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Article

Depicting the Physiological, Biochemical and Metabolic Responses to the Removal of Adventitious Roots and Their Functions in Cucumis melo Under Waterlogging Stress

by
Huanxin Zhang
*,
Chengpu Yan
,
Qian Chen
and
Guoquan Li
*
Institute of Horticulture, Jiangxi Academy of Agricultural Sciences, Nanchang 330200, China
*
Authors to whom correspondence should be addressed.
Agronomy 2025, 15(10), 2281; https://doi.org/10.3390/agronomy15102281
Submission received: 20 August 2025 / Revised: 24 September 2025 / Accepted: 25 September 2025 / Published: 26 September 2025
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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Abstract

Waterlogging poses a grave abiotic stress that hampers crop productivity and survival due to reduced oxygen availability in the impacted tissues. To adapt to this hypoxic environment, the hypocotyls of melon (Cucumis melo L.) seedlings can produce a profusion of adventitious roots when exposed to waterlogging stress. However, research on the significance of these adventitious roots under waterlogging stress has been limited. The present study aimed to elucidate the critical role of adventitious roots by investigating the physiological, biochemical, and metabolic changes that occur following their removal during waterlogging stress. The removal of adventitious roots compromised the normal growth of melon seedlings, resulting in phenotypic abnormalities such as chlorotic and withered leaves. Our results indicated that the removal of adventitious roots led to significant reductions in total chlorophyll levels by 62.89% and 43.60% compared to the normal control condition and waterlogging stress alone, respectively. Additionally, in the adventitious root removal treatment, higher malondialdehyde (MDA) content, O2•− production rate, monodehydroascorbate reductase (MDHAR) activity, alcohol dehydrogenase (ADH) activity, the AsA/DHA ratio, proline content, jasmonic acid (JA) content, and 1-aminocyclopropane-1-carboxylic acid (ACC) content were observed. Specifically, JA levels were significantly enhanced by 180.54% and 52.05%, and ACC levels were significantly increased by 519.23% and 125.16% compared to the control and waterlogging stress conditions, respectively. Through untargeted metabolomic analysis, a total of 447 differentially accumulated metabolites (DAMs) were identified. Notably, jasmonic acid and brassinolide, which are involved in plant hormone signal transduction, along with cyanidin 3-(2G-xylosylrutinoside) classified as flavonoids, (2S,3′S)-α-amino-2-carboxy-5-oxo-1-pyrrolidinebutanoic acid categorized as proline and derivatives, and ligstroside-aglycone and foeniculoside VII annotated as terpenoids, exhibited key roles in the waterlogging response. This research enhances our understanding of the mechanisms underlying the removal of adventitious roots during waterlogging stress, as well as the associated physiological, biochemical, and metabolic changes. These findings provide valuable insights into the crucial role of adventitious roots in melon seedlings subjected to waterlogging stress and may inform strategies for enhancing waterlogging tolerance in breeding practices.

1. Introduction

Global climate change has led to the emergence of waterlogging as a significant abiotic stressor affecting crops worldwide, with detrimental impacts on their productivity and survival [1,2]. The pronounced reduction in oxygen availability within waterlogged organs creates hypoxic or anoxic conditions, which disrupt normal physiological and biochemical processes in crops. These adverse disruptions encompass a transition from aerobic to anaerobic respiration, decreased stomatal aperture, impaired gas exchange, reduced photosynthesis, limited water and nutrient uptake, and the accumulation of toxic compounds [1,3]. Collectively, these challenges severely impede the normal growth and development of crops, resulting in a marked decline in yield.
When exposed to waterlogging stress, crops exhibit a variety of morphological, physiological, and biochemical adaptations to cope with excessive water and oxygen deficiency. Research has shown that certain species have evolved specific morphological adaptations, including shoot elongation, leaf epinasty, aerenchyma formation, and the development of adventitious roots [4]. A critical adaptive response to waterlogging in various crops, such as melon [4], cucumber [5], tomato [6], and tamarack [7], is the formation of adventitious roots. Adventitious rooting is complex and is precisely regulated by both internal and external factors [8]. It is widely accepted that the development of adventitious roots undergoes induction stage, initiation stage and expression stage [9]. Adventitious roots contain advanced aerenchyma, which allows them to directly obtain oxygen from the air, thus facilitating adaptation to hypoxic environments caused by waterlogging [10,11]. Furthermore, it has been reported that overexpressing CsPrx73 can enhance the formation of adventitious roots in transgenic cucumber plants under waterlogging conditions, thereby improving their waterlogging tolerance [5].
To mitigate peroxidative damage caused by imbalances in reactive oxygen species (ROS), crops have evolved mechanisms to activate their antioxidant defense systems. This system includes a variety of antioxidative enzymes, such as catalase (CAT), superoxide dismutase (SOD), peroxidase (POD), glutathione reductase (GR), ascorbate peroxidase (APX), dehydroascorbate reductase (DHAR), and monodehydroascorbate reductase (MDHAR), alongside non-enzymatic antioxidants, including glutathione (GSH), ascorbic acid (AsA), and flavonoids [12,13]. Furthermore, changes in the synthesis and transport of phytohormones play a crucial role in mediating responses to waterlogging stress. Previous studies have identified jasmonic acid (JA), salicylic acid (SA), gibberellin (GA), abscisic acid (ABA), ethylene, auxin, and melatonin as essential endogenous signals that promote crop survival under waterlogging conditions [1,14,15,16].
Melon (Cucumis melo L.) is an economically important member of the Cucurbitaceae family, celebrated for its appealing flavors and cultivated worldwide as a fleshy fruit for fresh consumption. However, waterlogging stress can significantly reduce both yield and fruit quality, presenting a considerable challenge to melon production [3]. Under waterlogging conditions, melon seedlings exhibit the capacity to develop adventitious roots on their hypocotyls, which can promote oxygen diffusion and enable the plants to withstand saturated environments [4]. Despite this adaptation, there has been limited research on the importance of these adventitious roots under waterlogging stress. We hypothesized that the removal of adventitious roots would result in severe negative effects on melon seedlings exposed to waterlogging stress. The mechanisms involved in the removal of adventitious roots during waterlogging stress require further elucidation. In this study, we investigated the effects of adventitious root removal on the physiological, biochemical, and metabolic responses of melon seedlings subjected to waterlogging stress. Our findings will provide valuable insights into strategies for enhancing waterlogging tolerance in melon.

