Application Note 6: On-line Reaction
Monitoring of Alcoholic Fermentation
NMR spectroscopy is an excellent technique for monitoring organic reactions due to its high degree of functionalgroup specificity. This allows one to integrate over one or more sections of the spectrum to track the increase ordecrease of the species of interest.
The Spinsolve high-resolution benchtop NMR spectrometer now makes such reaction monitoring extremely easy toset up and run for many reaction processes. It can be installed directly in a fume hood of a chemistry lab to monitor
the progress of chemical reactions on-line. Reactants can be pumped in continuous mode from the reactor to themagnet and back using standard PTFE tubing.
Fermentation is a naturally occurring chemical processes – and indeed one of the most popular around the world!
In this application note we show how easy it is to monitor a simple fermentation process, and to easily get chemical
conversion rates and to see where the optimal end point has occurred.

OptimalEnd PointFERMENTATION
The alcoholic fermentation in juice is governed by the conversion of fructose and glucose into ethanol and carbon
dioxide:C6H12O6

2 C2H5OH + 2 CO2The production of carbon dioxide creates the characteristic bubbles observed during fermentation.
A typical 1H NMR spectrum of a fermenting juice sample is shown in Figure 1. Note that the CH3 peak of the ethanol
is well separated from other peaks in the spectrum. The integral of this peak can be used to quantify the amount ofethanol in the sample.

Water
Ethanol OH
Sugarsx 50
Ethanol CH2
Sugarsx 50
Ethanol CH3

5.5

5.0

4.5

4.0

3.5

3.0
2.5
f1 (ppm)

Figure 1: A typical 1H NMR spectrum of a fermenting juice sample.

2.0

1.5

1.00.5

FLOW SETUP AND CALIBRATION
A typical setup for on-line monitoring is shown in Figure 2 (a). The reaction mixture is pumped through the bore ofthe magnet using a 2.5 mm od (1.8 mm id) PTFE tube.

Direction of flow

(b)

(a)

Spinsolve

PumpReactor
PumpReactor

Figure 2: (a) A typical setup for on-line reaction monitoring. (b) Photo of the system setup used to monitor
fermentation.

The system was calibrated and shimmed with 400 mL of tap water at a constant flow rate of 0.5 mL min-1. The
Reaction Monitoring protocol was then set up to record a 1D Proton spectrum every 30 s. After 5, 20, 35 and 50
minutes, 1 mL of ethanol was injected into the reactor. This corresponds to ethanol volume concentrations of 0.25,0.5, 0.75 and 1.0%.

Figure 3 (a) shows how the signal of the CH3 peak changes over time. There is a clear step response in the peak
integral about two minutes after each injection. This is the time it takes for the sample to be transferred from thereactor to the measurement volume. It could be shortened by using a transfer tube with a smaller inner diameter, but
for the experiment described in this note such a delay was not critical.

PTFEantube,
i.d. 1.8 ofmm,
0.5accuracy
mL/min of theThe integral graph in Figure 3 (b) provides an easy calibrationUsingand also
indication
theReactor: 400 mL of tap watermeasurement. After 60 min, the average integral value is 42.5Afterunits,
to 1mLan ethanol
concentration
5, which
20, 35 corresponds
and 50 minutes,of ethanol
wasof 1%. The standard deviation of the data is 1.2 units or 0.03%
ethanol
injectedintoconcentration.
the reactor. This corresponds toethanol concentrations of 0.25, 0.5, 0.75 and 1.0%.
It takes about 2 min for the reactant to reach themeasurement volume.
(a)(b)
CH3 triplet
used for signal integration

4540

Y

Methyl peak integral

3550 min
35 min15 min30250.25% steps

65 minadded 1 mL ethanol

20151055 min

Baseline

02.5

2.0

1.5
1.0f1 (ppm)

0.5

0.00102030

40 50 60time (min)Figure 3: The spectral region of the CH3 peak over time (a), and the integral of this peak (b)708090MONITORING FERMENTATION
For this experiment, 400 mL of apple juice was inoculated with some brewer’s yeast. The system was shimmed
initially on the flowing juice sample, and the Reaction Monitoring protocol was then set up to record a 1D Proton
spectrum once every 10 min. A photo of the setup is shown in Figure 2 (b).
Figure 4 shows some spectra taken during the first hours of the reaction (a) and the methyl peak integral (b). Since
the fermentation produces CO2 gas, it is inevitable that gas bubbles will eventually reach the measurement volume.
As a result, the spectrum will be severely distorted if a gas bubble is present during an acquisition. A good example
can be seen at 10 hours in Figure 4 (a). The integral values of such bad spectra can easily identified as outliers inFigure 4 (b) and filtered out when processing the data.

(a)

(b)

40
13 hours

Y

35
10 hours
8 hours
6 hours
4 hours

Methyl peak integral

12 hours

30
25
20
15
102 hours

5start

0
4.0

3.5

3.0

2.5 2.0 1.5
f1 (ppm)

1.00.50.00 1 2 3 4 5 6 7 8 9 10 11 12 13time (h)Figure 4: The first 13 hours of the fermentation. (a) Spectra, (b) methyl peak integral

(a)

(b)

Maximum
Conversion
Rate

OptimalEnd Point

OptimalEnd Point

Figure 5: (a) The ethanol percentage as measured on-line during a fermentation process after filtering distorted datapoints. The slope of this curve gives the ethanol conversion rate (b).

The fermentation process was monitored for a total duration of ten days. With the calibration data from Figure 3 (b)the ethanol percentage and conversion rate can be quantified. This is shown in Figure 5. The start and end points of
the reaction are easily identified after 3 and 150 hours, where the conversion rate is basically zero. The conversion
rate reaches a maximum at 14 hours after inoculation.
This shows that on-line reaction monitoring is a valuable tool, as it enables the user to take appropriate action if theprocess goes along an unexpected path or when the reaction reaches its end point.

Conclusions
It has been shown that a simple flow loop setup allows on-line reaction monitoring on a lab bench. Shimming wasperformed at the start of the experiment on the reactant itself. No extra shimming was required during the ten day
long experiment, although it is possible if necessary. Even gas bubbles in the measurement volume did not disrupt
subsequent measurements.

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