 2011).

A simpler explanation describes beer as a fermented alcoholic beverage derived from malted cereal grains-usually barley, hops, water, and yeast (Barth, 2013). Some breweries also use malt alternatives, fruits, vegetables, lactic acid bacteria, and many other different ingredients when formulating their beers.

Beer can be categorized into two main types: ale and lager. Ale yeast,

Saccharomyces cerevisiae, is usually called “top-fermenting” and has huge variety in characteristics between types, including flocculation, attenuation, and flavor profile development. Ale yeast was traditionally collected off the top of fermenting tanks where it forms a thick foam layer, called krausen, hence being called “top-fermenting.” In reality both yeast types are distributed throughout the beer during fermentation. Ale yeasts function best in the upper 60s °F (18-21 °C), and produce fruity and aromatic flavors and aromas. Lager yeast, Saccharomyces pastorianus (carlsbergensis), usually 6 called “bottom-fermenting” yeast, is the product of a hybridization between S. eubayanus and S. cerevisiae. Lager yeasts are not high flocculators, work slower, and function best between 50-55 °F (10-13°C). These yeasts produces light, crisp, and effervescent beers with a clean flavor and aroma. Using this type of yeast also requires a “lagering,” slow temperature decreasing and aging the beer at 40°F, step during brewing. This allows some fermentable sugars to remain and allows the yeast to absorb byproducts that may be considered beer faults (White & Zainasheff, 2010).

The process of brewing (summarized in Figure 1) begins with the processing of barley or additional adjuncts like corn, rice, and oats. Malting is the process that generates enzymes, develops grain color and flavor, and releases starches necessary for brewing from the barley. This is not commonly completed by brewers, but by external manufacturers (Willaert, 2006). Barley is steeped, germinated, and kilned, which allow endogenous enzymes to develop (Hardwick, 1995). By controlling kilning temperature and time maltsters can produce various types of malts with different colors, flavors, and compositions. After malting, grains are milled to expose the cotyledon of the barley which contains most of the carbohydrates of the plant (Willaert, 2006). Grinding of the grains allows for better extraction of sugars, due to increased surface area during brewing, thus rendering the overall mass more “wettable.” After malting and grinding,

“mashing,” completed at a single temperature or in a multi-temperature system in the brew house, facilitates enzymatic conversions of the malt (Hardwick, 1995). During mashing the milled grains are mixed with water and heated to convert starches in the barley into fermentable sugar. This saccharification conversion is completed by the enzymes developed during malting. To finish this process and deactivate enzymes, the 7 temperature of the now sugar-rich solution, called wort, is raised to 75-78°C. “Sparging,” addition of warm water over the grains, may also be completed at this step to extract additional sugars. At the bottom of the mash tun (the vessel where mashing is completed) a false bottom allows for “lautering,” the separation of grain from the wort (Willaert,

2006). As the solids are removed the wort is pushed into the kettle for boiling.

Boiling is a major stage that affects flavor, color, and aroma of the final product.

This process terminates enzymatic processes, precipitates proteins, and concentrates and sterilizes the wort. Hops are also added during boiling to extract their aroma, flavor, and antibacterial qualities (Hardwick, 1995). After resting in the kettle to clarify, the wort is sent to the whirlpool to further separate solid particles from the liquid. The clarified wort is cooled through a heat exchanger as it is moved into a cleaned and sanitized fermentation vessel (Willaert, 2006). The wort is aerated before yeast is pitched in and fermentation begins. Fermentation is the process that turns the sugar of the wort into carbon dioxide and alcohol, in this case forming beer (Hardwick, 1995). After fermentation, temperature drop, and filtration much of the yeast is removed from the final beer product. The beer may then be allowed to age for flavor maturation, clarification, and chill proofing (the prevention undesirable haze). When ready for release the beer can be force carbonated and put into cans, bottles, and kegs. Additionally, under-carbonated beer may have sugar added, allowing the yeast to naturally carbonate the beer before serving (Hardwick, 1995). While this outlined process is common in modern breweries beer was not always made this way. The evolution of brewing and craft beer in the

United States is a notable model to show how this process and consumer’s palates and desires have changed over time. 8

Beer in the United States

Jackson (1977) found that early Native American tribes created fermented beverages with ingredients like birch sap and maize long before Europeans arrived and colonized. However, it wasn’t until 1632 that the first commercial brewery opened by

Dutch merchants in what is now Manhattan (Jackson, 1977). As additional colonies developed, more breweries opened and beer was produced throughout the land. Ogle

(2006) claims that until the mid-19th century British-style ales dominated the American market. Lager style beers were not introduced until German immigrants came to the US during the 19th century. As these immigrants began to establish breweries the popularity of lagers, which soured less quickly than ales, increased dramatically. Throughout the

1800s breweries such as Miller and Anheuser-Busch grew to industry giants. Beer production continued to rise until January 16, 1919 and the passing of the 18th amendment, which brought production to a halt. This amendment, supported by the

Temperance movement (one standing against the consumption of alcoholic beverages), made it illegal to produce, sell, and transport alcoholic beverages. The number of breweries throughout the US decreased significantly with many shutting down for good.

Larger breweries were able to weather the storm of prohibition by exploring other ventures such as production of soda, ice cream, malt extract, and “near beer,” a beverage less than 0.5% ABV (Ogle, 2006). In 1933 the Cullen-Harrison Act amended the prohibitive Volstead Act and allowed beer to be produced and sold up to 3.2% ABV. At this point it was believed that a beer low in alcohol was not “intoxicating” or a danger to health. By December of 1933 the 21st amendment repealed the 18th amendment, but the brewing industry was slow to recover (Ogle, 2006). Many states refused to repeal 9 prohibition and a large percentage of the breweries present before prohibition could not afford to begin producing again (Ogle, 2006).

The stress of World War II also slowed the recovery of the brewing industry, as grain supplies were needed for consumption and not readily available to brewers.

However, beer was soon used during the war to generate additional revenue through tax collection and it was given to soldiers for its nutritional benefits (Ogle, 2006). This wartime growth allowed for a few industry giants, such as Miller and Anheuser-Busch who still stand today, to develop a monopoly on the beer market that lasted for nearly 50 years. These breweries produced beer on a large scale for a low cost. The products were known for their uniformity and not particular flavors, as their beers all had little to none.

By the early 1970s, after consolidation of smaller breweries and the growth of few major breweries, the number of craft breweries in modern US history was at an all-time low.

This was the era of the “macrobrew,” a time that characterized American beer as poor in quality and flavor internationally (Bilefsky & Lawton, 2004). The major style of beer produced during this time, defined by the Beer Judge Certification Program (BJCP) as 1A. Lite American Lager, is still widely popular today. The BJCP is responsible for certifying industry judges while also publishing guidelines and standards for beer styles.

Under this style guideline two or six row barley may be used during brewing with up to

40% adjunct (such as rice and corn). Aromatically there should be little to no malt or hop aroma, and low levels of yeast character are acceptable. The beer should be a very pale straw or yellow, clear, and have a small short-lived white head. Hop bitterness should be extremely low to not present and overall it should have a crisp and dry flavor. Lite

American Lagers should be light in body, watery, refreshing, and thirst quenching. This 10 light colored, low alcohol, low calorie beer is designed to appeal to the widest range of consumers. In general, any strong flavors of any variety are considered a fault. Common commercial examples of Lite American Lagers include: Sam Adams Light, Heineken

Premium Light, Miller Light, Bud Light, and Coors Light (BJCP, 2008).

American beer has become less bitter over time. Despite their relatively low bitterness levels to begin with, Anheuser-Busch (A-B) beers have observed a “bitterness drift” over time (Hieronymus, 2012). The beer has become less and less bitter as a result of A-B changing recipes to make the beer palatable to all consumers. The overall beer is the same, changing only the hop profile, but the bitterness has decreased noticeably

(Hieronymus, 2012). Between 1972 and 1982 the same trend was observed in Miller Lite, which had decreased its bitterness levels by 20% in just 10 years (Hieronymus, 2012).

This phenomenon harkens back to the desires for low flavored beers from US consumers throughout time. Nineteenth-century Americans did not like the “bitter” and “sour” flavors of traditionally hopped malt beers (NYT, 1877). They desired the “sweeter” taste of light-bodied lagers that were rising in popularity (NYT, 1877). Consumers began to reject bitter, hoppy taste, and had become “so accustomed to a light colored beer that a beer colored somewhat darkly [was] considered of inferior or indeed bad quality,”

(Western Brewer, 1879). While brew masters and some consumers liked the full-bodied hoppy beers, the general public preferred “blandness,” (Tenney, 1951). Ogle (2006) reasons that generations of Americans born in the 1920s and 1930s had a much more limited and bland diet than those before them. People were starting to consume more processed foods and thus were used to a sweeter diet (Ogle, 2006). This could explain why consumers sought light, bland, and flavorless beer. Strong hop presence was too 11 bitter and flavorful for Americans during the 18th, 19th, and most of the 20th century (Ogle.

2006).

Satran (2012) calculated that in 2000 Anheuser-Busch still controlled 50% the beer market in the US. Of this share, Budweiser, a lightly flavored beer, accounted for

18% of all beer sold. Although American Lite Lagers were invented over a century earlier they were, and still are, considered desirable in the market. Despite the popularity of these beers, the US beer industry began to introduce new, flavorful, innovative beers toward the end of the 1970s. On October 14, 1978 H.R. 1337 was passed legalizing home brewing of beer and wine for personal consumption (Satran, 2012). Spurred by this law the US has seen a drastic increase in the number and success of craft breweries alongside a renewed sense of brewing culture amongst consumers.

In 2014 the Brewers Association (BA) defined American craft breweries as

“small, independent, and traditional.” Brewery production must be less than 6,000,000 barrels annually and less than 25% of ownership can belong to an alcoholic beverage industry member who is not the craft brewer. Microbreweries produce less than 15,000 barrels (17,600 hL) whereas regional craft breweries can produce between 15,000-

6,000,000 barrels (bbl). Brewpubs, which have less of a standard definition, are restaurants that serve food and produce 2,000 or less barrels of beer that is only served on premise. In 1994 the United States had only 329 brewpubs, 192 microbreweries, and 16 regional breweries. By 2014 those numbers had increased to 1,412 brewpubs, 1,871 microbreweries, and 135 regional breweries. During the 2014 fiscal year market shares were divided as follows: domestic beer (145,918,317 bbl, 74% total sales), import

(29,430,185 bbl, 15%), and craft (21,775,905 bbl, 11%). These shares amount to $101.5 12 billion in beer sales overall and $19.6 billion in the craft beer market alone. During this time period Pennsylvania produced 4,074,883 bbl of craft beer, making it the top ranked producer in the US (BA, 2015). The US craft beer revolution has led brewers and consumers to think about the quality of ingredients and flavors of the beers they are drinking. This has and continues to change the amount and varieties of beer in the market. New flavors, styles, and brands are disrupting the status quo of beer in the United

States.

