Next Article in Journal
A Simple, Semi-Automated, Gravimetric Method to Simulate Drought Stress on Plants
Next Article in Special Issue
Soil Water Content Directly Affects Bud Burst Rate in Single-Node Cuttings of Perennial Plants
Previous Article in Journal
Temporary Immersion Bioreactor System as an Efficient Method for Mass Production of In Vitro Plants in Horticulture and Medicinal Plants
Previous Article in Special Issue
The Impact of Irrigation on Olive Fruit Yield and Oil Quality in a Humid Climate
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Using HPLC–MS/MS to Assess the Quality of Beet, Mizuna, Lettuce and Corn Salad after Juglone and Walnut Leaf Extract Treatments

Department of Agronomy, Biotechnical Faculty, University of Ljubljana, Jamnikarjeva 101, 1000 Ljubljana, Slovenia
*
Author to whom correspondence should be addressed.
Submission received: 7 January 2022 / Revised: 26 January 2022 / Accepted: 28 January 2022 / Published: 29 January 2022
(This article belongs to the Special Issue Plant Responses to Stress and Environmental Stimulus)

Abstract

:
The present study was carried out to investigate the yield, quality, and metabolomic responses of four different vegetable crops to treatments with pure juglone standard and walnut (Juglans regia L.) leaf extract at soil concentrations found in walnut orchards. A total of 60 phenolic compounds were identified and quantified, some for the first time in these crop vegetables. Beta vulgaris L. and Lactuca sativa L. were less susceptible to juglone. For crop quality, B. vulgaris showed the least effects of the different treatments. Both Brassica rapa L. var. japonica and Valerianella locusta Laterr. showed lower yields, even at the lower juglone concentration, and reduced quality, so their cultivation in juglone-containing soils should be avoided. This study also investigated leaf quality at different ages and the quality and yield of these crop vegetables grown under the influence of allelochemicals, to determine the influence of allelochemicals on metabolomics and, thus, on the uptake of phenolic compounds considered to be beneficial to human health.

Graphical Abstract

1. Introduction

Consumption of fresh or processed vegetables is an essential part of the human diet and has been associated with many health benefits (e.g., reduced diet-related diseases and risk of obesity) [1]. The most important factors that contribute to the nutritional and health benefits of vegetables are vitamins and phytochemicals. To date, over 5000 phytochemicals have been identified. Phytochemicals are usually classified into three major classes: (i) phenols, (ii) terpenes, and (iii) nitrogen-containing compounds [2]. Of these phytochemicals, phenols, or phenolic compounds, are the best-studied and most abundant group of phytochemicals and are associated with various health benefits [3,4]. Phenolic compounds also have important roles in the quality of vegetables, as they affect their taste, appearance, and stability [5].
The concentration and types of phenolic compounds vary within different vegetables and plant tissues [6]. Phenolic compounds can be unique and found only in one crop or cultivar, or they can be present across several varieties. They also have important roles in plant defence against pathogens, predators, and biotic and abiotic stresses [7,8]. If a plant is under stress, its content of phenolic compounds increases as a response to the stress [8], and therefore, the plant uses energy and nutrients meant for growth and other primary functions to produce these defensive compounds [9,10,11]. As higher levels of phenolic compounds are associated with higher vegetable quality, plant stress is considered beneficial to some degree [9]. The problem is that the higher the levels of phenolic compounds, the lower the growth of the plants and, therefore, the lower the yield, so there is the need for a balance between quality and yield. While some stress factors can be controlled through agronomic practices (e.g., irrigation, pest and disease control, fertilisation), others are more difficult or are not possible to control (e.g., plant residues and fungi in the soil) [9].
Plant residues can release allelochemicals into the soil, some of which have positive effects on plant growth, while others have negative effects. In some plants, allelochemicals can cause deformity, chlorosis, and wilting, thus reducing vitality, slowing down or preventing germination, hindering growth and development, and increasing susceptibility to disease, which can lead to their collapse [12]. In agriculture, this is especially problematic when one crop follows another. The greatest problems occur when walnut (Juglans regia L.) orchards are replaced by other crops because walnuts contain one of the first and most studied allelochemicals—juglone [13]. Juglone is released into the soil and affects the growth of surrounding crops and of crops planted after the walnut trees are cut down, with effects lasting for years [12].
Although clearing an old orchard to make way for new varieties or crop fields is common practice, little is known about the short- and long-term effects of allelochemicals that might still be present in the soil, and how they might affect the quality and yield of future crops [12]. There have been some studies on the effects of juglone, but most have focused on seed germination rather than mature crop yield or quality [11,13,14].
Therefore, the aim of the present study was to investigate the yield, quality, and molecular responses to known concentrations of juglone alone and in walnut leaf extract with concentrations of juglone normally found in the soil of walnut orchards [15], based on four different vegetable crops: beet (Beta vulgaris L.), mizuna (Brassica rapa L. var. japonica), lettuce (Lactuca sativa L.), and corn salad (Valerianella locusta Laterr.). The goal was also to determine whether juglone is really the crucial and only allelochemical in walnut, or whether there are other allelochemicals that have remained hidden in the shadow of juglone, as suggested more recently [13]. The data obtained represent an important basis for determining which crop varieties are susceptible to juglone and/or walnut leaf allelochemicals, and how these allelochemicals affect the yield and metabolomics of selected crops that influence human health and nutrition.

2. Materials and Methods

2.1. Plant Material

To determine whether pure juglone and a juglone-containing leaf extract have the same effects on different crop vegetables, or whether the effects are specific, four commonly cultivated crop vegetables were used: beet (Beta vulgaris L.), mizuna (Brassica rapa L. var. japonica), lettuce (Lactuca sativa L.), and corn salad (Valerianella locusta Laterr.). The juglone concentrations used were based on our previous germination study [13]. The plants were treated using (i) two control treatments, with K1 as the juglone extraction medium and vehicle control (0.17% dimethylsulphoxide (DMSO), 0.17% ethanol in H2O) and K2 as the water control; (ii) positive control pure juglone treatments, prepared for final juglone concentrations of 1 mM and 10 μM in extraction medium; (iii) leaf juglone extract, prepared for the final juglone concentration of 10 μM in extraction medium. The juglone was dissolved in the extraction medium, as it is only partially soluble in water (52 mg/L), and thus, the required concentration of 1 mM control juglone cannot be achieved in water alone. As previously noted [13], studies that have used >100 μM juglone dissolved in water are questionable at best.

