1

Automated Multicomponent Analysis of Soft Drinks Using 1D 1H and 2D 1H-1H

J-resolved NMR Spectroscopy

Svenja M. Ackermann1,2, Kulvadee Dolsophon3, Yulia B. Monakhova2,4, Thomas Kuballa2, Helmut

Reusch2, Tienthong Thongpanchang3, Mirko Bunzel1, Dirk W. Lachenmeier2* Tel.: +49-721-926-5434, Email: Lachenmeier@web.de

1Karlsruhe Institute of Technology (KIT), Institute of Applied Bioscience, Department of Food Chemistry and

Phytochemistry, Adenauerring 20a, 76131, Karlsruhe, Germany2Chemisches und Veterinäruntersuchungsamt (CVUA) Karlsruhe, Weissenburger Strasse 3, D-76187 Karlsruhe,

Germany

3Department of Chemistry, Faculty of Science, Mahidol University, Rama 6 Road, Bangkok 10400, Thailand

4Spectral Service AG, Emil-Hofmann-Straße 33, 50996 Cologne, Germany

Bruker Biospin GmbH, Silberstreifen, 76287 Rheinstetten, Germany

Institute of Chemistry, Saratov State University, Astrakhanskaya Street 83, 410012 Saratov, Russia

Abstract

Nuclear magnetic resonance (NMR) spectroscopy is evaluated as an efficient analytical technique for

simultaneous identification and quantitation of multiple compounds in alcohol-free beverages. The method was

validated for three different types of soft drinks, including a beverage with high sugar content, a diet product,

and an energy drink. The sample preparation required only 600 μL of degassed soft drink, 70 μL of 0.1% TSP-

d4 in D2O (for referencing and locking), and 100 μL of phosphate buffer (pH=2.89). The simultaneous

quantitative analysis of eleven compounds, such as sugars, flavourings, sweeteners, organic acids, alcohol

(ethanol), vitamins, and amino acids, was achieved using an automated procedure based on the PULCON

principle (pulse length based concentration determination). Recovery rates were between 80% (HMF) and 106%

(ethanol). The limits of quantitation (LOQ) varied between 52 mg/L for saccharin and 12 g/L for sucrose due to

different matrix contents. Sample analysis time is about 25 minutes including sample preparation and automated

data processing. A comparison with conventional methods showed the suitability of NMR for routine analysis of

soft drinks.

Keywords: Nuclear magnetic resonance (NMR), Automated analysis, Soft drink, PULCON methodology,

QNMR

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Introduction

Soft drinks are alcohol-free beverages containing sweeteners, flavourings, preservatives and other ingredients.

These beverages, especially the sub-segment of energy drinks, are increasingly offered on the market. Some

ingredients of soft drinks may contribute to health problems if consumed in excess. For example excessive

consumption of sugar-sweetened soft drinks potentially contributes to obesity (Malik et al. 2006), type 2 diabetes

(Romaguera et al. 2013) or dental diseases (Tahmassebi et al. 2006), and excessive caffeine intake may result in

anxiety and sleep disruption (Lachenmeier et al. 2013). Food laws regulate several compounds including

caffeine, sweeteners, additives, and preservatives, thus, methods to control their legal maximum contents are

required. Furthermore, labelling of nutritional information for some ingredients such as sugars is required. A

variety of conventional methods were applied for the regulatory control of beverages, including reverse-phase

high performance liquid chromatography (HPLC) (McDevitt et al. 1998; Morales et al. 2001; Kritsunankul and

Jakmunee 2011; Grembecka and Szefer 2012), mass spectrometry (MS) (Bergen et al. 2000; Chen et al. 2009;

Tobolkina et al. 2014), vibration spectroscopic methods such as Raman spectroscopy (Ilaslan et al. 2015) and

Fourier transform infrared (FTIR) spectroscopy (Kemsley et al. 1992; Paradkar and Irudayaraj 2002), capillary

electrophoresis (CE) (McDevitt et al. 1998; Frazier et al. 2000; Cortacero-Ramírez et al. 2014), UV spectroscopy

(McDevitt et al. 1998), gas chromatography (GC) (Pan et al. 2005), enzymatic methods (Harms et al. 1999), and

nuclear magnetic resonance (NMR) spectroscopy (Lachenmeier et al. 2005; Charlton et al. 2008; Spraul et al.