Beer Color

Malt and color extraction

Beyond serving as sugar sources, malted barley and additional “adjuncts”, such as corn, rice, and oats, give beer its characteristic colors. Mallett (2014) explains that barley,

Hordeum vulgare, is one of the oldest cultivated cereal grains. As a grass the barley plant will produce several stems containing many nodes. Barley kernels contain both an embryo and a source of nutrition, an endosperm. The starch-rich endosperm, making up over 80% of the grains weight, is composed of starch granules embedded in a protein matrix. This structure is what releases fermentable sugars for yeast to consume during fermentation. Various other compounds are present in other areas of the kernel that are also important during brewing. Polyphenolic tannins are found in the tesla layer and ferulic acid (3-methoxy-4-hydroxycinnamic) in the seed coat and aleurone layer. Similar to wine, high levels of these tannins can produce bitterness and astringency. Ferulic acid 13 can produce clove-like aromas in wheat beers as it produces 4-vinyl-guaiacol (4VG) in the presence of yeast and tannins can contribute astringency (Mallett, 2014).

As discussed previously, color develops during the mashing and boiling steps of brewing when compounds are extracted from the grains and as additional compounds form (Mallett, 2014). Malt color is controlled by temperatures used during “kilning”

(Figure 2). Kilning occurs in two phases: drying at lower temperatures and curing at high temperatures, where most of the color compounds are developed. During this time enzymes are also deactivated. Levels of active enzymes are thus inversely proportional to malt color. Increased temperature and thus color during kilning generally increases flavor compounds in the malt (Fix, 1999).

Beer color develops through two major mechanisms: caramelization and Maillard reactions. Caramelization produces both roasted aromas and brown-colored chemical products. This process is a pyrolysis: the thermochemical decomposition of sugar. It begins at high temperatures: for example, 180°C for maltose and 160°C for glucose.

Caramelization can produce hundreds of different chemical products with different colors, flavors, and aromas. During kilning this reaction may form compounds such as ethyl acetate and diacetyl (Mallett, 2014). Maillard reactions occur between amino acids and reducing sugars, and are responsible for much of the aroma and taste of browned foods. This includes grilled meats, roasted coffee, baked goods, and the malted barley used in beer (Chichester, 1986). As an additional non-enzymatic browning reaction,

Maillard products contribute greatly to the color and flavor. The process proceeds in a step-wise fashion optimally between 140-165°C, but it can happen at room temperature.

Briefly, the carbonyl group of a sugar molecule reacts with the amino group of a protein 14 and produce a N-substituted glycosylamine. The glycosylamine isomerizes into a 1,2- enaminol compound before undergoing Amadori rearrangement to form a ketosamine.

Depending on the conditions of the reaction the compound can react to form one of a large variety of end products. Melanoidins are just one type of compound formed through this pathway that give beer a red-brown color and a roasted caramel-like flavor.

Additional classes of Maillard product are pyrazines, furanones, furans, pyrroles, and alkylpyridines (Coultate, 2002). Increased levels of these compounds will cause a beer to become browner and darken in color. Pale yellow beers are brewed with less roasted and highly kilned malts, so levels and extraction of these compounds are decreased (Mallett,

2014).

Measurement of color

Several different scales are used to describe and quantify beer color. For all methods, spectrophotometric absorbance is used with standard equations (outlined below). The EBC (European Brewery Convention) and SRM (Standard Reference

Method), identical methods with different scales, are the most commonly used methods.

These scales run from pale yellow to dark brown/black. SRM, standardized by the

American Society of Brewing Chemists (ASBC) is defined as:

�� = 12.7×�×�!"#

where D is the dilution factor (1 for undiluted samples) and A430 is the absorbance of beer at 430 nm (the chosen standard wavelength) in a 1 cm cuvette. Absorbance is read against a blank of deionized water (Stone & Miller, 1949). EBC simply replaces the 12.7 constant with 25. Therefore converting between the two systems can be accomplished by: 15

�� = ��×1.91

�� = ��×0.508 (Kumpanenko et al., 2014)

When analyzing grain, and historically beer, the Lovibond (°L) color scale is often used. In this method samples are placed into tintometers and compared to various slides of colored glass. Lovibond color is determined by matching samples to corresponding tinted slides. For grain samples, wort is made from tested grain under standard conditions before being graded a certain color (Gibson & Harris, 1925). Another method used in other food-product color analysis applications is tristimulus analysis (also known as CIELAB [Commission Internationale de l'Eclairage L* A* B*]). This multi- wavelength method, based on absorbance’s between 380 and 720 nm, provides for more accurate readings allowing for better comparison of shifts in or differences between samples. Using the multiple readings data is transformed onto a three-dimensional color scale with the coordinates L*, a*, and b*. These coordinates correspond to lightness (L*), the red-to-green component (a*), and the yellow-to-blue component (b*) (ASBC, 1958).

An example of the color scale used by brewers is shown below in Figure 3. In all methods darker beers may be diluted (with deionized water) and turbid beers centrifuged before readings. However, SRM will be used in this experiment as it used most frequently in brewing industry literature.

Darkening techniques

Brewers can control the color and flavor intensity of beer by changing the levels or types of malt in the grain bill. Darkening beer color while making minimal changes to the aroma and flavor characteristics is a challenge faced by many brewers. Two methods 16 of achieving this are: the use of black malt during brewing and the addition of a malt based dyeing agent, such as commonly used Sinamar®.

Black malt is also commonly referred to as Black Patent or Black Prinz. Mallett

(2014) explains this name is a remnant of the patent on the process originally discovered in Germany. Black malt, regularly used in porters and stouts, is roasted to a point of near flavorlessness. This bitter, nearly burnt, black malt flavor comes from a high concentration of pyrazines, especially alkyl-pyrazines (Foster et al., 1998). As the grain is nearly incinerated during malting it is able to provide 435-550 SRM to beer during brewing. Husk material of barley contains high levels of astringent tannins, by removing this before malting grain is considered to be “de-bittered” (Mallett, 2014). This allows for the addition of color, but not acrid bitterness. While some report that black malt should not exceed 1% of the total grist weight, others indicate that up to 3% is appropriate

(Riese, 1997). Coffee-like, smoky, and acrid bitter flavors are possible if used in excess

(Gruber, 2006). It is not until 3-4% that flavor changes may become noticeable, there should also be no change in foam color below 3% (Gruber, 2001).

Some brewers have begun using specially formulated malt extracts to eliminate the possibility of black malt influence over flavor. Sinamar® is a roasted Carafa malt extract made by Weyermann® Specialty Malts. This extract follows the Reinheitsgebot

(German Beer Purity law), remains pH stable, causes no turbidity, is gluten free, and can be used in a variety of products including: beer, baked goods, non-alcoholic beverages, and pharmaceutical products. The color of the extract itself is between 4114-4369 SRM, and 16.5 g (14.0 mL) can be used to darken one barrel of beer by 0.60 SRM

(Weyermann, 2015). In home-brewing volumes 4 ounces of sinamar can darken a 5- 17 gallon batch by 16 SRM. Despite offering a huge shift in color, Sinamar® has relatively little flavor, so it is a viable option for a beer with a desired dark color but low roasted malt flavor (Mallett, 2014). The process of making Sinamar® begins with roasting debittered barley at extreme temperatures before being used to make a low ABV non- hopped beer (Dornbusch, 2005). During the slow lautering process bitter compounds are trapped within the grain and do not move on to the kettle. During this boil unpleasant aromas are driven out of the wort. An increased whirlpool step can also extract more of the undesirable bitter compounds, before fermentation (Dornbusch, 2005). After filtration, evaporation, and sterilization of the finished beer all residual particles and remaining bitter substances are removed from the product along with carbon dioxide, water, alcohol, volatile oils, and aromatics (Dornbusch, 2005). The final sterile product is then packaged into hermetically sealed containers to be used either during brewing or post fermentation (Dornbusch, 2005).

Beer Bitterness

Hops and bitterness extraction

Hops, Humulus lupulus, are the ingredients usually responsible for the bitter flavor and characteristic aromas in beer. This species is divided into five subspecies including: H. lupulus var. lupulus, H. lupulus var. cordifolius, H. lupulus var. neomexicanus, H. lupulus var. pubescens, and H. lupulus var. lupuloides. Two additional species, Humulus japonicas and Humulus yunnanensi, exist but are not relevant in the brewing industry. Hop plants grow successfully in temperate climates between 30- 50° on both sides of the equator. As perennial, herbaceous plants, hops do not exhibit much secondary growth and can live to up to 20 years (UW-L, 2012). Annual harvesting of 18 hops begins late in August, allowing time for the cones to ripen and dry, increasing alpha and beta acid content. Whole “leaf” or flower hops can be used, but many industrial breweries and home brewers use processed hop products like pellets or extracts. These processed products require less storage, produce stronger aromas and flavors, and retain freshness better (Gales, 2010). While a dioecious plant, only the female hop cone, or flower, is of value to brewers (UW-L, 2012). Bracts and bracteoles, small bracts, are the leafy structures connected to the central axis, which make up the cone. Underneath the bracts are the lupulin glands (Figure 4), responsible for the production of chemical compounds, such as resins and essential oils, considered desirable in beer (Gales, 2010).

Chemical composition of hops, with approximate percentages, include: alpha acids (2-12%), beta acids (1-10%), essential oils (0.5-1.5%), polyphenols (2-5%), oil and fatty acids (traces to 25%), protein (15%), cellulose (40-50%), water (8-12%), pectin

(2%), and salts [ash] (10%) (Verzele, 1986). The structures of the most common compounds can be referenced to in Figure 5. Alpha (α) acids (AA), consisting of humulone and its analogs are responsible for the bulk of hop bitterness in beer (Fix,

1999). Analogs, with approximate percentages, include three major compounds,

Humulone (35-70%), Cohumulone (20-55%), and Adhumulone (10-15%), and small percentages of Prehumulone (1-10%) and Posthumulone (1-5%) (Verzele, 1986).

Characteristics of hops depend on levels of each compound and where they were grown.

Cohumulone is more soluble than the other analogs, but it is thought to give a more harsh bitterness (Fix, 1999).

Alpha acids alone are not bitter compounds and have very low solubility in water, therefore beer. During the boiling of wort during brewing these compounds are 19 isomerized to form iso-alpha acids (IAA). In humulone, the bond between the first and sixth carbon is broken and a new one is formed between the first and fifth forming iso- humulone. After isomerization (Fig 6), the resulting iso-alpha acids are much more soluble than alpha acids and nearly four times as bitter (Hieronymus, 2012). Iso-alpha acids also have bacteriostatic effects on many gram-positive (some resistant strains exist), but not gram-negative bacteria. This is particularly important in preventing contamination from common beer spoilers such as Pediococcus and lactic acid bacteria (Sakamoto,

2003). Beyond bittering potential, iso-alpha acids and other hop compounds also promote stability of beer foam, act as a preservative, and help improve clarity by coagulating water-insoluble proteins (Sidor, 2006).

Beta (β) acids, another class of compounds extracted from hops, do not play as prominent a role in beer production. Primary beta acids, and common composition percentages in hops, include: Lupulone (30-55%), Colupulone (20-55%), Adlupulone (5-

10%) (Verzele, 1986). Beta acids are not soluble, nor do they isomerize and become more soluble during boiling. Hieronymus (2012) explains that recent studies have found that other beta acid transformation pathways may be responsible for causing bitterness during boiling. Oxidation products of these acids, like hulupinic acid and other soluble non-humulone compounds, can be quite bitter, water-soluble, and found in final beer products (Hieronymus, 2012). Beta acids have also exhibited antiseptic qualities, improving shelf life, and aiding yeast in their ability to grow (UW-L, 2012).

