Dissolved Oxygen in Beer: How It Compares to Total Package Oxygen

When it comes to questions about oxygen in beer, I think the one I’m asked most often is, “What is the difference between dissolved oxygen and total package oxygen (TPO)?”  The main source of this confusion is that when measuring O2 in packages, the O2 in the headspace is often overlooked. If you don’t take headspace oxygen into account, then you are measuring a partial concentration, period. So let’s talk about the differences and what each one tells you.

A significant number of craft brewers have a dissolved oxygen (dO2) analyzer they use to measure the dO2 content of their beer in process. The most common point of measurement is the finished beer tank. The beer in a finishing tank will have O2 pickup from the empty vessel and from the filtration process, plus it will pickup more O2 as it goes through packaging.

Once the beer is packaged, however (assuming good packaging,) rapid O2 pickup from outside sources all but stops. So what can we tell about how much oxygen actually made it into the package?  It is not a simple matter of measuring the O2 in the beer.  The package must be shaken to equilibrate the oxygen in the beer and the headspace before the 02 in the beer is measured, and that number must then be used to calculate your TPO. Let’s think about what it is possible to measure and what each thing tells you.

Package dO2 –

The easiest measurement to take on packaged beer is the dO2 of a package just off the filler without shaking the beer. It is important to measure as quickly as possible, so the product does not “consume” the oxygen in the beer. (Residual or live yeast may be hungry, plus oxidation by trace metals, etc.) In some packages there is a measurable difference within five minutes and in other packages the rate of oxygen consumption takes significantly longer, sometimes hours. It is always best to measure as quickly as possible.

This unshaken package measurement represents the combination of the dO2 of the beer at the base of the filler and the oxygen pickup of the filler. Oxygen picked up at the filler can be quite variable. Most fillers run at about 25 to 50 percent deviation, but in some cases it can be up to 100 percent deviation. The best way to measure the percent deviation is to determine the dO2 at the base of the filler and then measure six to ten packages and determine the variation of each package as compared to the average of all the containers. But remember: this measurement only tells you what is in the liquid. When measuring unshaken packages, any gas in the headspace is left uncounted.

Shaken Package dO2 –

When you shake a package of beer so that the partial pressure of the oxygen in the liquid is equal to the partial pressure in the headspace, it changes the characteristics of the oxygen partitioning in the package. If most of the oxygen in the package is locked in the liquid, then shaking the container will move the O­2 from the liquid to the headspace until equilibrium is reached.

So, you have measured the dO2 and then shaken the package. Now what do you do with the data? If you really want to quantify the TPO of the package you have to take into account the headspace oxygen. To do this accurately you need to know the headspace volume and the package temperature.

Total Package Oxygen –

When using the dissolved oxygen measurement, the TPO can only be calculated from a shaken package. To do this calculation you also need to know the headspace volume, liquid volume and the package temperature. The temperature and the headspace volume are critical values and small inaccuracies can alter the results significantly, but the liquid volume may be estimated by using the average fill volume. Once you have your figures, then you can use a TPO calculator to determine the concentration from your initial DO2 measurements.

My final thought is to not skimp on how much you shake the packages. Cold containers should be shaken for five minutes and room temperature cans or bottles need about three minutes. If you’d like a copy of a TPO calculator built into an Excel spreadsheet, then please click here to request one.



Validation Techniques for Optical Dissolved Oxygen Sensors in Beer

I’ve recently spent a few posts discussing measurement validation, mostly with a focus on situations where instruments were reading properly and there was a problem somewhere in the brewing process. Now I’d like to continue the discussion with an example of the reverse: the beer was actually okay, but sensors were in need of validation and calibration.

Last week I visited a brewery where they were getting unusually high portable dO2 measurements on beer that had been fermenting for a week. After a day of sitting in a conical fermenter, beer usually has a dissolved oxygen concentration of less than 5 ppb, but in this case their optical oxygen analyzer was reading 30 ppb. The brewer was wondering if there was an issue with his fermentation, so here’s what we did:

  • We measured the beer in the fermenter with a second instrument that we could easily calibrate and validate, should the reading fall outside the expected range.
  • Then we measured 99.999% N2 calibration gas on both instruments.