2.2. Growing Conditions

The experiment was conducted using nutrient film technique (NFT) hydroponics systems in a greenhouse, to better control the environment (especially to control the soil as a medium) and the juglone concentrations in the water. Five NFT systems were used, one for each treatment. Each NFT system had 4 rows with 10 plants of the same crop vegetable grown in each row, for a total of 5 biological repetitions per measure (5 for metabolomics studies and 5 for yield determination).
The plants were grown from seed in a greenhouse. After the appearance of the third leaf, the roots of the seedlings were washed to remove the growth substrate, and the seedlings were placed in plastic pots filled with rockwool. Overall, 50 evenly grown plants per crop vegetable were transferred to an NFT system, where they were grown for 3 weeks with added nutrients, as reported previously [16]. After this acclimatisation in the NFT system for 3 weeks, the treatments were added. When the crops reached technological maturity, they were collected and further analysed.

2.3. Chemicals and Plant Material

The plants were grown from seeds obtained as follows: Beta vulgaris L. ‘Delta’; Brassica rapa L. var. japonica ‘Mizuna grun’; Lactuca sativa L. ‘Grazer Krauthäuptel 2 Treibstamm’; Valerianella locusta Laterr. ‘Verte de Cambrai’ (Austrosaat AG, Wien, Austria).
The leaf extract was prepared in the extraction medium, with HPLC–mass spectrometry (MS) used to determine the juglone content as accurately as possible. The control juglone and leaf extract dilutions were prepared as previously described [13].
The following standards were used: p-coumaric acid, ferulic acid, quercetin-3-O-galactoside, quercetin-3-O-glucoside, kaempferol-3-O-glucoside, apigenin-7-glucoside (Fluka Chemie GmbH, Buchs, Switzerland); neochlorogenic acid (3-caffeoylquinic acid), chlorogenic acid (trans-5-caffeoylquinic acid), cryptochlorogenic acid (4-caffeoylquinic acid), sinapic acid, caffeic acid, gallic acid, luteolin-7-glucoside, juglone (5-hydroxy-1,4-naphthoquinone) (Sigma-Aldrich Chemie GmbH, Steinheim, Germany); gluconapin and isorhamnetin-3-O-glucoside (Extrasynthese, Genay, France).
A Milli-Q water purification system (Millipore, Bedford, MA, USA) was used to bi-distil and purify the water used in the preparation of the samples. The acetonitrile and formic acid used for the mobile phases for MS analysis were HPLC–MS grade (Fluka Chemie GmbH, Buchs, Switzerland). The methanol used for the phenolic compound extraction was HPLC–MS grade (Sigma-Aldrich, Steinheim, Germany).

2.4. Sampling of the Plants

When the plants had reached technological maturity, they were collected and analysed. First, all of the roots were cut from the plants. Once removed from the plants, the roots and leaves were weighed to determine the yield per plant for the different treatments. To determine the dry weights, five sets of roots and leaves per crop vegetable and treatment were placed in an oven at 105 °C, to constant mass. The remaining five leaves per crop vegetable and treatment were divided into three categories: (i) young leaves (undeveloped leaves); (ii) semi-old leaves (the remaining fully developed leaves); (iii) old leaves (four outer fully developed leaves). Thereafter, the fresh leaves were immediately frozen with liquid nitrogen and stored at −20 °C until further analysis.

2.5. Extraction of the Phenolic Compounds

The protocol for extraction of the individual phenolic compounds was as previously described [13]. Briefly, 200 mg of previously lyophilised samples of B. vulgaris, B. rapa var. japonica, L. sativa, and V. locusta were extracted at a tissue:solution ratio of 1:100 (w/v). The phenolics extraction medium used was 80% methanol and 3% formic acid in water.

2.6. Preparation of J. regia Leaf Extract

Leaves for the leaf extract were obtained on 10 September 2020, from a 24-year-old J. regia tree grown at a planting density of 10 m × 10 m. It belonged to the French cultivar ‘Franquette’, which has been most frequently studied and used in research. Leaves were collected from the south side of the tree, from the middle part of the canopy, placed in a paper bag, frozen with liquid nitrogen, and then lyophilised. After lyophilisation, the leaves were ground with an automatic grounder (IKA A11 Basic, IKA-Werke GmbH & Co., KG, Köln, Germany) and added to the extraction medium containing 0.17% DMSO and 0.17% ethanol in H2O. The extraction was performed in an ultrasonic bath filled with ice (Sonis 4; Iskra Pio, Sentjernej, Slovenia) for 60 min. The extraction was then centrifuged at 10,000× g for 10 min at 4 °C (5810 R; Eppendorf, Hamburg, Germany). A sample was taken from the extract (i.e., supernatant) for quantification of juglone by HPLC–MS. The samples were then diluted to prepare the required leaf extract containing 10 µM juglone (referred to here as ‘leaf juglone’). Parallel juglone solutions were prepared from the juglone dissolved in the extraction medium (0.17% DMSO, 0.17% ethanol in H2O) at the required final juglone concentrations (1 mM and 10 µM), referred to here as ‘control juglone’.

2.7. HPLC–Mass Spectrometry Analysis of Individual Phenolic Compounds

The individual phenolic compounds were analysed on a UHPLC system (Vanquish; Thermo Scientific, Waltham, MA, USA). The diode detector used was at 350 nm for flavonols and 280 nm for the other phenolic compounds. The spectra were recorded between 200 nm and 600 nm. A C18 column (Gemini 150 × 4.60 mm; 3 μm; Phenomenex, Torrance, CA, USA) operated at 25 °C was used to separate the phenolic compounds. Solvent A was 0.1% formic acid with 3% acetonitrile in bi-distilled water (v/v/v), and solvent B was 0.1% formic acid with 3% bi-distilled water in acetonitrile (v/v/v). The flow rate of elution was 0.6 mL/min. The gradient, washing, and reconditioning of the column between samples were similar to those described previously [17], with minor modifications. The gradient used was as follows: 0–15 min, 5–20% B; 15–20 min, 20–30% B; 20–25 min, 30–50% B; 25–30 min, 50–90% B; 30–35 min, 90–100% B; 35–45 min, 100–5% B; 46–50 min, 5% B.
Identification of the phenolic compounds was achieved by tandem MS (MS/MS; LCQ Deca XP MAX; Thermo Scientific, Waltham, MA, USA), with heated electrospray ionisation operated in negative ion mode. The parameters were as follows: sheath temperature, 320 °C; sheath gas, 50 arb; auxiliary gas, 20 arb; ion spray voltage, 3.5 kV; capillary temperature, 320 °C; capillary voltage, 10.0 V; tube lens, −68 V. Scans were performed from m/z 50 to 2000. The collision energy was 35 eV, with helium used as the collision gas to achieve collision-induced dissociation. The Xcalibur 2.2 software (Thermo Fischer Scientific Institute, Waltham, MA, USA) was used for data acquisition.
Known compounds were identified and quantified using external standards, with the literature data and MS fragmentation used for identification of the unknown compounds. The quantification of unknown compounds was based on a similar standard. Total flavonols, total flavones, total hydroxycinnamic acids, and total analysed phenolics content (TAPC), which represents the sum of all of the identified phenolics, are expressed as g/kg fresh weight, while individual phenolic compounds are expressed as mg/kg fresh weight.