Plant materials, hops included, contain volatile essential oils, which are commonly used in food and flavor chemistry. Myrcene, Humulene, and Caryophyllene 20 represent 80-90% of total hop essential oils (Verzele, 1986). Sidor (2006) describes that during boiling most essential oils are carried off with the steam, but some may remain from late addition of hops during brewing. “Dry hopping,” the addition of hops during fermentation while aging, can also add to the aroma of the beer while not adding significant bitterness (Sidor, 2006). Essential oils include hydrocarbon, oxygen-bearing, and sulfur-containing components. Hydrocarbon components include Myrcene,

Humulene, and Caryophyllene, composed of either monoterpene or sesquiterpene compounds. Oxygen containing components tend to provide floral and herbal aromas where sulfur-containing components are considered a flaw in beer (Fix, 1999).

Measurement of bitterness

Peacock (2009) explains that research into analytical methods to measure bitterness began in the mid-1800s. Over time, chemical testing methods developed to measure perceived bitterness and not iso-alpha acid content. These methods were meant to analyze the overall bitterness of a beer, including both iso-alpha acids and oxidized beta acids in measurement. The International Bittering Units (IBU) scale is used in the brewing industry to rate bitterness levels in beer. Current methodology is believed to measure both iso-alpha and non-iso-alpha (oxidized beta acids) hop bittering material.

IBU measurement does not take into account differences in flavors or between the various IAA homologs, such as iso-n-humulone, iso-cohumulone, and iso-ad-humulone

(Peacock, 2009). Starting at 0, the scale is thought to consistently measure up to 100, the presumed maximum threshold of bitterness perception. Past 100 the measurement is not considered as accurate or representative of a beer’s bitterness. Mosher (2009) claims the human threshold for detection of bitterness in beer has been determined to be 6 IBU. Six 21

IBU is also the approximate limit of discrimination between levels of bitterness (Mosher,

2009).

Estimated IBUs can be calculated using mathematical equations. While there are three widely-used equations: Rager, Tinseth, and Garetz, the Tinseth is generally considered the most accurate and is the most widely used (Palmer 2006). Thus IBU can be calculated using the following equation:

��×�×75 IBU = �!"#$%"

Where AAU is alpha acid units, U is utilization, and V is the total volume of the recipe.

AAU can be determined by multiplying the weight of hops used (in ounces) by the reported percent alpha acid of the hop variety used (Palmer, 2006). Utilization, the most significant factor, expresses the efficiency of the isomerization of alpha acids into iso- alpha acids. During boiling, not all alpha acids will be converted into iso-alpha acids.

Hop type, contact time, pressure, and temperature all alter the effectiveness of this process (Fix, 1999). This numerical value, a function of boil gravity and time, is found in standardized charts (Palmer, 2006). The Tinseth will be used in this experiment to determine extraction efficiency.

This equation only yields an approximate IBU level. During brewing other factors, such as the intensity of the boil and the true alpha acid content of hops used affect the bitterness intensity level. The ASBC (1975) has a standardized laboratory method for chemically quantifying IBUs of beer. In general, a beer sample is acidified with 6N HCl 22 before being extracted with isooctane (2,2,4-trimethylpentane). This acidification drives alpha acids out of the beer as their solubility in water decreases. The beer and isooctane are emulsified by vigorous shaking to allow for increased contact time and extraction.

After centrifugation the isooctane layer is read against an isooctane blank at 275 nm on a spectrophotometer. IBU is calculated by multiplying the recorded absorbance by 50

(ASBC, 1975). Bitterness may be completed on wort diluted with deionized water. As with all testing, manual isooctane extraction does not extract all bitter compounds in the beer. There is also no relationship between numerical IBU and the quality of hop flavors

(Fix, 1999). IBU cannot necessarily define how bitter a beer will taste as malt sweetness and other aromas or flavors may mask or amplify bitterness (Shellhammer, 2009).

Polyphenols from both the hops and malt can contribute bitterness to beer. Extremely dark beers, darkened with large amounts of black malt, can have a slight acrid bitterness from melanoidins and pyrolysis products (Shellhammer, 2009). Despite not taking all compounds or sources of bitterness account measuring IBUs offers a method to measure consistency of relative beer bitterness. It will be used accordingly in the following study to ensure all beers are within the same levels of bitterness.

Perception of bitterness

Depending on the food product and the palate of the human consumer, bitter taste has potential to be either desirable or unpleasant. Throughout nature bitter taste often indicates toxic compounds, signaling the individual not to taste or consume further

(Levin, 1976). It is often believed that disliking of bitterness is an innate trait that allowed for our increased chances of survival. However, recent findings have actually disputed the idea that aversion to bitter compounds is innate. Hieronymus (2012) explains that one 23 study, based on reactions of newborn infants (up to six days old) and older infants

(between 2 weeks to six months old), found minimal rejection of bitterness by newborns while older infants constantly rejected bitterness. It appears there are early developmental changes in regard to reception of bitterness, and that a dislike for bitter taste may be learned or acquired (Hieronymus, 2012). This also mean that a liking of bitterness could be learned (Hieronymus, 2012). While liking of bitter tastes can be learned, there are also many genetic factors which may influence tasting ability.

Arthur Fox, a chemist at DuPont in the early 1930s, determined that some individuals found the compound phenylthiocarbamide (PTC) to be bitter while others did not (Bartoshuk, 2000). Over time PTC was replaced with propylthiouracil (PROP), a safer alternative chemical. In the early 1990s Linda Bartoshuk and her research colleagues coined the phrase “supertaster” to describe any individual with increased taste response to these bitter compounds. They determined that tasters made up 50% of the population with supertasters and non-tasters both comprising 25% of the population.

Their research also indicated that women, with more taste pores and fungiform papillae than men, are more likely to be supertasters (Bartoshuk, 2000).

Categorization as a supertaster and the ability to taste bitter compounds have been linked to TAS2R, taste receptors type 2, particularly TAS2R38. TAS2R proteins are human taste receptors responsible for the perception of bitterness. This family is thought to have 25 different taste receptors with the potential to identify a large range of compounds. These receptors are coupled to the G protein gustducin, transimitting signals, and allowing perception of bitter flavor (Intelmann et al., 2009). Figure 7 outlines the general pathway of G proteins. A ligand, in this case iso α-acid, binds to the receptor and 24 causes conformational change. This change allows the receptor to exchange guanine diphosphate (GDP) to guanine triphosphate (GTP), activating the G protein. Protein subunits are then able to separate and activate target proteins, causing a cellular response.

While the pathway is not completely elucidated, it is thought that cyclic nucleotide

(cNMP) levels decrease during this process. This decrease may then act on protein kinases which are responsible for regulation of taste receptor cell ion channel activity, thus taste perception (Margolskee, 2002). As discussed previously, the TAS2R38 gene on chromosome 7 has been linked to the ability to detect the thiourea drug PTC. Differences in threshold perception are due to three single-nucleotide substitutions (SNPs) that form

Proline-Alanine-Valine (PAV) and Alanine-Valine-Isoleucine (AVI) haplotypes. These haplotypes, or DNA variations, cause changes individuals in genotypes (a collection of their genetic information), which is observed through their phenotype, characteristics that can be observed (such as not tasting PTC). The PAV haplotype, giving the ability to taste

PTC, is considered ancestral while the AVI halotype is less functional. While these variations are important in understanding bitterness reception they are not able to explain supertaster ability (Hayes et al., 2013).

To determine how hop compounds are related to bitter perception Intelmann et al.

(2009) transiently transfected plasmids for the 25 human TAS2Rs into human embryonic kidney 293T cells. These cells express the protein G16gust44 and investigators paired activation of the hTAS2R receptor with the release of calcium. Cells were loaded with fluorescent calcium dye and exposed to 15 hop derived compounds, such as alpha acids, beta acids, and iso-alpha acids. At some threshold all compounds were found to activate combinations of each of three bitter taste receptors, hTAS2R1, hTAS2R14, and 25 hTAS2R40. Chemical thresholds were determined to be lower than those determined by human tasting. Therefore it took higher concentrations of substances for subjects to the detect bitterness than in vitro experiments. This may be due in part to interaction in the oral mucosa disrupting more sensitive perception. Evidence suggested that bitter receptors may be activate by several different agonists. For example, α-thujone, a compound found in absinthe has also been found to activate the hTAS2R1 receptor.

There also appears to be redundancy in activation as a single compound can activate more than one receptor (Intelmann et al., 2009). While recent experiments have begun to elucidate the pathway of bitterness taste reception in humans (and specifically bitterness in beer), more research is necessary.

Sensory Evaluation

Throughout the food industry completing sensory evaluation is a critical point during research, development, and quality testing on products. While biological and chemical testing are important and often necessary for regulation and compliance they tell you little information on how a product is perceived (Lawless & Heymann, 2010).

Sensory evaluation can be used numerous ways ranging from whether consumers will like a proposed product to determining if a minute change in a formulation will be detectable. This allows for the generation of feedback data which can be used to make informed decisions and actions. There are a large number of experiment setups, test protocols, and analytical techniques that may be used throughout sensory evaluation. As taste, let alone perception of food in general, is a complex mechanism it is important to ensure that testing is appropriate. 26

In sensory evaluation discrimination testing, also known as difference testing, is used to determine if there is a detectable sensory difference between samples (Lawless &

Heymann, 2010). There are a number of different discrimination tests. Throughout

discrimination testing a null hypothesis (H0) is defined as there being no detectable difference between the samples, as opposed to the alternative hypothesis (HA) that there is a detectable difference. During testing, results can reject the null hypothesis but not accept the alternative. That is, in each test there is a certain probability (for example, 1/3 for the triangle test) that participants are guessing correctly, and the null hypothesis is formulated to account for this (Lawless & Heymann, 2010).

One test used commonly by sensory analysts in the brewing industry is the triangle test. Melgaard et al. (2007) states that it is commonly used to determine whether ingredient changes or slight alterations to a product make it noticeably different from the original. For this method panelists are asked to taste three samples and indicate which (of the three) is different. This test is simple to run but should not be used in situations where fatigue or carry over effects may be a problem (Melgaard et. 2007). Analysis of this data can be completed by using the normal approximation to the binomial distribution:

� − �� − 0.5 � = ��

Where X is the number of correct responses, n the total number of responses, p the probability of correct decision by chance (1/3 for triangle test), and q=1-p. Significance 27 is determined by comparing the calculated value to the critical Z-value for a one tailed test of 1.645 when p < 0.05 (Lawless & Heymann, 2010).

Affective consumer testing is used to collect and analyze liking and consumer data. This type of test is completed when investigators want to know how products are liked or accepted. Affective tests can be used for: product maintenance, improvement, optimization, development of new products, assessment of market potential, or even support for advertising claims. These tests will allow producers to known if characteristics of a product are still acceptable after a change or whether changes to a product are necessary.

Qualitative methods examine consumers “feelings” about a product. This is often accomplished in focus groups, panels, and through one-on-one interviews. Affective tests can be broken down into quantitative (preference and acceptance) protocols. Preference testing more so deals with ranking while acceptance is based on scaling. Quantitative methods collect data on overall consumer liking, preference, and perception of products.

