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Evaluation of Nonvolatile Chemistry Affecting Sensory Bitterness

Mar 10, 2018 - (8−10) Recent work has shown that oxidized hop acids, hulupones and humulinones, are 84% and 66% as bitter as isohumulones, respectiv...
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Chemistry and Biology of Aroma and Taste

A Comprehensive Evaluation of the Nonvolatile Chemistry Affecting the Sensory Bitterness Intensity of Highly Hopped Beers Christina Hahn, Scott Lafontaine, Clifford Pereira, and Tom H. Shellhammer J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b05784 • Publication Date (Web): 10 Mar 2018 Downloaded from http://pubs.acs.org on March 11, 2018

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Journal of Agricultural and Food Chemistry

1 Evaluation of the Nonvolatile Chemistry Affecting the Sensory Bitterness Intensity of Highly Hopped Beers Christina D. Hahn¹, Scott R. Lafontaine¹, Cliff B. Pereira¹, Thomas H. Shellhammer¹* ¹Oregon State University Department of Food Science & Technology 234 Wiegand Hall Corvallis, OR 97330 *Corresponding author. Phone: 1-541-737-9308. E-mail: [email protected]

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Abstract

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The range of different nonvolatile constituents extracted from hops in highly hopped

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beers suggests that isohumulones may not be the sole contributor to beers’ bitterness. Among

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brewers producing hop-forward beer styles there is concern that the Bitterness Unit (BU) is no

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longer an accurate predictor of beer bitterness. This study examined factors within the beer

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matrix that influence sensory bitterness perception in highly hopped beers. Over 120 commercial

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beers were evaluated using sensory and instrumental techniques. Chemical analysis consisted of

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the BU via spectrophotometry, hop acids via HPLC, total polyphenols via spectrophotometry,

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and alcohol content plus real extract via an Alcolyzer. Sensory analysis was conducted over two

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studies, and the beers’ overall bitterness intensity were rated using a 0-20 scale. This study

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identified that the BU measurement predicts sensory bitterness with a nonlinear response, and it

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proposed an alternative approach to predicting bitterness based on isohumulones, humulinones,

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and ethanol concentrations. The study also revealed the importance of oxidized hop acids,

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humulinones, as a significant contributor to beer bitterness intensity.

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Keywords: Hops, bitterness, brewing, beer, isohumulones, humulinones.

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Introduction

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With the rise in popularity of hop-forward beer styles there has been a growing concern

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in the beer industry surrounding the accuracy of instrumental bitterness analyses. Anecdotally,

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some in the brewery quality assurance field feel that current methods for predicting beer

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bitterness, such as the Bitterness Unit (BU) method, a liquid/liquid extraction of bitter

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compounds, and the direct measurement of isohumulones via high performance liquid

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chromatography (HPLC), often fail to accurately predict the sensory bitterness of beer of highly

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hopped beer styles The projects presented herein were designed to test existing methodology and

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to search for potential new approaches to instrumentally predicting sensory bitterness intensity in

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beer.

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Hops (Humulus lupulus) are the primary source of bitter compounds in beer, and these

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bitter compounds can be categorized into three groups: isohumulones, oxidized hop acids, and

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polyphenols.1 There is little question that isohumulones are the main contributor to beer

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bitterness, however all three groups have the ability to impact both sensory bitterness intensity

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and the BU value of a beer.2-5 How a brewer uses the hops will determine their concentration in

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finished beer. The timing and mass of hop additions in the brewing process will influence the

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overall aroma, bitterness, and astringency of the finished beer.6 In the production of hop-forward

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beer styles, such as American craft Pale Ales and India Pale Ales (IPAs), brewers add

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significantly more hop material to beer relative to traditional lager beer styles. This shifts both

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the concentration and ratio of bitter compounds present in the finished beer from solely

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isohumulones (as in American light lager beer) to a broad array of hop-derived compounds such

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as humulones, oxidized humulones (humulinones), oxidized lupulones (hulupones), and

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polyphenols, in addition to isohumulones.

