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Article

The Utilization Value of Condensate Water from the Drying Process of Lonicera japonica via Metabolomics Analysis

by
Da Li
1,†,
Jiaqi Zhang
1,2,†,
Yining Sun
1,
Chongchong Chai
2,
Fengzhong Wang
2,3,
Bei Fan
2,3,
Long Li
2,
Shuqi Gao
3,
Hui Wang
1,
Chunmei Yang
1,* and
Jing Sun
2,3,*
1
School of Biology and Medicine, Beijing City University, Beijing 100094, China
2
Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-Products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
3
National Center of Technology Innovation for Comprehensive Utilization of Saline-Alkali Land, Dongying 257345, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Metabolites 2025, 15(9), 569; https://doi.org/10.3390/metabo15090569
Submission received: 2 July 2025 / Revised: 7 August 2025 / Accepted: 15 August 2025 / Published: 25 August 2025
(This article belongs to the Section Plant Metabolism)
Browse Figures
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Abstract

Background: Lonicerae japonicae flos (LJF), a traditional food and medicine with a history spanning thousands of years, undergoes drying as a critical processing step in modern applications after regular processing. While the by-products of this process are typically discarded as waste, the potential value of LJF condensate water (JYHC) remains largely unexplored. To address this gap and investigate its potential utilization, this study conducted widely targeted metabolome and volatile metabolomics profiling analyses of ‘JYHC’. Methods: This study analyzed the differential metabolites of ‘JYHC’ and dried Lonicerae japonicae flos (JYHG) based on widely targeted metabolomics using UPLC-MS/MS. Additionally, the metabolic differences between fresh Lonicerae japonicae flos (JYHX) and ‘JYHC’ based on GC-MS volatile metabolomics were comprehensively analyzed. Results: A total of 1651 secondary metabolites and 909 volatile metabolites were identified in this study. Among these, flavonoids and terpenoids were the predominant secondary metabolites, while esters and terpenoids dominated the volatile fraction. Further comparison of the ‘JYHC’ and ‘JYHG’ groups revealed that 58 differential metabolites with potential biological activities were significantly up-regulated, with the types being terpenoids, phenolic acids, and alkaloids, which included nootkatone, mandelic acid, sochlorogenic acid B, allantoin, etc. Notably, a total of 186 novel compounds were detected in ‘JYHC’ that had not been previously reported in LJF such as isoborneol, hinokitiol, agarospirol, 5-hydroxymethylfurfural, α-cadinol, etc. Conclusions: This study’s findings highlight the metabolic diversity of ‘JYHC’, offering new theoretical insights into the study of LJF and its by-products. Moreover, this research provides valuable evidence supporting the potential utilization of drying by-products from LJF processing, paving the way for further exploration of their pharmaceutical and industrial applications.

1. Introduction

Lonicerae japonicae flos (LJF), which originates from the dried buds of Lonicera japonica Thunb., is a member of the Caprifoliaceae family and is native to East Asia, including China, Korea, and Japan. This plant is sun-preferring and cold-hardy, and is now widely distributed across temperate to subtropical regions. Lonicera japonica Thunb. is a semi-evergreen climber; its branchlets, petioles, and peduncles are covered with yellowish-brown stiff hairs or soft pubescence. Its leaves are papery and predominantly ovate or lanceolate in shape. Its fragrant flowers are paired and form axillary structures at branchlet apices. LJF has been extensively utilized in Traditional Chinese Medicine (TCM) for thousands of years [1,2]. In China, it is used as healthy food, as well as in cosmetics and soft drinks, due to its pleasant fragrance and high safety profile [3]. Recent research has indicated that LJF is composed of essential oils, organic acids, flavonoids, and triterpenoids, which demonstrate various effects such as antimicrobial, anti-inflammatory, antiviral, and immune-regulatory properties. Its clinical applications are widely recognized [4,5,6,7].
Drying is considered a crucial step in the processing of LJF (Figure 1). Drying effectively extends the shelf life of LJF and improves the stability and concentration of its active ingredients. However, its aromatic components are often lost or chemically transformed during the drying process [8,9]. At the same time, condensate water (JYHC) is usually generated. It is still unclear whether this by-product contains bioactive compounds. It is typically discarded as waste, leading to significant environmental pollution and a substantial waste of resources.
In recent years, the valorization of food industry by-products and agricultural wastes has been the focus of research worldwide [10,11]. Efforts have been made to explore the potential applications of these by-products for energy and resource conservation [12,13,14,15]. Metabolomics has been identified as a qualitative and quantitative analysis of all metabolites from different organisms, samples, or tissues. It is widely used in biomedical, botanical, and food science research [16,17,18,19,20,21]. A widely targeted metabolomics analysis is an innovative method that merges the benefits of both non-targeted and targeted metabolomics. This technique has been extensively applied in the analysis of plant metabolites across different species, including Zingiberis rhizoma and its processed forms, as well as citronella before and after drying [22,23].
This research utilized UPLC-ESI-MS/MS-based broad-spectrum metabolome profiling to identify differential metabolites in ‘JYHC’ and ‘JYHG’ (dry Lonicerae japonicae flos). In addition, a comprehensive analysis of the metabolic differences between ‘JYHX’ (Fresh Lonicerae japonicae flos) and ‘JYHC’ was conducted using GC-MS-based volatile metabolomics. The differential metabolites were analyzed by utilizing multivariate methods for statistical analysis. The findings of this study can be used as a new theoretical reference for the study of LJF and its by-products. Meanwhile, it also provides valuable insights into the potential utilization of the by-products generated during the drying process of LJF.