These tests can ask participants to rate, rank, or choose which products they like

(Melgaard et. 2007). Commonly a 9-point hedonic scale (ranging from “like extremely” to “dislike extremely”) is used to measure acceptance. Data collected using this scale can be analyzed using a parametric statistical method. In the following study a paired t-test will be used to determine significance.

Participants in sensory studies may also be asked to rate a product for certain attributes on a scale anchored with defined terms such as “not present” to “extremely present.” ANOVA analysis can determine significance of data collected in this manner.

Consumer testing is a valuable tool in both industry and research to display how a 28 product will be accepted. When completing these tests several demographic questions may be helpful in data analysis and product formulation. These categories can include age, gender, income, nationality, geographic location, and whether participants actually use the product. This can give insight into the collected data and may help answer specific questions. These tools have been used to analyze the relationship of color and flavor throughout the food industry.

Throughout the current study a variety of sensory evaluation techniques will be utilized. Discrimination testing, in the form of triangle testing, will be used to determine if there is a significant difference between the two outlined darkening techniques. Several triangle tests will also be employed to determine if beers darkened for color perception testing are significantly different. All triangle (discrimination) tests will be analyzed using the normal approximation to the binomial distribution. Perception of bitterness will be completed using affective testing. This data will be analyzed using a one-way

ANOVA with repeated measures. Sensory data was collected and analyzed to determine how a consumer’s preconceptions can drastically alter how beer with known chemical characteristics is perceived.

Relationship between Color and Flavor

Despite the differences in perception of color and bitterness in beer there are still trends and beliefs implying that they are related. The appearance of a food plays an important role in determining how consumers perceive and like a product. A classic chemosensory experiment tested participants’ threshold for salty, sour, sweet, and bitter 29 tastes in dyed aqueous solutions. In most cases levels of the flavoring compound had to be increased in colored solutions for participants to detect their presence (Maga, 1974).

Additional studies found that darker colored sweetened solutions were rated 2-10% sweeter than light colored solutions (Spence et al., 2010). In general it has been observed that higher colored solutions provoke a stronger flavor evaluation (DuBose et al., 1980).

Despite many researchers reporting significant crossmodal effects between the intensity of a food or drinks color and perceived flavor intensity many others have failed to demonstrate this effect (Spence et al., 2010). Often, experiments that found no significant result between color and flavor intensity did not have sufficient power or a large enough sample size to draw conclusions (Spence et al., 2010). Color-induced expectancy, such as citrus flavor for an orange colored solution, has been indicated in influencing flavor perception and identification (Spence et al., 2010).

The International Organization for Standardization (ISO) defines flavor as a

“complex combination of the olfactory, gustatory and trigeminal sensations perceived during tasting. The flavor may be influenced by tactile, thermal, painful and/or kinesthetic effects.” While comprehensive this definition does not fully capture the combination of sensations that an individual undergoes while eating and drinking. When a product has a strong odor or taste-and-color association, the impact color has on perception increases greatly. For example, in white wine that was colored red participants tended to describe red or dark objects instead of yellow or clear objects as used with the white uncolored wine (Delwiche, 2004). Koch & Koch (2003) studied the effects of colors (such as red, green, yellow, blue, brown, orange, purple, black, gray, and white) on flavor expectation (sweet, sour, bitter, and salty) in soft drinks. Participants in this study 30 were asked to rate proposed sodas on a questionnaire ranging from 1 (least) to 10 (most) for each flavor. Interestingly there was a significant relationship for black and bitter, but it was a bi-modal relationship, the only of this nature in the study. Twenty-three respondents indicated no relationship between black and bitter while 17 indicated a strong relationship (Koch & Koch, 2003).

The color of food packaging or serving vessel can have an effect on the perception of flavor. In one study, by Van Doorn et al. (2014), examining coffee served in a white, blue, or clear mug found that a white mug increased the “intensity” of the coffee. The brown color of the coffee was associated with bitterness (and negatively associated with sweetness) (Van Doorn et al., 2014). This blur in definitions between

“strong,” “heavy,” “dark,” and “bitter” is also present in beer. Zellner & Durlach (2003) found that in other beverages a dark or brown color resulted in lower refreshment ratings.

Participants in these studies indicated that they had a strong expectation of how color would impact refreshment, pleasantness, and intensity of beverages (Zellner & Durlach,

2003).

Training and past experiences will affect how beer is judged and organized. In one study, by Lelièvre et al. (2009), the effect of training and visual observations on beer categorization was examined. Three types of beers (blonde, amber, and dark) were chosen from three different breweries (Pelforth, Chti, and Leffe) yielding nine total samples. Both trained and un-trained participants were asked to group beers into categories in one of two test conditions: visual (where they could smell, taste, and see the beer) and blind (where colors of beer were masked in booths with red light). In the visual condition both trained and un-trained participants categorized beers into groups based on 31 color. This was unexpected for trained participants; as they usually taste beer in blind conditions, authors believed they should have relied more on other characteristics over color. It indicated individuals tend to rely on visual cues over chemosensory information.

Trained participants were also not brewing professionals, but trained in general sensory analysis. Another unanticipated results was participant’s grouping beers by brewery (and not by style) in the blind condition. In this case the “house character” such as yeast or ingredients used could have cause the grouping (Lelièvre et al., 2009). There was not an effect of training on organization as all assessors used visual observations before chemosensory properties of the beer samples.

Smythe et al. (2002) recounts that in the early 1990s Miller Brewing Company developed yet failed to sell consumers on a perfectly clear beer. This failure indicated that beer color plays a large role on acceptability and perception of the product. Based on this, a study at the University of California-Davis created three beers of varying colors and asked participants to rank beers for a variety of test categories (Smythe et al., 2002).

Beers brewed included a 2.3 SRM pale lager, a 3.0 SRM lager, and a 8.1 SRM ale. Each of three beers was poured live three times in front of the participants. For each beer, the first glass was filled and emptied, the second glass filled and emptied halfway, and the third filled and left full. These different pours would allow participants to observe characteristics of the beer, but they were not allowed to taste, smell, or touch them during this study. Participants were asked to rank the beers (first, second, and third) for attributes including: best to worst (poured, handled, brewed, head, overall flavor, and overall appearance), most to least (carbonated, stable foam, fresh, thirst quenching, bitter, sweet, off-flavors, likely to buy), greatest to worst drinkability, and highest to lowest alcohol 32 content. With 16 participants the dark 8.1 SRM beer was ranked most bitter, with the highest alcohol content, and the best overall appearance. In contrast, the lighter 2.3 SRM beer was ranked the least bitter, with the lowest alcohol content, and the worst overall appearance. The small sample size or perceived assignment of a specific beer style to samples by participants could both have played a role in the collected results. A large test population could work to remedy this possible point of error (Smythe et al., 2002).

As discussed, beer color develops from the kilned malt during the brewing process. This malt adds roasted, caramel, and bread-like characteristics to beer, but rarely any bitterness. If black, or other highly kilned, malts are used excessively they can produce acrid bitter compounds. With this in mind brewers use extract alternatives or only small percentages of black malt to add color but not flavor to their beers (Mallett,

2014). Bitterness in beer is derived from the hops added during the boiling step. Alpha acids isomerize into iso-alpha acids, which are perceived as quite bitter by humans. The addition of hops will have negligible changes on color while drastically adding bitterness to the flavor profile (Hieronymus, 2012). While certain food products do show a correlation between color and type or intensity of flavor beer does not. There is no absolute relationship between beer color and how bitter it tastes.

Specific Objectives

As described above there is a common misconception that a dark-colored beer will be more bitter than a lighter yellow beer. In this study beers will be developed to test this belief in the general population. During the first phase two different darkening 33 methods—black malt versus a malt-based dye—will be explored to determine if there is a detectable difference between these darkened beers and a yellow beer during blinded tastings. After determining a successful method to darken beer, three beers (yellow, red/brown, and black), will be brewed for a larger consumer sensory evaluation.

Participants will rate these beers for perceived bitterness and liking while they are able to observe the color. Chemical quantification (for color and bitterness) will be completed alongside sensory evaluation to confirm these results. It is the hope of investigators to observe color-flavor interactions in beer, specifically the relationship between beer color and bitterness.

Hypotheses

Throughout this study it is expected that:

I. There will be no chemical or perceived sensory difference between darkening

beer with Sinamar and a dark malt during brewing.

II. Beer brewed with darkening agents will not be discriminable from un-darkened

beer.

III. Consumers in Philadelphia (represented by Drexel University students, staff, and

faculty) will perceive a darker colored beer as more bitter, despite color being the

only changed variable.

Figures and Tables Figure 1: Overview of brewing

• Barley is steeped, germinated, and kilned to develop enzymes and coloring compounds Malting

• Malt is crushed to expose starch-rich cotyledon and increase surface area on grains Milling

• Water and malt are heated to extract color and convert starches into fermentable sugars Mashing

• Solids are seperated from the sugar-rich wort solution Lautering

• Wort is boiled with hops to deactivate enzymes, add flavor, clarify, and sterilize Boiling

• Wort settles to seperate additional solids before cooling through a heat exchanger Whirlpool

• Yeast is pitched into wort and allowed to convert sugars into alcohol and carbon Fermentation dioxide

• Beer is allowed to age to remove unwanted flavors before filtration and carbonation Conditioning

• Finished product is bottled, canned, kegged, or filled into a cask for consumption Packaging

Steps involved in brewing beer on an industrial scale. This basic outline may have additional steps or changes depending on technique or beer style. 35

Figure 2: Malt Types

Intensity of color and roasted flavors can be controlled during the kilning of barley. A higher temperature will produce a darker (toward black) malt (MAGB,2015).

Figure 3: EBC/SRM Scale

A visual representation of the EBC and SRM scales used by brewers to quantify beer color (BJCP, 2008).

Figure 4: Hop Flower Anatomy

The hop cone, or flower, is responsible for giving beer its floral aroma and bitterness. Bittering compounds are produced by the lupulin glands

and extracted during boiling (UW-L, 2012).

Figure 5: Compounds extracted from hops

Chemical compounds extracted from hop flowers or pellets during the boiling step of brewing. Extraction of hops is responsible for the flavor and aroma of beer. These can be broken down into three main types: alpha acids, beta acids, and essential oils. 37

Figure 6: Isomerization of Alpha Acids

Alpha acids, extracted from the lupulin glands of hops, do not have a bitter flavor. However, during boiling the alpha acids are isomerized into iso-alpha acids with a much more bitter flavor. This mechanism outlines the structural changes during isomerization.

Figure 7: G protein pathway

Generalized pathway showing activation, action, and termination of G protein activity (Reece et al., 2013). 38

Chapter 3: Beer Production and the Brewing Process

Materials and Methods Material acquisition

The yeast, Saccharomyces cerevisiae (WLP002 English Ale Yeast) cultures were prepared by White Labs Inc. Citra™ in San Diego, CA. Hop pellets were prepared by

Hopunion LLC in Yakima, WA. All crushed grains, dry malt extractions, hop pellets, yeast cultures, and fermentation equipment was obtained from Keystone Homebrew

Supply in Montgomeryville, PA. Crushed grains were prepared on site and were composed of 1 part Briess Crystal Malt 20° L and 1 part Munton Carapils Malt 20° L.

Briess Midnight Wheat was also obtained from Keystone Homebrew Supply.

Weyermann Sinamar® was obtained from Midwest Supplies online homebrewing store based out of St Louis Park, MN. Figure 8 displays some of the different brewing ingredients.