2.8. Statistical Analysis

The data were collated using Microsoft Excel 2016 and R commander (Package Rcmdr) version 2.7.1. (Team, R.D.C., 2008, Stanford, CA, USA). For each methodology, five biological repetitions were performed. Data are expressed as means ± standard error (SE). One-way analysis of variance (ANOVA) with Tukey tests was used to determine significant differences between treatments, and statistical means were calculated at the 95% confidence level to determine the significance of the differences.

3. Results and Discussion

3.1. Identification of Individual Phenolic Compounds in the Crop Vegetables

A total of 60 phenolic compounds were identified based on the previous literature data: 15 for B. vulgaris; 15 for B. rapa var. japonica; 17 for L. sativa; 13 for V. locusta. Some of these were identified for the first time in these crop vegetables. Of these 60 compounds, 9 were identified, and their fragmentation was confirmed using standards. The remaining compounds were tentatively identified according to their pseudo-molecular ions (i.e., [M-H]) and specific fragmentation patterns (i.e., MS2, MS3). The phenolic compounds identified, their fragmentation, and the standards used to express them, are given in Table 1. Representative chromatograms of the phenolic compounds identified can also be seen in the Supplementary Materials.
For the 25 hydroxycinnamic acids, 4 were identified through the use of standards and their fragmentation: neochlorogenic acid (3-caffeoylquinic acid); cryptochlorogenic acid (4-caffeoylquinic acid); chlorogenic acid (trans-5-caffeoylquinic acid); ferulic acid. The remaining 21 hydroxycinnamic acids were identified through their typical fragmentation patterns. p-coumaric acid and caffeic acid derivatives were identified through their fragmentation patterns of MSn ion m/z 163 and 119 and m/z 179, as reported by Liu et al. [18]. cis 5-O-p-coumaroylquinic acid, trans 5-O-p-coumaroylquinic acid, caffeoyltartaric acid hexoside, and dicaffeoylquinic acid were identified through their fragmentation patterns as previously reported for V. locusta and L. sativa by Hernández et al. [19] and Abu-Reidah et al. [20]. Coumaroyl malate, sinapoyl malate, sinapoyl glycoside, feruloyl malate, and caffeoyl malate were identified by their specific fragmentation patterns as reported for pak choi (Brassica campestris L. ssp. chinensis var. comunis) by Harbaum et al. [21], which are described here for the first time for B. rapa var. japonica. Ferulic acid derivatives were identified through their fragmentation patterns of MSn ion m/z 193 and 175, as reported by Vieira et al. [22], and cis 5-O-feruoylquinic acid and trans 5-O-feruoylquinic acid were identified through their fragmentation patterns as reported by Hernández et al. [19]. There were only two hydroxybenzoic acids identified, dyhydroxybenzoic acid hexoside and galloyl hexoside, both of which were previously identified by Abu-Reidah et al. [20].
All of the 11 flavones identified were in B. vulgaris and V. locusta. Four flavones (luteolin-7-rutinoside, diosmetin apiosylglucoside, diosmin, and apigenin-rutinoside) were identified in V. locusta, all of which were previously reported by Hernández et al. [19], and seven (vitexin hexoside 1 and 2, vitexin pentoside, luteolin dihexoside, vitexin, vitexin hexoside derivate, and malonyl pentosylvitexin) in B. vulgaris. Vitexin, vitexin hexoside, vitexin pentoside, and malonyl pentosylvitexin were previously reported in B. vulgaris by Vissers et al. [23] and AbdEl-Ghffar et al. [24], while, luteolin dihexoside and vitexin hexoside derivatives are reported here for the first time in B. vulgaris.
There were 13 flavonols identified, 2 in B. vulgaris, 7 in B. rapa var. japonica, and 6 in L. sativa. In B. vulgaris, both of the flavonols identified (isorhamnetin dihexoside, rutinoside) are reported here for the first time in B. vulgaris, and these followed the typical fragmentation pattern MSn m/z 315 and 300, MSn+1 m/z 300, 287 for isorhamnetin. In B. rapa var. japonica, of the seven flavonols identified, only kaempferol hexoside derivative is reported for the first time, which followed the kaempferol typical fragmentation pattern MSn m/z 285 and 284. The other flavanols identified in B. rapa var. japonica were previously identified in pak choi (Brassica campestris L. ssp. chinensis var. comunis) and curly kale (Brassica oleracea L. Convar. acephala var. sabellica) by Harbaum et al. [21] and Olsen et al. [25], and here for the first time in B. rapa var. japonica. In L. sativa, all six flavonols identified were previously reported by Medic et al. [13].

3.2. Effects of the Juglone Treatments on the Crop Vegetable Yields

The control effects of juglone (1 mM, 10 μM) and the leaf extract with 10 μM juglone were not the same across these different crop vegetables, as was also seen previously in germination studies by Medic et al. [13]. The effects of the different treatments on the crop yields and root weights are shown in Figure 1 and in Supplementary Materials.
Interestingly, the highest crop yields and root weights were obtained for the 10 μM leaf juglone treatments for B. rapa var. japonica and L. sativa, and for the K2 control as the second-highest for B. vulgaris and V. locusta. This might be because the leaf extracts contain other nutrients and beneficial allelochemicals besides juglone that can stimulate plant growth and increase crop yields. In contrast to our previous seed germination study [13], where the 10 μM juglone leaf extract was not different from the control treatments, here, the 10 μM leaf juglone even showed higher yields, compared with the other treatments. Indeed, this would appear logical considering that most biostimulants are produced from plant waste [26]. However, higher concentrations of juglone in the leaf extract might have inhibitory effects also on crop yields, as observed in the germination trial by Medic et al. [13], where 1 mM juglone leaf extracts significantly inhibited seed germination and seedling growth. Therefore, further studies are needed before a conclusion can be drawn.
It is known that juglone is absorbed from the soil through the roots and, therefore, acts first on the roots of the plants. It penetrates the plasma membrane of the root cells and induces depolarisation by blocking the K+ channels, which inhibits root and, consequently, shoot, nutrient uptake, and growth [27]. This explains the lowest yields for all of these crop vegetables, as well as the lowest root weights, which were seen for 1 mM, followed by 10 μM, control juglone treatments. Overall, juglone showed allelopathic effects on the yields of all of these crop vegetables. However, the yields of B. vulgaris and L. sativa appeared to be less affected by the lower concentration of the control juglone (10 μM) than that of B. rapa var. japonica and V. locusta and would, therefore, be a better choice for cultivation in soils where juglone is still present.