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Generally, early additions of hops during wort boiling impart more bitterness and less

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aroma while the inverse is true for hops added late in wort and/or beer production.3 A traditional

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hopping scheme for lager beer would be a single early addition in the range of 1.5 g/L at the

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beginning of a 60-90 minute wort boil. By contrast, a hopping scheme for an American craft IPA

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will involve the addition of hops at multiple stages in the brewing process and to the finished

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beer itself, a technique referred to as “dry-hopping”. The Brewers Association reported that in

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2014 the top selling American Imperial IPAs contained between 9 and 11.5 g/L of hop material,7

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while American light lager beer contains approximately 1 g/L. Brewers looking to increase hop

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aroma by adding large quantities of hops late in process also potentially increase the

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concentration of oxidized hop acids and total polyphenols in the finished beer.

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Oxidized hop acids are present in freshly baled, aged or improperly stored hops at

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varying levels.8-10 Recent work has shown that oxidized hop acids, hulupones and humulinones,

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are 84% and 66% as bitter as isohumulones, respectively.2 Separately, polyphenols can

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contribute both bitterness and astringency to a wide variety of food and beverages depending on

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their degree of polymerization and molecular weight, and have been shown to have an additive

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effect on beer bitterness in the presence of isohumulones.5,

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polyphenols contribute to sensory bitterness alone is not understood. A 2008 study showed that

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at concentrations less than 300 mg/L, total polyphenols influence BU values in lager beer

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The magnitude to which

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systems. For every 15-20 mg/L increase in total polyphenols, a one-unit increase in BU was

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observed.5

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At relatively high concentrations in beer (ranging 14 mg/L to 28 mg/L) humulones, the

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precursors to isohumulones, have been shown not contribute to beer bitterness.13 However, at

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these elevated concentrations they may influence the BU value. Although the BU method

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captures these compounds in its measurement, there is no accounting for their relative abundance

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or relative bitterness. Furthermore, beer matrix effects, such as alcohol, residual extract and pH,

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may also influence bitter taste sensation.14-17 Residual extract and ethanol concentrations are well

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known factors brewers manipulate to balance a beer’s bitterness. Typically, beers with a high

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concentration of bittering compounds will have higher levels of residual extract.6 Ethanol

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concentration may also play a role in bitterness perception, as numerous studies in wine show

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that ethanol enhances bitter taste sensation.11, 17-19

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To predict sensory bitterness intensity, the International Bitterness Unit, or BU method, is

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most frequently employed. The BU method is a manual liquid-liquid extraction technique that

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utilizes polarity to separate the bittering components of beer using a non-polar solvent (2,2, 4-

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trimethylpentane).20 The absorbance of the extracted components in the non-polar phase is

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measured via a spectrophotometer at 275 nm and multiplied by a factor of 50 to obtain the BU

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value. The BU method was developed in 1955 by Rigby and Bethune with the intent of rapidly

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measuring the concentration of isohumulones in beer prior to the advent of HPLC.21 By 1968,

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the BU was internationally recognized as a standard method by the American Society of Brewing

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Chemists (ASBC) and the European Brewery Convention.22 In addition to measuring

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isohumulones, other ultraviolet-adsorbing compounds may influence the BU value.4,

20, 23

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inclusion of non-isohumulone substances in the BU assay presents a challenge to brewers,

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particularly when using this technique to evaluate beer styles that have been heavily hopped.4, 10

The

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Advances in instrumentation now allow for the rapid and easy measurement of

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isohumulones in beer using HPLC. The measurement of isohumulones by solid phase extraction

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and HPLC was first published by Donley in 1992 and became an official method of the ASBC in

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1993 (Beer-23, C).24 By 2011 the ASBC approved a direct injection method for the measurement

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of isohumulones by HPLC that eliminated the need for solid-phase extraction (Beer-23, E).20, 25

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Although HPLC allows for the measurement of a wide range of different hop acids, historically

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the focus has been solely on isohumulones.

