# Evaluation of trap discs for root exudate eco-friendly sampling using rhizoboxes: Application to untargeted screening of organic compounds by gas chromatography hyphenated with high resolution mass spectrometry

Victoria Bohm, Estelle Forey, Matthieu Chauvat, Pascal Cardinael, Valerie Peulon-Agasse

► To cite this version:

Victoria Bohm, Estelle Forey, Matthieu Chauvat, Pascal Cardinael, Valerie Peulon-Agasse. Evaluation of trap discs for root exudate eco-friendly sampling using rhizoboxes: Application to untargeted screening of organic compounds by gas chromatography hyphenated with high resolution mass spectrometry. Journal of Chromatography Open, 2025, 7, pp.100205. 10.1016/j.jcoa.2025.100205. hal-04963395

HAL Id: hal-04963395

https://normandie-univ.hal.science/hal-04963395v1

Submitted on 31 Oct 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

# Evaluation of trap discs for root exudate eco-friendly sampling using rhizoboxes: Application to untargeted screening of organic compounds by gas chromatography hyphenated with high resolution mass spectrometry

Victoria Bohm<sup>a</sup>, Estelle Forey<sup>b, c</sup>, Matthieu Chauvat<sup>b, c</sup>, Pascal Cardinal<sup>a</sup>, Valérie Peulon-Agasse<sup>a, *, c</sup>

## ARTICLE INFO

### Keywords:

Soil

Rhizobox

Root exudate

Sampling

GC-HRMS

Sample preparation

## ABSTRACT

In the present paper, an unusual sampling method, called EcoRoot, was investigated for sampling directly in soil, root exudates of Poa annua L., belonging to the Poaceae family. Using a rhizobox, sorption filters were placed directly onto roots to serve as traps for root exudates. Various trap compositions, namely, cellulose nitrate, glass microfiber and nylon, were evaluated for their ability to adsorb/desorb a standard mixture of known exuded compounds and for recovery yield. Cellulose nitrate supports exhibited better yields for compounds known to be exudated by plants of the Poaceae family. Then, two crucial parameters were investigated: the contact and extraction times. The most suitable methodology for extracting the target compounds was a cellulose nitrate support with a contact time of 60 min and 30 min in an ultrasonic bath using a mixture H₂O/MeOH. Soil and root sampling was carried out under the optimized conditions. Then, silylation of extracts was performed, and GC-HRMS was used to demonstrate that this sampling method could be used to efficiently trap compounds from soil and roots. Moreover, among the 6,136 compounds detected in extracts, 516 appeared to be specific to root exudates. This Ecoroot methodology allows root exudates to be collected in conditions as close as possible to natural growth environment, limiting the environmental impact with a 0.59 score (AGREEprep) compared to hydroponic methods. Ecoroot offers interesting perspectives for studying root exudate metabolome and their temporal and spatial dynamics in the rhizosphere, with important issues in both Ecology and Plant biology.

## 1. Introduction

Root exudates play a vital role in plant growth, crop production, and ecosystem functions and might partly explain soil biodiversity patterns [1]. The term root exudate refers to the soluble organic compounds released by plant roots into the surrounding rhizosphere [2]. These released compounds are mainly described in the literature as compounds with low molecular weight, primary (e.g., organic acids, sugars, amino acids) and secondary metabolites (e.g., terpenoids, phenolics, flavonoids) as well as compounds with high molecular weight (e.g., enzymes, mucilage) [3–5]. Exudates may act as signaling molecules, that is, as communication intermediates between plants and the surrounding rhizosphere microbiome consisting of fungi, bacteria, viruses or nematodes [6]. Thus, through the release of a wide variety of

compounds into the rhizosphere by roots, plants may, for example, regulate soil microbial communities, repel pathogens, facilitate beneficial symbiotic relationships, modify physical and chemical soil properties and reduce competition with other plant species [7,8]. Understanding root exudation is essential for elucidating rhizosphere communication and promoting an understanding of plant-soil interactions.

However, the sampling of root exudates is particularly challenging. Although exudates are produced in the soil, most of the knowledge on exudates has been acquired with artificial devices (e.g., hydroponics, sandy substrate) that do not reflect the biological, physical or chemical properties of soils [4,9]. Furthermore, the quantity and composition of root exudates vary significantly among plant species, plant ages, root depths, and environmental conditions as determined by various soil

<footnote><sup>a</sup> Univ Rouen Normandie, Normandie Univ, FR3038, SMS, UR 3233, F-76000 Rouen, France</footnote>

<footnote><sup>b</sup> Univ Rouen Normandie, INRAE, Normandie Univ, ECODIV USC 1499, F-76000 Rouen, France</footnote>

<footnote><sup>c</sup> La Rochelle Université, CNRS, UMR 7266 LIENSs, La Rochelle, France</footnote>

