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Article

Response of Metabolites in Cymbopogon distans Leaves to Water Addition in Karst Areas during Different Seasons

by
Aiwei Huang
1,†,
Hongxia Jing
1,†,
Muhammad Umair
1,2 and
Hongmei Du
1,*
1
School of Design, Shanghai Jiao Tong University, Shanghai 200240, China
2
College of Life Science, Zhejiang Normal University, Jinhua 321004, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Horticulturae 2024, 10(1), 16; https://doi.org/10.3390/horticulturae10010016
Submission received: 3 November 2023 / Revised: 18 December 2023 / Accepted: 20 December 2023 / Published: 22 December 2023
(This article belongs to the Section Biotic and Abiotic Stress)
Browse Figures
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Abstract

:
Climate change could influence the plant response to drought stress in karst environments. However, fewer related studies have been reported. This study examined the impact of artificial water addition on the accumulation of metabolites of Cymbopogon distans with a non-targeted metabolomics approach during both the dry and wet seasons. Three water treatment gradients (CK, T1, and T2, indicating 0%, +20%, and +40% relative to the average monthly precipitation, respectively) were chosen. The findings of our study indicate that the levels of primary metabolites were higher in the leaves of C. distans during the dry season compared to the rainy season. In addition, the presence of water did not have a substantial impact on the composition and functionality of metabolites between the wet and drought seasons. The contents of some lipids were greater during the dry season, while others were greater during the wet season. During the dry season, the contents of FA, DG, MGDG, SQDG, TG, and PR decreased with water addition. Our findings demonstrated that artificial water addition might have a greater impact on metabolite accumulation during the dry season in drought-tolerant species in karst areas. Due to the buildup of certain metabolites, they exhibit clear drought resistance. At the same time, water addition during the dry season will also cause a certain stress, affecting the adaptability of plants. These findings have significant ramifications for the management and choice of species in various sea seasons in karst regions.

1. Introduction

Karst landscapes are a dichotomy of surface and subsurface formations created by the weathering and dissolution of limestone [1]. It is characterized by pronounced precipitation cycles with significant seasonal features and regional differences in the karst region of southwest China. And the soil layer is thin with weak water retention capacity. There is an obvious dry season and a rainy season, and much change in temperature exists in this area [2].
Dryland soils and plants play important roles in global carbon storage. Vegetation regulates energy flows and biogeochemical cycles through photosynthesis, respiration, and transpiration on Earth [3]. Complex climatic factors, disturbances caused by climate change, and environmental changes induced by human activity, can alter vegetation dynamics [4]. Due to water scarcity, dryland ecosystems are vulnerable to changes in regional temperature, rainfall, and atmospheric CO2 [5,6].
Drought stress directly affects plant metabolism [7]. Previous studies have investigated the metabolic regulation of Arabidopsis thaliana [8], wheat (Triticum astivum) [9], poplar (Populus simonii and P. deltoides ‘Danhong’) [10], and other plant species under drought stress [11]. Osmoregulation is one of the main mechanisms for plants to cope with water shortages. Substances, such as amino acids, amines, and carbohydrates, accumulate in large quantities under osmotic stress and maintain the normal shape and function of cells by restoring osmotic balance [11,12]. In addition, substances such as glutathione and ascorbic acid can also restore redox metabolism by scavenging reactive oxygen species and play multiple protective roles during abiotic stress in plants [13].
Membrane lipids of higher plants not only form the biological backbone of the cell membrane and provide energy for metabolism, but also serve as precursors for the synthesis of signal molecules [14,15,16]. Lipid regulation during plant exposure to abiotic stress has been extensively studied. For example, changes in membrane fatty acid composition help Arabidopsis adapt to different temperature conditions [17]. Arabidopsis under freezing stress altered membrane lipid composition, membrane fusion, and cell death due to increased lipolytic activity [18]. Salt stress induces lipid adjustment in sorghum (Sorghum bicolor) leaves [19]. Drought stress decreased the total lipid contents of rape (Brassica napus) leaves [20]. And the main lipid components, such as galactolipids and phospholipids, decreased under drought stress [20,21].
Nowadays, global warming is showing climate change trends of elevated temperatures, increased precipitation, and frequent extreme weather. It has been observed that there has been an increase in annual precipitation in southwest China for the last decade [22]. Cymbopogon distans is a typical indigenous plant that dominates grasslands in this area [23] and is well-known for the production of high-value essential oils used in medicines, perfumes, and cosmetics [24,25]. As a warm-season grass, it prefers high temperatures and proper humidity but often ceases growth in cold or drought conditions [23] and is very sensitive to supplemental irrigation [26,27]. The metabolic response of C. distans has been studied in this region during the dry season, with the conclusion that water addition favored the accumulation of metabolites in the leaves [27], but that study did not take into account the effects of naturally increased precipitation during the wet season. The aim of this study was to predict the potential effects of future rainfall increases on the growth of typical vegetation and community structure in karst areas using metabolomic methods. This was achieved by artificially adding water to the soils of natural shrub-grass communities in southern Yunnan karst during both the dry and wet seasons.

2. Materials and Methods

2.1. Description of Study Area and Experimental Design

The study area is located on a gentle southern slope at the Ecological Research Station in Jianshui County (23°59′ N, 102°93′ E), Honghe Hani and Yi Autonomous Prefecture, Yunnan Province, which falls into a typical subtropical monsoon climate with distinct dry season and wet seasons [27]. The vegetation in this area is typical of a shrub-grass community, with C. distans as the dominant species in the herbaceous layer. Fifteen 3 m × 3 m sample plots were delineated in a random grouping, each containing C. distans, and the corners of the plots were marked with PVC tubes, as reported in our previous research [27]. A volumetric water content (VWC) monitoring system (HOBO Micro Station, S-TMB*M006, S-SMDM005, Onset, Bourne, MA, USA) was installed in the surface soil of each sample plot. The system monitors and records data on the VWC of the soil surface layer every 15 min.
Three water treatment gradients, namely CK, T1, and T2, were employed in the study. Each gradient was applied to five sample plots as five replicates. CK served as the control group (the natural precipitation of the area), and T1 and T2 were monthly additions of 20% and 40% of the average monthly precipitation based on the climate data from 2010 to 2017, respectively, on this area. In April 2017, a total of ten sample plots, denoted as T1 and T2, were subjected to a controlled spiking procedure with water. The process was conducted on the 10th, 20th, and 30th mornings of each month, collecting samples with 1/3 of the monthly precipitation, as specified by the planned experimental design [27] using climatic data, which encompassed the precipitation in 2017 [27] and 2018 (Figure S1). The month of April was classified as the period of low precipitation, known as the dry season, while the month of August was designated as the period of high precipitation, known as the rainy season.

2.2. Sample Collection and Chemical Analysis

2.2.1. Sample Collection and Preparation

The sampling intervals were established at the end of April and August of 2018, which occurred one year after the implementation of the water addition treatment. For each sample, a total of 2–4 completely expanded leaves from mature and typically growing C. distans were carefully chosen and gathered. The leaves were promptly gathered and placed in a thermally insulated container containing dry ice. Subsequently, they were air transferred to the laboratory and stored in a freezer operating at a temperature of −80 °C in the School of Agriculture and Biology, Shanghai Jiao Tong University.
Metabolites were determined using techniques described by Lisec et al. [28] and Mutsumi et al. [29], with minor adjustments made to assure accuracy and appropriateness. A fresh sample weighing 0.1 g was carefully measured and transferred into a 2 mL centrifuge tube. Subsequently, the tube was inserted into a freezer grinder (model JXFSTPRP-III) that was connected to a liquid nitrogen supply. Using low-temperature steel spheres, the specimen was ground to a fine powder. A total volume of 0.35 mL of chloroform and 1.05 mL of methanol was introduced. Additionally, 20 uL of a ribitol solution with a concentration of 2 mg/mL was added as an internal standard. The resulting mixture was subjected to a full vortex, followed by thorough mixing and shaking at 70 °C for 10 min. Subsequently, the mixture was centrifuged at a speed of 12000× g at 4 °C for 15 min. Next, 0.7 mL of supernatant was transferred into a new centrifuge tube with a capacity of 2 mL. After adding 0.1 mL of chloroform and 0.5 mL of deionized water to the mixture, it was vortexed and centrifuged for 20 min at 2200× g.
Subsequently, a volume of 0.4 mL from the uppermost layer was transferred to the headspace vial. Simultaneously, a volume of 20 μL from each sample was placed into a fresh headspace vial and combined to create a quality control sample. In the process of derivation, following complete desiccation, a volume of 80 μL of pyridine-methoxamine solution with a concentration of 20 mg/mL was introduced. Following the vortexing process, the bottle was incubated for two hours at 37 °C. Following this, 80 μL of MSTFA (BSTFA:TMCS = 99:1) solution and 80 μL of pyridine were added to the mixture, and it was then incubated for 1.5 h at 70 °C.

2.2.2. GC-MS Analysis of Metabolome

The Agilent GC-MS apparatus (7890A-5975C) was utilized to conduct gas chromatography-mass spectrometry (GC-MS) measurements, with each individual sample lasting roughly 55 min. The GC inlet utilized for this experiment was a PAL injector, which had a 1 μL injection volume. The GC column used was a DB-5ms column with dimensions of 30 m in length, 250 μm in diameter, and a film thickness of 0.25 μm. The initial temperature set for the column was 60 °C. Following the execution of the sample, it was subjected to a gradual increase in temperature, reaching 300 °C at a rate of 5 °C per minute, and subsequently maintained at this temperature for a duration of 6 min. Helium was used as the mobile phase at a flow rate of 1 mL/min. Within the mass spectrometry region, the solvent delay was 6.5 min, the scan range was 33–600 amu, the MS ion source temperature was 230 °C, and the MS quadrupole temperature was 150 °C.
Following the preliminary screening and analysis of the GC-MS data, employing the LECO Chroma TOF Database Connection specifically optimized for the Pegasus program. The pertinent metabolites were further subjected to a comprehensive search and identification process using the NIST 2011 spectrum library. The determination of the relative content of each product was based on the peak area of the internal standard ribitol.

2.2.3. UPLC-MS Analysis of Metabolome

UPLC was performed with a Waters ACQUITY UPLC I-Class System and Vion IMS QT of Mass Spectrometer (Waters Corp., Milford, MA, USA) equipped with a binary pump, a vacuum degasser, an auto-sampler, and a column oven. The column temperature was maintained at 45 °C, and the chromatographic separation was achieved on a Waters ACQUITY UPLC BEH C18 column (100 × 2.1 mm, 1.7 μm, Waters). Mobile phases A and B were water and acetonitrile, both with 0.1% (v/v) formic acid, respectively. The linear gradients for UPLC-HPLC chromatographic conditions transplantation were 5–100% B in 15 min. The flow rate was 0.4 mL/min. The injection volume of the sample was 0.1–1 μL. The analysis time was 20 min.
Mass spectrometry analysis was performed on a Vion IMS QTof Mass Spectrometer (Waters Corp., MA, USA) equipped with a LockSpray ion source and operated in positive and negative electrospray ionization mode. Two independent scans, a low energy scan (CE, 4 eV) and a high energy scan (CE, 15–40 eV) with different collision energies, were acquired during the running cycle. The scan time was 0.25 s, and the scan range was 50 to 1000 amu. Argon (≥99.999%) was used as a collision-induced dissociation gas. The capillary voltage and cone voltage were set at 2000 V and 40 V, respectively. The source temperature was 115 °C. The desolvation gas flow was set to 900 L/h at 450 °C. Nitrogen (>99.5%) was employed as desolvation and cone gas. For lock mass correction, a 250 ng/mL standard solution of leucine-enkephalin in acetonitrile, water, and formic acid (50:49.9:0.1, v:v:v) was continuously infused (5 μL/min) through the reference probe and scanned every 30 s. Using the Waters Corporation UNIFI informatics platform, an accurate mass screening methodology was used to review all of the data.

2.3. Data Analysis

The data were initially collected and summarized using Microsoft Excel 2016. The statistical technique known as Analysis of Variance (ANOVA) was utilized to examine and visualize the variations in metabolite contents across different groups. This analysis was conducted utilizing the SPSSAU platform, which can be accessed at https://spssau.com (28 March 2022). The figures displayed were drawn with Sigma-Plot 10.0. The Metabo Analyst 5.0 software was utilized to conduct partial least squares discriminant analysis (PLS-DA) and visualize the metabolite profiles of different groups. The metabolic pathway analysis was performed using the Oryza sativa subsp. japonica (Japanese rice) library available in the KEGG pathway database.

3. Results

3.1. Changes of Soil Volumetric Water Content under Dry and Wet Seasons

In comparison to the dry season, there was a significant increase in the soil volumetric water content (SVWC) during the wet season (p < 0.05). During the rainy season, the SVWC for CK (control group), T1, and T2 exhibited an increase of 2.32, 2.41, and 2.31 times, respectively. The SVWC exhibited a notable rise as the amount of water added increased during the same season as compared to the control group (CK) (Figure 1).

3.2. Accumulation of Metabolites in Cymbopogon distans Leaves under Different Seasons

A total of 126 metabolites were identified in the leaves of C. distans, including 40 organic acids, 12 amino acids, 46 sugars and sugar alcohols, 5 amine compounds, and 23 miscellaneous chemicals (Table S1). PLS-DA methods were employed to differentiate the metabolites between the two seasons and the three watering treatments. Components 1 and 2 explained 51.4% of the variation. More precisely, the sample points displayed complete segregation on component 1 throughout various seasons. Moreover, it was noted that the inclusion of water during the arid season had a more significant influence on the buildup of metabolites, as illustrated in Figure 2.
During the rainy season, there was a substantial drop (p < 0.05) in the overall contents of organic acids in the CK group, as well as in the amino acids, sugars, and sugar alcohols in both the CK and T1 groups. Additionally, the contents of other substances in all three groups also exhibited a significant decrease during the wet season as compared to the dry season. Furthermore, when compared to the control group, there was a notable decrease in the concentrations of various chemicals at the T1 and T2 plots. During the dry season, a considerable reduction in the level of organic acids was specifically observed at the T1 plots. During a specific season, there were no significant differences in the amounts of sugars, sugar alcohols, and amino acids between the CK and watering treatment groups (Figure 3).
The levels of 91 metabolites exhibited statistically significant variation (p < 0.05) as determined by ANOVA (Table S1). Furthermore, a total of 30 differential metabolites were selected by applying a filter based on their variable importance in projection (VIP) values, with a threshold of VIP > 1.3, in the PLS-DA. Only four metabolites (carbamate, ascorbic acid, galactose, and ethylene glycol) were up-regulated, but the other 26 metabolites were down-regulated during the wet season compared with the dry season, as shown in Figure 4. Many sugars and sugar alcohols, such as fucose, turanose, ribofuranose, methyl α-D-glucofuranoside, and 3,4-dihydroxyphenylglycol, exhibited an accumulation pattern in C. distans leaves during the period of dryness. However, their levels demonstrated a decline subsequent to rainfall or the introduction of water through artificial methods (Figure 4).

3.3. Primary Metabolites Pathways in Cymbopogon distans Leaves

The Kyoto Encyclopedia of Genes and Genomes (KEGG) conducted an analysis of 91 metabolites with varying accumulation levels, resulting in the identification of 42 metabolic pathways that are interconnected. Six significant metabolic pathways were identified that met the following criteria: a p score less than 0.05, an impact score greater than 0.10, and a match status of more than one. These pathways included galactose metabolism, glyoxylate, dicarboxylate metabolism, glycine, serine, and threonine metabolism, TCA cycle, glutathione metabolism, and alanine, aspartate, and glutamate metabolism (Figure 5A).
In the absence of water (in the CK group), the majority of metabolites involved in galactose metabolism, glyoxylate and dicarboxylate metabolism, TCA cycle, glutathione metabolism, and alanine, aspartate, and glutamate metabolism exhibited greater activity during the wet season compared with the dry season. However, metabolites linked with glycine, serine, and threonine metabolism were found in higher concentrations during the dry season. In terms of the effect of water addition on metabolism, it was found that when water was added, the metabolites involved in alanine, aspartate, and glutamate metabolism were up-regulated, regardless of the season. On the other hand, the metabolites associated with glyoxylate and dicarboxylate metabolism, as well as the TCA cycle were only up-regulated when water was added during the dry season. Additionally, the metabolites related to glutathione metabolism were up-regulated during the dry season but down-regulated during the wet season in response to water addition (Figure 5B).
In the present study, it was shown that the addition of water across different seasons resulted in the up- or down-regulation of 12 metabolites across the six metabolic pathways (Figure 6). Cadaverine was the only amine compound. Additionally, the mixture contained three components belonging to the category of sugars and sugar alcohols, namely galactose, galactinol, and glycerol. Furthermore, five amino acids, namely alanine, 5-oxoproline, glutamic acid, threonine, and glycine, were present in the mixture. This group also includes three organic acids, i.e., oxalic acid, aconitic acid, and citric acid. It was observed that the levels of cadaverine, galactose, galactinol, alanine, 5-oxoproline, glutamic acid, oxalic acid, aconitic acid, and citric acid in the CK group exhibited an up-regulation during the wet season in comparison to the dry season. Conversely, the levels of glycerol, glycine, and threonine in the CK group displayed a down-regulation. The concentration of amino acids, particularly alanine, exhibited an increase upon the onset of the rainy season in both the CK and T2 plots. Furthermore, during the dry season, water injection resulted in a significant rise in the levels of 5-oxoproline, whereas glycerol and glycine experienced a substantial decline. Compared to the CK, there was a significant reduction in the levels of cadaverine in T1 and T2 plots, as well as glutamic acid in T1 plots during the rainy season (Figure 6).

3.4. Changes of Lipid Metabolites in Cymbopogon distans Leaves under Different Seasons

UPLC-MS discovered a total of 310 lipid compounds, the contents of 34 of which did not differ substantially between any two treatment groups. The 276 substances with significant changes were classified into 16 classes: 46 Fatty Acyls (FA), 3 Monoradylglycerols (MG), 17 Diacylglycerols (DG), 4 Triacylglycerols (TG), 7 Monogalactosyldiacylglycerols (MGDG), 2 Sulfoquinovosyldiacylglycerols (SQDG), 14 phosphatidylcholines (PC), 16 phosphatidylethanolamines (PE), 12 phosphatidylserines (PS), 8 phosphatidylglycerols (PG), 10 PI, 21 PA, 50 Prenol Lipids (PR), 1 Saccarolipids (SL), 6 SP, and 59 Sterol Lipids (ST) (Table S2).
The PLS-DA score plot revealed a clear differentiation in the lipid content of C. distans between the dry and wet seasons, as seen by their varied positions along component 1. Additionally, the CK and T2 groups exhibited noticeable disparities in their locations along component 3. Components 1 and 3 accounted for 62.3% of the overall variation, as depicted in Figure 7A. Based on the plot of VIP scores for component 1, it can be shown that out of the total of 276 metabolites, 15 exhibited a noteworthy categorical impact (VIP > 1.30) on lipid composition across the six groups. The entities can be categorized into six distinct groups, namely ST, FA, PS, PE, PR, and SP. Cannogenin (ST2), which is classified as one of the 59 sterol lipids, exhibits the most elevated VIP score among all the identified compounds, with a value of 1.40 (Figure 7B).
In comparison to the dry season, there was a significant increase in the overall lipid content observed during the rainy season. Specifically, the CK, T1, and T2 groups showed increases in lipid content of 81.54%, 100.23%, and 64.39%, respectively (Figure 8). Furthermore, the relative proportions of each lipid class within the total lipids remained consistent throughout all six treatment groups. The predominant lipid classes were ST, MGDG, PR, and PA, all of which accounted for more than 4% of the total lipids. Conversely, the lipid classes MG, TG, SQDG, PG, and SL constituted less than 1% of the total lipids. Nevertheless, there were notable variations in the relative proportions of the predominant lipid species, namely ST, MGDG, and PR, across different conditions. Specifically, the percentage of ST increased from 29.4% (CK in the dry season) to 53.7% (T1 in the wet season), while the percentage of MGDG decreased from 30.9% (CK in the dry season) to 18.9% (T1 in the dry season). Additionally, the percentage of PR decreased from 16% (CK in the dry season) to 6% (T1 in the wet season) (Figure 9).
The influence of seasonal factors on lipid levels showed a notably robust effect. The ANOVA results revealed that out of the 16 lipid classes examined, the levels of seven classes (MGDG, SQDG, PC, PE, PS, PA, and ST) were significantly higher during the wet season compared to the dry season (Figure 10A–G). Conversely, the levels of six classes (TG, DG, FA, PI, PR, and SL) were found to be significantly elevated during the dry season in comparison to the wet season (Figure 10H–M). The remaining three classes did not exhibit a statistically significant difference in contents between the two seasons (Figure 10N–P).
In contrast to the rainy season, the dry season had a more pronounced impact of water addition on lipid concentrations. Additionally, it was observed that the levels of FA were comparatively higher in both the CK and T1 groups in comparison to the T2 group, as depicted in Figure 10I. Furthermore, the CK group exhibited higher levels of DG, MGDG, and SQDG in comparison to both the T1 and T2 groups, as illustrated in Figure 10F,G,J. Moreover, the content of TG was found to be higher in the CK group compared to the T1 group, as shown in Figure 10K. Lastly, the content of PR was observed to be higher in the CK group in comparison to the T2 group (Figure 10H).
Based on the column chart, an analysis was conducted on the composition of the top 15 lipids with the highest VIP scores in the PLS-DA. This analysis was performed separately for both the dry and wet seasons, considering various water treatments (Figure 11). During the dry season, the CK group exhibited a recording of 60% of the maximum values, as depicted in Figure 11A–G, I, O. Furthermore, the highest values for four FA compounds (Figure 11A–D) were observed exclusively in CK plots during the dry season. The concentrations of these compounds in the three treatment groups during the dry season were found to be 15, 8, 7, and 9 times greater than their corresponding levels during the wet season. Three out of four primary metabolites (Figure 11E–G) exhibited a notable increase of 4-, 6-, and 8-fold during the dry season compared with the rainy season. In contrast, the observed PR4 exhibited a four-fold increase during the wet season compared with the dry season, as depicted in Figure 11H. During the dry season, ST1 and SP1 exhibited greater values (Figure 11I,O), whereas ST2, PS1, PS2, PE1, and PE2 had higher values during the rainy season (Figure 11J–N). Compared to CK, the expression levels of FA2, FA3, PR1, PR2, and SP1 were observed to be down-regulated in the water addition treatment plots during the dry season (Figure 11B,C,E,F,O). Conversely, the expression of ST2 was found to be up-regulated (Figure 11J).

4. Discussions

The objective of this investigation was to assess the alterations in metabolite composition within the leaves of the prevailing grass species, C. distans, in a controlled water supplementation experiment conducted in a representative karst shrub-grass ecosystem located in southern Yunnan. The indigenous plants in the region are well-suited to the climatic patterns of that region. Prior studies have indicated that the metabolic attributes of leaves exhibit seasonal variations [30]. The findings of this study have substantiated the correlation between leaf metabolism and seasonal moisture patterns while additionally unveiling the impact of soil moisture fluctuations within the same season on the accumulation of leaf metabolites.

4.1. Characteristic Polar Metabolites in Cymbopogon distans Leaves between Two Seasons and Three Water Addition Treatments

Insufficient water availability can lead to the physiological response of wilting and cellular impairment in plant species [31]. C. distans, being one of the indigenous warm-season herbaceous plants, exhibited a state of dormancy during the period of low precipitation [24]. In this research, it was found that the dry season was associated with elevated levels of primary metabolites with polar characteristics. Our results supported previous results that many soluble chemicals possess the ability to enhance intracellular osmotic pressure and facilitate water retention during periods of drought-induced stress [12].
Research has indicated that the presence of antioxidants, such as ascorbic acid and glutathione, significantly contributes to plants’ ability to withstand oxidative stress [13]. Furthermore, it has been found that the galactose metabolic pathway serves as a crucial mechanism for the biosynthesis of ascorbic acid in plants [32]. The accumulation of galactose, galactinol, and ascorbic acid may aid the grass in scavenging harmful compounds that have acquired as a result of increasing water levels.
Similar to sugars, plants also accumulate a large number of amino acids in response to stress [33]. Consistent with the pathway of glycine, serine, and threonine metabolism analyzed by KEGG, the contents of amino acids (glycine and threonine) were high during the dry season and significantly reduced during the wet season, and the effects of water addition on them were not significant during the wet season. The observed phenomenon can be attributed to the robust proliferation of vegetation in the rainy season, wherein an increased consumption of amino acids occurs, facilitating the production of proteins necessary for the purposes of growth and maturation.
It was observed that a majority of the important metabolic pathways exhibited up-regulation during the wet season compared with the dry season. Additionally, during the dry season, the metabolite pathways showed up-regulation in the water addition groups as opposed to the control group. These findings may potentially indicate the consistent elevation of physiological activities in C. distans following water supplementation in an environment characterized by water scarcity. Throughout the month of August, the addition of water did not induce any substantial modifications in the chemical composition or metabolic activity. The impact of water supplementation may be insignificant due to abundant water availability in the control group and the inadequate water retention capacity of the karst soils.

4.2. Characteristic Lipids in Cymbopogon distans Leaves between Two Seasons and Three Treatments

During periods of stress, there are often significant alterations in membrane lipids, both in quality and quantity. These changes might manifest as modifications in different phospholipids within the cell, as well as variations in the degree of unsaturation of fatty acids [34]. Drought reduced the overall number of lipids found in the leaves of C. distans, as it did in rape [21]. Glycerophospholipids, including PA, PC, PE, PG, PI, PS, MGDG, and SQDG, are the primary constituents of membrane lipids [35]. During the wet season, there was a substantial increase in the levels of PA, PC, PE, PS, and ST. This could perhaps be attributed to the rapid cell division and a higher proportion of biofilm that occurs during the rainy season, which promotes the rapid proliferation of C. distans.
MGDG and SQDG are integral and significant constituents of photosynthetic membranes. The quantities of MGDG and SQDG have a direct impact on the composition and characteristics of chloroplasts and thylakoids, which play a crucial role in sustaining the optimal efficiency of photosynthesis [36]. The levels of MGDG tend to decrease in plants when they are subjected to stressors such as drought, salt, or frost [37]. In this study, MGDG and SQDG increased during the wet season but decreased during the dry season under water-added conditions when compared to the control group, suggesting that the water addition during the dry season damaged the photosynthetic membranes of C. distans and that extensive MGDG and SQDG were decomposed.
Plant leaves, being vital tissues, comprise considerable amounts of lipids found on the surface and in the membranes. On the other hand, the concentrations of FA, DG, and TG are comparatively moderate and demonstrate a downward trajectory throughout the senescent phase. [38,39]. FAs play a significant role as primary constituents of glycerolipids and are synthesized within plastids. Alternatively, they can be transported to the endoplasmic reticulum to support the synthesis of membrane lipids [38]. The occurrence of abiotic stress conditions results in the degradation of thylakoids, leading to the liberation of FA and DG [35,40]. Compared to CK, the water treatment groups exhibited reductions in FA, DG, TG, and PR during the dry season. This finding also supported the fact that C. distans is a locally adapted vegetation and that rainfall during the dry season created an unfavorable adversity.

5. Conclusions

High temperatures, droughts, and poor soil layers make the indigenous plants in the karst areas show strong drought resistance and adaptability to changes in soil moisture during both the dry and rainy seasons. However, the anticipated rise in precipitation in the area would significantly affect the development of indigenous plants. C. distans is a typical drought-resistant plant in karst areas. The study revealed that the high content of polar metabolites enabled C. distans to withstand prolonged periods of drought stress. The introduction of water during the dry season resulted in increased activity of C. distans. Conversely, the provision of artificial watering during the wet season had a minimal effect on the accumulation of metabolites. It was also found that water addition during the dry season created an unfavorable environment, as shown by the degradation of some kinds of membrane lipids. This implies that indigenous plants, such as C. distans, have adapted to the dry conditions. The increase in rainfall might affect the growth of dominant species in the karst areas, leading to a loss of C. distans’ prevailing status. Therefore, on the one hand, we should further study the effect of water addition on the growth of local dominant species and, on the other hand, the selection of species more suitable for local climate change.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/horticulturae10010016/s1: Table S1. 126 polar primary metabolites of Cymbopogon distans leaves comparing three water addition treatments across two seasons (dry and wet) (Mean ± SE, n = 5); Table S2. 276 lipids of Cymbopogon distans leaves comparing three water addition treatments across two seasons (dry and wet) (Mean ± SE, n = 5); Figure S1. The distribution of average monthly precipitation (mm) in 2018.

Author Contributions

Conceptualization, H.D.; methodology, H.D., H.J. and A.H.; software, A.H. and H.J.; validation: H.D. and M.U.; formal analysis: A.H. and H.J.; investigation, A.H. and H.J.; resources, H.D.; data curation, A.H. and H.J.; writing—original draft preparation, A.H. and H.D.; writing—review and editing, A.H., M.U. and H.D.; visualization, A.H. and H.D.; supervision, H.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by The National Key R & D Program of China (2016YFC0502501).

Data Availability Statement

All analyzed data are included in the article and its Supplementary Materials.

Acknowledgments

We thank the assistance of the Yunnan Jianshui Research Station and the staff during the field work. The experimental analyses were carried out at the Analytical and Testing Center of Shanghai Jiao Tong University. Thanks to Fiza Liaquat for the helpful review of our manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

ANOVAAnalysis of variance
DGDiacylglycerols
FAFatty acyls
GC-MSGas chromatography-mass spectrometry
KEGGKyoto Encyclopedia of Genes and Genomes
MGMonoradylglycerols
MGDGMonogalactosyldiacylglycerols
PAPhosphatidic acid
PCPhosphatidylcholines
PEPhosphatidylethanolamines
PGPhosphatidylglycerols
PIPhosphatidylinositols
PRPrenol lipids
PSPhosphatidylserines
SLSaccarolipids
SPSphingolipids
STSterol lipids
SQDGSulfoquinovosyldiacylglycerols
SVWCSoil volumetric water content
TGTriacylglycerols
VIPVariable importance in projection
VWCVolumetric water content

References

  1. Yu, Z. The origin and evolution of the karst landscape. Yunnan Geol. 2003, 22, 1–15. [Google Scholar]
  2. Ford, D.; Williams, P. Karst Hydrogeology. In Karst Hydrogeology and Geomorphology; John Wiley & Sons, Ltd.: Hoboken, NJ, USA, 2007; pp. 103–144. [Google Scholar]
  3. Jackson, R.; Randerson, J.; Canadell, J.; Anderson, R.; Avissar, R.; Baldocchi, D.; Bonan, G.; Caldeira, K.; Diffenbaugh, N.; Field, C.; et al. Protecting climate with forests. Environ. Res. Lett. 2008, 3, 044006. [Google Scholar]
  4. Chen, B.; Xu, G.; Coops, N.; Ciais, P.; Innes, J.; Wang, G.; Myneni, R.; Wang, T.; Krzyzanowski, J.; Li, Q.; et al. Changes in vegetation photosynthetic activity trends across the Asia–Pacific region over the last three decades. Remote Sens. Environ. 2014, 144, 28–41. [Google Scholar]
  5. Berg, A.; Sheffield, J. Climate change and drought: The soil moisture perspective. Curr. Clim. Change Rep. 2018, 4, 180–191. [Google Scholar]
  6. Hanan, N.P.; Milne, E.; Aynekulu, E.; Yu, Q.; Anchang, J. A role for drylands in a carbon neutral world? Front. Environ. Sci. 2021, 9, 786087. [Google Scholar]
  7. Fàbregas, N.; Fernie, A.R. The metabolic response to drought. J. Exp. Bot. 2019, 70, 1077–1085. [Google Scholar]
  8. Rizhsky, L.; Liang, H.; Shuman, J.; Shulaev, V.; Davletova, S.; Mittler, R. When defense pathways collide. The response of arabidopsis to a combination of drought and heat stress. Plant Physiol. 2004, 134, 1683–1696. [Google Scholar]
  9. Zhao, Y.; Du, P.; Chen, Z.; Bai, X.; Lin, R.; Xiao, K. Characterization on the water deprivation-associated physiological traits as well as the related differential genes during seed filling stage in wheat (T. aestivum L.). Plant Cell Tissue Organ Cult. 2020, 140, 605–618. [Google Scholar]
  10. Jia, H.; Wang, L.; Li, J.; Sun, P.; Lu, M.; Hu, J. Comparative metabolomics analysis reveals different metabolic responses to drought in tolerant and susceptible poplar species. Physiol. Plant. 2020, 168, 531–546. [Google Scholar]
  11. Kumar, M.; Kumar Patel, M.; Kumar, N.; Bajpai, A.B.; Siddique, K.H.M. Metabolomics and molecular approaches reveal drought stress tolerance in plants. Int. J. Mol. Sci. 2021, 22, 9108. [Google Scholar]
  12. Yancey, P.H. Organic osmolytes as compatible, metabolic and counteracting cytoprotectants in high osmolarity and other stresses. J. Exp. Bot. 2005, 208, 2819–2830. [Google Scholar]
  13. Mittler, R. Oxidative stress, antioxidants and stress tolerance. Trends Plant Sci. 2002, 7, 405–410. [Google Scholar]
  14. Wallis, J.G.; Browse, J. Mutants of Arabidopsis reveal many roles for membrane lipids. Prog. Lipid Res. 2002, 41, 254–278. [Google Scholar]
  15. Wang, X.; Chapman, K. Lipid signaling in plants. Front. Plant Sci. 2013, 4, 216. [Google Scholar]
  16. Boutté, Y.; Jaillais, Y. Metabolic cellular communications: Feedback mechanisms between membrane lipid homeostasis and plant development. Dev. Cell 2020, 54, 171–182. [Google Scholar]
  17. Falcone, D.L.; Ogas, J.P.; Somerville, C.R. Regulation of membrane fatty acid composition by temperature in mutants of Arabidopsis with alterations in membrane lipid composition. BMC Plant Biol. 2004, 4, 17. [Google Scholar]
  18. Welti, R.; Li, W.; Li, M.; Sang, Y.; Biesiada, H.; Zhou, H.E.; Rajashekar, C.B.; Williams, T.D.; Wang, X. Profiling membrane lipids in plant stress responses. Role of phospholipase D alpha in freezing-induced lipid changes in Arabidopsis. J. Biol. Chem. 2002, 277, 31994–32002. [Google Scholar]
  19. Ge, S.; Liu, D.; Chu, M.; Liu, X.; Wei, Y.; Che, X.; Zhu, L.; He, L.; Xu, J. Dynamic and adaptive membrane lipid remodeling in leaves of sorghum under salt stress. Crop J. 2022, 10, 1557–1569. [Google Scholar]
  20. Dakhma, W.S.; Zarrouk, M.; Cherif, A. Effects of drought-stress on lipids in rape leaves. Phytochemistry 1995, 40, 1383–1386. [Google Scholar]
  21. Moradi, P.; Mahdavi, A.; Khoshkam, M.; Iriti, M. Lipidomics unravels the role of leaf lipids in thyme plant response to drought stress. Int. J. Mol. Sci. 2017, 18, 2067. [Google Scholar]
  22. Piao, S.; Ciais, P.; Huang, Y.; Shen, Z.; Peng, S.; Li, J.; Zhou, L.; Liu, H.; Ma, Y.; Ding, Y.; et al. The impacts of climate change on water resources and agriculture in China. Nature 2010, 467, 43–51. [Google Scholar]
  23. Zhao, Z.Q.; Chai, Y.; Cui, M.; Li, G.X.; He, L.P.; Ma, S.Y.; Liu, Y.G. Study on species diversity of plant communities in dry-hot valleys of northwest and southeast Yunnan. Res. Environ. Sci. 2022, 35, 2447–2457, (In Chinese with English Abstract). [Google Scholar]
  24. Verma, R.S.; Padalia, R.C.; Chauhan, A. Introduction of Cymbopogon distans (Nees ex Steud.) Wats to the sub-tropical India: Evaluation of essential-oil yield and chemical composition during annual growth. Ind. Crop. Prod. 2013, 49, 858–863. [Google Scholar]
  25. Wang, S.; Li, S.C.; Cheng, F.S.; Ren, T.; Li, F.; Mei, D.H.; Gao, K.; Song, Q.Y. Antifungal, repellency, and insecticidal activities of Cymbopogon distans and Ruta graveolens essential oils and their main chemical constituents. Chem. Biodivers. 2022, 19, e202200351. [Google Scholar]
  26. Umair, M.; Sun, N.; Du, H.; Chen, K.; Tao, H.; Yuan, J.; Abbasi, A.M.; Liu, C. Differential stoichiometric responses of shrubs and grasses to increased precipitation in a degraded karst ecosystem in Southwestern China. Sci. Total Environ. 2020, 700, 134421. [Google Scholar]
  27. Umair, M.; Sun, N.; Du, H.; Yuan, J.; Abbasi, A.M.; Wen, J.; Yu, W.; Zhou, J.; Liu, C. Differential metabolic responses of shrubs and grasses to water additions in arid karst region, southwestern China. Sci. Rep. 2019, 9, 9613. [Google Scholar]
  28. Lisec, J.; Schauer, N.; Kopka, J.; Willmitzer, L.; Fernie, A.R. Gas chromatography mass spectrometry–based metabolite profiling in plants. Nat. Protoc. 2006, 1, 387–396. [Google Scholar]
  29. Watanabe, M.; Netzer, F.; Tohge, T.; Orf, I.; Brotman, Y.; Dubbert, D.; Fernie, A.R.; Rennenberg, H.; Hoefgen, R.; Herschbach, C. Metabolome and lipidome profiles of Populus × canescens twig tissues during annual growth show phospholipid-linked storage and mobilization of C, N, and S. Front. Plant Sci. 2018, 9, 1292. [Google Scholar]
  30. Bloomfield, K.J.; Cernusak, L.A.; Eamus, D.; Ellsworth, D.S.; Colin Prentice, I.; Wright, I.J.; Boer, M.M.; Bradford, M.G.; Cale, P.; Cleverly, J.; et al. A continental-scale assessment of variability in leaf traits: Within species, across sites and between seasons. Funct. Ecol. 2018, 32, 1492–1506. [Google Scholar]
  31. Colmer, T.D.; Barton, L. A review of warm-season turfgrass evapotranspiration, responses to deficit irrigation, and drought resistance. Crop Sci. 2017, 57, S-98–S-110. [Google Scholar]
  32. Wheeler, G.L.; Jones, M.A.; Smirnoff, N. The biosynthetic pathway of vitamin C in higher plants. Nature 1998, 393, 365–369. [Google Scholar]
  33. Araniti, F.; Lupini, A.; Mauceri, A.; Zumbo, A.; Sunseri, F.; Abenavoli, M.R. The allelochemical trans-cinnamic acid stimulates salicylic acid production and galactose pathway in maize leaves: A potential mechanism of stress tolerance. Plant Physiol. Biochem. 2018, 128, 32–40. [Google Scholar]
  34. Devi, S.R.; Prasad, M.N.V. Membrane lipid alterations in heavy metal exposed plants. In Heavy Metal Stress in Plants: From Molecules to Ecosystems; Prasad, M.N.V., Hagemeyer, J., Eds.; Springer: Berlin/Heidelberg, Germany, 1999; pp. 99–116. [Google Scholar]
  35. Yu, L.; Zhou, C.; Fan, J.; Shanklin, J.; Xu, C. Mechanisms and functions of membrane lipid remodeling in plants. Plant J. 2021, 107, 37–53. [Google Scholar]
  36. Kalisch, B.; Dörmann, P.; Hölzl, G. DGDG and Glycolipids in plants and algae. In Lipids in Plant and Algae Development; Nakamura, Y., Li-Beisson, Y., Eds.; Subcellular Biochemistry; Springer International Publishing: Cham, Switzerland, 2016; pp. 51–83. [Google Scholar]
  37. Benning, C. Mechanisms of lipid transport involved in organelle biogenesis in plant cells. Annu. Rev. Cell Dev. Biol. 2009, 25, 71–91. [Google Scholar]
  38. Yang, Z.; Ohlrogge, J.B. Turnover of fatty acids during natural senescence of Arabidopsis, Brachypodium, and Switchgrass and in Arabidopsis β-Oxidation Mutants. Plant Physiol. 2009, 150, 1981–1989. [Google Scholar]
  39. Xu, C.; Shanklin, J. Triacylglycerol metabolism, function, and accumulation in plant vegetative tissues. Annu. Rev. Plant Biol. 2016, 67, 179–206. [Google Scholar]
  40. Xu, C.; Fan, J.; Shanklin, J. Metabolic and functional connections between cytoplasmic and chloroplast triacylglycerol storage. Prog. Lipid Res. 2020, 80, 101069. [Google Scholar]
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Figure 1. Surface soil volumetric water content under dry and wet seasons with different water treatments (CK, T1, and T2). Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments during a specific season. A star indicates a significant difference (p < 0.05) when comparing seasons at a particular water treatment.
Figure 1. Surface soil volumetric water content under dry and wet seasons with different water treatments (CK, T1, and T2). Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments during a specific season. A star indicates a significant difference (p < 0.05) when comparing seasons at a particular water treatment.
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Figure 2. PLS-DA scores plot of compatible solutes of Cymbopogon distans leaves comparing three water addition treatments across two seasons.
Figure 2. PLS-DA scores plot of compatible solutes of Cymbopogon distans leaves comparing three water addition treatments across two seasons.
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Figure 3. Contents of organic acids (A), amino acids (B), sugars and sugar alcohols (C), and other substances (D) in Cymbopogon distans leaves comparing three water addition treatments across two seasons (dry and wet seasons). Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments for a particular season. A star indicates a significant difference (p < 0.05) when comparing seasons at a particular water treatment.
Figure 3. Contents of organic acids (A), amino acids (B), sugars and sugar alcohols (C), and other substances (D) in Cymbopogon distans leaves comparing three water addition treatments across two seasons (dry and wet seasons). Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments for a particular season. A star indicates a significant difference (p < 0.05) when comparing seasons at a particular water treatment.
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Figure 4. Differential metabolites and their expression changes in Cymbopogon distans leaves during the dry and wet seasons. “VIP” means the scores in component 1 of PLS-DA.
Figure 4. Differential metabolites and their expression changes in Cymbopogon distans leaves during the dry and wet seasons. “VIP” means the scores in component 1 of PLS-DA.
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Figure 5. Impact analysis of KEGG pathways of deferentially accumulated metabolites (A) and changes in metabolite abundance in important pathways (B) with seasonal changes and water addition in the leaves of Cymbopogon distans.
Figure 5. Impact analysis of KEGG pathways of deferentially accumulated metabolites (A) and changes in metabolite abundance in important pathways (B) with seasonal changes and water addition in the leaves of Cymbopogon distans.
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Figure 6. The contents of 12 important metabolites in Cymbopogon distans leaves associated with 6 important pathways were used to compare the three watering treatments across two seasons (dry and wet). Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments for a particular season. The star sign indicates a significant difference (p < 0.05) when comparing seasons at a particular water addition treatment.
Figure 6. The contents of 12 important metabolites in Cymbopogon distans leaves associated with 6 important pathways were used to compare the three watering treatments across two seasons (dry and wet). Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments for a particular season. The star sign indicates a significant difference (p < 0.05) when comparing seasons at a particular water addition treatment.
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Figure 7. PLS-DA scores plot (A) and VIP scores (B) of lipids of Cymbopogon distans leaves were chosen to compare the influences of water additions across two seasons (dry and wet). Note: FA1, FA2, FA3 and FA4 indicates 7,10-heptadecadiynoic acid, 8E-heptadecenedioic acid, 2E,4E,6E,11Z-octadecatetraenoic acid and 2,2-difluoro-hexadecanoic acid, respectively; PR1, PR2, PR3 and PR4 indicates etretinate, gibberellin A53 aldehyde, gibberellin A3 O-β-D-glucoside and dolichyl-4 phosphate, respectively; ST1 and ST2 indicate 1α,17α,21-trihydroxy-20-oxo-22,23,24,25,26,27-hexanorvitamin and cannogenin; PS1 and PS2 indicates PS(22:4(7Z,10Z,13Z,16Z)/17:1(9Z)) and PS(22:2(13Z,16Z)/15:0); PE1 and PE2 indicates PE(18:3(6Z,9Z,12Z)/0:0) and PE(16:0/18:3(6Z,9Z,12Z)); SP1 (t18:0/h26:0).
Figure 7. PLS-DA scores plot (A) and VIP scores (B) of lipids of Cymbopogon distans leaves were chosen to compare the influences of water additions across two seasons (dry and wet). Note: FA1, FA2, FA3 and FA4 indicates 7,10-heptadecadiynoic acid, 8E-heptadecenedioic acid, 2E,4E,6E,11Z-octadecatetraenoic acid and 2,2-difluoro-hexadecanoic acid, respectively; PR1, PR2, PR3 and PR4 indicates etretinate, gibberellin A53 aldehyde, gibberellin A3 O-β-D-glucoside and dolichyl-4 phosphate, respectively; ST1 and ST2 indicate 1α,17α,21-trihydroxy-20-oxo-22,23,24,25,26,27-hexanorvitamin and cannogenin; PS1 and PS2 indicates PS(22:4(7Z,10Z,13Z,16Z)/17:1(9Z)) and PS(22:2(13Z,16Z)/15:0); PE1 and PE2 indicates PE(18:3(6Z,9Z,12Z)/0:0) and PE(16:0/18:3(6Z,9Z,12Z)); SP1 (t18:0/h26:0).
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Figure 8. Contents of total lipids in Cymbopogon distans leaves between two seasons and three water adding treatments. Vertical bars above columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments during a specific season. A star indicates significant difference (p < 0.05) when comparing seasons at a particular water treatment.
Figure 8. Contents of total lipids in Cymbopogon distans leaves between two seasons and three water adding treatments. Vertical bars above columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments during a specific season. A star indicates significant difference (p < 0.05) when comparing seasons at a particular water treatment.
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Figure 9. Percentages of 16 classes of lipid in Cymbopogon distans leaves between two seasons and three treatments.
Figure 9. Percentages of 16 classes of lipid in Cymbopogon distans leaves between two seasons and three treatments.
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Figure 10. Contents of 16 lipid classes, ST (A), PE (B), PS (C), PA (D), PC (E), MGDG (F), SQDG (G), PR (H), FA (I), DG (J), TG (K), PI (L), SL (M), MG (N), PG (O), and SP (P), in Cymbopogon distans leaves between two seasons and three treatments. Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate a significant difference (p < 0.05) when comparing different treatments during a specific season. A star indicates a significant difference (p < 0.05) when comparing seasons at a particular water treatment. Note: DG: Diacylglycerols; FA: Fatty Acyls; MG: Monoradylglycerols; MGDG: Monogalactosyldiacylglycerols; PA: Phosphatidic acid; PC: Phosphatidylcholines; PE: Phosphatidylethanolamines; PG: Phosphatidylglycerols; PI: Phosphatidylinositols; PR: Prenol Lipids; PS: Phosphatidylserines; SL: Saccarolipids; SP: Sphingolipids; SQDG: Sulfoquinovosyldiacylglycerols; ST: Sterol Lipids; TG: Triacylglycerols.
Figure 10. Contents of 16 lipid classes, ST (A), PE (B), PS (C), PA (D), PC (E), MGDG (F), SQDG (G), PR (H), FA (I), DG (J), TG (K), PI (L), SL (M), MG (N), PG (O), and SP (P), in Cymbopogon distans leaves between two seasons and three treatments. Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate a significant difference (p < 0.05) when comparing different treatments during a specific season. A star indicates a significant difference (p < 0.05) when comparing seasons at a particular water treatment. Note: DG: Diacylglycerols; FA: Fatty Acyls; MG: Monoradylglycerols; MGDG: Monogalactosyldiacylglycerols; PA: Phosphatidic acid; PC: Phosphatidylcholines; PE: Phosphatidylethanolamines; PG: Phosphatidylglycerols; PI: Phosphatidylinositols; PR: Prenol Lipids; PS: Phosphatidylserines; SL: Saccarolipids; SP: Sphingolipids; SQDG: Sulfoquinovosyldiacylglycerols; ST: Sterol Lipids; TG: Triacylglycerols.
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Figure 11. The contents of important lipids, including four FA (A–D), four PR (E–H), two ST (I,J), two PS (K,L), two PE (M,N) and one SP, in Cymbopogon distans leaves between two seasons and three treatments. Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments during a specific season. A star indicates a significant difference (p < 0.05) when comparing seasons at a particular water treatment. Note: (A) 7,10-heptadecadiynoic acid (FA1), (B) 8E-heptadecenedioic acid (FA2), (C) 2E,4E,6E,11Z-octadecatetraenoic acid (FA3), (D) 2,2-difluoro-hexadecanoic acid (FA4), (E) etretinate (PR1), (F) gibberellin A53 aldehyde (PR2), (G) gibberellin A3 O-β-D-glucoside (PR3), (H) dolichyl-4 phosphate (PR4), (I) 1α,17α,21-trihydroxy-20-oxo-22,23,24,25,26,27-hexanorvitamin D3 (ST1), (J) cannogenin (ST2), (K) PS(22:4(7Z,10Z,13Z,16Z)/17:1(9Z)) (PS1), (L) PS(22:2(13Z,16Z)/15:0) (PS2), (M) PE(18:3(6Z,9Z,12Z)/0:0) (PE1), (N) PE(16:0/18:3(6Z,9Z,12Z)) (PE2), and (O) cer(t18:0/h26:0) (SP1).
Figure 11. The contents of important lipids, including four FA (A–D), four PR (E–H), two ST (I,J), two PS (K,L), two PE (M,N) and one SP, in Cymbopogon distans leaves between two seasons and three treatments. Vertical bars above the columns indicate the SE of each mean. Columns marked with lower-case letters indicate significant differences (p < 0.05) when comparing different treatments during a specific season. A star indicates a significant difference (p < 0.05) when comparing seasons at a particular water treatment. Note: (A) 7,10-heptadecadiynoic acid (FA1), (B) 8E-heptadecenedioic acid (FA2), (C) 2E,4E,6E,11Z-octadecatetraenoic acid (FA3), (D) 2,2-difluoro-hexadecanoic acid (FA4), (E) etretinate (PR1), (F) gibberellin A53 aldehyde (PR2), (G) gibberellin A3 O-β-D-glucoside (PR3), (H) dolichyl-4 phosphate (PR4), (I) 1α,17α,21-trihydroxy-20-oxo-22,23,24,25,26,27-hexanorvitamin D3 (ST1), (J) cannogenin (ST2), (K) PS(22:4(7Z,10Z,13Z,16Z)/17:1(9Z)) (PS1), (L) PS(22:2(13Z,16Z)/15:0) (PS2), (M) PE(18:3(6Z,9Z,12Z)/0:0) (PE1), (N) PE(16:0/18:3(6Z,9Z,12Z)) (PE2), and (O) cer(t18:0/h26:0) (SP1).
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Huang, A.; Jing, H.; Umair, M.; Du, H. Response of Metabolites in Cymbopogon distans Leaves to Water Addition in Karst Areas during Different Seasons. Horticulturae 2024, 10, 16. https://doi.org/10.3390/horticulturae10010016

AMA Style

Huang A, Jing H, Umair M, Du H. Response of Metabolites in Cymbopogon distans Leaves to Water Addition in Karst Areas during Different Seasons. Horticulturae. 2024; 10(1):16. https://doi.org/10.3390/horticulturae10010016

Chicago/Turabian Style

Huang, Aiwei, Hongxia Jing, Muhammad Umair, and Hongmei Du. 2024. "Response of Metabolites in Cymbopogon distans Leaves to Water Addition in Karst Areas during Different Seasons" Horticulturae 10, no. 1: 16. https://doi.org/10.3390/horticulturae10010016

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