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Regardless of the advances made in beer analyses tools, the American craft beers

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produced today are unlike the beers for which the current methods (BU and isohumulones by

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HPLC) were designed to measure. American craft beers are complex in their non-volatile

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chemistry relative to light lager beer, and there is concern surrounding the BU’s ability to

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adequately predict sensory bitterness in these new, highly hopped beer styles. This study aimed

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to address this concern by (1) evaluating a broad array of chemical factors known to affect bitter

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taste sensation along with sensory evaluation of bitterness using commercially-available,

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American beers with a focus on hop-forward styles, (2) performing multiple linear regression

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modeling to determine the significant drivers of beer bitterness, and (3) proposing a new,

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analyte-specific, predictive model of beer sensorial bitterness intensity.

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Materials and methods

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To gain insight into the drivers of sensory bitterness in beer, 121 unique commercial

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beers from 42 breweries across the United States were tested for 7 factors known to impact the

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sensory perception of bitterness in beers. Sensory analysis was conducted in two separate studies

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with specific objectives for each. A multiple replication study focused on evaluating a smaller

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number of beers (30) with a small (10 member) trained sensory panel. The beers’ overall

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bitterness intensity were rated using a 0 to 20 scale. This study revealed the chemical drivers of

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sensory bitterness, confirmed the inadequacy of total isohumulone content as a complete

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measure of beer bitterness, and proposed an alternative, liquid chromatography approach to

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predicting bitterness based on the combination of isohumulones, humulinones, and ethanol

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concentrations. A separate, single replication study was used to validate the results from the

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multiple replication study and was focused on evaluating a larger number of commercial beers

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(104 in total, 13 of which had been evaluated in the multiple replication study) with a larger (19

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member) trained sensory panel.

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Reagents and standards

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Ferric

ammonium

citrate

(green)

was

purchased

from

Fisher

Chemicals.

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Ethylenediaminetetraacetic acid disodium salt, dihydrate (EDTA),

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carboxymethylcellulose, and octyl alcohol were obtained from Sigma-Aldrich Chemical Co (St.

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Louis, MO). HPLC grade methanol was obtained from VWR International, BDH analytical

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(West Chester, PA, USA). Hydrochloric acid, 2,2,4-trimethylpentane, phosphoric acid and

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ammonium hydroxide obtained from Avantor performance materials (Center Valley, PA).

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DCHA-Iso ICS-I3 and international calibration extract ICE-3 standards were obtained from

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ASBC. DCHA humulinone and hulupone standards were produced2 and pure standards were

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obtained through Robert Smith at S.S. Steiner, Inc.

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Beer analysis

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The concentrations of hop acids in beer samples were assayed using a modified version

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of ASBC method Beer-23E.20 The modified conditions were as follows: analysis was performed

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on a 2.6 um EVO C-18 100 A LC column 100 x 4.6 mm (Phenomenex, Torrance, CA) at 40°C

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measuring absorbance at 275 nm for the isohumulones and humulinones, 330 nm for the

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hulupones, and 314 nm for the humulones. These wavelengths were chosen considering the

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absorbance spectrum of each hop acid.2 Prior to analysis beer was degassed and 7 µL of each

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beer sample was injected into a mobile phase consisting of 10% A (reagent water) and 90% C

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(75% MeOH, 24% H2O, 1% H3PO4) flowing at 1.6 ml/min. Ten minutes following the injection

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the mobile phase was switched to 100% B (100% MeOH), and at 14 minutes it was switched

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back to 10% mobile phase and A 90% mobile phase C.

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Total polyphenols were measured spectrophotometrically according to the EBC

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Analytica methods (9.11).26 Bitterness units were measured according to ASBC methods of

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analysis Beer 23A.20 Spectrophotometric analysis for total polyphenols and bitterness units were

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carried out using a Shimadzu PharmaSpec UV-1700 spectrophotometer, Shimadzu Corporation

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(Columbia, MD). Ethanol, residual extract, and pH were analyzed using an Anton-Paar

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Alcolyzer with supporting pH module (Anton Paar USA, Ashland, VA).

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Sensory Methodology: Multiple replication study

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For the multiple replication study, the sensory panel consisted of 10 members - 6 males

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and 4 females, ranging from ages 21 to 54, with a median age of 28. Thirty (30) unique beers

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were evaluated, 13 of which were also evaluated in the single replication study. The panel

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included 4 individuals with previous training on bitterness intensity and 6 self-identified frequent

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craft beer drinkers with minimal training on bitterness intensity. All panelists were over the age

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of 21 and self-identified beer consumers.