2. Materials and Methods

2.1. Plant Material and Stress Treatment

The melon line ‘L20’, which exhibits good capacity of adventitious rooting under waterlogging stress, was cultivated by Jiangxi Academy of Agricultural Sciences and served as the experimental material. The seeds of ‘L20’ were soaked in distilled water for a duration of 6 h before being sown in plastic pots with a diameter of 7 cm. These pots were filled with a mixture of peat, vermiculite, and perlite (3:1:1, v/v/v). The pots were placed in a well-ventilated greenhouse that provided natural temperature and lighting, maintaining a day/night temperature regime of 28 °C/20 °C for a 12 h/12 h cycle, with relative humidity level ranging from 70% to 80%.
For the waterlogging stress treatment, healthy and uniform seedlings, each possessing four true leaves, were carefully selected. The pots containing these seedlings were then submerged in plastic containers filled with tap water, ensuring that the water level reached the top of the hypocotyls. The flooding depth was strictly regulated to remain constant throughout the experiment. For the adventitious root removal treatment, once the primordia of the adventitious roots became visible (approximately 5 mm in length), they were promptly excised using a razor blade. The waterlogging stress condition was sustained for seven consecutive days, during which poor phenotypes were observed in the adventitious root removal treatment. The control group of seedlings, which were not subjected to waterlogging, were placed in similar plastic containers and kept adequately watered. For metabolic and physiological analysis, primary roots were collected after seven days of exposure to stress treatments, with primary root samples from the control plants collected concurrently. Samples from the control group were designated as CK, while those exposed solely to waterlogging stress were labeled WL, and samples from the adventitious root removal treatment were designated as R-AR. There were four biological replicates for metabolomics and three replicates for physiological analysis, with 20 seedlings utilized for each replicate. Immediately after collection, the samples were placed in liquid nitrogen and subsequently stored at −80 °C until further analyses.

2.2. Detection of Chlorophyll, Proline, Flavonoids and ROS Contents

The contents of chlorophyll, proline, flavonoids, malondialdehyde (MDA), H2O2, and O2•− production rate were assayed according to the previous methods [17,18,19,20,21,22], employing a plant chlorophyll content detection kit, proline assay kit, flavonoids assay kit, MDA assay kit, H2O2 assay kit and O2•− assay kit (Solarbio, Beijing, China), respectively. For chlorophyll content determination, approximately 0.1 g of leaf samples were ground in liquid nitrogen and extracted in the dark for 3 h using an extraction buffer. After centrifugation at 10,000× g for 10 min, the supernatants were analyzed with a microplate reader (BioTek, Winooski, VT, USA) at absorption wavelengths of 645 and 663 nm. To quantify proline content, approximately 0.1 g of root samples were ground in liquid nitrogen, mixed with the extraction solution, and incubated in a boiling water bath for 10 min before centrifugation at 10,000× g for 10 min at room temperature. The supernatant was then treated with reagents according to the kit instructions and subsequently analyzed using a microplate reader (BioTek, Winooski, VT, USA) at an absorption wavelength of 520 nm. Following the flavonoids assay kit instructions, flavonoids were extracted from the root samples of melon, and the absorbance was measured at a wavelength of 470 nm. For MDA measurement, approximately 0.1 g of root samples were ground in liquid nitrogen and extracted with an extraction buffer. After centrifugation at 8000× g for 10 min at 4 °C, the supernatant was analyzed for MDA content using a microplate reader (BioTek, Winooski, VT, USA) at absorption wavelengths of 532 and 600 nm. The determination of H2O2 content was carried out by observing the formation of a yellow titanium peroxide complex, resulting from the reaction between H2O2 and titanium sulfate, and measured based on its absorption at 415 nm. According to the kit’s instructions, the production rate of O2•− was indicated by the absorbance detected at 530 nm.

2.3. Detection of Enzyme Activity

The enzyme activities of POD, SOD, CAT, APX, MDHAR, succinate dehydrogenase (SDH), alcohol dehydrogenase (ADH) and pyruvate decarboxylase (PDC) were measured using corresponding commercial detection kits (Solarbio, Beijing, China). Following the manufacturers’ instructions, approximately 0.1 g of root samples from each treatment were pulverized in liquid nitrogen and immediately homogenized in the extraction solutions. The activity of POD was assessed by measuring the increase in absorbance at 470 nm due to the oxidation of guaiacol [23]. SOD activity was determined by evaluating its inhibition of superoxide radicals at 450 nm [24]. CAT activity was evaluated by monitoring the breakdown of H2O2 at 240 nm over a duration of 1 min [25]. APX catalyzes the oxidation of AsA by H2O2, and its activity was calculated by measuring the oxidation rate of AsA at 290 nm [26]. MDHAR activity was determined by quantifying the rate of absorbance decline at 340 nm [22]. SDH activity was represented by changes in absorbance at 600 nm [27]. The activities of ADH and PDC were monitored by detecting the oxidation of NADH, reflected by a decrease in absorbance at 340 nm [21,28].

2.4. Detection of Non-Enzymatic Antioxidants

The contents of AsA, dehydroascorbic acid (DHA), GSH and oxidized glutathione (GSSG) were quantified using the respective kits (Solarbio, Beijing, China), as demonstrated in previous studies [29,30]. Following the manufacturers’ protocols, approximately 0.1 g of root samples from each treatment were first ground into powder in liquid nitrogen and then immediately homogenized in the extraction solutions. Centrifugation of the homogenates was performed according to the established guidelines. The AsA content was determined by measuring the oxidation rate of AsA at a wavelength of 265 nm. The DHA content was evaluated by measuring the generation rate of AsA at 265 nm. The GSH content was determined by observing the formation of a yellow complex resulting from the reaction between GSH and 5,5′-dithiobis-2-nitrobenoic acid (DTNB), and measured at an absorption wavelength of 412 nm. To determine the GSSG content, it was initially reduced to GSH, and finally, the absorption at 412 nm was measured.

2.5. Detection of Hormones Contents

Root samples from each treatment were crushed in liquid nitrogen and subsequently analyzed for levels of endogenous hormones using high-performance liquid chromatography (HPLC). The contents of endogenous jasmonic acid (JA), 1-aminocyclopropane-1-carboxylic acid (ACC, ethylene precursor), and brassinolide (BR) were measured according to previously established methods [4,31,32]. The content of abscisic acid (ABA) was determined following a previously described method [33], with certain modifications. Briefly, approximately 0.1 g of frozen powder was extracted using 1.5 mL of pre-chilled 80% methanol (v/v) for 24 h at 4 °C. After centrifugation at 8000× g for 10 min, the residue was extracted with 0.5 mL of 80% methanol (v/v) for 2 h. The supernatants were pooled after centrifugation, and subsequently evaporated at 40 °C to remove the organic phase. The solution was extracted and decolorized with three additions of petroleum ether, and the pH was adjusted to 2–3 using a citric acid solution. A volume of 2 mL of ethyl acetate was added for two extractions of the solution, and the upper organic phase was transferred to a new EP tube and dried under a nitrogen stream. The dried samples were re-dissolved in 0.2 mL of methanol and filtered through a 0.22-µm nylon filter. HPLC quantification was performed using an Agilent 1100 system equipped with a UV detector (Agilent, Waldbronn, Germany). The detection wavelength was set at 254 nm, with ABA exhibiting a retention time of 20.289 min. A standard curve was constructed using the known concentrations of standard and their corresponding HPLC elution peak areas, and the ABA content was calculated based on this standard curve.

