# Multi-solvent suppression ultrafast 2D COSY for high-throughput wine screening

Pia S. Mayer, Jérémy Marchand, Marine P. M. Letertre, Jean-nicolas Dumez,

Søren B. Engelsen, Patrick Giraudeau

► To cite this version:

Pia S. Mayer, Jérémy Marchand, Marine P. M. Letertre, Jean-nicolas Dumez, Søren B. Engelsen, et al.. Multi-solvent suppression ultrafast 2D COSY for high-throughput wine screening. Magnetic Resonance in Chemistry, In press, 10.1002/mrc.70078. hal-05466646

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1 **Multi-solvent suppression ultrafast 2D COSY for high-throughput wine screening**

2 Pia S. Mayer¹*, Jérémy Marchand², Marine P.M. Letertre², Jean-Nicolas Dumez³, ², Søren B.

3 Engelsen¹ and Patrick Giraudeau²*

4 ¹Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958,

5 Frederiksberg C, Denmark

6 ²Nantes Université, CNRS, CEISAM, UMR 6230, Nantes, France

7 †Passed away in August 2025

8 *correspondence to pia.mayer@food.ku.dk; patrick.giraudeau@univ-nantes.fr

9

10 **Abstract**

11 Nuclear Magnetic Resonance (NMR) is a powerful analytical tool for wine analysis, to identify
12 and quantify a metabolite composition. However, a limiting factor of 1D ¹H NMR spectroscopy
13 is the overlap of signals in complex mixtures. While conventional 2D NMR methods disperse
14 the signal over two dimensions, they are associated with long experiment times. In the case of
15 wine, interesting metabolites are also often masked by the large water and ethanol peaks. To
16 improve wine analysis by NMR, a method that uses the advantages of 2D NMR while
17 suppressing solvent signals and being within the timeframe of 1D NMR is highly desirable.

18 Interleaved ultrafast COSY (iuf-COSY) offers a possibility for fast acquisition of a 2D
19 spectrum and has been demonstrated as a powerful tool in metabolomics studies, as a
20 complement to 1D NMR methods. Here, the iuf-COSY experiment has been adapted to
21 suppress water and ethanol signals by using a shaped pulse and a NOESY block. This approach
22 efficiently suppresses solvent signals and gives a 2D COSY spectrum of wine in approximately
23 20 min. Important metabolites that originally were covered by solvent signals could be
24 annotated, while minimal interleaving artefacts were observed. This is an efficient method to
25 acquire a COSY spectrum of a wine sample, which can aid with the identification and
26 discrimination of metabolites in future wine studies through additional cross peaks, while
27 working within a high-throughput time scale. This might be particularly interesting in the field
28 of wine metabolomics, quality control, authenticity and fraud.

29

30 Keywords: NMR, ¹H, 2D, COSY, ultrafast, solvent suppression, high-throughput analysis,
31 wine

32

33 **Biography**

34 Pia S. Mayer – MRC award at the EUROMAR 2025

35 Pia is one of two winners of the MRC award at the 2025 EUROMAR conference, which
36 recognises her work on the adaptation of the interleaved ultrafast COSY sequence to the
application of wine. She completed her Bachelor's degree in Chemistry with Business Management from the University of Birmingham, UK, before pursuing her Master's degree during the COVID pandemic, at the University of Stuttgart, GER. Her thesis, supervised by Maria Buchweitz and Birgit Claasen, focused on investigating polyphenol-protein interactions using NMR and ITC. Alongside her studies, she gained experience as a working student in the Analytical Laboratory of Mercedes-Benz Group AG (Stuttgart, GER).

Pia is currently a final-year PhD fellow in the Department of Food at the University of Copenhagen (DK) under the supervision of Søren B. Engelsen. Her research investigates the application of fast 2D NMR techniques combined with multidimensional chemometric tools to quantify and characterise complex mixtures in food systems. During her PhD, she visited the lab of Patrick Giraudeau in Nantes (FR), where she worked on adapting the ultrafast method.

Her research explores the potential of 2D NMR methods to provide deeper insight into food composition and to address the current limitations of quantifying complex mixtures.