Brewing procedure

Throughout this investigation two major brewing trials, darkening testing

(Experiment 1) and color perception testing (Experiment 2), occurred (Fig 9). Darkening testing was completed to determine the difference (if any) between darkening a beer with

Sinamar® or black malt during brewing. After completing the test the chosen darkening method was then used to create three different colored beers in Experiment 2. In both cases, brewing methods were adapted from the American Pale Ale procedure outlined by

Keystone Homebrew Supply (2015). 39

Darkening testing for Experiment 1 (Fig 9a) included developing a light yellow beer (L), a dark brown beer made with black malt grain (DG) and a dark brown beer made with Sinamar® (DS). To develop the light beer, 454 g of cracked grain (Briess

Crystal Malt 20° L and Munton Carapils Malt 20° L) was divided into three muslin bags, added to 9.5 L of cold water, and then heated slowly. After thirty minutes 2722 g of

Munton Extra Light Dried Malt Extract was added and brought to a boil. At boiling, 21.3 g of Citra hops were placed into a muslin bag and added to the boiling mixture. This was repeated at 30, 50, and 58 minutes of boil with 7.09 g, 14.17 g, and 14.17 g of hops respectively. After the full sixty-minute boil all of the muslin bags were removed and the mixture was poured into a clean and sanitized five-gallon plastic fermenter. An additional

9.5 L of cold water was poured into the boil fermenter and mixed. This wort was then divided evenly between two cleaned and sanitized fermenters. One was left untreated (L) and one had an addition of 120 mL Sinamar® (DS) added. After cooling below 27°C, 45 mL of the prepared WLP002 English Ale liquid yeast culture was vigorously mixed into solution. Each fermenter lid and airlock were placed on top of the fermenters and beer was allowed to ferment at ambient temperature for two weeks. DG was created separately following the same steps except for the addition of 141.7g of Briess Midnight Wheat and the fermentation of this beer in one fermenter.

Brewing for Experiment 2 (Fig 9b) was comprised of developing a light yellow

(L), medium brown (M), and dark black (D) beer. This was completed by making a triple sized base batch of beer L before splitting into thirds at fermentation with the addition of various levels (outlined below) of Sinamar®. To develop the light beer, 1362 g of cracked grain (Briess Crystal Malt 20° L and Munton Carapils Malt 20° L) was divided 40 into three muslin bags, and added to 28.5 L of cold water then heating slowly. After thirty minutes 8166 g of Munton Extra Light Dried Malt Extract was added and brought to a boil. At boiling, 63.90 g of Citra hops were placed into a muslin bag and added to the boiling mixture. This was repeated at 30, 50, and 58 minutes of boil with 21.27 g, 42.51 g, and 42.51 g of hops respectively. After the full sixty-minute boil all of the muslin bags were removed and the mixture was divided into three clean and sanitized five-gallon plastic fermenters. An additional 3.2 L of cold water was poured into the boil fermenter and mixed. At this point Sinamar® additions were completed: 0 mL (L), 100 mL (M), and 240 mL (D) were added respectively. After cooling below 27°C, 45 mL of the prepared WLP002 English Ale liquid yeast culture was vigorously mixed into solution.

Each fermenter lid and airlock was placed on top of the fermenters and beer was allowed to ferment at ambient temperature for two weeks

Hydrometer readings

Hydrometer readings were completed for each beer brewed. Before transfer into the fermenter a sample of the wort was taken and tested with a Triple Scale Beer and

Wine Hydrometer, 60°F. After floating the hydrometer in the testing jar and dislodging bubbles, a figure was determined by reading where the liquid cuts across the stem. This original gravity was recorded to three decimal places. This process was repeated after fermentation and a final gravity was recorded. Readings were corrected based on the temperature of wort being read by a standard provided with the Triple Scale hydrometer.

The alcohol by volume (ABV) of the finished beer was determined by using a standard equation as follows:

ABV = (Original Gravity – Final Gravity) x 131.25 (Papazian, 2003). 41

Bottling procedure

For bottling, standard 12 oz. amber long neck bottles were used. Bottles and bottling buckets were sanitized with Star San Acid sanitizer, rinsed, and allowed to dry before filling. From fermenters beer was transferred into the bottling buckets using a

Fermtech auto-siphon and 5/16 inch food grade tubing. During transfer 142 g of priming sugar was dissolved in 470 mL of water and mixed into the fermented beer. In the case of split batches this was divided evenly among batches. The tubing and filling gun were then sanitized and connected to the spigot of the bottling bucket. Bottles were filled according to standard home brewing procedure and capped using U.S. size crown caps and an Emily Red Bottle capper. Bottled beers were then sealed into divided cases and allowed to age at 70°F for three weeks.

Results

Brewing procedure

Throughout Experiment 1 brewing 2.5 gallons (~9.5 L) each of L and DS were produced while 5 gallons (~18.9 L) of DG was produced. From the base 15 gallon (~56.8

L) boil, 5 gallons (~18.9 L) each of L, M, and D beer were produced. Experiment 1 beer was brewed and fermented throughout August 2015 while Experiment 2 testing beer was brewed and fermented throughout September and October of 2015.

Hydrometer readings

All wort samples had an original gravity of 1.056 and a final gravity of 1.014.

Using the standard ABV equation it was determined that the final beers had an alcohol content of 5.513%.

Bottling procedure

Each recipe produced forty-eight 12 ounce (~355 mL) bottled samples of beer.

Within darkening testing, 24 bottles of both L and DS beer were produced while 48 bottles of DG were produced. Within color perception testing 48 bottles of L, M, and D beer were each produced.

Discussion

The initial darkening test was completed to compare two potential methods to be used later in this study. Both the use of Sinamar® and addition of black malt during brewing have been found to effectively darken beer color while remaining fairly flavor neutral (Mallett, 2014). Chemical testing (Chapter 4) and subsequent sensory studies (see

Chapter 5), found there was no statistically significant difference (p < 0.05) between darkening methods. Sinamar® was selected for use throughout color perception testing for its ease of use. By adding it right before fermentation a larger volume of base yellow

(L) beer could be brewed without the addition of additional malt during brewing. The use of Sinamar® also allowed for greater precision through volume control during beer darkening. 43

Figures and Tables

Figure 8: Specialty ingredients used during brewing

Ingredients used during darkening testing. A) Base malt, commonly used during brewing production, contributes little color and flavor. B) Black Malt and C) Sinamar were both tested for their flavor impact and darkening ability. 44

Figure 9: Overview of brewing protocol

M D

Visual representation of brewing steps during both a) darkening testing and b) color perception testing. Experiment 1 darkening testing (a) was completed first to determine which method would be used throughout color perception testing. In darkening testing Sinamar® was used to darken a portion of base L beer before fermentation. Black malt was added during the mashing step of an additional batch of this base beer to compare darkening methods. While not statistically different, Sinamar® was used throughout Experiment 2 color perception (b) testing for its ease of use and added before fermentation.

Figure 10: Final Beer (color perception) products

Photograph of Experiment 2 (color perception) beers L, M, and D (from left to right)

before bottling.

Chapter 4: Biological and Chemical Analyses Materials and Methods

Material and equipment acquisition

All materials and equipment were provided by Yards Brewing Company.

Additionally all testing outlined below occurred at the Quality Assurance/Control laboratory of Yards Brewing Company in Philadelphia, PA. Reagents used throughout testing included Ricca® 6.00 Normal Hydrochloric acid and EMD Millipore Emsure®

Isooctane (2,2,4-Trimethylpentane). Microbiological media used included Lin’s Wild

Yeast Medium (LWYM), Lin’s Cupric Sulfate Medium (LCSM), Wallerstein Differential

Broth (WLD), and Hsu’s Lactobacillus/Pediococcus (HLP) Medium. Equipment used included: Fisher Scientific accument® AR 15 pH meter, Hermle Labnet Z206A centrifuge, Haffman’s Inpack 2000 CO2 Calculator, Hach DR6000 UV VIS

Spectrophotometer, and a Branson 5510 Sonicator. All reagents, media, and equipment was sourced through Thomas Scientific based out of Swedesboro, NJ.

Microbiological testing

Six bottled samples (three from Experiment 1 and three from Experiment 2) were brought to the Quality Control lab of Yards Brewing Company in Philadelphia, PA for further testing. Here each sample was plated on Lin’s Wild Yeast Medium (LWYM),

Lin’s Cupric Sulfate Medium (LCSM), Wallerstein Differential Broth (WLD), and Hsu’s

Lactobacillus/Pediococcus (HLP) Medium. Samples were allowed to incubate at 25°C in a 6% CO2 environment for 120 hours. Samples were then analyzed and observed using microscopy if necessary. 47

Color testing

Color, in SRM, was measured using the American Society of Brewing Chemists

(ASBC) photometric method (1958). Before testing samples were sonicated for three minutes to remove carbonation and spun at 3000 rpm to pellet yeast and other material.

DS, DG, and D samples were diluted 1:1 with distilled water (3 mL beer in 3 mL water) before reading. This was taken into account with the spectrophotometer’s settings before reading. Using program 2020 (ASBC Beer Color) SRM was measured by reading each beer sample in 10 mm quartz cuvettes against a distilled water sample at 430 nm. Results were reported with calculated standard deviation.

Bitterness testing

Beer bitterness, in IBU, was measured using the ASBC manual isooctane extraction reduced solvent technique (1975). After sonication and centrifugation 10 mL of each beer sample were placed in individual test tubes with 250 µL of 6N HCl and mixed. Ten milliliters of isooctane were then added to acidified beer sample. Samples were vortexed until a complete emulsion of the beer and isooctane occurred. After mixing samples were shaken on a mechanical shaker for 15 minutes at 80% maximum speed.

Once the extraction step was complete samples were centrifuged at 3000 rcf for 10 minutes to break the emulsion and separate the layers into beer and isooctane with extracted iso-alpha acids. Using program 202 (ASBC Beer Bitter Units) IBU was measured by reading each extracted isooctane sample in 20 mm quartz cuvettes against a pure isooctane sample at 275 nm. Results were reported with calculated standard deviation. 48

Additional laboratory tests

To ensure consistency between L, M, and D samples (beyond color) additional testing was completed on finished bottles. This included common industry standard testing like carbonation, pH, and fill. Carbonation was completed on a CO2 calculator bottle punch (Figure 11) calibrated to atmospheric pressure. pH was taken using a standard calibrated pH meter. Fill height (in mL) was recorded in a class-A glass 500 mL graduated cylinder. Results were reported with calculated standard deviation.

Results

Microbiological testing

Lin’s Wild Yeast Medium (LWYM) and Lin’s Cupric Sulfate Medium (LCSM) were used for the detection and quantitative determination of wild yeast populations.

Wallerstein Differential Broth (WLD) was used for the selective isolation of bacteria.

Hsu’s Lactobacillus/Pediococcus (HLP) Medium was used for detecting lactic acid bacteria, the most common beer spoilers (White & Zainasheff, 2010). No bacteria, foreign yeast, or pathogenic organisms were found within the beer samples (Table 1).

Brewing yeasts were however found on the plated samples. After microscopy, the colonies tested (Figure 12) were identified as S. cerevisiae. The observed yeast colonies exhibited known morphology and size (~10 µm) of the WLP002 brewing strain.

