Tag Archives: beer measurements

IBUs and the SMPH Model

Introduction
When I first started brewing, the software I used had three options for predicting IBUs: Tinseth, Rager, and Garetz. The word “Tinseth” had a nice sound to it, so I chose that one. I was quite happy with that option until I became interested in flameout additions and hop stands, where the Tinseth formula predicts zero IBUs. Then I found out that I could get IBUs professionally measured at a very reasonable cost. So I did one small experiment to measure IBUs in finished beer with and without a hop stand. And then another experiment, and then another. Just when I thought I could predict IBUs reasonably well, I’d get results that challenged my assumptions. I wrote detailed blog posts about almost all of my experiments, so that anyone can (hopefully) replicate my findings. More than seven years and well over 300 measured IBU values after my first experiment, I put the finishing touches on a new model for predicting IBUs. The purpose of this post is not to go into the gory details, but to give an overview of the model’s higher-level concepts and to address some common misconceptions about the IBU. I also give test results that compare this model with four other IBU models on 18 different beers ranging from 20 to 70 IBUs.

This new model, called SMPH, is available at https://jphosom.github.io/alchemyoverlord/. Even if you don’t use it for recipe planning, I encourage you to play around with it to see how different brewing conditions can yield very different (or sometimes not so different) IBU predictions.

It’s important to note that I’ve been pretty obsessive about measuring or estimating volumes, alpha-acid ratings, weights of hops, hop steep times, wort cooling times, pH, and any other factor that seems relevant. While I’m not saying that you need to be this obsessive in your brewing (it’s supposed to be fun, right?), realize that small measurement or estimation errors might have a large impact on predicted IBUs. If your post-boil volume measurement is off by 10%, then your IBU prediction will also be off by 10%. There is also 10% to 15% variation in alpha-acid content within the same bale of hops [Verzele and De Keukeleire, p. 331], and so the AA rating on your package may not be an accurate indicator of the amount of alpha acids that are in your hops. If your predicted IBU value is off by 20%, that might reduce your prediction from 40 to 32 IBUs. If you’re unlucky, all of these measurement errors can add up and make the prediction meaningless; if you’re lucky, they can cancel each other out. Your mileage may vary.

If predicting IBUs is such an imprecise and difficult art form, why bother? Obviously, you don’t need to care about predicting IBUs if you’re happy with the bitterness levels of the beers that you make. Or, if you find that a beer turns out more (or less) bitter than you’d like and you don’t mind brewing it again with a different amount of hops (or adding iso-alpha acid extract, or blending several beers), then you don’t need to worry about it. But, if you find that your first attempt at a beer can sometimes yield a bitterness that isn’t quite right, you may want to get the best prediction of bitterness that you can before brewing. That prediction might still be a bit off, but an in-the-ballpark estimate is still better than no estimate at all. By way of analogy, even though pH test strips aren’t as accurate as a digital pH meter, if you don’t have a pH meter it’s still better to use test strips than to pretend that pH doesn’t matter and ignore it.

IBUs: IAAs and ABCs
The IBU is a measurement of the amount of infrared light absorbed by a sample of processed beer [Thermoscientific; Anon.]. It is often (and incorrectly) reported that one IBU equals one part per million (ppm) of isomerized alpha acids (IAAs). However, as Val Peacock explains, the IBU was developed in the 1950s and 1960s to measure the combination of both IAAs and “auxiliary bittering compounds” (ABCs) [Peacock, pp. 158-161]. The researchers at that time knew that there are bitter substances in beer other than IAAs, and they deliberately included them in the IBU measurement. The IBU combines the concentration of IAAs and ABCs in beer into a single measure of approximate bitterness. The confusion about one IBU equaling one ppm of IAAs has come up because they scaled the IBU measurement so that the two numbers would often be close to each other. However, this rough correspondence only holds under specific brewing circumstances that were common in the 1960s and are less common today. When the IBU was developed, IAAs contributed to about 70% of the IBU value, and ABCs contributed the remaining 30%. The proportion of IAAs contributing to the IBU can change greatly depending on brewing techniques and how well the hops have been stored. In the 18 beers used in testing the SMPH model (described in more detail below), I estimate that IAAs contribute to between 50% and 75% of the IBU. (A West-Coast IPA with lots of late-hop and dry-hop additions has an IAA contribution of 50%, and a more traditional beer with one early and one late addition has an IAA contribution of 75%.) In the data used for finding SMPH parameter values, the estimated IAA contribution ranges from 0% to over 80% of the IBU.

I have found that the largest fraction of ABCs are oxidized alpha acids (oAAs) that are produced when hops are added to hot wort [Algazzali, p. 17]. I estimate that about 10% of the available alpha acids oxidize quickly in boiling wort, producing oAAs. In most beers, the second-largest contributors to ABCs are malt and hop polyphenols, followed by oxidized beta acids. In her Master’s thesis, Christina Hahn (advisor: Tom Shellhammer) notes that “individually, iso-alpha acids and [oxidized alpha acid] concentrations are relatively poor predictors of sensory bitterness, while the sum of iso-alpha acids and [oxidized alpha acids] is almost as good a predictor of sensory bitterness as [the IBU]” [Hahn, p. 48]. She found a strong correlation (R2 = 0.86) between sensory bitterness and the IBU, and a strong correlation (R2 = 0.80) between sensory bitterness and the combination of IAAs, oAAs, and alcohol (ABV) [Hahn, p. 50]. In short, the concentrations of IAAs and oAAs are, together, very good predictors for both sensory bitterness and the IBU. These findings support the claim that oAAs are the largest component of the auxiliary bittering compounds.

SMPH Model: The Big Picture
The SMPH model was developed to have one key advantage over other IBU models: it separates out the contribution of isomerized alpha acids (IAAs) from auxiliary bittering compounds (ABCs). The conversion of alpha acids to IAAs takes place relatively slowly (e.g. over the course of an hour-long boil), but ABCs are quickly produced or dissolved in the wort. These different time scales mean that IAAs and ABCs should be modeled separately. (The mIBU calculator includes some approximations in this regard, but it is inherently limited in its ability to accurately separate the two.) While IAAs contribute the most to the IBU in “typical” beers (if there is such a thing as a typical beer anymore), ABCs can contribute a significant amount, especially when using hops late in the boil, when using a hop stand, and/or when dry hopping (techniques commonly used in brewing IPAs).

The starting point for development of the SMPH model was an understanding of Val Peacock’s explanation that IBUs are a specific proportion of the concentrations of IAAs and ABCs in beer [Peacock, p. 161], and realizing that Mark Malowicki’s model of the production and degradation of IAAs in boiling wort [Malowicki, p. 27] could be combined with rough estimates of the concentration of each ABC and different loss factors to predict IBUs. At that point there was the skeleton of a model but a lot of missing factors and unknown parameter values. These values were determined (or found to be irrelevant) by controlled experiments in which only the factor in question was varied. Data from those experiments were gradually added to the set of model training data. The process of estimating a loss factor and then minimizing the mean-squared error on the remaining parameters was iterated until the error on a cross-validation set was reduced to an acceptable level.

The SMPH model first makes a prediction of the concentration of IAAs in wort using Malowicki’s model of alpha-acid isomerization. It then estimates of the concentration of each auxiliary bittering compound in wort. The concentrations of IAAs and ABCs are then modified by various factors (described below) occurring during the boil, fermentation, and conditioning. Finally, it uses an equation proposed by Val Peacock [Peacock, p. 161] to convert from these estimated concentrations in beer to a final IBU value.

Like the Garetz model, the SMPH model can account for a large number of factors that influence IBUs. In the SMPH model, that means accounting for the boiling point of water, wort gravity, wort pH, wort clarity (e.g. a careful vorlauf vs. brew-in-a-bag wort collection), form of the hops (whole cones or pellets), hopping rate, hop freshness, krausen loss, flocculation, finings, filtering, and age of the beer. Basically every step in the brewing process seems to have some influence on IBUs.

The SMPH model uses approximations of all of the known factors that might influence IBUs. (Unknown factors are probably still waiting to be discovered.) The goal has not been to precisely quantify each of the myriad factors (I only have one life to live), but to put all of the approximations together into one imperfect but reasonable model. Where even approximations have been difficult to come by, I used over 300 measured IBU values to find the parameter values that give the best fit to the data.

Figure 1 illustrates the different components of the SMPH model. Measured IBU values from finished beer are shown at 10-minute intervals during a 90-minute boil. The green area shows the contribution from isomerized alpha acids (using the Malowicki model), the blue area shows the contribution from oxidized alpha acids, and the red area shows the contribution from malt and hop polyphenols. The SMPH model output is the sum of these contributions. (In this example, the hops were well preserved and so the contribution from oxidized beta acids is negligible.)

Figure 1. Measured IBUs and the components of the SMPH model.

A much more detailed explanation of the concepts and factors used in the SMPH model is described in a separate blog post, A Summary of Factors Affecting IBUs.

Factors Influencing IBUs
The SMPH model accounts for a number of factors that influence IBUs. These factors can be put into one of three groups for the purposes of discussion: “large-impact”, “medium-impact”, and “small-impact” factors.

Large-Impact Factors
The factors that can have a large impact on IBUs are (a) hops added to hot wort (kettle hops) vs. ambient-temperature or “cold-side” wort (dry hops), (b) form of the hops (whole cones or pellets), (c) hopping rate, (d) wort pH, and (e) wort clarity.

Kettle vs. Dry Hops: Hops added to hot wort in the kettle undergo alpha-acid isomerization, which produces the majority of bitterness in most beers. Dry hopping will produce no IAAs, but in large amounts it can produce significant bitterness from ABCs [Parkin, pp. 33-34; Maye and Smith, p. 135], especially from oxidized alpha acids created during hop storage. Oddly enough, at higher IBUs the use of dry hopping also reduces the concentration of IAAs from kettle additions [Parkin, p. 34; Maye and Smith, p. 135]. The IBUs from a dry-hop addition are difficult to estimate, but the difference between adding hops to the boil kettle or to the fermentation or conditioning vessel will have the largest impact on the IBU value.

Form of Hops: Hop pellets produce more IBUs than whole cones. With pellets, the production of oxidized alpha acids when hops are added to the boiling wort is about double that of whole cones. This factor seems to be variety specific, with some varieties producing very little increase from pellets, and other varieties producing a large increase. The rate of alpha-acid isomerization appears to be the same when using pellets or whole cones.

Hopping Rate: It is well known that doubling or tripling the amount of hops generally won’t produce a doubling or tripling of the IBU. As the concentration of hops increases, the resulting IBU value increases more slowly. An alpha-acid solubility limit is a reasonable explanation for this effect, with all alpha acids dissolving up to about 200 ppm and a reduction in the percent that dissolves as the alpha-acid concentration increases. Mark Garetz incorporated a hopping-rate factor into his model, but I suspect that he underestimated the effect.

Wort pH: I’ve found that lowering the pH from 5.75 (the approximate pH of a mash made from untreated low-alkalinity water and two-row malt) to 5.25 (within the recommended range of 5.2 to 5.4) can reduce IBUs by 15% to 35%. Most of the decrease in IBUs appears to come from a loss of ABCs, with only a small loss of IAAs.

Wort Clarity: Much to my surprise, I’ve found that the clarity of the wort can have a significant impact on IBUs. In this case, “clarity” refers to how visually clear or cloudy the wort is when it is transferred to the fermentation vessel (FV), ignoring the effect of hop matter. Cloudy wort yields relatively fewer IBUs. In other words, wort produced using the brew-in-a-bag technique with no filtering of the grain bed can yield a much lower IBU value than clear wort produced with a careful vorlauf and good grain-bed filter. (This is not to say that one method is better than the other, just that they may yield different IBUs.) Likewise, stirring the wort just before transferring into the FV can produce a lower IBU value than letting the wort settle and racking only the clear wort into the FV. I’ve observed very clear wort producing 30% more IAAs than typical wort, and very cloudy wort producing 30% fewer IAAs than typical wort. The reason for IBUs being affected by wort clarity is unknown, but wort protein levels do not seem to be a factor.

Medium-Impact Factors
Factors that often have only a medium impact on IBUs are: (a) how well the hops have been stored (hop freshness), (b) wort specific gravity, (c) the use of a hop stand, (d) losses to krausen deposits, and (e) the age of the beer.

Hop Storage Conditions: The storage conditions of hops can have a large impact on the amount of alpha acids remaining in those hops. As the amount of alpha acids decreases due to poor storage conditions and/or longer storage duration, the amount of oxidized alpha and beta acids increases, somewhat mitigating the reduction in IBU values [Peacock, p. 162]. (Nitrogen-flushed packaging and cold storage are the best ways to preserve hops.) While differences in storage conditions may not have a large effect on the IBU, I think storage conditions do have a large impact on overall beer quality.

Wort Gravity: Wort gravity is one of the factors common to all IBU prediction models. On average, the difference in IBUs between a 1.030 wort and a 1.080 wort is about 15%. The difference between a 1.040 wort and a 1.070 wort is about 10%.

Hop Stands: During a hop stand, alpha acids continue to isomerize in the hot wort, increasing the IBU. The amount of impact from a hop stand depends a lot on the duration of the stand and when hops are added to the wort, so I’ve classified this as a medium-impact factor.

Krausen: Most brewers let krausen deposits accumulate on the sides of the fermentation vessel. If you skim off the krausen as it is produced (which is sometimes recommended to produce a “smoother” beer [e.g. Troester; Hough et al., pp. 652-653]), the resulting IBU value can be about 5% to 10% lower. If you use a blow-off tube and remove a lot of the krausen, the IBU value may be 25% lower. If you mix the krausen back into the beer (or use an anti-foaming agent) during fermentation then the IBU may be about 10% higher. I’ve classified krausen as a medium-impact factor because the loss of lots of krausen through a blow-off tube is quite possible but perhaps not so common.

Age of the Beer: After primary fermentation, IBUs will decrease as the beer conditions. I have noticed a 20% decrease in IBUs as a beer ages from 1 week to 13 weeks at about 60°F (16°C). While a lot of the decrease seems to happen in the first several weeks, most beers aren’t conditioned for months at cellar or room temperature, and if a beer is conditioned or stored at cold temperatures, IBUs are probably much better preserved. Therefore, I’ve put this factor in the “medium-impact” category, but it’s probably a small impact for cold-conditioned lagers.

Small-Impact Factors
The factors that usually have a minor impact on IBUs are (a) the boiling point of water, (b) the rate at which wort is force-cooled after flameout or a hop stand, and (c) flocculation, finings, and filtering.

Boiling Point of Water:
The difference in IBUs when brewing at sea level compared with Boulder, Colorado or Johannesburg, South Africa is about 20% for typical beers. This would be a large-impact factor, but most cities are at 1000 feet (300 meters) or less, in which case the impact is 4% or less. (In a typical beer, the majority of IBUs come from alpha-acid isomerization, and we can use the Malowicki model of temperature-dependent isomerization to estimate the impact of altitude.)

Rate of Wort Cooling: After flameout or a hop stand, alpha acids continue to isomerize in the hot wort while it is force-cooled, down to about 140°F (60°C). These post-boil IAAs increase the IBU. While there may be a large difference in IBUs when going (for example) from an ice bath to a Hydra wort chiller, smaller differences in cooling technique may have only a small impact on IBUs.

Flocculation, Filtering, and Finings: These factors are each estimated to influence the IBU by about 5% or less [Garetz, pp. 140-140; Fix and Fix, p. 129].

No-Impact Factors
There is one more group of factors that aren’t in the SMPH model because I don’t believe that they have any meaningful impact on IBUs. Such factors include the kettle size and kettle geometry, containing hops in a mesh bag, and the use of malt extract instead of wort from all-grain brewing. Kettle size or geometry is sometimes claimed to have an impact on IBUs, but one explanation for the correlation between kettle size and IBUs is the time it takes to cool a large volume of wort and the isomerization that happens while the wort is being cooled. My experiments have used a wide range of volumes, and I’ve seen no effect of volume or kettle size on IBUs. However, it is possible that hydrostatic pressure is a factor that may increase IBUs; an experiment by Brülosophy found a significant perceptual difference resulting from a change in hydrostatic pressure.  Further tests of IBUs and hydrostatic pressure may yield interesting results.  Putting hops in a mesh bag is sometimes claimed to reduce IBUs, but experiments conducted by both Brülosophy and me have shown no meaningful difference in measured IBUs. I’ve also heard that brewing with malt extract can yield different IBUs than with all-grain brewing, but my direct comparison of beers brewed with Briess Pilsen Dried Malt Extract and Great Western Premium two-row malt showed no meaningful difference in measured IBU values. (Also, I can think of no plausible mechanism through which the concentration of wort into dried malt extract could affect alpha-acid isomerization or the concentration of ABCs.) Future experiments may show some relationship for some of these factors under different conditions, for example with hops in a fine-mesh bag or specific brands of malt extract, but for now there is no known difference worth modeling.

SMPH Parameter Estimation
For most parameters in the SMPH model, estimated values could be obtained from the literature, direct experimentation, or reasonable assumptions. For a few parameters, though, there was no good estimate: (a) the loss of IAAs to trub during the boil, (b) what percent of the available alpha acids are quickly oxidized when added to hot wort, and (c) what percent of the alpha acids that oxidize during storage are dissolved when added to wort. In addition, I wanted to use all available data to get better estimates of the two parameters used in a hopping-rate correction model. A set of 347 measured IBU and IAA values were used to estimate values for these five parameters. (Four IBU and four IAA values were taken from Val Peacock’s reported numbers [Peacock, p. 162]. The other values came from my experiments.)

While this may seem like a lot of data for estimating five parameters, the estimation was complicated by the fact that I often didn’t have precise estimates of the alpha-acid content on brew day and/or how the hops had degraded during storage. Each measured value was therefore associated with a small parameter search for these experiment-specific values as well as the five common values.

Optimizing the parameter values to fit the data resulted in a root-mean-square (RMS) error of 1.6 IBUs and a maximum difference of 7.1 IBUs (for a condition that had 81 measured IBUs). The estimated loss factor for IAAs during the boil is 0.51. The percent of available alpha acids that quickly oxidize when added to hot wort is estimated at 11%. The percent of storage-generated oxidized alpha acids that dissolve in the wort is estimated at 33%. The solubility of alpha acids (for hopping-rate correction) is estimated to have a minimum limit of 200 ppm (below which all alpha acids are dissolved) and a maximum of 580 ppm.

Test Results
To evaluate and compare different IBU models, I collected an additional set of 18 IBU values that were not used in parameter estimation or for cross-validation of the SMPH model. These values ranged from 20.2 to 70.0 IBUs, including a variety of ale styles (two stouts, one ESB, one Kölsch, an English IPA, a West-Coast IPA, and twelve single-malt-and-single-hops (SMASH) beers with different timings of the hop additions). All IBU values were measured from finished beer.

The table below shows, for five IBU models, the RMS error and maximum difference between a measured and modeled IBU value on this set of 18 data points.

Model RMS Error (IBUs)
Max. Error (IBUs)
SMPH 2.4 5.2
Tinseth 20.4 70.5
Rager 39.6 137.9
Garetz 12.34 28.14
mIBU 11.4 33.2

Figure 2 compares measured IBUs and predicted IBUs for the five models, with measured IBUs on the horizontal axis and predicted IBUs on the vertical axis. The straight dashed line from lower left to middle right indicates where predicted and measured IBUs are equal. It can be seen that on this set of data, the Tinseth, Rager, and mIBU models all have very large predicted IBUs for the higher-IBU beers. The Garetz model has a good fit with the higher-IBU samples, but predicts values about 50% too low in the range of 20 to 25 IBUs.

Figure 2. A comparison of measured and predicted values for five IBU models.

Other Considerations
Some people are more sensitive to bitterness than others [Reed et al., p. 215]. From what I’ve observed, people who are very sensitive to bitterness find it unpleasant, and therefore they don’t tend to drink high-IBU beers. Also, the perception of bitterness changes with each sip. Therefore, I wouldn’t worry much about minor IBU differences; getting somewhere in the ballpark is probably just fine.

The IBU scales linearly with the concentrations of IAAs and ABCs. Bitterness, like most perceptual phenomena, does not increase linearly with the strength of the stimulus (as noted by Fechner’s law). Therefore, there is a divergence from the linear relationship between IBU values and the perception of bitterness, starting at about 60 IBUs [Hahn, p. 50]. However, as noted earlier, there is a strong correlation between IBUs and perceived bitterness, even at high IBUs. Hahn has developed a quadratic equation to map between IBUs and perceived bitterness, accounting for this non-linearity [Hahn, p. 50]. The SMPH calculator includes Hahn’s perceived bitterness value (or “bitterness intensity”) as an additional output.

Oxidized alpha acids are perceived as being about 34% less bitter than isomerized alpha acids [Algazzali, p. 45]. They absorb about 8.5% less infrared light than IAAs when measuring the IBU [Maye et al., p. 25, Figure 7], and so their perceptual bitterness is about 28% less than their measured contribution to the IBU (0.66/0.915 = 0.72). This is enough of a difference that if a beer containing only oxidized alpha acids (no IAAs) has 40 measured IBUs, it might be perceived as having the bitterness of a beer with only 29 IBUs.  This difference of 11 IBUs is above the perceptual threshold of 5 IBUs [Daniels, p. 76].

If the concentration of residual sugars in a beer is low and the IBU is large, the resulting beer may be perceived as overly bitter. Likewise, if there are a lot of residual sugars and a low IBU, the beer may be considered too sweet. Hahn’s perceptual study did not control for residual sugars, and yet panelists were able to fairly consistently judge a beer’s bitterness. The perception of bitterness and sweetness are different, but we prefer some relationship between them in our beers. The ratio of IBU to original-gravity points can be a useful (if imprecise) way to estimate this bitter/sweet balance and design a pleasing beer. Personally, I find that an IBU/OG ratio of about 0.5 creates a “balanced” beer a bit on the sweeter side, and an IBU/OG ratio of about 1.0 creates a pleasantly bitter (e.g. West-Coast) IPA.

One of the advantages of the Tinseth, Rager, and Garetz models is that no computer is needed to estimate IBUs. You just need to look up some values in tables and do basic math. These models are also easy to program, which has contributed to their popularity in brewing software. Unfortunately, the SMPH calculator is quite complex, using thousands of lines of code to compute concentrations and loss factors. This calculator is, however, available online to anyone who wants to use it.

Summary
An IBU value is determined by measurement of the amount of infrared light absorbed by (acidified) beer. The IBU deliberately includes the effects of both isomerized alpha acids and auxiliary bittering compounds. Even at higher IBUs, there is a strong correlation between IBUs and the perception of bitterness. IBU prediction usually doesn’t need to be very precise, because many people aren’t really all that good at detecting minor (or sometimes even moderate) differences in bitterness.

The SMPH model is a new method for estimating IBUs, which may be useful when trying to predict a beer’s bitterness before brewing. A key difference between the SMPH model and other IBU models is that it accounts separately for the contribution of IAAs and ABCs. Predicting IBUs is a bit of a “black art”, because there are so many variables and there is so much variability. The only way to really know the IBU level of a beer is to have it professionally tested, which is something I highly recommend.

Acknowledgments
I’d like to give a big shout-out to Dana Garves at Oregon BrewLab for the IBU measurements (as well as protein, polyphenol, and other measurements) used in developing the SMPH model.  I can always rely on the accuracy of the measured values and Dana’s cheerfulness. Scott Bruslind at Analysis Laboratory was also hugely supportive, helpful, and encouraging with my initial experiments. Zach Lilla at AAR Lab has been a friendly and reliable source for measuring alpha and beta acids (and the hop storage index) in my hops. I’d also like to thank Glenn Tinseth and Randy Mosher for prompt and encouraging answers to my out-of-the-blue questions. I greatly appreciate the spirit of cooperation and support that is a critical part of the homebrewing culture.

The SMPH model would not have been possible without the excellent research and publications by Tom Shellhammer (and his graduate students) at Oregon State University, Mark Malowicki (in particular), and Val Peacock at Hop Solutions, Inc.  While the model would not have been possible without their previous work, they had no input on its development, and so the name “SMPH” is simply a sequence of four letters, not an acronym.

References

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Four Pilot Studies for Maximizing Hop Flavor with Late-Hop Additions

Abstract
The purpose of the experiments described here was to estimate at what point in the boil, and at what temperature, hops should be added in order to maximize hop flavor.  The first two perceptual tests were conducted using beers with the same amount of hops added at different times before flameout (from 1 to 20 minutes).  The third test was conducted with the same amount of hops added at 10 minutes before flameout and the kettle covered or not covered.  The fourth test was conducted with hops added at 10 minutes before flameout to boiling wort or to wort held at 170°F (77°C) .  The bitterness of the beers within each perceptual test was kept constant by adjusting the amount of a 40- or 45-minute hop addition.  These experiments were pilot studies due to the small number of test comparisons, the use of a single test subject, and the use of a single variety of hops.  The results indicate that hop flavor may be most pronounced with a 1-minute steep time, that evaporation has a gradual effect on hop flavor (with 10 minutes probably corresponding to a just-noticeable difference), and that the difference between a 1-minute and 20-minute steep time with an uncovered kettle was the most easily perceived of the conditions tested.  The 10-minute hop stand at 170°F (77°C) showed no perceptual difference from a 10-minute boil.  The results suggest that a “best practice” for maximizing hop flavor may be to add the hops very close to flameout, but that other late-hopping techniques may produce results that are perceptually very similar.

1. Introduction
The purpose of the experiments described here was to estimate at what point in the boil, and at what temperature, hops should be added for maximum hop flavor.  The term “hop flavor” can mean different things to different people.  For example, George Fix says that it has been traditionally (and not quite correctly) believed that the hop resins (which are responsible for bitterness) contribute to hop flavor, while the hop oils (including flavor compounds) contribute to hop aroma [Fix and Fix, p. 33 (emphasis mine)].  In this case, because the resins are responsible for bitterness, the term “hop flavor” is associated with the taste of bitterness.  Somewhat more recently, it has been recognized that hop oils contribute to hop “flavor and aroma” [Oliver, p. 539] and that “late-hopping [is] a well-accepted technique for adding hop flavor and aroma” [Oliver, p. 539], and so “hop flavor” can refer not to a bitter taste, but to a distinct non-bitter flavor.  Mark Garetz uses the term “character” to define this non-bitter flavor [Garetz, p. 14].  In this post, I use the term “flavor” for the non-bitter hop flavor that comes from the hop oils, with typical descriptions such as “floral,” “citrus,” “spicy,” “grapefruit,” or “earthy.”  These oils are also responsible for hop aroma [Oliver, p. 539], and so the terms “flavor” and “aroma” are often used together to describe their sensory impact.  I will use the term “flavor” with the understanding that flavor and aroma are intertwined.

It is usually said that hops should be added earlier in the boil for bitterness and later in the boil for flavor and/or aroma [e.g. Fix and Fix, p. 33; Garetz, pp. 10-11; Noonan, p. 160; Oliver, p. 539]. Therefore, the experiments in this blog post focus on late-hop additions ranging from 1 to 20 minutes before flameout and forced cooling.  (The distinction between “early” and “late” hopping is at around 30 minutes before flameout [Oliver, p. 539].)

While the belief in late hopping for flavor is nearly universal, it is difficult to find in the literature a “best” time for maximizing flavor or a quantified relationship between hop steep time and flavor.   Greg Noonan says that “flavoring hops are commonly added ten or fifteen minutes before the end of the boil for lager beer” [Noonan, p. 159].  Charlie Papazian is the only source I know of who provides a graph of the relationship between steep time and hop flavor, with a peak at 10 minutes before flameout (and a separate peak at 0 minutes for aroma) [Papazian, p. 68], but it’s unclear what set of data was used to produce this graph.  It is possible that chemical reactions between boiling wort and hop oils require some amount of time to produce the most hop flavor in finished beer.  Because flavor and aroma are intertwined, and the oils responsible for hop aroma are lost with evaporating steam [e.g. Lewis and Young, p. 271], it’s also possible that  peak hop flavor comes from flameout additions.  The use of hop stands, with hops steeped at below-boiling temperatures, are common in hop-forward ales and might also contribute to increased hop flavor.

Attempting to answer the question of when to add hops for maximum flavor presents two logistical challenges.  The first challenge is that the bitterness of beer increases with hop steep time and temperature, and so simply adding the same amount of hops at different times or temperatures will change the bitterness level in addition to any flavor changes.  This topic is discussed more in Section 2.  The second challenge is how to measure hop flavor in order to know when it has been maximized.  The perceptual-testing approach used here is discussed in more detail in Section 3.

I’ve created a separate web page as an interactive tutorial for the mathematics behind perceptual difference testing, including significance testing, the power of a test, likelihood ratios, estimating the effect size (d’), and confidence intervals.  These different analysis methods can be used to obtain a detailed interpretation of the results, which can be especially useful when the number of samples per trial is small and/or the statistical power of the test is low.

The perceptual experiments described below used only a single test subject and a single hop variety (Amarillo).  In addition, the number of test samples used in these experiments was too small to reliably detect minor perceptual differences. These experiments are therefore pilot studies; results are tentative and these results may or may not be supported by future studies.  Having tentative results is at least a first step toward having more conclusive results.

2. Controlling for Bitterness
In order to control the bitterness level of the beers in these experiments, I used up to two hop additions in each condition.  One addition was the same weight of hops added at different times or temperatures before flameout.  Another addition (if used) was always made at 40 or 45 minutes before flameout (40 minutes for the first two experiments; 45 minutes for the second two), and the weight of this other addition was varied in order to target the same IBU value across all conditions within a test.  Because additions at 40 or 45 minutes are considered to be primarily for bittering and not for flavor, the goal was to change the flavor with the timing of the late-hop addition but to keep total bitterness of each condition the same with the smaller but earlier addition.

To predict IBU values for each condition, I used the technique described in Estimating Isomerized Alpha Acids and nonIAA from Multiple IBU Measurements.  This technique is used, with Mark Malowicki’s model of alpha-acid isomerization [Malowicki], to estimate two parameters for modeling IBUs: scalingIAA and scalingnonIAAhops.  The scalingIAA parameter indicates how much of the isomerized alpha acids (IAA) are lost during the boil and fermentation, and the scalingnonIAAhops parameter indicates (a) what percent of the weight of the hops becomes auxiliary bittering compounds during the boil and (b) to what degree these compounds are lost during the boil and fermentation.  I obtained initial estimates of these two parameters from a preliminary study.   I used these values, along with wort volume, weight of the hops, AA rating, pH, and original gravity to predict IBUs.  The preliminary study and all experiments described here used hops from the same one-pound (0.45 kg) bag, to keep the alpha-acid (AA) rating and alpha-acid decay factor [e.g. Garetz, pp. 103-118] as equal as possible across conditions.

For the late-hop addition, I targeted an initial alpha-acid concentration close to the estimated alpha-acid solubility limit of about 200 ppm.  The IBU prediction technique estimates a certain IBU value from this amount of hops, wort, temperature, and steep time (ranging from 1 up to 20 minutes).  I then adjusted the weight of another hops addition, always added at 40 or 45 minutes before flameout, so that the model predicted the same total IBU value across all conditions within an experiment.  The goal was to have all of the conditions in a perceptual comparison within 5 measured IBUs of each other, as 5 IBUs has been reported to be the perceptual threshold [Daniels, p. 76].  Up to about 50 or 60 IBUs there is a strong linear relationship between IBUs and perceived bitterness [Hahn, p. 50], and so for beers in this range the IBU is a good (and linear) metric for perceived bitterness.

3. Flavor Testing Methodology
3.1 Overview
To measure hop flavor, I used the triangle test (also used at Brülosophy) in order to judge whether two conditions can be distinguished from each other [e.g. Angevaare; Society of Sensory Professionals].  In the triangle test, a test subject tastes three samples of beer where two of the samples are from the same condition and one is from a different condition.  The subject is asked which one of the three beers is different.  This test is repeated a number of times.  If the number of correct answers is above a threshold, then the two conditions can be considered perceptually different.  It is important to note that if the number of correct answers is below the threshold, nothing can be concluded from a standard significance test; standard significance testing can not accept the hypothesis that there is no perceptual difference between two conditions.  However, likelihood ratios can be used to estimate the relative strength of the evidence for whether two beers are perceptually the same or different.  We can also estimate the effect size (d’), which indicates the amount of difference between the two conditions.  A d’ of 0 indicates identical conditions, a d’ of 1.0 corresponds to a just-noticeable difference, and larger values of d’ indicate greater perceptual differences.

In this test, the beer judged as different was also rated by the subject as having either “more hop flavor” or “less hop flavor” than the others.  By comparing beers at a range of steep times, one can first determine which steep times can be distinguished from each other.  Then, for those samples that are correctly identified as different, one can look at how often one steep time is judged more flavorful than the other.

3.2 Testing Details
These experiments used a single subject or taster (this author).  This single-subject design has advantages and disadvantages.  One significant disadvantage of using a single subject is that the results from these experiments may or may not generalize to the larger population.  One significant advantage of using a single subject is that there is probably a lower threshold for detecting perceptual differences, compared with a larger group of subjects.  (Even if the one subject has a high threshold compared with the average population, the variance in the responses will be less for one subject than for many subjects due to individual threshold differences.  This variance in responses negatively affects the effect size (lowering the value of d’), making it more difficult to distinguish between conditions in a study with many subjects.)

In the first two perceptual studies, both experiments had four conditions for different hop steep times, labeled A, B, C, and D in Experiment #1 and E, F, G, and H in Experiment #2. This resulted in six comparisons between conditions (in Experiment #1, Condition A vs. B, A vs. C, A vs. D, B vs. C, B vs. D, and C vs. D).  Each comparison was tested eight times, for a total of 48 tests per experiment.  The third experiment had two conditions: (J) kettle covered or (K) uncovered during the 10-minute late-hop addition.  The fourth experiment also had two conditions: hops added to (L) boiling or (M) 170°F (77°C) wort for 10 minutes.  Each of the comparisons in the third and fourth experiments was tested 24 times.  The final two perceptual studies were conducted simultaneously, for a total of 48 tests.

A computer program was written to arrange the tests in random order with random ordering of conditions within a test.  Tests were conducted up to four times per day with at least an hour between tests (to reduce order effects), and so each experiment took about two weeks to test.  A second person poured samples for two to four tests every morning according to an instruction sheet with the randomized order of conditions.  Each test sample was 1.5 oz (44 ml), and so more than 74 oz (2.2 liters) of each condition were required for testing.  While the beers were stored close to freezing to preserve flavor, each sample of beer came up to room temperature before tasting.

The subject marked their responses (i.e. indicated the beer that was judged different, and if they thought this beer was more or less flavorful than the others) on a separate sheet.  Testing was conducted in a quiet room with as much time as needed for making a decision.  The subject did not know the correct answers until the end of the experiment.

3.3 Evaluating Results
With eight tests of a comparison and a significance level of 0.05, six tests need to be correctly identified in order to reach statistical significance and reject the null hypothesis of “no perceptual difference.”  At the same significance level, seven of the eight comparisons need to be correctly identified in order to reach statistical significance rejecting the null hypothesis of a just-noticeable difference (JND).  Unfortunately, with only eight results per trial, the power of a significance test comparing no perceptual difference against the JND is an abysmal 6%, meaning that 94% of the time that there really is a just-noticeable perceptual difference, a statistically-significant result will not be obtained.  (This is one reason why a test result that does not show significance should not be used to conclude that the conditions are perceptually equal.  These experiments were conducted with the expectation that there would be more than a just-noticeable difference in at least one comparison.)

With 24 tests of a comparison and the same significance level, 13 tests need to be correctly identified to reach statistical significance and reject the null hypothesis of “no perceptual difference”, and 16 tests need to be correctly identified in order to reject the null hypothesis of a just-noticeable difference.  The power of a test comparing no perceptual difference against the JND is still a miserable 15%, meaning that 85% of the time that there really is a just-noticeable perceptual difference, a statistically-significant result will not be obtained.

In order to obtain more information from the test results, the likelihood ratios and maximum-likelihood estimates of the effect size (d’) with a 95% confidence interval were computed, in addition to significance testing.  For those less familiar with these concepts, there is an interactive tutorial on the terminology and mathematics of perceptual testing.

4. Experiment #1: Varying Steep Times with an Uncovered Kettle
4.1 Experiment #1: Experimental Overview
In this experiment, a late-hop addition was made at 1, 5, 10, or 20 minutes.  The kettle was uncovered during the final 20 minutes of the boil, allowing volatile hop oils to evaporate.

4.2 Experiment #1: Experimental Methods
All conditions used 2.55 lbs (1.16 kg) of Briess Pilsen Dried Malt Extract with 3.37 G (12.75 liters) of 120°F (49°C) water to create 3.50 G (13.25 liters) of room-temperature wort with specific gravity 1.031.  The wort sat for about 90 minutes to let the pH stabilize, at which point the pH was adjusted with phosphoric acid to 5.30.  The wort was boiled (uncovered) for 5 minutes to reduce the foam associated with the start of the boil.  A 12-oz (0.35 liter) sample was taken for measuring specific gravity and a 40-minute timer was started.  The first addition of Amarillo hops (AA rating 8.8%) was made with the weight listed in Table 1 (using a weighted coarse-mesh bag).  The kettle was covered for the first 20 minutes of the boil to reduce evaporation, after which time the cover was removed to allow evaporation.  At each target time, the second addition of 0.850 oz (24.1 g) of the same Amarillo hops (with the steep time listed in Table 1) was added in a weighted coarse-mesh bag.  At flameout the wort was quickly cooled with an immersion chiller to 75°F (24°C) and the hops were removed.  Sterilized, room-temperature water was added to bring the volume up to about 3.0 G (11.36 liters).  The wort was stirred and then sat for about 15 minutes, covered, to settle the heavier trub.  Then, 0.813 G (3.08 liters) of wort was transferred to a sanitized fermentation vessel.  This wort was aerated for 1 minute by vigorous shaking, and 0.08 oz (2.20 g) of Safale US-05 yeast was added.  A final sample was taken from the kettle for measuring specific gravity.

The wort fermented for one week, after which time 92 oz (2.72 liters) were decanted, leaving the trub behind.  From that, a 4-oz (0.12 liter) sample was taken for IBU measurement by Oregon BrewLab.  The remainder was stored at close to freezing with minimal exposure to oxygen until the results from Oregon BrewLab confirmed that the samples were all within 5 IBUs of each other.  Except when bringing samples up to room temperature for tasting, the beers were kept at near freezing and with minimal exposure to oxygen.

The perceptual experiment was conducted as described in Section 3.2.  Conducting up to four tests per day took 17 days.  Due to the difficulty in detecting clear differences between samples, tasting of each sample was spaced out by about 30 seconds and small sips of water or a tiny amount of dry bread was taken between tastings to reset the palate.

Condition: A B C D
weight of 1st addition:
0.379 oz /
10.75 g
0.289 oz /
8.20 g
0.185 oz /
5.25 g
0 oz /
0 g
steep time of 2nd addition:
1 min. 5 min. 10 min. 20 min.
pre-boil specific gravity (SG):
1.031 1.031 1.031 1.031
pre-boil volume:
(measured, room temp.)
3.51 G /
13.30 liters
3.49 G /
13.22 liters
3.50 G /
13.25 liters
3.50 G /
13.26 liters
SG at 1st addition:
1.033 1.033 1.034 1.033
volume at 1st addition:
(estimated from SG)
3.30 G /
12.50 liters
3.27 G /
12.38 liters
3.26 G /
12.34 liters
3.29 G /
12.46 liters
post-boil SG:
(after volume correction)
1.036 1.036 1.036 1.036
post-boil volume:
(estimated from SG)
3.03 G /
11.46 liters
2.99 G /
11.32 liters
3.02 G /
11.43 liters
3.02 G /
11.44 liters
measured IBUs 23.6 24.5 23.0 22.8

Table 1.  Measured and estimated (where indicated) values for the four conditions with an uncovered kettle.

4.3 Experiment #1: Results and Analysis
The IBU levels from the four conditions were well within the perceptual threshold of 5 IBUs.  The average was 23.5 IBUs, with a standard deviation 0.66 IBUs.  The maximum difference between two conditions was 1.7 IBUs.  These results indicate that the beers were not perceptually different in terms of bitterness.

The results of the perceptual test are shown in Table 2.  The top-right corner of the table provides the number of correct responses, the p value associated with this response rate (with the value in bold font if significance was reached), the likelihood ratio for a just-noticeable difference relative to no perceptual difference, and the low, maximum-likelihood, and high estimates of d’ (using a 95% confidence interval; a d’ of 0 corresponds with no perceptual difference, and a d’ of 1 corresponds with a just-noticeable difference).  The bottom-left corner of the table shows the identity of the preferred sample for each correct response.

The expected amount of variability in the results is quite large, given only 8 samples per trial (standard deviation 1.4 samples).  Two trends in the correct-response rate are visible, however: (1) Condition A is more likely to be distinguished from the other conditions, and (2) other comparisons indicate that no perceptual difference is approximately just as likely as a just-noticeable difference.

One unusual result is that the comparison of A vs. B demonstrates a significant difference, and A vs. D also demonstrates a significant difference, but A vs. C does not demonstrate significance.  Jumping ahead a little bit in the story in order to explain these results, the experiment described in Section 6 (to test the impact of evaporation on a 10-minute steep time) has results which indicate that the true underlying trend is probably that A and B actually have the least perceptual difference, A and C probably have a not significant and just-noticeable difference, and A and D have the largest perceptual difference.  In other words, evaporation and steep time probably affects perception, but the effect is more likely to be a gradual change over a period of about 10 or 20 minutes.

For the preferences, all of the correct responses involving Condition A were associated with a preference for Condition A.  For comparison B vs. C, the preference was equally split.  For B vs. D, the single correct response favored D.  For C vs. D, four out of the five favored Condition C.  Shorter steep times appear to be somewhat preferred over longer steep times, but the only universal preference was for the shortest steep time of 1 minute.

These results (and taking into account the results from Section 6) suggest that the shortest hop steep time has the most perceived hop flavor, and that evaporation probably affects hop flavor gradually over a 10- to 20-minute period.  Based on these results, one should keep hops in the wort for the shortest time possible in order to maximize flavor.

Comparison: A: B: C: D:
A:
6 / 8 correct
p = 0.020
LR: d’=1/d’=0 = 2.98
d’ (low, ML, high) =
0.68, 2.79, 4.68
2 / 8 correct
p = 0.805
LR: d’=1/d’=0 = 0.69
d’ (low, ML, high) =
0, 0, 2.10
7 / 8 correct
p = 0.003
LR: d’=1/d’=0 = 4.28
d’ (low, ML, high) =
2.10, 3.75, 4.68
B:
more flavor:
AAAAAA
4 / 8 correct
p = 0.259
LR: d’=1/d’=0 = 1.44
d’ (low, ML, high) =
0, 1.46, 3.75
1 / 8 correct
p = 0.961
LR: d’=1/d’=0 = 0.48
d’ (low, ML, high) =
0, 0, 0.68
C:
more flavor:
AA
more flavor:
BB CC
5 / 8 correct
p = 0.088
LR: d’=1/d’=0 = 2.07
d’ (low, ML, high) =
0, 2.10, 3.75
D: more flavor:
AAAAAAA
more flavor:
D
more flavor:
CCCC D

Table 1.  Results from perceptual testing with an uncovered kettle.  The top-right corner shows analysis of the number of correct responses.  The bottom-left corner shows, for those samples correctly identified as different, which sample was considered to have more hop flavor.

5. Experiment #2: Varying Steep Times with a Covered Kettle
5.1 Experiment #2: Experimental Overview
The experiment with an uncovered kettle showed that hop flavor is probably maximized with the shortest possible steep time.  There are two likely explanations for this: (1) the hop oils degrade when they’re in boiling wort, and/or (2) the hop oils are removed from the wort through evaporation.  If the first explanation is true, then one may be able to vary the temperature of the wort in order to minimize degradation and maximize flavor.  If the second explanation is true, then one only needs to cover the kettle in order to prevent the loss of hop oils.  The experiment described here tested the second explanation by covering the kettle during the boil.  If there is no perceptual difference between any of the conditions, that would suggest that the oils are lost primarily through evaporation.  If results are similar to the experiment with the uncovered kettle, that would suggest that oils are mostly degraded in boiling wort.

5.2 Experiment #2: Experimental Methods
This experiment was conducted using the same general methods as the first experiment.  The first addition of Amarillo hops was made with the weight listed in Table 3 (using a weighted coarse-mesh bag).  The kettle was covered during the entire 40-minute steep time, except for brief stirring and to add the second hop addition.  At each target time, the second addition of 0.765 oz (21.7 g) of Amarillo hops (with the steep time listed in Table 3) was added in a weighted coarse-mesh bag.

The perceptual experiment was conducted as described in Section 3.2.  Unfortunately, a bug in the randomization yielded between 7 and 12 samples per trial, instead of always 8 samples per trial.  Conducting up to four tests per day took 16 days.  Due to the difficulty in detecting clear differences between samples, tasting of each sample was spaced out by about 30 seconds and small sips of water or a tiny amount of dry bread was taken between tastings to reset the palate.

Condition: E F G H
weight of 1st addition:
0.363 oz /
10.30 g
0.274 oz /
7.77 g
0.181 oz /
5.14 g
0.096 oz /
2.71 g
steep time of 2nd addition:
1 min. 5 min. 10 min. 15 min.
pre-boil specific gravity (SG):
1.031 1.032 1.032 1.031
pre-boil volume:
(measured, room temp.)
3.48 G /
13.18 liters
3.48 G /
13.18 liters
3.48 G /
13.19 liters
3.50 G /
13.25 liters
SG at 1st addition:
1.033 1.033 1.033 1.034
volume at 1st addition:
(estimated from SG)
3.31 G /
12.54 liters
3.33 G /
12.62 liters
3.18 G /
12.04 liters
3.28 G /
12.42 liters
post-boil SG:
1.034 1.0345 1.036 1.035
post-boil volume:
(estimated from SG)
3.18 G /
12.03 liters
3.18 G /
12.04 liters
3.01 G /
11.41 liters
3.14 G /
11.88 liters
measured IBUs 20.2 21.4 21.2 18.7

Table 3.  Measured and estimated (where indicated) values for the four conditions with a covered kettle.

5.3 Experiment #2: Results and Analysis
The IBU levels from the four conditions were well within the perceptual threshold of 5 IBUs.  The average was 20.4 IBUs with standard deviation 1.07 IBUs.  The maximum difference between two conditions was 2.7 IBUs.  These results indicate that the beers were not perceptually different in terms of bitterness.

The results of the perceptual test are shown in Table 4.  The top-right corner of the table provides the number of correct responses, the p value associated with this response rate (none of the results reached significance), the likelihood ratio for a just-noticeable difference relative to no perceptual difference, and the low, maximum-likelihood, and high estimates of d’.  The bottom-left corner of the table shows the identity of the preferred sample for each correct response.

In this experiment, condition E (the shortest steep time) does not demonstrate any significant differences against the other conditions.  Overall, the likelihood ratios show no clear trend; for example, conditions with a greater difference in steep time are not more likely to have a just-noticeable difference than conditions with a small difference in steep time.  Unlike the first experiment, all of the 95% confidence intervals include a d’ of 0, or no perceptual difference.

For the preferences, there is also no clear preference for any one steep time.  The number of correct responses is quite small in most comparisons, and the only comparison with more than four correct responses was evenly split in preference between the two conditions.

While it’s not possible to demonstrate that two conditions are perceptually the same using standard significance testing, the set of results here suggests that all conditions in this experiment have at most a just-noticeable difference and quite likely no perceptual difference. In the previous experiment, Condition A had greater perceptual differences from other conditions and was universally preferred over other conditions; those patterns were not observed in this experiment.  These results suggest that hop oils lost through evaporation are an important component of hop flavor.

Comparison: E: F: G: H:
E:
3 / 8 correct
p = 0.532
LR: d’=1/d’=0 = 1.00
d’ (low, ML, high) =
0.0, 0.68, 2.79
2 / 7 correct
p = 0.737
LR: d’=1/d’=0 = 0.79
d’ (low, ML, high) =
0, 0, 2.58
3 / 8 correct
p = 0.532
LR: d’=1/d’=0 = 1.00
d’ (low, ML, high) =
0.0, 0.68, 2.79
F:
more flavor:
EE F
1 / 9 correct
p = 0.974
LR: d’=1/d’=0 = 0.42
d’ (low, ML, high) =
0, 0, 0
4 / 8 correct
p = 0.259
LR: d’=1/d’=0 = 1.44
d’ (low, ML, high) =
0, 1.46, 3.75
G:
more flavor:
GG
more flavor:
G
7 / 12 correct
p = 0.066
LR: d’=1/d’=0 = 2.48
d’ (low, ML, high) =
0, 1.89, 3.38
H: more flavor:
E HH
more flavor:
BB DD
more flavor:
GGG HHHH

Table 4.  Results from perceptual testing with a covered kettle.  The top-right corner shows analysis of the number of correct responses.  The bottom-left corner shows, for those samples correctly identified as different, which sample was considered to have more hop flavor.

6. Experiment #3: Covered vs. Uncovered Kettle with 10-Minute Addition
6.1 Experiment #3: Experimental Overview
The first experiment demonstrated an unexpected result: a significant difference between 1 and 5 minutes (A vs. B comparison with 6 correct responses out of 8 tests), no significant difference between 1 and 10 minutes (A vs. C with 2 out of 8 correct), and a significant difference between 1 and 20 minutes (A vs. D with 7 out of 8 correct).  It is mathematically more likely that the lack of perceptual difference in the A vs. C comparison is an incorrect conclusion, which implies that hop oils quickly evaporate with steam.  However, the number of data points in this experiment was small and therefore the uncertainty is large.  A third experiment was conducted to test this hypothesis with more data.  This experiment had two conditions, J and K, both with a 10-minute late-hop addition.  The primary difference between the two conditions was that in Condition J the kettle was covered during the final 10 minutes and in Condition K the kettle was uncovered (allowing steam to escape).  If the tentative conclusion from the first experiment is correct and hop oils are quickly lost with evaporating steam, then there should be a perceptual and significant difference between Conditions J and K.  (With an estimated d’ of 2.79 in the A vs. B comparison and 3.75 in the A vs. D comparison, an estimate of d’ for a 10-minute steep time is about 3.  With 24 tests and a d’ of 3.0, the power of the test is close to 1.0.)

6.2 Experiment #3: Experimental Methods
This experiment was conducted using the same general methods as the first and second experiments.  Wort for each condition was created using 2.47 lbs (1.12 kg) of DME and 3.27 G (12.38 liters) of water, yielding 3.43 G (13.0 liters) of wort with specific gravity 1.031.  The first addition of 0.176 oz (5.0 g) of Amarillo hops (AA rating 8.8%) was made at 45 minutes before flameout (in a weighted coarse-mesh bag).  Both conditions had 0.811 oz (23.0 g) of Amarillo hops added in a weighted coarse-mesh bag at 10 minutes before flameout.  Safale S-04 yeast was used for fermentation.

For Condition J, the kettle was uncovered for the first 10 minutes after the initial hop addition, and then covered for the remaining 35 minutes of the boil (with the brief exception of adding the 10-minute hop addition).  For Condition K, the kettle was uncovered during the first 10 minutes, covered during the next 25 minutes, and uncovered during the final 10 minutes (after the second hop addition was made).

The perceptual experiment was conducted as described in Section 3.2.  Conducting 24 tests with up to four tests per day, along with the 24 tests in the fourth experiment, took 17 days.  With the expectation of less difficulty in detecting a clear difference between samples and a desire to balance memory effects with adaptation effects, tasting of each sample was spaced out by about 10 seconds and only small sips of water were taken between tastings to reset the palate.

6.3 Experiment #3: Results and Analysis
The measured IBUs were 24.7 for Condition J and 28.9 for Condition K.  The difference between these IBU levels, 4.2, is within the perceptual threshold of 5 IBUs.  These results indicate that the beers were not perceptually different in terms of bitterness.

The results of the perceptual test were that 11 out of the 24 tests were correctly identified, and of those correct responses, 3 times Condition J was preferred and 8 times Condition K was preferred.  The p value associated with this response rate is 0.14 (not significant at a threshold of 0.05), and the likelihood ratio for a just-noticeable difference relative to no perceptual difference is 2.07. The low, maximum-likelihood, and high estimates of d’ are 0.0, 1.24, and 2.32, respectively.

These results were very much unexpected, in the low estimate of d’, the lack of significance, and the general preference for the uncovered late-hop addition over the covered late-hop addition.  These results imply that in the first experiment the A vs. B comparison (1 min. vs. 5 min.) yielded an incorrect result that supported a perceptual difference, and that the A vs. C comparison (1 min. vs. 10 min.) was actually correct in not demonstrating significance.  Given the strength of the A vs. D comparison (1 min. vs. 20 min., with 7 out of 8 correct and consistent responses), it seems prudent to continue to assume that the result of that comparison was correct.

The preference for Condition K over Condition J might be due to (a) difficulty in distinguishing these two conditions (with a fairly low d’) (b) small differences in the perceptual testing methodology that may have had an unexpectedly large effect , (c) the use of a different strain of yeast, and/or (d) flavor changes over time due to the transformation of hop oils in the hot wort in addition to the loss of oils through evaporation.  The simple explanation that hop oils are simply lost through evaporation may or may not be the complete explanation.

Considering the set of results of the first three experiments, it appears that hop flavor does decrease with longer steep times, but only relatively slowly.  We can estimate the perceptual change over time (with an uncovered kettle) as a d’ of roughly 1.0 after 10 minutes (a just-noticeable difference) and a d’ of roughly 3.0 (with a maximum-likelihood estimate of 3.75) at 20 minutes.  With the preference for the shortest steep time in the first experiment not consistent with the preference for the uncovered kettle in the third experiment, it is unclear if flavor changes occur only through evaporation, through additional mechanisms, or if testing differences or statistical variation in the third experiment caused a different result.  The universal preference for the shortest steep time in the first experiment leads to the tentative conclusion that flavor is maximized with the shortest steep time.

7. Experiment #4: Boiling vs. Sub-Boiling Hop Addition
7.1 Experiment #4: Experimental Overview
A comparison of the results from the first and second experiments indicates that covering or not covering the kettle can be responsible for a noticeable change (or lack of change) in hop flavor.  The results of the third experiment suggest that the effect of covering the kettle is only a just-noticeable difference at a 10-minute steep time.  Other than volatile hop oils evaporating with steam, another likely explanation for a change in hop flavor is a transformation of hop oils in contact with boiling wort.  The fourth experiment tested the effect of wort temperature on hop flavor, comparing a 10-minute steep time at boiling (Condition L) with a 10-minute steep time at 170°F (77°C)  (Condition M).

7.2 Experiment #4: Experimental Methods
This experiment was conducted using the same general methods as the previous three experiments.  Dried malt extract was used to create 3.43 G (13.0 liters) of wort with pre-boil specific gravity 1.031.  The first addition of Amarillo hops (AA rating 8.8%) was made at 45 minutes before flameout (in a weighted coarse-mesh bag).  Condition L used 0.176 oz (5.0 g) of hops in the first addition and was identical with Condition J in Experiment #3.  Condition M used 0.388 oz (11.0 g) of  hops in the first addition.   Both conditions had 0.811 oz (23.0 g) of Amarillo hops added in a weighted coarse-mesh bag at 10 minutes before flameout, and the kettle was covered during the final 10 minutes.  In Condition L the wort was kept at boiling; in Condition M, the wort was cooled from boiling to 170°F (77°C) during the 11th minute before flameout using an immersion chiller, and the target temperature was maintained (to within a few degrees) during the final 10 minutes before flameout.  Safale S-04 yeast was used for fermentation.

The perceptual experiment was conducted as described in Section 3.2.  Conducting 24 tests with up to four tests per day, along with the 24 tests in the third experiment, took 17 days.  As in the third experiment, tasting of each sample was spaced out by about 10 seconds and only small sips of water were taken between tastings to reset the palate.

7.3 Experiment #4: Results and Analysis
The measured IBUs were 25.1 for Condition L and 29.6 for Condition M.  The difference between these IBU levels, 4.5, is within the perceptual threshold of 5 IBUs.  These results indicate that the beers were not perceptually different in terms of bitterness.

The results of the perceptual test were that 5 out of the 24 tests were correctly identified, and of those correct responses, 3 times Condition L was preferred and 2 times Condition M was preferred.  The p value associated with this response rate is 0.94 (not significant at a threshold of 0.05), and the likelihood ratio for no perceptual difference relative to a just-noticeable difference is 4.29. The low, maximum-likelihood, and high estimates of d’ are 0.0, 0.0, and 0.8, respectively.

While it is not possible to conclude that two conditions are perceptually identical using significance testing with a null hypothesis of no difference, it would be difficult to get results that more clearly indicate no perceptual difference between the two conditions.  Even random guessing would result in, on average, 8 of the 24 tests being correctly identified.  The result of 5 correct responses is not so low that one should be concerned about experimental error, but low enough that the likelihood of there being no perceptual difference is more than four times greater than there being a just-noticeable difference.  The maximum-likelihood estimate of d’ is 0, indicating no perceptual difference.  In short, there is no evidence that there is a perceptual difference between hops boiled for 10 minutes and hops kept at 170°F (77°C)  for 10 minutes.  I will abuse the mathematics a bit and conclude that a sub-boiling hop stand produces no noticeable difference in hop flavor, at least for a 10-minute steep time and these experimental conditions.

8. Conclusions
8.1 Summary of Results
The results from these experiments indicate that hop flavor is lost primarily through evaporating steam while the hops are steeped in hot wort.  After about 10 minutes of steeping there may be a just-noticeable difference in hop flavor; after about 20 minutes the difference may be more easily perceived.  Flavor appears to be lost through the evaporation of hop oils, but it is also possible that other factors also affect the flavor compounds over time.

The best-practice recommendation resulting from these experiments is to keep hops in boiling wort for as short a time as possible in order to preserve hop flavor, but a difference of 10 minutes or a decrease in wort temperature may not have a perceptible impact, especially with a covered kettle.  This recommendation might be paraphrased as: minimize the time that the hops are in hot wort, but (in the words of Charlie Papazian) relax, don’t worry, and maybe have a homebrew.

One potential concern with a covered kettle is the production of dimethyl sulfide (DMS) which can then not be removed by evaporation.  Most ales, however, “have DMS levels well below threshold” [Fix and Fix, p. 50].  Because the precursor S-methylmethionine (SMM) and DMS are reduced more at ale fermentation temperatures than at lager fermentation temperatures, “any hint of DMS in ales is likely from technical brewing errors, most notably contamination” [Fix, p. 75].  In lagers, the increase in DMS caused by a covered kettle can be counteracted with a longer (uncovered) boil time and/or faster wort cooling [Fix and Fix, pp. 50-51].  (The other option is to not worry about DMS and brew lager in the style of Rolling Rock [Bamforth, p. 18].)

8.2 Comments on Perceptual Testing
In general it was very difficult to tell the beers in these conditions apart, despite the nearly ideal testing conditions.  This difficulty was compounded (or caused) by the first taste of a beer being the most perceptually distinctive and subsequent tastes of other samples having less sensory impact.   There was therefore a balance between waiting long enough to reset the palate but not waiting so long that the specifics of the flavor were forgotten.  Taking small sips of water or eating a tiny amount of dry bread to reset the palate in between tastings seemed to help, but in most cases the differences between conditions were very subtle (or nonexistent).

My general preference for the flavor obtained from a 1-minute steep time with Amarillo hops may or may not be shared by others.  As a counterexample, my wife thinks that every IPA she has ever encountered tastes and smells disgusting.  Another hop variety might yield different results.  In short, your perceptions and preferences may be different from the results of these experiments.

9. Acknowledgment
I would like to sincerely thank Dana Garves at Oregon BrewLab for the IBU measurements in these experiments.  Oregon BrewLab has been a pleasure to work with, and I can always rely on the accuracy of the measured values.

References

  • J. Angevaare,  A New Triangle Test Calculatorhttps://onbrewing.com/a-new-triangle-test-calculator/.  Accessed Apr. 21, 2021
  • C. Bamforth.  Beer is Proof God Loves Us.  FT Press, 1st edition, 2011.
  • R. Daniels, Designing Great Beers: The Ultimate Guide to Brewing Classic Beer Styles. Brewers Publications, 2000.
  • G. Fix, Principles of Brewing Science. Brewers Publications, 2nd edition, 1999.
  • G. J. Fix and L. A. Fix, An Analysis of Brewing Techniques. Brewers Publications, 1997.
  • M. Garetz, Using Hops: The Complete Guide to Hops for the Craft Brewer. HopTech, 1st edition, 1994.
  • C. D. Hahn, A Comprehensive Evaluation of the Nonvolatile Chemistry Affecting the Sensory BItterness Intensity of Highly Hopped Beers.  Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2017.
  • M. G. Malowicki, Hop Bitter Acid Isomerization and Degradation Kinetics in a Model Wort-Boiling System, Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2005.
  • G. J. Noonan, New Brewing Lager Beer. Brewers Publications, 1996.
  • G. Oliver, The Oxford Companion to Beer, Oxford University Press, 2011.
  • C. Papazian, The Home Brewer’s Companion.  William Morrow / HarperCollins,  1st edition, 1994/2002.
  • Society of Sensory Professionals, Triangle Testhttps://www.sensorysociety.org/knowledge/sspwiki/Pages/Triangle%20Test.aspx. Accessed Apr. 21, 2021.
  • Wikipedia.  Hopshttps://en.wikipedia.org/wiki/Hops.  Accessed Apr. 21, 2021.

Why Do Hop Pellets Produce More IBUs Than Hop Cones?

Abstract
Hop pellets are usually described as having higher utilization than hop cones.  A separate blog post looks at the amount of increase in IBUs caused by using pellets instead of cones. It finds that the amount of increase is constant over a range of hop steep times, instead of increasing with steep time.  This means that the increase in IBUs is not caused by an increase in the rate of alpha-acid isomerization or availability of alpha acids, which would result in longer steep times having a greater increase in IBUs. The first experiment in this post looks at whether this constant increase is more likely to be caused by a greater concentration of isomerized alpha acids (IAA) produced soon after a hop addition, or by other bittering compounds (nonIAA, also called “auxiliary bittering compounds”).  This experiment analyzes the rate at which IAA and nonIAA are removed from beer over time, and a comparison is made with the rate at which the increase in IBUs from pellets decreases over time.  The results indicate that pellets yield increased IBUs from an increase in auxiliary bittering compounds, not from increased IAA.  In other words, the concentration of isomerized alpha acids in finished beer is the same for beer made with cones or pellets, but the concentration of nonIAA is greater in beer made from pellets.  Data from a second experiment indicate that while the concentration of polyphenols is greater with the use of pellets, this greater polyphenol concentration cannot explain the observed increase in IBUs.  In this experiment, the increase in IBUs from pellets does not increase linearly with the amount of hops added, which is consistent with the IBU increase being caused by oxidized alpha acids.  (The same alpha-acid solubility limit that explains relatively lower IAA at higher alpha-acid concentrations can explain the relatively lower production of oxidized alpha acids at higher concentrations.)  The most likely explanation for the increase in IBUs when using pellets is that the pelletization process gives the alpha acids greater surface area, and that these exposed alpha acids oxidize quickly when brought into contact with hot wort, creating an increase in the concentration of oxidized alpha acids during the boil.

1. Background: Utilization, Reported Differences, and IBU Models
1.1 Utilization
Hop utilization, U, is the amount of isomerized alpha acids (IAA) in finished beer divided by the amount of alpha acids added to the kettle, and then multiplied by 100 to convert to percent [e.g. Lewis and Young, p. 266]:

U = 100 × (isomerized alpha acids in beer) / (alpha acids added to kettle) [1]

Utilization refers only to the relative amount of isomerized alpha acids, not to IBUs.  While IAA and IBUs can be considered roughly equivalent as a quick rule of thumb, IBUs measure a number of bitter components in addition to IAA.  These other bitter components are called nonIAA or “auxiliary bittering compounds”.  With short boil times, high hopping rates, low steeping temperatures, improperly-stored hops, and other factors, one can see significant differences between measured IBUs and the concentration of IAA.

1.2 Reported Differences Between Cones and Pellets
Hop pellets are almost always described as having greater utilization than hop cones [e.g. Daniels p. 78].  According to Michael Lewis and Tom Young, “the alpha acids dissolve most easily from extracts, less easily from pellets …, and least with whole hops” [Lewis and Young, p. 266].  It is said that the higher rate at which alpha acids from pellets “dissolve,” compared with whole cones, is because “the pelletization process ruptures the lupulin glands and spreads the resins over the hop particles, giving a larger surface area for isomerization” [Hall, p. 58].  Greg Noonan says that “with pelletized hops, ruptured and better-exposed lupulin glands give greater utilization” [Noonan, p. 154].

1.3 Modeling IBUs from Pellets with Scaling Factors
A previous blog post describes a model of IBUs based on equations from Val Peacock [Peacock, p. 157] and Mark Malowicki [Malowicik, p. 27].   This model can be used to estimate the scaling factors for isomerized alpha acids (IAA) and auxiliary bittering compounds (nonIAA) in beer made from either cones or pellets.  Another blog post used those scaling factors to show that the increase in IBUs is modeled well by an increase in the concentration of nonIAA, or by some process that adds IBUs at the beginning of the boil but not during the rest of the boil.

2. Introduction
Although the other blog post on pellet-based IBUs found that the increase in IBUs resulting from the use of pellets was modeled well by an increase in nonIAA concentrations, it is still possible that this increase is actually caused by the rapid production of isomerized alpha acids close to the start of a hop addition, instead of the usual time-dependent alpha-acid isomerization.  The model referred to in Section 1.3 groups all compounds that are produced near the beginning of a hop addition as nonIAA compounds, under the assumptions that isomerization is a fairly slow process and that nonIAA compounds are produced quickly.  If IAA are also somehow produced quickly after adding hops, this model would not be able to distinguish these IAA from nonIAA.

Perhaps the process of manufacturing pellets (which includes heat [Srečec, pp. 141-143], a primary factor in isomerization [Verzele and De Keukeleire, pp. 102-109]) transforms alpha acids into an intermediate compound which then quickly results in IAA when the pellets are added to boiling wort.  Such a process would mean that pellets show increased IBUs because of greater utilization, even if this increase in utilization happens much more quickly than the typical isomerization process.  (The existence of such an intermediate compound is postulated simply to explain how the increase in IBUs seen with the use of pellets might be caused by isomerized alpha acids, since the rate of isomerization or availability of alpha acids is not affected when using pellets.)

The rest of this blog post addresses the question of whether the increase in IBUs observed with the use of pellets is more likely to be the result of (a) IAA that are produced soon after a hop addition (i.e. greater utilization), (b) oxidized alpha acids produced when the hops are added to the boiling wort [Algazzali, p. 17; Dierckens and Verzele, p. 454], or (c) hop polyphenols.  (It is highly unlikely that this increase is related to oxidized beta acids because of the negligible impact that oxidized beta acids have on the IBU when using well-preserved hops.)

3. Experiment #1: Experimental Overview and Methods
3.1 Overview of Experiment #1
The IBU level and the concentration of IAA in beer decrease over time, especially at room temperature [Peacock, p. 164].  This decrease may be caused by IAA and possibly nonIAA transforming over time into different products or binding with other compounds and precipitating out of solution.  In either way, IAA and possibly nonIAA compounds are removed from beer over time.  The current analysis assumes that the rate at which IAA and nonIAA compounds are removed from beer is different.  By transforming multiple IBU measurements taken from a single beer at multiple points throughout the boil (both fresh beer and aged beer) into estimates of IAA and nonIAA factors in a model of IBUs, we can evaluate how these factors (and therefore IAA and nonIAA concentrations) change with the age of the beer.  If the increase in IBUs produced by the use of pellets decreases over time at the same rate as IAA loss, we can conclude that this increase in IBUs is probably produced by IAA.  Conversely, if the decrease matches the rate of nonIAA loss, we can conclude that nonIAA compounds are most likely responsible for the increase in IBUs with pellets.  (If the different-rate-of-decay assumption is wrong, then the decrease in IAA will be the same as the decrease in nonIAA, and no conclusions will be possible.)

A picture may help to illustrate the overall concept.  Figure 1 shows hypothetical cases of (a) IBUs produced using hop cones (solid dark blue line), (b) IBUs produced using hop pellets (solid dark green line), (c) the same cone-produced beer after 10 weeks of aging (dotted light-blue line), and (d) the same pellet-produced beer after 10 weeks (dotted light-green line).  This set of hypothetical data is based on two assumptions: (1) the change in IBUs over 10 weeks is due entirely to the loss of IAA; nonIAA compounds do not decrease in beer over time, and (2) the increase in IBUs caused by the use of pellets comes entirely from nonIAA compounds.  These assumptions produce a particular pattern in the IBU levels in Figure 1: (a) the solid green line and solid blue line are different by a constant factor (due to nonIAA compounds), (b) the dotted blue line starts at the same value as the solid blue line at 0 minutes, and then gradually decreases relative to the solid blue line (because only IAA levels decrease with age), and (c) the dotted green line and dotted blue line are different by the same constant factor (because the increase in IBUs with pellets comes only from nonIAA, which does not decrease over time).  Neither of these assumptions may be true, but we can analyze real IBU data using the model mentioned in Section 1.3 to estimate scaling factors.  The scaling factors, which could be used to produce graphs like Figure 1, will tell us how much loss occurs in both IAA and nonIAA over 10 weeks. We can then compare the change in pellet-related IBUs over the 10 weeks to the IAA and nonIAA scaling factors.  Comparing the rates at which losses occur will help us determine if the increase in IBUs from the use of pellets is more likely caused by IAA or nonIAA.

degradation

Figure 1. Hypothetical IBU levels from fresh and aged beer made with cones and pellets.  The data in this figure are made up in order to illustrate the patterns one might see as IBUs change over time in both types of beer.

I previously brewed two batches of beer that were nearly identical in all respects except for the use of cones in one case and pellets in the other, as part of a previous blog post (Hop Cones vs. Pellets: IBU Differences, Experiment #5).  For each batch, I took samples of wort at 10-minute intervals during a 60-minute boil.  Each sample was fermented into beer and 4 oz of each was sent to Oregon BrewLab for IBU analysis about 10 days after the start of fermentation.  I kept whatever wasn’t sent to Oregon BrewLab at room temperature for aging.  Those additional 12 samples were sent to Oregon BrewLab for IBU analysis at 10 weeks after the start of fermentation.

3.2 Methods for Experiment #1
All data for this experiment consisted of two batches of beer brewed on the same day, one batch using hop cones and the other using hop pellets.  I used 7.0 lbs (3.18 kg) of Briess Pilsen DME in 8.0 G (30.28 l) of water, yielding about 8.5 G (32 l) of wort with a specific gravity of about 1.037.  I did not adjust the water profile or pH, which resulted in a pre-boil wort pH of 5.80.

In this experiment, I used Comet cones from Hops Direct (stored in my freezer soon after harvest for about 4 months) and Comet pellets from YCH Hops (lot P92-ZLUCOM5216, about 2½ years old at the time of the experiment).   The previous blog post concluded that the age of the hop pellets did not have any impact on the pellet-based increase in IBUs.

I added hops (i.e. started the steep time at 0) after the wort had been boiling for 5 minutes, to avoid the foam associated with the start of the boil.  The hops were boiled for a total of 60 minutes with the cover on the kettle (except for taking samples) to minimize evaporation and the resulting changes in specific gravity.  I used 1.939 oz (54.96 g) of hop cones (alpha-acid rating 9.70%) and 2.147 oz (60.86 g) of hop pellets (alpha-acid rating 8.76%) to target an initial alpha-acid concentration of 170 ppm in both batches.

Samples were taken every 10 minutes from the start of steeping.  Each sample was taken from the boil in a measuring cup and then transferred to an aluminum cup using a wire mesh sieve to remove larger hop particles.  For the cones condition, 32-oz (0.95-liter) samples were taken; for the pellets condition, 16-oz (0.44-liter) samples were taken.  The aluminum cup was placed in an ice bath and the contents were stirred to cool quickly.  Once cooled to 75°F (24°C), the sample was transferred to a sanitized, sealed, and labeled quart (liter) container.  I aerated each sample by vigorous shaking for 60 seconds, then added .008 or 0.017 oz (0.24 or 0.48 g) of Safale US-05 yeast (depending on the volume of the sample) to target 750,000 viable cells per ml and degree Plato [Fix and Fix, p. 68].  After all samples were taken, the containers were cracked open to vent, and they fermented for eight days.  I swirled the samples every day to remove most of the krausen deposits on the sides of the containers.  After fermentation, I sent 4 oz (0.12 l) of each sample to Oregon BrewLab for IBU measurement.  The remainder of each sample then proceeded to age for 10 weeks at room temperature.  After 10 weeks, another 4 oz (0.12 l) was sent to Oregon BrewLab for IBU measurement.

4. Experiment #1: Results
The estimated room-temperature volume at the start of steeping was 8.34 G (31.57 liters).  The specific gravity after 10 minutes of steeping was about 1.0384.  The specific gravity after a 60-minute steep time was 1.0396.  The small change in specific gravity during the boil (due to keeping the lid on the kettle) means that there is little difference between using the measured IBU values for analysis or normalizing these IBUs by the volume when the sample was taken.  For simplicity and clarity, the measured IBU values are used below.

Figure 2 shows the measured IBU values from this experiment.  The average  difference in IBUs between cones and pellets is shown for both the fresh and aged beer.

AGE2-measuredIBUs-weeks1and10

Figure 2. Measured IBU data from beer made with cones or pellets, at 1 and 10 weeks after the start of fermentation.  The average IBU difference between cones and pellets at week 1 is 11 IBUs, and the average difference at week 10 is 8.5 IBUs.

5. Experiment #1: Analysis
5.1 Average Differences and Visual Analysis
The increase in IBUs caused by the use of pellets decreases from an average of 11.02 IBUs at week 1 to 8.50 IBUs at week 10.  This implies that whatever is causing this increase in IBUs, it does decay as the beer ages.  This pellet-based increase in IBUs decayed by a factor of 0.77 over the 10-week period (0.77 = 8.50/11.02).

It appears that the slope of the line changes between weeks 1 and 10 for both cones and pellets, with less of a difference at 10 minutes and more of a difference at 60 minutes, but the effect is subtle.  This change in slope is caused by the loss of IAA; a 10% loss of IAA will have less of an absolute effect on 20 IBUs than it will on 40 IBUs.  Because the data do not extend back to a steep time of 0, it is difficult to see if the vertical-axis offset of the lines changes with the age of the beer, which would correspond with a decrease in nonIAA concentrations.

In short, whatever is causing the increase in IBUs does decrease with age, and both IAA and nonIAA might decrease with age.  To get a more conclusive answer, we need to distill the data in this graph into a smaller set of numbers for easier comparison.

5.2 Model and Scaling Factors
We can use the technique described in Estimating Isomerized Alpha Acids and nonIAA from Multiple IBU Measurements to split the IBU value into estimates of (a) the concentration of IAA and (b) the concentration of other bitter substances measured with the IBU that are called nonIAA.  Since nonIAA are predominately oxidized alpha acids (oAA), we can use existing models of the other factors (polyphenols and oxidized beta acids) and focus on estimating the concentration of oAA.  (The assumption of oAA as the primary source of nonIAA differences between cones and pellets is examined in Experiment #2.  Even if this assumption is incorrect, the model uses a direct translation between the concentration of oAA and total nonIAA, and so the results of this experiment will still be valid for nonIAA although off by a constant scaling factor.)

We can use multiple IBU values from the same batch of beer, along with an equation that describes the isomerization of alpha acids as a function of time and temperature [Malowicki, p. 27], an equation that describes the IBU as a combination of IAA and nonIAA in the finished beer [Peacock, p. 161], and models of polyphenols and oxidized beta acids, to estimate two scaling factors: scalingIAA and scalingoAA.  The scalingIAA parameter is the scaling factor that accounts for losses of IAA during the boil, fermentation, and aging; scalingoAA is the scaling factor from the initial concentration of alpha acids in the wort to the concentration of oxidized alpha acids in the beer.  With scalingIAA and scalingoAA, as well as the volume of wort, weight of the hops, initial alpha-acid concentration, steep time, original gravity, and models of polyphenols and oxidized beta acids, we can map from IBU value to IAA and oAA concentrations, and vice versa.  The IBU values resulting from this analysis are listed in Table 1.

10
20
30
40
50
60
cones, week 1
(meas., estimate)
16.4,
15.7
21.2,
21.8
26.6,
27.0
31.3,
31.4
35.2,
35.3
39.0,
38.5
cones, week 10
(meas., estimate)
13.5,
12.8
17.5,
18.1
22.1,
22.6
26.6,
26.6
30.0,
30.0
33.2,
32.8
pellets, week 1
(meas., estimate)
26.0,
26.4
33.6,
32.6
37.8,
37.9
41.6,
42.5
46.9,
46.5
49.9,
49.8
pellets, week 10
(meas., estimate)
20.7,
21.4
27.9,
26.6
31.2,
31.2
33.6,
35.1
40.0,
38.4
40.5,
41.3

Table 1. Measured and estimated IBUs for each sample in each condition. Samples are identified by the duration of hop boiling, in minutes (column headings). The type of hops (cones or pellets) and the age of the beer are identified by row headings. Each cell in the table shows measured IBUs followed by estimated IBUs. Estimates are from the model described in Section 5.2.

5.3 Analysis of Cones Data
The analysis of IBU data of the beer made with hop cones and aged one week resulted in scalingIAA = 0.472 and scalingoAA = 0.067.  These results indicate that somewhat less than half of the isomerized alpha acids from this batch made it into the finished beer, and about 7% of the alpha acids added to the wort ended up as oxidized alpha acids in the beer.  The analysis of beer made with hop cones and aged 10 weeks resulted in scalingIAA = 0.414 and scalingoAA = 0.049.

From these results, we can estimate that IAA levels decayed by a factor of 0.877 over the 10 weeks (0.877 = 0.414/0.472), and nonIAA levels decayed by a factor of 0.731 (0.049/0.067).  The decrease over time attributed to pellet-specific factors (0.77 from Section 5.1) is closer to 0.73 than it is to 0.88, and so this suggests that the pellet-based increase in IBUs is more likely to be caused by oxidized alpha acids.

5.4 Analysis of Pellet Data
We can perform a similar analysis on the set of pellet data.  However, we don’t want to include the effect of the increase in IBUs caused by pellets in our analysis results, so when we estimate values for scalingIAA and scalingoAA, we add 11.02 IBUs to the model of week-1 data and 8.50 IBUs to the model of week-10 data.  (Or, equivalently, we can subtract 11.02 from the measured values from week 1 and 8.50 from the measured values at week 10.)  When this is done, the beer made with hop pellets and aged one week results in scalingIAA = 0.484 and scalingoAA = 0.059.  The beer made with hop pellets and aged 10 weeks results in scalingIAA = 0.411 and scalingoAA = 0.047.

From these results of pellet-based IBUs, we can estimate that IAA levels decayed by a factor of 0.849 over the 10 weeks (0.849 = 0.411/0.484) and nonIAA levels decayed by a factor of 0.797 (0.047/0.059).  While this difference between IAA and nonIAA degradation is smaller than that estimated for cones, the decrease over time attributed to pellets (0.77) is even slightly less than the estimated nonIAA decay factor for pellets (.797).  This indicates again that the pellet-based increase in IBUs is more likely to be caused by nonIAA compounds than by IAA.

The IAA scaling factor (scalingIAA), oxidized alpha acid scaling factor (scalingoAA), and root-mean-square (RMS) error resulting from this analysis are listed in Table 2.

IAA scaling factor
oAA scaling factor
RMS error
cones, week 1
0.472 0.067 0.429
cones, week 10
0.414 0.049 0.461
pellets, week 1
0.484 0.059 0.613
pellets, week 10
0.411 0.047 1.106

Table 2. Estimated IAA and oAA scaling factors, and the associated RMS error, for each condition.

5.5 Averaged Analysis
The results in this study rely on parameter estimation that is subject to errors in the model, in the “known” values used in this model (i.e. the concentration of alpha acids at the start of steeping), and in the measured IBU values.  The pellet-based decay factor (0.77) is somewhat higher than the estimated nonIAA factor for cones (0.73), and the pellet-based decay factor is somewhat lower than the estimated nonIAA factor for pellets (0.80).

Assuming that these differences in results for cones and pellets are due to errors in the “known” or measured values, we can average the IAA and nonIAA decay factors (or the scaling factors) to arrive at a more robust combined estimate.  This averaging yields an IAA decay factor of 0.86 and a nonIAA decay factor of 0.76.  From these averaged values, we can conclude that the increase in IBUs caused by pellets (with a decay factor of 0.77) is most likely due entirely to nonIAA.

6. Experiment #2: Experimental Overview and Methods
6.1 Overview of Experiment #2
Having concluded in Experiment #1 that the increase in IBUs is more likely to come from nonIAA than from IAA, Experiment #2 looked at which of the components that are collectively referred to as nonIAA might be responsible for the increase. While Experiment #1 modeled the nonIAA increase assuming oxidized alpha acids are the unknown scaling factor, it is possible that this assumption is not correct, and that (for example) oxidized alpha acids are constant while the concentration of polyphenols is actually responsible for the increase in IBUs.

Malt polyphenols can obviously not be responsible for a change in IBUs caused by the type of hops used, and oxidized beta acids have a negligible impact on IBUs when using well-preserved hops.  This leaves oxidized alpha acids and hop polyphenols as the possible contributors.  It is possible that, even though hop polyphenols normally contribute only a small amount to the IBU [e.g. Shellhammer, p. 177; Almaguer, p. 300], the pelletization process produces such an increase in soluble hop polyphenols that this increase can explain the IBU differences between cones and pellets.

In order to test this theory, Oregon BrewLab measured the polyphenol concentrations in beer made with varying concentrations of hop cones and varying concentrations of hop pellets.  While isomerized alpha acids do not increase linearly with an increase in alpha acids, polyphenols should not have a solubility limit at even fairly high hopping rates.  We can then plot the change in polyphenol levels as a function of concentration to determine (a) the concentration of malt polyphenols, (b) the rate of increase of hop polyphenols when using cones, (c) the rate of increase of hop polyphenols when using pellets, and (d) whether any differences in the polyphenol concentrations between cones and pellets might explain the observed increase in IBUs from pellets.

6.2 Methods for Experiment #2
The data for this experiment consisted of five batches of beer brewed on the same day, two batches using hop cones and the other three batches using hop pellets.  Batch A used 0.76 oz (21.68 g) of cone hops with AA rating 8.32%.  Batch B used 2.04 oz (57.81 g) of the same cone hops.  Batch C used 0.67 oz (18.89 g) of pellet hops with AA rating 9.55%.  Batch D used 1.78 oz (50.37 g) of the same pellet hops.  Finally, Batch E used 2.66 oz (75.55 g) of the same pellet hops.  These weights, when used with the expected volume of wort when hops were added and with the estimated alpha-acid ratings, were designed to result in initial alpha-acid concentrations of 150 ppm, 400 ppm, 150 ppm, 400 ppm, and 600 ppm for Batches A through E, respectively.  Therefore Batches A and C can be directly compared, and Batches B and D can be directly compared.

For each batch, I used 2.88 lbs (1.31 kg) of Briess Pilsen DME in 3.32 G (12.57 l) of water, yielding about 3.47 G (13.14 l) of wort with a specific gravity of about 1.036.  I did not adjust the water profile or pH, which resulted in a pre-boil wort pH of 5.77.

The hops used in this experiment were from the same source as in Experiment #1.  This experiment was conducted nine months after the first; during that time, the hops were stored at about −9°F (−23°C) in vacuum-sealed bags.  I added hops (i.e. started the steep time at 0) after the wort had been boiling for 5 minutes, to avoid the foam associated with the start of the boil.  Samples were taken every 10 minutes from the start of the hop addition, for a total steep time of 40 minutes (4 samples).  Each 15-oz (0.44-liter) sample was taken from the boil in a measuring cup and then transferred to an aluminum cup using a wire mesh sieve to remove larger hop particles.  The aluminum cup was placed in an ice bath and the contents were stirred to cool quickly.  Once cooled to 75°F (24°C), the sample was transferred to a sanitized, sealed, and labeled quart (liter) container.  I aerated each sample by vigorous shaking for 60 seconds, then added .009 oz (0.25 g) of Safale US-05 yeast.  After all samples were taken, the containers were cracked open to vent, and they fermented for nine days. After fermentation, I sent 4 oz (0.12 l) of each sample to Oregon BrewLab for IBU measurement.  The sample taken at 10 minutes of steep time was also analyzed by Oregon BrewLab for polyphenol concentration.

7. Experiment #2: Results
The measured polyphenol levels were, for Batches A through E respectively: 112 mg/L, 125 mg/L, 112 mg/L, 130 mg/L, and 141 mg/L.  Figure 3 shows these polyphenol concentrations plotted as a function of the estimated concentration of total hop matter in the wort at the time the sample was taken (10 minutes of steeping).  The cone polyphenol concentrations are shown with green points and connecting dashed lines, and the pellet concentrations are shown with red points and connecting dashed lines.  The cones data and pellets data were each fit to a linear function (referred to as “model” in Figure 3), which are plotted in lighter green and red with solid lines.

Figure 4 shows the measured IBU values from this experiment, with cones in green and pellets in red.  The average difference in IBUs between Batches A and C is 8.3 IBUs, and the average difference between Batches B and D is 10.1 IBUs.

Figure 3. Concentration of polyphenols as a function of the concentration of total hop matter. Data for cones are plotted in green; data for pellets are plotted in red. The raw data are shown with triangles and dashed lines. The best linear fit to the data is shown using solid lines.

Figure 4. Measured IBU values for the five batches of beer in Experiment #2. Values for hop cones are shown in green, and pellets are shown in red. The average difference between Batches A and C is 8.3 IBUs, and the average difference between B and D is 10.1 IBUs.

8. Experiment #2: Analysis
In Experiment #2, the results from cones indicate a malt polyphenol concentration of 104.20 mg/L (when the hop polyphenol concentration is zero), and the results from pellets indicate a malt polyphenol concentration of 102.84 mg/L.  On average, the results indicate that in this experiment the malt contributed 103.5 mg/L of polyphenols.  The model of polyphenols developed in The Contribution of Malt Polyphenols to the IBU predicts 97.66 mg/L from the specific gravity and boil time, which is within 6% of the measured values.  The model of IBUs developed in that blog post predicts 0.81 IBUs from the malt polyphenols, based on the specific gravity and wort pH.

We can use the slope of the lines in Figure 3 to estimate what percent of the weight of the hops comes from polyphenols.  First, we assume that 20% of polyphenols dissolve in wort [Forster, p. 124] and that there is a fermentation loss factor of 0.70 (estimated in The Contribution of Malt Polyphenols to the IBU and assuming the same loss factor for malt and hop polyphenols).  From those assumptions and the slope of the lines in Figure 3, the hop cone polyphenols are 3.1% of the weight of the hops, and the pellet polyphenols are 4.5% of the weight of the hops.  Both of these values are within published estimates that hop polyphenol levels are in the range from 2% to 6% of the weight of the hops [Shellhammer, p. 169; Hough et al., p. 422; Algazzali, p. 5; Verzele and De Keukeleire, p. 9].  In general, the hop pellets here demonstrate a 43% increase in polyphenol concentrations, compared with hop cones (0.00628 / 0.00439 = 1.43 or 43% increase).

We can then use the slope of the lines in Figure 3 to estimate the IBUs contributed by the hop polyphenols.  Ellen Parkin reports that “an increase of 100 mg/L of polyphenols was predicted to increase the [IBU] value by 2.2” [Parkin, p. 28], and so the increase in hop polyphenols in Figure 2 can be mapped to an increase in IBU levels using a conversion factor of 0.022 from concentration (in mg/L) to IBUs.  Using this conversion results in estimates of 0.17, 0.21, 0.46, 0.57, and 0.85 IBUs for Batches A through E, respectively.

Figure 4 shows the measured IBU values from this experiment.  The average difference between Batches A and C is 8.2 IBUs, and the average difference between Batches B and D is 10.1 IBUs.  The first point of interest is that the observed increase in IBUs from using pellets is at least an order of magnitude greater than the expected increase in IBUs caused by hop polyphenols.  This effectively rules out hop polyphenols as being the primary cause of the increase in IBUs observed with pellets.  The second point of interest is that even though the concentration of hops increased by a factor of 2.67 between Batches A and B and between Batches C and D, the IBUs associated with the use of pellets increased only from 8.2 to 10.1 (on average) with the increase in hop concentration, or a factor of 1.22.  This implies that the increase in IBUs associated with pellets is subject to a solubility limit somewhere between 150 ppm and 400 ppm.  Such a solubility limit is already expected with alpha acids, but is not expected with other auxiliary bittering compounds.  This implied solubility limit is consistent with the hypothesis that the increase in IBUs with pellets is caused by the production of oxidized alpha acids when hops are added to the kettle; this oAA production would be restricted by the same solubility limit that limits the isomerization of alpha acids.

9. Summary and Conclusion
The results of the first experiment indicate that the increase in IBUs associated with the use of pellets is caused by an increased concentration of auxiliary bittering compounds, not by increased availability of alpha acids that quickly become isomerized alpha acids.

Of the possible auxiliary bittering compounds (oxidized alpha acids, oxidized beta acids, hop polyphenols, and malt polyphenols), oxidized alpha acids (especially those produced during the boil [Algazzali, p. 17]) are the only likely candidate, with the increase in IBUs from pellets as a function of hopping rate consistent with an alpha-acid solubility limit.  Oxidized beta acids produced during the boil are highly unlikely because of their very low presence in finished beer when using well-preserved hops.  Hop polyphenols are estimated to contribute about an order of magnitude less to the IBU than observed differences, and the contribution of malt polyphenols is obviously unrelated.

Based on the results of these experiments, oxidized alpha acids appear to be the source of the increase in IBUs when using pellets.  Why would the use of pellets increase the concentration of oxidized alpha acids?  Maye et al. found that oxidized alpha acids make up less than 0.5% by weight of hop pellets before being added to wort [Maye, p. 24], which is not enough to explain the observed increase in IBUs.  However, the “creation of [oxidized alpha acids] occurs when hops are added to boiling wort” [Algazzali, p. 17].  The pelletization process ruptures the luplin glands [Hall, p. 58], and therefore the alpha acids of pellet hops have a much greater surface area (compared with cones).  It seems plausible that the oxidation of alpha acids that happens during the boil is limited by both the initial available surface area of the alpha acids and their solubility; in other words, only those alpha acids that are initially exposed to (and dissolve in) the boiling wort are quickly oxidized.  Therefore, the greater surface area of alpha acids in hop pellets allows more production of oxidized alpha acids during the boil, thereby increasing the IBU value.

10. Acknowledgements
I would, as usual, like to thank Dana Garves at Oregon BrewLab for the IBU and polyphenol analyses for these experiments.  The conclusions reached by these experiments would not be possible without the level of accuracy that Oregon BrewLab provides.

References

  • V. A. Algazzali, The Bitterness Intensity of Oxidized Hop Acids: Humulinones and Hulupones, Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2014.
  • C. Almaguer, C. Schönberger, M. Gastl, E. K. Arendt, and T. Becker, “Humulus lupulus – a story that begs to be told: A review,” in Journal of the Institute of Brewing, vol. 120, pp. 289-314, 2014.
  • R. Daniels, Designing Great Beers: The Ultimate Guide to Brewing Classic Beer Styles.  Brewers Publications, 2000.
  • J. Dierckens and M. Verzele, “Oxidation Products of Humulone and Their Stereoisomerism,” in Journal of the Institute of Brewing, vol. 75, pp. 453-456, 1969.
  • G. J. Fix and L. A. Fix, An Analysis of Brewing Techniques.  Brewers Publications, 1997.
  • A. Forster, “Influence of Hop Polyphenols on Beer Flavor,” in Hop Flavor and Aroma: Proceedings of the 1st International Brewers Symposium, ed. Thomas H. Shellhammer, Master Brewers Association of the Americas, 2009.
  • M. L. Hall, “What’s Your IBU,” in Zymurgy.  Special Edition, 1997.
  • J. S. Hough, D. E. Briggs, R. Stevens, and T. W. Young, Malting and Brewing Science. Volume 2: Hopped Wort and Beer. Springer-Science+Business Media, B. V., 2nd edition, 1982.
  • M. J. Lewis and T. W. Young, Brewing. Springer Science+Business Media, 2nd edition, 2001.
  • M. G. Malowicki, Hop Bitter Acid Isomerization and Degradation Kinetics in a Model Wort-Boiling System, Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2005.
  • J. P. Maye, R. Smith, and J. Leker, “Humulinone Formation in Hops and Hop Pellets and Its Implications for Dry Hopped Beers”, in MBAA Technical Quarterly, vol. 51, no. 1, pp. 23-27, 2016.
  • G. J. Noonan, New Brewing Lager Beer. Brewers Publications, 1996.
  • E. J. Parkin, The Influence of Polyphenols and Humulinones on Bitterness in Dry-Hopped Beer, Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2014.
  • V. Peacock, “The International Bitterness Unit, its Creation and What it Measures,” in Hop Flavor and Aroma: Proceedings of the 1st International Brewers Symposium, ed. Thomas H. Shellhammer, Master Brewers Association of the Americas, 2009.
  • T. H. Shellhammer, “Hop Components and Their Impact on the Bitterness Quality of Beer,” in Hop Flavor and Aroma: Proceedings of the 1st International Brewers Symposium, ed. Thomas H. Shellhammer, Master Brewers Association of the Americas, 2009.
  • S. Srečec, T. Rezić, B. Šantek, and V. Marić, “Hop Pellets Type 90: Influence of Manufacture and Storage on Losses of α-Acids,” in Acta Alimentaria. Vol. 38, no. 1, pp. 141–147, 2009
  • M. Verzele and D. De Keukeleire, Chemistry and Analysis of Hop and Beer Bitter Acids.  Developments in Food Science 27.  Elsevier, 1991.

 

How Lautering and Wort Clarity Affect IBUs

Abstract
Lautering is the process of separating wort from spent grains.  Two of the three experiments described here look at wort produced using different lautering techniques and how the resulting wort characteristics impact IBUs.  The third experiment looks at the impact of wort clarity after lautering.  The results indicate that very turbid (cloudy) wort can yield about 30% fewer IBUs than average, and very clear wort (free from smaller particles) can yield about 30% more IBUs than average.  A 10-minute rest period to allow hot and cold break to settle before transfer into the fermentation vessel can have an 8% impact on IBUs, suggesting that it’s not the lautering technique itself but the final clarity of the wort going into the fermentation vessel that affects IBUs.  The reason for the difference in IBUs may be that isomerized alpha acids (IAA) bind to small particles in the wort during fermentation and precipitate out of solution.  A proposed model of the impact of wort clarity on IAA uses a linear scaling factor with a value of 1.30 for very clear wort, 1.0 for average wort, and 0.70 for very cloudy wort.  While the results indicate that clear wort yields more IBUs than cloudy wort, the adage that “clear wort produces clear beer” was not confirmed.

1. Introduction
A number of factors are typically listed as having an impact on IBUs and/or isomerized alpha acids, including alpha-acid concentration, boil time, wort temperature, hopping rate, wort pH, form of the hops (e.g. cones or pellets), and wort gravity.  Lewis and Young state that “iso-alpha-acids react with proteins of wort whence they are partially removed as trub or hot break” [Lewis & Young, p. 266], implying that a wort higher in protein might result in reduced isomerized alpha acid concentration and therefore lower IBUs.  In the first experiment described in this blog post, I was looking for the effect that wort protein levels might have on IBUs.  Because the teig layer on top of the grain bed that results from recirculation is high in proteins [Lewis & Young, p. 216, p. 247], I thought that it would be interesting to compare protein levels from lautering with and without recirculation, and to compare the IBUs from these different worts when using the same amount of hops.  When this experiment (described in Section 3) did not show the expected results, but other preliminary data indicated the possible impact of wort clarity instead of proteins, I performed the second experiment with lautering techniques that produced different levels of wort clarity, and the third experiment with the same post-boil wort but different levels of clarity going into the fermentation vessel. When looked at as a single set of data, the first two experiments provide six examples of wort lautered in five different ways, producing wort of varying clarity.  These experiments present the first data I’m aware of that look at the impact of lautering technique and wort clarity on IBUs.

2. Terminology
2.1 The IBU
The IBU is a measure of the concentration of a number of different bitter compounds in beer.  (To be more precise, the IBU is a measure of the absorbance of light at 275 nm through acidified beer.  A number of bitter compounds in beer absorb light at this frequency.  The greater the concentration of these compounds, the more light is absorbed, and the higher the IBU.)  In typical beers, the IBU value represents mostly the concentration of isomerized alpha acids (IAAs) [Peacock, pp. 164-165], which are produced during the boil from alpha acids (AA).  The other bitter compounds, known as “auxiliary bittering compounds” (ABCs), or nonIAA, are polyphenols, oxidized alpha acids, and oxidized beta acids.  These compounds can be considered to be present in the wort soon after the hops addition [e.g. Dierckens and Verzele, p. 454; Askew, p. 18].  The majority of ABC appear to be oxidized alpha acids, which are produced when hops are added to the boiling wort [Parkin, p. 11, Algazzali, p. 17; Dierckens and Verzele, p. 454; Oliver p. 471] as well as during storage [Lewis and Young, p. 265].

2.2 Lautering
Lautering is the process of separating wort from spent grains.  There are several possible steps in lautering: mash-out, recirculation, sparging, and drawing (or run-off) of the liquid wort.  All of these steps are optional except for the drawing of wort.  If performing a mash-out, the temperature of the wort is raised to 170°F (77°C) to stop (or greatly reduce) enzymatic activity.  If performing recirculation (also called vorlauf), some of the wort is drawn out and recirculated back onto the grain bed.  The grain bed acts as a filter to remove larger particles from the wort [Oliver, p. 819].  There are two common types of sparging: fly sparging and batch sparging; it is also possible to omit this step entirely for “no sparge” wort collection. While the drawing of wort is not typically discussed much, in my experience the speed at which the wort is drawn, in combination with how well the grain bed filter has set, can have a large effect on wort clarity.  There is an adage that “clear wort makes clear beer“, and so some brewers aim for the clearest wort possible.

2.3 Brew-in-a-Bag (BIAB)
The Brew-in-a-Bag (BIAB) technique is one method of lautering.  In its most basic form, the mash is performed while the grains are inside a mesh bag; when the mash is complete, the bag is removed (with the grains), leaving the wort behind.  There are several variations on this technique, including with and without mash-out, and with and without sparging.  The standard BIAB approach is essentially lautering with an optional mashout, no recirculation, no sparge, and fast drawing of the wort.

2.4 Teig and Wort Proteins
Recirculation and/or continuous sparging can form a layer of teig (“top dough”) on the top of the grain bed [Palmer, p. 306].  This teig layer is high in proteins [Lewis & Young, p. 216, p. 247].  Because the teig layer is separate from the liquid wort, wort that is produced leaving a layer of teig on the grain bed should have a lower concentration of proteins than wort in which no teig layer is formed.

2.5 Wort Clarity
While there are instruments for measuring turbidity, I judged wort clarity/turbidity in these experiments on an entirely subjective basis.  (Tubidity meters do exist but are not cheap.)  If I were to re-do these experiments, I would more strongly consider investing in such a meter.

3. Experiment #1
3.1 Experiment #1: Experimental Overview
The intended difference between conditions in the first experiment was the level of protein in the wort, which was expected to differ according to the amount of teig on the grain bed, which in turn was controlled by lautering with and without recirculation.

This first experiment had three conditions.  Condition A used wort produced with mash-out, without recirculation, and no sparge (in a manner similar to BIAB). Condition B used wort produced with mash-out, with recirculation, and no sparge.  Condition C used wort produced from Briess Pilsen Light Dried Malt Extract (DME).  The intended difference between Conditions A and B was a teig layer in Condition B that would decrease the concentration of proteins in the wort relative to Condition A.  Condition C was used as a reference condition, as most of the experiments conducted for this blog have used wort produced using DME.

For lautering Conditions A and B, I used a 13 G (49 l) picnic-cooler lautering vessel with a 12″ (30 cm) mash screen connected to a ball valve and tubing.  To prevent very large particles from ending up in the wort of Condition A, I covered the mash screen with a fine mesh bag.   In Condition B, I performed the recirculation for 10 minutes, gently recirculating the wort to the other end of the lautering vessel.  In both Condition A and Condition B, I kept the ball valve approximately one-third open, allowing the wort to flow at a moderate rate.

In other respects, all three conditions were intended to be identical, having the same target specific gravity, volume, and hops.  I did not expect the wort pH to differ significantly between conditions, and so I did not control for pH.

3.2 Experiment #1: Methods
For Conditions A and B, 7.06 lbs (3.20 kg) of two-row malt was added to 4.87 G (18.42 l) of low-alkalinity water in a 10 G (38 l) kettle.  The crushed grains were heated to 153°F (67°C) and this temperature was held for 60 minutes.  The kettle was then heated to 170°F (77°C) for 10 minutes.  The mash was transferred to the lauter tun, and for Condition B a 10-minute recirculation step was performed.  The wort was drawn into the boil kettle with a moderate flow to collect 3.58 G (13.55 l) of wort at ~160°F (~70°C), corresponding to a room-temperature volume of 3.50 G (13.25 l).

For Condition C, 3.58 lbs (1.62 kg) of Briess Pilsen Light DME was added to 3.26 G (12.36 l) of 120°F low-alkalinity water to target 3.54 G (13.40 l) of wort at 120°F (49°C), corresponding to a room-temperature wort volume of 3.50 G (12.25 l).  The wort then sat for 2 hours to let the pH stabilize.

For all conditions, the wort was brought to a boil, a 33-oz (0.98-liter) sample of wort was taken (the “pre-boil” sample), the wort was boiled for 5 minutes, and 0.72 oz (20.4 g) of Comet hops were added.  These hops were analyzed shortly after harvest and found to have an AA rating of 10.8%.  The hops were 7.5 months old at the time of the experiment, and so the estimated alpha-acid rating at the time of the experiment was 9.73% using the Garetz formula [Garetz].  The volume of wort and amount of hops were designed to yield an alpha-acid concentration of 170 ppm when the hops were added to the kettle.  The kettle was covered during the boil (except for the initial 5 minutes and for taking samples) in order to minimize evaporation and the resulting changes in volume and specific gravity.  A 15-oz (0.44-liter) sample was taken every 10 minutes after the hop addition, for a total of 40 minutes (4 samples per condition).  Each sample was quickly cooled in an aluminum cup and ice bath to 75°F (24°C) and then transferred to a sanitized quart (liter) container.  The wort in each container was aerated for 1 minute by vigorous shaking, and 0.0085 oz (0.24 grams) of Safale US-05 yeast (age 9 months) was pitched to target 750,000 cells per ml and degree Plato.  At the end of the 40-minute boil, another sample was taken (the “post-boil” sample) and cooled to room temperature.

The 10, 20, 30, and 40-minute samples fermented for about one week (with a small opening to vent CO2).  The pre- and post-boil samples were stored in sanitized and refrigerated sample containers during this time.  The krausen of the fermenting samples was left to deposit on the sides of the vessel during fermentation.  I removed the krausen deposits one day before taking samples for analysis by Oregon BrewLab.  Oregon BrewLab analyzed the unfermented pre- and post-boil samples for protein levels, the 40-minute sample from Condition C for protein, and all fermented samples for IBUs.

3.3 Experiment #1: Results
The subjective clarity of wort increased between Conditions A, B, and C.   The wort from Condition A was very cloudy, as expected; perhaps the word “murky” would be a good descriptor.  Despite my attempt at using recirculation to produce clear wort, Condition B was judged probably cloudier than Condition C.

The specific gravity at the start and end of the boil was nearly the same for all three conditions, with a starting gravity of 1.045 and a post-boil gravity of 1.046 (Conditions A and C) or 1.047 (Condition B).  The pre-boil pH, however, was unexpectedly low for the all-grain conditions, at 5.55 and 5.54 for Conditions A and B, respectively; the DME condition had a more expected pre-boil pH (given the specific gravity) of 5.74.

The protein levels at the start of the boil were 2.4, 2.3, and 2.7 g/12oz for Conditions A, B, and C, respectively.  The post-boil protein levels were 2.2, 2.4, and 2.9 g/12oz for Conditions A, B, and C.  The protein level of the finished beer of Condition C was 2.5 g/12oz.  The protein levels between Conditions A and B are nearly identical, and certainly not the difference that was expected.

The IBU values are plotted in Figure 1.  It can be seen that Condition A has significantly lower IBU values than Condition B, and Condition B has lower values than Condition C.  For the 40-minute samples, Condition C (34.8 IBUs) has 55% more IBUs than Condition A (22.4 IBUs) .

Figure 1. Measured IBU values from the first experiment.  Condition A used lautering with no recirculation and a medium rate of drawing wort, Condition B used lautering with recirculation and a medium rate of drawing wort, and Condition C used dried malt extract.

4. Experiment #2
4.1 Experiment #2: Experimental Overview
While Experiment #1 did not show the expected change in protein levels, it did show a remarkable difference in IBU levels.  Some additional preliminary experiments (not described here) suggested that rather than protein, the wort clarity might be correlated with IBUs.  The purpose of Experiment #2 was to obtain additional data for evaluating the relationship between wort clarity and IBUs.  By the time I conducted Experiment #2, I was able to successfully produce very clear wort by resting the mash for 30 minutes, using a 10-minute recirculation, and drawing the wort very slowly from the lauter tun.  I again used a fine mesh bag over the mash screen to filter out large particles from the wort.

This experiment had three conditions.  Condition D used (like Condition A in Experiment #1) a mash-out, no-recirculation, no-sparge lauter, but this time I opened the ball value fully to quickly collect the wort.  Condition E used a 30-minute rest of the mash after mash-out, 10-minute recirculation, and very slow drawing of the wort (over one hour to collect less than 2 G (7.6 l) of wort), to produce a very clear wort.  Condition F used (like Condition C in Experiment #1) DME, and again serves as a point of reference with other experiments.

In other respects, all three conditions were intended to be identical, having the same target specific gravity, volume, and hops.  This time, I adjusted the pre-boil wort pH of Condition F (using phosphoric acid) to be the same as that in Conditions D and E.

4.2 Experiment #2: Methods
In this experiment, I created one high-gravity mash for Conditions D and E.  I added 16.46 lbs (7.47 kg) of two-row malt to 6.33 G (23.96 liters) of low-alkalinity water at 105°F (40.5°C).  I heated this mash in a kettle to 153°F (67.2°C) and held this temperature for 60 minutes.  Then I raised the mash temperature to 170°F (76.7°C) for 15 minutes.  I then transferred all of the mash to the lauter vessel and immediately drew 1.79 G (6.78 l) of hot wort with the ball valve completely open for fast transfer.  I added 1.75 G (6.62 l) of room-temperature water to this wort to create (room-temperature-normalized) 3.50 G (13.25 l) of wort for Condition D.  I stirred the mash remaining in the lauter vessel and let it sit for 30 minutes, followed by 10 minutes of recirculation with the ball valve open just enough to let through a steady trickle of wort.  After the recirculation, I drew the wort slowly into another boil kettle, taking over an hour to collect 2 G (7.6 l) of wort.  I decanted 1.76 G (6.66 l) of this warm wort and added 1.75 G (6.62 l) of room-temperature water to create 3.50 G (13.25 l) of wort (normalized to room temperature) for Condition E.

The wort for Condition F was created using 3.15 lbs (1.43 kg) of DME with 3.30 G (12.49 l) of 120°F (49°C) water, corresponding to a room-temperature wort volume of 3.50 G (13.25 l).  This wort sat for over two hours to let the pH stabilize.  I then adjusted the wort of Condition F to be the same as Conditions D and E, using phosphoric acid.

For all conditions, the wort was brought to a boil, a 12 oz (0.35 l) sample of wort was taken for measuring specific gravity and pH, the wort was boiled for 5 minutes, and 1.33 oz (37.57 g) of Cascade hops (AA rating 6.4%, analyzed soon after harvest) were added.  The hops were 18.5 months old at the time of the experiment, and so the estimated alpha-acid rating at the time of the experiment was 5.53% using the Garetz formula [Garetz].  The volume of wort and amount of hops were designed to yield an alpha-acid concentration of 170 ppm when the hops were added to the kettle, the same as in Experiment #1.  The kettle was covered during the boil (except for the initial 5 minutes and for taking samples) in order to minimize evaporation and the resulting changes in volume and specific gravity.  A 15-oz (0.44-liter) sample was taken every 10 minutes after the hop addition, for a total of 40 minutes (4 samples per condition).  Each sample was quickly cooled in an aluminum cup and ice bath to 75°F (24°C) and then transferred to a sanitized quart (liter) container.  The wort in each container was aerated for 1 minute by vigorous shaking, and 0.010 oz (0.29 grams) of Safale US-05 yeast (age 14 months) was pitched to target 750,000 cells per ml and degree Plato.  At the end of the 40-minute boil, another sample was taken for measuring specific gravity and pH.

The 12 samples fermented for about one week (with a small opening to vent CO2).  The krausen was left to deposit on the sides of the vessel during fermentation.  I removed the krausen deposits one day before taking samples for analysis by Oregon BrewLab.  Oregon BrewLab analyzed all samples for IBUs and the 40-minute samples for both protein and polyphenol concentrations.

4.3 Experiment #2: Results
While the intent with Condition D was to create a cloudy wort, I found that by completely opening the ball valve, the initial wort was cloudy but the grain bed quickly compacted.  By the time I was collecting the second gallon of wort, the wort had become noticeably clearer.  Therefore, Condition D was cloudy (and more cloudy than Conditions E or F), but subjectively less cloudy than Condition A even though neither method used recirculation.  The wort for Condition E was, as hoped, subjectively much clearer than the wort for Conditions D and F.

The specific gravity at the start and end of the boil was nearly the same for all three conditions, with a gravity at the start of the boil of 1.041 to 1.042 and a post-boil gravity of 1.041 to 1.044.  The measured pre-boil pH was 5.69 for Condition D and 5.67 for Condition E.   The initial pH of Condition F was 5.86, and this was lowered to 5.68 using phosphoric acid.  While the pH of Conditions D and E was still lower than expected, it was much greater than the pH observed in Experiment #1 for the all-grain conditions.

The protein levels of the finished beer were 2 g/12oz for all conditions, indicating that the protein levels did not vary significantly between the conditions or between the experiments.

The polyphenol concentrations were 156, 165, and 138 mg/L for Conditions D, E, and F, respectively.  The recirculated wort therefore had a somewhat higher polyphenol concentration than the non-recirculated wort.  This difference can be attributed entirely to the higher specific gravity of Condition E (1.0436) relative to Condition D (1.0411) using a previously-developed model of malt polyphenols. (A higher-gravity wort contains not only more sugars, but also a higher concentration of malt polyphenols.)

The IBU values are plotted in Figure 2.  It can be seen that Condition D (cloudy wort) has on average somewhat lower IBU values than Condition F (DME), and that both of these conditions have much lower IBU values than Condition E (clear wort).  For the 40-minute samples, Condition E (37.5 IBUs) has 21% more IBUs than Condition D (30.9 IBUs).

In this experiment, I took note of the subjective clarity of the finished beer, expecting the clear wort to produce clear beer.  In contrast, the beer from Condition D (cloudy wort) was noticeably clearer than the other two, and the beer from Condition E (clear wort) was not noticeably clearer than the beer from Condition F (DME).

Figure 2. Measured IBU values from the second experiment.  Condition D used lautering with no recirculation and fast drawing, Condition E used lautering with recirculation and slow drawing, and Condition F used dried malt extract.

5. Experiment #3
5.1 Experiment #3: Experimental Overview
Both Experiments #1 and #2 demonstrated an impact of lautering technique on IBUs.  Because Mark Malowicki showed that the production of IAA is not greatly affected by factors such as brewing-range pH or maltose levels [Malowicki, p. 31], it is likely that the impact of lautering technique on IBUs is caused by a reduction in the levels of IAA (and/or auxiliary bittering compounds) after they have been produced.  This leaves us with the question of whether the reduction in IBUs occurs primarily during the boil or during fermentation.

The third experiment looked at the impact of wort settling on IBUs, using the same post-boil wort in all conditions.  Four samples were created with either “settled” wort or “stirred” wort, and IBUs were measured from the beers produced from these samples.  If the IBUs of the four conditions are quite similar, then we don’t need to worry about settling or wort clarity going into the fermentation vessel; the IAA (and possibly nonIAA) are already reduced during the boil.  If the IBUs are different, then the final wort clarity is more important than the specific lautering technique, and the reduction happens primarily during fermentation.

Condition G (settled wort) used a 32-oz (0.946-liter) sample of wort taken from the top of the wort at the end of the boil.  This sample sat undisturbed in an ice bath to cool and settle, after which 16 oz (0.473 liters) of clear wort were decanted for fermentation.  Condition H (stirred wort) used a 16-oz (0.473-liter) sample of wort taken after Condition G and after the hot wort had been thoroughly stirred.  Condition J (stirred wort) used a 16-oz (0.473-liter) sample of wort taken immediately after forced cooling of the full volume of wort to room temperature, and Condition K (settled wort) used a 16-oz (0.473-liter) sample taken from the top of the full volume of wort after forced cooling and a 10-minute rest.

5.2 Experiment #3: Methods
In this experiment, I created one set of wort for all samples.  I added 2.55 lbs (1.16 kg) of DME to 3.370 G (12.755 liters) of low-alkalinity water at 120°F (49°C) to yield 3.50 G (13.25 l) of room-temperature wort at specific gravity ~1.030. This wort sat for 90 minutes to let the pH stabilize, after which I adjusted the pH to 5.30 using phosphoric acid.  I heated the wort to boiling, boiled it for 5 minutes to reduce the foam associated with the start of the boil, and took a 12-oz (0.355-liter) sample for measuring specific gravity and pH.  I then added 1.24 oz (35.13 g) of Cascade hops with an average AA rating at harvest of 7.7% and estimated decay factor of 0.80, targeting about 180 ppm of alpha acids at the start of the steep.  The hops were contained in a coarse mesh bag and boiled in the wort for 40 minutes.

At the end of the boil, 32 oz (0.946 liters) were taken from the top of the kettle and set aside in an ice bath to both cool and settle for Condition G.  The wort was stirred, and 16 oz (0.473 liters) were taken and set in an ice bath for Condition H.  The remaining wort was then quickly cooled to 75°F (24°C) using an immersion chiller.  When the full volume of wort reached 75°F (24°C), it was stirred and a 16-oz (0.473-liter) sample was immediately transferred to a sanitized quart (liter) container for Condition J.  The full volume of wort then sat undisturbed for 10 minutes (with the lid on the kettle), after which a 16-oz (0.473-liter) sample was taken from the top of the wort and transferred to a sanitized quart (liter) container for Condition K.  When Condition G had reached 75°F (24°C), 16 oz (0.473 liters) of clear wort were decanted to a sanitized quart (liter) container.  When Condition H reached the same temperature, all of it was transferred to a sanitized quart (liter) container.

Each sample was then aerated for 1 minute by vigorous shaking, and 0.0085 oz (0.24 g) of Safale US-05 yeast (age 11 months) was pitched to target 750,000 cells per ml and degree Plato.  Each sample fermented for about one week (with a small opening to vent CO2).   Each sample was swirled once a day to reduce krausen deposits.  Oregon BrewLab analyzed all samples for IBUs.

5.3 Experiment #3: Results
Condition G (settled wort) had 29.2 IBUs.  Condition H (stirred wort) had 26.9 IBUs.  Condition J (stirred wort) had 26.5 IBUs.  Condition K (settled wort) had 28.5 IBUs.  Comparing the two conditions taken before immersion chilling, Condition H had 7.8% lower IBUs than Condition G.  Comparing the two conditions taken after immersion chilling, Condition J had 7.0% lower IBUs than Condition K.  While the reduction in IBUs is not as pronounced as in the first two experiments, (a) the use of DME in all conditions (which had average or better-than-average wort clarity in the previous experiments) might have prevented a larger difference in wort clarity from being achieved through settling, and (b) the differences might have become larger with a settling time longer than 10 minutes.  At any rate, it appears that clarifying the wort by settling does yield relatively greater IBUs than stirred wort.  This result indicates that it is probably the clarity of the wort going into the fermentation vessel that is important.

6. Analysis
6.1 IBUs, IAA, and oAA
While there are differences between the first two experiments in terms of wort pH, specific gravity, and variety and weight of hops used, the IBU results from the two DME conditions are quite similar (the green lines in Figure 3), indicating that a comparison between two conditions from the different experiments is not unwarranted.  (Note that one would expect Condition F to have somewhat lower IBU values than Condition C, as observed, because the pH of the wort in Condition F was lowered to 5.68, and lower pH is associated with lower IBU values.)

The following analysis combines the results of the first two experiments, yielding 6 data points produced using five techniques: Condition A, with very cloudy wort produced without recirculation and a moderate drawing rate; Condition B, with moderately cloudy wort produced with recirculation and a moderate drawing rate; Condition C, with moderately clear wort produced from DME; Condition D, with moderately cloudy wort produced without recirculation and a fast drawing rate; Condition E, with very clear wort produced with recirculation and a slow drawing rate; and Condition F, with moderately clear wort produced from DME.  Figure 3 shows the IBU results from all six conditions.

Figure 3. Measured IBU values from the first and second experiments.    Condition A used lautering with no recirculation and a medium rate of drawing wort, Condition B used lautering with recirculation and a medium rate of drawing wort, and Condition C used dried malt extract.  Condition D used lautering with no recirculation and fast drawing, Condition E used lautering with recirculation and slow drawing, and Condition F used dried malt extract.

Figure 3 shows a general correspondence between subjective wort clarity and IBUs; the more turbid the wort, the lower the IBU levels.  The increase in IBUs from the average IBU at a time point (over the six conditions) to the IBU of the clearest wort (Condition E) ranges from 20% (at 40 minutes) to 29% (at 30 minutes).  The decrease in IBUs from the average to the most turbid wort (Condition A) ranges from 21% (at 10 minutes) to 29% (at 40 minutes).  The IBU values from the two DME conditions are within 6% of each other, which (a) is well within the possible range of alpha-acid variation between and within bales, estimated at 15% to 20% [Verzele and De Keukeleire, p. 331] and (b) follows the expected trend of lower-pH worts having lower IBUs.  Therefore, the IBU differences between the two DME conditions are well within expected variation.

We can use the IBU values from each condition to estimate an IAA scaling factor and an oxidized-alpha acid (oAA) scaling factor, using the technique described in Estimating Isomerized Alpha Acids and nonIAA from Multiple IBU Measurements and assuming that the other auxiliary bittering compounds can be modeled reasonably well with existing formulas (as described in Section 5 of that blog post).  This estimation yields the scaling factors specified in Table 1.  The most turbid wort (Condition A) has the lowest IAA scaling factor, and the clearest wort (Condition E) has the highest IAA scaling factor.  There is, however, no clear pattern to the oAA scaling factor, other than the two DME conditions having the two lowest values. The oAA scaling factor has a mean of 0.085 with standard deviation 0.012.

Because the oAA scaling factor shows no clear pattern correlating with the IBU measurements, and because the standard deviation is fairly small relative to the mean, the variation in oAA scaling factor may be due to measurement error, modeling error, and/or a limited number of data points.  We can then set this value to the average oAA scaling factor, 0.085, and re-estimate the IAA scaling factors.  These results are listed in Table 2.  With these results, the most turbid wort (Condition A) (still) has the lowest IAA scaling factor and the clearest wort (Condition E) (still) has the highest IAA scaling factor.  These estimated IAA scaling factors have a strong positive correlation of 0.975 with the measured IBU values at 40 minutes.

Condition: A B C D E F
IAA scaling factor: 0.289 0.417 0.507 0.432 0.523 0.503
oAA scaling factor: 0.086 0.096 0.077 0.081 0.102 0.069

Table 1.  Estimated IAA and oAA scaling factors for each of the six conditions in the combined set of experiments.  Each scaling factor was estimated from four measured IBU values.

Condition: A B C D E F
IAA scaling factor: 0.291 0.441 0.483 0.419 0.575 0.453

Table 2.  Estimated IAA scaling factors for each of the six conditions in the combined set of experiments, holding the oAA scaling factor constant at 0.085.  Each IAA scaling factor was estimated from four measured IBU values.

The average of the six IAA scaling factors, 0.433, is close to the average of the four “mid-range” scaling factors, 0.444.  If we take 0.444 as the scaling factor for “average” wort turbidity, we can create a linear scaling factor for the impact of wort turbidity on IAA concentration.  This scaling factor has a value of 1.0 for average wort, 1.30 (1.30=0.575/0.444) for very clear wort (Condition E), and 0.66 (0.66=0.291/0.444) for very cloudy wort (Condition A).  While precisely quantifying wort turbidity from subjective descriptions is an additional challenge, the impact on IBUs may be roughly estimated using general descriptors and associated scaling factors.  For example, wort descriptions and scaling factors might be “very clear” (1.30), “clear” (1.20), “somewhat clear” (1.10), “average” (1.0), “somewhat cloudy” (0.90), “cloudy” (0.80), and “very cloudy”  (0.70).  Mapping from scaling factor to description, Condition A is even more than “very cloudy” (0.66 < 0.70), Condition B is “average” (0.993 ≈ 1.00), Condition C is “somewhat clear” (1.088 ≈ 1.10), Condition D is in between “somewhat cloudy” and “average” (0.90 < 0.944 < 1.00), Condition E is “very clear” (1.295 ≈ 1.30), and Condition F is close to “average” (1.020 ≈ 1.00).  While this turbidity scale ranges from 30% less than average to 30% more than average, the four non-extreme cases here all fall within 10% of average turbidity.

Why might wort turbidity affect the IAA concentration?  Lewis and Young say that “iso-alpha-acids, being surfactants, react with inert surfaces of all sorts” [Lewis & Young, p. 267].  It is therefore possible, especially given the results of the third experiment, that IAA react or bind with the fine particles in turbid wort during fermentation and then precipitate out of solution, lowering the IBU.  The wort clarity going into the fermentation vessel (instead of the pre-boil clarity resulting from the lautering technique) appears to be the most relevant factor.

6.2 Protein Levels
For Experiments #1 and #2, I had the protein levels in the wort and beer measured, in order to check the hypothesis that protein levels and IBUs are negatively correlated.   The results listed in Sections 3.3 and 4.3 demonstrate that the protein levels were very similar across all three pre-boil worts in Experiment #1.  The protein levels in Experiment #1 didn’t change significantly during the boil or during fermentation.  The protein levels in Experiment #2 showed no difference from each other or the values in Experiment #1.  Therefore,  the expected difference in protein levels did not materialize, indicating that recirculation and teig formation did not lower the protein concentration in the wort.  While there might be a relationship between protein levels and IBUs, these experiments do not evaluate such a relationship.

6.3 Polyphenols
I also had polyphenol concentrations measured in Experiment #2, as a way of testing the model of malt polyphenols proposed in the blog post The Contribution of Malt Polyphenols to the IBU and the model of hop polyphenols described in the blog post The Relative Contribution of Oxidized Alpha- and Beta-Acids to the IBU. Table 3 lists (a) the measured total polyphenol concentration in each condition, (b) the predicted polyphenol concentration derived from malt according to the model, (c) the estimated IBUs obtained from this model of malt polyphenols, (d) the predicted polyphenol concentration derived from hops, (e) the estimated IBUs obtained from these hop polyphenols, (f) the total polyphenol concentration from both malt and hops (the sum of the individual model concentrations), and (g) the total IBUs predicted to come from polyphenols according to the model.   The measured polyphenol concentrations are greater than the model concentrations by 21 mg/L in both Conditions D and E, and less than the model by 2 mg/L in Condition F.  The last row of Table 3 estimates the impact of the observed and model differences on IBUs, by changing the model’s malt polyphenol concentration to be equal to the measured concentration minus the estimated hop concentration, estimating the IBUs from the sum of the changed malt polyphenols and the hop polyphenols, and taking the difference between this new IBU estimate and the original IBU estimate.  Although the measured polyphenol concentration is up to 14% greater than the model concentration, the estimated impact of this difference is less than 0.2 IBUs.

Condition: D E F
Measured total polyphenol concentration:
156 mg/L 165 mg/L 138 mg/L
Model malt polyphenol concentration:
118.0 mg/L 126.5 mg/L 122.4 mg/L
Model malt IBU contribution:
0.84 1.00 1.29
Model hops polyphenol concentration: 16.9 mg/L 17.6 mg/L 17.3 mg/L
Model hops IBU contribution: 0.37 0.39 0.38
Model total polyphenol concentration:
134.9 mg/L 144.1 mg/L 139.7 mg/L
Model total IBU contribution: 1.21 1.39 1.67
Estimated model error, in IBUs:
0.13 0.14 0.0

Table 3.  Measured polyphenol concentrations, predicted polyphenol concentrations and IBUs (from malt, hops, and the combination), and estimated error in IBUs.

6.4 Wort and Beer Clarity
It would be interesting to repeat these experiments using a turbidity meter to obtain precise measurements of turbidity.  The subjective classifications I’ve used might be sufficient for describing a general trend, but they limit the objectiveness, and therefore the usefulness, of these results.

In the second experiment I found that Condition D, which had moderately cloudy wort, ended as an exceptionally clear beer.  Condition E, which had a very clear wort, ended as a somewhat cloudy beer after one week of fermentation.  Condition F, which like Condition D was neither exceptionally turbid nor exceptionally clear, also ended as a somewhat cloudy beer.  These results therefore show no relationship between wort clarity and beer clarity, in contrast with expectations.

6.5 Wort pH
From the blog post Some Observations of Mash and Wort pH, a wort made from either two-row malt or DME and with low-alkalinity water to a specific gravity of 1.040 to 1.045 should have a pH of about 5.75 to 5.85.  The pre-boil pH of the all-grain conditions in the first experiment (Conditions A and B) was much lower than expected given the specific gravity, at about 5.55.  The pH of the wort produced from DME in this experiment (Condition C) was close to the expected range, at 5.74.  The pH of Conditions D and E in the second experiment was higher than in the first experiment, at about 5.68, but still lower than Condition F (DME) at 5.86.  The reasons for the low pH values and differences in pH are unclear.  The all-grain conditions in both experiments used malt from the same 55-lb (25 kg) bag of Great Western two-row malt.  John Palmer and Colin Kaminski note that different lots of malt from the same maltster can produce variation in mash pH, and that pH can vary with growing conditions and microflora [Palmer and Kaminski, p. 76], which might explain the lower-than-expected pH from the all-grain conditions in both experiments.  (Another beer produced from this same bag of base malt also had a lower-than-expected unadjusted pH.)  The grist ratio (volume of water per weight of grain) was different between the two experiments, which might explain some of the difference between the pH observed in the two experiments [Palmer and Kaminski, p. 70].

7. Conclusion
Two of the experiments described here show that wort turbidity can affect IBUs by as much as 60%, with a ~30% increase in IBUs for very clear wort and a ~30% decrease for very cloudy wort.  The estimated IAA loss factor varies from 0.66 to 1.30 in the data from this experiment.  The third experiment indicates that this change in IBUs probably occurs during fermentation instead of during the boil.  In other words, the IAA levels appear to be affected by overall wort clarity during fermentation, not just the pre-boil wort clarity (from lautering technique).  The wort protein levels did not change with wort turbidity, and so the impact of protein on IBUs is still unclear.

Wort clarity was not well correlated with beer clarity, which does not support the adage that “clear wort makes clear beer”.

The combination of a previously-described model of malt polyphenols and model of hop polyphenols predicted the measured total polyphenol concentration reasonably well, with relative differences of -14%, -13%, and 1% for the three samples.

8. Acknowledgment
I would like to sincerely thank Dana Garves at Oregon BrewLab for the IBU, protein, and polyphenol measurements for these experiments.  Oregon BrewLab has always been a pleasure to work with.

References

  • V. A. Algazzali, The Bitterness Intensity of Oxidized Hop Acids: Humulinones and Hulupones, Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2014.
  • H. O. Askew, “Changes in Concentration of α and β Acids and of Iso-Compounds on Heating Extracts of Hops in Aqueous Solutions and Unhopped Wort,” in Journal of the Institute of Brewing, vol. 71, pp. 10-20, 1965.
  • J. Dierckens and M. Verzele, “Oxidation Products of Humulone and Their Stereoisomerism,” in Journal of the Institute of Brewing, vol. 75, pp. 453-456, 1969.
  • M. Garetz, “Hop Storage: How to Get – and Keep – Your Hops’ Optimum Value” in Brewing Techniques, January/February 1994, hosted on morebeer.com.
  • M. J. Lewis and T. W. Young, Brewing. Springer Science+Business Media, 2nd edition, 2001.
  • G. Oliver, The Oxford Companion to Beer, Oxford University Press, 2011.
  • J. J. Palmer, How to Brew: Everything You Need to Know to Brew Beer Right the First Time. 3rd edition, Brewers Publications, 2006.
  • E. J. Parkin, The Influence of Polyphenols and Humulinones on Bitterness in Dry-Hopped Beer, Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2014.
  • V. Peacock, “The International Bitterness Unit, its Creation and What it Measures,” in Hop Flavor and Aroma: Proceedings of the 1st International Brewers Symposium, ed. Thomas H. Shellhammer, Master Brewers Association of the Americas, 2009.
  • M. Verzele and D. De Keukeleire, Chemistry and Analysis of Hop and Beer Bitter Acids.  Developments in Food Science 27.  Elsevier, 1991.

 

The Production of Oxidized Alpha Acids at Hop-Stand Temperatures

Abstract
The IBU combines the concentration of isomerized alpha acids (IAAs) and the concentration of “auxiliary bittering compounds” (ABCs) in beer into a single measure of approximate bitterness.  While IAAs contribute the most to the IBU in typical beers, ABCs play a significant role and may have contributions greater than IAAs in very late-hopped beers.  The auxiliary bittering compounds are composed of polyphenols, oxidized alpha acids, and oxidized beta acids.  Oxidized alpha acids are produced as the hops age, but they are also produced in fairly large quantities during the boil.  (There is evidence that the oxidized alpha acids produced during the boil are the second-greatest contributor to the IBU, after IAA.)  It is known that temperature has a large effect on how quickly alpha acids isomerize, but it is not clear what impact wort temperature has on the production of oxidized alpha acids.  This blog post estimates the concentration of oxidized alpha acids in finished beer from hops steeped at three temperatures: boiling (100°C or 212°F), 90°C (194°F), and 80°C (176°F).  The results, while not definitive, indicate that these different temperatures do not yield significant differences in the production of oxidized alpha acids.  Polyphenol levels in the beer samples were also measured in order to check previously-developed polyphenol models and provide supporting evidence that most of the ABCs are, as expected, probably coming from oxidized alpha acids and not from polyphenols.

1. Introduction
The IBU is a measure of the concentration of a number of different bitter compounds.  (To be more precise, the IBU is a measure of the absorbance of light at 275 nm through acidified beer.  A number of bitter compounds in beer absorb light at this frequency.  The greater the concentration of these compounds, the more light is absorbed, and the higher the IBU.)  In typical beers, the IBU value reflects mostly the concentration of isomerized alpha acids (IAAs) [Peacock, pp. 164-165], which are produced during the boil from alpha acids (AA).  The other bitter compounds, known as “auxiliary bittering compounds” (ABCs), or nonIAA, are polyphenols, oxidized alpha acids, and oxidized beta acids.  These compounds can be considered to be present in the wort soon after the hops addition [e.g. Dierckens and Verzele, p. 454; Askew, p. 18].

Alpha acids (without isomerization) “do not survive to any significant extent into beer” [e.g. Lewis and Young, p. 259] and are not bitter [Shellhammer, p. 169], but as they age and become oxidized, the resulting oxidized alpha acids (oAAs) are both soluble in wort and bitter [Algazzali, pp. 14-15, p. 19, p.45; Maye et al, p. 23; Hough et al., pp. 435-436; Hough et al., p. 439; Lewis and Young, p. 265].  Oxidized alpha acids are also produced during the boil [Parkin, p. 11, Algazzali, p. 17; Dierckens and Verzele, p. 454; Oliver p. 471].  A previous blog post has estimated that oxidized alpha acids (oAA) are the second-largest contributor to the IBU, after isomerized alpha acids, and that a typical beer may have equal contributions of IAA and oAA after about 10 minutes of boiling hops in wort.  In beers brewed with large additions of hops at flameout, the IBU may be a measurement of mostly oxidized alpha acids.

While the impact of wort temperature on the rate of isomerization is well known [Malowicki, p. 27], the impact of temperature on the production of oxidized alpha acids is not known.  (At room temperature, dry hopping will contribute oxidized alpha acids to the finished beer [Parkin, p. 30; Maye, p. 25], but it seems unlikely that there is much production of oAA.  Instead, it is more likely that during dry hopping (most of) the oAA already present in the hops (coming from oxidation during storage) dissolve into the beer [Maye, p. 25].)  If boiling transforms x% of the available alpha acids to oxidized alpha acids in the finished beer, then does steeping hops at 80°C (176°F) transform only 0.80 × x% of the alpha acids?  Or, more generally, how do temperatures typically encountered in hop stands affect the oxidization of alpha acids, relative to oxidation at boiling? The purpose of this blog post is to answer this question.

When collecting data to answer this question, I also measured polyphenol concentrations as a way of testing the model of malt polyphenols proposed in the blog post The Contribution of Malt Polyphenols to the IBU and the model of hop polyphenols described in the blog post The Relative Contribution of Oxidized Alpha- and Beta-Acids to the IBU.  To the extent that the polyphenol models accurately predict polyphenol concentration, we can have confidence in the models’ estimate of the contribution of polyphenols to the IBU, and support (or contradict) the claim that oxidized alpha acids contribute much more to the IBU than other auxiliary bittering compounds.

2. The Concentration of Isomerized Alpha Acids in Beer
Mark Malowicki developed formulas to estimate the concentration of IAAs in the wort from the initial concentration of alpha acids [Malowicki, p. 27]:

k1(T) = 7.9×1011 e-11858/T [1]
k2(T) = 4.1×1012 e-12994/T [2]
[IAA]wort = [AA]0 × (k1(T)/(k2(T) − k1(T))) × (ek1(T)− ek2(T)t) [3]

where k1(T) and k2(T) are empirically-derived rate constants, T is the temperature in Kelvin (i.e. 373.15 K for boiling), t is the steep time (in minutes), e is the constant 2.71828, and [AA]0 is the initial concentration of alpha acids in the wort (in ppm).  This concentration of IAA in the wort, [IAA]wort, decreases as IAAs are lost to trub and krausen during the boil and fermentation.  The concentration of IAAs in beer ([IAA]beer) can then be expressed as the IAA concentration in wort multiplied by a loss scaling factor, scalingIAA:

[IAA]beer = [IAA]wort × scalingIAA [4]

3. The IBU Expressed as Concentrations of Bitter Compounds
Val Peacock [Peacock, p. 161] provides an equation to express the IBU as a combination of the concentration of IAAs and ABCs (also called nonIAA):

IBU = 5/7 × ([IAA]beer + [ABC]beer) [5]

where IBU is the IBU value of the beer, [IAA]beer is the concentration of isomerized alpha acids in the finished beer (in ppm, from Section 2), and [ABC]beer is the concentration of all other bittering compounds (also in ppm).

The concentration of ABCs in beer ([ABC]beer) can be expressed as the sum of the concentrations of the individual ABC components multiplied by appropriate scaling factors that relate each concentration to absorption at 275 nm:

[ABC]beer = [PPmalt]beer × scalePPmalt + [PPhops]beer × scalePPhops + [oAA]beer × scaleoAA + [oBA]beer × scaleoBA [6]

where [PPmalt]beer, [PPhops]beer, [oAA]beer, and [oBA]beer are the concentrations in the beer of malt polyphenols, hop polyphenols, oxidized alpha acids, and oxidized beta acids, respectively, and scalePPmalt, scalePPhops, scaleoAA, and scaleoBA are the scaling factors that relate concentration to absorption at 275 nm for these compounds.

Alternatively, we can express the concentration of ABCs in beer as the concentration of total hop particles added to the wort, multiplied by a single scaling factor that accounts for (a) the proportion of each ABC compound to total hop matter, (b) different absorption factors of these compounds, and (c) losses of each ABC to trub and during fermentation:

[ABC]beer = [hops]wort × scalingABC [7]

where [hops]wort is the concentration of hops added to the wort and scalingABC is the above-mentioned scaling factor.

We can estimate the scaling factors scalingIAA and scalingABC from equations [3], [4], [5], and [6] and measured IBUs of beer samples fermented from wort taken at different time points during the boil.  This technique is described in the blog post Estimating Isomerized Alpha Acids and nonIAA from Multiple IBU Measurements.

4. Experimental Overview
To evaluate the production of oxidized alpha acids at hop-stand temperatures, I brewed three batches of beer (A, B, and C) with identical wort, hops, and yeast, and varied only the temperature at which the hops steeped in the wort.  The total steep time was 40 minutes, and I took samples every 10 minutes.  I fermented these 12 samples into beer, and had the IBU values of the finished beer measured by Oregon BrewLab.

I then used the technique described in Estimating Isomerized Alpha Acids and nonIAA from Multiple IBU Measurements to model the concentrations and scaling factors of IAA and ABC that contribute to the measured IBU values.  In particular, the temperature T in Equations [1], [2], and [3] (above) was set to the steep temperature in order to account for the reduced rate of production of isomerized alpha acids at below-boiling temperatures.  Using estimates of malt and hop polyphenol concentrations and their contribution to the IBU (described in The Relative Contribution of Oxidized Alpha- and Beta-Acids to the IBU) and ignoring the contribution of oxidized beta acids (due to their negligible concentration in finished beer when using well-preserved hops), I estimated the contribution of oxidized alpha acids to the IBU in each batch.  These estimates were then examined for a relationship with wort temperature.

In addition, Oregon BrewLab measured the polyphenol concentrations at the 10-minute sample of all three batches and at the 40-minute sample of Batch A.  I computed the expected malt polyphenol concentration using the model developed in The Contribution of Malt Polyphenols to the IBU and the expected hop polyphenol concentration using the model in The Relative Contribution of Oxidized Alpha- and Beta-Acids to the IBU, and compared the predicted with measured polyphenol values.

5. Experimental Methods
Each batch of wort was prepared from 2.53 lbs (1.147 kg) of Briess Pilsen Light Dried Malt Extract and 3.35 G (12.68 liters) of 120°F (49°C) low-alkalinity water, yielding 3.49 G (13.21 liters) of room-temperature wort.  This wort sat for 90 minutes to let the pH stabilize.  The pH was then adjusted to about 5.30 (at room temperature) using phosphoric acid.  The measured pre-boil specific gravity was 1.032 for all three batches.  The wort was boiled for 5 minutes before adding hops, in order to reduce the foam associated with the start of the boil.  A 12-oz (0.35 l) sample of wort was taken after this 5-minute period to measure specific gravity and pH at around the time of the hop addition.

Just before adding hops, the temperature was reduced with the use of a wort chiller to the target steep temperature.  For Batch A, the target temperature was boiling (100°C, 212°F) and no temperature reduction was made.  For Batch B, the target temperature was 90°C (194°F).  For Batch C, the target temperature was 80°C (176°F).  This target was held as closely as possible throughout the hop steeping time.

I used 0.868 oz (24.6 grams) of Amarillo hops in this experiment with a package AA rating of 8.8%.  These hops were harvested in Fall 2019 for the experiment in January 2020.  The hops were analyzed by AAR Lab shortly after I received them, and they showed an alpha-acid (AA) rating of 9.56% and a beta-acid (BA) rating of 5.84%, with a hop storage index (HSI) of 0.272.  To estimate the alpha-acid content at the time of brewing, I used the Garetz formula for estimating alpha-acid decay [Garetz] to obtain a decay factor of 0.96 and an alpha-acid rating at the time of the experiment of 9.21%.

After adding the hops, 16-oz (0.473 l) samples were taken every 10 minutes and quickly cooled in an aluminum cup and ice bath.  The kettle was covered during the boil (or hop stand) to minimize evaporation and the resulting changes in specific gravity.  Each sample was transferred to a sanitized quart (liter) container after it was cooled to 75°F (24°C).  The wort in each container was aerated for 1 minute by vigorous shaking, and 0.008 oz (0.24 grams) of Safale US-05 yeast (age 11 months) was pitched to target 750,000 cells per ml and degree Plato.  At the end of the 40-minute boil (or hop stand), another sample was taken for measuring specific gravity and pH.

Each sample fermented for 10 days (with a small opening to vent CO2).  The krausen was left to deposit on the sides of the vessel during fermentation.  I removed the krausen deposits one day before taking samples for IBU and polyphenol analysis by Oregon BrewLab.

6. Results
Unfortunately, I kept the hops in Batch B at boiling for the first 3 minutes of the boil, and only then decreased the heat to the target temperature.  To correct for this, the models below use instantaneous temperatures and integrate IAA levels over time for Batch B, with a temperature of boiling for the first 3 minutes and the target of 90°C (194°F) after that, and so the effect of this mistake should be accounted for in the models.

The measured IBU values are plotted in Figure 1 with solid lines.  The polyphenol concentrations are listed in Table 1.

IBU_measured

Figure 1. Measured IBU values at steep times of 10, 20, 30, and 40 minutes (horizontal axis) and at steep temperatures 100°C (212°F) (red line), 90°C (192°F) (blue line), and 80°C (176°F) green line.

6. Analysis
6.1 Model #1: Batch-Specific IBU Analysis
The first analysis (Model #1) used the technique described in Estimating Isomerized Alpha Acids and nonIAA from Multiple IBU Measurements to estimate scaling factors for IAA and ABC and use these scaling factors to model IBU values.  We can identify the portion of the IBU value that comes from oxidized alpha acids by subtracting estimates of the malt and hop polyphenol IBU contributions and the estimate of the IAA contribution from the model IBU value.  The results of this analysis are IAA scaling factors of 0.40, 0.49, and 0.59 for Batches A, B, and C, respectively, and a ABC scaling factors of 0.0048, 0.0047, and 0.0044 for Batches A, B, and C, respectively.   The estimated oAA levels (expressed as the oAA contribution to the IBU) are 6.8, 6.7, and 6.2 IBUs for Batches A, B, and C, respectively.  The RMS error over all values is 0.40 IBUs.  The estimated IBU levels from Model #1 are plotted in Figure 2 with solid lines (red for Batch A, blue for Batch B, and green for Batch C).  The estimated oAA levels decrease slightly with decreasing temperature.  However, the IAA scaling values increase as the temperature decreases, and there is no clear reason for IAA scaling values to increase in this way.  This suggests that the model is overfitting to the data, and that this trend is an artifact of the data and analysis technique.

IBU_model1

Figure 2. IBU values from Model #1 at temperatures 100°C (212°F) (red line), 90°C (192°F) (blue line), and 80°C (176°F) green line.  The measured IBU values (from Figure 1) are plotted with gray markers and dashed lines for reference.

6.2 Model #2: IBU Analysis with Constant IAA Scaling
The results from analyzing each batch independently (Model #1) showed an unexpected increase in the IAA scaling factors as temperature decreases.  All of these batches should, in theory, have the same scaling value for IAA; the kettle temperature should not influence the loss of isomerized alpha acids.  I therefore repeated the estimation of IAA and ABC scaling factors, but constrained the value of the IAA scaling factor to be the same for all three batches.  This analysis is called Model #2.  The results of this analysis are an IAA scaling factor of 0.43 and ABC scaling factors of 0.0041, 0.0055, and 0.0051 for Batches A, B, and C, respectively.  The estimated oAA levels (expressed as the oAA contribution to the IBU) are 5.8, 7.8, and 7.2 IBUs for Batches A, B, and C, respectively.  The RMS error over all values is 0.60 IBUs.  The trend that we are looking for, where oAA levels are constant or decrease as the temperature decreases, is not apparent.  The estimated IBU levels from Model #2 are plotted in Figure 3.

IBU_model2

Figure 3. IBU values from Model #2 at temperatures 100°C (212°F) (red line), 90°C (192°F) (blue line), and 80°C (176°F) green line.  The measured IBU values (from Figure 1) are plotted with gray markers and dashed lines for reference.

6.3 Model #3: IBU Analysis with Constant IAA and ABC Scaling
The results from enforcing a constant IAA scaling value across all three batches show no clear trend in oAA values with temperature.  If the oxidized alpha-acid levels do not change significantly with temperature and the observed differences are all caused by experimental error, then we can constrain both IAA scaling and ABC scaling to be the same for all three batches, and evaluate if the resulting model error might be explained by experimental errors.  This analysis, called Model #3, resulted in an IAA scaling factor of 0.40 and a ABC scaling factor of 0.0053, with an RMS error of 0.88 IBUs (about double that of Model #1 with no constraints).  The estimated oAA levels (expressed as the oAA contribution to the IBU) are 7.5 IBUs for all batches. This constraint causes the model values for Batch A to be somewhat higher than observed values, and the model values for Batch B to be a bit lower than observed values at higher steep times. The estimated IBU levels from Model #3 are plotted in Figure 4.

IBU_model3

Figure 4. IBU values from Model #3 at temperatures 100°C (212°F) (red line), 90°C (192°F) (blue line), and 80°C (176°F) green line.  The measured IBU values (from Figure 1) are plotted with gray markers and dashed lines for reference.

Can we explain this measured error (0.88 IBUs, compared with 0.40 IBUs for the unconstrained model) with plausible experimental errors?  If we hypothesize that the differences are because the steep temperatures did not reach their targets, then it would take a steep temperature of 93°C (199.4°F) in Batch B (instead of the target 90°C/194°F) and a steep temperature of 83°C (181.4°F) in Batch C (instead of the target 80°C/176°F) to reduce the error to 0.44 IBUs.  It seems possible that the temperature in the kettle was not uniform, but possibly higher at the bottom of the kettle (near the heat source) and lower at the top of the kettle (where I measured temperature).  (It is also very likely that I did not reach exactly the target temperature over the entire duration of steeping, even after accounting for the mistake in Batch B.)  Such effects might conceivably lead to a 3°C (5.4°F) difference between the average actual temperature and the measured temperature, although my gut feeling is that this is stretching the bounds of plausibility.  If we hypothesize that the alpha-acid ratings varied between batches, then Batch A would have to be 8% lower, Batch B 7% higher, and Batch C 8% higher than expected in order to reduce the error to 0.50 IBUs.  Alpha-acid ratings can vary 15% to 20% within the same bale of hops [Verzele and DeKeukeleire, p. 331], and it is worth noting that the measured AA rating of 9.56% is 9 percent higher than the package rating of 8.8%.  So, it is also conceivable that the actual AA ratings in each batch varied by up to 8% from the expected value, but once again my gut feeling is that this is pushing the bounds of plausibility.  If we have a combination of smaller differences in both temperature and AA rating (namely that Batch A has 4% lower AA, Batch B has a temperature of 91.5°C (196.7°F) and 3.5% higher AA, and Batch C has a temperature of 81.5°C (178.7°F) and 4% higher AA) then the error is 0.46 IBUs.  Such errors seem plausible, but they are of course a hypothetical “post-mortem” explanation of the data.

6.4 Summary of IBU Analysis
A pattern of decreasing oAA levels with decreasing temperature is slight in the first model and does not exist in the other two models.  There is also no easy explanation for the increase in IAA scaling factors with decreasing temperature in the unconstrained model (Model #1).  If the model is adjusted to account for several small potential experimental errors, both IAA scaling and oAA levels can be held constant and result in a low overall error.  Therefore, the data suggest, but do not prove, that the production of oxidized alpha acids is not greatly influenced by steep temperature.  It is estimated that in this experiment, oxidized alpha acids contributed about 7 of the measured IBUs, regardless of the model, steep time, or steep temperature.

6.5 Analysis of Polyphenol Concentrations
In order to test the model of polyphenols developed in a previous blog post, Oregon BrewLab measured the polyphenol concentrations of four conditions: the 10-minute sample for Batches A, B, and C, and the 40-minute sample for Batch A.  Results are listed in Table 1; these values are the sum of both malt and hop polyphenols.

Sample Measured Polyphenol Concentration (ppm) Modeled Polyphenol Concentration (ppm)
Batch A, 10 minutes 91 95.2
Batch B, 10 minutes 92 95.2
Batch C, 10 minutes 92 95.2
Batch A, 40 minutes 107 106.7

Table 1.  Measured and modeled polyphenol levels of four samples in this experiment.

We can use the model of malt polyphenols with the model of hop polyphenols described in Section 4 of The Relative Contribution of Oxidized Alpha- and Beta-Acids to the IBU to estimate the total polyphenol concentration.  For using the model of malt polyphenols at steep time 10, we have a boil time of 10 minutes, a specific gravity of 1.0342 and a pH of 5.31.  For the model of hop polyphenols, we have 24.60 grams (0.868 oz) of hops added to 12.306 liters (3.25 gallons) of wort.  These models predict 84.0 ppm of malt polyphenols  and 11.2 ppm of hop polyphenols at 10 minutes, for a total of 95.2 ppm.  Since this model does not depend on wort temperature, it predicts the same value for each batch at the 10-minute sample time.  Changing the boil time to 40 minutes yields 95.5 ppm of malt polyphenols and the same 11.2 ppm of hop polyphenols, for a total of 106.7 ppm.

The model values of 95.2 ppm for all batches at 10 minutes and 106.7 ppm at 40 minutes are in good agreement with the measured values in Table 1.  These results provide some confidence in how well these models predict malt and hop polyphenol levels.

9. Conclusion
While not conclusive, the data from this experiment indicate that hop steeping temperatures from boiling to as low as 80°C (176°F) do not result in significant differences in the production of oxidized alpha acids.  Also, the measured polyphenol concentrations correspond well with the models of malt and hop polyphenols proposed in previous blog posts.

It is estimated that in this experiment, the oxidized alpha acids produced during the boil contribute more to the IBU than isomerized alpha acids up to about a 15-minute steep time.  At the 10-minute steep time and boiling, it is estimated that the 14.9 measured IBUs reflect 5.6 IBUs from isomerized alpha acids, 7.8 IBUs from oxidized alpha acids, 1.3 IBUs from malt polyphenols, and 0.2 IBUs from hop polyphenols.  At the 40-minute steep time and boiling, it is estimated that the 29.1 measured IBUs reflect 19.8 IBUs from IAA, 7.8 IBUs from oAA, and 1.5 IBUs from polyphenols.

10. Acknowledgment
I would like to sincerely thank Dana Garves at Oregon BrewLab for her attention to quality and detail that is reflected in the IBU and polyphenol measurements presented here and in previous posts.

References

  • V. A. Algazzali, The Bitterness Intensity of Oxidized Hop Acids: Humulinones and Hulupones, Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2014.
  • J. Dierckens and M. Verzele, “Oxidation Products of Humulone and Their Stereoisomerism,” in Journal of the Institute of Brewing, vol. 75, pp. 453-456, 1969.
  • M. Garetz, “Hop Storage: How to Get – and Keep – Your Hops’ Optimum Value” in Brewing Techniques, January/February 1994, hosted on morebeer.com.
  • J. S. Hough, D. E. Briggs, R. Stevens, and T. W. Young, Malting and Brewing Science.  Volume 2: Hopped Wort and Beer.  Springer-Science+Business Media, B. V., 2nd edition, 1982.
  • M. J. Lewis and T. W. Young, Brewing. Springer Science+Business Media, 2nd edition, 2001.
  • M. G. Malowicki, Hop Bitter Acid Isomerization and Degradation Kinetics in a Model Wort-Boiling System, Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2005.
  • J. P. Maye, R. Smith, and J. Leker, “Humulinone Formation in Hops and Hop Pellets and Its Implications for Dry Hopped Beers”, in MBAA Technical Quarterly, vol. 51, no. 1, pp. 23-27, 2016.
  • G. Oliver, The Oxford Companion to Beer, Oxford University Press, 2011.
  • E. J. Parkin, The Influence of Polyphenols and Humulinones on Bitterness in Dry-Hopped Beer, Master of Science thesis (advisor: T. H. Shellhammer), Oregon State University, 2014.
  • V. Peacock, “The International Bitterness Unit, its Creation and What it Measures,” in Hop Flavor and Aroma: Proceedings of the 1st International Brewers Symposium, ed. Thomas H. Shellhammer, Master Brewers Association of the Americas, 2009.
  • T. H. Shellhammer, “Hop Components and Their Impact on the Bitterness Quality of Beer,” in Hop Flavor and Aroma: Proceedings of the 1st International Brewers Symposium, ed. Thomas H. Shellhammer, Master Brewers Association of the Americas, 2009.
  • M. Verzele and D. De Keukeleire, Chemistry and Analysis of Hop and Beer Bitter Acids.  Developments in Food Science 27.  Elsevier, 1991.

The Relative Contribution of Oxidized Alpha- and Beta-Acids to the IBU

Abstract
The IBU combines the concentration of isomerized alpha acids (IAAs) and the concentration of “auxiliary bittering compounds” (ABCs) in beer into a single measure of approximate bitterness.  While IAAs contribute the most to the IBU in typical beers, ABCs play a significant role and may have concentrations greater than IAAs in very late-hopped beers.  The auxiliary bittering compounds are composed of polyphenols, oxidized alpha acids, and oxidized beta acids.  This blog post estimates the relative contribution of oxidized alpha acids and oxidized beta acids to the IBU, using data from beer brewed with four varieties of hops.  The data indicate that when using well-preserved hops, the concentration of oxidized alpha acids in beer is much greater than the concentration of oxidized beta acids. It is estimated that the auxiliary bittering compounds in most beers made with well-preserved hops are composed primarily of oxidized alpha acids, with much lower contributions from malt polyphenols, hop polyphenols, and finally oxidized beta acids. When hops have been stored for long periods with exposure to oxygen, however, the oxidized beta acids may contribute significantly to the IBU.

1. Introduction
The IBU is a measure of the concentration of a number of different bitter compounds.  (To be more precise, the IBU is a measure of the absorbance of light at 275 nm through acidified beer.  A number of bitter compounds in beer absorb light at this frequency.  The greater the concentration of these compounds, the more light is absorbed, and the higher the IBU.)  In typical beers, the IBU value represents mostly the concentration of isomerized alpha acids (IAAs) [Peacock, pp. 164-165], which are produced during the boil from alpha acids (AA).  The other bitter compounds, known as “auxiliary bittering compounds” (ABCs), or nonIAA, are polyphenols, oxidized alpha acids, and oxidized beta acids.  These compounds can be considered to be present in the wort soon after the hops addition [e.g. Dierckens and Verzele, p. 454; Askew, p. 18].  (Alpha acids, which are present in wort [Hough et al., p. 491] and also absorb light at 275 nm [Hough et al., p. 434, p. 491], are not bitter [Shellhammer, p. 169] but also not typically present in the fermented beer [e.g. Lewis and Young, p. 259, Hough et al., p. 491].  Therefore, they do not contribute to the measured IBU value of beer except when dry hopping.)

While “typical” beers (if there is such a thing anymore) have a much greater concentration of IAAs compared to ABCs, beers produced with a large amount of hops added very late in (or after) the boil can have ABC concentrations greater than IAAs.  In modeling IBUs and getting a better understanding of the bitterness qualities of late-hopped beers, it is beneficial to have an estimate of the relative concentrations of the compounds that are collectively referred to as ABCs.  While the contribution of malt and hop polyphenols to the IBU is generally known (as discussed in Section 4), a quantitative analysis of the relative contribution of oxidized alpha- and beta-acids is not easily found in the literature.

This blog post estimates the relative concentrations of oxidized alpha- and beta-acids in beer by analysis of IBU values.  These IBU values were obtained by ASBC Beer-23A analysis of samples taken at different points in the boil from four beers brewed with different varieties of hops (and different alpha-acid and beta-acid ratings).

2. The Concentration of Isomerized Alpha Acids in Beer
Mark Malowicki developed formulas to estimate the concentration of IAAs in the wort from the initial concentration of alpha acids [Malowicki, p. 27]:

k1(T) = 7.9×1011 e-11858/T [1]
k2(T) = 4.1×1012 e-12994/T [2]
[IAA]wort = [AA]0 × (k1(T)/(k2(T) − k1(T))) × (ek1(T)− ek2(T)t) [3]

where k1(T) and k2(T) are empirically-derived rate constants, T is the temperature in Kelvin (i.e. 373.15 K for boiling), t is the steep time (in minutes), e is the constant 2.71828, and [AA]0 is the initial concentration of alpha acids in the wort (in ppm).  This concentration of IAA in the wort, [IAA]wort, decreases as IAAs are lost to trub and krausen during the boil and fermentation.  The concentration of IAAs in beer ([IAA]beer) can then be expressed as the IAA concentration in wort multiplied by a loss scaling factor, scalingIAA:

[IAA]beer = [IAA]wort × scalingIAA [4]

3. The IBU Expressed as Concentrations of Bitter Compounds
Val Peacock [Peacock, p. 161] provides an equation to express the IBU as a combination of the concentration of IAAs and ABCs (also called nonIAA):

IBU = 5/7 × ([IAA]beer + [ABC]beer) [5]

where IBU is the IBU value of the beer, [IAA]beer is the concentration of isomerized alpha acids in the finished beer (in ppm, from Section 2), and [ABC]beer is the concentration of all other bittering compounds (also in ppm).

The concentration of ABCs in beer ([ABC]beer) can be expressed as the sum of the concentrations of the individual ABC compounds multiplied by appropriate scaling factors that relate each concentration to absorption at 275 nm:

[ABC]beer = [PPmalt]beer × scalePPmalt + [PPhops]beer × scalePPhops + [oAA]beer × scaleoAA + [oBA]beer × scaleoBA [6]

where [PPmalt]beer, [PPhops]beer, [oAA]beer, and [oBA]beer are the concentrations in the beer of malt polyphenols, hop polyphenols, oxidized alpha acids, and oxidized beta acids, respectively, and scalePPmalt, scalePPhops, scaleoAA, and scaleoBA are the scaling factors that relate concentration to absorption at 275 nm for these compounds.

Alternatively, we can express the concentration of ABCs in beer as the concentration of total hop particles added to the wort, multiplied by a single scaling factor that accounts for (a) the proportion of each ABC compound to total hop matter, (b) different absorption factors of these compounds, and (c) losses of each ABC to trub and during fermentation:

[ABC]beer = [hops]wort × scalingABC [7]

where [hops]wort is the concentration of hops added to the wort and scalingABC is the above-mentioned scaling factor.

We can estimate the scaling factors scalingIAA and scalingABC from these equations and measured IBU values of beer samples fermented from wort taken at different time points during the boil.  This technique is described in the blog post Estimating Isomerized Alpha Acids and nonIAA from Multiple IBU Measurements.

4. The Concentration of Polyphenols in Beer
Polyphenols in beer come from both malt and hops. This section describes how to estimate their concentration in beer and their impact on IBUs.

4.1 Malt Polyphenols
According to Tom Shellhammer, IBUs are in the range of 1 to 3 for unhopped beer [Shellhammer, p. 177].  In one experiment, I brewed several unhopped beers and developed a formula for predicting IBUs that come from malt polyphenols:

IBUPPmalt = ((OG − 1.0) × 1000) × 0.019) × ((1.734 × (5.75 − pH) / 0.7) + 1.0) [8]

where IBUPPmalt is the IBU value obtained from malt polyphenols, OG is the original gravity of the beer, and pH is the post-boil pH.  This formula predicts 2.4 IBUs from an OG of 1.050 and post-boil pH of 5.15, which is generally in line with Shellhammer’s statement.  We can convert this formula from a prediction of IBUs to a prediction of scaled malt polyphenol concentrations if we multiply by 7/5 (from Equations [5] and [6]):

[PPmalt]beer × scalePPmalt = 7/5 × IBUPPmalt [9]

where [PPmalt]beer is the concentration of malt polyphenols in the finished beer (in ppm) and scalePPmalt is the scaling factor for light absorption at 275 nm.  This scaling factor is dependent on both pH and boil time, but we often don’t need to determine the separate values of [PPmalt]beer and scalePPmalt; knowing their product, as specified by 7/5 × IBUPPmalt, is usually sufficient.  (The implication of a non-constant scaling factor is that not all of the malt polyphenols contribute to the IBU; those that do contribute are affected by pH and time.)

4.2 Hop Polyphenols
Hop polyphenol levels are often reported in the range from 2% to 6% of the weight of the hops [Shellhammer, p. 169; Hough et al., p. 422; Algazzali, p. 5; Verzele and De Keukeleire, p. 9].  After having been added to the wort, polyphenols are removed “extensively by precipitation with proteins during wort boiling”; 80% of hop flavanols are removed in the trub when boiling hopped wort [McLaughlin, p. 7]. Yeast has only a minor effect on polyphenol concentrations during fermentation [Leiper and Miedl, p. 136; Alexander], but losses to trub and krausen may be similar to those of malt polyphenols, estimated at 30%.  Finally, we need a scaling factor, scalePPhops, to use with the concentration of hop polyphenols in Equation [6].  According to Ellen Parkin, “an increase of 100 mg/L of polyphenols was predicted to increase the [IBU] value by 2.2” [Parkin, p. 28], so that 1 ppm of hop polyphenols should increase the IBU by 0.022.  We can multiply this by 7/5 to convert from an IBU value to a concentration scaling factor (using Equations [5] and [6]).

From this, we can construct a model of the concentration of hop polyphenols in beer and the associated scaling factor, with an initial level of polyphenols at 4% of the weight of the hops, a loss factor (or combined solubility and loss factor) for polyphenols during the boil estimated at 0.20 (corresponding to 80% loss), and a loss factor of 0.70 (corresponding to 30% loss) during fermentation:

[PPhops]beer = 0.04 × 0.20 × 0.70 × W × 1000 / V [10]
scalePPhops = 7/5 × 0.022 = 0.0308 [11]

where [PPhops]beer is the concentration of hop polyphenols in the beer (in ppm), W is the weight of hops added (in grams), V is the final wort volume (in liters), and scalePPhops is the scaling factor for light absorption at 275 nm.

4.3 Relative Contributions of Malt and Hop Polyphenols
The majority of polyphenols in beer come from malt.  According to Steve Alexander, “roughly 75% of total beer phenolics come from malt, and the remaining 25% come from hops” [Alexander].  Denis De Keukeleire states that “hops may contribute up to about one third of the total polyphenols in beer” [De Keukeleire, p. 109].  According to Cynthia Almaguer et al., “about 20–30% of the polyphenols found in the wort come from the hop material” [Almaguer, p. 300].

5. Oxidized Alpha- and Beta-Acids in Beer
Alpha acids (before isomerization) “do not survive to any significant extent into beer” [e.g. Lewis and Young, p. 259] and are not bitter [Shellhammer, p. 169], but as they age and become oxidized, the resulting oxidized alpha acids (oAAs) are both soluble in wort and bitter [Algazzali, pp. 14-15, p. 19, p.45; Maye et al, p. 23; Hough et al., pp. 435-436; Hough et al., p. 439; Lewis and Young, p. 265].  Oxidized alpha acids are also produced during the boil [Parkin, p. 11, Algazzali, p. 17; Dierckens and Verzele, p. 454; Oliver p. 471], but the amount of oxidized alpha acids produced in this way is unclear.

Oxidized beta acids (oBAs) are also soluble [Algazzali, p. 16] and may be produced and contribute to bitterness in the same way as oxidized alpha acids [Malowicki, p. 2; Peacock, p. 157; Fix, p. 36; Lewis and Young, p. 265; Hall, p. 55; Oliver, p. 132; Oliver, p. 470; Parkin, p. 11; Algazzali, p. 17; Hough et al., p. 489]. Val Peacock says that “the beta oxidation products contribute to analytical IBUs” [Peacock, p. 161] and that “much of the nonIAA material originates from the oxidation of the beta acids as hops age” [Peacock, p. 164].  Oxidized beta acids may also be produced during the boil [Spetsig, p. 350].  Stevens and Wright provide an estimate of the amount of oxidized beta acids produced during the boil, noting that “as much as 10% of the beta acid had been converted into cohulupone” [Stevens and Wright, p. 500].  If 10% of the beta acids are oxidized during the boil, and if oxidized beta acids contribute to analytical IBUs, then oxidized beta acids can contribute to a significant portion of ABCs even when using fresh hops. If beta acids are not oxidized during the boil, then the contribution of oxidized beta acids may depend on how well the hops have been stored.  In this case, poorly-preserved hops may have a greater contribution of oxidized beta acids to the IBU than well-preserved hops.  Almaguer notes that “further oxidation of the [oxidized beta acids] will result in the non-bitter hulupinic acid” [Almaguer, p. 295].  It is not clear how quickly the oxidized beta acids are converted into hulupinic acid.  This process might occur very quickly, in which case even oxidized beta acids from poorly-stored hops will not contribute to the IBU.  Or, this transformation might occur over weeks or months, in which case oxidized beta acids may contribute significantly to the IBU.

In addition to the concentrations of these products in beer, [oAA]beer and [oBA]beer, we’re also concerned with how their concentrations relate to IBU measurement via the scaling factors scaleoAA and scaleoBA.  According to the data in Maye et al. (Figure 7), the scaling factor for scaleoAA is 0.0130 / 0.0142 = 0.9155 [Maye, p. 25].   According to Hough et al., “[oxidized beta acids] exhibit 80-90% of the absorption of the iso-alpha-acids at [275 nm in acid solution]” [Hough et al., p. 491].  Therefore, the oxidized beta-acid scaling factor is about 0.85.

scaleoAA = 0.0130 / 0.0142 = 0.9155 [12]
scaleoBA = 0.85 [13]

Although oxidized alpha- and beta-acids are both bitter and soluble, potentially contributing to the IBU measurement, the literature is not clear on the relative proportion of oxidized alpha acids to oxidized beta acids produced during the boil and ending up in the finished beer.

6. Experimental Overview
To evaluate the relative proportion of oxidized alpha- and beta-acids in beer, I designed two new experiments and took IBU data from three earlier experiments. The new experiments used Teamaker hops, known for having almost no alpha acids and a very high concentration of beta acids.

The three other experiments are described in the blog posts The Impact of Krausen Loss on IBUs, The Effect of pH on Utilization and IBUs, and Hop Cones vs. Pellets: IBU Differences.  I took data from Condition B of the Krausen Loss experiment, Condition A of the Effect of pH experiment, and Condition A of the Cones vs. Pellets experiment because those conditions were most similar to the new experiment with the exception of hop variety.  The primary difference between the different sets of data was in the variety of hops used, with different alpha- and beta-acid ratings, and in the storage conditions of the Teamaker hops.

7. Experimental Details and Results
7.1 New Experiment #1 (Experiment #1)
The first new experiment used well-preserved Teamaker hops.  Wort was prepared from 4.13 lbs (1.87 kg) of Briess Pilsen Light Dried Malt Extract and 3.22 G (12.20 liters) of 120°F (49°C) low-alkalinity water, yielding 3.48 G (13.17 liters) of room-temperature wort.  This wort sat for 90 minutes to let the pH stabilize.  The measured pre-boil specific gravity was 1.054.  The wort was boiled for 5 minutes before adding hops in order to reduce the foam associated with the start of the boil.

I used 2.01 oz (57.0 grams) of Teamaker hops in this experiment.  The hops were analyzed by AAR Lab and showed an alpha-acid (AA) rating of 0.41% and a beta-acid (BA) rating of 11.93%, in line with expectations.  (I had harvested and dried these hops four weeks earlier and stored them in a vacuum-sealed bag in my freezer.  The resins were a deep orange color, in contrast with the normal bright yellow.  The AAR results also showed 13% moisture and a hop storage index (HSI) of 0.188.)

When the hops were added to the kettle (defined as time t = 0), the (temperature-corrected) specific gravity was 1.0565 and the pH was 5.74.  The estimated volume at the time when hops were added was 3.36 G (12.71 liters), estimated from the initial volume and gravity and the measured gravity at time 0.

After adding the hops, 15-oz (0.44 l) samples were periodically taken from the boiling wort and quickly cooled in an aluminum cup and ice bath.  Samples were taken after the hops had been steeping for 5, 10, 20, 40, and 60 minutes.  The kettle was covered during the boil to minimize evaporation and the resulting changes in specific gravity.  Once they reached 75°F (24°C),  the cooled samples were transferred to sanitized quart (liter) containers.  The wort in each container was aerated for 1 minute by vigorous shaking, and 0.011 oz (0.31 grams) of Safale US-05 yeast (age 7 months) was pitched to target 750,000 cells per ml and degree Plato.  At the end of the 60-minute boil, the specific gravity was 1.0577 and the pH was 5.69.

Each sample fermented for 8 days (with a small opening to vent CO2).  The krausen was left to deposit on the sides of the vessel during fermentation.  After a week the krausen was more “billowy” than normal, still covering the beer.  I removed this krausen one day before taking samples for IBU analysis by Oregon BrewLab.

The measured IBU values at 5, 10, 20, 40, and 60 minutes were 3.3, 3.6, 3.8, 3.8, and 4.0, respectively.  These values are plotted with a solid red line in Figure 1.

7.2 Results from Experiment on Krausen Loss (Experiment #2)
The full details of the experiment on krausen loss are given in that blog post.  In summary, for Condition B, the gravity when the hops were added (t = 0) was 1.037 and the estimated volume was 8.38 G (31.72 liters).  I added 1.88 oz (53.31 grams) of Comet hops to the wort with an alpha-acid rating of 9.7% and a beta-acid rating of 3.7%, for an initial alpha-acid concentration of about 160 ppm.  The gravity at the end of the boil was 1.039 and the estimated volume was 8.06 G (30.49 liters).  The measured IBU values of the resulting beer are plotted with a solid green line in Figure 1.

7.3 Results from Experiment on Impact of pH on Utilization and IBUs (Experiment #3)
The full details of the experiment on the effects of pH on IBUs are given in that blog post.  In summary, for Condition A, the gravity when the hops were added (t = 0) was 1.038 and the estimated volume was 4.25 G (16.09 liters).  I added 0.65 oz (18.28 grams) of Citra hops to the wort with an alpha-acid rating of 14.2% and a beta-acid rating of 3.35%, for an initial alpha-acid concentration of about 160 ppm.  The gravity at the end of the boil was 1.039 and the estimated volume was 4.08 G (15.43 liters).  The measured IBU values of the resulting beer are plotted with a solid blue line in Figure 1.

7.4 Results from Experiment on Cones and Pellets (Experiment #4)
The full details of the experiment on the differences between hop cones and pellets are given in the blog post Hop Cones vs. Pellets: IBU Differences.  In summary, for Condition A, the gravity when the hops were added (t = 0) was 1.039 and the estimated volume was 8.28 G (31.36 liters).  I added 3.72 oz (105.57 grams) of Willamette hops to the wort with an alpha-acid rating of 5.0% and a beta-acid rating of about 3.4%, for an initial alpha-acid concentration of about 170 ppm.  The gravity at the end of the boil was 1.039 and the estimated volume was 8.16 G (30.88 liters).  The measured IBU values of the resulting beer are plotted with a solid orange line in Figure 1.

oAAandoBa-measuredIBUsAndModel

Figure 1. Measured IBUs (solid lines) and model IBUs (dotted lines) from the four experiments in this blog post. Experiment #1 (red line) used 57.0 g of Teamaker hops with an alpha-acid rating of 0.4%. Experiment #2 (green line) used 53.3 g of Comet hops with an alpha-acid rating of 9.7%. Experiment #3 (blue line) used 18.3 g of Citra hops with an alpha-acid rating of 14.2%.  Experiment #4 (orange line) used 105.6 g of Willamette hops with an alpha-acid rating of 5.0%.

7.5 New Experiment #2 (Experiment #5)
The second new experiment had two conditions: (A) one condition using Teamaker hops stored in oxygen-barrier packaging in a freezer for six months (well-preserved hops), and (B) one condition using the same harvest of Teamaker hops stored with exposure to oxygen and at room temperature for six months (poorly-preserved hops).

Wort for each condition was prepared from 3.02 lbs (1.37 kg) of Briess Pilsen Light Dried Malt Extract and 3.31 G (12.53 liters) of 120°F (49°C) low-alkalinity water, yielding 3.50 G (13.25 liters) of room-temperature wort. This wort sat for 90 minutes to let the pH stabilize. The measured pre-boil specific gravity was 1.037. The wort was boiled for 5 minutes before adding hops in order to reduce the foam associated with the start of the boil.

I used 2.0 oz (56.7 grams) of Teamaker hops in each condition. The hops were analyzed by AAR Lab within one week of the experiment and showed an alpha-acid (AA) rating of 0.64% and a beta-acid (BA) rating of 10.92% for the well-preserved hops, and an AA rating of 0.57% and a BA rating of 3.61% for the poorly-preserved hops. (The AAR results also showed 9.8% moisture and a hop storage index (HSI) of 0.291 for the well-preserved hops, and 7.5% moisture and an HSI of 1.050 for the poorly-preserved hops.)

When the hops were added to the kettle (defined as time t = 0), the specific gravity was 1.041 and the pH was 5.87. The estimated volume at the time when hops were added was 3.21 G (12.15 liters).

After adding the hops, 15-oz (0.44 l) samples were periodically taken from the boiling wort and quickly cooled in an aluminum cup and ice bath. Samples were taken after the hops had been steeping for 10, 20, and 40 minutes. The kettle was covered during the boil to minimize evaporation and the resulting changes in specific gravity. The cooled samples were transferred to sanitized quart (liter) containers once they reached 75°F (24°C). The wort in each container was aerated for 1 minute by vigorous shaking, and 0.009 oz (0.25 grams) of Safale US-05 yeast (age 10 months) was pitched to target 750,000 cells per ml and degree Plato. At the end of the 60-minute boil, the specific gravity was 1.042 and the pH was about 5.78.

Each sample fermented for 10 days (with a small opening to vent CO2). Very little krausen accumulated on the sides of the vessel during fermentation. IBU values were measured by Oregon BrewLab.

The measured IBU values for the well-preserved hops at 10, 20, and 40 minutes were 4.2, 5.1, and 5.7, respectively. The measured IBU values for the poorly-preserved hops at 10, 20, and 40 minutes were 18.0, 22.1, and 25.9, respectively. These values are plotted with blue (well-preserved hops) and red (poorly-preserved hops) lines in Figure 2.

Figure 2. Measured IBU values from well-preserved Teamaker hops (blue line) and poorly-preserved Teamaker hops (red line).

8. Analysis
We now have all of the information we need to estimate the concentrations of oxidized alpha acids and oxidized beta acids in finished beer.  First, we will consider oxidized beta acids produced during the boil using well-preserved hops.  Then we will consider what happens when using poorly-preserved hops

8.1 Analysis Step 1
The first step is to estimate the concentrations of IAAs, malt polyphenols, and hop polyphenols in the beer and (using the associated scaling factors) subtract their effects from the measured IBUs, yielding the “remaining” IBUs that come from oxidized alpha- and beta-acids.  This step is repeated for all four experiments.  The rest of this section explains this step in more detail and provides the analysis results from each experiment.

To estimate the IAA concentration, we can use the technique described in Estimating Isomerized Alpha Acids and nonIAA from Multiple IBU Measurements to determine the values of scalingIAA and scalingABC for each experiment.  The results of fitting the data to this model are shown with the dashed red, green, blue, and orange lines in Figure 1 for Experiments #1, #2, #3, and #4, respectively.

We can combine Equations 4, 5, and 6 to be explicit about all of the contributions to the IBU, and highlight variables with “known” values in green and variables with “unknown” values in red:

IBU = 5/7 × ([IAA]wort × scalingIAA + ([PPmalt]beer × scalePPmalt) + [PPhops]beer × scalePPhops + [oAA]beer × scaleoAA + [oBA]beer × scaleoBA) [14]

where “known” variables can have their values measured, computed, or estimated from the experimental data and equations described above. We can define IBUremaining to represent the difference between the measured IBU and the other “known” portion of Equation [14] as follows:

IBUremaining = IBU − 5/7 × ([IAA]wort × scalingIAA + [PPmalt]beer × scalePPmalt + [PPhops]beer × scalePPhops) [15]

and note that, by rearranging terms from Equations [14] and [15], IBUremaining is the sum of the (scaled) contributions from oxidized alpha- and beta-acids:

IBUremaining = 5/7 × ([oAA]beer × scaleoAA + [oBA]beer × scaleoBA) [16]

We can define the IBUs that are derived from oxidized alpha- and beta-acids as IBUoAA and IBUoBA, and note their relationship with IBUremaining:

IBUoAA = 5/7 × ([oAA]beer × scaleoAA) [17]
IBUoBA = 5/7 × ([oBA]beer × scaleoBA) [18]
IBUremaining = IBUoAA + IBUoBA [19]

While we don’t (yet) know [oAA]beer or [oBA]beer, we can compute IBUremaining from Equation [15].

For each of the four experiments, Table 1 lists (a) the root-mean-square (RMS) error between the measured IBU values and the model that solves for scalingIAA and scalingABC, (b) the IBUs at time 0 (when the hops are added to the boiling wort) according to this model, at which point the ABCs have been added to the wort but there is not yet any production of isomerized alpha acids, (c) the estimated IBUs from malt polyphenols (determined from the original gravity and Equation [8]), (d) the estimated IBUs from hop polyphenols (determined from Equations [10] and [11]), and (e) the remaining IBUs according to Equation [15].

In Experiment #1, there was an initial alpha-acid concentration of 18 ppm and an initial beta-acid concentration of 535 ppm.  In Experiment #2, the initial alpha-acid concentration was 163 ppm and the initial beta-acid concentration was 53 ppm.  In Experiment #3, the initial alpha-acid concentration was 161 ppm and the initial beta-acid concentration was 38 ppm.  In Experiment #4, the initial alpha-acid concentration was 168 ppm and the initial beta-acid concentration was 116 ppm.

IBU model RMS error
model IBUs at time 0
IBUs from malt polyphenols
IBUs from hop polyphenols
remaining IBUs
Experiment #1
0.136 3.21 1.23 0.55 1.42
Experiment #2
0.314 6.42 0.86 0.21 5.35
Experiment #3
0.295 8.11 0.85 0.14 7.12
Experiment #4
0.399 8.78 0.86 0.42 7.50

Table 1. Results from the IBU model for each of the four experiments.  The “RMS error” is the root-mean-square error between the measured IBUs and the model.  The “model IBUs at time 0” show the model with the effect of ABC but no isomerized alpha acids.  The “IBUs from malt polyphenols” shows the estimated IBUs contributed by the malt.  The “IBUs from hop polyphenols” shows the estimated IBUs contributed by the hop polyphenols.  The “remaining IBUs” shows the difference between the model IBU at time 0 and the effect of polyphenols, which is the effect of oxidized alpha- and beta-acids.

8.2 Analysis Step 2
Assuming that the hops have been preserved well and have undergone very little oxidation during storage, we can express the concentration of oxidized alpha acids in the beer as the initial concentration of alpha acids added to the wort multiplied by a scaling factor, lossFactoroAA, that accounts for (a) the percentage of alpha acids that oxidize during the boil and (b) the percentage of oxidized alpha acids that remain after boiling and fermentation.  The same formulation can be applied to the beta acids:

[oAA]beer = [AA]0 × lossFactoroAA [20]
[oBA]beer = [BA]0 × lossFactoroBA [21]

where [AA]0 is the initial concentration of alpha acids (in ppm), [BA]0 is the initial concentration of beta acids (in ppm), lossFactoroAA is the scaling factor for alpha acids, and lossFactoroBA is the scaling factor for beta acids.

We can then note the following relationships by combining Equations [17, 18, 20, 21]:

IBUoAA = 5/7 × ([AA]0 × lossFactoroAA × scaleoAA) [22]
IBUoBA = 5/7 × ([BA]0 × lossFactoroBA × scaleoBA) [23]

All of this preparation has laid the groundwork for the formula that will be useful to us, obtained by combining Equations [19, 22, 23]:

IBUremaining = 5/7 × [AA]0 × lossFactoroAA × scaleoAA + 5/7 × [BA]0 × lossFactoroBA × scaleoBA [24]

This formula expresses the remaining IBU value as a combination of the initial concentrations of oxidized alpha- and beta-acids multiplied by scaling factors and loss factors.  We know IBUremaining, [AA]0, scaleoAA, [BA]0, and scaleoBA, and we want to estimate lossFactoroAA and lossFactoroBA.

We can solve for these two loss factors by using the data from the four experiments (obtained in Analysis Step 1) to construct four equations (based on Equation [24]) with the two unknowns:

1.42 = 5/7 × 18.38 × lossFactoroAA × 0.9155 + 5/7 × 534.87 × lossFactoroBA × 0.85 [25]
5.35 = 5/7 × 163.03 × lossFactoroAA × 0.9155 + 5/7 × 53.28 × lossFactoroBA × 0.85 [26]
7.12 = 5/7 × 161.35 × lossFactoroAA × 0.9155 + 5/7 × 38.06 × lossFactoroBA × 0.85 [27]
7.50 = 5/7 × 168.32 × lossFactoroAA × 0.9155 + 5/7 × 116.14 × lossFactoroBA × 0.85 [28]

We can perform a least-squares estimation, minimizing the root-mean-square (RMS) error between predicted and observed remaining IBU values, to solve for lossFactoroAA and lossFactoroBA.  The results of this analysis are that lossFactoroAA = 0.059 and lossFactoroBA = 0.0023, with RMS error 0.76 IBUs.

Independent of any particular batch of beer, lossFactoroAA and lossFactoroBA describe our best estimate of the contribution of oxidized alpha- and beta-acids to the IBU.  For any batch of beer where we know [AA]0 and [BA]0, we can use lossFactoroAA and lossFactoroBA to estimate [oAA]beer and [oBA]beer, and/or their contributions to the IBU.   (These estimates may be further influenced by wort pH, age of the beer, the treatment of krausen, among other factors.)

8.3 Analysis of Aged Hops
The experiment comparing well-preserved and poorly-preserved hops clearly indicates that oxidation of the beta acids produced during storage can yield significant IBUs. (I find it remarkable that hops with only 0.57% alpha acids and 3.61% beta acids can yield a beer with more than 20 IBUs.  This beer not only tasted more bitter or astringent, it had a more “herbal” quality, similar to Ricola “natural herb” throat drops.)  In Figure 2 it can be seen that the IBU values increase with boil time, which was unexpected. Is there some isomerization of oxidized beta acids that occurs along the same time-frame as the isomerization of alpha acids? Because there is no well-motivated explanation for why these IBU values increase, I will simplify the analysis by focusing on a single “representative” boil time, i.e. 20 minutes.

The increase in oxidized beta acids produced during aging at room temperature can be computed from the decrease in beta acids between the two conditions. The beta acids decreased from 10.92% to 3.61%, and so the increase in oxidized beta acids was 7.31% of the weight of the hops. With a volume of 3.16 G (11.96 liters) at the end of the boil and a weight of 2.0 oz (56.70 grams) of hops, the 4741 ppm of hops translates into 346.55 ppm of oxidized beta acids in the post-boil wort. If we assume various relative losses during fermentation and aging (fermentation loss of 0.85, krausen relative increase of 1.38 compared with normal krausen deposits, and an age-related loss factor of 0.96), there are 391 ppm of oxidized beta acids in the finished beer. The increase in IBUs between the two conditions (at a 20-minute boil time) is 17.0 IBUs. We can then map between IBUs and an “oxidized beta acid boil factor”, boilFactoroBA, which expresses the reduction in storage-produced oxidized beta acids during the boil:

IBUoBA = 5/7 × ([oBA]0 × boilFactoroBA × fermentFactoroBA × scaleoAA) [29]
17.0 = 5/7 × (346.55 × boilFactoroBA × 1.126 × 0.85) [30]

and so boilFactoroBA equals 0.07. This implies that about 7% of the beta acids that oxidize during storage survive the boil and end up in the wort. This factor is about the same as the factor for oxidized alpha acids produced during the boil (0.06), indicating that both can contribute significantly to the IBU.

9. Conclusion
The estimated scaling factor lossFactoroAA (0.059) being 25 times larger than the scaling factor lossFactoroBA (0.0023) for well-preserved hops means that the oxidized alpha acids contribute much more to the IBU than oxidized beta acids, as long as the hops are well preserved.  The estimated contribution of oxidized beta acids is so low in this case, it seems quite likely that oxidized beta acids are not produced during the boil at all.

For poorly-preserved hops, however, the contribution from oxidized beta acids produced during storage appears to be roughly equal to the contribution from oxidized alpha acids produced during the boil. (The better the storage conditions, the less impact that beta acids will have on the IBU.)  With oxidized beta acids produced during aging and present in finished beer, the reduction in IBUs from using older hops with a lower alpha-acid content is offset by the oxidation products. As Hough et al. say, “The level of alpha-acid in hops falls during storage but the bittering potential of the hops does not fall to the same extent. This is because many of the oxidation products of both alpha- and beta-acids … are capable of bittering beer” [Hough et al., p. 489].

If we consider a “typical” beer produced with well-preserved hops, such as an American Pale Ale as described by Ray Daniels [Daniels, pp. 167-172], we might have an original gravity of 1.050, a post-boil volume of 5.25 G (19.87 liters), and a post-boil pH of 5.25.  This beer might have five hop additions, all with 9% AA and 5.0% beta acids: one of 0.75 oz (21.26 g) at the start of the 60-minute boil, a second of 0.75 oz (21.26 g) at 45 minutes before flameout, a third of 0.50 oz (14.18 g) at 20 minutes before flameout, a fourth of 0.75 oz (21.26 g) at 10 minutes before flameout, and a dry-hop addition of 1.0 oz (28.35 g).  In this case, we might get 50.0 IBUs in total, 33 of those from isomerized alpha acids and 17 from ABCs.  Of these 17 ABC IBUs, using the model described above, oxidized alpha acids contribute 14.0 IBUs, oxidized beta acids contribute 0.3 IBUs, malt polyphenols contribute 2.1 IBUs, and hop polyphenols contribute 0.7 IBUs.  The oxidized alpha acids are therefore by far the greatest component of the auxiliary bittering compounds (at 82% of all ABC), followed by malt polyphenols (12%), then hop polyphenols (4%), and finally oxidized beta acids (2%). A single hop addition at 10 minutes before flameout will have about as many IBUs coming from oxidized alpha acids as from isomerized alpha acids.  This can be seen in Figure 1, with about 13.5 IBUs at a 10-minute steep time averaged over Experiments #2, #3, and #4, and about 7.5 IBUs estimated at time 0 when isomerization begins.

Even if you are uncomfortable with some (or all) of the assumptions made in this model, it is still clear from the measured IBUs in Figure 1 that oxidized beta acids produced during the boil can not contribute significantly to the IBU.  First, there is the fact that 535 ppm of beta acids in Experiment #1 yielded less than 4 IBUs, and at least some of those IBUs come from polyphenols.  Additionally, if we compare the results of Experiments #3 and #4, the IBU values are very similar.  Although the alpha-acid ratings of the hops in the two experiments were very different (14.2% and 5.0%), the amount of hops added to the kettle was set to target a similar alpha-acid concentration (160 to 170 ppm).  This resulted in Experiment #3 having an initial beta-acid concentration of 38 ppm and  Experiment #4 having an initial beta-acid concentration of 116 ppm.  The similarity of the IBU values between the two experiments, with three times the beta-acid concentration in Experiment #4, can best be explained by the alpha acids (both isomerized and oxidized) contributing to the vast majority of the IBU and the beta acids contributing very little to the IBU value.

10. Discussion
From the results of these experiments, it appears that (a) there is little or no production of oxidized beta acids during the boil, (b) about 7% of the oxidized beta acids produced during storage end up in the wort and finished beer, and (c) any transformation of oxidized beta acids to hulupinic acid ([Almaguer, p. 295]) occurs slowly (e.g. over the course of weeks or months).

It is interesting to note similarities between the Rager [Rager] and Tinseth [Tinseth] IBU formulas and the model described here.  The Rager formula predicts 5% utilization even for a steep time of 0 minutes, which correlates extremely well with the estimated lossFactoroAA of 0.059 in this blog post.  In both cases, before there is any significant isomerization, about 5% of the available alpha acids contribute to the IBU (in the form of oxidized alpha acids).  Tinseth, on the other hand, knew that isomerization can be modeled with a first-order reaction [Tinseth], and so the shape of the Tinseth utilization curve is similar to the rate of alpha-acid isomerization determined by Malowicki (Equation [3]).

The slopes of the lines formed by the IBU values in Experiments #2 and #3 imply that Experiment #2 had a higher concentration of alpha acids than Experiment #3 or less loss of isomerized alpha acids.  The AA rating of the hops would have to be increased from 9.7% to 12.6% for the loss of IAAs to be the same.  While AA levels can be highly variable even within the same bale of hops [Verzele and DeKeukeleire, p. 331], a 30% variation is larger than one would normally expect.  It is therefore unclear why there is such a difference between the results of these two experiments.  My best guess is that small differences in my degassing procedure when preparing samples for IBU analysis resulted in less loss of IAAs in Experiment #2, and that this effect was combined with normal variation in AA levels.  (I have seen a 12% difference in IBUs from the same beer that was degassed in slightly different ways.)  On the other hand, the similarity of the results between Experiments #3 and #4 is remarkable given the difference in AA ratings, amount of hops used, and other various differences.

11. Acknowledgment
I would like to thank Dana Garves at Oregon BrewLab for her attention to quality and detail that is reflected in the IBU measurements presented here.  The change in measured IBU values over time very closely follows the expected trend, even to the point of a fractional increase between 5 minutes and 60 minutes for the well-preserved Teamaker hops with an AA rating less than 1%.  An analysis can only be as good as the data it is based on, and so I greatly appreciate the data of such high caliber.

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Predicting Wort Temperature After Flameout

Abstract
In a previous post, I described a method for estimating IBUs that are produced in hot wort after flameout.  This method relies on both (a) relative utilization as a function of temperature, described elsewhere, and (b) a function that describes the decrease in wort temperature after flameout (but before “forced cooling” with a wort chiller).  In this blog post, I describe temperature data collected under a variety of conditions and the resulting formula for predicting the temperature of wort as it naturally cools after flameout.  The data suggest that this rate of natural cooling is primarily influenced by (a) the release of steam, which is in turn influenced by the wort volume, surface area of wort exposed to air, and size of the opening in the kettle through which steam can escape, and (b) radiation of heat from the kettle.  Other factors, such as ambient temperature, are of much lesser significance.  The resulting formula, for homebrew-scale batch sizes, is T = 53.70 × exp(-b × t) + 319.55, where b = (0.0002925 × effectiveArea / volume) + .00538 and effectiveArea = (surfaceArea × openingArea)0.5.  The parameter T is temperature (in degrees Kelvin), t is time after flameout (in minutes), b is the rate constant that describes how quickly the temperature decreases, effectiveArea is the “effective” area through which steam ventilates, surfaceArea is the surface area of wort exposed to air (in square centimeters), openingArea is the area of the opening in the kettle (in square centimeters), and volume is the wort volume (in litres).

1. Motivation
The motivation for the work described here was to predict the temperature decrease of wort after flameout, in order to facilitate computation of the mIBU method of predicting IBUs for homebrew-scale batch sizes.

If one thinks about the various factors that might influence this temperature decrease, many things may come to mind:

  1. The wort volume, with larger volumes potentially cooling more slowly,
  2. The size or surface area of the kettle (which may be much larger than the wort volume), with larger kettles potentially radiating more heat than smaller kettles,
  3. The size of the opening in the kettle (with potentially slower cooling for a smaller opening that traps more heat),
  4. The ambient or room temperature (with wort potentially cooling faster if the room temperature is 10°C (50°F) as opposed to 30°C (86°F)),
  5. The relative humidity (with wort potentially cooling faster in drier conditions),
  6. The specific gravity of the wort (with higher specific gravities potentially cooling differently from water),
  7. The removal of the kettle from the heat source (with potentially slower cooling if the kettle remains on a still-hot burner),
  8. The kettle material (with materials such as aluminum potentially cooling faster than materials such as stainless steel), and
  9. Whether the kettle is insulated or not (with potentially slower cooling for an insulated kettle).

In order to investigate these possibilities, I tested these factors with either wort or (for simplicity) water, plotted the results, and determined which factors have the greatest impact on the rate of temperature change.  With this information, I then constructed a formula for predicting wort temperature after flameout as a function of time.  This function can be used directly in the mIBU method.

2. Data
I measured the decrease in temperature after boiling for 33 conditions in order to test the various factors listed above; these conditions are listed in Table 1 at the very bottom of this post.  (I did not control for ambient temperature and relative humidity separately; generally, a lower ambient temperature was correlated with a higher relative humidity.)  I measured the temperature of wort or water after flameout in 22 conditions with the kettle uncovered, and additional 11 conditions with the kettle partially or fully covered.   I used wort in 5 cases and water in 28 cases.  I used a Thermapen Mk4 for measuring temperature in all cases except condition AG, in which I used a TelTru analog thermometer with a 30 cm (12″) probe.  I took measurements at 1-minute intervals for the first 15 or 20 minutes after flameout. (Measurements were taken for only 15 minutes for three conditions: T, U, and V.)  For the conditions using water, I measured volume to the nearest 30 ml (1 ounce) using a “Legacy Pro” 4000-ml (128-oz) graduated pitcher (which looks identical to the US Plastics Corp. Accu-Pour™ PP Measuring Pitcher),  recorded the temperature of each addition, and normalized from this volume and temperature to the volume at boiling using Equation 3 in “ITS-90 Density of Water Formulation for Volumetric Standards Calibration” (Jones and Harris, Journal of Research of the National Institute of Standards and Technology, vol 97, no. 3, pp. 335-340 (1992)).  For the conditions using wort, I estimated the volume at close to boiling using a measuring stick or the difference between pre- and post-boil specific gravity.  Twelve of the more interesting conditions are plotted in Figure 1, with time on the horizontal axis and temperature (in degrees Celsius) on the vertical axis.

I will mostly use metric units throughout this blog post in order to simplify the presentation, with apologies to readers in the United States.  The final formula uses degrees Kelvin.

tempDecayExp-Fig1-rawData

Figure 1. Temperature (in degrees Celsius) as a function of time (in minutes) for twelve of the 33 conditions.  The legend for each condition specifies the volume of liquid (water or wort, in litres), the amount by which the kettle was covered (in percent; 0% = uncovered and 100% = completely covered), the size of the kettle (in litres), and any other details about the condition, such as ambient temperature or insulation.  Only one of the conditions in this plot used wort (specific gravity 1.052); the other cases here used water.

3. Parameter Estimation
3.1 Exponential Decay

It can be seen that all of the data in Figure 1 can have a good fit to a function with exponential decay.  Those conditions not plotted in Figure 1 also show a similar goodness of fit to an exponential decay function.  (For many of the cases, a straight line also seems to be a good fit, but the exponential decay function can model nearly-straight lines as well as curved lines of the type seen here.)  An exponential decay function is of the general form a × exp(-b×t) + c, where t is (in this case) time, a, b, and c are parameters that describe the shape of the function, and exp(x) indicates the constant “e” to the power of x, or 2.71828x.  In this case, the parameter b is called the rate constant, and it describes how quickly the function (or temperature) decreases.  (I like using fooplot to visualize different functions and parameter values; one can enter something like “54*exp(-0.03x)+46” on this page to see a representative exponential decay function, setting the graph lower limits to 0, the x-axis upper limit to 50, and the y-axis upper limit to 100.)  The liquid was at boiling in all cases at time 0, with an average measured temperature over all conditions of 100.1°C.  (The expected boiling point of water at my elevation (76 meters above sea level) is 99.7°C.  However, the boiling point of wort is higher than that of water, so the average boiling point over all conditions (with 5 of the 33 cases using wort) was higher than 99.7°C.  The difference of less than 0.4°C is within the  specified accuracy of my Thermapen, which is ±0.4°C.)    If t = 0, then exp(-b×t) is 1 for any value of b, and so a + c must equal 100.1.

In order to simplify the parameter estimation, I searched over conditions A through V (those conditions in which the kettle is uncovered) minimizing the root-mean-square (RMS) error to find the best value of b in each case and the values of a and c that were the best over all conditions.  (In other words, a and c were optimized to have the same value over all conditions, whereas b was optimized per condition.)  If the total RMS error over all conditions is small with constant values of a and c, then the different shapes of each curve can be described well with a single parameter, b.

The search for a and c yielded a=53.70°C and c=46.40°C with an overall RMS error of 0.31°C.   The maximum RMS error was 0.64°C for condition O.  The small RMS error over all conditions indicates that we can, in fact, describe the different rates of temperature decay of these conditions with a single parameter, the rate constant b.  The question then becomes whether we can predict b from the various factors in each condition, and if so, if certain factors are more important than others in predicting b.  (It’s also worth noting that the optimal value of c in this case is not room temperature.  Presumably, if time were measured in hours instead of minutes, the values of a and c would have turned out differently, with c at around room temperature.  Or, there are other factors involved at longer time scales that don’t fit well to a simple exponential decay function.)

3.2 Predicting the Rate Constant for Uncovered Kettles
Figure 2 plots the values of b that minimize the RMS error in each uncovered-kettle condition with a=53.70°C and c=46.40°C.  The horizontal axis is the volume of wort or water, and the vertical axis is the value of b.  A few clear patterns emerge: the data obtained from a single kettle are grouped in a curved line with negative slope (for the two cases where there are multiple data points per kettle), and these curves (representing different kettles) are separated from each other by possibly constant scaling factors.  The curved line with negative slope for the 38-litre kettle looks like a function of the form 1/x, where x in this case is volume.  This suggests that b can be approximated as a function of scaling/volume, where scaling is some (still unknown) property of the kettle and volume is the wort volume (in litres).

tempDecayExp-Fig2-rateConstVsVolume

Figure 2. Temperature-decay rate constants for all conditions with uncovered kettles, plotted as a function of wort volume.  Each group (e.g. black squares or red diamonds) is for a different kettle (and kettle diameter).

After considering various possibilities for the factor called scaling, the area of the kettle opening (πr2), which equals the surface area of wort exposed to the air, shows a good fit to this set of data.  The black “×” marks in Figure 3 plot the values of area/volume on the horizontal axis for the uncovered kettle (where area is the area of the kettle opening (or πr2, where r is the radius of the kettle) in square centimeters, and volume is the volume of liquid, in litres) and values of the rate constant b on the vertical axis.  The approximately straight line of black × marks in Figure 3 is interesting.  It implies that the rate of temperature decay, represented by the parameter b, can be predicted quite well from only the area of the kettle opening and the volume of liquid.  The value of b when the area is zero implies a rate of cooling caused by heat radiated from the kettle (with an entirely closed system), and the slope of the line implies faster cooling as more steam escapes the kettle with greater wort surface area.  In other words, if b is modeled as a straight line of the form b = slope × (area / volume) + offset, where slope is the slope of the line and offset is the value when area = 0, then offset represents the temperature decay due to heat radiated from the kettle, and slope represents the temperature decay caused by the loss of heat in the steam.  In this case, a good fit can be seen for the line b = 0.0002925 × (area / volume) + 0.00538.

tempDecayExp-Fig3-rateConstVsArea

Figure 3. Temperature-decay rate constant as a function of (kettle opening area) divided by volume, for uncovered kettles. In this case, the kettle opening area equals the area of wort exposed to air.

3.3 The Rate Constant for (Partially) Covered Kettles
I then plotted the values of b for those cases in which the kettle is partially or completely covered, as shown in Figure 4 (with much lower limits on the X and Y axes of this graph).  The cases in which the kettle is completely covered cluster somewhat around the predicted value of b when the area is zero.  Larger kettles and volumes have smaller values of b, implying less radiated heat loss from larger kettles and/or volumes.  Conditions Z and AG are nearly identical except for the size of the kettle; Z used 15.4 litres of water in a covered 18.9 litre kettle, and AG used 15.6 litres of water in a covered 37.9 litre kettle.  The temperature after 20 minutes was very close in both conditions, and the estimated value of b is nearly the same in both cases (0.00371 vs 0.00373).  Therefore, it seems that the size of the kettle has very little impact on the rate of temperature decay through radiated heat, but the volume of liquid does have an impact on radiated heat.

Again looking at Figure 4, the conditions in which the kettle is only partially covered deviate from the predicted line, regardless of whether area (the horizontal axis) is (a) the exposed wort surface area (blue circles) or (b) the kettle opening area (green squares).  The predicted line lies somewhere between these two extremes.  This suggests that if the kettle is partially covered, the amount of steam produced is (still) roughly proportional to the surface area of the wort exposed to air (i.e. the area of the fully-open kettle), but that this steam is not able to escape quite as quickly, leaving more heat trapped in the kettle.  (For an uncovered kettle, the area of the opening in the kettle and the surface area of wort exposed to air are the same.)

One possibility is that the rate of heat loss is proportional to the geometric average of the wort surface area and the opening area.  We can call this the “effective area,” i.e. effectiveArea = (surfaceArea × openingArea)0.5, where surfaceArea is the wort surface area, openingArea is the area of the kettle opening, and (x)0.5 indicates the square root of x.  In this case, when the area of the opening is zero (for a covered kettle), the effective area is also zero.  When the area of the opening equals the surface area of the wort, the effective area is the same as the surface area of the wort.  When we plot effectiveArea / volume on the horizontal axis and b on the vertical axis in Figure 5, we observe that the data from the partially-covered conditions are much closer to the straight line, allowing us to predict temperature decay fairly well with a small number of parameters.

tempDecayExp-Fig4-rateConstCoveredKettle

Figure 4. Rate constants for uncovered kettles (black “×” marks), fully-covered kettles with area = 0 (red triangles), partially-covered kettles with area = area of kettle opening (green squares), and (the same) partially-covered kettles with area = wort surface area (blue circles). The line with the best fit to uncovered-kettle data is also plotted.

tempDecayExp-Fig5-rateConstCoveredKettleEffectiveArea

Figure 5. Rate constants for uncovered kettles (black “×” marks), partially covered kettles (dark red diamonds), and fully covered kettles (light red triangles), plotted as a function of “effective area”. Effective area is the geometric mean of the exposed wort surface area and kettle opening area.

4. Model Accuracy
4.1 Looking at Factors Potentially Influencing Temperature
In the model we have developed, we can predict temperature after flameout using three parameters: wort volume, kettle diameter (to compute exposed wort surface area), and kettle opening diameter (to compute the area of the opening).  Other factors, such as ambient temperature and specific gravity, have a fairly small deviation from the predicted line, indicating that these factors have only a minor impact on the decrease in temperature.  For example, in Figures 3, 4, and 5 there are two rate constants that have the same area/volume value of 46.9 cm2.  (This is most easily seen in the two “×” marks at area/volume=46.9 on the right-hand side of Figure 4.)  The one just below the predicted line, with a value of 0.0190, was from Condition C with water from an uncovered 19-litre kettle and an ambient temperature of 12°C (53°F).   This case has a predicted temperature of 86.9°C after 15 minutes, which is very close to the measured temperature of 86.8°C.  The one even lower than the predicted line, with a value of 0.0176, was obtained under the same conditions except with an ambient temperature of 33°C (91°F), Condition J.  This case has the same predicted temperature of 86.9°C, but a measured temperature of 87.8°C after 15 minutes.  From this, we can conclude that ambient temperature does have an effect on the rate of temperature decrease, with warmer ambient temperatures yielding a slower decrease in temperature.  However, this effect is minor, with a large difference in ambient temperatures (21°C (38°F)) yielding a small difference of 1.0°C (1.8°F) after 15 minutes.  (I also learned that brewing in very hot climates would not be very pleasant for me.  I respect anyone with the dedication to brew when the temperature is above 30°C (86°F).)

Over all conditions, the average absolute difference in temperature at 15 minutes between measured and modeled temperatures is 0.8°C.  The largest difference at 15 minutes, 1.9°C, is for Condition AE, which has a large volume in an entirely closed kettle.

4.2 Factors Potentially Influencing Temperature
In general, we can look at the difference in measured temperatures at 15 minutes between two conditions when only one factor is different between the conditions.  A factor with a larger difference can be considered more important in influencing temperature decay than a factor with a smaller difference.  (The value of 15 minutes is somewhat arbitrary but I think not unreasonable.  It is the largest time point for which I have measured data in all conditions.)  One issue with this metric is that smaller volumes will generally have greater temperature differences over time than larger volumes.  In addition, the diameter of the kettle and area of the kettle opening will have an impact on the magnitude of the measured temperatures.  In order to normalize for these factors, one could look at the difference divided by the temperature of one of the conditions, but this relative error is less intuitive.  I’m not aware of an intuitive error metric that addresses the dependence on volume and kettle characteristics, so I’ll simply report the measurement difference as well as the volume.  Unless otherwise indicated, the kettle diameter and area of the kettle opening are the same within each comparison.

As discussed in the previous section, a high ambient temperature can have a measured temperature difference after 15 minutes of 1.0°C at 15.6 litres.  Removing the kettle from the hot metal burner yields a measured difference of -0.8°C at 25 litres.  A stainless steel kettle (instead of an aluminum kettle) yields a measured difference of 1.0°C at 7.8 litres.  The enamel kettle yields a measured difference of -3.3°C at 11.7 litres, but the two kettles have different exposed surface areas (75.2 cm2 for enamel, 60.6 cm2 for aluminum), and so this difference may appear larger than it is, even after accounting for volume.  (The predicted difference in temperature for the enamel kettle is -1.4°C).  An insulated kettle yields a measured difference of 1.0°C at 15.6 litres.  (The insulation in this case was a combination of closed-cell foam insulation and mylar wrap, around and over the aluminum kettle.)   As noted earlier for covered kettles, larger volumes have slower temperature decay than smaller volumes, with a measured difference of 0.7°C for 31.2 litres compared with 15.6 litres.

To compare the decrease in temperature of wort with water, we can compare (a) the temperature of the 24.6-litre wort case (R) with the 27.3-litre water case (M), with a difference in measured temperatures of -0.3°C; (b) the temperature of the same 24.6-litre wort case (R) with the 23.4-litre water case (D), with a difference of 1.1°C; (c) the temperature of the 29.1-litre wort case (T) with the 31.2-litre water case (E), with a difference of 0.2°C; and (d) the temperature of the 28.9-litre wort case (U) with the 31.2-litre water case (E), with a difference of 0.8°C.  In short, Condition R has no real difference with the temperature of water, while conditions T and U have a small positive difference that is contrary to the expected small negative difference based on different volumes.  The difference between measured and predicted temperatures for conditions R, T, U, and V are 1.5°C, 0.6°C, 1.3°C, and 0.0°C, respectively.  Overall there does not seem to be a large difference between the temperature decrease of wort and of water, although the model may predict slightly lower temperatures than are observed.

4.3 Incorporating Additional Factors into the Model
Because the factors described above seem to have at least some impact on the rate of temperature decrease, should we be modeling them in the temperature-decrease formula?  The answer to that question depends on our purpose (predicting IBUs) and our tolerance for error.  If we have a scenario with fairly typical homebrewing conditions, we can look at how a temperature difference of 3°C after 15 minutes impacts IBUs predicted with the mIBU method.  A difference of 3°C at 15 minutes is somewhat arbitrary, and is 1.5 times larger than the largest observed difference in these 33 conditions, but might be observed with a combination of factors different from those factors used to develop the formula.  Given a post-boil volume of 19.9 litres (5.25 gallons) in an uncovered kettle with diameter 36.8 cm (14.5 inches), a single addition of 28.35 g (1.0 oz) of 10% AA hops at flameout, and a 15-minute hop stand, the predicted temperature after 15 minutes with the formula developed in this blog post is 85.55°C (186.0°F), and we predict 9.92 IBUs using the mIBU method.  If we change the rate constant from 0.02106 to 0.01614 so that the temperature after 15 minutes is 88.55°C (191.4°F), or 3°C warmer, we then predict 10.87 IBUs, or a difference of 0.95 IBUs. If the temperature decreases by 3°C using a rate constant of 0.02638, we predict 9.06 IBUs, or a difference of -0.86 IBUs.  If, instead of a 15-minute whirlpool, we use the same rate constants with a 45-minute whirlpool, we predict 12.48 IBUs when the temperature is 85.55°C after 15 minutes, 14.31 IBUs when the temperature is 88.55°C after 15 minutes, and 10.97 IBUs when the temperature is 83.55°C after 15 minutes, or IBU differences of 1.83 and -1.51 in a 45-minute whirlpool.

Can we tolerate a difference of about 1 to 2 IBUs if our temperature decay model is off by 3°C after 15 minutes?   The short answer to that question is “yes,” for two reasons.  First, it has been reported that people can’t detect a difference less than 5 IBUs (e.g. J. Palmer, How to Brew, p. 56).  So a prediction error of even 2 IBUs is well below our ability to detect with our taste buds.  Second, there are a wide variety of other factors that make IBU prediction so inexact that getting anywhere close to a measured IBU value is cause for celebration.  For example, things that are not accounted for in the Tinseth or basic mIBU formulas are: (a) the inherent variability (up to 15 to 20%) in alpha acid levels within a single bale of hops (M. Verzele, and D. De Keukeleire, Chemistry and Analysis of Hop and Beer Bitter Acids, p. 331), (b) the hopping rate, which can have a significant impact on IBUs, (c) wort pH, which can affect IBU losses, (d) wort clarity, (e) krausen deposits or loss, (f) age of the beer, (g) the effect of pellets instead of hop cones, and (h) the age and storage conditions of the hops.  Any of these factors alone can yield a difference greater than 2 IBUs, and in combination the net effect is a high degree of uncertainty in predicted IBU values.

In summary, factors such as ambient temperature, kettle size, insulation, kettle material, etc. do have an impact on the rate of temperature decay.  However, for our purposes, it does not seem necessary to extend the formula to specifically account for these factors.

5. Summary and Conclusion
The final formula for predicting wort temperature as a function of time after flameout, for homebrew-scale batch sizes, is

T = 53.7 × exp(-b × t) + 319.55
b = (0.0002925 × effectiveArea / volume) + 0.00538
effectiveArea = (surfaceArea × openingArea)0.5

where T is temperature (in degrees Kelvin), t is time after flameout (in minutes), b is the rate constant that describes how quickly the temperature decays, effectiveArea is the “effective” area through which steam ventilates, surfaceArea is the surface area of wort exposed to air (in square centimeters), openingArea is the area of the opening in the kettle (in square centimeters), and volume is the wort volume (in litres).  The area values can be easily determined from the diameters of the kettle and the kettle opening.

It is not clear how well this formula will scale up to commercial-size batches.  If anyone who has such a system can provide me with the necessary parameter values and temperature measurements, I’ll be happy to evaluate the formulas and adjust as necessary.  To contact me for this or any other reason, send an e-mail to the name associated with this blog (no spaces or other punctuation) at yahοο.

Appendix: Specifics of Each Condition
This section lists some details about each condition in table form.  The volume is either of water or wort; if specific gravity is not specified, water was used.  For partially-covered kettles, I constructed cardboard and aluminum-foil “lids” that had openings of 25%, 50%, or 75% of the area of the open kettle.  The kettle size is noted using approximate capacity, in litres.  Unless otherwise noted, the ambient temperature was approximately 13°C (55°F), and the kettle material was aluminum.

 

Condition volume (litres)
kettle size (litres)
wort surface area (cm2)
percent of kettle covered other notes
measured temp. at 15 minutes (°C)
predicted temp. at 15 minutes (°C)
A
7.8 18.9 710.33 0% 78.4 79.6
B 15.6 37.9 1083.80 0% 81.8 82.9
C 15.6 18.9 710.33 0% 86.8 86.9
D 23.4 37.9 1083.80 0% 87.6 86.8
E 31.2 37.9 1083.80 0% 88.9 88.9
F 7.8 11.4 457.30 0% stainless steel kettle 84.2 84.7
G 7.8 11.4 500.39 0% 83.2 83.7
H 7.8 37.9 1083.80 0% 73.0 73.3
I 15.6 18.9 710.33 0% ambient temp. 27°C 87.8 86.9
J 15.6 18.9 710.33 0% ambient temp. 33°C 87.8 86.9
K 3.9 37.9 1083.80 0% 61.7 61.0
L 11.7 37.9 1083.80 0% 78.6 79.4
M 27.3 37.9 1083.80 0% 89.0 88.0
N 11.7 18.9 710.33 0% 83.9 84.4
O 11.7 18.9 881.21 0% enamel kettle 80.6 82.0
P 19.5 37.9 1083.80 0% 85.2 85.2
Q 15.6 37.9 1083.80 0% insulated kettle 82.8 82.9
R 24.6 37.9 1083.80 0%  wort (SG=1.052) 88.7 87.2
S 25.4 37.9 1083.80 0%  wort (SG=1.052), kettle removed from heat source 87.8 87.5
T 29.1 37.9 1083.80 0%  wort (SG=1.042), loose cones 89.1 88.5
U 28.9 37.9 1083.80 0%  wort (SG=1.042), pellets 89.7 88.4
V 4.6 18.9 710.33 0% wort (SG=1.065), mIBU Exp.#3 71.6 71.6
W 15.4 18.9 710.33 25% 87.3 88.0
X 15.4 18.9 710.33 50% 88.2 89.3
Y 15.5 18.9 710.33 75% 89.7 91.2
Z 15.4 18.9 710.33 100% 97.2 95.9
AA 23.4 37.9 1083.80 50% 87.8 89.3
AB 23.4 37.9 1083.80 75% 90.9 91.1
AC 31.2 37.9 1083.80 50% 90.8 90.9
AD 31.2 37.9 1083.80 75% 92.4 92.3
AE 31.2 37.9 1083.80 100% 97.8 95.9
AF 7.8 11.4 500.39 100% 94.8 95.9
AG 15.6 37.9 1083.80 100% 97.2 95.9

Table 1. Details about each condition in this blog post.

numbers

It wasn’t too long into making beer that I found that the original gravity or final volume was always lower than expected.  The OG and volume should be pretty predictable, especially with extract brewing.  By taking better measurements and computing additions and losses of sugars and water at each step, I’ve been able to get much closer to my predicted targets.  It turns out that in my case the main culprit was how much wort was being absorbed by the hops and then discarded… and I was adding a lot of hops!

For those who might be interested, I present a bunch of numbers intended to help with predicting the effects of different brewing techniques.

water absorbed by 80% 2-row, 20% specialty malts 0.147 G/lb = 0.59 qt/lb
or
0.210 G/lb = 0.84 qt/lb
(see text below; the larger number is probably the better estimate)
wort left in bottom of 52-quart Coleman Xtreme cooler 0.21875 G (3.5 cups)
evaporation during steeping of grains at 160°F, uncovered 0.35 G/hr
evaporation during low rolling boil, uncovered, targeting ~10% total evaporation, with 10G pot and 7G of wort about 1.0 G/hr
evaporation during uncovered hop stand (170°F to 180°F) 0.35 G/hr
water absorbed by hops during boil and hop stand 0.063 G/oz
water absorbed by hops after dry-hopping (in weighted mesh bag) 0.006 G/oz
PPG of crystal 20 malt 10 PPG
PPG of crystal 40 malt 15 PPG
wort and break lost during transfer from 10G pot, using “auto siphon” racking cane with no spacer. 0.30 to 0.45 G (extract)
0.15 G (all-grain)
wort and break lost when racking from 6G “better bottle” carboy, using “auto siphon” racking cane with no spacer. 0.30 G
wort and break lost when racking from 5G glass carboy, using “auto siphon” racking cane with no spacer. 0.15 G
weight of 1 tsp of Calcium Chloride anhydrous (CaCl2) 4.462 g = 0.157 oz
weight of 1 tsp of Calcium Chloride dihydrate (CaCl2·2H2O) 5.035 g = 0.1776 oz
weight of 1 tsp of Calcium Carbonate (CaCO3) 2.825 g = 0.996 oz
weight of 1 tsp of Calcium Sulphate dihydrate (CaSO4·2H2O) 3.266 g = 0.115 oz
weight of 1 cup of Briess Pilsen Light Dried Malt Extract (DME) 5.1 oz

Water Absorbed by Grains: The first set of numbers for the absorption rate of grains was computed from three measurements: (a) the amount of wort that dripped out of the cooler after I stopped collecting wort for the boil, (b) the weight of all of the wet grains, and (c) the dry-to-wet grain ratio, obtained by drying 2.0 lbs of the wet grains and measuring the dry weight of the spent grains.  I collected 9 ⅓ cups of wort just letting it drip out slowly into a container, or 0.5833 G.  The 15 original pounds of grain weighed 21.625 lbs (346 oz) when spent and wet.  The 2 lbs of wet, spent grain weighed 0.575 lbs (9.2 oz) after being dried in the oven for two hours.  So, the dried, spent grain weight is 28.75% of the wet, spent grain weight.  For the total of 15 lbs, that would yield 6.217 lbs of dried, spent grain.  The amount of water in the grains was therefore 21.625 lbs – 6.217 lbs = 15.408 lbs of water.  With the weight of water at 8.34 lbs/G, that’s 1.8475 G of water absorbed by the spent grains.  (This means that 0.49 qt/lb was retained by the grains (and didn’t drip out), which may be where Palmer obtained his 0.5 qt/lb estimate.)  If we add 1.8475 G that was retained by the grains to the 0.5833 G that dripped out from the cooler, and subtract the 0.21875 G of water that simply collects at the bottom of the cooler without being absorbed, we get 2.212 G of water that were absorbed by the grains when I stopped collecting wort.  This translates into 0.59 qt/lb or 0.147 G/lb absorbed by the malt (2.212 G x 4 / 15 lbs).  This is in between the 0.5 qt/lb reported by Palmer in “How to Brew” (p. 184) and the 0.8 qt/lb reported by Daniels in “Designing Great Beers” (p. 64).

Note that the dried, spent grain weight, 6.217 lbs, is 41.44% of the original grain weight of 15 lbs, which accords well with Daniels in “Designing Great Beers” on page 64, in which he says “the postmash grain mass is about 40% of the weight of the grain you added.”

I obtained a second estimate for the absorption rate of grains in a much more direct manner.  I added 6.2 G of water to 13.75 lbs of grains and measured the runoff at slightly less than 4.10 G.  Assuming that the value for the amount of wort left in the bottom of the cooler is correct (~0.22 G), that might mean that 1.89 G remained in the wort, or approximately 0.55 qt/lb.  However, this method of computation is flawed.  When you add 6.2 G of water to grains, you don’t get 6.2 G of wort; you get a larger volume of wort because of the sugars extracted from the grain contribute to the volume.  I’ve measured 0.059 gallons worth of dissolved sugar per pound of dried malt extract, and 0.074 gallons worth of dissolved sugar per pound of grain.  This would add about 1 G of liquid, resulting in about 7.2 G of wort in this example.  With runoff of 4.10 G and known loss of 0.22 G, this would mean grain absorption of 0.84 qt/lb, which is close to the value reported by Daniels.  Why did the two methods yield such different results (0.59 qt/lb and 0.84 qt/lb)?  The lower number represents the amount that is retained by the grains if all of the excess wort is drained off.  The higher number represents the amount that is retained by the grains with some amount not quite absorbed but not drained in a reasonable time.  Therefore, I think the 0.84 qt/lb is the better number to use in brewing.

Evaporation Rates: The evaporation rates were obtained with a measuring stick (i.e. a long aluminum rod) calibrated to my pot with ¼- and ⅓-gallon markings.  I’ve found the strength of the boil a little difficult to “dial in” with my propane burner and outdoor brewing.  Several authors recommend a “vigorous” boil, going so far as to say “boil it as hard as you can” (Mosher,  “The Brewer’s Companion”, p. 136). Lewis and Young say that “efficient boiling requires a ‘full rolling boil’ meaning intense and rapid motion as well as evolution and removal of steam (“Brewing”, 2nd edition, p. 272).   Miller says to “maintain a vigorous rolling action” (p. 145), but also cautions that “overboiling can create harsh bitterness in your beer.” (p. 186). Others also caution about too vigorous a boil, noting for example that this will cause “more color development, melanoidin production, … [and] can also cause the hop bitterness to take on additional harshness” (Strong, “Brewing Better Beer”, p. 61).  Fix is the only source I know of who has quantified this, saying that “volume reduction should be at least 7%. … Evaporation rates above 12% may produce level 2 [of non-enzymatic browning], leaving vegetal malt tones that are accompanied with some astringency.  A wide range of [non-enzymatic browning] is possible once evaporation rates exceed 15%.” (Fix, “Principles of Brewing Science”, p. 78).  He summarizes this as “The best general recommendation is an evaporation rate of 9 to 11%.  This can usually be achieved with a ninety-minute boil” (Fix and Fix, “An Analysis of Brewing Techniques”, p. 54).  I’ve found it quite easy to go beyond a 15% reduction in volume in a sixty-minute boil with my propane burner and an uncovered pot, and in trying to keep the volume reduction to around 10% in sixty minutes, I aim for a “low rolling boil”, in which there are many small bubbles but few big bubbles.

I’ve found that, other than the strength of the flame, the biggest impact on evaporation rate is the size of my pot and amount of wort.  In my 10G pot with about 7G of wort, I observe an evaporation rate around 1.0 G/hr.  In my smaller 5G pot with 4 G of wort, I observe an evaporation rate around 0.8 G/hr.  In my smaller 5G pot with 1 to 2 G of wort, I observe an evaporation rate of around 0.55 G/hr.

I’ve developed a model for evaporation rates at sub-boiling temperatures, available at my web site by clicking on the “Cooling and Evap.” button on the left-hand side.

Water Absorbed by Hops: The absorption rate of hops during the boil was computed by weighing the wet hops after removal from the wort, converting weight to gallons (approximating the weight of wort as about that of water, 8.34 lbs/gallon), and dividing the total number of gallons by the total ounces of hops.

The absorption rate after dry hopping was computed in the same way, but using the hops after removal from the secondary fermenter.  This absorption rate is quite low because of the technique I use that removes much of the beer from the hops, described in Dry Hopping in a Weighted Mesh Bag.

Yields of Steeped Malts: The yields of crystal 20 and crystal 40 are much lower than the values reported by Palmer in his third edition. The steeping was performed by soaking the grain in 2 gallons of water per pound (see http://beersmith.com/blog/2009/03/22/steeping-grains-for-extract-beer-brewing/) for 30 minutes at 160°F.  I’m not sure why my measured yields are so much lower than Palmer’s.

Wort and Break Loss: These numbers are the volumes of wort, hot break, and cold break left in the bottom of a vessel after racking with a 1/2” “auto siphon” without the spacer at the bottom (in order to minimize the loss).  I have noticed that brewing with the combination of extract (Briess liquid malt extract) and steeped grains leaves much more break in suspension, compared with all-grain brewing.  The all-grain brews tend to settle more quickly, leave a denser layer on the bottom, and produce a clearer beer in the end.  As a result, I feel that with extract+steep brewing I need to leave more wort behind during the first transfers.  (I have brewed with Briess LME and no steeped grains, and in those cases the wort has settled nicely and a clear beer was produced; the extract itself doesn’t seem to be an issue, but the addition of steeped grains.)

Weight of Salts:  I used salts marketed by LD Carlson Company and MoreFlavor.  (As determined from the Material Safety Data Sheets (MSDS) available online, the CaCl2 from LD Carlson Company and Brewcraft USA are anhydrous, i.e. CaCl2 instead of the CaCl2·2H2O used by Palmer and sold by MoreFlavor, which changes the amount of each ion contributed by weight of salt.  The CaSO4 from all three companies is CaSO4·2H2O, the same as used by Palmer.)  Using a jewelry scale, I weighed 5 teaspoons in ¼-teaspoon increments (since I add to the mash in ¼-tsp units), and divided by 5 to get a weight per teaspoon.  I repeated the measurements by measuring 5 teaspoons in 1-teaspoon increments and then dividing by 5.  (All measurements were level teaspoons or ¼-teaspoons.)  The resulting per-teaspoon values were close.  I then averaged these two measurements per salt.  The values reported here are, for reasons not entirely clear to me, quite different from those reported by Palmer in “How to Brew” (p. 166).  If you’re trying to predict mash pH or know how much of a salt you’re adding, you may want to weigh your salts yourself for greater confidence.  (A wine-making website that is no longer available gave 2.6 g/tsp for CaCO3, which is an in-between value that might be good to use as a compromise.)

Weight of DME: I measured out Briess Pilsen Light DME into a 1-cup measuring cup three times, and took the average.   Each cup was filled and level with malt extract.  A weight of 5.1 oz translates into 3.1 cups per pound, which is in between the 4⅛ reported by homebrew4less (no longer available online), the 2.4 reported by brewersdirect, and the 2.75 reported by BYO.

Many measurements in this table were not only averaged over a few sessions, but also adjusted in order to make the entire set of measurements be in accordance with predicted measurements.