2.6. Untargeted Metabolomic Analysis

For untargeted metabolomic analysis, 100 mg root samples from each treatment were placed into a 2 mL centrifuge tube, along with a 6 mm diameter grinding bead. Metabolite extraction was performed using 400 μL of an extraction solution (methanol: water = 4:1 (v:v), which contained four internal standards. The samples were ground using the Wonbio-96c frozen tissue grinder (Wanbo, Shanghai, China) for 6 min at −10 °C and 50 Hz. Following low-temperature ultrasonic extraction and centrifugation, the supernatant was transferred into the injection vial for LC-MS/MS analysis. As part of the operations for system conditioning and quality assurance, a pooled quality control (QC) sample was prepared by combining equal volumes of every sample, and the QC samples were disposed and tested using the exact same protocol as the analytical samples [34,35]. All samples were analyzed using the SCIEX UPLC-Triple TOF 6600 system equipped with an ACQUITY UPLC BEH C18 column (Waters, Redwood, CA, USA) at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). Mass spectrometry signal acquisition was conducted in both positive and negative modes.
The raw LC/MS data were pretreated using Progenesis QI software (Waters Corporation, Milford, CT, USA). Internal standard peaks and all known false positive peaks, which encompass noise, column bleed, and derivatized reagent peaks, were excluded during the process. The data matrix obtained from database searching was uploaded to the Majorbio cloud platform (https://cloud.majorbio.com, accessed on 28 March 2025) for analysis. At least 80% of the detected metabolic features in each sample set were preserved. Following filtration, the minimum value within the data matrix was used to fill in the missing value, and each metabolic signature was normalized to its sum. To mitigate errors arising from sample preparation and instrument instability, the response intensities of the mass spectrometry peaks were normalized via the sum normalization approach, yielding a normalized data matrix. Concurrently, variables from QC samples with a relative standard deviation (RSD) > 30% were removed and log10 transformed to generate the final data matrix for subsequent analysis. Variance analysis was performed on the preprocessed matrix file. Principal component analysis (PCA) and orthogonal least partial squares discriminant analysis (OPLS-DA) were performed using the R package “ropls” (Version 1.6.2), with 7-cycle interactive validation employed to assess model stability. Based on the OPLS-DA model and Student’s t test, the metabolites with variable importance in the projection (VIP) > 1 and p < 0.05 were designated as differentially accumulated metabolites (DAMs). The DAMs were mapped to their biochemical pathways based on the KEGG database (http://www.genome.jp/kegg/, accessed on 28 March 2025). The enrichment analysis was conducted using the Python package “scipy.stats” (Version 1.0.0) (https://docs.scipy.org/doc/scipy/, accessed on 28 March 2025).

2.7. Statistical Analysis

The physiological and biochemical index data were analyzed with the software SAS 9.1.3 (SAS Inc., Cary, NC, USA). Significance analysis of difference between treatments was conducted using the ANOVA program, followed by the LSD test at a significance level of p < 0.01.

3. Results

3.1. Phenotypic Observation and Chlorophyll Content Measurement

Here, we compared the phenotypic changes in melon seedlings across different treatments. Under control conditions, the seedlings exhibited robust growth (Figure S1A). However, under waterlogging stress, adventitious roots emerged from the hypocotyls (Figure S1B). The removal of these adventitious roots resulted in wilting leaves and deterioration of primary roots in seedlings subjected to waterlogging stress (Figure S1C). Notably, compared to the control group, the contents of chlorophyll a, chlorophyll b, and total chlorophyll in seedlings under waterlogging stress and adventitious root removal treatments were significantly reduced, with total chlorophyll levels decreasing by 34.19% and 62.89%, respectively (Figure 1A–C). Furthermore, seedlings subjected to adventitious root removal displayed markedly lower levels of chlorophyll a, chlorophyll b, and total chlorophyll than those experiencing waterlogging stress alone (Figure 1A–C).

3.2. Changes in Contents of Malondialdehyde (MDA), H2O2 and O2•− Production Rate

The contents of MDA, H2O2 and O2•− production rate were assessed in the control, waterlogging stress, and adventitious root removal treatments. Compared to the control group, MDA levels were significantly elevated under both waterlogging stress and adventitious root removal treatments, rising by 81.98% and 162.26%, respectively (Figure 1D). The H2O2 content in the waterlogging stress and adventitious root removal treatments increased to 2.26-fold and 2.64-fold of the control, respectively (Figure 1E). Additionally, the O2•− production rate was significantly higher in the adventitious root removal treatment compared to the waterlogging stress treatment, while the control exhibited the lowest production rate (Figure 1F).

3.3. Changes in Antioxidant Enzyme Activity

The activities of several antioxidant enzymes, including CAT, POD, SOD, APX and MDHAR were assessed across different treatments. No significant differences in CAT activity were observed among the various treatments (Figure 2A). In contrast, POD activity increased to 1.63-fold and 1.72-fold of the control in the waterlogging stress and adventitious root removal treatments, respectively (Figure 2B). Similarly, SOD activity rose to 2.65-fold and 3.06-fold in these treatments (Figure 2C). No significant differences in APX activity were observed between the waterlogging stress treatment and the control (Figure 2D). However, the removal of adventitious roots significantly enhanced APX activity, which increased to 2.57-fold of the control. Furthermore, compared to the control group, MDHAR activity was significantly elevated under both waterlogging stress and adventitious root removal treatments, rising by 407.93% and 768.16%, respectively (Figure 2E).

3.4. Changes in Non-Enzymatic Antioxidants

AsA and GSH serve as main non-enzymatic antioxidants within the free radical scavenging system. The levels of AsA were significantly increased under both waterlogging stress and adventitious root removal treatments compared to the control (Figure 3A). Specifically, AsA contents increased to 2.20-fold and 2.75-fold of the control in the waterlogging stress and adventitious root removal treatments, respectively. Furthermore, the removal of adventitious roots markedly reduced the levels of DHA compared to both the waterlogging stress treatment and the control (Figure 3B). Additionally, compared to the control group, the AsA/DHA ratios were significantly elevated under both waterlogging stress and adventitious root removal treatments, rising by 131.57% and 335.62%, respectively (Figure 3C).
We observed that GSH levels were significantly elevated under both waterlogging stress and adventitious root removal treatments compared to the control, increasing to 1.50-fold and 1.95-fold, respectively (Figure 3D). The GSSG content under adventitious root removal treatment was significantly higher than that observed in the control group (Figure 3E). Additionally, no significant differences were detected in the GSH/GSSG ratio across the various treatments (Figure 3F).