Color testing

As expected, SRM varied greatly between beer samples. While testing darkening techniques (Table 2) DS was measured at 54.4 ± 0.3 and DG at 54.0 ± 0.3 while the base

L beer was measured at 13.4 ± 0.2. Beers tested during color perception (Table 3) were measured at 13.0 ± 0.2, 30.7 ± 0.3, and 55.1 ± 0.4 for L, M, and D respectively. Raw data is collected in Chapter 9 Appendix B.

Bitterness testing

No difference in IBU was observed between any beer samples. Throughout darkening testing (Table 2) IBU was measured as 43.4 ± 0.8, 44.0 ± 0.9, and 43.7 ± 0.2 for L, DG, and DS respectively. Color perception testing (Table 3) beer IBU was measured at 45.2 ± 0.3, 45.2 ± 0.2, and 45.2 ± 0.1 for L, M, and D respectively. Raw data is collected in Chapter 9 Appendix B.

Additional laboratory tests

No major differences were observed between L, M, and D beer samples for carbonation, fill, or pH (Table 3). Raw data is collected in Chapter 9 Appendix B.

Discussion

Biological testing was used to ensure the safety of the beer product for consumption and to indicate whether any spoilage microorganisms may be present. While not at a large risk for pathogens, other bacteria, such as lactic acid bacteria, can drastically alter a beers flavor and other characteristics (Sakamoto, 2003).

Microbiological testing on all beers in testing indicated no infection of samples had 50 occurred and only the desired yeast was present upon completion. Chemical quantification tests were used to ensure beer samples were exactly the same in all characteristics except for controlled color difference. Testing of carbonation, fill, pH, and

IBU were all within normal variation indicating no detectable difference between samples. Other flavors beyond bitterness may have changed the profile of the beer, thus the perception of certain characteristics, and should be examined more thoroughly in the future. This could include compounds such as diacetyl, with a butterscotch like aroma and flavor, and acetaldehyde, reminiscent of fresh green apples, which may form depending on yeast activity and health. While this should be examined in the future there were no indications throughout testing that these other flavors raised concerns.

Figures and Tables

Figure 11: Carbonation testing equipment

Bottle punch used to test the carbonation (in volumes of CO2) of bottled beer. 51

Table 1: Summary of microbiological testing results

Darkening Technique Color Perception

L DG DS L M D

LWYM + + + + + +

LCSM ------

WLD ------

HLP ------

Figure 12: Yeast Microscopy

Observed yeast colonies at 400X under a standard light microscope. Based on characteristic morphology and size observed cells were identified as WLP002 colonies. Thus, the only microorganisms found present in bottled beer samples was the yeast type used to ferment.

Table 2: Color and bitterness of darkening technique beers

L DG DS

Color (SRM) 13.4 ± 0.2 54.0 ± 0.3 54.4 ± 0.3

Bitterness (IBU) 43.4 ± 0.8 44.0 ± 0.9 43.7 ± 0.2

Table 3: Color and bitterness of color perception testing beers

L M D

Carbonation (Volumes CO2) 2.85 ± 0.03 2.81 ± 0.03 2.82 ± 0.02

Fill (mL) 646 ± 2 642 ± 3 645 ± 3

pH 4.31 ± 0.01 4.32 ± 0.03 4.40 ± 0.01

Color (SRM) 13.0 ± 0.2 30.7 ± 0.3 55.1 ± 0.4

Bitterness (IBU) 45.2 ± 0.3 45.2 ± 0.2 45.2 ± 0.1

Chapter 5: Sensory Studies

Materials and Methods

Material acquisition

All testing material, including sample cups and ballots, were provided by Drexel

University’s Center for Hospitality and Sports Management.

Drexel University IRB Review

On July 9, 2015 a request for an Exempt Institutional Review Board (IRB) # 3

(Adult Social/Behavioral) protocol review was submitted to the Drexel University

Human Research Protection Program (HRPP). The official protocol (1507003786) included: HRP 211 Application Form, HRP 201 Contact Form, Conflict of Interest

Forms, HRP 503 Template Protocol, Electronic Recruitment text, Recruitment flyers,

Data Collection Tools, a Proposal summary, and CITI (Collaborative Institutional

Training Initiative) social behavior research training. With the application an alcohol exemption was granted by the Interim Provost and Senior Vice President of Academic

Affairs, Dr. James D. Herbert.

On July 17, 2015 protocol 1507003786 was approved under Exempt Category 2

(Chapter 8 Appendix A). Exemption Category 2 Section 6 allows for exemption of studies involving taste and food quality evaluation and consumer acceptance studies. As stipulated with approval, all requirements outlined within the HRP 103 Investigator

Manual were fulfilled when conducting the protocol.

Test 1: Experiment 1 Discrimination test

This study was completed in the Tasting Room of Yards Brewing Company at

901 N. Delaware Ave, Philadelphia, PA 19123.

All participants in this study were employees of Yards. Participants (n=24) were asked to complete two triangle tests including a base light yellow beer L and a dark brown beer made with black malt grain (DG), and L beer against a dark brown beer made with Sinamar® (DS). Beer samples were placed in black plastic cups with lids to mask the beers color. All sample orders were balanced and randomized with three digit identification codes. Water and spit cups were provided for participant use throughout testing. Data were analyzed following the normal approximation to the binomial distribution through Microsoft Excel (p < 0.05). An example ballot can be found in

Chapter 8 Appendix A.

Test 2: Experiment 2 Affective test

This study was completed in the Academic Bistro of Drexel University in the Paul

Peck Problem Solving and Research Building at 101 N. 33rd Street, Philadelphia, PA

19104.

All participants in this study were faculty, staff, or students of Drexel. Subjects

(n=85) were given three beer samples. One of the light yellow (L) base beer, one of the medium brown (M) beer, and one of the dark black (b) beer. As indicated previously all beers were darkened with Sinamar®.

For each sample participants were asked to rate the sample for several attributes

(bitter, sweet, sour, and salty flavor) from 1 to 15 (indicating no flavor present to its 55 extreme presence). Participants also noted liking of each beer on a 9 point hedonic scale ranging from “dislike extremely” to “like extremely.” At the end of testing demographic information (age, sex, level of education, general beer liking, purchasing habits, consumption habits, and notes on beers they enjoyed) were collected for each participant.

Purchase and consumption habits were rated from 1 to 4 (labelled less than once a month, more than once a month but less than once a week, once a week, and more than once a week, respectively) and liking followed the standard 9 point hedonic scale.

All sample orders were balanced and randomized with three digit identification codes. Beer samples were placed in clear plastic cups without lids so participants could observe beers color Water, spit cups, and snacks were provided for participant use throughout testing. Data was analyzed using a One-way analysis of variance (ANOVA) with repeated measures in R programming software. An example ballot and consent form can be found in Chapter 8 Appendix A.

To determine if past experience or “beer expertise” made a difference in rating additional analysis was completed after initial color perception testing. Participants were broken into two groups, regular beer experts (or “experts”) and non-experts (or

“novices”), based on beer liking and consumption habits. If a participant indicated that they both consumed beer once a week or more (scores 3 and 4) and liked beer slightly or greater (scores 6-9 on hedonic scale), they were considered beer experts. Results of attribute rating for beer experts (n=51) and novices (n=34) were analyzed (p<0.05) using a two-way ANOVA (Chapter 10 Appendix C).

Test 3: Experiment 2 Discrimination test 56

This study was completed in the Tasting Room of Yards Brewing Company at

901 N. Delaware Ave, Philadelphia, PA 19123. All participants in this study were employees of Yards. Participants (n=21) were asked to complete a series of six triangle tests. Testing included selecting the difference between: light yellow (L) beer and a

“medium” brown (M) beer, L and a dark black (D) beer, and M versus D. Beer used was the same as samples used during Test 2 (color perception affective testing). Each test was repeated twice for a total of six tests. Beer samples were placed in black plastic cups with lids to mask the beers color. All sample orders were balanced and randomized with three digit identification codes. Water, spit cups, and snacks were provided for participant use throughout testing. Data was analyzed following the normal approximation to the binomial distribution through Microsoft Excel (p<0.05). An example ballot can be found in Chapter 8 Appendix A.

Results

Test 1: Experiment 1 Discrimination test

Z-score was 1.516 for DG against L and 0.217 for DS compared to L. Both of these values are below the critical value at 0.05 of 1.645. These results indicate there was no significant difference between L, DG, or DS. All raw data can be found within

Chapter 10 Appendix C.

Test 2: Experiment 2 Affective test

In the overall investigation of the effects of beer color on the perception of flavor, participants were instructed to rate flavors of three beers (L, M, and D) for five attributes

(sweetness, saltiness, sourness, bitterness, and liking). Overall, statistical analysis indicated no significant difference (p<0.05) in relation to beer color and sweet, salty, sour, and liking ratings (Figure 13). The results of the one-way ANOVA for these attributes are summarized in Table 4. Color, however, did have a significant effect on perception of beer bitterness (Figure 14). The one-way ANOVA showed the effect of color on bitterness perception was significant, F(2, 164) = 5.15, p=0.007. At a confidence interval of 95% a yellow beer was perceived as more bitter than a black beer, despite having the exact same characteristics. L, M, and D, were rated as 5.5 ± 3.6, 5.0 ± 3.4, and

4.5 ± 3.2 for bitterness respectively. All raw data can be found within Chapter 10

Appendix C.

When broken into expertise groups no significant difference (p<0.05) was observed relation to beer color and sweet and sour ratings. The results of the two-way

ANOVA for these attributes are summarized in Table 5. The two-way ANOVA showed the effect of expertise on saltiness perception significant at F(1, 81) = 5.82, p=0.018.

Similarly, a significant (p < 0.05) effect on bitterness perception was observed in both the one between-subjects variable (expertise) and one within-subjects variable (color).

Expertise and color were calculated to be F(1, 81) = 5.73, p=0.019 and F(2, 162) = 5.18, p=0.007, respectively. As liking divided participants into expertise groups those rated

“experts” liked beer significantly more (F(1, 81) = 23.60, p=0.007). 58

Collected demographic information indicated 51 self-identified males and 34 self- identified females took part in the study. Average age of participants was 27.9 ± 10.6, with a minimum participant age of 21, and a maximum participant age of 70 years old.

Purchasing habits indicated most participants bought beer more than once a month but less than once a week (2.5 ± 1.1) and consumed beer about once a week (2.9 ± 1.1). Most participants in the study also indicated the liked beer moderately to very much (7.2 ±

1.8). Throughout the short answer preferred beer question of the ballot 35.5% of comments mentioned craft beer or breweries and 27.1% mention “macrobreweries”

(producing over 6 million barrels of beer annually). Specifically, 20% of participant’s mentioned the IPA (India Pale Ale) style or bitter beers and 17.6% indicated like “dark” beers.

Test 3: Experiment 2 Discrimination test

Z-scores are summarized in Table 5. All values were below the critical value at

0.05 of 1.645. These results indicate there was no significant difference between L, M, or

D. All raw data can be found within Chapter 10 Appendix C

Discussion

Darkening technique testing was simply completed to determine if one could darken a beer without effecting flavor, and if so whether one method was more effective than another. As indicated by the results, beer can be darkened in color with both black malt or Sinamar® with no detectable change in flavor. Sinamar® was chosen as the darkening technique moving forward as it allowed for one single brewing process that 59 was divided and easily dyed before fermentation. This allowed for increased specificity in coloring the beers and was not as labor intensive as the grain method would have been.