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# 1. Introduction

Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful analytical method for the analysis of complex mixtures. It is widely used in metabolomics, alongside mass spectrometry (MS), for profiling metabolites with a range of applications including plant metabolism, environmental sciences and personalised medicine. Furthermore, NMR spectroscopy plays an important role in the context of food analysis and quality both in research and in industry. In particular, it can be used to verify a specific metabolite fingerprint within a sample matrix which is interesting for metabolomics studies and important for food authenticity, food fraud, and food faults. Among others, wine is one of the product categories that is published in the monthly EU Agri-Food Fraud Suspicions Report because of frequent adulterations [1].
NMR profiling has previously been used on wine to determine geographical origin, variety, vintages and cultivation conditions [2-5]. The standard method used for untargeted analysis is a 1D ¹H pulse sequence, due to fast data acquisition and rich information that can be extracted from the spectra [6]. However, wine, like other complex mixtures, is far from being trivial to analyse due to the variety of metabolites and the differences in concentration levels. This can lead to severely overlapped signals, limiting accurate metabolite identification and quantification. A possible solution is the addition of a second dimension to better disperse signals and improve ambiguous metabolite identification through correlation peaks. However, conventional 2D NMR methods often suffer from exceedingly long acquisition times, which contradict the principle of high-throughput screening. For this reason, several fast 2D NMR methods have been proposed in the context of metabolite profiling [7-10]. Amongst these, ultrafast 2D NMR is particularly promising for such applications since a full 2D spectrum can be recorded within a single scan [11, 12]. This can be achieved by spatially encoding the spins through the simultaneous application of gradients and frequency-swept pulses, most commonly along the z-axis, thereby giving them a position-dependent evolution time. A train of bipolar gradients after the mixing time can unravel the encoded information using an echo-planar spectroscopic imaging (EPSI) sequence. The method of choice for ultrafast sequences in the context of metabolomics has been interleaved ultrafast COSY (iuf-COSY), which combines different hybrid strategies [13]. A first step transforms the experiment from single-scan to multi-scan in order to increase sensitivity by signal averaging. A second step aims to improve the observable spectral width by increasing the incremented pre-acquisition delay before the EPSI decoding scheme.

Ultrafast and conventional COSY have previously been compared by analytical measurements and discrimination power in model mixture and metabolomic studies, showing comparable or even exceeding performance in signal to noise ratio, linearity, precision and discrimination power [8, 14, 15]. In one of the previous metabolomics studies, the combination of iuf-COSY with an external calibration approach allowed the accurate quantification of eight targeted metabolites found in tomato fruit extracts, enabling quantification of metabolite concentrations down to 0.3 mM within only 5 min of acquisition [16]. Different untargeted approaches using iuf-COSY included the profiling of lipids from serum extracts and sea sponge extracts [17, 18]. Although this method is associated with a sensitivity penalty compared to 1D ¹H NMR, the resulting spectra are completely devoid of t₁ noise, which is interesting for samples containing analytes with a broad span in analyte concentrations [14, 15].

In the special case of wine, the water and ethanol concentrations are several orders of magnitude higher than those of other metabolites (e.g. organic acids, sugars, alcohols, amino acids or phenolics) and give rise to three large solvent signals in the spectrum [19]. Therefore, the efficient removal of those solvent signals is necessary, and different approaches have been published in literature, such as evaporation of the solvents, freeze-drying or instrumental multi-solvent suppression [2, 20-22]. One advantage of NMR is the ease of sample preparation and the ability to analyse the sample “as is”. To preserve this benefit, an accelerated 2D method with instrumental multi-solvent suppression would be ideal. Several suppression schemes are available, with 1D NOESY with presaturation being the most common one in metabolomics. It is simple to implement and provides efficient and repeatable suppression of faraway solvent
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signals [23, 24]. It has been further adapted to offer a 1D ¹H method for the analysis of wine
[2, 25].

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The study extends and adapts this approach by presenting a multi-solvent suppression interleaved ultrafast COSY method for wine analysis. It acquires a 2D spectrum in approximately 20 minutes and exhibits efficient water and ethanol suppression, allowing for the identification of 26 metabolites in a specific white wine sample. The new proposed method for solvent suppression is compared to other suppression techniques that have previously been used in connection with ultrafast experiments (no solvent suppression, presaturation and WET suppression) to evaluate its potential for future high-throughput screenings of wine samples.

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## 2. Materials and Methods

### 2.1. Materials

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#### 2.1.1. Chemicals

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KH₂PO₄ (p.a. 99%, Fluka Chemie) and Trimethylsilyl-3-Propionic acid d₄, 2,2,3,3 sodium salt ((TSP) 98% d₄, Euroisotop) were used with D₂O (99.9% d, Euroisotop) and ultra-pure water (Milli-Q, Merck) to prepare the buffer as stated in sample preparation.

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#### 2.1.2. Sample preparation

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A white wine sample was prepared by mixing 700 µL of wine (Melon de Bourgogne grape from vineyard Vignoble de l'ECU, Granit, 2023 vintage, 12.5% (v/v)) with 300 µL of 1 M KH₂PO₄ buffer (5 mM TSP, H₂O:D₂O 4:1 v/v, pH = 4.3) in an Eppendorf which had been filled with N₂ to minimise oxidation. The sample was vortexed for 15 s, topped up with N₂ and stored in the fridge until use. On the day of acquisition, 200 µL were transferred into a 3 mm NMR tube.

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#### 2.1.3. Spectrometer

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Data acquisition was performed on an Avance III HD 16.4 T spectrometer (Bruker Biospin) with an inverse ¹H/¹³C/¹⁵N/²H (²H lock) cryogenically cooled probe equipped with a Z gradient coil, operating at a ¹H Larmor frequency of 700.28 MHz and running under Topspin 3.2. All NMR experiments were conducted at 298 K.