3.5. Changes in Enzyme Activities of Aerobic and Anaerobic Respiration

The activities of ADH and PDC serve as indicators of anaerobic respiration, while SDH activity reflects aerobic respiration. The results showed that both waterlogging stress and the removal of adventitious roots significantly enhanced the activities of ADH and PDC when compared to the control group (Figure 4A,B). Specifically, waterlogging stress and adventitious root removal increased ADH activities by 184.68% and 562.24%, respectively. Moreover, the ADH activity in the adventitious root removal treatment was significantly higher than that observed under waterlogging stress alone. In contrast, when compared to the control, both waterlogging stress and the removal of adventitious roots resulted in significant reductions in SDH activity, with decreases of 57.42% and 67.58%, respectively (Figure 4C).

3.6. Changes in Proline and Flavonoids Contents

As illustrated in Figure 5A, proline levels were markedly elevated under both waterlogging stress and adventitious root removal treatments, which increased to 2.72-fold and 4.28-fold of the control, respectively. Furthermore, the flavonoids contents was significantly enhanced under waterlogging stress and removal of adventitious roots, with increases of 110.77% and 175.53%, respectively, compared to the control group (Figure 5B).

3.7. Changes in Plant Hormones Contents

The levels of endogenous abscisic acid (ABA), 1-aminocyclopropane-1-carboxylic acid (ACC, the precursor of ethylene), jasmonic acid (JA) and brassinolide (BR) were quantified using high-performance liquid chromatography (HPLC) in this study. The results showed that both waterlogging stress and the removal of adventitious roots significantly increased ABA levels compared to the control, with increases of 183.31% and 196.92%, respectively (Figure 6A). Additionally, waterlogging stress and adventitious root removal significantly increased ACC content compared to the control (Figure 6B). Notably, the ACC content of waterlogging stress and adventitious root removal treatments increased to 2.75-fold and 6.19-fold of the control, and the ACC content of adventitious root removal was significantly higher than that of waterlogging stress alone. Furthermore, JA levels under waterlogging stress and adventitious root removal were significantly enhanced by 84.50% and 180.54%, respectively, compared to the control (Figure 6C). Conversely, both waterlogging stress and the removal of adventitious roots resulted in significant reductions in BR levels by 58.91% and 63.37%, respectively, compared to the control (Figure 6D).

3.8. Overview of Detected Metabolites

The primary roots from the control, waterlogging stress, and adventitious root removal treatments were collected for metabolites quantification. Principal component analysis (PCA) demonstrated distinct separation among the control, waterlogging stress, and adventitious root removal treatments (Figure S2), indicating significant differentiation in metabolite profiles. After pre-processing, a total of 450 metabolites were identified in positive mode and 293 metabolites in negative mode. Using a phytochemical classification approach, 224 metabolites were categorized as primary metabolites, 268 as secondary metabolites, and 251 as others (Figure 7A). Among the primary metabolites, lipids constituted the largest proportion, followed by amino acids and derivatives, as well as carbohydrates and derivatives (Figure 7C). In contrast, terpenoids represented the predominant category of secondary metabolites, followed by steroids and steroid derivatives, and flavonoids (Figure 7B).
The identified metabolites were classified according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The results showed that these metabolites were assigned into three first-grade KEGG pathways and 14 s-grade pathways (Figure 7D). For the ‘metabolism’ term, the top pathway was ‘global and overview maps’, followed by ‘biosynthesis of other secondary metabolites’, ‘amino acid metabolism’, ‘lipid metabolism’ and ‘metabolism of terpenoids and polyketides’. For the ‘environmental information processing’ term, the enriched pathways included ‘membrane transport’ and ‘signal transduction’. Furthermore, for the ‘genetic information processing’ term, the enriched pathways were ‘translation’ and ‘folding, sorting and degradation’.

3.9. Identification of Differentially Accumulated Metabolites (DAMs)

A total of 447 DAMs were identified across the three pairwise comparison groups (Table S1). In the WL vs. CK comparison group, 284 DAMs were detected, comprising 130 up-regulated and 154 down-regulated metabolites. The number of DAMs in the R-AR vs. CK comparison group was 319, with 193 up-regulated and 126 down-regulated metabolites. Meanwhile, in the R-AR vs. WL comparison group, 263 DAMs were identified, including 190 up-regulated and 73 down-regulated metabolites (Figure 8A). KEGG enrichment analysis indicated the presence of 3, 4, and 5 significantly enriched pathways in the WL vs. CK, R-AR vs. CK, and R-AR vs. WL comparisons, respectively. Notably, the pathways associated with ‘plant hormone signal transduction’, ‘α-linolenic acid metabolism’ and ‘nucleotide metabolism’ were enriched across all comparison groups (Figure 8B–D).
Venn diagrams of the DAMs identified were constructed (Figure 8E,F). Among the up-regulated DAMs, 18 DAMs were found to be common across all three comparison groups, with the ‘arginine and proline metabolism’ pathway being highly enriched (Figure 8E, Table S2). Additionally, a total of 31 DAMs were specific to WL vs. CK comparison group, and these DAMs were notably enriched in ‘biosynthesis of cofactors’ pathway. In the R-AR vs. CK comparison group, 20 DAMs were uniquely up-regulated, exhibiting marked enrichment in the ‘nucleotide metabolism’ pathway. Furthermore, the R-AR vs. WL comparison group revealed 98 uniquely up-regulated DAMs, which were enriched in the ‘brassinosteroid biosynthesis’ and ‘α-linolenic acid metabolism’ pathways (Figure 8E, Table S2).
Among the three comparison groups, seven down-regulated DAMs were identified as common, with the ‘plant hormone signal transduction’ pathway exhibiting significant enrichment in these metabolites (Figure 8F, Table S2). The WL vs. CK comparison group presented 56 uniquely down-regulated DAMs, which were significantly enriched in the ‘nucleotide metabolism’ pathway. A total of 14 DAMs were specific to R-AR vs. CK comparison group, and these DAMs were enriched in three KEGG pathways, including ‘nucleotide metabolism’, ‘purine metabolism’ and ‘thiamine metabolism’. Additionally, the R-AR vs. WL comparison group identified 52 uniquely down-regulated DAMs (Figure 8F).