2008; Winning et al. 2008; Spraul et al. 2009b; Campo et al. 2010; Maes et al. 2012; Wegert et al. 2012;

Monakhova et al. 2014b). However, by using the most commonly applied techniques, the simultaneous

quantitation of all ingredients of interest was often not possible, making the application of several different

assays for a single sample necessary (such as GC for ethanol, different HPLC or enzymatic methods for sugars,

preservatives and sweeteners etc). During the last decade, NMR has become an extremely versatile tool in the

field of multi-component analysis, i.e. for simultaneous quality control of a large number of compounds

requiring only a single spectrum (Spraul et al. 2009a; Spraul et al. 2009b). Especially with the pulse length based

concentration determination (PULCON) principle (Wider et al. 2006), which is an external quantitation

technique that includes device specific properties into the calculation, multi analysis has achieved the potential

for routine applications.

Another advantage of many NMR methods is their rapidity, without need for separation or derivatisation.

Besides the use of NMR spectroscopy for measuring samples, automated procedures play an important role for

identification and quantitation of multi-component systems, making NMR spectroscopy one of the most efficient

and convenient tools for routine analysis. The fully automated system combines sample transfer, measurement,

data analysis and reporting of results, e.g. exporting into a LIMS (laboratory information and management

system). This study describes the application and validation of an NMR assay for the automated multi-

component analysis of three different types of soft drinks using 1H NMR and 2D 1H-1H J-resolved (JRES) NMR

spectroscopy.

Materials and methods

Reagents, standards and samples

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Reagents and standard compounds were of analytical or HPLC grade (≥ 99 %). Ethanol, D-fructose, D-glucose

and saccharin were purchased from Merck (Darmstadt, Germany). Sucrose, sodium L-lactate, nicotinamide,

sodium N-cyclohexylsulfamate, taurine, 5-(hydroxymethyl)furfural (HMF), and acesulfame K were from Sigma-

Aldrich (Steinheim, Germany). Citric acid (monohydrate) was obtained from Roth (Karlsruhe, Germany), D2O

(99.9 atom% D) and 3-(trimethylsilyl)-propionic acid-d4 sodium salt (98 atom % D) from Sigma-Aldrich

(Steinheim, Germany). The reagents for the buffer monosodium phosphate and phosphoric acid (85 wt. % in

H2O) were sourced from Sigma-Aldrich (Steinheim, Germany).

For each analyte (for full list of initially tested compounds, see Supporting Information), a stock solution with

concentrations of about 5 g/L for major compounds such as sugars or 0.1 g/L for minor compounds e.g.

sweeteners were prepared. Reference solutions were prepared according to in house sample standard preparation

procedures (see below) and spectra were acquired (see measurement settings).

Soft drinks including those used for validation (matrix 1 (cola-orange lemonade mix); matrix 2 (diet lemonade);

matrix 3 (energy drink)) were purchased from grocery stores in Karlsruhe, Germany.

Buffer selection

During method development, buffer systems were optimised for their application to soft drinks with different pH

values without further pH adjustments or titration. To do this, pH values of eight different soft drinks were

measured before and after buffer addition. The optimised buffer was prepared by mixing 10 mL of deionised

water with 7.5 g of NaH2PO4 and 1 g of H3PO4 (85%). The initial pH values of the eight soft drinks tested were

between 2.50 and 3.86; following buffer addition, the pH values ranged between 2.87 and 2.93 (average value of

2.89 +/-0.02).

Sample preparation

Before analysis, the soft drinks were degassed in an ultrasonic bath for 10 min and, if necessary, filtered or

centrifuged (especially required for samples with fruit pulp). For sample preparation, 600 μL degassed soft drink

were mixed with 100 μL buffer solution, and 70 μL internal standard solution (D2O containing 0.1% of sodium

salt of 3-(trimethylsilyl)-propionic acid-d4 (TSP-d4)). For direct measurement, 600 μL of the final solution were

transferred into a 5 mm NMR tube (Wilmad Labglas Inc., Vineland, NJ, USA).