After determining that Sinamar® would be used, a similar discrimination test

(Test 3) was used to ensure that flavor profile of all beers for color testing were not noticeably different. As they were not found to be significantly different on flavor alone, the affective test that followed allowed the investigators to determine the effect of color on perception of certain flavors in the beer. Results from this study indicated that participants did perceive a difference in the bitterness of beers, despite chemical and flavor testing proving they were the same exact beer. Additional variables, such as age, sex, and level of education were not explored as a Fisher’s Least Significant Difference

(LSD) test indicated no significant difference. It appears there was some interaction between what participants observed, what preconceived notions they had, and what bitterness they tasted in each beer.

Analysis of the different expertise groups revealed both expected and unexpected results. Expertise, and not color, has a significant effect on liking and saltiness. Liking was not unexpected as this was one factor that divided participants into expert or novice groups. The difference in saltiness perception may a self-perception effect, with experts being more aware and paying more attention to scale use. Bitterness, on the other hand, was effect by both expertise status and beer color. More specifically, color only had an effect within bitterness perception amongst all categories. The novice group generally found the beer as more bitter and this drove the results observed in the general data analysis before subdivision of expert groups. While a minimalistic look at the collected 60 data, it is clear that past experience with beer plays a large role in how its flavors are perceived by consumers.

As craft beer is widely popular in Pennsylvania, ranking 1st in the nation for number of barrels produced, 2nd for economic impact, and 7th for the number of craft breweries (BA, 2015), the previously observed historical trends may be changing. India pale ales and double IPAs are a very popular style in the US and often exhibit a pale or light yellow color (Steele, 2012). This may have led participants to believe that a lighter yellow beer would in fact be more bitter than a brown colored beer, which they may believe was a lager. Anecdotally, many participants mentioned while exiting that they rated the beers based on perceived style. They indicated that they thought of the black beer as a stout or porter, the yellow as an IPA, and the brown as a lager. These assumptions may have drastically influenced how they rated the flavors and acceptance of each beer. Interestingly, those less experienced with beer drinking perceived the lighter beer as more bitter, in contrast to established historical trends. This indicates that experience and general knowledge of beer and the brewing has potentially increased throughout recent history. In the future, studies on perceived flavors based on an indicated beer style should be examined to determine the presence of any biases.

Additionally, due to the large volume of data collected in this study further statistical analysis should be completed. Data mining techniques could be utilized to look at patterns and trends between variables.

Figures and Tables

Figure 13: Statistical Results of Color Perception Testing

a) b)

c) d)

Graphical representations of one way ANOVA with repeated measures analysis. Attributes shown include: a) sweetness rating, b) saltiness rating, c) sourness rating, and d) liking on beer based on the color of each sample. For these attributes there was no significant differences between beers. 62

Table 4: Color Versus Attribute One-Way ANOVA Results Sweetness df F p Between Groups 2 2.10 0.126 Within Groups 166 Total 168 Saltiness df F p Between Groups 2 0.83 0.439 Within Groups 166 Total 168 Sourness df F p Between Groups 2 1.55 0.215 Within Groups 166 Total 168 Liking df F p Between Groups 2 0.18 0.834 Within Groups 166 Total 168 Bitterness df F p Between Groups 2 5.15 0.006* Within Groups 164 Total 166 *Indicates statistical significance at p < 0.05

Figure 14: Effect of Beer Color on Bitterness Perception

Statistical results indicate a significant (p<0.05) effect of color on how a beers bitterness is perceived. Lighter colored yellow beer was perceived as more bitter than a dark colored black beer.

Table 5: Expertise Two-Way ANOVA Results Sweetness Liking df F p df F p Expert Expert Between Groups 1 1.67 0.199 Between Groups 1 23.60 5.7 x 10-6* Within Groups 81 Within Groups 81 Total 82 Total 82 Color Color Between Groups 2 2.46 0.089 Between Groups 2 0.24 0.789 Within Groups 162 Within Groups 162 Total 164 Total 164 Expert*Color Expert*Color Between Groups 2 0.54 0.584 Between Groups 2 1.96 0.145 Within Groups 162 Within Groups 162 Total 164 Total 164 Saltiness Bitterness df F p df F p Expert Expert Between Groups 1 5.82 0.018* Between Groups 1 5.73 0.019* Within Groups 81 Within Groups 81 Total 82 Total 82 Color Color Between Groups 2 0.92 0.400 Between Groups 2 5.18 0.007* Within Groups 162 Within Groups 162 Total 164 Total 164 Expert*Color Expert*Color Between Groups 2 1.11 0.333 Between Groups 2 1.51 0.223 Within Groups 162 Within Groups 162 Total 164 Total 164 Sourness df F p Expert Between Groups 1 0.53 0.469 Within Groups 81 Total 82 Color Between Groups 2 1.43 0.242 Within Groups 162 Total 164 Expert*Color Between Groups 2 1.46 0.236 Within Groups 162 Total 164 *Indicates statistical significance at p < 0.05 65

Figure 15: Effect of Expertise on Saltiness and Liking a) b)

Significant effect (p < 0.05) of beer expertise on a) saltiness perception and b) liking. Color did not effect perception of either beer attribute.

Figure 16: Effect of Color and Expertise on Bitterness

Two-way ANOVA results indicated a significant effect (p < 0.05) of both color and bitterness perception between expertise levels. Overall, the novice group generally perceived all beer samples as more bitter. 66

Table 6: Summary of Color Perception Discrimination Test Test 1 Test 2 Test 3 Test 4 Test 5 Test 6 Z Score -0.231 0.231 0.231 1.620 -1.620 0.694

Chapter 6: Conclusions

The goal of the current research was to determine if beer color influenced consumer perception of bitterness. Original hypotheses, based on observed historical and socioeconomic trends, stated that consumers of beer would rate a black or darker colored beer as more bitter than a pale yellow beer when presented side by side. This was completed by pairing chemical quantification techniques, such as measuring IBU and SRM spectrophotometrically, with a series of sensory evaluation tests. Throughout the study darkening techniques, black malts versus Sinamar®, were also evaluated to confirm that both methods will not impart or change beer flavors when being used. Sensory evaluation included both discrimination and affective tests to confirm significance of the findings.

While both darkening techniques were able to change color but not influence flavor, as indicated by non-significant difference results in discrimination testing, Sinamar® was chosen for its ease of use. Color testing indicated differences in SRM (producing a yellow, brown, and black beer) while bitterness testing indicated all beers had the same level of iso-alpha acids. Within affective testing participants unexpectedly perceived the lighter yellow beer as significantly more bitter than the dark black beer. This is likely due to the high level of regular beer experts who took part in the study and an increased general knowledge of beer and how it is made. When broken into groups based on “expertise” (regular beer drinkers versus not regular drinkers or novices), novices rated lighter samples as significantly more bitter, causing the general effect observed in initial analysis to be driven by this group. Clearly, experience with beer plays a significant role on how beer is perceived, and should be continuously investigated in the future.

Future research should also focus on preconceptions consumers have on beer and flavors.

Research could evaluate the effect of color on other desireable beer flavors (such a “malty” or

“fruity”) or off-flavors, like acetaldehyde (green apple), diacetyl (butter), and trans-2-nonenal 68

(papery). The effect of style perception would also be interesting to investigate. This could be between styles ales versus lagers) or within a style (such as pale ales versus stouts in the ale category). Before physical testing, an online survey was considered as part of this current research. The survey would present participants with images or brands of beer and ask them to rate them for specific flavors or liking. In the future this type of survey should be considered alongside further studies that present participants with physical beer samples, but ask them to rate them without consumption. A sensory study specifically selecting for “macro-brew” or craft beer experts could also indicate how past experience or drinking habits effect perception. Additionally, data collected from this study should be further explored. Data mining techniques or use of this data in future meta-analysis studies could be useful in elucidating trends or relationships present.

Chapter 7: References

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Chapter 8: Appendix A (Sensory Test Materials) Drexel University Institutional Review Board Approval 77

Informed Consent Sheet

Informed Consent Documentation

Research project subject: Consumer perception of beer flavor.

Principal investigators: Jacob Lahne, PhD

You are being asked to take part in a research study, meant to investigate the sensory properties of beers. Someone will explain the research and your participation to you. You are being asked to take part in this research because you may offer information valuable information on how these beers taste.

We encourage you to ask questions or express concerns to any of the researchers before you agree to participate in the study. You are at any time free to decide not to participate, or to discontinue your participation during the study. Please feel free to ask the researchers or anyone else any questions as you decide whether or not to participate.

Who can you talk to about this study?

If you have questions, concerns, or complaints, or feel the research has hurt you, talk to the research team at [email protected] (Dr. Jacob Lahne).

This research has been reviewed and approved by an Institutional Review Board (IRB). An IRB reviews research project so that steps are taken to protect the rights and welfare of human subjects taking part in the research. You may talk to them at (215)-355-7857 or email [email protected] for any of the following:

• Your questions, concerns, or complaints are not being answered by the research team • You cannot reach the research team • You want to talk to someone besides the research team • You have questions about your rights as a research subject • You want to get information or provide input about this research

Purpose of the study

The purpose of this study is to investigate the flavor of beer using consumers. The study will increase scientific knowledge of the structure of consumer likings. 78

Duration of study

The study will consist of one session. Your participation should take 10-15 minutes.

Number of subjects

The total expected number of study participants is 150-200.

What happens if I agree to participate in this research?

This study will take place in two locations: the Yards Brewing Company testing room and the Academic Bistro of the Department of Culinary Arts and Sciences. Before beginning you must provide the investigator with valid government issued identification proving that you are 21+ years old, and, if you are participating at Drexel, a valid Drexel ID. You will be seated with other participants and served three beer samples. During the sampling you will be asked to complete a paper questionnaire in which you will answer questions on the taste of the beer and your liking for each beer. Please complete one beer sample at a time and spit out the sample after tasting. Please try not to swallow any of the beer sample. Water and crackers will be available between tastings.

By agreeing to participate in this research, you are indicating that you are willing to consume beer and furnish your opinions and comments to the researchers.

What are my responsibilities if I take part in this research?

If you take part in this research, it is very important that you:

• Are 21+ years old. • Are not pregnant or taking medications (prescription or nonprescription) or suffering from illnesses which are contraindicated with alcohol consumption. • Follow the researchers’ instructions. • Provide valid Drexel and Government issued identification. • Spit out beer samples in provided cups after tasting. • Tell the investigator right away if you have a complication, injury, or complaint. • Sample the beer provided for you and complete the accompanying questionnaire.

What happens if I do not want to be in this research? You may decide not to take part in the research and it will not be held against you.

What happens if I say yes, but I change my mind later? 79

If you agree to take part in the research now, you can stop at any time and it will not be held against you.

Is there any way this study could be bad for me? The main risk involved in this study is to those with food allergies or other dietary restrictions. If you have a food allergy or dietary restriction and have not yet identified it to the principal investigators, please do so now. Please also inform the researchers if you are pregnant or should otherwise not consume alcoholic beverages.