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Of the 30 beers evaluated, the majority were commercially categorized as pale ales, India

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pale ales (IPA), session IPAs, and imperial or double IPAs. Beer selection began by evaluating

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the chemistry of 60 unique beers from 17 American craft breweries. The beers were sorted based

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on the highest and lowest values of the seven chemical factors of interest. The 30 beers selected

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consisted of the extreme values of ethanol, residual extract, pH, isohumulones, humulinones, and

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humulones in the larger beer set and represented the wide range of variation found in heavily

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hopped beer styles.

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The panel met as a group for five one-hour training sessions. Training sessions focused

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on differentiating and identifying peak bitterness intensity in different beers. To minimize

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sensory fatigue only 10 beers were evaluated per one-hour session with three separate sessions

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making a full replication. The 30 beers were evaluated over the course of 12 sessions for a total

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of 4 replications. To minimize variation in bitterness intensity among the sessions, a randomized

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incomplete block design was used to ensure that the beers evaluated per session had

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approximately the same variance in BU values (See Supporting Information). Each 10-beer

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group was evaluated in its own session, and Qualtrics software (Qualtrics, Provo, UT) was used

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to generate a random presentation order for each panelist within each session. Beers samples (45

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ml) were presented in open 120 ml clear glasses, blind coded with random three-digit numbers.

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Beers were stored at 4°C for the duration of the study and removed from cold storage and poured

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30 minutes prior evaluation. Training and testing took place in the same location; a conference

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room held at 20°C and lit with Fluorescent lighting.

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At the beginning of each session, panelists were assigned a Chromebook tablet (Google,

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Mountain View, CA), and directed to an online Qualtrics survey. Each testing session began with

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the panelists warming up and calibrating bitterness intensity scaling by tasting four reference

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samples. External reference samples for anchoring the overall bitterness scale were chosen by

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using four commercially available beers of varying sensory bitterness intensities. The sensory

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scores for these references were determined by consensus during training. The zero reference

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point (0) was anchored by Michelob Ultra-Light (Anheuser-Busch, St. Louis, MO) (BU = 4), the

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low reference point (4) was anchored by Session Lager (Full Sail Brewing Co., Hood River, OR)

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(BU = 18)., the medium-low reference point (8) was anchored by Mirror Pond Pale Ale

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(Deschutes Brewery, Bend, OR) (BU = 40), and the medium-high reference point (15) was

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anchored by Torpedo IPA (Sierra Nevada Brewing Co., Chico, CA) (BU = 66). No reference

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was selected to anchor the high end of the scale (20) thereby reducing potential sensory fatigue.

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After the reference samples were evaluated, panelists were instructed to taste the samples

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in the order in which they appeared on their ballot. Panelists scaled the overall bitterness

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intensity of a given sample using a sliding bar scale (0 = none, 20 = extreme), and the scaling

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data were collected using Qualtrics. After assessing a sample, the panelists were instructed to

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rinse their mouths with a 0.1% pectin solution to aid in the reduction of bitterness carry-over,35

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and then to rinse their mouths again with deionized water. Panelists were instructed to wait until

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all perceivable bitterness had dissipated before tasting the next sample. Panelists repeated this

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procedure for each sample. After all samples had been assessed, panelists were allowed to re-

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taste the samples (if necessary) in any order deemed necessary to most accurately assess a given

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sample’s overall sensory bitterness intensity.

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Sensory Methodology: Single replication study

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For the single replication study, the panel consisted of 19 members - 14 males and 5

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females, ranging from ages 22 to 65, with a median age of 28. The panel contained 4 individuals

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with previous training on bitterness intensity and 15 self-identified frequent craft beer drinkers

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with minimal training on bitterness intensity. Of the 19 panelists, 4 also participated in the

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multiple replication study. The study started with 116 unique beers from 42 American breweries

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but was reduced to 104 unique beers from 38 American breweries, due to quality defects

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(preliminary data not shown). Thirteen (13) of the 104 beers had also been evaluated in the

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multiple replication study. This study included a greater number of beer styles in an effort to

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capture the variability within styles produced by craft and macro breweries alike. The beers were

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not screened based on their chemical composition prior to sensory evaluation.