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### 2.2. Methods

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In the following paragraph, the workflow of the iuf-COSY is described, starting from the 1D optimisation processes, followed by the 2D experimental parameters, and finally the processing information.

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#### 2.2.1. 1D ¹H experiments for suppression parameter optimisation

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##### Presaturation experiment
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A standard presaturation experiment was used to optimise water suppression for the carrier frequency and presaturation power, as well as the 90° ¹H pulse. The recovery delay was set to 5 s, and the acquisition time to 3.9 s with a spectral width of 12 ppm. Two scans and two dummy scans were used.

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## Multi-solvent presaturation experiment

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To optimise the multi-solvent suppression, integral regions were defined on the resulting water presaturation spectrum. These regions were chosen to be in the middle of the ethanol triplet and quartet (7 Hz dispersion each) and on the residual water peak (20 Hz dispersion) to generate a shaped pulse using the “selective 1D” set-up tool for presaturation within Topspin. The generated multiple-band selective shaped pulse was tested in a multi-solvent presaturation pulse sequence that uses the shaped pulse during the relaxation delay, a NOESY block and additional spoil gradients (see Fig. S1). The power of the shaped pulse was optimised for efficient suppression without baseline distortion. Acquisition parameters were as follows: duration of the suppression shaped pulse was set to 100 ms, and repeated 50 times to have a total of 5 s of relaxation delay with an acquisition time of 3 s and a spectral width of 12 ppm. Four dummy scans and eight scans were recorded with a mixing time of 10 ms between the second and the third 90° pulse. Two additional 1 ms defocusing gradients of + 31.3 G/cm (G₁) and – 6.2 G/cm (G₂) (smooth-square shape) were placed after the shape pulse and after the mixing time of the NOESY block.

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## WET experiment

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The pulse sequence WET was used to optimise water and ethanol suppression. It was performed with four selective Seduce pulses with a duration of 15 ms each. The power of these pulses was manually tuned to optimise the resulting solvent suppression. Otherwise, the relaxation delay was 5 s, the acquisition time was 3 s, and the spectral width was 12 ppm. For optimisation purposes, only one scan was acquired.

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### 2.2.2. Set-up of ultrafast COSY experiment

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Previous work has led to the current version of the interleaved ultrafast COSY (iuf-COSY), including interleaving and multi-scan methods [13]. A detailed implementation protocol is available online [26].

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All iuf-COSY methods share the same core (Fig. 1, S2 and S3), differing only in their solvent suppression techniques. The parameters in this paragraph were identical across all iuf-COSY experiments; otherwise, any additions or modifications are specified in the following suppression section. 90° pulses were calibrated as mentioned before. Both encoding chirp pulses have a duration of 15 ms and a sweep range of 28 kHz and encoding gradients (G<sub>e</sub>) of ± 3.6 G/cm, while for the acquisition (G<sub>a</sub>) ± 50.1 G/cm (smooth-square shape) gradient amplitudes were applied for 748 µs. Coherence selection gradients G<sub>3</sub> and G<sub>4</sub> were + 50.1 G/cm for 800 µs (sine shape), while coherence selection gradients G<sub>5</sub> and G<sub>6</sub> were ± 50.1 G/cm for 1 ms (sine shape). An acquisition time of 98 ms with 64 incremented acquisition loops (N<sub>acq</sub>), 8 interleaved scans (N<sub>i</sub>) and 32 scans (N<sub>s</sub>), along with 4 dummy scans
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and a recovery delay of 5 s, resulted in an experimental time of 23 min per spectrum. The recovery delay of 5 s was chosen as it is the minimum recommended rest time for the gradient coil between two successive ultrafast experiments. All experiments were performed with five replicates.

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## Water and no solvent suppression

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Both spectra were recorded using the same pulse sequence based on a continuous wave presaturation pulse in F2 (¹H) (see Fig. S2). Optimised parameters from the presaturation 1D ¹H experiment were taken for water suppression, while the power was set to 0 W for the experiments with no solvent suppression. Post-mixing gradient ($G_p$) for the iuf-COSY with presaturation (iuf-COSY-pr) was set to – 21.8 G/cm for 748 µs.

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## Multi-solvent suppression

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This pulse sequence of iuf-COSY with multi-solvent suppression (iuf-COSY-msup) is shown in Figure 1. It consists of a shaped pulse, followed by a defocusing gradient ($G_1$), two 90° pulses followed by mixing time ($t_m$ = 10 ms), and a 2nd defocusing gradient ($G_2$) before the spatial encoding. Parameters and shape were taken from optimised 1D ¹H experiments, except for additional defocusing gradients which were set to 31.1 G/cm ($G_1$) and 15.6 G/cm ($G_2$) for 1 ms (smooth-square shape) and the post-mixing gradient ($G_p$) was set to – 21.8 G/cm for 748 µs.