3.10. Identification of Metabolites with Top Fold Change

To comprehensively investigate the metabolic alterations induced by waterlogging stress and the removal of adventitious roots, we analyzed the top ten metabolites exhibiting significant up-regulation and down-regulation within each comparison group (Figure 9, Table S3). In the WL vs. CK comparison group, the ten metabolites that were significantly up-regulated included (2S,3′S)-α-amino-2-carboxy-5-oxo-1-pyrrolidinebutanoic acid, jasmonic acid, Val-Gly-Ile-Ser-Asp, methylmalonic acid, (+)-cis-5,6-dihydro-5-hydroxy-4-methoxy-6-(2-phenylethyl)-2H-pyran-2-one, estrone glucuronide, cyanidin 3-(2G-xylosylrutinoside), malvidin 3-(6-malonylglucoside) 5-glucoside, osthenol and physagulin A (Figure 9A). These metabolites were notably enriched in the KEGG pathways of ‘α-linolenic acid metabolism’, ‘plant hormone signal transduction’, ‘pyrimidine metabolism’ and ‘valine, leucine and isoleucine degradation’ (Table S4). In R-AR vs. CK comparison group, we observed that (2S,3′S)-α-amino-2-carboxy-5-oxo-1-pyrrolidinebutanoic acid, jasmonic acid, Glu-Asp-Val-Asp, methylmalonic acid, Val-Gly-Ile-Ser-Asp, (+)-cis-5,6-dihydro-5-hydroxy-4-methoxy-6-(2-phenylethyl)-2H-pyran-2-one, ligstroside-aglycone, foeniculoside VII, coroloside and p-Hydroxyfelbamate were highly up-regulated with top fold change (Figure 9B). Interestingly, the KEGG pathways enriched by metabolites in the R-AR vs. CK comparison group included those found in the WL vs. CK comparison group, as well as the ‘propanoate metabolism’ pathway (Table S4). In the R-AR vs. WL comparison group, the ten metabolites with substantial up-regulation included all-trans-farnesyl acetate, humilixanthin, Glu-Asp-Val-Asp, p-Hydroxyfelbamate, ligstroside-aglycone, Tyr-Ser, foeniculoside VII, 3,4-dhpea-ea, 1-methyladenosine, and morusinol (Figure 9C).
Subsequently, we identified the top ten significantly up-regulated metabolites that were common across various comparison groups. As illustrated in Figure 9, five metabolites were shared between the WL vs. CK and R-AR vs. CK comparison groups, including methylmalonic acid, jasmonic acid, Val-Gly-Ile-Ser-Asp, (+)-cis-5,6-dihydro-5-hydroxy-4-methoxy-6-(2-phenylethyl)-2H-pyran-2-one, and (2S,3′S)-α-amino-2-carboxy-5-oxo-1-pyrrolidinebutanoic acid. Additionally, ligstroside-aglycone, p-hydroxyfelbamate, foeniculoside VII, and Glu-Asp-Val-Asp were identified as common in both the R-AR vs. CK and R-AR vs. WL comparison groups. Notably, jasmonic acid is involved in plant hormone signal transduction, methylmalonic acid belongs to the class of organic acids and derivatives, and (2S,3′S)-α-amino-2-carboxy-5-oxo-1-pyrrolidinebutanoic acid is classified as the class of proline and derivatives (Table S3).

3.11. Identification of Metabolites with Top Variable Importance in Projection (VIP) Scores

Metabolomics data typically contains a large amount of metabolite information, and VIP scores can be utilized to select the metabolites that contribute the most to the grouping. In this study, we identified the top 30 metabolites with the highest VIP scores across each comparison group (Figure 10, Table S5). In the WL vs. CK comparison group, these metabolites were notably enriched in the KEGG pathways of ‘plant hormone signal transduction’ and ‘brassinosteroid biosynthesis’ (Table S6). Conversely, the metabolites in the R-AR vs. CK comparison group did not exhibit significant enrichment in any KEGG pathways. In the R-AR vs. WL comparison group, the top 30 metabolites were associated with four KEGG pathways, namely ‘plant hormone signal transduction’, ‘brassinosteroid biosynthesis’, ‘glucosinolate biosynthesis’, and ‘pyrimidine metabolism’ (Table S6). Notably, cyanidin 3-(2G-xylosylrutinoside) was classified as an anthocyanidin within the flavonoids category (Table S1). This metabolite achieved the highest VIP score in the WL vs. CK comparison group (Figure 10A) and ranked second in the R-AR vs. CK group (Figure 10B). Additionally, cyanidin 3-(2G-xylosylrutinoside) was significantly up-regulated in both comparison groups above (Table S1), suggesting that this metabolite might play a significant role in waterlogging response. The VIP value of jasmonic acid ranked in the top 30 for both the WL vs. CK (Figure 10A) and R-AR vs. CK comparison groups (Figure 10B), with its fold change in up-regulation ranking second in both comparison groups (Figure 9). The metabolite (2S,3′S)-α-amino-2-carboxy-5-oxo-1-pyrrolidinebutanoic acid, categorized as a proline derivative, exhibited the highest VIP score in the R-AR vs. CK comparison group (Figure 10B) and the third highest in the WL vs. CK group (Figure 10A), alongside the highest fold change in up-regulation in both groups (Figure 9, Table S3). Furthermore, the VIP value of brassinolide ranked fifth (Figure 10A) and the down-regulation fold change within the top ten metabolites (Figure 9A, Table S3) in the WL vs. CK comparison group. Although brassinolide was significantly down-regulated in the R-AR vs. CK comparison group, it exhibited a lower VIP score (Table S1). Lastly, ligstroside-aglycone and foeniculoside VII, both classified as terpenoids, were included among the top 30 metabolites with VIP scores (Figure 10B) and were also among the top ten significantly up-regulated metabolites in the R-AR vs. CK comparison group (Figure 9B, Table S3), though they did not qualify as differentially accumulated metabolites in the WL vs. CK comparison group (Table S1).