2. Materials and Methods

2.1. Experimental Materials

In this study, fresh Lonicerae japonicae flos (JYHX) was collected on 27 June 2024 in Dakuang Town, Laiyang City, Yantai, Shandong Province, China, and samples were annotated as JYHX (JYH-202406) by Professor Fengzhong Wang of the Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, China. The drying process of LJF was carried out at Yantai Riga Energy Saving Technology Co., Ltd. (Yantai, China), which mainly produces drying equipment; JYHC is considered a by-product of this process. The drying process used the whole fresh LJF plant (Figure 1).

2.2. Sample Preparation for Metabolite Extraction

2.2.1. Preparation of ‘JYHC’ Test Material

We removed the ‘JYHC’ sample from an −80 °C freezer, and thawed it on ice. We vortexed the sample for 30 s. Then, 18 mL of the sample was transferred into a designated centrifuge tube, which was frozen at −80 °C overnight in a refrigerator, before proceeding with vacuum freeze-drying. After freeze-drying, 300 μL of 70% methanol extract containing an internal standard (2-chlorophenylalanine, ≥98% purity, J&K Scientific, Shanghai, China) was added at a concentration ratio of 60 times. The mixture was vortexed for 15 min, and then subjected to ultrasound in an ice water bath (KQ5200E, Beijing, China) for 10 min. The solution was centrifuged at 12,000 r/min and 4 °C (5424R, Eppendorf, Shanghai, China) for 3 min. The supernatant was collected, filtered through a microporous membrane (0.22 μm), and stored in an injection bottle.

2.2.2. Preparation of ‘JYHG’ Test Material

The ‘JYHG’ sample was vacuum freeze-dried and subsequently ground into a fine powder. An amount of 50 mg of the powdered sample was weighed and added to 1200 μL of 70% methanol extract containing the internal standard. The mixture was vortexed for 15 min, and then left in a refrigerator at 20 °C for 30 min. The solution was centrifuged at 12,000 r/min and 4 °C for 3 min. The supernatant was collected, filtered through a microporous membrane (0.22 μm), and stored in an injection bottle.

2.2.3. Preparation of ‘JYHX’ Test Material

The collected ‘JYHX’ was pulverized into a fine powder using liquid nitrogen. A total of 500 mg of the powder was added to a 20 mL headspace vial containing a saturated NaCl solution (Agilent, Waltham, MA, USA) for headspace solid-phase microextraction (HS-SPME).