3.3. Effects of the Juglone Treatments on the Crop Vegetable Quality

Looking at the effects of the juglone treatments with the same 10 μM concentration of control juglone and leaf juglone on the crop quality in terms of TAPC, it can be seen that these were not the same across the crop vegetables (Figure 2, Figure 3, Figure 4 and Figure 5), as also previously reported by Medic et al. [13] and Ercisli and Turkkal [28]. While L. sativa and V. locusta showed similar responses, the responses of B. vulgaris and B. rapa var. japonica were almost contrary. All of the data that showed significant differences are further detailed in the Supplementary Materials.
As can be seen in Figure 2A, the extraction medium control (K1; with vehicles used for the control juglone and leaf juglone treatments) affected the quality of B. vulgaris, compared with K2 (water control), with lower TAPC in the younger and semi-old leaves. There were no differences between the K1, 1 mM and 10 μM control juglone, and 10 μM leaf juglone treatments, except for TAPC in older leaves treated with 10 μM leaf juglone, which had lower TAPC than for the other treatments. Figure 2B shows that for B. vulgaris, there were no differences in the proportions of total hydroxycinnamic acid, total flavonols, and flavones, indicating that the quality of B. vulgaris was not greatly affected by the 1 mM and 10 μM control juglone and 10 μM leaf juglone treatments. In terms of quality, the younger leaves tended to have the highest TAPC and, therefore, the highest quality, while the older leaves had lower TAPC, which is usually the case for all plants [29]. The higher TAPC in the younger leaves is the result of the plant defence mechanisms, as leaves with higher TAPC are better protected against bacterial infections than older leaves [30]. The TAPC of B. vulgaris was consistent with previous measures of Vissers et al. [23]; however, most of the phenolic compounds identified, as well as the highest contents seen in the present study, were flavones, compared with the phenolic acids reported by Vissers et al. [23].
The vehicle effect (i.e., K1 vs. K2) on quality seen for B. vulgaris was not seen for B. rapa var. japonica, L. sativa, or V. locusta. As shown in Figure 3A, in B. rapa var. japonica, there were no clear trends seen for TAPC, and thus, 1 mM and 10 μM control juglone and 10 μM leaf juglone did not have any effects on the crop quality. However, if the contents of hydroxycinnamic acids and flavonols are considered, it can be seen that the 1 mM and 10 μM control juglone treatments resulted in higher hydroxycinnamic acids contents in the semi-old leaves, while the semi-old leaves treated with 10 μM leaf juglone had lower hydroxycinnamic acids content, compared with both controls (K1, K2), as can be seen in Figure 3B. In addition, the treatments with 1 mM and 10 μM control juglone also affected the flavonols content, with increased total flavonols in the older leaves, compared with the young leaves, which was not seen for the control or 10 μM leaf juglone treatments. Overall, in the semi-old leaves, 10 μM leaf juglone decreased the hydroxycinnamic acids content, while the flavonols content increased, in contrast to the 1 mM and 10 μM control juglone treatments, for which in the semi-old leaves, the hydroxycinnamic acids content increased and the flavonols content decreased. This suggests that other allelochemicals are present in J. regia that can have actions similar to those of juglone, as also previously indicated by Medic et al. [13]. The TAPC of B. vulgaris was consistent with that of Harbaum et al. [21] in Brassica campestris L. chinensis var. communis and higher than previously reported in B. rapa var. japonica by Khanam et al. [31]. Most of the phenolic compounds identified in the present study, as well as the highest contents, were for the hydroxycinnamic acids, similar to a previous report by Khanam et al. [31].
Similar to B. rapa var. japonica, in L. sativa the majority of the identified and quantified phenolic compounds represented the hydroxycinnamic acids, followed by the flavonols, which is in agreement with Abu-Reidah et al. [20] and Ribas-Agustí et al. [32]. TAPC was slightly lower than previously reported by Santos et al. [33]. Figure 4 shows that the 1 mM and 10 μM control juglone treatments affected the metabolic response of L. sativa in the same way as for B. rapa var. japonica, while the 10 μM leaf juglone treatment had no effects on the secondary metabolites. The highest TAPCs were seen for the older leaves in the 1 mM and 10 μM control juglone treatments, compared with the younger leaves, mainly due to the higher flavonols and hydroxycinnamic acids contents. Considering the relative values of the phenolic compounds (Figure 4B), it can be seen that the treatments with 1 mM and 10 μM control juglone resulted in higher proportions of hydroxycinnamic acids and lower proportions of flavonols in the younger leaves, compared with the older leaves, contrary to other treatments (K1, K2, 10 μM leaf juglone), in which the proportions of hydroxycinnamic acids were higher in the older leaves, and proportions of flavonols were higher in the younger leaves. This has been observed previously for B. vulgaris, B. rapa var. japonica, and V. locusta, and it suggests a uniform metabolomics response of these crop vegetables to produce hydroxycinnamic acids when affected by the allelochemical juglone.
As can be seen in Figure 5, both of the 1 mM and 10 μM control juglone treatments had effects on the quality of V. locusta, while there were no differences between the controls and the 10 μM leaf juglone treatments. The metabolic responses of V. locusta were similar to those of L. sativa, with the older leaves showing the highest levels of TAPC, mainly due to the increase in the hydroxycinnamic acids content in the older leaves treated with juglone. Apart from this difference in the hydroxycinnamic acids in the 1 mM and 10 μM control juglone treated plants in the old leaves, the major difference was in the contents of the other phenolic compounds, which were higher in older leaves, compared with younger leaves. The TAPC of V. locusta is in agreement with that reported by Hernández et al. [19]. Most of the phenolic compounds identified in the present study, as well as the highest contents, were hydroxycinnamic acids, followed by flavones, as previously reported by Hernández et al. [19].