1H NMR experiments

All NMR measurements were performed on a Bruker Avance III 400 Ultrashield spectrometer (BrukerBiospin,

Rheinstetten, Germany) equipped with a 5-mm selective inverse probe (SEI) with Z-gradient coils, using a

Bruker Automatic Sample Changer (Sample Xpress). 1H NMR spectra were acquired using the standard pulse

program noesygppr1d (1D NMR spectra) with presaturation of water signal and a prolonged d7. With a time

domain (TD) of 65 k, 32 scans and 4 dummy scans, a spectral width (SW) of 20.55 ppm (8223 Hz), an

acquisition time (AQ) of 3.98 s and RG (receiver gain) of 16 for the 1H 1D measurement. 2D 1H-1H JRES NMR

spectra were acquired using the jresgpprqf pulse program with 8 scans, 16 dummy scans, an SW of 16.7 ppm

(6684 Hz) in F2 and 0.19 ppm (78 Hz) in F1 dimension.

The temperature was set at 300 K (+/-0.2 K). All spectra were automatically phased and baseline

corrected. Data were acquired under the control of Sample Track Client (BrukerBiospin, Rheinstetten,

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Germany), requiring about 15 min per sample. NMR spectra were analysed using TopSpin version 3.2 (Bruker

Biospin, Rheinstetten, Germany) and MATLAB version 2015b (The Math Works, Natick, MA, USA).

Quantitation

Compounds concentrations were determined using the PULCON principle (Pulse Length Based Concentration

Determination) (Wider et al. 2006; Monakhova et al. 2014a).

To calculate the ERETIC factor (Monakhova et al. 2014a), an water solution containing citric acid (5

g/L), sodium lactate (1.2 g/L) and taurine (4 g/L) was prepared. This solution was measured daily in each series

with the authentic samples. The calculated concentration is documented on a control chart and must not exceed

specified limits. Another internal quality control of the measurement is the width at half height of the TSP

(internal standard) peak. It must not exceed 1.2 Hz, otherwise the measurement or even the sample preparation

has to be repeated.

The following equation was used to calculate the ERETIC factor:

ERETIC=IRe f⋅SW Re f⋅MW Re f

SI Re f⋅CRe f⋅NRe f⋅DF (1)

IRef is the absolute integral (Ref= reference), SWRef is the sweep width (20.5504), MWRef is the molecular weight

(192.13 g/mol for citric acid (water-free), 125.14 g/mol for taurine, and 90.08 g/mol for lactic acid), NRef is the

number of protons generating the selected peak, CRef is the concentration, SIRef is the size of the real spectrum,

which shows the number of data points after Fourier transformation (131072) and DF is the dilution factor

(0.78). The peaks (at δ 3.05-2.75 ppm (N= 4) for citric acid, the doublet at δ 1.60-1.20 ppm (N= 3) for lactic acid

and the triplet at δ 3.273-3.289 (N= 2) for taurine were used to calculate the ERETIC factor. The average

ERETIC value was used for quantitation.

The analyte concentration (CX ) in authentic samples was calculated using the following equation:

CX=I X⋅SW X⋅MW X⋅NSRe f⋅PulseX

SI X⋅ERETIC⋅N X⋅NSX⋅PulseRe f⋅DF (2)

IX is the absolute integral, DF is the dilution factor (0.78), NSX and NSRef are the number of scans for spectrum of

sample and number of scans for the reference respectively, SIX is the size of real spectrum (131072), PulseX and

PulseRef are the respective pulses and ERETIC is the ERETIC factor (see eq. 1).

As an exception sucrose was quantified differently because of overlapping peaks with other substances

in the 1D 1H NMR spectrum. The quantitation was performed with 2D 1H-1H J-RES NMR spectroscopy (see

Figue 1C). Therefore, a series of different concentrations was prepared in water and a linear calibration curve

was determined. The resulting linear equation was integrated in the automated analysis to calculate

concentrations.