<footnote>* Corresponding author at: Place Emile Blondel, UFR des Sciences et Techniques, 76821 Mont-Saint-Aignan Cedex, France. E-mail address: valerie.agasse@univ-rouen.fr (V. Peulon-Agasse).</footnote>
properties or microclimates [10,11]. Finally, plant-microbe-soil in-
teractions strongly affect root architecture and plant metabolism. Thus,
sampling exudates on realistic and natural soil substrates is highly
challenging [4]. Researchers have proposed a wide range of methods
and devices for sampling these root exudates, and many critical meth-
odological aspects have been addressed both in exudate sampling pro-
cedures and in analytical approaches [1,4,12,13]. In most cases, roots
are grown in solutions (hydroponics and semihybrid solutions, substrate
culture) that do not reflect the natural growth environment of plants;
plants typically interact with soil organisms. The sampling of root exu-
dates using these cultivation methods presents advantages such as pre-
venting the contamination of exudates by soil degradation or biotic
components. However, they have a major drawback: they induce
abnormal stimulatory effects or stress in plants [4,14], which un-
doubtedly impacts and modifies root exudation patterns [15]. Recently,
alternative methods have been developed, such as the use of exudate
sorption/diffusion traps in rhizoboxes, i.e. pots with a transparent side
to visualize and access part of the root system [10,14,16]. This method
allows for the semiquantitative and qualitative sampling of exudates
from soil without damaging roots. This approach allows plants to grow
in soil, and root development can be visualized through an observation
window, enabling the sampling of root exudates more precisely. Devices
called exudation traps, composed of filter paper, can be placed onto root
segments to obtain localized sampling [10,17]. This sampling approach
induces limited stress on roots, the sampling position can be adjusted,
and sampling can be repeated. Despite the clear advantages of
mimicking a natural microsystem, such a setup for sampling only exu-
dates is tricky, and the recovery efficiency of exudate sampling needs to
be improved [4]. Sampling root exudates in soil is challenging mainly
because of three parameters: the exudates are released in very small
amounts, in a very limited area around the roots and can be very quickly
assimilated by rhizosphere organisms [4,12]. Differentiating com-
pounds derived from the rhizosphere released by roots from those
derived from cellular decomposition is another barrier to overcome.

The main goal of this article was to provide a green methodology
with minimal perturbations for sampling exudates directly in soil using
rhizoboxes to get as close as possible to natural conditions. This meth-
odology called EcoRoot corresponds to the combination of the rhizo-
boxes and sorption traps. Thus, root exudate sampling in annual
herbaceous plants using sorption traps were evaluated and optimized.
First, a screening of sorption traps, including those made of nitrocellu-
lose membranes (CelN), nylon and glass microfiber (GMF), was per-
formed on a standard mixture containing compounds known to be found
in root exudates [5,18]. Adsorption and desorption processes were
optimized. After optimization, an evaluation of the environmental
impact of this sampling method was performed using the analytical
greenness metric for sample preparation (AGREEprep) [19]. The ob-
tained score was compared with those obtained for hydroponic
methologies, based on the literature. In a second step, soluble root ex-
udates of Poa annua L., which belongs to a family of grasses (Poaceae),
were collected from the selected sorption traps into rhizoboxes. Poa
annua L. was selected for the study as it is one of the most widespread
grasses in the world. Consequently, this species, that is a fast-growing
species, is often used as a plant model in experiments [20]. Untar-
geted analysis was performed using gas chromatography coupled with
high-resolution mass spectrometry (GC-HRMS) after silylation in full
scan mode. The detected compounds were compared to those trapped in
soil without plants. Finally, untargeted screening allowed for the
detection and identification of soluble root exudate compounds and the
identification of the first metabolomic fingerprint of P. annua.

## 2. Materials and methods

### 2.1. Chemicals and reagents

L(-)-Tryptophan was purchased from Acros Organics (Geel,

Belgium), and *trans*-resveratrol from BioVision (Zurich, CH), fumaric
acid, caffeic acid, (+)-catechin hydrate and the derivatization agent
BSTFA (N,O-bis(trimethylsilyl)trifluoroacetamide) were purchased from
Sigma Aldrich (Steinheim, Germany). Pyridine and acetone (HPLC
gradient grade) were purchased from VWR (Fontenay-Sous-Bois,
France), and hexane was obtained from Carlo Erba (Val-de-Reuil,
France). Methanol (HPLC gradient grade) and formic acid were obtained
from Fischer Scientific (Waltham, MA, USA). Ultrapure water was ob-
tained from a Milli-Q water purification system from Millipore Ltd.
(Bedford, MA, USA). The nylon membrane filters (pore size of 0.45 µm),
glass microfiber filters (binder-free, pore size of 1.6 µm) and cellulose
nitrate membrane filters (pore size of 0.45 µm) used for this study were
all purchased from Whatman (Maidstone, UK).

### 2.2. Plant materials and exudate sampling

The experiments were carried out with two rhizoboxes made of
hemispheric glass cylinders (46 mm radius and 200 mm height) and
with a removable glass window, which made the roots accessible
without soil perturbation. The experimental design is presented in Fig. 1.
The base of each rhizobox was composed of a rigid glass concrete filter
with a mesh size smaller than 0.1 mm to facilitate leaching. Each rhiz-
zobox was filled with 510 ± 10 g of 40 % humid soil. The soil used for
this experiment was a rendosol (organic matter content = 6.17 %; pH
H₂O = 7.79) collected in September 2017 from a chalk grassland in
Normandy, France. In each rhizobox, 3 seedlings of *P. annua* (two-week-
old seedlings with two leaves) were transplanted. Throughout the
duration of the experiment, the two rhizoboxes were angled at 45° to
ensure that the roots grew close to the removable glass window. The
rhizoboxes were also covered with opaque film to avoid light exposure,
which could favor the development of algae. The rhizoboxes were
incubated in a phototron (climate chamber; temperature: 18.5 °C/64.4
°F; daily light/dark cycle: 18 h/6 h) for nine weeks until exudate sam-
pling. The plants were watered every two days to maintain approxi-
mately 40 % humidity.

### 2.3. Evaluation and optimization of trap sorption abilities

#### 2.3.1. Sample preparation

To assess the sorption abilities of the exudate traps, a mixture con-
taining five compounds of various polarities was prepared. This mixture
contained molecules that are representative of root exudates and are
already highlighted in the literature for Poaceae species [5], but it
contained also other compounds known to be present in root exudates,
especially allelopathic compounds such as polyphenols or small organic
acids [18]. L(-)-Tryptophan, fumaric acid, caffeic acid, (+)-catechin
hydrate and *trans*-resveratrol were solubilized in methanol, and their
concentrations were adjusted with water to obtain a similar UV response
for each compound at their maximum absorption wavelength. The final
concentrations used for the analysis ranged from 5 mg.L⁻¹ to 100 mg.L⁻¹.
A perforating tool was used to shape sorption traps into 0.6 cm diameter
discs (Fig. 1). Ten traps were then placed into a Petri dish and put in
contact with a 10 µL drop of the mixture. The sorption traps were placed
after a contact time in flasks in 2 mL of a mixture of H₂O-MeOH (4:1)
with the same proportions of solvents as the mobile phase used for the
analysis. Then, extraction was carried out in an ultrasonic bath for 15
min or 30 min to desorb the compounds from the traps. Finally, 1 mL of
supernatant was collected and kept at +4 °C until further analysis.