4. Discussion

In recent years, global warming has emerged as a significant challenge to agricultural production, leading to increased frequency and intensity of precipitation events, thereby augmenting the risk of waterlogging stress [13]. Waterlogging stress is reported to severely impact crop production at all stages, from seed germination to maturation, affecting nearly 16% of the global agricultural production area [36]. As global climate change progresses, it is estimated that the area affected by waterlogging will expand, which will undoubtedly heighten the risk to agricultural production [37].
To withstand the detrimental effects of waterlogging stress, various crop species have evolved distinct adaptive strategies, with the development of adventitious roots being a crucial component [4]. In our previous research, we found that, in response to low oxygen environments, the hypocotyls of melon (Cucumis melo L.) seedlings can produce abundant adventitious roots when subjected to waterlogging stress [4]. In the present study, we aim to elucidate the significance of adventitious roots by examining the physiological, biochemical, and metabolic alterations following their removal under waterlogging stress.
Under normal conditions, the generation and elimination of reactive oxygen species (ROS) in plants maintain a dynamic equilibrium [38]. However, adverse environmental stressors can disrupt this balance, leading to increased ROS levels [39,40]. Consistent with previous research, we found that both H2O2 content and the rate of O2•− production were significantly elevated under waterlogging stress and adventitious root removal treatments compared to the control (Figure 1E,F). Notably, the O2•− production rate in the adventitious root removal treatment was the highest (Figure 1F). Malondialdehyde (MDA), a byproduct of lipid peroxidation in cell membranes, is generally considered a reliable indicator of oxidative stress [41]. Our findings revealed that the MDA level in the adventitious root removal treatment was significantly higher than that in waterlogging stress and the control (Figure 1D). These results suggest that the removal of adventitious roots leads to increased ROS production and accelerated membrane lipid peroxidation under waterlogging stress. It has been reported that an overabundance of ROS can result in leaf wilting and root rot [42,43]. Similarly, in this study, the seedlings subjected to the adventitious root removal treatment exhibited poor phenotypes characterized by withered leaves and decayed roots (Figure S1C), which corresponded with decreased levels of chlorophyll a, chlorophyll b, and total chlorophyll (Figure 1A–C). This indicates that the removal of adventitious roots results in the most detrimental phenotypic outcomes, highlighting the irreplaceable and critical role of adventitious roots in supporting melon seedlings under waterlogging stress.
An antioxidant system serves as the main driving force in regulating excessive ROS generation and plays a crucial role in managing lipid peroxidation through a combination of antioxidant enzymes and non-enzymatic antioxidants [39,44,45,46]. In the present study, we observed a significant increase in the activities of POD and SOD under both waterlogging stress and adventitious root removal compared to the control group (Figure 2B,C). These findings are consistent with previous research [47,48] and confirm the antioxidant roles of POD and SOD in response to waterlogging. Additionally, ascorbic acid (AsA) and glutathione (GSH) are recognized as potent antioxidants capable of scavenging ROS [49,50]. Our results demonstrated that the levels of AsA and GSH were significantly elevated under both waterlogging stress and adventitious root removal treatments compared to the control (Figure 3A,D). Notably, the GSH level in the adventitious root removal treatment was the highest (Figure 3D). Furthermore, the AsA/DHA ratio in the adventitious root removal treatment was significantly higher than that in waterlogging stress and the control (Figure 3C). Monodehydroascorbate reductase (MDHAR), a pivotal enzyme for the regeneration of AsA, reduces MDHA to AsA, thereby maintaining AsA levels [13]. Our findings revealed that MDHAR activity in the adventitious root removal treatment was significantly higher than that observed under waterlogging stress and in the control group (Figure 2E). It has been reported that proline can scavenge free radicals and accumulates in plants under detrimental conditions [51,52,53]. Expectedly, in this study, the proline level in the adventitious root removal treatment was the highest (Figure 5A). These results indicate that the removal of adventitious roots induces a more severe oxidative stress response compared to waterlogging stress alone, stimulating a stronger ROS elimination mechanism in melon seedlings.
When soil becomes waterlogged, the pores within the soil are filled with water. Nevertheless, the rate of oxygen diffuses is four orders of magnitude lower in water compared to that in air [54]. This results in a marked decrease in the availability of oxygen for plant roots [4,55]. Previous studies have demonstrated that plants have evolved survival strategies to cope with hypoxia conditions, which involve transforming aerobic respiration into anaerobic respiration to compensate for energy supply [2,38,39,42,55,56,57,58]. In the present study, we observed that the activity of succinate dehydrogenase (SDH), a key enzyme representative of aerobic respiration [42], was significantly suppressed under both waterlogging stress and adventitious root removal compared to the control group (Figure 4C). Pyruvate decarboxylase (PDC) and alcohol dehydrogenase (ADH) are regarded as key enzymes in the ethanol fermentation process, with PDC transforming pyruvate to acetaldehyde and ADH facilitating the conversion of acetaldehyde to ethanol [15,39,59]. Our findings indicated that both waterlogging stress and adventitious root removal treatments resulted in a significant increase in the activities of ADH and PDC compared to the control (Figure 4A,B). Notably, the ADH activity in the adventitious root removal treatment was markedly higher than that observed under waterlogging stress alone (Figure 4A). These results suggest that hypoxia triggers anaerobic respiration to provide temporary energy for melon seedlings, particularly in the absence of adventitious roots.
Metabolites play an essential and inseparable role in the stress responses of plants [50,53]. In this study, we examined the metabolic profiles of primary roots subjected to control, waterlogging stress, and adventitious root removal treatments. A total of 743 metabolites were identified and categorized into three first-grade KEGG pathways and 14 s-grade pathways (Figure 7D). Across the three pairwise comparison groups, we identified 447 differentially accumulated metabolites (DAMs) (Table S1), indicating a robust metabolic response to waterlogging. In the WL vs. CK comparison group, 284 DAMs were observed, while 319 DAMs were identified in R-AR vs. CK (Figure 8A). Compared to the control, the adventitious root removal treatment resulted in a greater number of differential metabolites than waterlogging stress alone, suggesting more extensive metabolic reprogramming following adventitious root removal. This extensive reprogramming may partially explain the observed poor phenotype associated with the removal of adventitious roots (Figure S1C).
Plant hormones, as key factors in signal transduction pathways, play important roles in plant growth and development, as well as in responses to various biotic and abiotic stresses. Previous studies have indicated that hormones such as ethylene, abscisic acid, brassinolide, and jasmonic acid are involved in the response to waterlogging stress [4,60]. Our metabolomic analysis further corroborated this, revealing significant enrichment of the ‘plant hormone signal transduction’ pathway across all three comparison groups (Figure 8B–D). Additionally, alterations in the levels of abscisic acid, jasmonic acid, and brassinolide under waterlogging stress and adventitious root removal treatments (Figure 6) provide compelling evidence for the involvement of these hormones in the waterlogging response. Jasmonic acid been reported to play a crucial role in coordinating plant stress responses [61,62,63]. Genes associated with the jasmonic acid pathway have been confirmed to participate in the response to waterlogging stress [64,65]. In this study, we observed a significant increase in jasmonic acid levels under both waterlogging stress and adventitious root removal compared to the control, with the jasmonic acid content in the adventitious root removal treatment being significantly higher than that in the waterlogging stress treatment (Figure 6C). This suggests that jasmonic acid is involved in the waterlogging response of melon, particularly under conditions involving the removal of adventitious roots. As anticipated, jasmonic acid was identified as a differentially accumulated metabolite in both the WL vs. CK and R-AR vs. CK comparison groups (Table S1), with its up-regulation exhibiting the second highest fold change in these groups (Figure 9, Table S3). Furthermore, the fold change in jasmonic acid in the R-AR vs. CK comparison group was greater than that in the WL vs. CK comparison group (Table S3). Moreover, the VIP value of jasmonic acid ranked sixth in the R-AR vs. CK group, while it ranked thirtieth in the WL vs. CK group (Figure 10, Table S5), suggesting that jasmonic acid contributes more significantly after the removal of adventitious roots under waterlogging stress. It has been reported that jasmonic acid can mediate the antioxidant defense system to mitigate waterlogging-induced damage [63]. In this study, adventitious root removal resulted in more severe oxidative stress and a detrimental phenotype. We speculate that the elevated levels of jasmonic acid in the adventitious root removal treatment may contribute to enhancing antioxidant potential. Brassinolide has also been recognized as an important signaling molecule in response to waterlogging stress [64,65,66]. In grapevine, waterlogging stress has been shown to significantly reduce the transcription levels of genes involved in brassinosteroid synthesis [65]. Consistent with this, our metabolomic results demonstrated that brassinolide was significantly down-regulated in both WL vs. CK and R-AR vs. CK comparison groups (Table S1), aligning with observations that brassinolide levels were notably repressed under waterlogging stress and adventitious root removal treatments (Figure 6D). This indicates that brassinolide might mediate potential pathways necessary for waterlogging tolerance in melon.
Flavonoids are a critical category of defensive antioxidants, characterized by their ability to scavenge free radicals and exhibit antioxidant activity [67,68]. In Pterocarya stenoptera, genes associated with flavonoid were significantly up-regulated in response to waterlogging stress [63]. In the present study, we observed that the contents of flavonoids were significantly increased under both waterlogging stress and adventitious root removal compared to control conditions (Figure 5B). Notably, cyanidin 3-(2G-xylosylrutinoside), a member of flavonoids, was significantly up-regulated in both WL vs. CK and R-AR vs. CK comparison groups (Table S1). This compound exhibited the highest VIP value in WL vs. CK (Figure 10A) and ranked second in R-AR vs. CK (Figure 10B). Additionally, both waterlogging and adventitious root removal resulted in an increase in reactive oxygen species (Figure 1E,F). Based on these results, we hypothesize that this metabolite may provide favorable function in defense to waterlogging-induced oxidative damages. Interestingly, our metabolomic analysis revealed that (2S,3′S)-α-amino-2-carboxy-5-oxo-1-pyrrolidinebutanoic acid, classified to proline and derivatives, exhibited the highest VIP value in the R-AR vs. CK comparison group (Figure 10B) and ranked third in the WL vs. CK comparison (Figure 10A). Furthermore, this metabolite demonstrated the highest fold change in up-regulation across both the R-AR vs. CK and WL vs. CK comparison groups (Figure 9, Table S3), indicating its potential contribution to the waterlogging response in melon seedlings. In watermelon, two terpenoids have been identified as key metabolites in response to flooding stress [69]. In our study, ligstroside-aglycone and foeniculoside VII, categorized as terpenoids, were among the top 30 metabolites based on VIP scores (Figure 10B) and ranked among the top ten significantly up-regulated metabolites in the R-AR vs. CK comparison group (Figure 9B, Table S3). However, they were not identified as DAMs in the WL vs. CK comparison group (Table S1), indicating that these two terpenoids metabolites may serve as specific pivotal marker metabolites for adventitious root removal under waterlogging stress.