Automated analysis of NMR spectra

The automated procedure for the analysis of soft drinks was developed in MatLab. The routine includes NMR

spectra import, extraction of data points, baseline correction, integration, quantitation according to the PULCON

5

principle (see quantitation) and reporting of results as excel and text (txt) files for direct import in the

laboratory’s LIMS system (Limsophy, AAC Infotray AG, Winterthur, Switzerland).

Validation experiments

For spiking experiments, three different types of soft drinks (a beverage with high sugar content (matrix 1), a

light/diet product (matrix 2), and an energy drink (matrix 3)) were used. Within each series, a reference 1H NMR

spectrum of a non-spiked soft drink sample was acquired.

A set of authentic samples was additionally measured for the sweeteners, acesulfame K (n = 22), saccharin (n =

23), and sugars, that is sucrose (n = 68), fructose (n = 102), and glucose (n = 97). The concentrations were

compared using reference methods (HPLC-UV/DAD methods for sweeteners, DIN EN 12856:1999-07, German

Institute for Standardization 1999; enzymatic method for sugars, OIV MA-E-AS311-02 realised on a Random

Access Analyzer) to evaluate the developed NMR method by means of the relative sensitivity (Mandel 1964).

The “relative sensitivity” (RSNMR/other method) reflects which of the methods has the greater ability to detect a

difference in the actual amount of the analyte. If RSNMR/other method appreciably exceeds unity, the NMR approach

will have the better sensitivity. The opposite conclusion holds when RSNMR/other method is clearly smaller than unity.

The calculation was done according to the mathematical procedure described by Mandel (1964).

For the sample preparation of the spiked solution, each pure compound was weighed and dissolved in 20-50 mL

of each soft drink matrix. Then at least five subsequent dilutions with soft drink matrix were made along the

concentration range specific for each compound in 10 mL volumetric flasks. These concentrations were chosen

in accordance with typical concentration ranges for the selected compounds in soft drinks or they reflect the

range around the legal maximum content for official food control.

For sucrose an external series of ten calibration standards in the range of 0.09 -150 g/L was prepared in

deionised water using a stock solution of 150 g/L. Additionally five spiked solutions with similar content

(around the concentration normally used in soft drinks) were prepared and measured in each matrix. Spiking

solutions were prepared for NMR measurement according to the sample preparation for soft drinks described

above.

The recovery was determined with five similar concentrations in every matrix and the average of these

values of each matrix was used to establish a recovery range, which shows the variation of the recovery values

for the different matrices used.

The limit of detection (LOD) and the limit of quantitation (LOQ) were calculated according to DIN

32645:2008 (German Institute for Standardization 2008) using statistical software Valoo 2.7 (2014) (Analytik

Software, Leer, Germany). To determine the variation coefficient, five different concentrations were prepared in

each matrix, analysed and statistically evaluated. For the final result the poorest/highest variation coefficient

obtained was used.

Results and discussion

Application of NMR spectroscopy to soft drinks

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Many types of different soft drinks are available on the market, and their compositions (both qualitative and

quantitative) vary considerably. In total, 36 different ingredients (i.e., sugars, flavourings, sweeteners, organic

acids, alcohols, vitamins) were identified (Supporting Information), which can be present in soft drinks in

concentrations that are of interest regarding official food control.

To evaluate whether a quantitative NMR spectroscopy approach is suitable, proton spectra of these 36

commercially available, potential soft drink ingredients were acquired and compared to the spectra of authentic

soft drink samples. For 20 of the tested compounds, direct quantitation by peak integration was not possible.

This mostly affects compounds, which have their resonances in the mid-field region (around 3.3-4.1 ppm), where

intensive and overlapping peaks of carbohydrates and other substances are found. The large signals of the main

carbohydrates – sucrose, glucose and fructose hide comparably small peaks of other, lower concentrated

ingredients. This is a well-known problem and has been described earlier, for example for the analysis of honey

by using NMR spectroscopy (Ohmenhaeuser et al. 2013).

Also the attempt to use a JRES experiment to quantify these substances as performed with sucrose

failed due to the still crowded mid-field region and the low concentrations of the substances. The main

advantage of JRES instead of 1D 1H NMR for quantitation is at first the increased spectral dispersion and second

the information about the J-coupling in a second dimension. On the other hand, the quantitation at lower

concentrations is error prone due to lower sensitivity and overlap of the dispersive tails of nearby signals

(Ludwig et al. 2009). Hence a 1D 1H NMR spectrum is more suitable and practicable for quantitation.