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## WET suppression

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For this method, the WET block with the four composite pulses was added as a suppression technique to the iuf-COSY (iuf-COSY-WET) (see Fig. S3). The parameters were taken from the optimised 1D experiment. The post-mixing gradient ($G_p$) was - 28.0 G/cm for 748 µs.

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### 2.2.3. Processing

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#### 1D ¹H experiments

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Processing was performed on Topspin 3.2 with a decaying exponential window function, a line-broadening of 0.3 Hz and zero-filling to 131072 data points (SI 128k). The phase and baseline were automatically corrected within Topspin and manually adapted if necessary.

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#### iuf-COSY

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A custom Python processing script, running within Topspin, was used for processing all iuf-COSY spectra. The code file is available online and was run on Topspin 3.2 and 4.3.[26] The iuf-COSY data was processed by an inverse Fourier transformation along the ultrafast dimensions, followed by a Gaussian apodisation in the spatial domain and a Fourier transform, while for the conventional dimension, a sine window function was applied before Fourier transformation [27]. Data were zero-filled to 512 x 1024 data points. The chemical shift for each spectrum was manually calibrated with a custom Python script, using the TSP (0.00 / 0.00 ppm) and tartaric acid peak (4.47 / 4.47 ppm) [26].

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### 2.2.4. Metabolite annotation

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Annotation of metabolites was performed using the 1D ¹H spectra, supplemented with additional structural information from the iuf-COSY and a 2D TOCSY spectrum, which applied NUS and multi-solvent suppression (Fig. S4). Literature and spectral database comparison were performed, resulting in metabolite annotation of Level 2 (25 metabolites) and 3 (1 metabolite) based on the definition of the Metabolomics Standards Initiative [28].

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### 2.2.5. Signal-to-noise ratio calculations

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To calculate the signal-to-noise ratio (SNR), data were transferred to Matlab (Mathworks, Version 2023a). Signals of cross peaks were preferred whenever possible, since they appear in less crowded regions and show less overlap. However, in spectra without solvent suppression, only diagonal peaks were observed, except for cross peaks from lactate. To facilitate comparison of several signals across all methods, four diagonal peaks (TSP, succinate, lactate, and tartrate) and one cross peak (lactate) were selected. Additional cross peaks became visible in water and multi-solvent suppression, and five of these (isopentanol, isobutanol, acetoin, 1,3-propanediol, and myo-inositol) were included. Only peaks that were not influenced by interleaving artefacts or remaining solvent signals in any of the three methods were considered. The maximum intensity of selected peaks was verified to ensure the correct row extraction. Rows were extracted, and the signal maximum, noise mean, and noise standard deviation were calculated using standard Matlab functions. The following equation was used for SNR calculations: $SNR = \frac{max_{peak}}{std_{noise}}$. A table with precisely selected peaks, extracted rows, and noise areas is provided in the Supplemental Materials (Table ST1).

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### 2.2.6. Technical repeatability

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Selected metabolite peaks from SNR calculations were integrated from iuf-COSY-msup experiments using a home-written Matlab script to assess repeatability of the method. Afterwards, the mean, standard deviation, and coefficient of variation were calculated from the relative peak volumes. Integration areas, mean relative peak volumes and standard deviation can be found in Supplemental Materials (Table ST2).

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<figure><img src="image_3.png" /><figcaption>Figure 1: Pulse sequence of interleaved ultrafast COSY with multi-solvent suppression (iuf-COSY-msup). To the general method a solvent suppression with a shaped pulse, two defocusing gradients (G₁ & G₂) and NOESY block (t_m) were added for efficient water and ethanol signal suppression. The iuf-COSY-msup consists of two opposing gradients (G_e) with smoothed chirp pulses for encoding, a post-mixing gradient (G_p) with additional coherence selection gradients (G₃ – G₆). An interleaving delay (d_i) for interleaved scans (N_i) is also used before the start of the acquisition block which features bipolar gradients (G_a) that are repeated N acq times. Phase cycling was as follow φ₁ = x, -x; φ₂ = x, x, x, x, x, x, x, -x, -x, -x, -x, -x, -x, -x; φ₃ = x, x, -x, -x, y, y, -y, -y; φ₄ = x; φacq = x, -x, -x, x, y, -y, -y, y, -x, x, x, -x, -y, y, y, -y. Gradients were applied as follows: G₁ = 31.3 G/cm for 1 ms ; G₂ = 15.6 G/cm for 1 ms; G₃ and G₄ = ± 50.1 G/cm for 800 µs; G₅ and G₆ = ± 50.1 G/cm for 1 ms; G_e = ± 3.6 G/cm for 15 ms; G_a = ± 50.1 G/cm for 784 µs; G_p = - 28.1 G/cm for 784 µs.</figcaption></figure>