5. Limitations of the Study

Under waterlogging stress, the removal of adventitious roots inevitably caused mechanical damage to melon seedlings. Consequently, the severely compromised phenotypes observed in the adventitious root removal treatment could be attributed to the combined effects of adventitious root removal and wounding stress. Ideally, a wounding-only control should have been implemented to isolate the impact of mechanical injury from that of adventitious root loss. However, we observed that melon seedlings develop adventitious roots on their hypocotyls exclusively under waterlogging stress, whereas they do not produce adventitious roots under normal control conditions. Unfortunately, it appears that a wounding-only control cannot be established. Furthermore, waterlogging stress leads to reduced oxygen availability in the affected tissues, with primary roots being the initial site of injury. In this study, primary roots were exclusively collected to assess their physiological, biochemical and metabolic alterations, thereby missing a crucial opportunity to directly profile the metabolic state of the adventitious roots. In future research, the response mechanisms of both primary roots and adventitious roots under waterlogging stress should be analyzed.

6. Conclusions

In conclusion, seedlings subjected to the removal of adventitious roots exhibited phenotypic abnormalities such as withered leaves and decayed roots, along with increased production of reactive oxygen species (ROS). Subsequent untargeted metabolomic analysis revealed that R-AR vs. CK group exhibited the highest number of differential metabolites, indicating extensive metabolic reprogramming following adventitious root removal. These results underscore the indispensable role of adventitious roots under waterlogging stress, as demonstrated through physiological, biochemical, and metabolic investigations. Furthermore, complex metabolic response differences in plant hormones, flavonoids, proline and derivatives, and terpenoids were detected. This research highlights the critical role of adventitious roots and identifies potential pathways and metabolites that perform vital functions in the waterlogging response of melon, providing a foundation for further exploration of the mechanisms underlying waterlogging stress.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15102281/s1, Table S1: Detailed information of differentially accumulated metabolites; Table S2: KEGG enrichment analysis of up-regulated and down-regulated differentially accumulated metabolites (DAMs); Table S3: Detailed information of the top ten metabolites with significantly up-regulated and down-regulated in each comparison group; Table S4: KEGG enrichment analysis of the top ten metabolites with significantly up-regulated in each comparison group; Table S5: Detailed information of the top 30 metabolites with variable importance in projection (VIP) scores in each comparison group; Table S6: KEGG enrichment analysis of the top 30 metabolites with VIP scores; Figure S1: Plant growth of melon seedlings under control condition (A), waterlogging stress alone (B), and adventitious root removal of waterlogged plants (C). The red arrow indicates the adventitious roots that arise from the hypocotyls under waterlogging stress. Bars, 1 cm; Figure S2: Principal component analysis (PCA) for all samples based on untargeted metabolomic data. CK, control condition; WL, waterlogging stress; R-AR, removal of adventitious roots; QC, quality control sample.

Author Contributions

Formal analysis, H.Z. and G.L.; Methodology, H.Z. and G.L.; Validation, C.Y. and Q.C.; Writing—original draft, H.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Natural Science Foundation of China (32260756), Basic Research and Talent Cultivation Project of Jiangxi Academy of Agricultural Sciences (JXSNKYJCRC202311), China Postdoctoral Science Foundation (2021M701514), Postdoctoral Research Optimal Funding Project of Jiangxi Province (2021KY44), the Modern Agricultural Research Collaborative Innovation Program of Jiangxi Province (JXXTCXQN202007 and JXXTCX202109), the Jiangxi Province Science Foundation for Youths (20192BAB214017), and the Innovation Program of Jiangxi Academy of Agricultural Sciences (20181CBS002).