2.3. Secondary Metabolites Analysis by UPLC-ESI-MS/MS

An ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) system equipped with a triple quadrupole-linear ion trap (QTRAP) mass analyzer was employed for the analysis of secondary metabolites. Chromatographic separation was achieved using an Agilent SB-C18 column (1.8 μm, 2.1 mm × 100 mm) at 40 °C with a flow rate of 0.35 mL/min and an injection volume of 2 μL. The mobile phases consisted of 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B), and the gradient program was set as follows: linear decrease from 95% A to 5% A within 0–9 min and maintained for 1 min; followed by recovery to the initial ratio (95% A) within 1.1 min and equilibration for 2.9 min. Mass detection was performed using electrospray ionization (ESI) operated in both positive and negative modes.
Mass spectrometry was performed using an electrospray ionization (ESI) source with the following parameter settings: ion source temperature of 500 °C, spray voltage of +5500 V/−4500 V (positive/negative ion mode), nebulizing gas (GSI), auxiliary gas (GSII) and curtain gas (CUR) pressures were set to 50, 60 and 25 psi, respectively. Collision-induced dissociation (CAD) was operated in high-sensitivity mode. Multi-reaction monitoring (MRM) was employed for the detection of target metabolites. The dissociation potential (DP) and collision energy (CE) were individually optimized for each transition. All MRM transitions were dynamically scheduled according to the expected retention time of each analyte to maximize detection sensitivity.

2.4. Volatile Analysis by GC-MS

Volatile organic compounds (VOCs) were analyzed using an Agilent 8890 gas chromatography system coupled to a 7000D mass spectrometry (GC-MS, Agilent Technologies, Santa Clara, CA, USA). Sample injection was performed in splitless mode at an inlet temperature of 250 °C. After a 5 min solvent delay, the separation was carried out on a DB-5MS capillary column (30 m × 0.25 mm × 0.25 μm, 5% phenyl-polymethylsiloxane stationary phase) using helium as the carrier gas at a constant flow rate of 1.2 mL/min.
The chromatographic separation was carried out using the following temperature program: initial temperature held at 40 °C for 3.5 min, and then increased at 10 °C/min. The chromatographic separation was performed with a programmed temperature ramp: initial temperature of 40 °C for 3.5 min, ramp to 100 °C at 10 °C/min, ramp to 180 °C at 7 °C/min, and finally, ramp to 280 °C at 25 °C/min and held for 5 min. Mass spectrometric detection was conducted in electron bombardment ionization (EI) mode at 70 eV. The temperatures of the ion source, quadrupole, and transmission line were set at 230 °C, 150 °C, and 280 °C, respectively. Data acquisition was performed in selective ion monitoring (SIM) mode to enhance the detection accuracy of the target compounds.

2.5. Multivariate Statistical Analysis

To investigate the accumulation patterns of germplasm-specific metabolites, multivariate statistical analysis was applied to the metabolomic dataset. PCA and OPLS-DA were employed for metabolic profiling and pattern recognition. The distinct accumulation patterns of metabolites were visualized through heatmaps. All these analyses were performed in the Metware Cloud online platform. Differential metabolites were screened using the following criteria: FC ≥ 2 or ≤0.5, VIP ≥ 1, and t-test p-value ≤ 0.05 (MetaboAnalyst 5.0 platform).

2.6. KEGG Pathway Analysis

The KEGG pathway database was utilized to identify and show differential metabolites.

3. Results

3.1. Overview of the Metabolites in ‘JYHC’

This study integrated targeted and volatile metabolomics to comprehensively profile the secondary metabolites in ‘JYHC’. A total of 1651 metabolites were detected by comprehensive targeted metabolomics and further classified into eight categories (Figure 2A). Flavonoids represented the most abundant class, with a content that is 1.4 times that of terpenoids, 1.7–1.8 times that of alkaloids/phenolic acids, and 3.6 times that of lignans/coumarins. As secondary dominant components, terpenoids have an advantage of 1.2–1.3 times over alkaloids and phenolic acids. Collectively, flavonoids and terpenoids constituted the dominant secondary metabolites in ‘JYHC’, accounting for 44.88% of the total detected metabolites.
Volatile metabolomics profiling identified 909 metabolites, which were categorized into 14 categories (Figure 2B). It can be seen that the main volatile components in ‘JYHC’ are esters and terpenoids, collectively accounting for 37.29% of the total. Their relative abundances were approximately 1.7- and 1.6- fold higher than that of ketones, 1.8- and 1.7-fold greater than heterocyclic compounds, and 2.1- and 2.0-fold above those of alcohols, respectively. Compared to hydrocarbons, esters and terpenoids were 3.0 and 2.9 times more abundant, whereas trace components such as halogenated hydrocarbons and nitrogenous compounds exhibited substantially lower levels—only 1/26 to 1/138 of the abundance of esters.