## Results and discussion

### General iuf-COSY acquisition and metabolite coverage

The interleaved ultrafast COSY with multi-solvent suppression (iuf-COSY-msup) pulse sequence is shown in Figure 1. The suppression block contains a shaped pulse, which selectively excites the previously determined three solvent frequencies of water and ethanol, as well as a NOESY block, to improve faraway water suppression (water nuclei at the edge of the radiofrequency coil). Two additional defocusing gradients (G₁ and G₂) further aid solvent suppression. The original approach applied eight individual bands including one for water and seven for each of the peaks of the ethanol triplet and quartet and has been proposed for 1D ¹H NMR by Monakhova and coworkers to analyse alcoholic beverages, with further adaptation to specific alcoholic beverages, i.e. wine or whisky [2, 20, 29]. In the pulse sequence shown in
Figure 1, the shaped pulse was placed in the 2nd channel to be independent of the carrier frequency chosen for the iuf-COSY spectra. This has the advantage that the shaped pulse offset does not need to be recalculated when changing the spectral window position through the carrier frequency in the first channel of the iuf-COSY spectrum. As described above, an interleaving strategy was used to optimise the compromise between spectral width and resolution, a typical feature of ultrafast experiments [30]. Interleaved scans were recorded with an increasing delay before the bipolar gradient acquisition block, according to $d_i = \frac{2\times T_a}{N}$ with $d_i$ the interleaving delay, $T_a$ the duration of the acquisition gradient and $N$ the number of interleaved scans. The spectral width improvement through an interleaved strategy can, however, introduce artefacts that appear systematically at periodic intervals in the conventional dimension. These artefacts have been described in the literature and can arise from partial saturation, and also from slight phase, amplitude and time variations in the pulse sequence [13, 30]. They are particularly intense when they arise from strong solvent peaks. In this study, interleaved acquisitions enabled the recording of a COSY spectrum spanning the entire aliphatic window (0–6 ppm) on a 700 MHz spectrometer. Accessing a larger spectral width at this magnetic field with the same number of scans would have exceeded an experiment duration of 30 min, which was avoided to prevent damage to the gradient coils. However, at a lower magnetic field and with the same interleaving strategy, the spectral window would be increased [16].

The iuf-COSY pulse sequence with multi-solvent suppression was tested on a white wine sample and compared to experiments with no solvent suppression and with water suppression. The results are shown in Figure 2, which shows the spectra without solvent suppression (subpanel A, D, G), with water suppression (subpanel B, E, H) and with multi-solvent suppression (subpanel C, F, I). For better comparison, the 1D ¹H spectra (subpanel A, B, C) are shown as well as the projection of the ultrafast dimension (subpanel D, E, F) and the iuf-COSY spectra (subpanel G, H, I).

Water (at 4.8 ppm) was the overpowering signal when no solvent suppression was applied (subpanel G). Only ethanol and a few of the more intense metabolites, such as acetate, lactate, succinate, tartrate, and TSP were observed, as well as systematic interleaving artefacts from the strong solvent peaks. These artefacts can be recognised as ghost peaks along the vertical dimension, with a periodicity that depends on the number of interleaved scans. Depending on the solvent's chemical shift, the overlap with real NMR peaks can become more challenging (Fig. 2H). With the suppression of the water signal (subpanel B, E, H), the receiver gain could be adjusted from 3.56 to 128, with ethanol being the new limiting metabolite intensity for further receiver gain adaptations. A total of 15 metabolites could be detected. With the multi-solvent suppression technique, the signals from water and ethanol were efficiently suppressed, leading to a final receiver gain adjustment of 724. Especially, the suppression of ethanol cross peaks allowed the observation of other metabolite cross peaks, resulting in a total of 28 annotated metabolites (Fig. 2). In addition to optimising the receiver gain, the efficient solvent suppression of water and ethanol signals distinctly reduced the occurrence of systematic interleaving artefacts that overlap with peaks of interest.
A recognised limitation of ultrafast experiments is the sensitivity, which is especially important for metabolomic research [11]. Sensitivity has been optimised in this study through signal averaging and a compromise between sensitivity and spectral window size. However, ultrafast experiments are devoid of t₁ noise, which is especially interesting in wine, where distinct concentration differences are possible (e.g. organic acids, sugars and phenols). Additionally, the advantage of 2D correlation experiments lies in the cross peaks, which provide additional structural information and a lower degree of signal overlap compared to their diagonal counterparts. Both factors enable better annotation, integration and optional quantification when combined with a calibration method [31]. In this specific wine sample, the cross peaks of thirteen metabolites were observed and annotated (Figure 2I). These include isobutanol, isopentanol, 2,3-butanediol, 1,3-propanediol, proline, ethyl acetate, ethyl lactate, lactate, acetoin, glycerol, ethanolamine, myo-inositol and fructose. Some of these metabolites have been reported to be crucial for the flavour of wines, while others enable differentiation of grape variety or geographical location.