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The panel met as a group for three one-hour training sessions. Training was followed by

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twelve testing sessions conducted over the course of ten weeks. Panelists evaluated 10 beers per

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session and scaled bitter intensity using a paper ballot. Paper ballots were utilized due to the

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limited number of available Chromebooks and the increased number of panelists. XLSTAT

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software was used to randomly assign the beers to each session, and to randomize the sample

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presentation order for each panelist. Two beers were selected to be replicated throughout the

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study thereby serving as internal controls: Fat Tire (New Belgium Brewing, Fort Collins, CO)

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served as a low bitterness intensity control (overall bitterness intensity = 3) (BU = 20)and

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Torpedo IPA (Sierra Nevada Brewing Co., Chico, CA) (BU = 66) served as the medium-high

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bitterness intensity control (overall bitterness intensity = 15). These beers were randomly

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replicated three times during the study. The remainder of the samples were not replicated.

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Panelists scaled the overall bitterness intensity of a given sample using a sliding bar scale (0 -

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20) on a paper ballot. Sensory training, commercial reference beers, environmental conditions,

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and general sensory protocol was carried out as described previously for the multiple replication

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study.

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Statistical analysis

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In the multiple replication study, each of the 30 beers was evaluated 40 times,

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independently (10 panelists over 4 replications). Panel performance ANOVA revealed

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significant main effects for panelist, beer, and panelist by beer interaction (Table 1). A

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significant panelist effect is not unexpected in sensory analysis as individual panelists interpret

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stimuli differently. No effects were observed for replication, replication by panelist, or

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replication by beer. The 40 bitterness intensity scores generated for each beer were averaged into

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a single value and assigned to that beer as an overall bitterness intensity score. Results were

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evaluated using a mixed model, two-way, analysis of variance (ANOVA) model. Fixed effects

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included beer. Random effects included panelist, replication, panelist by beer, replication by

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beer, and panelist by replication interactions. Data analysis was carried out using XLStat 2016

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(Addinsoft, New York, NY, U.S.A.).

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In the single replication study, most panelists missed at least one session during the study,

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thus each of the 104 unique beers was evaluated singly by 9 to 19 panelists. This unbalancedness

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with respect to number of panelists per beer required the generation of adjusted means for each

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beer (adjusted for panelist differences) to be used as the Overall Bitterness Intensity score for

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each beer.

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Multiple linear regression using stepwise (forward) model selection in the SAS

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GLMSELECT procedure was carried out for the seven predictive chemical factors of interest

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(linear and quadratic in each factor as well as linear-by-linear interactions) to develop a model to

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predict the overall bitterness intensity scores that were derived from each of the two sensory

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panel studies. The model selection criterion used was AICC (Corrected Akaike’s Information

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Criterion) and it was found that the same conclusions would be reached with other criteria

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(Akaike’s Information Criterion (AIC), Schwartz’s Bayesian Criterion (SBC) or prediction sum

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of squares (PRESS)). A model hierarchy requirement was used so that quadratic in a predictor

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could enter the model only when linear in that predictor was already present in the model and a

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linear-by-linear interaction could enter the model only when the two linear terms were already

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present in the model. Resampling and model selection for each resampled set of data was used

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to assist in determining the relative importance of predictors (effect selection percentage).

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Second order polynomial models and other linear models were fit with the SAS

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GLMSELECT procedure. Nested models were compared using F tests (numerator = the change

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in model sum of squares divided by the change in number of parameters; denominator = residual

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mean square from the full model).

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Results and Discussion

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The beers evaluated in this study presented a broad range of chemistry and sensory

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bitterness (Figure 1). Furthermore, the beer subsets as a group for each study were not

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statistically different as assessed by a means comparison (2-sided t-test, p>0.05).