Here’s the reasoning behind these steps:

  • Optical oxygen analyzers will drift upward over time due to photo bleaching of the fluorescent matrix.
  • Using a 99.999% N2 or CO2 calibration gas to check the zero of the instrument is a way to validate low-level (less than 200 ppb) measurements. It is important that the pressure of the gas flowing through the instrument be as low as possible. (Do this by controlling the gas flow at the inlet to the instrument and opening the analyzer flow valve completely. Ideal gas flow should produce about 2-5 bubbles per second when the outlet tube from the analyzer is placed in a few inches of water.)
  • If instrument readings using calibration gas are above 3 to 5 ppb, then it’s probably time to calibrate the instrument.

In this case we discovered that both instruments needed calibration. On the beer, one was reading 8 ppb and the other 30 ppb. On the calibration gas, the first instrument read 3.5 ppb and the second read 16 ppb. We didn’t proceed to calibrate right then, but knew that once they were calibrated they would agree.

My final thought is to validate whenever a reading does not seem logical. In this case, the brewer was wondering if there was an issue with his fermentation, but it wasn’t his process, it was the need for instrument maintenance.

Using Basic Verification Techniques to Qualify Brewery Instrumentation

Any method of analysis — whether measuring pH, turbidity, sensory, dO2, TPO, or CO2 –will have some inherent error. I think that it’s always best to acknowledge problems up front and be ready to deal with them, so today I’d like to talk about understanding best practices and ways to anticipate and quantify errors, especially if you are in the process of qualifying a new instrument.

I’ve seen a lot of instrumentation improvement through the years, ranging from ease of use and maintenance to complexity of capability. However, even the most sophisticated instruments need the balance of statistical analysis and upfront testing to ensure reliable quality and minimal person-to-person variability. By learning the ways to test and verify an instrument during the demo period or just after purchase, we can learn the strengths and limitations of our analyzer, and know what best practices should be implemented before the data we gather is used in daily production.

Regardless of the type of analysis, the more statistical data we capture the higher the certainty that we understand our instrumentation, but even large amounts of data won’t help if we don’t understand the way our instruments fit into the context of the parameter being measured. For example, we may want to measure the turbidity of beer, but if we don’t understand that copious bubbles can throw off our measurements and that we need to either de-carbonate our product or keep it under pressure, then we can gather all the data points we want, but they won’t tell us what we need to know.

So understanding the context of the thing we want to measure is our first step, but assuming we have that part under control, how can we then experiment with the data from our new instrument, to ensure our measurements are meaningful and that we can trust our results? Here are a few ideas:

  • Take multiple measurements. If you’re using a portable instrument, measure multiple types of samples that are similar, but different, and measure multiple times. For example, with a dO2 meter choose three bright tanks that were recently filled and move between the tanks ten times. Record the readings and look at the variability. If this is done in a short amount of time on filtered beer, the readings shouldn’t decay much during testing.
  • Have three different people run the same tests, each rotating between the same samples. Record the values and see if there is user variability. Do this ten times per person and analyze the data. Is there a technique issue that yields an erroneous result? If you can correct it, then that information can be used to education future users.
  • Understand the variability and expectations of your process. Say you are evaluating a new TPO analyzer. The more you know about your filler, the easier it will be to evaluate your instrument, but statistics can help you regardless. For example, if your instrument is able to measure TPO and not just dissolved oxygen, understand whether it can also compare results on shaken and unshaken packages. Most of the new systems sold today can do both and should yield the same TPO concentration for packages, whether shaken or unshaken. If the results don’t match, understand why. It may point to a problem with the instrument.

My final thought is to use good statistics to drive your process control. Don’t base a decision on one data point. Whenever possible, validate your analyzers on a regular basis. I’ll have more on process and portable instrumentation validation in my next post.

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