For further five compounds recovery values were found to be too low (< 80%), LOD and LOQ too high,

or the quantitation has to be optimised (e.g., with integrated line fitting regarding peak overlap). Finally, it was

possible to identify peaks of eleven compounds well enough separated for integration, which are listed in Table

1. Table 1 also contains information for quantitative analysis using the PULCON methodology such as

molecular weights, the number of protons and typical concentration ranges in soft drinks or their legal maximum

limits.

Most of the signals do not overlap with each other or interfere with matrix peaks, however, in some

cases this may occur. For example, only one part of the aromatic saccharin peaks were integrated (see Figure 1B)

due to overlap with other matrix inherent substances. Therefore, a factor was calculated considering the changing

proton content for this specified resonance range. The factor is an average value, which was determined from

varying saccharin concentrations.

For the carbohydrates glucose and fructose different anomeric and tautomeric forms exist in aqueous

solutions. Also, water suppression influences the surrounding spectral area especially for the anomeric glucose

peaks located around 4.6 and 5.2 ppm (Spraul et al. 2009a). The α-and β-anomers of the pyranosidic form are

predominant for glucose with around 30 and 70 %, respectively, at pH 2.98. To quantitate glucose, the peak of α-

glucopyranose (5.20-5.26 ppm, see Figure 1B) was used because it is only slightly affected by water suppression

(Spraul et al. 2009a). Due to the fact that there is still an impact of water suppression, and to determine the total

content of glucose and not just of the α-anomer, the calculation of a correction factor for glucose is necessary.

For this reason a factor from varying glucose concentrations was determined and included into the calculation.

The same was done for fructose, which exists in at least five tautomeric forms in solution (Barclay et al.

2011). The peak chosen for quantitation (see Figure 1A) originates from more than one tautomer (4.083-4.128

ppm) therefore a factor from varying fructose concentrations was calculated to determine the full fructose

content.

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The peaks used for integration of the eleven substances are shown in Figure 1. The integration areas

(chemical shift areas) used for automatic integration, the multiplicity and the proton responsible for the signal are

listed in Table 1.

Validation studies

Based on previous experience in validating quantitative multicomponent NMR assays (Monakhova et al. 2014b),

validation was performed “in matrix” and not just in aqueous standard solutions. As ingredient concentrations in

soft drinks vary considerably (see Table 1), all compounds were arranged in groups according to their typical

contents in soft drinks (see Table 2). For each group five concentrations for spiking were defined (Table 2). The

spiking experiments were carried out in each of the three selected matrices to show the variations between and

influence of the selected matrices. Three different matrices were selected to cover all “extrema” from small

amounts and less ingredients as in matrix 2 to high contents and variety of ingredients as in matrix 3.

LOD and LOQ values for the investigated compounds are listed in Table 3. The LODs varied in the

range of 7 mg/L to 181 mg/L (without sugars), with the lowest values being determined for lactic acid (7 mg/L)

and saccharin (14 mg/L) and the highest value being found for ethanol (181 mg/L). The LOQ values (without

sugars) were in the range between 52 mg/L (saccharin) and 665 mg/L (ethanol). The three sugars have much

higher LODs and LOQs with sucrose showing the highest values (LOD 3.4 g/L and LOQ 11.7 g/L). This is due

to the wide concentration range chosen (glucose and fructose 1-50 g/L and sucrose 1-100 g/L) and the high

content already present in matrix. Another reason why sucrose has high LOD and LOQ values is the lower

sensitivity of the JRES signal. As mentioned before, sucrose is the only compound quantified with 2D 1H-1H

JRES and external calibration.

Unfortunately, the LOD (23 mg/L) and LOQ (82 mg/L) of the heat treatment marker HMF is higher

than the demanded concentration of 20 mg/L. However, this value is just a recommendation from A.I.J.N

(European Fruit Juice Association) for fruit juice and not for soft drinks. The LODs and LOQs of all other

analytes are lower or within the demanded concentration range for the analysed soft drink ingredients. Thus

NMR spectroscopy can be considered as a suitable tool to monitor soft drinks by official food control authorities

(Thompson et al. 2002; Bièvre et al. 2011).

Recovery values were determined at five similar concentrations with the actual concentration, however,

depending on the analyte (see Table 4). Recovery data of the three matrices were pooled to describe a recovery

range, with values between 80 % (HMF, matrix 2) and 106 % (ethanol, matrix 1). The widest range was obtained

for sucrose (90-104 %). Good recovery values (i.e. >94%) are considered those with good consistency between

the different matrices such as the ones obtained for fructose, glucose, citric acid and acesulfame K (see Table 4).

The lowest recoveries were determined for HMF (80-90 %) and saccharin (85-97 %). The low recovery

of HMF could be due to the general tendency of aldehydes to hydrate especially under acidic conditions, similar

to the degradation of acrolein (Kächele et al. 2014).

Variation coefficients were determined at five different concentration levels (see Table 2) with the

highest value of the different matrices being reported (in Table 4). As the variation coefficient was calculated

along the concentration range in soft drinks, typically at extremes and within the necessary concentration range

for regulatory control, potential variation of results of the analytical method at high and low concentrations has

been taken into account (Thompson et al. 2002; International Organization for Standardization (ISO) 2005;

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Bièvre et al. 2011; Joint Committee for Guides in Metrology (JCGM) 2012). The lowest precision was found for

nicotinamide and saccharin with coefficients of variation over 10 %. In general, however, the method has been

proven to be sufficiently precise for quantitative analyses in official soft drink control. Finally we were able to

quantitate eleven out of 36 substances. Six of these eleven analytes have regulatory limits, which have to be

checked in official food control. For the other five, there is no regulatory limit, but the manufacturers’

declaration can be controlled.

Comparison with other methods

A series of samples that contained sweeteners (acesulfame K, saccharin) and sugars (sucrose, glucose, fructose)

at different concentration levels were examined with both NMR and reference analytical methods. Then, the

results obtained from the conventional method were plotted versus the NMR-determined values (Figure 2 for

fructose) and a straight line was fitted to the data. Taking into account that both quantities are subject to error,

Deming regression was applied (Mandel 1964, Skiera et al. 2012). For example, the functional relationship

between the enzymatic fructose values (y) and the NMR-determined values (x) was found to be given by

y = 1.04x – 1.79

The RSNMR/ARENA was calculated to be 0.96, which indicates that both methods provide a similar analytical

performance.

For each compound (saccharin, acesulfame K, glucose, and sucrose) NMR spectroscopy and the

particular other reference method was compared as described above. The calculated RSNMR/other Method values were

between 0.8-1 (data not shown), which shows that NMR is a suitable analytical method for soft drink analysis.

Application in routine analysis

1H NMR spectroscopy represents a most efficient analytical technique in food and beverage control. However,

the increasing number of samples per year (due to centralization of official laboratories in, for example,

Germany) demands for accurate and efficient high-throughput data processing workflows. Intense ongoing

research activities focus on solving these technical difficulties and some NMR analyser packages were already

commercialised (e.g., "Juice Screener" and “Wine Screener” by Bruker) (Spraul et al. 2009a; Spraul et al.

2009b). Such systems are fully automated, but users have no opportunities for further package development or

applying these systems to other matrices as it is installed on a NMR spectrometer in the form of a “black box”

system.

Therefore, in-house automated procedures for the analysis of soft drinks have been developed. The

routine includes NMR spectra import, extraction of data points, baseline correction using moving average filter,

integration, quantitation according to the PULCON principle (see quantitation) and reporting of results. Only the

path to the selected experimental series and the ERETIC factor are necessary as input parameters for the

calculations. The report for each experimental series contains concentrations of the 11 analytes in each sample as

excel and txt files for direct importation into LIMS. This algorithm is characterised by high throughput as it

allows to analyse a large number of samples without human intervention within reasonable time (for example, it

requires about 3 minutes for 25 samples).