Institutional Review Board Statement

This study does not contain any studies with human participants or animal experiments.

Data Availability Statement

All datasets obtained for this study are included in the manuscript/Supplementary Data.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

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Figure 1. Fluctuation in the chlorophyll a content (A), chlorophyll b content (B), total chlorophyll content (C), malondialdehyde (MDA) content (D), H2O2 content (E) and O2•− production rate (F). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01. CK, control condition; WL, waterlogging stress; R-AR, removal of adventitious roots.
Figure 1. Fluctuation in the chlorophyll a content (A), chlorophyll b content (B), total chlorophyll content (C), malondialdehyde (MDA) content (D), H2O2 content (E) and O2•− production rate (F). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01. CK, control condition; WL, waterlogging stress; R-AR, removal of adventitious roots.
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Figure 2. Fluctuation in the catalase (CAT) activity (A), peroxidase (POD) activity (B), superoxide dismutase (SOD) activity (C), ascorbate peroxidase (APX) activity (D) and monodehydroascorbic acid reductase (MDHAR) activity (E). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
Figure 2. Fluctuation in the catalase (CAT) activity (A), peroxidase (POD) activity (B), superoxide dismutase (SOD) activity (C), ascorbate peroxidase (APX) activity (D) and monodehydroascorbic acid reductase (MDHAR) activity (E). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
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Figure 3. Fluctuation in the ascorbic acid (AsA) content (A), dehydroascorbic acid (DHA) content (B), AsA/DHA ratio (C), glutathione (GSH) content (D), oxidized glutathione (GSSG) content (E) and GSH/GSSG ratio (F). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
Figure 3. Fluctuation in the ascorbic acid (AsA) content (A), dehydroascorbic acid (DHA) content (B), AsA/DHA ratio (C), glutathione (GSH) content (D), oxidized glutathione (GSSG) content (E) and GSH/GSSG ratio (F). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
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Figure 4. Fluctuation in the alcohol dehydrogenase (ADH) activity (A), pyruvate decarboxylase (PDC) activity (B) and succinate dehydrogenase (SDH) activity (C). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
Figure 4. Fluctuation in the alcohol dehydrogenase (ADH) activity (A), pyruvate decarboxylase (PDC) activity (B) and succinate dehydrogenase (SDH) activity (C). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
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Figure 5. Fluctuation in the proline content (A) and flavonoid content (B). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
Figure 5. Fluctuation in the proline content (A) and flavonoid content (B). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
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Figure 6. Fluctuation in the abscisic acid (ABA) content (A), 1-aminocyclopropane-1-carboxylic acid (ACC) content (B), jasmonic acid (JA) content (C) and brassinolide (BR) content (D). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
Figure 6. Fluctuation in the abscisic acid (ABA) content (A), 1-aminocyclopropane-1-carboxylic acid (ACC) content (B), jasmonic acid (JA) content (C) and brassinolide (BR) content (D). Data are shown with standard deviation. Different letters denote significant differences at p < 0.01.
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Figure 7. Phytochemical classification (A–C) and KEGG functional pathway (D) of the detected metabolites.
Figure 7. Phytochemical classification (A–C) and KEGG functional pathway (D) of the detected metabolites.
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Figure 8. A survey of differentially accumulated metabolites (DAMs). (A) Statistical histogram of DAMs. (B) KEGG enrichment analysis of WL vs. CK comparison group. (C) KEGG enrichment analysis of R-AR vs. CK comparison group. (D) KEGG enrichment analysis of R-AR vs. WL comparison group. (E) Venn diagram of up-regulated DAMs among the three comparison groups. (F) Venn diagram of down-regulated DAMs among the three comparison groups.
Figure 8. A survey of differentially accumulated metabolites (DAMs). (A) Statistical histogram of DAMs. (B) KEGG enrichment analysis of WL vs. CK comparison group. (C) KEGG enrichment analysis of R-AR vs. CK comparison group. (D) KEGG enrichment analysis of R-AR vs. WL comparison group. (E) Venn diagram of up-regulated DAMs among the three comparison groups. (F) Venn diagram of down-regulated DAMs among the three comparison groups.
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Figure 9. Top fold change metabolites with significantly up-regulated and down-regulated in WL vs. CK comparison group (A), R-AR vs. CK comparison group (B) and R-AR vs. WL comparison group (C). The orange bars indicate up-regulated metabolites, while the green bars indicate down-regulated metabolites.
Figure 9. Top fold change metabolites with significantly up-regulated and down-regulated in WL vs. CK comparison group (A), R-AR vs. CK comparison group (B) and R-AR vs. WL comparison group (C). The orange bars indicate up-regulated metabolites, while the green bars indicate down-regulated metabolites.
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Figure 10. Metabolites with top variable importance in projection (VIP) scores in WL vs. CK comparison group (A), R-AR vs. CK comparison group (B) and R-AR vs. WL comparison group (C).
Figure 10. Metabolites with top variable importance in projection (VIP) scores in WL vs. CK comparison group (A), R-AR vs. CK comparison group (B) and R-AR vs. WL comparison group (C).
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MDPI and ACS Style

Zhang, H.; Yan, C.; Chen, Q.; Li, G. Depicting the Physiological, Biochemical and Metabolic Responses to the Removal of Adventitious Roots and Their Functions in Cucumis melo Under Waterlogging Stress. Agronomy 2025, 15, 2281. https://doi.org/10.3390/agronomy15102281

AMA Style

Zhang H, Yan C, Chen Q, Li G. Depicting the Physiological, Biochemical and Metabolic Responses to the Removal of Adventitious Roots and Their Functions in Cucumis melo Under Waterlogging Stress. Agronomy. 2025; 15(10):2281. https://doi.org/10.3390/agronomy15102281

Chicago/Turabian Style

Zhang, Huanxin, Chengpu Yan, Qian Chen, and Guoquan Li. 2025. "Depicting the Physiological, Biochemical and Metabolic Responses to the Removal of Adventitious Roots and Their Functions in Cucumis melo Under Waterlogging Stress" Agronomy 15, no. 10: 2281. https://doi.org/10.3390/agronomy15102281

APA Style

Zhang, H., Yan, C., Chen, Q., & Li, G. (2025). Depicting the Physiological, Biochemical and Metabolic Responses to the Removal of Adventitious Roots and Their Functions in Cucumis melo Under Waterlogging Stress. Agronomy, 15(10), 2281. https://doi.org/10.3390/agronomy15102281

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