The influence of four parameters was studied: the number of sorption
traps used; the chemical nature of the sorption traps (nylon, CelN and
GMF); the contact time with the mixture (30 min, 60 min and 90 min);
and the extraction time (15 min and 30 min) in an ultrasonic bath.

#### 2.3.2. HPLC-DAD operating conditions

Targeted analyses were performed with an HPLC system (Dionex
UltiMate 3000, Thermo Scientific, Sunnyvale, CA, USA) consisting of a
<figure><img src="image_4.png" /><figcaption>Fig. 1. Rhizobox designed with observation window and exudate collection using 20 sorption traps (A); Experimental design of the rhizobox used for plant growth (B); Photography of the traps (C).</figcaption></figure>

quaternary low-pressure gradient LPG-3400RS pump, an autosampler WPS-3000RS maintained at +5 °C and a diode array detector 3000RS (DAD). A Halo phenyl-hexyl column (100 mm × 4.6 mm) with a particle size of 2.7 µm was purchased from Advanced Materials Technology (Wilmington, DE, USA) and maintained at 30 °C in a TCC-3 × 00RS oven. The injection volume was 20 µL in full loop mode. The UV wavelengths used for quantitative analysis were 305 nm for resveratrol, 275 nm for catechin and tryptophan, 330 nm for caffeic acid and 210 nm for fumaric acid. These wavelengths were determined by injecting each solution separately. The solvents used for the mobile phase were H₂O + 0.1 % formic acid (pH 3) (eluent A) and MeOH (eluent B). Analyses were performed in triplicate using an elution gradient at a constant flow rate (0.4 mL.min⁻¹) as follows: 0–5 min, 20 % B; 5–15 min, linear gradient from 20 % to 80 % B maintained for 0.1 min; 15.1–20 min, linear gradient back to 20 % B. Each experiment was performed at least twice. Chromeleon 7.2.10 software was used for data acquisition and processing.

## 2.4. Greenness score evaluation

AGREEprep tool was used to assess the greenness of the proposed sampling preparation and to compare it with the main sampling method of root exudates, which is the hydroponic method. This calculation is based on the 10 principles of green sample preparation (GSP). As criteria are not equal in terms of green significance, Wojnowski et al. suggested that their default weight with a higher weight for the solvents used or the amount of waste or energy consumption [19]. To compare the sampling strategies, two hydroponic methodologies from the literature were selected to be evaluated with the same metrics [21,22]. Also, the Blue Applicability Grade Index (BAGI) [23] was used to evaluate through a metric tool the practicability of the method.

## 2.5. Untargeted analysis

### 2.5.1. Real sample preparation

Once the different parameters were optimized, 20 CelN traps were placed along the roots for 60 min in moistened soil to collect root exudates, as illustrated in Fig. 1. During this stage, the roots were covered

with opaque film to avoid light exposure and root desiccation. The traps were then collected in vials and frozen at -20 °C. An additional derivatization step was required for sample preparation prior to gas chromatography analysis to make the compounds more volatile and less polar so that they could be vaporized and quantitatively transferred into the system. A protocol similar to that described by Neumann [10] was carried out by the addition of the silylating reagent BSTFA (N,O-bis (trimethylsilyl)trifluoroacetamide). After being in contact with the roots, the traps were placed in 2 mL of methanol for 30 min of ultrasonic extraction. A volume of 1 mL of the supernatant was collected and evaporated to dryness under nitrogen flow at room temperature. The dry sample was then solubilized with 500 µL of a mixture of hexane-acetone (1:1) since a wide range of compounds with various polarities could be solubilized in a mixture containing an apolar and a more polar solvent. The solution was then derivatized by adding 100 µL of pyridine and 100 µL of BSTFA under nitrogen flow and then magnetically stirred for 2 h. The resulting solution was then filtered through a 0.2 µm PTFE filter and stored at +5 °C until analysis. Soil blank and trap blank samples were prepared with the same methodology.

A series of n-alkanes (C₁₂, C₁₆-₁₉, C₂₂, C₂₄, C₂₇-₂₈, and C₃₀) prepared in hexane at 5 mg.L⁻¹ was also analyzed under the same operating conditions to calculate the retention indices (RIIs) from the van den Dool and Kratz equation (Eq. 1), which is a variant of the Kovats RI adapted for non-isothermal temperature programs, constituting an additional identification parameter.

$$I(x) = 100 \times \left( n + \frac{tr(x) - tr(n)}{tr(n+1) - tr(n)} \right) \quad (1)$$

I(x): RI of the unknown compound x n: number of carbons of the n-alkane eluted before the analyte tr(x): retention time of the unknown analyte x tr(n): retention time of the n-alkane eluted before the analyte tr(n+1): retention time of the longer n-alkane eluted after the analyte

### 2.5.2. GC-HRMS operating conditions

The GC-Q-Orbitrap (Q-Exactive, Thermo Scientific, Bremen, Germany) system used consisted of a Trace 1310 GC, an MPS (Multi-Purpose Sampler) autosampler from Gerstel (Mülheim, Germany), a PTV (Programmed Temperature Vaporizer) injector, an electron ionization (EI)
source, and a hybrid Q-Orbitrap mass spectrometer. A cool injection system (CIS6) was used in pulsed splitless mode. Helium (99.999 %, Air liquid, Bagneux, France) was used as the carrier gas with a constant flow rate of 1.7 mL/min. The analytical column used for GC separation was a WCOT BP5MS-UI (30 m x 0.25 mm) (5 % Phenyl Polysilphenylene-siloxane) fused silica capillary column with a film thickness of 0.25 µm from SGE Analytical Science (Milton Keynes, UK). The following temperature program was used: hold for 3 min at 40 °C, ramp up at 15 °C/min to 325 °C, then hold for 3 min. The injection volume was 1 µL, and the injector temperature program was as follows: hold for 0.2 min at 30 °C and ramp up at 10 °C/s to 300 °C, then hold for 18 min. The transfer line was kept at 320 °C during analyses, and EI was performed at 70 eV with a source temperature set to 250 °C. MS acquisition was performed in full scan mode with a *m/z* range of 50–550. Nitrogen gas (Air liquid, Bagneux, France) was used for the C-Trap supply. Each analysis was performed in triplicate.

Xcalibur 4.0 and Compound Discoverer 3.3 were used for processing and deconvolution, respectively. The NIST 1.4 Mass spectral Library & Search Software (NIST 2014/EPA/NIH) version 2.2 build version June 10, 2014, was used to compare the Orbitrap spectra with the library spectra.

## 3. Results

### 3.1. Evaluation and optimization of sorption abilities

Prior to untargeted analysis, the collection system was first evaluated through targeted analysis to estimate the yield of sorption/extraction. The tradeoff between trap adsorption and desorption was determined by calculating the recovery yields and by estimating the repeatability of extractions using relative standard deviations (%RSD). This targeted study was conducted using a test mixture in HPLC-DAD to optimize sample preparation prior to the screening of root exudate analytes by GC-HRMS.

First, each compound in the test mixture was injected to determine the elution order. Since a total of 100 µL of the test mixture was placed on the traps (a 10 µL droplet on ten traps), the same quantity of the test mixture was placed in a vial and the same sample preparation (ultrasonication step and solvents) and the same experimental conditions were used. The resulting chromatogram is presented in supplementary materials, Figure S1. The peak areas determined from this chromatogram for the different analytes were used to calculate the recovery yields, which reflect the sorption abilities of the traps.

Recovery yields were determined for each compound by calculating the ratio between the peak area measured from the chromatogram obtained from the sorption on discs (Fig. 2) and the area obtained by injection of the studied mixture (supplementary materials, Figure S1).

To optimize sample preparation and obtain the best recovery yields, traps of different compositions were compared to determine the best sorption material. Three supports were retained due to their ability to retain the analytes in the test mixture: CelN, nylon and GMF. The resulting chromatograms are presented in Fig. 2.

The peak areas obtained using the same experimental conditions varied according to the support type. With the experimental conditions used and at 275 nm, the chromatogram corresponding to the CelN support (blue) presented the most peaks. The recovery yields, calculated as explained above as a function of the trap composition, are presented in Fig. 3.

As expected, the recovery yield values varied greatly depending on trap composition. These values ranged from 0 % for fumaric acid on nylon to 94 % for fumaric acid on CelN. The recovery yields obtained on the nylon support were low, except for tryptophan, which had a recovery yield of 73 %, but the yields were close to zero for fumaric acid and *trans*-resveratrol. The CelN and GMF supports appeared suitable for the studied compound families, with recovery yields above 50 % (except for *trans*-resveratrol on CelN filters). The recovery yields obtained from GMF for the five compounds ranged from 48 % to 71 %, with very low variability. Moreover, the CelN support was well adapted for the sorption of small acids with high levels of recovery (79 % and 94 % for caffeic acid and fumaric acid, respectively). The %RSD values obtained were lower than 20 %, highlighting good repeatability for the CelN and GMF supports. However, the %RSD resulting from sorption to nylon traps presented excessive variability, exceeding 20 %, and thus were considered irrelevant.

After it was found that CelN traps were more suitable for the study, two other parameters were studied: the contact time between traps and roots and the extraction conditions. This sampling method is not yet well described in the literature; a contact time of 4 h was reported in one study [10]. Neumann et al. used a 4 h contact time to recover aromatic compounds, which are presumed to be less exuded than polar entities. To evaluate the trap sorption capacities and avoid compound degradation, three contact times, 30 min, 60 min and 90 min, were used. The recovery yields obtained at different contact times with the CelN traps are presented in Fig. 4.

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Chromatograms obtained recorded at 275 nm resulting from the deposition of a 10 µL droplet on 10 traps: nylon (black), GMF (red) and CelN (blue); fumaric acid (A), RT 2.6 min; tryptophan (B), RT 5.1 min; catechin (C), RT 7.0 min; caffeic acid (D), RT 10.0 min; and *trans*-resveratrol (E), RT 14.4 min.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Recovery yields (%) of the 5 compounds of interest using nylon (light blue), GMF (red) and CelN (dark blue) as trap supports. %RSD was calculated based on three replicates.</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Evaluation of recovery yields (%) for the 5 compounds of interest with contact times of 30 min (light blue), 60 min (red), and 90 min (dark blue) on CelN. The %RSD was calculated based on three replicates.</figcaption></figure>

The yields obtained, as well as the relative standard deviations (< 20 %), are all of the same order of magnitude for each compound regardless of the contact time, except for *trans*-resveratrol at a contact time of 90 min. Therefore, no general conclusions could be reached regarding the influence of contact time. However, it appeared that a 30 min contact time was not optimal; thus, a contact time of 60 min was chosen for the study of exudates.

The last parameter studied was the extraction time. Ultrasonication is commonly used for the extraction of compounds from either roots or leaves [18,24]. Therefore, ultrasonication for 15 and 30 min was tested, and the recovery yields obtained are presented in Fig. 5.

It was observed that extraction time influenced yield, with higher yields for an ultrasonication time of 30 min except for fumaric acid. At

all extraction times and contact times, the recovery yields of fumaric acid were overestimated, and they were low for *trans*-resveratrol. An increase of approximately 20 % in recovery yield was observed for three out of the five compounds with 30 min of extraction compared to 15 min, which represents a significant improvement. The final conditions used in the study of root exudates were as follows: 20 CelN traps, since it was observed that sorption was directly related to the number of traps, with a contact time of 60 min and an ultrasonic extraction time of 30 min.

### 3.2. Greenness sample preparation score evaluation

Two hydroponic-based methods, as this is the leading strategy to
<figure><img src="image_8.png" /><figcaption>**Fig. 5.** Evaluation of recovery yields (%) for the 5 compounds of interest on CelN as a function of ultrasonic extraction time (US): 15 min (light blue) and 30 min (red). The %RSD was calculated based on three replicates.</figcaption></figure>

sample root exudates, were chosen to be compared to the methodology presented here, with variations in the sample preparation to get an insight of the environmental impact of each methodology. The GSP scores obtained are presented in Fig. 6.

The calculation is based on a score given from 0 to 1 for each criterion, corresponding to the worst and best scores, respectively. The final score is obtained by combination of each criterion score with its proper weight. The closer to 1 the final score is, the less the methodology studied is impacting for the environment. The AGREEprep score for the proposed method is 0.59, indicating an environmentally friendly and sustainable method. The methods compared show quite lower scores, with respectively 0.22 and 0.26 for hydroponics with automated SPE and with manual SPE methods. The score obtained with the BAGI metric tool can range from 25 to 100. The higher the score is, the more practical the method is. The score obtained for the methodology is of 67.5, indicating a practical and applicable methodology (presented in Supplementary materials in Figure S2).

### 3.3. Untargeted analysis for root exudate profiling

Once the sample preparation was optimized, untargeted screening using GC-HRMS was performed to obtain specific chemical signals related to root exudates. GC is the ideal method for analyzing volatile

compounds, and silylation can be carried out to make compounds volatile and less polar. An adaptation of Neumann's protocol was used to avoid the heating step during derivatization, as root exudates potentially contain thermosensitive compounds. The silylation reagent chosen for this reaction was BSTFA because it enables the derivatization of many chemical families at room temperature [25].

A deconvolution of the obtained chromatograms was needed, first to extract the peak from the background signal and second to identify coeluted compounds. As example, the total ion current chromatogram (TICC) from RT 7.53–9.06 min, the non-deconvoluted spectrum and the deconvoluted spectrum at a retention time of 8.03 min are presented in supplementary materials in Figure S3.

Apart from the noise, the TICC at a RT ranging from 7.53–9.06 min showed no chromatographic peak. Among the 330 ions detected at this RT, only 87 ions remained after deconvolution. This deconvoluted peak was attributed to oxalic acid trimethylsilyl (TMS). However, the database spectrum of the oxalic acid TMS derivative shows a peak at *m/z* 73.04628 corresponding to the C₃H₉Si group, which was present in the non-deconvoluted spectrum but missing in the deconvoluted spectrum due to its recurrence in the background noise (stationary phase bleeding).

A total of 7095 compounds were detected and isolated via the deconvolution process. Blank samples were made of *n*-hexane and were

<figure><img src="image_9.png" /><figcaption>**Fig. 6.** The results of AGREEprep assessment of procedures for root exudate sampling: a- the sample preparation with EcoRoot, b- the sample preparation with hydroponics and automated SPE [21], c- the sample preparation with hydroponics and manual SPE [20].</figcaption></figure>
used to remove blank sample compounds through a filtering step in which each feature area is compared with the maximum value of the area of all blanks and all samples. If no area in the sample is greater than 10 times that of the blank sample, then the feature is considered un-specific and is considered to be in the blank. To avoid nonspecific root exudate compounds, analyses of sorption discs placed in soil areas far from the roots were conducted; as well as the sorption discs alone. This step increased specificity by hiding compounds that were present in the soil and/or sorption discs. After the deconvolution process and the blank filtering step, 6271 features remained. These features could be either specific to sorption discs, soil or roots or could be common to at least two sample types. To organize and categorize these features, various filters were used, leading to the Venn diagram (Fig. 7).

The root circle corresponds to the compounds detected on the sorption traps placed on the root tips. The soil circle and sorption trap circle correspond to the compounds detected on the sorption traps placed in the soil and to the sorption discs alone, respectively. Among the 6271 features, 134 were manually filtered because they arose from stationary phase degradation or from derivatization impurities, resulting in 6136 features that were specific to our samples. A feature is considered common if areas on the samples do not exceed a 10-fold ratio. Otherwise, the feature was considered specific. Only 11 % of the 6136 features were sample-specific, with 36 % of the features common to sorption traps, soil and roots, 38 % common to soil and roots, 13 % common to sorption discs and soil and 1 % common to sorption discs and roots. Among those 11 %, 8 % were root-specific, 2 % were soil-specific and 1 % were sorption trap-specific. Among the 6136 features, 44 % were annotated, and thus, 56 % remained unannotated. In terms of the percentages of annotated and nonannotated features among the categories, features common to sorption traps and roots and specific to roots represented the greater percentages of annotated features. Other categories showed a higher percentage of unannotated features, with a maximum of 58 % for features common to all samples. A comparison of the specific compound families among samples (soil, plant and trap), based on the putative annotations, has been performed and is presented in supplementary materials, in Figure S4. The most represented chemical families are alcoholic compounds, small organic acids, ketones, amines, sugars and amino acid derivatives.

# 4. Discussion

## 4.1. Evaluation and optimization of sorption abilities

The first step of this study was aimed at establishing the sorption capacity of the different trap supports. Importantly, trap sorption

abilities represent a compromise between adsorption and desorption. On the one hand, some traps could lead to high retention of compounds, which resulted in a low extraction yield if the desorption step was not efficient. On the other hand, some traps could lead to poor retention of the analytes of the studied mixture, and thus, recovery yields were also low. Here, the extraction efficiency was governed not only by the solvents used but also by the extraction time. Therefore, if the compounds of interest have a greater affinity for the support than for the extraction solvents, or if the extraction solvents have a lesser affinity for the support than the compounds of interest, desorption will not be sufficient.

Poor peak shape was observed for fumaric acid (supplementary materials, Figure S1). This could be explained by additional interactions between the chromatographic support and the ionic form of the acid.

The peak areas shown in Fig. 2 varied depending on the support used due to differences in the affinity of the materials for the studied mixture. A split peak was also observed for *trans*-resveratrol, which was not observed in the chromatogram of the standard mixture. One hypothesis is that compound degradation can occur during the sample preparation step. During this time, *trans*-resveratrol could be isomerized upon contact with atmospheric oxygen or with exposure to light. Moreover, the use of ultrasonic extraction can potentially degrade compounds with low thermal stability. A study reported that the isomerization of *trans*-resveratrol to *cis*-resveratrol is affected by various parameters, such as temperature or light intensity [26]. Additional compounds could be released by the trap matrices. The extra peak at 10.7 min was attributed to an isomer of caffeic acid produced by light exposure [27,28]. The chromatogram obtained with CelN support showed the most peaks because of its composition, which consisted of nitrate esters that could be detected via UV detection.

Recovery yields and %RSD were used to distinguish among the supports (Fig. 3). According to the results, it seemed that the nylon support reacted with acidic compounds, which might be linked to the fact that nylon traps have limited compatibility or even non-compatibility with acids according to the supplier chart. Moreover, recoveries on the nylon support presented an excessive variability. Overall, nylon appeared unsuitable for the sorption of the compounds of interest. In contrast, the GMF and CelN supports showed satisfactory overall sorption for the compounds of interest with low variability. The CelN support appeared to be the best choice for the adsorption of small organic acids, amino acids, and flavonoids described in the exudates of plants of the Poaceae family [5] and was therefore used for exudate collection from Poa annua L.

The next parameter studied was the contact time between the support and the standard mixture (Fig. 4). It is important to let enough contact time to allow compound adsorption on discs, but an excessively long contact time could lead to compound degradation. No significant difference was detected in recovery at different contact times. Thus, to be able to recover enough exudates and to avoid bacterial development, a contact time of 60 min was selected for root sampling. This time is drastically shorter compared to the 4 h recommended by Neumann et al. [10] and thus limits compounds degradation and microbial contamination. The low yields obtained for *trans*-resveratrol may be explained by the fact that the traps had either low or excessively high retention of this compound. This could have also occurred due to the degradation of *trans*-resveratrol or its isomerization to *cis*-resveratrol. In contrast, the overestimation of recovery yields for fumaric acid could be attributed to coelution with matrix compounds.

The last parameter investigated was the duration of extraction in the ultrasonic bath (Fig. 5). A clear trend appeared, with better recovery yields for an extraction time of 30 min, except for fumaric acid. The yields obtained for *trans*-resveratrol were still underestimated. The low yields and relative standard deviations greater than 34 % after 15 min in an ultrasonic bath may have been obtained due to insufficient extraction times or due to the variability induced by the instability of phenolic compounds in the diluted solution.

Regarding the AGREEprep score obtained of 0.59, the methodology

<figure><img src="image_10.png" /><figcaption>**Fig. 7.** Venn diagram showing the compound distribution among samples after deconvolution.</figcaption></figure>
studied here is thus quite interesting compared to the two hydroponics methods with scores of 0.22 and 0.26 (Fig. 6). The main differences between these two sample preparation methodologies are the use of automated SPE with a high energy consumption against a manual SPE, but also the waste quantities and the size economy of the sample. Indeed, the proposed methodology here miniaturizes the sample preparation in terms of sample volumes, waste and consequently volumes of hazardous solvents. Moreover, another key parameter explaining the good score obtained is the reduced number of sample preparation steps and the high sample throughput, inducing a low energy consumption.

## 4.2. Untargeted analysis for root exudate profiling

The methodology developed was applied to real samples first to evaluate whether root exudates could be recovered with this sampling method and second to determine whether specific molecules could be identified in the exudate. Combining this sampling method with non-targeted analyses conducted in GC-HRMS allowed for 3-factor identification based on mass precision, mass spectrum and retention index. Retention indices allowed to get rid of many parameters, such as the apparatus used or the analysis conditions. This enabled us to normalize the retention times obtained for the eluted compounds with the retention times of a series of linear n-alkanes. The only parameter that induced a variation in the retention indices was the nature of the stationary phase used. Thus, the indices listed in the databases allowed us to estimate the retention time of a given compound for a given stationary phase type, which constitutes an orthogonal information to that obtained with mass spectrometry. This sampling method was already proven to be successful by Neumann et al. for identifying certain lettuce exudate compounds by GCMS with a time-of-flight mass spectrometer [10]. To our knowledge, no studies have been reported on optimizing this sampling method with different traps, different contact times and extraction times for GC-HRMS analyses.

The raw data generated required a deconvolution step to extract the spectra of compounds of interest from the background noise, as exuded compounds are released in trace amounts by roots. Deconvolution makes it possible to detect and isolate compounds masked by background noise and to remove signals from coeluting compounds. The algorithm calculations were performed by following the evolution of all the ions present scan after scan, to group them according to their evolution. In this way, the spectrum of each metabolite could be reconstructed from the composite spectra (example presented in Figure S3 of supplementary materials). There was an issue with the way the software deconvoluted spectra, as *m/z* 73.04628 was considered nonspecific to a compound. This phenomenon drastically reduced the attributed similarity score with database spectra, which resulted in its absence in the deconvoluted spectra of TMS derivative compounds. It is considered nonspecific because this *m/z* ratio also corresponds to an ion in the stationary phase, which constantly bleeds and is then filtered as background noise by the software algorithm. Consequently, manual reconstruction was required to account for this important ion in the derivatized compounds.

The Venn diagram (Fig. 7) shows, as expected, that a large majority of the detected features were common to the different sample types. However, these results highlighted the significant sorption capacity of the exudate traps, showing that three-quarters of the total specific compounds were root-specific (516 features). Overall, 56 % of the 6136 features remained unannotated. This could have been caused by a lack of compounds in the databases or by nonresolved peaks. Two-dimensional GC could be efficient at improving separation and thus limiting coelution.

These results are promising and demonstrate that the sampling of root exudates in soil with traps enables the isolation and identification of organic compounds derived from root exudates without causing stress or damage to plant roots. Nevertheless, the main limitation of this sampling method is the low recovery, which is limited by the root exudation rate

and traps positioning. However, GC hyphenated with HRMS is a powerful tool to address these issues, allowing the analysis to be conducted with very high sensitivity.

## 5. Conclusions

Assessing root exudate compounds is a key challenge in understanding plant-soil interactions. The challenge here was to develop an unusual soil based-methodology, called EcoRoot, to access root exudates while retaining near-natural conditions. The results obtained for the sorption capacities of the different supports showed that the traps could both adsorb compounds and desorb them. The use of CelN traps led to the best sorption/desorption yields for most of the targeted compounds, up to 91 % for fumaric acid, followed by GMF and nylon traps. No general conclusions could be reached regarding the influence of contact time between the sorption traps and exudates (here our test mixture) on recovery; therefore, a contact time of 60 min was selected. Regarding extraction with an ultrasonic bath, a clear trend was observed with higher recovery yields at a 30 min extraction time. After optimization of the sample preparation method, screening via GC-HRMS was performed. After excluding all compounds specific to the soil and CelN traps or those in common, 516 features remained and were considered arising from *P. annua* root exudates. Therefore, the EcoRoot methodology used to assess root exudates was validated. Additionally, the BAGI and GAC scores (respectively 67.5 and 0.59) enable to prove the practicality of the methodology and the limited environmental impact of the sample preparation proposed. Nevertheless, further investigations should be conducted, especially on sample preparation steps involving, for example, the use of combinations of traps with different compositions or a reduction of the trap size to be closer to the root size to avoid soil contamination as much as possible.

### CRediT authorship contribution statement

**Victoria Bohm:** Writing – original draft, Validation, Methodology, Investigation, Data curation, Conceptualization, Writing – review & editing.
**Estelle Forey:** Writing – review & editing, Validation, Supervision, Project administration, Methodology, Conceptualization.
**Matthieu Chauvat:** Writing – review & editing, Validation, Supervision, Project administration, Methodology, Conceptualization.
**Pascal Cardinael:** Writing – review & editing, Validation, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization.
**Valerie Peulon-Agasse:** Writing – review & editing, Validation, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgements

The authors would like to thank Charles Lanel, former glass blower at the Université de Rouen Normandie, for designing and manufacturing the rhizoboxes. Additionally, we would like to thank Gaëlle Miller, a former intern at the ECODIV laboratory, P. Delporte and S. Buquet for their help on plant growth monitoring. VB is supported by a doctoral grant from the region Normandie.

### Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.jcoa.2025.100205.
# Data availability

Data will be made available on request.

# References

[1] W. Ma, S. Tang, Z. Dengzeng, D. Zhang, T. Zhang, X. Ma, Root exudates contribute to belowground ecosystem hotspots: a review, Front. Microbiol. 13 (2022) 937940, https://doi.org/10.3389/fmicb.2022.937940.

[2] D.V. Badri, J.M. Vivanco, Regulation and function of root exudates, Plant Cell Environ. 32 (2009) 666-681, https://doi.org/10.1111/j.1365-3040.2009.01926.x.

[3] D. Faure, D. Vereecke, J.H.J. Leveau, Molecular communication in the rhizosphere, Plant Soil 321 (2009) 279-303, https://doi.org/10.1007/s11104-008-9839-2.

[4] E. Oburger, D.L. Jones, Sampling root exudates - Mission impossible? Rhizosphere 6 (2018) 116-133, https://doi.org/10.1016/j.rhisp.2018.06.004.

[5] A.D. Rovira, Plant root exudates, Bot. Rev. 35 (1969) 35-57, https://doi.org/10.1007/BF02859887.

[6] H.J. Bouwmeester, C. Roux, J.A. Lopez-Raez, G. Bécard, Rhizosphere communication of plants, parasitic plants and AM fungi, Trends Plant Sci. 12 (2007) 224-230, https://doi.org/10.1016/j.tplants.2007.03.009.

[7] R.M. Callaway, W.M. Ridenour, Novel weapons: invasive success and the evolution of increased competitive ability, Front. Ecol. Environ. 2 (2004) 436-443, https://doi.org/10.1890/1540-9295(2004)002[0436:NWISAT]2.0.CO;2.

[8] A. Rugova, M. Puschenreiter, G. Koellensperger, S. Hann, Elucidating rhizosphere processes by mass spectrometry - A review, Anal. Chim. Acta 956 (2017) 1-13, https://doi.org/10.1016/j.aca.2016.12.044.

[9] J. Luster (Ed.), Handbook of Methods Used in Rhizosphere Research, Swiss Federal Research Inst. WSL, Birmensdorf, 2006.

[10] G. Neumann, S. Bott, M.A. Ohler, H.-P. Mock, R. Lippmann, R. Grosch, K. Smalla, Root exudation and root development of lettuce (Lactuca sativa L. cv. Tizian) as affected by different soils, Front. Microbiol. 5 (2014), https://doi.org/10.3389/fmicb.2014.00002.

[11] T. Tückmantel, C. Leuschner, S. Preusser, E. Kandeler, G. Angst, C.W. Mueller, I. C. Meier, Root exudation patterns in a beech forest: dependence on soil depth, root morphology, and environment, Soil Biol. Biochem. 107 (2017) 188-197, https://doi.org/10.1016/j.soilbio.2017.01.006.

[12] S. Döll, H. Koller, N.M. Van Dam, A simple, cost-effective and optimized protocol for collecting root exudates from soil grown plants, Rhizosphere 30 (2024) 100899, https://doi.org/10.1016/j.rhisp.2024.100899.

[13] A. Williams, H. Langridge, A.L. Straathof, G. Fox, H. Muhammadali, K. A. Hollywood, Y. Xu, R. Goodacre, F.T. de Vries, Comparing root exudate collection techniques: An improved hybrid method, Soil Biol. Biochem. 161 (2021) 108391, https://doi.org/10.1016/j.soilbio.2021.108391.

[14] E. Oburger, M. Dell'mour, S. Hann, G. Wieshammer, M. Puschenreiter, W. W. Wenzel, Evaluation of a novel tool for sampling root exudates from soil-grown plants compared to conventional techniques, Environ. Exp. Bot. 87 (2013) 235-247, https://doi.org/10.1016/j.envexpbot.2012.11.007.

[15] G. Neumann, T.S. George, C. Plassard, Strategies and methods for studying the rhizosphere—the plant science toolbox, Plant Soil 321 (2009) 431-456, https://doi.org/10.1007/s11104-009-9953-9.

[16] E. Oburger, B. Gruber, Y. Schindlegger, W.D.C. Schenkeveld, S. Hann, S. M. Kraemer, W.W. Wenzel, M. Puschenreiter, Root exudation of phytosiderophores from soil-grown wheat, New Phytol. 203 (2014) 1161-1174, https://doi.org/10.1111/nph.12868.

[17] S. Haase, G. Neumann, A. Kania, Y. Kuzyakov, V. Römheld, E. Kandeler, Elevation of atmospheric CO2 and N-nutritional status modify nodulation, nodule-carbon supply, and root exudation of Phaseolus vulgaris L., Soil Biol. Biochem. 39 (2007) 2208-2221, https://doi.org/10.1016/j.soilbio.2007.03.014.

[18] A.M. Stefanowicz, P. Kapusta, M. Stanek, M. Frąc, K. Oszust, M.W. Woch, S. Zubek, Invasive plant Reynoutria japonica produces large amounts of phenolic compounds and reduces the biomass but not activity of soil microbial communities, Sci. Total Environ. 767 (2021) 145439, https://doi.org/10.1016/j.scitotenv.2021.145439.

[19] W. Wojnowski, M. Tobiszewski, F. Pena-Pereira, E. Psillakis, AGREEprep – analytical greenness metric for sample preparation, TrAC Trends Anal. Chem. 149 (2022) 116553, https://doi.org/10.1016/j.trac.2022.116553.

[20] E. Forey, S.F.M. Coulibaly, M. Chauvat, Flowering phenology of a herbaceous species (Poa annua) is regulated by soil Collembola, Soil Biol. Biochem. 90 (2015) 30-33, https://doi.org/10.1016/j.soilbio.2015.07.024.

[21] N. Strehmel, C. Böttcher, S. Schmidt, D. Scheel, Profiling of secondary metabolites in root exudates of Arabidopsis thaliana, Phytochem 108 (2014) 35-46, https://doi.org/10.1016/j.phytochem.2014.10.003.

[22] V. Calabrese, I. Schmitz-Afonso, W. Riah-Anglet, I. Trinsoutrot-Gattin, B. Pawlak, C. Afonso, Direct introduction MALDI FTICR MS based on dried droplet deposition applied to non-targeted metabolomics on Pisum Sativum root exudates, Talanta 253 (2023) 123901, https://doi.org/10.1016/j.talanta.2022.123901.

[23] N. Manousi, W. Wojnowski, J. Plotka-Wasyłka, V. Samanidou, Blue applicability grade index (BAGI) and software: a new tool for the evaluation of method practicality, Green Chem. 25 (2023) 7598-7604, https://doi.org/10.1039/D3GC02347H.

[24] H. Chen, T. Tuck, X. Ji, X. Zhou, G. Kelly, A. Cuerrier, J. Zhang, Quality assessment of Japanese Knotweed (Fallopia japonica) grown on Prince Edward Island as a source of resveratrol, J. Agric. Food Chem. 61 (2013) 6383-6392, https://doi.org/10.1021/jf4019239.

[25] P. Cardinael, H. Casabianca, V. Peulon-Agasse, A. Berthod, Sample derivatization in separation science, in: V. Pino, J.L. Anderson, A. Berthod, A.M. Stalcup (Eds.), Analytical Separation Science, Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, 2015, p. 063, https://doi.org/10.1002/9783527678129.assep063.-063.

[26] J. Flieger, M. Tatarczak-Michalewska, E. Blicharska, Characterization of the cis/trans isomerization of resveratrol by high-performance liquid chromatography, Anal. Lett. 50 (2017) 294-303, https://doi.org/10.1080/00032719.2016.1178756.

[27] G. Kahnt, Trans-cis-equilibrium of hydroxycinnamic acids during irradiation of aqueous solutions at different pH, Phytochem 6 (1967) 755-758, https://doi.org/10.1016/S0031-9422(00)86017-3.

[28] A. Le Person, A.-S. Lacoste, J.-P. Cornard, Photo-degradation of trans-caffeic acid in aqueous solution and influence of complexation by metal ions, J. Photochem. Photobiol. A 265 (2013) 10-19, https://doi.org/10.1016/j.jphotochem.2013.05.004.