4. Conclusions

As also previously reported by Medic et al. [13], we can confirm that each of these crop vegetables responds differently to the allelochemicals, and although juglone appears to be the most toxic of the allelochemicals, it might not be the only one in these leaf extracts of J. regia. Here, the treatment with the leaf extract (i.e., 10 μM leaf juglone) resulted in the highest yields and comparable qualities in terms of TAPC, compared with the other treatments. This either means that this leaf extract of J. regia also contains beneficial allelochemicals that can stimulate growth, or that the leaf extract is simply a good source of additional minerals and nutrients that stimulate growth without affecting the metabolic responses of the plants themselves. The possibility that different concentrations of J. regia leaf extracts have different biostimulatory effects on such crop yields should be further investigated.
In addition to the identification and quantification of the phenolic compounds in these crop vegetable leaves of different ages, the main objective of this study was to investigate the yields, quality, and metabolic responses of these different crop vegetables, so as to determine which of them cannot thrive in soils containing juglone or other J. regia allelochemicals. From the data obtained, it can be concluded that B. vulgaris and L. sativa are more suitable for planting in soils where walnuts were previously grown, since, although they were affected by the 1 mM control juglone, they showed fewer negative effects for the 10 μM control juglone in terms of crop yields. In terms of crop quality, the smallest effects of the different treatments were seen for B. vulgaris. Both B. rapa var. japonica and V. locusta showed lower yields even for the lower of the control juglone treatments (i.e., 10 μM), and the quality was also affected, so cultivation in juglone-containing soils should be avoided.
Apart from identifying and quantifying 60 compounds from B. vulgaris, B. rapa var. japonica, L. sativa, and V. locusta, with some reported for these crop vegetables for the first time, this study also serves as a basis for the selection of more suitable crops in the early years of planting of crops in the soils where walnuts were previously planted. The quality of the leaves of these crop vegetables at different ages and the quality and yields of these selected crop vegetables grown under the influence of allelochemicals were also investigated, to determine the influence of allelochemicals on their metabolomics and, thus, on the uptake of phenolic compounds considered to be beneficial to human health. The data obtained could be relevant for future studies on crop management in different soils and the use of allelochemicals to modify the phytochemical composition of vegetables.

Supplementary Materials

The following supporting information can be downloaded at: https://0-www-mdpi-com.brum.beds.ac.uk/article/10.3390/agronomy12020347/s1, Figure S1: Representative full scan for the HPLC–MS analysis, and identification of the phenolic compounds for Beta vulgaris L., Figure S2: Representative full scan for the HPLC–MS, and identification of the phenolic compounds for Brassica rapa L. var. japonica, Figure S3: Representative full scan for the HPLC–MS, and identification of the phenolic compounds for Lactuca sativa L., Figure S4: Representative full scan for the HPLC–MS, and identification of the phenolic compounds for Valerianella locusta Laterr., Table S1: Yields for the different crop vegetables in terms of leaf fresh weight and dry matter, and root dry weight, Table S2: Individual phenolic compounds quantified in Beta vulgaris L., Table S3: Individual compounds quantified in Brassica rapa L. var. japonica, Table S4: Individual compounds quantified in Lactuca sativa L., Table S5: Individual compounds quantified in Valerianella locusta Laterr.