Beyond the risk of potential food allergies, the researchers cannot guarantee that every participant will enjoy the beer provided. The beers are an experimental variable, and so cannot be tailored to the participants. Therefore, it is possible you will be asked to taste something you do not enjoy, although in general all beers in this research are designed to be palatable.

Do I have to pay for anything while I am on this study? There is no cost to you for participating in this study.

Will being in this study help me in any way?

We cannot promise any benefits to you or others from taking part in this research.

What happens to the information we collect? Efforts will be made to limit access to your personal information. We cannot promise complete secrecy. However, we will not collect identifying information.

We may publish the results of this research. However, we will keep your name and other identifying information confidential.

All data collected from this research will be kept in a locked filing cabinet in a locked office, and digital copies will be kept only on password-protected, encrypted hard drives. No personal or identifying information will be collected. All data will be dealt with in a manner meant to guarantee your privacy at all times.

Can I be removed from the research without my OK?

The person in charge of the research study or the sponsor can remove you from the research study without your approval. Possible reasons for removal include: 80

• Lack of proper identification (Drexel and Government issued identification) proving that you are at least 21 years of age • Refusal to sample the beer • Refusal to complete the provided questionnaire • Refusal to follow protocol (consuming beer when being asked to spit each sample out)

What else do I need to know?

This research study is being done by Drexel University.

GOVERNMENT WARNING:

(1) According to the Surgeon General, women should not drink alcoholic beverages during pregnancy because of the risk of birth defects.

(2) Consumption of alcoholic beverages impairs your ability to drive a car or operate machinery, and may cause health problems.

By agreeing to participate in this research, you indicate that you have been informed of the risks, benefits, and responsibilities of participation. Please keep this copy of the Informed Consent Documentation for your records.

Darkening Method Discrimination Triangle Test Ballot 82

Beer Color and Bitterness Affective Consumer Test Ballot

Sinamar Darkening Discrimination Triangle Test Ballot

Chapter 9: Appendix B (Raw Chemical Analysis Data)

Darkening Discrimination Test Data

L DG DS Sample 1 13.2 54.3 54.2 Sample 2 13.4 54.0 54.2 Color Sample 3 13.5 53.8 54.7 (SRM) Average 13.3667 54.0333 54.3667 Standard 0.15275 0.25166 0.28868 Deviation Sample 1 42.5 44.9 43.7 Sample 2 43.7 43.9 43.5 Bitterness Sample 3 44.0 43.2 43.8 (IBU) Average 43.4 44.0 43.6667 Standard 0.79373 0.8544 0.15275 Deviation

Color Perception Discrimination Test Data

L M D Sample 1 2.87 2.79 2.8 Sample 2 2.82 2.8 2.84 Carbonation Sample 3 2.85 2.84 2.83 (Volumes CO2) Average 2.84666667 2.81 2.82333333 Standard 0.02516611 0.02646 0.02081666 Deviation Sample 1 647 645 642 Sample 2 648 641 647 Sample 3 644 640 645 Fill (mL) Average 646.333333 642 644.666667 Standard 2.081666 2.64575 2.51661148 Deviation Sample 1 4.3 4.32 4.4 Sample 2 4.32 4.29 4.39 Sample 3 4.31 4.35 4.4 pH Average 4.31 4.32 4.39666667 Standard 0.01 0.03 0.0057735 Deviation Sample 1 13 31 54.7 Sample 2 12.8 30.4 55.5 Color (SRM) Sample 3 13.1 30.6 55.2 Average 12.9666667 30.6667 55.1333333 Standard 0.15275252 0.30551 0.40414519 Deviation Sample 1 45.5 45 45.2 Sample 2 45.1 45.4 45.3 Bitterness Sample 3 45 45.3 45.2 (IBU) Average 45.2 45.2333 45.2333333 Standard 0.26457513 0.20817 0.05773503 Deviation

Chapter 10: Appendix C (Raw Sensory Analysis Data)

Darkening Discrimination Test Data

Where “0” indicates an incorrect response and “1” a correct response. Test 1 compares yellow beer (L) and dark beer darkened with black malt (DG). Test 2 compares L and dark beer darkened with Sinamar (DS). Participant Test 1 Test 2 1 0 0 2 1 0 3 1 1 4 1 0 5 1 0 6 0 1 7 1 0 8 0 0 9 0 1 10 1 0 11 0 1 12 0 1 13 1 0 14 0 1 15 0 1 16 1 0 17 0 0 18 1 1 19 1 0 20 0 0 21 0 1 22 1 0 23 1 0 24 0 0 Observed Correct 12 9 Z Score 1.516 0.217 Significance No difference No difference

Color Perception Affective Test Data – R Coding Beer Color vs. Bitterness ezANOVA(data=beer.ez, dv=Bitter, wid=participant, within = color); $ANOVA

Effect DFn DFd F p p<.05 ges 2 color 2 164 5.152 0.006760713 * 0.02132526

$`Mauchly's Test for Sphericity` Effect W p p<.05 2 color 0.9877415 0.6068123

$`Sphericity Corrections` Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 2 color 0.98789 0.006982963 * 1.012129 0.006760713 *

Beer Color vs. Liking ezANOVA(data=beer.liking, dv=rating, wid=participant, within = color);$ANOVA

$ANOVA Effect DFn DFd F p p<.05 ges 2 color 2 166 0.1817141 0.8340053 0.001015427

$`Mauchly's Test for Sphericity` Effect W p p<.05 2 color 0.9959059 0.8451812

$`Sphericity Corrections` Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 2 color 0.9959226 0.8331516 1.02036 0.8340053

Beer Color vs. Sweetness ezANOVA(data=beer.sweet, dv=rating, wid=participant, within = color);$ANOVA

Effect DFn DFd F p p<.05 ges 2 color 2 166 2.100758 0.1256051 0.01154298

$`Mauchly's Test for Sphericity` Effect W p p<.05 2 color 0.953741 0.1434328

$`Sphericity Corrections` 89

Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 2 color 0.9557863 0.1279955 0.9777727 0.1268046

Beer Color vs. Saltiness ezANOVA(data=beer.salty, dv=rating, wid=participant, within = color);$ANOVA $ANOVA Effect DFn DFd F p p<.05 ges 2 color 2 166 0.826602 0.4393262 0.005071297

$`Mauchly's Test for Sphericity` Effect W p p<.05 2 color 0.9844076 0.5250178

$`Sphericity Corrections` Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 2 color 0.984647 0.4377395 1.008387 0.4393262

Beer Color vs. Sourness ezANOVA(data=beer.sour, dv=rating, wid=participant, within = color);$ANOVA $ANOVA Effect DFn DFd F p p<.05 ges 2 color 2 166 1.552396 0.2147982 0.006195291

$`Mauchly's Test for Sphericity` Effect W p p<.05 2 color 0.9398358 0.07854725

$`Sphericity Corrections` Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 2 color 0.9432501 0.21595 0.9644881 0.2155337

Expertise vs. Bitterness

$ANOVA Effect DFn DFd F p p<.05 ges 2 expert 1 81 5.729545 0.018993551 * 0.043427244 3 color 2 162 5.184242 0.006570969 * 0.022411203 4 expert:color 2 162 1.513164 0.223307857 0.006646812

$`Mauchly's Test for Sphericity` Effect W p p<.05 3 color 0.9894979 0.6555347 4 expert:color 0.9894979 0.6555347

$`Sphericity Corrections` Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 3 color 0.9896071 0.006757618 * 1.014262 0.006570969 * 4 expert:color 0.9896071 0.223486415 1.014262 0.223307857

Expertise vs. Sourness

$ANOVA Effect DFn DFd F p p<.05 ges 2 expert 1 81 0.5289479 0.4691464 0.004357866 3 color 2 162 1.4294731 0.2424388 0.005785539 4 expert:color 2 162 1.4558187 0.2362439 0.005891540

$`Mauchly's Test for Sphericity` Effect W p p<.05 3 color 0.9426961 0.09437747 4 expert:color 0.9426961 0.09437747

$`Sphericity Corrections` Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 3 color 0.9458019 0.2427974 0.9677323 0.2426702 4 expert:color 0.9458019 0.2367748 0.9677323 0.2365770

Expertise vs. Sweetness

$ANOVA Effect DFn DFd F p p<.05 ges 2 expert 1 81 1.6744931 0.19933527 0.011027378 3 color 2 162 2.4607265 0.08855876 0.013800411 4 expert:color 2 162 0.5390666 0.58433505 0.003056166

$`Mauchly's Test for Sphericity` Effect W p p<.05 91

3 color 0.9451126 0.1045543 4 expert:color 0.9451126 0.1045543

$`Sphericity Corrections` Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 3 color 0.9479685 0.09166902 0.9700313 0.09033932 4 expert:color 0.9479685 0.57497659 0.9700313 0.57900337

Expertise vs. Saltiness $ANOVA Effect DFn DFd F p p<.05 ges 2 expert 1 81 5.8235902 0.0180699 * 0.033103429 3 color 2 162 0.9226286 0.3995511 0.005930973 4 expert:color 2 162 1.1071859 0.3329752 0.007108937

$`Mauchly's Test for Sphericity` Effect W p p<.05 3 color 0.982041 0.4843787 4 expert:color 0.982041 0.4843787

$`Sphericity Corrections` Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 3 color 0.9823578 0.3981271 1.006555 0.3995511 4 expert:color 0.9823578 0.3322308 1.006555 0.3329752

Expertise vs. Liking $ANOVA Effect DFn DFd F p p<.05 ges 2 expert 1 81 23.5971547 5.706134e-06 * 0.122663458 3 color 2 162 0.2373535 7.889862e-01 0.001521649 4 expert:color 2 162 1.9576240 1.445193e-01 0.012413224 92

$`Mauchly's Test for Sphericity` Effect W p p<.05 3 color 0.9943898 0.7984843 4 expert:color 0.9943898 0.7984843

$`Sphericity Corrections` Effect GGe p[GG] p[GG]<.05 HFe p[HF] p[HF]<.05 3 color 0.9944211 0.7877682 1.019382 0.7889862 4 expert:color 0.9944211 0.1447923 1.019382 0.1445193

Color Perception Discrimination Test Data

Where “0” indicates an incorrect response and “1” a correct response. Test 1 compares light yellow beer (L) and medium brown beer (M). Test 2 compares L and dark beer (D). Test 3 compares M and D beers. As duplicates tests 4, 5, and 6 compare L and M, L and D, and M and D respectively.

Participant Test 1 Test 2 Test 3 Test 4 Test 5 Test 6 1 0 1 1 1 0 1 2 1 0 0 0 0 1 3 1 0 0 1 0 1 4 1 0 1 1 0 1 5 0 1 1 1 1 1 6 1 0 0 0 0 0 7 0 0 0 1 1 0 93

8 0 1 0 0 0 0 9 1 0 1 1 0 0 10 0 1 0 1 0 0 11 0 1 1 0 0 1 12 0 0 0 1 0 0 13 1 0 0 0 0 0 14 0 0 1 0 0 0 15 0 1 0 1 0 1 16 1 0 0 0 0 0 17 0 0 0 1 0 1 18 0 0 0 1 1 0 19 0 1 0 0 0 0 20 0 1 1 0 0 1 21 0 0 1 0 1 0 Observed 7 8 8 11 4 9 Correct Z Score -0.231 0.231 0.231 1.620 -1.620 0.694 No No No No No No Significance difference difference difference difference difference difference