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Across both studies, residual extract concentrations ranged from 2.5 to 8.1% w/w with an

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average concentration of 4.9% w/w (Figure 1.A). Residual extract concentration is largely

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determined by beer style. Lager beers often have lower residual extract relative to ales such as

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porters, stouts, pale ales and IPAs. Residual extract is mostly comprised of the un-fermentable

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carbohydrates that remain following the alcoholic fermentation, and these dextrins are primarily

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lower molecular weight polymers of D-glucose units linked by α-(1→4) or α-(1→6) glycosidic

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bonds. The breakdown of these dextrins in the oral cavity can lead to the sweet taste of some

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beers.14-15,

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extract to influence the flavor, mouthfeel, and bitterness of beer. Beers with increased bitterness

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tend to be brewed with a higher residual extract, a technique used by brewers to create

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“balanced” beers.6 Across all food systems, sweet taste suppresses bitter taste, and bitter taste

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suppresses sweet taste.14,

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taste qualities exhibit this inhibitory pattern.29-30

27

The residual extract also contains protein and minerals. Brewers adjust residual

28

This phenomenon is known as mixture suppression, and all basic

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Like residual extract, the ethanol concentration of a beer may be determined by beer

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style, however significant variation in alcohol concentration may also be found within styles. It is

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not uncommon to find “sessionable” (low ethanol) or “imperial” (high ethanol) versions of a

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brewery’s flagship beer seasonally. The beers in this study displayed a wide range of ethanol

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concentrations from 3.8% to 10.1% v/v. The average concentration of ethanol across both studies

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was 6.4% v/v (Figure 1.B). The influence of ethanol on beer flavor is multifaceted, and its effect

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on bitterness intensity is one example. Ethanol is considered to have a sweet taste at low

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concentrations,18 however numerous studies have shown that the presence of ethanol increases

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bitter taste sensation in alcoholic beverages.11,

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evaluating bitterness intensity of commercial beer, as many beers tend increase in both residual

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extract and ethanol concentration as hopping rates increase.

16-19, 28

This can be a confounding factor when

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The range of pH values was somewhat wider than expected at pH 4.0 to 5.4 (Figure 1.C).

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The elevated pH values are likely the result of beers with high levels of dry-hopping.8 It is worth

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noting, that as pH increases, so does the solubility of humulones (α-acids), lupulones (β-acids),

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and humulinic acid. A 1955 study by Spetsig showed that the solubility of these hop acids

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increased exponentially with pH.31 Thus, the effect of elevated pH via dry hopping may increase

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the concentration of humulones in finished beer.

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The solubility of humulones in wort and beer is low, and thus it was not unexpected to

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find very low levels of these compounds in the beers in this study. While the solubility of

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humulones is pH dependent, it has been reported to be approximately 3 mg/L in water.32 In a

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traditional brewing process, where the hop material is boiled in wort for an extended period of

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time (60-90 minutes), very little humulone will persist into the finished beer.1 In dry-hopped beer

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styles, the solvating power of ethanol increases the solubility of humulones. The majority of the

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beers tested in the study presented herein had little to no humulones, however four of the beers

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had humulone concentrations greater than their solubility in beer (14 mg/L)13 with a maximum of

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24.2 mg/L (Figure 1.F). Although humulones did not contribute bitterness to beer at these levels,

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they do adsorb at 275 nm and may contribute to a beer’s BU value if present. Because

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humulones may contribute to the BU value, but are not bitter, they may affect the BU’s ability to

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accurately predict bitterness intensity.13, 23

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As previously stated, isohumulones are the primary source of bitter taste in beer. They are

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isomers of hop-derived humulones which are transformed with heat and time via a first order

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reaction that is temperature-dependent.3 Isohumulone concentrations (as determined by HPLC)

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averaged 36 mg/L across both studies and ranged from 7.0 to 74.2 mg/L (Figure 1.D). The most

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prominent forms of isohumulone are isohumulone, iso-co-humulone and iso-ad-humulone,33-35

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and it is standard practice to sum their concentrations to obtain the reported value of

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isohumulone.20

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The role of oxidized hop acids has been the focus of several studies related to hop and

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beer quality.2, 36-38 Although there is little evidence to support the theory, there is a widespread

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belief within the brewing community that as hops age and decrease in total α-acids the increase

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in oxidized lupulones (hulupones) prevents the loss of bittering potential in the hop itself.32 Of

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the 121 unique beers tested in this study, most had no detectible levels of lupulones or their

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oxidation products. In a small number of cases, very low levels of hulupones were detected, but

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these levels were below the limit of quantification.

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In contrast, both the prevalence and concentration of the oxidized humulones

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(humulinones) (Figure 1.E) were higher than previously reported in literature. The average

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concentration of humulinones was 17 mg/L and 117 out of the 121 unique beers contained

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detectible levels of humulinones (≥1 mg/L). The concentration of humulinones in finished beer

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is dependent on the concentration of humulinones present in the hop varieties used, total hop

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mass, and hop contact time.4, 8 A recent study by Algazzali and Shellhammer confirmed the bitter

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quality of humulinones as previously published.35,

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detect humulinones as low as 8 mg/L, and it was proposed that humulinones have a relative

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bitterness intensity of 66% when compared to isohumulones.2 A recent study by Oladokun et

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al.40 examined the impact of hop bitter acids and polyphenols on beer bitterness in 34 global

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commercial lager beers. In this study humulinone concentrations were considerably lower (≤ 3

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mg/L) in the lager beers tested in comparison to the American hoppy ales and lagers tested in

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this study.40

39

The study’s trained sensory panel could

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The concentration of total polyphenols in finished beer is dependent on hop mass, hop

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type (extract, pellet or whole cone), the hop varieties used, the temperature of dry-hopping and

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contact time.9-10 Polyphenols comprise a vast group of different compounds that contribute to

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bitterness and/or astringency of beer.41 Typically, heavily late-hopped and/or dry-hopped beer

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styles contain elevated levels of total polyphenols.40 A study by McLaughlin and Shellhammer5

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showed polyphenols to have an additive effect on bitter taste perception when combined with 10

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mg/L isohumulones in lager beer. The magnitude in which polyphenols alone influence the

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bitterness of beer is currently not understood. However, Oladokun et al.40 showed polyphenols to

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influence the bitter quality of lager beer. In the study, beers with increased concentrations of

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polyphenols were perceived as having ‘harsh’ and ‘progressive’ bitterness. It is worth noting that

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these studies were conducted in lager beers with maximum total polyphenol concentrations

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below 300 mg/L. In this study, total polyphenol concentrations ranged from 135 to 697 mg/L

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with an average of 329 mg/L (Figure 1.G). Over 60% of the beers tested in the study presented

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herein contained total polyphenol concentrations in excess of 300 mg/L. Additional research is

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needed to understand the impact of polyphenols in beer at these concentrations.

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The BU method was developed in 1955 as a way to rapidly measure isohumulones prior

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to the advent of the HPLC.21 When analyzing beers in which isohumulones are the primary

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source of bitter compounds, the BU is an accurate predictor of sensory bitterness. In hop-forward

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beer styles, such as American craft IPAs and pale ales, brewers add hops to the wort late in

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production or to finished beer. This technique preserves volatile hop aroma compounds that

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would otherwise be lost during wort boiling. In addition to adding hop aroma, late additions of

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hops also add non-volatile compounds such as humulones, oxidized hop acids, and

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polyphenols.42 These compounds may contribute to a beer’s BU value, and at elevated

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concentrations may potentially impact a beer’s bitterness intensity. In this study, bitterness units

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ranged from 10 to 118 with an average BU of 60 (Figure 1.H). A mistaken conventional wisdom

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is that 1 mg/L of isohumulones is equal to 1 BU. Although this may hold true for low bitterness

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lager beers, the relationship did not hold true for the beers evaluated in this study (Figure 2).