Author Contributions

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

Funding

This study is a part of programme P4-0013-0481, which is funded by the Slovenian Research Agency (ARRS) and the infrastructural centre IC RRC-AG (IO-0022-0481-001).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Part of the data presented in this study are available in Supplementary Materials here. The remaining data presented in this study are available on request from the corresponding author. The remaining data are not publicly available due to privacy.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ahmed, S.; Shanks, C.B. Quality of Vegetables Based on Total Phenolic Concentration Is Lower in More Rural Consumer Food Environments in a Rural American State. Int. J. Environ. Res. Public Health 2017, 14, 924. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Liu, R.H. Health-Promoting Components of Fruits and Vegetables in the Diet. Adv. Nutr. Int. Rev. J. 2013, 4, 384S–392S. [Google Scholar] [CrossRef] [PubMed]
  3. Medic, A.; Jakopic, J.; Solar, A.; Hudina, M.; Veberic, R. Walnut (J. regia) Agro-Residues as a Rich Source of Phenolic Compounds. Biology 2021, 10, 535. [Google Scholar] [CrossRef] [PubMed]
  4. Wolfe, K.L.; Kang, X.; He, X.; Dong, M.; Zhang, Q.; Liu, R.H. Cellular Antioxidant Activity of Common Fruits. J. Agric. Food Chem. 2008, 56, 8418–8426. [Google Scholar] [CrossRef] [PubMed]
  5. Di Noia, J. Defining Powerhouse Fruits and Vegetables: A Nutrient Density Approach. Prev. Chronic Dis. 2014, 11, E95. [Google Scholar] [CrossRef] [Green Version]
  6. Medic, A.; Zamljen, T.; Hudina, M.; Veberic, R. Identification and Quantification of Naphthoquinones and Other Phenolic Compounds in Leaves, Petioles, Bark, Roots, and Buds of Juglans regia L., Using HPLC–MS/MS. Horticulturae 2021, 7, 326. [Google Scholar] [CrossRef]
  7. Ahmed, S.; Stepp, J.R. Beyond yields: Climate change effects on specialty crop quality and agroecological management. Elem. Sci. Anthr. 2016, 4, 92. [Google Scholar] [CrossRef] [Green Version]
  8. Medic, A.; Solar, A.; Hudina, M.; Veberic, R. Phenolic Response to Walnut Anthracnose (Ophiognomonia leptostyla) Infection in Different Parts of Juglans regia Husks, Using HPLC–MS/MS. Agriculture 2021, 11, 659. [Google Scholar] [CrossRef]
  9. Li, Z.-H.; Wang, Q.; Ruan, X.; Pan, C.-D.; Jiang, D.-A. Phenolics and Plant Allelopathy. Molecules 2010, 15, 8933–8952. [Google Scholar] [CrossRef] [Green Version]
  10. Wink, M. Introduction: Biochemistry, Role and Biotechnology of Secondary Metabolites. Annu. Plant Rev. Online 2018, 3, 1–17. [Google Scholar] [CrossRef]
  11. Zubay, P.; Kunzelmann, J.; Ittzés, A.; Zámboriné, É.N.; Szabó, K. Allelopathic effects of leachates of Juglans regia L., Populus tremula L. and juglone on germination of temperate zone cultivated medicinal and aromatic plants. Agrofor. Syst. 2021, 95, 431–442. [Google Scholar] [CrossRef]
  12. Islam, A.K.M.M.; Widhalm, J.R. Agricultural Uses of Juglone: Opportunities and Challenges. Agronomy 2020, 10, 1500. [Google Scholar] [CrossRef]
  13. Medic, A.; Zamljen, T.; Slatnar, A.; Hudina, M.; Veberic, R. Is Juglone the Only Naphthoquinone in Juglans regia L. with Allelopathic Effects? Agriculture 2021, 11, 784. [Google Scholar] [CrossRef]
  14. Aliskan, I.K.; Terzi, I. Allelopathic effects of walnut leaf extracts and juglone on seed germination and seedling growth. J. Hortic. Sci. Biotechnol. 2001, 76, 436–440. [Google Scholar] [CrossRef]
  15. de Scisciolo, B.; Leopold, D.J.; Walton, D.C. Seasonal patterns of juglone in soil beneath Juglans nigra (black walnut) and influence of J. nigra on understory vegetation. J. Chem. Ecol. 1990, 16, 1111–1130. [Google Scholar] [CrossRef] [PubMed]
  16. Maršić, N.K.; Mikulič-Petkovšek, M.; Hudina, M.; Veberič, R.; Slatnar, A. Leafy Asian vegetables cultivated on a floating hydroponic system and a substrate culture, during the autumn period in greenhouse. Acta Hortic. 2021, 1320, 413–420. [Google Scholar] [CrossRef]
  17. Medic, A.; Jakopic, J.; Hudina, M.; Solar, A.; Veberic, R. Identification and quantification of the major phenolic constituents in Juglans regia L. peeled kernels and pellicles, using HPLC–MS/MS. Food Chem. 2021, 352, 129404. [Google Scholar] [CrossRef]
  18. Liu, P.; Li, L.; Song, L.; Sun, X.; Yan, S.; Huang, W. Characterisation of phenolics in fruit septum of Juglans regia Linn. by ultra performance liquid chromatography coupled with Orbitrap mass spectrometer. Food Chem. 2019, 286, 669–677. [Google Scholar] [CrossRef]
  19. Hernández, V.; Botella, M.; Hellín, P.; Cava, J.; Fenoll, J.; Mestre, T.; Martínez, V.; Flores, P. Phenolic and Carotenoid Profile of Lamb’s Lettuce and Improvement of the Bioactive Content by Preharvest Conditions. Foods 2021, 10, 188. [Google Scholar] [CrossRef]
  20. Abu-Reidah, I.M.; Contreras, M.D.M.; Arraez-Roman, D.; Carretero, A.S.; Fernández-Gutiérrez, A. Reversed-phase ultra-high-performance liquid chromatography coupled to electrospray ionization-quadrupole-time-of-flight mass spectrometry as a powerful tool for metabolic profiling of vegetables: Lactuca sativa as an example of its application. J. Chromatogr. A 2013, 1313, 212–227. [Google Scholar] [CrossRef]
  21. Harbaum, B.; Hubbermann, E.M.; Wolff, C.; Herges, R.; Zhu, Z.; Schwarz, K. Identification of Flavonoids and Hydroxycinnamic Acids in Pak Choi Varieties (Brassica campestris L. ssp. chinensis var. communis) by HPLC–ESI-MSnand NMR and Their Quantification by HPLC–DAD. J. Agric. Food Chem. 2007, 55, 8251–8260. [Google Scholar] [CrossRef] [PubMed]
  22. Vieira, V.; Pereira, C.; Pires, T.C.; Calhelha, R.C.; Alves, M.J.; Ferreira, O.; Barros, L.; Ferreira, I.C. Phenolic profile, antioxidant and antibacterial properties of Juglans regia L. (walnut) leaves from the Northeast of Portugal. Ind. Crop. Prod. 2019, 134, 347–355. [Google Scholar] [CrossRef]
  23. Vissers, A.; Kiskini, A.; Hilgers, R.; Marinea, M.; Wierenga, P.A.; Gruppen, H.; Vincken, J.-P. Enzymatic Browning in Sugar Beet Leaves (Beta vulgaris L.): Influence of Caffeic Acid Derivatives, Oxidative Coupling, and Coupled Oxidation. J. Agric. Food Chem. 2017, 65, 4911–4920. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. El-Ghffar, E.A.A.; Hegazi, N.M.; Saad, H.H.; Soliman, M.M.; El-Raey, M.A.; Shehata, S.M.; Barakat, A.; Yasri, A.; Sobeh, M. HPLC–ESI–MS/MS analysis of beet (Beta vulgaris) leaves and its beneficial properties in type 1 diabetic rats. Biomed. Pharmacother. 2019, 120, 109541. [Google Scholar] [CrossRef] [PubMed]