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Conclusions

NMR spectroscopy is a fast and efficient methodology to quantitatively monitor ingredients of interest in soft

drinks. The detection limits allow for controlling legal maximum limits (e.g., of sweeteners) as well as

manufacturer declarations. Furthermore, performance parameters of the developed NMR spectroscopic method

are similar to other methods used for soft drink analysis. The developed automatic routine provides an integrated

workflow that performs all necessary steps (spectra import, extraction of data points, baseline correction using

moving average filter, integration, quantitation) for quantitative analysis. According to the obtained results, the

developed protocol provides an optimal data processing workflow for NMR analysis of soft drinks, which can be

simply transferred to other matrices as well.

Future work will focus on the quantitation of compounds represented by overlapping peaks in the 1H

spectrum. To analyse these compounds, the application of line fitting or multivariate regression techniques

appears promising.

Acknowledgements The authors are grateful to Margit Boehm, Bernd Siebler, Jürgen Geisser and Andreas

Scharinger for excellent technical assistance. YBM was supported in the framework of the state task of the

Russian Ministry of Education and Science (project 4.1708.2014K). Scholarship support from the Thailand

Research Fund through the Royal Golden Jubilee PhD Program (Grant No. PHD/0032/2554) to KD and TT is

acknowledged.

Conflict of Interest The authors declare that there is no conflict of interest regarding the publication of this

paper. This article does not contain any studies with human or animal subjects.

Informed consent: Not applicable.

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Table 1 Information about selected compounds in soft drinks

Class ofcompounds

Substance Concentration ranges in soft drinks / maximum limits

Chemical shift range used for integration [ppm], multiplicity of signal

Number of protons

Molecular weight

1 Sugars Glucosea 1 -50 g/L (A.I.J.N.)d 5.20-5.26, doublet, α-anomeric H

1 180.16

Fructoseb 1 -50 g/L (A.I.J.N.) 4.083-4.128 multiplet of different tautomeric forms

1 180.16

Sucrosec 1 – 80 g/L (A.I.J.N.) 4.1951-4.2208 (ppm)(-6.729)-6.8175 (Hz) doublet, C3-H of fructose ring

1 342.30

2 Sweeteners Saccharin H Max. 80 mg/L(ZZulVd / 1333/2008)

7.78-7.88, part of multiplet from benzene ring

4 183.18

Acesulfame K Max. 350 mg/L(ZZulV / 1333/2008)

5.65-5.70, singlet, H in ring

1 201.242

Cyclamate Max. 250 mg/L(ZZulV / 1333/2008)

1.6639-1.7694, multiplet, part of cyclohexyl ring

2 201.22

3 Organic acids

Citric acid (water-free)

0.1 – 10 g/L (A.I.J.N.)

2.9376-3.0256 part of multiplet, due to stereocenter

2 192.12

Lactic acid Max. 500 mg/L (A.I.J.N.)

2.9376-3.0256 doublet, methyl group

3 90.08

4 Alcohols Ethanol Max. 2000 mg/L 1.145-1.20 triplet, 3 46.07

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(Leitsätze AfG)d methyl group5 Vitamins Nicotinamide 10 – 15 mg

(DGEd, daily requirement)

9.13409-9.1973 multiplet, ortho ring position beside N

1 122.13

6 Other compounds

HMF Max. 20 mg/L (A.I.J.N.)

9.43-9.463 singlet, aldehyde group

1 126.11

a For quantitation the peak of α-glucopyranose was used.b For quantitation a peak that stems from different tautomeric forms of fructose was used.c Sucrose was quantified with 2D 1H-1H JRES NMR with a linear calibration curve prepared in water, the area of

integration in the 2D spectrum possesses a ppm and a Hz range.d abbreviations: A.I.J.N. (European Fruit Juice Association); ZZulV (Zusatzstoff-Zulassungsverordnung, is a

German regulation for food additives); Leitsätze AfG (German principles for alcohol free beverages); DGE

(German Nutrition Society); FrSaftErfrischGetrV (German regulation for fruit juice and soft drinks).

Table 2 Validation studies for different groups of compounds

Group

Compound 1 2 3 4 5 Unit

1 Fructose 4 10 25 30 50 g/LGlucose

2 Ethanol 0.4 0.8 2 4 8 g/L3 Saccharin H 50 10

0250 500 1000 mg/L

Acesulfame KCyclamate

4 HMF 10 50 100 250 500 mg/LNicotinamideLactic acid

5 Citric acid 100 200

300 400 500 mg/L

6 Sucrosea 45 g/L

a For sucrose a spiking series in each matrix was prepared five times, the determination was performed using an

external calibration curve in water (linear concentration range 0.9-100 g/L with r = 0.9995). The linear equation

was integrated in an automated analysis to determine concentrations.

Table 3 LOD and LOQ for selected compounds in soft drinks

Compound LOD [mg/L] LOQ [mg/L]

Demanded concentration [mg/L]

Hydroxymethylfurfural a 23 82 20Ethanol 181 665 max. 2000Fructose 1,953 6,725 b 2,000-50,000Glucose 1,484 5,187 b 2,000-50,000 Sucrose 3,362 11,657 b 1,000-80,000 Lactic acid 7 100 max. 500 Citric acid 74 262 100-10,000Nicotinamidec 21 76 10-15 mg (daily dose) Saccharin H 14 52 max. 80Acesulfame K 22 82 max. 350Cyclamate 17 64 max. 250

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a LOD and LOQ are higher than the recommended performance level. However 20 mg/L is just a

recommendation from A.I.J.N. for fruit juice and not for soft drinks.b All carbohydrates are higher than demanded concentration due to the wide concentration range from 1-50 mg/L

for glucose and fructose and 1-100 g/L for sucrose and because of the high content of these substances already

present in matrix.c The values for nicotinamide appear to be high; however, in fact, the demanded concentration is a recommended

daily dose (mg) and not a maximum concentration.

Table 4 Recovery values [%] at five similar concentrations in each matrix and summarised average ranges and

variation coefficient for all matrices.

Entry Substance Matrix 1 average value

(n = 5)

Matrix 2 average value

(n = 5)

Matrix 3 average value (n = 5)

Recovery range[%]

Variation coefficient*

[%]1 Hydroymethyl-

furfural84 (10 mg/L) 80 (10 mg/L) 90 (10 mg/L) 80-90 3.6

2 Ethanol 106 (830 mg/L)

100 (691 mg/L)

102 (751 mg/L) 100-106 12.6

3 Fructose 96 (25 g/L) 100 (25 g/L) 97 (25 g/L) 96-100 8.94 Glucose 100 (25 g/L) 102 (25 g/L) 99 (25 g/L) 99-102 4.15 Sucrose

90 (45 g/L)104 (45.2

g/L)91 (45 g/L) 90-104 6.7**

6 Lactic acid 103 (87 mg/L)

95 (85 mg/L) 98 (85 mg/L) 95-103 4

7 Citric acid 96 (4.57 g/L) 94 (4.59 g/L) 97 (4.57 g/L) 94-97 4.38 Nicotinamide 103 (10

mg/L)98 (10 mg/L) 96 (10 mg/L) 96-103 10.2

9 Saccharin 85 (37 mg/L) 97 (47 mg/L) 94 (41 mg/L) 85-97 11.210 Acesulfame K 98 (85 mg/L) 98 (84 mg/L) 95 (94 mg/L) 95-98 3.111 Cyclamate 91 (98 mg/L) 88 (96 mg/L) 91 (96 mg/L) 88-91 4.7

* Variation coefficients were determined at five different concentration levels (see Table 2) except for sucrose.

The highest calculated value of the three matrices is given.

** Five replicates of similar concentrations were tested to determine the coefficient of variation.

Figure 1 A, B) 1D 1H NMR (400 MHz) spectra of the analytes in matrix 2. Signals used for quantitation are

highlighted with red boxes; A) low field region 1-4.5 ppm and B) high field region 4.6-9.6 ppm. C) 2D 1H-1H

JRES NMR spectrum of sucrose dissolved in matrix 2. The integrated area is highlighted.

Figure 2 Fructose concentration as determined with an enzymatic method (ARENA) plotted against fructose

concentrations analysed by using NMR spectroscopy. The straight line was fitted by Deming regression, y =

1.04x – 1.79.