Many of the metabolites annotated in this sample using iuf-COSY-msup were reported to be relevant for differentiating wines according to various locations, terroirs, varieties, and vintages. Examples included Cabernet Sauvignon from France, the USA, and Australia, La Rioja wines from various terroirs in Spain, different white wine varieties in Germany, and several vintages of Bordeaux wines in France [2, 3, 5, 32].

<figure><img src="image_4.png" /><figcaption>Figure 2: Comparison of suppression schemes: iuf-COSY spectra without solvent suppression (A, D, G), with water suppression (B, E, H) and multi-solvent suppression (C, F, I) on a white wine sample recorded on a 700 MHz spectrometer with a cryogenic probe at 298 K. First row</figcaption></figure>
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shows 1D proton spectra (A, B, C), 2^nd^ row shows projection of iuf-COSY in the ultrafast dimension (D, E, F), 3^rd^ row shows iuf-COSY spectra (G, H, I). Annotation: 1: TSP, 2: isobutanol, 3: isopentanol, 4: ethanol, 5: ethyl acetate, 6: ethyl lactate, 7: lactate, 8: alanine, 9: 1,3-propanediol, 10: acetate, 11: proline, 12: acetoin, 13: succinate, 14: choline, 15: methanol, 16: glycerol, 17: fructose, 18: myo-inositol, 19: tartrate, 20: glucose, 21: H₂O, 22: γ-aminobutyric acid, 23: galacturonic acid, 24: caftaric acid, 25: phenyl ethanol, 26: sugar*, 27: 2,3-butanediol, 28: ethanolamine (Level 2 annotation, except for *-labelled, which are Level 3 annotation acc. to [28]).

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Signal-to-noise ratio calculation

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An analytical parameter to evaluate the new suppression scheme, apart from the improved number of metabolite observations, is the comparison of the signal-to-noise ratio (SNR) of established methods and the new one. However, only five metabolites (TSP, lactate, acetate, succinate and tartrate) are high enough in concentration to be observable in all three methods. Furthermore, only peaks unaffected by strong solvent signals or interleaving artefacts in any of the three methods were chosen for SNR calculation, with off-diagonal peaks preferred for analysis where possible. Lactate was the only metabolite to show a cross peak signal in the spectrum without solvent suppression and was therefore measured on- and off-diagonal. Isopentanol, isobutanol and acetoin cross peaks were chosen as an example for metabolites appearing in water and multi-solvent suppression, while 1,3-propanediol and myo-inositol cross peaks are examples of metabolites only observed in multi-solvent suppression. The calculated results from five repetitions per method are shown in Figure 3.

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In general, SNR would be expected to increase with improved suppression of solvent signals, due to the adaptation of the instrument receiver gain from 3.56 for no solvent suppression, to 128 for water suppression and a final optimisation of 724 for multi-solvent suppression. Figure 3 shows a distinct increase in SNR from no solvent suppression to either water or multi-solvent suppression for TSP, succinate, lactate and tartrate. The ratio of signal-to-noise between water and multi-solvent suppression was of the same magnitude for metabolite peaks that were detected in both methods. A possible explanation could be that an SNR plateau has been reached, as observed by Peters and coworkers in their work [33]. They tested different levels of receiver gain on different hyperpolarised nuclei and different NMR spectrometers (1, 7, 9.4, 11.7 and 14.1 T) and evaluated the signal intensity and SNR. From their findings, they proposed that an increasing receiver gain linearly increased the signal intensity while the SNR levelled out into an asymptotic plateau after an initial improvement. This compares with what has been observed with this wine sample, where the signal intensity increased linearly with the increased receiver gain between the methods (see Fig. S5), while the SNR levelled off in water and multi-solvent suppression.

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Despite this SNR plateau, the suppression of ethanol signals and the reduction of interleaving artefacts enabled the detection of eleven more metabolites compared to a total of 15 compounds with water suppression alone. 1,3-propanediol and myo-inositol are depicted in Figure 3 as examples of cross peaks that can only be accessed in the case of multi-solvent suppression.
<figure><img src="image_5.png" /><figcaption>Figure 3: Signal-to-noise ratio (SNR) comparison of ten metabolite peaks from iuf-COSY spectra between no solvent (blue), water (orange) and multi-solvent suppression methods (yellow). Bars represent mean SNR with error bars for standard deviation (n = 5), missing bars indicate undetected peaks.</figcaption></figure>

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## 388 Repeatability of relative peak volumes

389 Repeatability is a key factor in metabolomic studies and authentication analysis. This was 390 therefore evaluated using the same ten metabolite signals as in the SNR analysis, by calculating 391 the coefficient of variation (CV) on 2D peak volumes across five replicates (Table 1). The 392 variation for signals was determined to be between 0.2% and 6.1%. More concentrated 393 metabolites, such as succinate, lactate, and tartrate, showed a small coefficient of variation of 394 less than 1%. Signals with an SNR lower than 100 showed slightly higher variation (1.5 - 395 6.1%).