  25. Olsen, H.; Aaby, K.; Borge, G.I.A. Characterization and Quantification of Flavonoids and Hydroxycinnamic Acids in Curly Kale (Brassica oleracea L. Convar. acephala Var. sabellica) by HPLC-DAD-ESI-MSn. J. Agric. Food Chem. 2009, 57, 2816–2825. [Google Scholar] [CrossRef] [PubMed]
  26. Colla, G.; Rouphael, Y. Biostimulants in horticulture. Sci. Hortic. 2015, 196, 1–2. [Google Scholar] [CrossRef]
  27. Duroux, L.; Delmotte, F.M.; Lancelin, J.-M.; Kéravis, G.; Jay-Allemand, C. Insight into naphthoquinone metabolism: β-glucosidase-catalysed hydrolysis of hydrojuglone β-d-glucopyranoside. Biochem. J. 1998, 333, 275–283. [Google Scholar] [CrossRef]
  28. Ercisli, S.; Turkkal, C. Allelopathic effects of juglone and walnut leaf extracts on growth, fruit yield and plant tissue composition in strawberry cvs. ‘Camarosa’ and ‘Sweet Charlie’. J. Hortic. Sci. Biotechnol. 2005, 80, 39–42. [Google Scholar] [CrossRef]
  29. Liu, Z.; Bruins, M.E.; de Bruijn, W.J.; Vincken, J.-P. A comparison of the phenolic composition of old and young tea leaves reveals a decrease in flavanols and phenolic acids and an increase in flavonols upon tea leaf maturation. J. Food Compos. Anal. 2020, 86, 103385. [Google Scholar] [CrossRef]
  30. Dadáková, K.; Heinrichová, T.; Lochman, J.; Kašparovský, T. Production of Defense Phenolics in Tomato Leaves of Different Age. Molecules 2020, 25, 4952. [Google Scholar] [CrossRef]
  31. Khanam, U.K.S.; Oba, S.; Yanase, E.; Murakami, Y. Phenolic acids, flavonoids and total antioxidant capacity of selected leafy vegetables. J. Funct. Foods 2012, 4, 979–987. [Google Scholar] [CrossRef]
  32. Ribas-Agustí, A.; Gratacós-Cubarsí, M.; Sárraga, C.; García-Regueiro, J.-A.; Castellari, M. Analysis of Eleven Phenolic Compounds Including Novel p-Coumaroyl Derivatives in Lettuce (Lactuca sativa L.) by Ultra-high-performance Liquid Chromatography with Photodiode Array and Mass Spectrometry Detection. Phytochem. Anal. 2011, 22, 555–563. [Google Scholar] [CrossRef] [PubMed]
  33. Santos, J.; Oliveira, M.; Ibáñez, E.; Herrero, M. Phenolic profile evolution of different ready-to-eat baby-leaf vegetables during storage. J. Chromatogr. A 2014, 1327, 118–131. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Heat map showing leaf fresh weights and root dry weights, from highest (green) to lowest (red) values between treatments (columns). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control.
Figure 1. Heat map showing leaf fresh weights and root dry weights, from highest (green) to lowest (red) values between treatments (columns). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control.
Agronomy 12 00347 g001
Figure 2. Contents of the total phenolic groups identified in B. vulgaris expressed relative to fresh weight (A) and as proportions of the total phenolic groups identified (B). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control. Young leaves, undeveloped leaves; semi-old leaves, remaining fully developed leaves; old leaves, four outer fully developed leaves.
Figure 2. Contents of the total phenolic groups identified in B. vulgaris expressed relative to fresh weight (A) and as proportions of the total phenolic groups identified (B). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control. Young leaves, undeveloped leaves; semi-old leaves, remaining fully developed leaves; old leaves, four outer fully developed leaves.
Agronomy 12 00347 g002
Figure 3. Contents of the total phenolic groups identified in B. rapa var. japonica expressed relative to fresh weight (A) and as proportions of the total phenolic groups identified (B). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control. Young leaves, undeveloped leaves; semi-old leaves, remaining fully developed leaves; old leaves, four outer fully developed leaves.
Figure 3. Contents of the total phenolic groups identified in B. rapa var. japonica expressed relative to fresh weight (A) and as proportions of the total phenolic groups identified (B). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control. Young leaves, undeveloped leaves; semi-old leaves, remaining fully developed leaves; old leaves, four outer fully developed leaves.
Agronomy 12 00347 g003
Figure 4. Contents of the total phenolic groups identified in L. sativa expressed relative to fresh weight (A) and as proportions of the total phenolic groups identified (B). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control. Young leaves, undeveloped leaves; semi-old leaves, remaining fully developed leaves; old leaves, four outer fully developed leaves.
Figure 4. Contents of the total phenolic groups identified in L. sativa expressed relative to fresh weight (A) and as proportions of the total phenolic groups identified (B). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control. Young leaves, undeveloped leaves; semi-old leaves, remaining fully developed leaves; old leaves, four outer fully developed leaves.
Agronomy 12 00347 g004
Figure 5. Contents of the total phenolic groups identified in V. locusta expressed relative to fresh weight (A) and as proportions of the total phenolic groups identified (B). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control. Young leaves, undeveloped leaves; semi-old leaves, remaining fully developed leaves; old leaves, four outer fully developed leaves.
Figure 5. Contents of the total phenolic groups identified in V. locusta expressed relative to fresh weight (A) and as proportions of the total phenolic groups identified (B). K1: extraction medium control (0.17% DMSO, 0.17% ethanol in H2O); K2: water control. Young leaves, undeveloped leaves; semi-old leaves, remaining fully developed leaves; old leaves, four outer fully developed leaves.
Agronomy 12 00347 g005
Table 1. Tentative identification of the 60 phenolic compounds from B. vulgaris, B. rapa var. japonica, L. sativa, and V. locusta, and the standards used.
Table 1. Tentative identification of the 60 phenolic compounds from B. vulgaris, B. rapa var. japonica, L. sativa, and V. locusta, and the standards used.