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The beers tested had a wide range of sensory bitterness intensities (Figure 1.I). A variety

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of breweries, brands, and beer styles where tested, but an emphasis was placed on hop-forward

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beer styles, as one of objectives the study was to understand if the BU could accurately predict

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sensory bitterness intensity in these beers. At low levels of BU, the relationship between sensory

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bitterness intensity and the BU appeared to be linear. However, for BU values of 50 and above,

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the relationship became curvilinear, and increases in sensory bitterness intensity became smaller

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as the BU values increased (Figure 3, D & 4 D). This result may be from a saturation

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phenomenon, that is, as stimuli increases, it becomes increasingly difficult to differentiate

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changes in the stimuli as the senses become overwhelmed.30 Alternately, it may be that the

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compounds affecting increases in the BU at these elevated levels (> 50 BU) have a reduced

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impact on sensory bitterness intensity, or some combination of the two.

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For each of the two studies, model selection for predicting sensory bitterness intensity

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was conducted using all seven factors of interest (linear, quadratic and linear-by-linear

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interactions). For both studies, the most important predictors were linear in isohumulones, linear

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in humulinones, linear in alcohol by volume (ABV) and second-order terms involving

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isohumulones and/or humulinones). Because of the importance of linear and second-order effects

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involving isohumulones and humulinones, the second order response surface was investigated by

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fitting a full second-order model to the data (Eqn. 1).

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BI = β₀ + α₁(ISO) + γ(HU) + δ(ISO * HU) + α₂(ISO)² + γ₂(HU)²

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where BI = sensory bitterness intensity (0-20),

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ISO = Isohumulones and HU = humulinones (mg/L)

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(Eqn. 1)

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Within each study, the fitted model had the following characteristics:

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1) linear coefficients were similar to each other (α1 ≅ γ1);

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2) quadratic coefficients were similar to each other (i.e. α2 ≅ γ2);

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3) the interaction coefficient (δ) had the same sign as the quadratic terms (α2 & γ2) and

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(given the large standard error) was not very different from the sum of the quadratic

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coefficients.

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These three characteristics (and contour plots of the fitted surface) suggested that a much simpler

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model with a single predictor (sum(ISO + HU) = the sum of the isohumulones and humulinones)

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could predict sensory bitterness intensity well (Eqn. 2). Indeed, in both studies the simpler model

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fit well (R2= 0.913 in the multiple rep study and R2 = 0.772 in the single-rep study) and the more

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complex model (Eqn. 1) did not significantly improve the fit of the simpler model (F < 1, p >

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0.49 for both studies).

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 =  +  +  +   + 

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The effectiveness of sum(ISO + HU) as a predictor is shown graphically in Figures 3 and

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4. Individually, isohumulone and humulinone concentrations are relatively poor predictors of

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sensory bitterness (Figures 3 & 4, A & B), while the sum of isohumulones and humulinones

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(Figure 3 & 4, C) is almost as good a predictor of sensory bitterness as BU (Figure 3 & 4, D).

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These same figures also highlight a need for the model to capture curvilinearity as well as the

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greater variation about the relationship in the single-rep study (Figure 4) compared to the

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multiple rep study (Figure 3).

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(Eqn. 2)

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With the effectiveness of a single predictor established, model selection was repeated

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with sum(ISO + HU) as an 8th potential predictor. In both studies, the most important predictors

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were linear and quadratic in sum(ISO + HU) and linear in ABV (Eqn. 3). The addition of ABV

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increased the R-squared slightly, but significantly (p = 0.0002 for single-rep study and p=0.041

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in multiple rep study). The positive influence of ethanol on bitterness perception is not

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unexpected as it has been reported elsewhere that ethanol increases bitter perception in beer and

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wine.16-19, 27-28

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 =  +  +  +   +  + ₃ 

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It is important to note that although the simple sum of isohumulones and humulinones

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was effective as a single predictor, this does not mean that future studies should necessarily give

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equal-weight to isohumulones and humulinones. That is, a weighted sum of isohumulones and

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humulinones could potentially be even more effective as a predictor in future studies despite not

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being the case in this study.

(Eqn. 3)

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As it was devised, the BU describes the bitterness of beer in a linear fashion, and for low

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BU beers this relationship holds true. However, when using a linear BU response to predict

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bitterness intensity over the entire data set within each study, there was obvious systematic lack

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of fit with the tendency to under-predict in the mid-range of bitterness and over-predict at the

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extremes. Adding a quadratic term significantly improved the fit (p F Beer 29 11826 407.8 32.98