396 This is in the same range as the technical repeatability reported in a previous study of ultrafast 397 techniques on tomato fruit extract, where the variation was between 1.0% and 6.4 % on the 398 same magnetic field strength [16]. This highlights the characteristic high repeatability of iuf- 399 COSY, which is less sensitive to spectrometer instabilities and has no t1 noise compared to 400 conventional 2D methods [14, 15]. In comparison, an interlaboratory ring test evaluated the 401 possibility of the 1D ¹H multi-solvent suppression method for wine authentication in an 402 international collaboration [34]. They reported intra-laboratory repeatability based on absolute 403 quantification of 1.0-11.0% for glucose, 1.4-4.6% for acetic acid, 1.7-23.0% for malic acid, 404 and 1.3-71.5% for fumaric acid, among others. In contrast, the here presented method evaluated 405 different metabolites and focused on technical repeatability based on relative peak volumes; 406 yet the results still demonstrate acceptable repeatability levels.

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<table><caption>Table 1: Repeatability of relative peak volumes for iuf-COSY-msup (n = 5), measured on ten metabolites shown as coefficient of variation (CV) in %.</caption><thead><tr><td>Metabolite</td><td>CV [%]</td></tr></thead><tbody><tr><td>TSP</td><td>0.41</td></tr><tr><td>Succinate</td><td>0.32</td></tr><tr><td>Lactate cross peak</td><td>0.18</td></tr><tr><td>Lactate diagonal peak</td><td>0.96</td></tr><tr><td>Tartrate</td><td>0.56</td></tr><tr><td>Isopentanol cross peak</td><td>3.15</td></tr><tr><td>Isobutanol cross peak</td><td>1.49</td></tr><tr><td>Acetoin cross peak</td><td>5.61</td></tr><tr><td>1,3-propanediol cross peak</td><td>2.31</td></tr><tr><td>Myo-inositol cross peak</td><td>6.06</td></tr></tbody></table>

## Artefacts removal through optimised coherence selection

During the optimisation process of the iuf-COSY-msup, vertical artefact lines in the conventional dimension were observed, which initially limited the ability to adapt the receiver gain (Fig. 4, subpanels A & B). This is likely because the additional defocusing gradient from the solvent suppression block compensates coherence selection gradients when they are set to their default values. By adapting the defocusing gradient $G_1$, the artefacts could be moved outside the spectral window (Fig. 4, subpanel C), which led to a further adaptation of the receiver gain. The results presented above are based on these optimised parameters.

<figure><img src="image_6.png" /><figcaption>Figure 4: Impact of adaptation of defocusing gradient $G_1$ on vertical artefacts (A - C) observed during optimisation process of iuf-COSY with multi-solvent suppression. Gradient percentages translate to A: $G_1$ = 24.9 G/cm, B: $G_1$ = 21.8 G/cm; C: $G_1$ = 15.6 G/cm.</figcaption></figure>

## Comparison of iuf-COSY with multi-solvent vs WET suppression
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iuf-COSY has been previously combined with WET (iuf-COSY-WET) to suppress methanol in a reaction monitoring experiment using flow NMR [35]. Since WET can be optimised to suppress several solvent signals, this suppression scheme was tested on the wine sample. The comparison between iuf-COSY-WET (Fig. 5, subpanel A, C, E) and multi-solvent suppression (Fig. 5, subpanel B, D, F) can be observed in Figure 5, with subpanel A & B showing 1D ¹H spectra, C & D presenting the projection of the ultrafast dimension and E & F picturing the iuf-COSY spectra.

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From Figure 5A, which shows the proton spectra using wet suppression, it is evident that while the ethanol signals appear to be well suppressed, this was not the case for the water signal despite extensive optimisation tests. The unsuppressed solvent signals were likely to be the reason for the strong systematic interleaving artefacts observed in the iuf-COSY-WET. In comparison, interleaving artefacts were already visible in Figure 2 between the iuf-COSY spectra without water (Fig. 2, subpanel G), with water (Fig. 2, subpanel H), and with multi-solvent suppression (Fig. 2, subpanel I), although to a lesser extent.

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Overall, the iuf-COSY-WET did not provide suppression results comparable to those of the presaturation method and was strongly dominated by systematic interleaving artefacts. Lhoste and coworkers experienced similar artefacts when suppressing either MeOH or CHCl₃ as solvents in their work using iuf-COSY-WET in a flow set-up [35]. However, they observed a distinct spectral improvement when changing their encoding axis from z- to x-axis with a triple-axis gradient broadband inversion-detection probe. It is likely that they experienced these interleaving artefacts due to the flow direction of the flow tube in the z-axis direction, which does not apply to the static wine sample used in this experiment.