SourceCompoundRt (min)[M-H] (m/z)MS2 (m/z)MS3 (m/z)Expressed as
Beta vulgaris L.p-Coumaroylcaffeic acid11.09337119 (100), 179 (42), 163 (12) p-Coumaric acid
p-Coumaric acid hexoside12.17325163 (100), 145 (83), 119 (8), 235 (8) p-Coumaric acid
Ferulic acid hexoside13.12355193 (100), 217 (54), 175 (29) Ferulic acid
Vitexin hexoside14.85593311 (100), 341 (25)283 (100), 191 (3)Apigenin-7-glucoside
Ferulic acid15.13193149 (100), 178 (72), 134 (48) Ferulic acid
Ferulic acid derivative 117.48443267 (100), 193 (9)249 (100), 113 (72), 175 (14)Ferulic acid
Ferulic acid derivative 217.79639443 (100)267 (100), 193 (10)Ferulic acid
Vitexin hexoside18.23577413 (100)293 (100)Apigenin-7-glucoside
Luteolin dihexoside18.89609285 (100), 257 (4)257 (100), 241 (45), 229 (37), 151 (32) 213 (26) Luteolin-7-glucoside
Vitexin pentoside18.89563413 (100)293 (100)Apigenin-7-glucoside
Vitexin (apigenin-C-hexoside isomer)19.47431311 (100)283 (100), 191 (3)Apigenin-7-glucoside
Isorhamnetin dihexoside19.93639315 (100), 300 (17)300 (100), 287 (4)Isorhamnetin-3-glucoside
Vitexin hexoside derivative20.19651607 (100)457 (100), 293 (3)Apigenin-7-glucoside
Isorhamnetin rutinoside20.68609315 (100), 300 (13)300 (100), 287 (5)Isorhamnetin-3-glucoside
Malonyl pentosylvitexin21.59649605 (100)455 (100), 293 (5)Apigenin-7-glucoside
Brassica rapa L. var. japonicaNeochlorogenic acid (3-caffeoylquinic acid)9.27353191 (100), 179 (46), 135 (7) Neochlorogenic acid
Kaempferol-3-O-diglucoside-7-O-glucoside10.34771609 (100)285 (100), 284 (100), 429 (98), 257 (10), 179 (3)Kaempferol-3-glucoside
Gluconapin11.57372259 (100), 275 (29), 194 (20), 130 (7)139 (100), 97 (39), 199 (13), 241 (7)Gluconapin
Kaempferol-3-O-caffeoyldiglucoside-7-O-glucoside12.19933771 (100)609 (100)Kaempferol-3-glucoside
Kaempferol-3-O-sinapoyldiglucoside-7-O-glucoside13.42977815 (100)609 (100)Kaempferol-3-glucoside
Sinapoyl glycoside13.42385223 (100), 247 (48), 205 (40)164 (100), 208 (44), 179 (35)Sinapic acid
Kaempferol diglucoside13.57609447 (100), 285 (13), 284 (2)284 (100), 285 (46), 151 (5)Kaempferol-3-glucoside
Kaempferol-3-O-feruoylglucoside-7-O-glucoside14.07947785 (100)623 (100), 609 (92), 591 (43)Kaempferol-3-glucoside
Isorhamnetin-3-O-glucoside-7-O-glucoside14.07639477 (100), 315 (9), 300 (1) Isorhamnetin-3-glucoside
Caffeoyl malate17.50295179 (100), 133 (1) Caffeic acid
Hydroxyferuoyl malate17.89325209 (100), 133 (23), 165 (5) Ferulic acid
Kaempferol hexoside derivative19.92567447 (100)285 (100), 284 (31)Kaempferol-3-glucoside
Coumaroyl malate21.41279163 (100), 133 (19) p-Coumaric acid
Sinapoyl malate22.06339223 (100)164 (100), 208 (79), 179 (53)Sinapic acid
Feruloyl malate22.24309193 (100), 133 (7) Ferulic acid
Lactuca sativa L.Dihydroxybenzoic acid hexoside8.69315153 (100), 108 (19) Gallic acid
Esculetin glucoside9.87339177 (100) Gallic acid
Chlorogenic acid (5-caffeoylquinic acid)12.47353191 (100), 179 (4), 135 (1) Chlorogenic acid
Galloyl hexoside13.13331313 (100), 168 (61), 125 (19), 169 (24) Gallic acid
Cryptochlorogenic acid (4-caffeoylquinic acid)14.21353191 (100), 179 (3), 135 (1) Cryptochlorogenic acid
Sinapoyl hexoside derivative15.38431385 (100)223 (100), 179 (41), 208 (27)Sinapic acid
cis 5-O-p-Coumaroylquinic acid15.91337191 (100), 163 (8) p-Coumaric acid
trans 5-O-p-Coumaroylquinic acid17.24337191 (100), 163 (7) p-Coumaric acid
Caffeoyl malate17.60295179 (100), 133 (53) Caffeic acid
Quercetin-3-O-galactoside19.34463301 (100), 300 (3) Quercetin-3-O-galactoside
Quercetin-3-O-glucoside20.68463301 (100), 300 (19) Quercetin-3-O-glucoside
Kaempferol-3-O-glucuronide21.42463285 (100), 284 (41) Kaempferol-3-glucoside
Quercetin-3-O-glucuronide21.96477301 (100), 300 (4) Quercetin-3-O-glucoside
Quercetin 3-(6″-malonylglucoside)22.55549505 (100)301 (100), 300 (57)Quercetin-3-O-glucoside
Quercetin-3-(6″-acetylglucoside)23.70505301 (100), 300 (64) Quercetin-3-O-glucoside
Caffeoyltartaric acid hexoside 126.63473293 (100), 311 (99) Caffeic acid
Caffeoyltartaric acid hexoside 229.21473311 (100), 293 (87) Caffeic acid
Valerianella locusta Laterr.4-Hydroxyphenylaoyl glucoside derivative7.16359313 (100)151 (100), 269 (2), 185 (1)Gallic acid
Chlorogenic acid (5-caffeoylquinic acid)12.37353191 (100), 179 (4), 135 (1) Chlorogenic acid
Cryptochlorogenic acid (4-caffeoylquinic acid)14.10353191 (100), 179 (3), 135 (1) Cryptochlorogenic acid
cis 5-O-p-Coumaroylquinic acid15.89337191 (100), 163 (8) p-Coumaric acid
cis 5-O-Feruoylquinic acid16.88367191 (100), 173 (3) Ferulic acid
trans 5-O-p-Coumaroylquinic acid17.22337191 (100), 163 (7) p-Coumaric acid
trans 5-O-Feruoylquinic acid18.02367191 (100), 173 (2) Ferulic acid
Luteolin-7-rutinoside19.62593285 (100)285 (100), 241 (24), 217 (14), 199 (16), 175 (17), 151 (6)Luteolin-7-glucoside
Diosmetin apiosylglucoside21.74593299 (100), 284 (17)284 (100)Luteolin-7-glucoside
Diosmin (diosmetin-7-O-rutinoside)22.07607299 (100), 284 (24) Luteolin-7-glucoside
Dicaffeoylquinic acid22.58515353 (100), 179 (2) Caffeic acid
Apigenin-rutinoside24.75577531 (100), 269 (98) Apigenin-7-glucoside
Caffeic acid hexoside derivative25.48637535 (100), 341 (23)161 (100), 179 (57), 341 (57)Caffeic acid
Rt, retention time; [M-H], pseudo-molecular ion identified in negative ion mode; (), relative abundance of fragment ions.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Medic, A.; Zamljen, T.; Grohar, M.C.; Slatnar, A.; Hudina, M.; Veberic, R. Using HPLC–MS/MS to Assess the Quality of Beet, Mizuna, Lettuce and Corn Salad after Juglone and Walnut Leaf Extract Treatments. Agronomy 2022, 12, 347. https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020347

AMA Style

Medic A, Zamljen T, Grohar MC, Slatnar A, Hudina M, Veberic R. Using HPLC–MS/MS to Assess the Quality of Beet, Mizuna, Lettuce and Corn Salad after Juglone and Walnut Leaf Extract Treatments. Agronomy. 2022; 12(2):347. https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020347

Chicago/Turabian Style

Medic, Aljaz, Tilen Zamljen, Mariana Cecilia Grohar, Ana Slatnar, Metka Hudina, and Robert Veberic. 2022. "Using HPLC–MS/MS to Assess the Quality of Beet, Mizuna, Lettuce and Corn Salad after Juglone and Walnut Leaf Extract Treatments" Agronomy 12, no. 2: 347. https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020347

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop