DART-HRMS for the Rapid Assessment of Bioactive Compounds in Ultrasound-Processed Rapeseed Meal By-Product

Abstract

In line with the recommended European policy for a zero-waste crop supply chain, a lab-pilot optimisation process to valorise the by-products of industrially produced rapeseed meal (RM) was performed. Three batches of RM were first processed into ethanol-wash solutes (EWS) and then optimised (OEWS) by an ultrasound-assisted (UA) treatment. After direct analysis in real time–high resolution mass spectrometry (DART-HRMS) analysis, data were processed applying a partial least square–discriminant analysis (PLS-DA), which retrieved the 15 most discriminative ions able to characterise the biochemical changes during the ethanol-washing and UA optimisation process. The metabolomic fingerprinting of EWS and OEWS generated an accurate and well-defined 3D spatial clusterisation based on a restricted pool of informative bioactive compounds. A significantly higher relative abundance of sinapic, azelaic, and vernolic acids and a lower incidence of the oleic and palmitic fatty acids were detected in OEWS. DART-HRMS generated a vast amount of biochemical information in one single run, also demonstrating that its association with an untargeted multivariate statistical approach would be a valuable tool for revealing specific functional biomarkers. This would eventually enhance the circular and effective use of rapeseed residuals coming from this plant’s oilseed industry.

1. Introduction

Rapeseed (Brassica napus L.) is an oil- and protein-based cultivated plant formed many thousands years ago by the natural hybridisation of Brassica spp. (e.g., B. rapa and B. oleracea), and currently ranking third worldwide among oil crops after palm and soybean with an average seed oil content of around 44% [1]. In several countries, rapeseed is the oilseed predominantly used to produce domestic vegetable oil, especially because of its high flavoured edible compound content, such as vanillin, methylvanillin, and ethylvanillin [2,3]. Recently, the cultivation of rapeseed has increased significantly, driven by a high demand for vegetable oil for biodiesel production especially from the European Union [4]. As a consequence, the expansion of rapeseed oil production has led to a proportional growth of a co-stream in the form of press cake or meal, a residual by-product biomass rich in proteins and bioactive compounds [5,6,7]. To meet the growing global demand for sustainable alternative protein sources expected in the next decades, such a rapeseed meal (RM) by-product should be valorised and utilised for higher end-uses [8]. Indeed, RM has a high potential as an alternative animal protein feed for both lactating dairy cows [9] and fattening meat-animals [10]. However, despite the fact that RM by-product could be largely used as a feedstock in livestock farming, the presence of some anti-nutritional components like glucosinolates, phenolics, phytates, and lignocellulosic fibres could negatively affect protein digestibility [11], especially when increasing levels of this by-product are used to feeding monogastric farmed animals [12]. Similar limitations have been reported also in terms of its utilisation as a food ingredient since, if it is to be used as a natural source of proteins with versatile functional properties (e.g., foaming, emulsification, film-forming), the proteins need to be extracted and isolated from the residual press cakes and meals [1]. Moreover, the presence of intense bitter and astringent off-flavours, due to a wide range of phytometabolites such as glucosinolates and phenolic compounds, limiting the palatability in human consumption, still poses a challenge to the use of protein isolates in the food and beverage sector [13]. Therefore, in order to comply with a more circular and environmentally friendly European common agricultural policy (CAP), innovative solutions should be explored to support and boost the recycling of these protein-rich meals from the rapeseed oil industry [14]. This includes their processing into powder ingredients that are especially enriched in bioactive and/or superior taste profile molecules. Among these natural bioactive compounds, polyphenols are a wide and varied chemical family characterised by one or more aromatic rings substituted with hydroxyl groups in their structure, and they have been found to exhibit many beneficial biological activities [8]. Indeed, residuals after oil extraction from many varieties of rapeseed have been reported to have large amounts of polyphenols, which have strong antioxidant properties associated with anti-mutagenic and anti-inflammatory effects [15,16,17]. Several studies on animal models have reported that dietary supplementation with polyphenols isolated from oilseeds, including polyphenols isolated by using an ethanol extract, could help ameliorate metabolic disorders [18,19].

It has already been demonstrated that the use of washing solvents is a powerful approach to extract desirable healthy compounds, such as polyphenols, from raw oilseed by-products. Among these biorefinery protocols, the use of ethanol seems to be effective to recover bioactive compounds while also avoiding the interactions with anti-nutritional substances (i.e., soluble non-protein components) from by-product meals, as well as an authorised process within the food industry [20]. Furthermore, the use of ultrasounds as an effective pre-treatment method for obtaining targeted changes in both the molecular profile and compound-related biological activities has already been suggested [21,22]. Similarly, treatment based on microwave irradiation affected the composition of phenolic compounds such as sinapine, sinapoyl glucose, sinapic acid, and sinapoyl malate [23].

However, an in-depth characterisation of powdered ingredients through a comprehensive metabolomic approach, which can identify and quantify the presence of bioactive compounds and systematically provide information on the effects of a specific on-going physical and/or chemical processing at a metabolite level, remains a challenge [24].

The metabolomics analysis performed by high resolution mass spectrometry (HRMS) has several advantages. The ability of HRMS to precisely measure mass-to-charge ratios allows for more accurate compound detection and elemental composition determination [25,26]. Furthermore, it facilitates the distinction between isobaric molecules, which possess equivalent nominal masses. More recently, a plethora of innovative analytical techniques, including ambient ionisation mass spectrometry (AIMS) [27], have been coupled to HRMS and proposed with the objective of obtaining a comprehensive understanding of the composition of by-products and of their nutritionally enhanced derivatives, as well as of novel food. The majority of AIMS techniques use an external ionisation source to generate ions prior to introduction into the mass spectrometer without the need for liquid or gas chromatography effluents. These techniques, including the direct analysis in real time–high resolution mass spectrometry (DART-HRMS), facilitate the simultaneous characterisation of a vast array of bioactive compounds that could potentially enhance the nutritional value of plant and food by-products [28]. In fact, such advanced techniques offer a rapid, sensitive, and versatile approach to measure the chemical signatures of food compounds. In particular, as a rapid non-targeted foodomics technique able to profile the chemical changes in pre-processed foods from both vegetable [29] and animal raw materials [30,31], DART-HRMS has represented a significant advancement in food analysis, impacting a number of different fields, including food safety [32], quality control, and product authentication issues [33]. Thanks to a near real-time analysis and minimal sample preparation, DART-HRMS is a key technology at our disposal to provide consumers worldwide with safer and higher-quality food [34]. That is why DART-HRMS metabolomic profiling should be considered for a reliable assessment of the changed chemical signatures occurring during the recycling process of the RM into an optimised functional powdered ingredient.

Therefore, the aim of this study is to provide a novel insight into the metabolomic changes in a rapeseed meal (RM) by-product when it is first processed into an ethanol-wash solute (EWS) and then submitted to an ultrasound treatment for optimisation (optimised EWS, OEWS). To reveal the statistically significant modifications in the bioactive compounds, the metabolomic fingerprinting of EWS and OEWS samples was explored via a chemometric approach based on DART-HRMS combined with a partial least square–discriminant analysis (PLS-DA) to retrieve the most significant biomolecules that could potentially track the specific chemical pathways for the tested optimisation process.

2. Materials and Methods

2.1. Processing of the Rapeseed Meal By-Product and Experimental Design

In this study, all experimental procedures were conducted using three batches of RM as a by-product from the industrial production of a Bulgarian local company. The production of these RM residuals from rapeseed seeds via thermal treatment followed by oil extraction with hexane has already been described [35]. In order to promote a selective extraction of antioxidant bioactive compounds (e.g., phenolic compounds), the RM samples were processed into ethanol-wash solutes (EWS), and then doubly optimised (OEWS) by an ultrasound-assisted (UA) extraction performed following the steps reported in previous studies [36]. Briefly, the rapeseed meal was treated four times with an aqueous ethanol solution (75%), then the spent ethanol-washed liquids were collected, mixed, vacuum-concentrated (RV3 V Rotary Evaporator, IKA^®, Staufen, Germany), and lyophilised (Lyovac GT2, Leybold-Heraeus, Hanau, Germany) to recover powdery EWS. Distilled water was used as the extraction solvent of EWS powder at a ratio of 1/50 (w/v), at room temperature for 20 min, under constant stirring (220 rpm). After that, the ultrasound-assisted extraction (UAE) of this solution was performed with a SONOPULS (HD 2200.2, Bandelin, Berlin, Germany) ultrasonic homogeniser at 20 ± 0.5 kHz frequency, with a KE 76 tip (Bandelin electronic GmbH & Co. KG, Berlin, Germany). The independent variables studied were amplitude (10–35%) and time (1–8 min). After the first ultrasound treatment, the samples were centrifuged at 9500× g, at 4 °C for 5 min, and a second UAE was carried out under the same conditions.

2.2. Fingerprinting Analysis by DART-HRMS

Both EWS and OEWS samples were analysed in duplicate by DART-HRMS to assess the effect of a repeated chemical stamp-based protocol for the optimisation of RM residuals via a preliminary extraction with ethanol and then an UA processing procedure, thus ensuring a high level of compliance with the reproducibility, interpretability, and reusability of mass spectrometry data. An aliquot of approximately of 1 g of each sample (a total of n = 6 of EWS and n = 12 of OEWS) was extracted using 10 mL of ethylacetate (Sigma Aldrich, Darmstadt, Germany). A 5 µL volume of each extract was transferred on a glass capillary rod that was then positioned onto a Dip-it(R) autosampler (IonSense, Saugus, MA, USA). Subsequently, the melting point tubes were automatically moved by the autosampler at a constant speed of 0.3 mm/s through the DART SVP 100 source (IonSense, Saugus, MA, USA) in front of the orbitrap MS (Thermo Fisher Scientific, Waltham, MA, USA). Non-targeted analyses of the extracts were carried out with an Exactive Plus Orbitrap Mass Spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). NH₃ (33% purity, from Sigma Aldrich, St. Louis, MO, USA) was used as a dopant [37]. The parameters of the DART and the Orbitrap analysers were set as described in previous studies [38]. The spectra were acquired in negative ion mode in the mass range 75–1125 Da with a resolution of 70,000 FWHM. The extracts were analysed in duplicate and the spectra were converted into .csv files as already described in a previous study [39]. The tentative assignment of the ions was performed by interrogating the foodomics database library (FOODB, www.foodb.ca, accessed on 3 March 2025). In order to confirm the tentative annotation retrieved by the FOODB library, a literature search was also carried out to confirm the validity of the assignment.

2.3. Statistical Analysis

The DART-HRMS spectral data were pre-processed by using the R statistical software (release 4.3.2) with the MALDIquant package and statistically analysed using the web platform 5.0 (www.metaboanalyst.ca, accessed on 3 March 2025). Firstly, the absolute intensities of each spectrum were normalised by relative intensity of the most intense signal. The isotopes in the spectral data were removed using an internally developed R code. The ions with a signal-to-ratio lower than 5 were removed, and the signals were aligned with a tolerance of 15 ppm. Afterwards, the pre-processed spectral dataset was submitted to PLS-DA. The PLS-DA scores plot and coefficient plot were visualised. The outcomes of the PLS-DA were validated by leave-one-out cross-validation (LOOCV). For the 15 most significant ions, the box-whiskers plots were generated for an easier visualisation of their changes in relative abundance.

3. Results

3.1. Ambient Mass Spectrometry Spectra

Figure 1 shows a comparison between the chemical profiles of EWS and its optimised derivative (OEWS). In the spectra, the tentative annotation of the main ions characterising EWS are reported in green, while those characterising OEWS are reported in red. In the EWS samples, it is possible to note a greater relative intensity of succinic acid (m/z 117.0194), malic acid (m/z 133.0141), and indole-β-carboxylic acid (m/z 160.0404). Instead, the odorous metabolite dimethyldisulphide (m/z 135.0305), the natural inducer of plant defense azelaic acid (m/z 187.0974), and the phenolic compounds annotated as sinapic acid (m/z 223.0612) and vernolic acid (m/z 295.2279) exhibited a higher relative abundance in the optimised samples (OEWS). The OEWS were also characterised by lower levels of palmitic acid (m/z 255.2335) and oleic acid (m/z 281.2486).

3.2. Multivariate Statistical Analysis

The main purpose of this experimental trial was to establish the chemical fingerprints of industrial recycled RM processed using an ethanol-based extraction (i.e., EWS samples) and the further changes due to an optimisation treatment based on the use of ultrasound (i.e., OEWS samples). To this aim, a partial least square–discriminant analysis (PLS-DA) was carried out to allow for a graphical demonstration of the potential of DART-HRMS to capture the chemical signatures of EWS and of the optimised derivates (OEWS), as reported in Figure 2.

As reported in Figure 2A, the spatial separation and clustering of the two groups of samples is defined by the PLS-DA. Precisely, the total variance of the model is explained by the three components C1 (55.3%), C2 (18.0%), C3 (17.2%) which are defined in the three-dimensional space. The differences in the metabolic fingerprints of the two rapeseed-derived matrices observed in the spectra (Figure 1) are confirmed by the graphical spatial discrimination. The outcomes of the PLS-DA were validated by LOOCV as shown in the Supplementary Materials (Figure S1). Specifically, the performance measures of the LOOCV, using five components and expressed as accuracy = 1.00, Q² = 0.91, and R² = 0.98, are also summarised in Figure S1. Figure 2B illustrates the most helpful fifteen ions (m/z values), together with their coefficient values, that aid the separation into the two groups. The box-whisker plots of the fifteen ions are reported in Figure 3 and their tentative annotations are listed in Table 1.

3.3. Chemical Changes Between EWS and OEWS

Figure 3 illustrates the changes in metabolites occurring after the UA optimisation. The EWS were characterised by a high relative abundance of succinic acid (m/z 117.0194), malic acid (m/z 133.0141), indole-β-carboxylic acid (m/z 160.0404), pyridoxic acid (m/z 164.0355), diaminopurine (m/z 185.0357), and fatty acids such as palmitic acid (m/z 255.2335) and oleic acid (m/z 281.2486). Meanwhile, the OEWS showed a high intensity of phenols, such as sinapic acid (m/z 223.0612) and vernolic acid (m/z 295.2279), and it was also characterised by the odorous dimethyldisulphide (m/z 135.0305) and dihydroxypurine (m/z 151.0260). As shown in Figure 2, the fatty acids are less abundant in the optimised OEWS. The improvement in the levels of phenolic compounds, already visible in the DART-HRMS spectra (Figure 1), was confirmed by the graphical representation throughout a set of box-and-whisker plots (Figure 3). Overall, in the OEWS samples, these results suggested a decrease in the FA levels and an increase in phenols. This pattern could be due to the physical treatment based on ultrasounds that removed some FA or other lipolytic compounds and increased the phenols.

4. Discussion

The experimental trial was designed in order to detect the changes in the metabolic fingerprints between the ethanol-washed solute (EWS) samples coming from a rapeseed meal (RM) industrial by-product and their derivates optimised via an ultrasound-assisted treatment. Such metabolic modifications in the bioactive compounds were assessed by DART-HRMS characterisation coupled with a chemometric approach. The use of DART-HRMS as an untargeted and alternative AIMS technique instead of the more traditional hyphenated methods allowed us to annotate the most informative ions and to be able to perform an accurate visual clustering of the EWS and OEWS samples according to a fast and streamlined protocol. In fact, DART-HMS revealed its capability to perform a precise, rapid and preliminary screening of a diverse class of molecules that present varied chemical structures, which is a first step to identify potentially useful phytochemicals whose chemical structure will need to be further confirmed by advanced analytical techniques, together with their biological roles as well as nutritional and/or functional benefits [40]. Knowing both the types and relative abundances of the biomolecules detected in the two processed RM matrices could be useful for chemotaxonomic and biorefinery purposes, and it might also expand the basis for their future phytochemical exploration and food-confectionery applications.

The main experimental outcomes revealed the recovery of different relative abundances of biomolecules in the two processed RM by-product derivates. The first processing step based on an ethanol-washing treatment (i.e., EWS samples) seemed to be more correlated to a higher abundance of some residual FA, such as the palmitic and oleic ones, and to a restricted pool of other acids. In this respect, the 4-pyridoxic acid is a phosphorylated counterpart of pyridoxine, a B6 vitamer.

In addition, both the EWS and OEWS samples showed the presence of two purine derivatives (natural nucleoside analogue): 2,6-diaminopurine and 6,8-dihydroxypurine (also known as oxohypoxanthine). It is worth noting that the amount of purines and purine derivatives in the diet needs to be controlled as they increase the risk of gout [41]. In particular, when the body breaks down purines, it produces uric acid, which can lead to hyperuricemia, crystal formation in the kidney, intermittent gout and chronic gout [42]. As a consequence of the UA treatment, the OEWS samples exhibited a decrease in the diaminopurine levels and a slightly increase in dihydroxypurine (Figure 3).

Focusing on final food applications, the DART-HRMS-based screening showed that the OEWS samples tend to be characterised by a reduction in FA and in the incidence of other lipolytic compounds, an outcome already observed in a similar trial on sunflower by-products [39]. The UA physical treatment promoted a relatively high concentration of sinapic acid, a bioactive phenolic compound, which could be beneficial for human health thanks to its anti-microbial, anti-inflammatory, antioxidant and anti-cancer activity [43]. Note that sinapine (sinapoyl choline), sinapoyl glucose, and hydroxy-cinnamic derivatives, precursors of sinapic acid, are very abundant in rapeseed seeds and, during germination, more than 70% of sinapine is released as free sinapic acid [14,44]; and, therefore, its efficient recovery from rapeseed oil by-products must be pursued [45]. Indeed, an efficient recovery of useful compounds from industrial rapeseed oil by-products can be seen as one of the key drivers towards a circular economy, with the UA treatment proposed in this study being one of the tools that are potentially available. The OEWS samples also exhibited elevated levels of both lactic acid and dimethyldisulfide. It is noteworthy that the aforementioned acid imparts a cheese-like and sweaty flavour to rapeseed meal, while S-containing compounds are responsible for the sulphury odour note observed in rapeseed oil [46].

Moreover, the UA optimisation process also led to a relatively higher abundance of vernolic and azelaic acids, which both derive from FA. The first one (cis-12,13-epoxy-cis-9-octadecenoic acid) is a naturally occurring epoxy FA derived from the epoxidation of linoleic acid. Vernolic acid has shown several technological properties, such as a low viscosity, and it is pourable at temperature below 0 °C. However, the plant extraction of vernolic and related epoxy FA is still an important issue because only a few plants contain high amounts of these epoxy FA [47]. Azelaic acid can be obtained from oleic acid by oxidative cleavage [48], and it is considered as a bio-based monomer for the synthesis of several products useful for packaging, cosmetic, and pharmaceutical applications [49]. Given the higher levels of oxidation-derived compounds (dihydroxypurine, vernolic acid, and azelaic acid), we can speculate that the UA treatment caused the oxidation of some metabolites and a reduction in FA.

Therefore, as confirmed by the rapid DART-HRMS screening method, the UA optimisation generating OEWS could facilitate the enrichment of the final product with healthy bioactive compounds, such as phenolic sinapic acid, epoxy vernolic FA, and azelaic acid, while also lowering the incidence of residual FA. Thus, diverse and potentially important future feed and food applications exist for a whole-crop biorefining scheme based also on the valorisation of RM by-product involving the isolation and/or extraction of valuable bioactive compounds.

5. Conclusions

In this experimental research, a rapid, easy-to-perform, and low-cost method based on a DART-HRMS screening combined with a multivariate statistical approach was applied to assess the biochemical changes occurring between EWS and their derivates optimised via an UA process (OEWS): a two-step pilot chemical-stamp process performed to valorise the circular use of rapeseed meal (RM) by-products. Indeed, both the RM residuals after ethanol pre-processing treatment (EWS) and their OEWS derivates exhibited an interesting metabolomic fingerprinting, especially due to the presence of several bioactive compounds, such as sinapic, azelaic, and vernolic acids, in the OEWS. The metabolomics data coming from these valorised RM by-product derivates should be considered and a targeted isolation process should be developed to exploit the biological properties of the resulting bioactive compounds, as well as their applications in the production of functional foods. This would eventually enhance the zero-waste rapeseed crop supply chain. Moreover, the application of ambient ionisation mass spectroscopy (AIMS) generated a vast amount of biochemical information in one single run, demonstrating that DART-HRMS would be a valuable tool for revealing specific functional biomarkers.

Author Contributions

Conceptualization, A.L., D.M. and S.S.; methodology, A.L., C.Z., D.M., V.C. and A.T.; software, A.M., C.Z., S.S. and A.T.; validation, A.L., A.M., D.M., V.C., A.K., H.K., M.C., S.S. and A.T.; formal analysis, D.M., V.C., A.K., H.K., M.C., G.M. and G.R.; investigation, A.L., A.M., C.Z., D.M., V.C., A.K., G.M., G.R. and A.T.; resources, A.L., D.M., V.C. and S.S.; data curation, A.M., C.Z., M.C., G.M., G.R., S.S. and A.T.; writing—original draft preparation, A.L., D.M., V.C., G.R., S.S. and A.T.; writing—review and editing, A.L., G.R., S.S. and A.T.; visualization, A.M., C.Z., D.M., V.C., A.K., H.K., M.C., G.M., G.R., S.S. and A.T.; supervision, A.L., G.R., S.S. and A.T.; project administration, A.L., S.S. and A.T.; funding acquisition, A.L., D.M. and S.S. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available in the article and Supplementary Material.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:

AIMS	Ambient ionisation mass spectroscopy
CAP	Common agricultural policy
DART-HRMS	Direct analysis in real time–high resolution mass spectrometry
EWS	Ethanol-wash solutes
FA	Fatty acid
N/A	Not assigned
OEWS	Optimised EWS
PLS-DA	Partial least square–discriminant analysis
RM	Rapeseed meal
UA	Ultrasound-assisted

Footnotes

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Figures and Table

Figure 1 Representative spectra of rapeseed meal (RM) ethanol-washed solutes, EWS (A) and their optimised derivatives, OEWS (B), acquired by direct analysis real time–high resolution mass spectrometry (DART-HRMS) in negative ion mode. The tentative annotation of the ions characterising the EWS are reported in green; those of OEWS are reported in red.

Figure 2 Differences in the chemical signatures between the rapeseed meal (RM) ethanol-wash solutes (EWS) and their optimised derivates (OEWS) obtained by partial least square–discriminant analysis (PLS-DA) performed on the direct analysis in real time–high resolution mass spectrometry (DART-HRMS) data. (A) illustrates the three-dimensional scores plot showing the clustering of the EWS (•, green circles) and their optimised derivates OEWS (•, red circles). (B) illustrates the coefficient plot of the most discriminant informative ions. The assignments of the most discriminant ions are also given in Table 1.

Figure 3 Box-and-whisker plots showing the metabolites with the higher coefficients retrieved in the partial least square–discriminant analysis (PLS-DA), acquired by DART-HRMS. In (A–O), each subfigure contains information on one of the tentatively assigned metabolites (N/A, not assigned). The ethanol-washed solutes (EWS) are represented by green boxes, while the optimised samples (OEWS) are represented by red boxes. Each box has the 25th and 75th percentiles labelled at the bottom and top, respectively; the median is indicated by the midline; the mean is represented by the yellow square and the entire data range is represented by the black circles.

Table 1

Discriminative compounds retrieved via the partial least square–discriminant analysis (PLS-DA) that enabled the differentiation between EWS and OEWS in the model. Observed m/z, theoretical m/z mass, error (ppm), elemental formula, type of ion, and tentative annotation are listed.

Observed m/z	Theoreticalm/z	Error (ppm)	Predicted MolecularFormula	IonType	TentativeAnnotation
			EWS
117.0194	117.0193	0.9	C4H6O4	[M−H]−	Succinic acid
133.0141	133.0142	−0.8	C4H6O5	[M−H]−	Malic acid
137.0269	−	−	−	−	N/A
160.0404	160.0404	0.0	C9H7NO2	[M−H]−	Indole-β-carboxylic acid
164.0355	164.0348	4.3	C8H9NO4	[M−H2O−H]−	4-Pyridoxic acid
185.0357	185.0348	4.9	C5H6N6	[M+Cl]−	2,6-Diaminopurine
255.2335	255.2330	2.0	C16H32O2	[M−H]−	Palmitic acid
281.2486	281.2486	0.0	C18H34O2	[M−H]−	Oleic acid
			OEWS
89.0242	89.0244	−2.2	C3H6O3	[M−H]−	Lactic acid
135.0305	135.0308	−2.2	C2H6S2	[M−H]−	Dimethyldisulphide
151.026	151.0261	−0.7	C5H4N4O2	[M−H]−	6,8-Dihydroxypurine
187.0974	187.0976	−1.1	C9H16O4	[M−H]−	Azelaic acid
161.0444	161.0450	−3.7	C6H12O6	[M−H2O−H]−	Hexose
223.0612	223.0612	0.0	C11H12O5	[M−H]−	Sinapic acid
295.2279	295.2279	0.0	C18H32O3	[M−H]−	Vernolic acid

EWS, ethanol-wash solutes; OEWS, ultrasound-assisted optimised EWS; N/A, not assigned.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app15115952/s1, Figure S1: Performance indicators for the evaluation of the PLS-DA.

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