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<figure><img src="image_7.png" /><figcaption>Figure 5: Comparison of methods: iuf-COSY spectra with WET (A, C, E) and multi-solvent suppression (B, D, F) on a white wine sample of Muscadet recorded on a 700 MHz spectrometer at 298 K. 1st row shows 1D proton spectra (A & B), 2nd row shows projection of iuf-COSY in the ultra-fast dimension (C & D), 3rd row shows iuf-COSY spectra (E & F).</figcaption></figure>

High-throughput and other applications

The iuf-COSY-msup spectrum shown in this study was recorded in 23 minutes. This duration was chosen intentionally, as a compromise between throughput and sensitivity, and to preserve the integrity of the gradient coil. This is comparable to the timescale of 1D ¹H acquisitions used in wine profiling studies [4, 36]. However, this compromise of throughput and sensitivity can be adapted to the specific research question, making the iuf-COSY method an interesting candidate approach for future high-throughput wine profiling studies. It is, however, important to underline that iuf-COSY, together with other fast 2D NMR methods, should be seen as a complement to 1D NMR analysis. As shown in recent metabolomics studies, 2D NMR generally performs better to highlight more concentrated biomarkers that are overlapped in 1D NMR, while 1D NMR remains more sensitive to detect low-concentration biomarkers [17, 18]. The general power of the iuf-COSY method lies in the possibility of recording a 2D spectrum within one single scan. In the proposed method, a longer experiment time is required to achieve a sufficient spectral width and sensitivity, enabling phase cycling. Depending on the application and the sample analysed, it might be interesting to acquire single-scan spectra, e.g. for flow monitoring or samples of highly concentrated extractions. To serve these needs, an adapted version of the iuf-COSY with multi-solvent suppression consisting of only the shaped pulse
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and one defocusing gradient is provided (pulse sequence Fig. S6). Tests on the wine sample (Fig. S7) showed well-suppressed ethanol signals, but less effective water suppression, which resulted in more interleaving artefacts. However, depending on the research question, different options have been proposed, and researchers can consider which method fits their needs better.

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The results presented in this paper should also be discussed in light of the previous studies that employed ultrafast 2D NMR (and more specifically the iuf-COSY pulse sequence) for the study of complex mixtures. The comparison between ultrafast 2D COSY and its conventional counterpart has been reported in detail [14, 15]. Briefly, due to limitations that are inherent to the method, the sensitivity for iuf-COSY is 5 -10 times less than that of a 1D spectrum with the same acquisition time, and the iuf-COSY method also includes a trade-off between resolution and spectral widths [11]. However, the main advantage of iuf-COSY lies in the absence of t₁ noise compared to conventional COSY [14]. While this advantage can be partially reduced in favourable conditions (e.g., fast conventional COSY with a short recovery delay), it results in a better repeatability of iuf-COSY. In practice, this is true for experiment times below 30 min. When the low analyte concentrations require more than 30 minutes of signal averaging, ultrafast 2D NMR experiments are not recommended to preserve the integrity of the gradient coil. As a consequence, iuf-COSY experiments should be seen as a part of a toolbox for complex mixture analysis, which includes a range of fast 2D NMR experiments with complementary time-saving methods [37].

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Conclusion

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The proposed iuf-COSY method demonstrates an efficient multi-solvent suppression approach for high-throughput analysis of wine samples. The iuf-COSY spectrum of a wine sample can be recorded in approximately 20 minutes, providing reasonable high-throughput capabilities, enhanced structural information through correlation peaks and improved peak distribution compared to crowded regions in standard 1D ¹H experiments. The iuf-COSY experiment is, therefore, an interesting option for future metabolomic and authentication studies aiming to apply 2D NMR methods for high-throughput wine analysis.

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Acknowledgements

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The authors from University of Copenhagen acknowledge the generous support from the Independent Research Fund Denmark (DFF) to the project entitled: "Learning to EXplore the 2nd Order Advantage of 2D NMR" (LEX2) (2035-00294B).

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This work was supported by the MetaboHUB infrastructure funded by the Agence Nationale de la Recherche under the France 2030 program (MetaboHUB ANR-11-INBS-0010; MetEx+ ANR-21-ESRE-0035; MetaboHUB (JVCE) ANR-24-INBS-0012). The authors acknowledge the Corsaire metabolomics core facility (Biogenouest). This work has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement SUMMIT no. 814747). This work includes NMR experiments carried out on the CEISAM NMR platform.
512

513 **Conflicts of Interest**

514 Patrick Giraudeau is the Deputy Editor of Magnetic Resonance in Chemistry. In accordance
515 with the journal's policy and COPE guidelines, the manuscript was handled by an independent
516 editor to ensure a fair and unbiased review process.

517

518 **Data Availability Statement**

519 The data supporting the findings of this study are available on the Zenodo repository.

520 Mayer, P. S. (2025). Multi-solvent suppression ultrafast 2D COSY for high-throughput wine
521 screening (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.16310579.
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