3.2. PCA and OPLS-DA Analysis

PCA analysis was performed on the secondary metabolites of ‘JYHG’ versus (vs.) ‘JYHC’ (Figure 3A) and the volatile metabolites of ‘JYHX’ vs. ‘JYHC’ (Figure 3B), respectively. The ‘JYHG’ vs. ‘JYHC’ and ‘JYHX’ vs. ‘JYHC’ groups exhibited distinct separation on both PC1 and PC2, indicating significant differences in metabolite composition between ‘JYHC’ and ‘JYHG’, as well as between ‘JYHC’ and ‘JYHX’.
Pairwise comparative OPLS-DA revealed significant metabolic differences between ‘JYHC’ and ‘JYHG’ (R2X = 0.956), as well as between ‘JYHC’ and ‘JYHX’ (R2X = 0.962). The R2Y and Q2 values of all models were close to 1 (Q2 > 0.9), demonstrating that the models had excellent stability and predictive ability. As shown in Figure 3C,D, the scoring plots clearly showed the apparent separation of ‘JYHC’ from the other two sample groups, supporting the robustness of the model and providing a solid basis for subsequent screening of differential metabolites using variable importance in projection (VIP) analysis.

3.3. Differential Metabolites Screening

Differential metabolites were selected based on a variable importance in projection (VIP) value ≥ 1 from the OPLS-DA model, combined with univariate statistical criteria including a fold change ≥ 2 or ≤0.5 and a p-value ≤ 0.05. The results of this multi-criteria screening are visually summarized in volcano plots, which highlight metabolites meeting all these thresholds. In total, 1355 metabolites showed significant differences between ‘JYHC’ and ‘JYHG’, with 159 being upregulated and 1196 downregulated (Figure 4A); 984 volatile metabolites were significantly altered ‘JYHC’ and ‘JYHX’ (Figure 4B, 586 upregulated, 398 downregulated). Focusing on of the top 20 differential metabolites (VIP ≥ 1) between ‘JYHC’ and ‘JYHG’ groups, allantoin was the only metabolite showing significant accumulation, while the other 19 secondary metabolites showed pronounced downregulation. These downregulated metabolites primarily consisted of phenolic acids, terpenoids, and alkaloids (Figure 4C). Among the top 20 differential volatile metabolites between the ‘JYHC’ and ‘JYHX’, six metabolites (octadecane, piperonyl isobutyrate, (E)-3-methylpenta-1,3-diene-5-ol, 3-(1-methyl-2-propenyl)-1,5-cyclooctadiene, β-eudesmol, and tetrahydro-2H-pyran-2-one) showed significant increases, while the remaining 14 compounds exhibited significant decreases (Figure 4D).
Based on the VIP values, the top 50 differential secondary metabolites and volatile differential metabolites were selected and visualized by a heat map (Figure 5A,B). Heat map analysis results indicated that there was a significant difference in the abundance of these compounds between the ‘JYHC’ vs. ‘JYHG’ and ‘JYHC’ vs. ‘JYHX’ groups.
The results demonstrated that the metabolite profiles of the two sample groups formed two main clusters of metabolites, indicating significant differences in the metabolites between the groups. Combined with a literature search, 58 potentially biologically active up-regulated differential metabolites were screened in the ‘JYHC’ and ‘JYHG’ group (Table 1). Terpenoids, phenolic acids, and alkaloids were identified as the predominant classes of upregulated metabolites in ‘JYHC’.
Furthermore, volatile metabolomic analysis revealed the presence of 186 different components in ‘JYHC’ that were absent in ‘JYHX’ and have not been previously reported in LJF (Table 2). These metabolites may be produced under the specific conditions or processing of ‘JYHC’ and could have potential functional significance. The newly identified volatile components are mainly terpenoids, esters, and alcohols. Among them, terpenoids account for the highest proportion (25.27%). The 10 volatile metabolites with putative bioactivities were selected for further comparison analysis (Figure 6).

3.4. KEGG Pathway Analysis

To systematically investigate the biological implications of the observed metabolic changes, KEGG pathway enrichment analysis was performed to integrate the differential metabolites into functional pathways. In the ‘JYHC’ vs. ‘JYHG’ comparison, differential metabolites were annotated and enriched in 56 KEGG pathways. Among these, “flavonoid biosynthesis” and “flavone and flavonol biosynthesis” were significantly enriched (p < 0.05) (Figure 7A). In contrast, no pathways showed significant enrichment in the ‘JYHC’ vs. ‘JYHX’ comparison. Nevertheless, several pathways, including “biosynthesis of various plant secondary metabolites” and “biosynthesis of secondary metabolites”, exhibited relatively high enrichment factors, suggesting potential biological relevance.

4. Discussion

Thermal drying is a conventional step in the processing of LJF, which may lead to the loss of bioactive constituents through condensation. To evaluate whether the condensate ‘JYHC’ possesses potential utility, this study analyzed the secondary metabolites and volatile components in ‘JYHC’ using metabolomics approaches.
In this study, the UPLC-MS/MS-based widely targeted metabolome was employed to profile the metabolites of ‘JYHC’ and ‘JYHG’. A total of 1651 secondary metabolites were detected, including flavonoids, terpenoids, alkaloids, phenolic acids, lignans, coumarins, quinones, tannins, etc. Flavonoids and terpenoids were identified as the predominant secondary metabolites in ‘JYHC’ (Figure 2A). Flavonoids and terpenoids are widely involved in biological defence and have important pharmacological roles in human health, including anti-inflammatory, antimicrobial, and antioxidant properties [24,25,26,27,28,29,30].
A comprehensive comparative analysis and identification of metabolic differences between ‘JYHC’ and ‘JYHX’ were performed using GC-MS. A total of 909 metabolites, including esters, terpenoids, ketones, heterocyclic compounds, alcohols, hydrocarbons, etc. (Figure 2B). Esters and terpenoids were established as the dominant volatile metabolites in ‘JYHC’. Terpenes are widely found in plant essential oils and have anthelmintic, antibacterial, and anti-inflammatory activities [31,32]. Esters are closely related to the plant aromas and are widely used in the food, cosmetic, and flavor industries [33,34]. The composition and content of volatile metabolites are significantly affected by drying methods. Sun drying is a traditional method of drying LJF. Research has found that, while sun-dried Lonicerae Flos exhibits a greater variety of volatile compounds, its overall content is lower and it primarily contains hydrocarbons [35]. This outcome may be attributed to prolonged exposure to sunlight and air, which increases susceptibility to oxidative and photolytic degradation. Currently, convective drying methods are the most widely used in the industrial production of LJF, including programmed temperature oven drying, heat-pump drying, and hot-air drying [36]. Research indicates that Lonicerae flos dried via programmed temperature oven drying contains higher levels of esters and terpenes compared to other high-temperature drying methods [35]. Heat-pump drying is an advanced drying technology characterized by low temperature, mild conditions, and stable operation. This method is particularly suitable for preserving temperature-sensitive volatile components, such as short-chain fatty acids and terpenes [37].
To elucidate the functional significance of the altered metabolome, this study focused on the upregulated metabolites. Based on extensive literature and database mining, 58 potentially biologically active upregulated differential metabolites were screened in the ‘JYHC’ and ‘JYHG’ group (Table 1). Terpenoids, phenolic acids, and alkaloids are the main upregulated differential metabolites in ‘JYHC’. Terpenoids include nootkatone, catalpol, and isosteviol, etc. Nootkatone is an aromatic sesquiterpenoid with insecticidal and anti-inflammatory activities [38,39,40]. It is often used as a natural insecticide [41]. Isosteviol has been served as a cardiomyocyte protector [42,43,44]. Catalpol exhibits cardiovascular protective, neuroprotective, and hepatoprotective effects that were linked to NF-κB/NLRP3, PI3K/Akt, VEGF-A/KDR, and Jak-Stat pathways [45,46,47,48,49]. Among them, phenolic acid components include mandelic acid, vanillic acid, aloesone, isochlorogenic acid B, etc. Studies have shown that they possess biological activities such as anti-inflammatory and antibacterial effects [50,51,52]. Mandelic acid is widely used as a vital component in antiseptics and cosmetics due to its excellent antibacterial and anti-inflammatory activities [53]. Isochlorogenic acid B is recognized as a key active component in LJF. It exhibits significant blood sugar-lowering effects [54]. The alkaloids mainly include allantoin, betaine, solavetivone, aurantiamide, and stachydrine. Allantoin has activities such as antibacterial effects and skin damage repair, making it used in the development of cosmetic products [55,56,57,58]. Evidence has shown that betaine has beneficial actions in several human diseases and has anti-inflammatory functions in many diseases [59,60,61]. Stachydrine is a compound with anti-inflammatory activity, reducing inflammation through the P65, JAK2/STAT3, and NF-κB signaling pathways [62,63,64].
Additionally, 186 previously unreported compounds were identified in ‘JYHC’ that have not been documented in LJF, many of which demonstrate insecticidal, antimicrobial, and anti-inflammatory activities (Table 2). Terpenoids accounted for the highest percentage of newly identified volatile components. Terpenoids generally have some antibacterial and anti-inflammatory activity; for example, isoborneol and hinokitiol have good antimicrobial activity and are used in the application and development of natural antimicrobial materials [65,66,67]. Agarospirol, α-cadinol have been proven to be the main anti-inflammatory active ingredient in natural plant essential oils [68,69,70]. Curcumin has significant anti-inflammatory activity and can treat osteoarthritis by inhibiting NF-κB and MAPK pathways [71]. Moreover, 5-Hydroxymethylfurfural is a common reaction product during heat processing with good anti-inflammatory activity [72,73]. Esculetin is a natural dihydroxy coumarin, which has been shown to prevent cell growth in a variety of cancers [74,75,76]. Palmitoleic acid has been shown to regulate the gut microbiota and promote intestinal homeostasis [77]. However, it should be noted that this study is limited by the lack of absolute quantification for some differential metabolites. Future work will focus on validating these results through the construction of a more comprehensive standard compound library.

5. Conclusions

This research utilized UPLC-ESI-MS/MS-based widely targeted metabolomics method and GC-MS-based volatile metabolomics to comprehensively profile the metabolites in ‘JYHC’. The results shown that ‘JYHC’ is abundant in diverse secondary and volatile metabolites. Flavonoids and terpenoids were identified as the predominant secondary metabolites, whereas esters and terpenoids dominated the volatile fraction. Comparative metabolomic analysis revealed 58 upregulated differential secondary metabolites, primarily consisting of terpenoids, phenolic acids, and alkaloids. Additionally, 186 previously unreported compounds were identified in LJF, including isoborneol, hi-nokitiol, Agarospirol, and α-cadinol, etc. These metabolites are suggested to possess potential biological activities, such as anti-inflammatory and antimicrobial effects.
In the future, ‘JYHC’ shows potential for application as a functional additive with antibacterial and anti-inflammatory properties in cosmetics, or as a plant-derived biopesticide in green agriculture. The comprehensive utilization of ‘JYHC’ could enhance the economic value of LJF, while simultaneously reducing resource waste and wastewater pollution associated with its traditional processing. This approach aligns closely with the principles of green and sustainable development.

Author Contributions

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

Funding

This research was funded by the 2024 Beijing City University fund, grant number KYTD202401. The 2024–2026 Young Talent Lifting Program of Beijing City University, grant number TJ202402. The Beijing City University Graduate Student Research and Innovation Programme, grant number Yjscx202438. The Key R&D Program of Shandong Province, grant number 2024SFGC0401. The Mount Taishan Scholar Young Expert. The Hebei Province major scientific and technological achievements transformation project, grant number 22287101Z.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors would like to thank Wuhan Metavir Biotechnology Co., Ltd. (Wuhan, China) for their help with metabolomics analysis. In addition, the authors would like to thank Yantai Ruiga Energy Saving Technology Co., Ltd. (Shandong, China) for providing the LJF drying and recycling equipment, along with their staff, for their valuable technical support.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
LJFLonicerae japonicae flos
JYHCCondensate water during the drying of Lonicerae japonicae flos
JYHXFresh Lonicerae japonicae flos
JYHGDry Lonicerae japonicae flos
UPLC-MS/MSUltra-Performance Liquid Chromatography-Electrospray Ionization-Tandem Mass Spectrometry
GC-MSGas Chromatography-Mass Spectrometry
PCAPrincipal component analysis
OPLS-DAOrthogonal partial least-squares discrimination analysis
VIPVariable importance in projection
FCFold Change
KEGGKyoto Encyclopedia of Genes and Genomes

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Metabolites 15 00569 g001
Figure 1. Lonicerae japonicae flos drying process flowchart.
Figure 1. Lonicerae japonicae flos drying process flowchart.
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Figure 2. Classification of the metabolic profiles in ‘JYHC’. (A): the major secondary metabolites in ‘JYHC’ (B): volatile metabolomics in ‘JYHC’.
Figure 2. Classification of the metabolic profiles in ‘JYHC’. (A): the major secondary metabolites in ‘JYHC’ (B): volatile metabolomics in ‘JYHC’.
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Figure 3. Principal component analysis (PCA) and score plots generated from orthogonal partial least squares discriminant analysis (OPLS-DA) of ‘JYHC’ compared with ‘JYHX’/‘JYHG’ (A): PCA score plot in ‘JYHC’ vs. ‘JYHG’ (B): PCA score plot in ‘JYHC’ vs. ‘JYHX’ (C): OPLS-DA score plot in ‘JYHC’ vs. ‘JYHG’ (D): OPLS-DA score plot in ‘JYHC’ vs. ‘JYHX’.
Figure 3. Principal component analysis (PCA) and score plots generated from orthogonal partial least squares discriminant analysis (OPLS-DA) of ‘JYHC’ compared with ‘JYHX’/‘JYHG’ (A): PCA score plot in ‘JYHC’ vs. ‘JYHG’ (B): PCA score plot in ‘JYHC’ vs. ‘JYHX’ (C): OPLS-DA score plot in ‘JYHC’ vs. ‘JYHG’ (D): OPLS-DA score plot in ‘JYHC’ vs. ‘JYHX’.
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Figure 4. Differential metabolite results of ‘JYHC’ compared with ‘JYHX’/‘JYHG’ (A): Volcano plots showing the levels of the differential metabolites in ‘JYHC’ vs. ‘JYHG’ (B): Volcano plots showing the levels of the differential metabolites in ‘JYHC’ vs. ‘JYHX’ (C): Variable importance in the project (VIP) plot of the top 20 differential secondary metabolites identified by OPLS-DA in ‘JYHC’ vs. ‘JYHG’ (D): Variable importance in the project (VIP) plot of the top 20 differential volatile secondary metabolites identified by OPLS-DA in ‘JYHC’ vs. ‘JYHX’.
Figure 4. Differential metabolite results of ‘JYHC’ compared with ‘JYHX’/‘JYHG’ (A): Volcano plots showing the levels of the differential metabolites in ‘JYHC’ vs. ‘JYHG’ (B): Volcano plots showing the levels of the differential metabolites in ‘JYHC’ vs. ‘JYHX’ (C): Variable importance in the project (VIP) plot of the top 20 differential secondary metabolites identified by OPLS-DA in ‘JYHC’ vs. ‘JYHG’ (D): Variable importance in the project (VIP) plot of the top 20 differential volatile secondary metabolites identified by OPLS-DA in ‘JYHC’ vs. ‘JYHX’.
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Figure 5. A heat map of top 50 differential metabolites. (A): Heatmap is based on relative abundance of differential metabolites in ‘JYHC’ vs. ‘JYHG’ (B): Heatmap is based on relative abundance of differential metabolites in ‘JYHC’ vs. ‘JYHX’.
Figure 5. A heat map of top 50 differential metabolites. (A): Heatmap is based on relative abundance of differential metabolites in ‘JYHC’ vs. ‘JYHG’ (B): Heatmap is based on relative abundance of differential metabolites in ‘JYHC’ vs. ‘JYHX’.
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Figure 6. Chemical structures and quantities of 10 significant differential volatile metabolites in ‘JYHX’ and ‘JYHC’. The value bars with asterisks denote statistically significant differences: ** p < 0.01; *** p < 0.001.
Figure 6. Chemical structures and quantities of 10 significant differential volatile metabolites in ‘JYHX’ and ‘JYHC’. The value bars with asterisks denote statistically significant differences: ** p < 0.01; *** p < 0.001.
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Figure 7. Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations and enrichment results. (A): ‘JYHC’ vs. ‘JYHG’ (B): ‘‘JYHC’’ vs. ‘JYHX’.
Figure 7. Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations and enrichment results. (A): ‘JYHC’ vs. ‘JYHG’ (B): ‘‘JYHC’’ vs. ‘JYHX’.
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Table 1. The information on differential metabolites in ‘JYHC’ and ‘JYHG’ groups.
Table 1. The information on differential metabolites in ‘JYHC’ and ‘JYHG’ groups.
NoClassCompoundsVIPp-ValueFC
1Terpenoids11-acetylamarolide1.03140.002930.3923
2Epikatonic acid1.03100.004319.8401
3Isosteviol1.03090.003714.8007
4Verbenalin; Cornin1.03010.00375.5482
5Ilicic acid1.03010.007416.6428
6Catalpol1.03000.013145.3682
7Curcumenone1.02840.016023.8513
87-Oxodehydroabietic acid1.02830.0037318.2749
9Monomelittoside1.02830.022232.3884
10Nootkatone1.02670.018915.8299
1126,27-Dihydroxylanosta-7,9(11),24-trien-3-one 1.02520.026513.4889
12Pisiferic acid1.01850.056117.3450
13Oleuropeic acid1.01140.02467.5915
14Phenolic acids4-Methylbenzoic acid1.03150.002025.1366
15Mandelic acid1.03140.004360.8357
163-Methylsalicylic Acid1.03120.004028.0947
17Aloesone1.03110.007171.9037
182-Methylbenzoic acid1.03090.006241.9502
19Phthalic acid1.02950.005833.8591
20Propyl 4-hydroxybenzoate1.02950.013929.7368
212-(Formylamino)benzoic acid1.02950.000314.3260
22Piperonylic acid1.02900.014123.0521
234-Hydroxybenzoic acid1.02550.00626.0468
24Methyl 4-hydroxybenzoate1.02270.004810.3296
25Vanillic acid1.02190.00103.1129
263-Hydroxy-4-methoxybenzoic acid; Isovanillic Acid1.01650.00684.3149
27Dihydroferulic Acid1.01320.027711.6718
28Benzoic acid1.00920.00834.8672
29Isochlorogenic acid B1.00030.07238.4708
30AlkaloidsAllantoin1.03190.000170.7447
312,4,6,6-Tetramethyl-3(6H)-pyridinone1.03170.0028872.5247
326,7-dimethoxy-2-methyl-3,4-dihydro-1h-isoquinoline1.03160.001418.2081
33Solavetivone1.03100.005333.1317
342(3H)-Benzothiazolone1.03080.007844.7512
35Hordenine1.03070.006022.9234
36Aurantiamide acetate1.03060.005518.0396
37Betaine1.03050.003015.7049
38Candicine1.03040.0247411.4936
39Aurantiamide1.03030.007520.8872
40Isatin1.03010.014879.3473
41Stachydrine1.02910.001917.9690
42Dopamine1.02860.00182.8634
43N-Caffeoylputrescine1.02830.014716.4331
44N-Methylserotonin1.02720.020917.4776
45Cinnamamide1.02610.036544.7934
46N-Isobutyl Decanamide1.01240.00967.1458
47N-Butylbenzenesulfonamide1.00430.010120.8540
483-Hydroxypyridine1.00090.03284.9551
49Quinones2,7-Dihydroxy-4-methoxyphenanthrene1.03150.001618.1935
50anthraquinone-2-aldehyde1.03090.004618.8696
51Hircinol(2,5-Dihydroxy-4-methoxy-9,10-dihydrophenanthrene)1.02820.017519.3460
522-Methyl-1,3,6-trihydroxy-9,10-anthraquinone1.02810.017423.5978
532,3-Dihydro-1,4-naphthoquinone1.00420.000647.7627
54Flavonoids6-prenylnaringenin1.02800.0377114.6009
55Homomangiferin1.02740.035150.2422
564′-Hydroxy-2,4,6-trimethoxydihydrochalcone; Loureirin B1.02740.027435.3058
57Herbacetin1.02640.035337.1602
58Chrysin1.00480.031444.3305
Table 2. The information on differential metabolites in ‘JYHC’ and ‘JYHX’ groups.
Table 2. The information on differential metabolites in ‘JYHC’ and ‘JYHX’ groups.
NoClassCompoundsVIPp-ValueFC
1Terpenoids1-((1S,3aR,4R,7S,7aS)-4-Hydroxy-7-isopropyl-4-methyloctahydro-1H-inden-1-yl)ethanone1.03070.0041inf
2Caryophyllenyl alcohol1.03010.0128inf
32,6-Dimethyl-2-trans-6-octadiene1.03090.0049inf
42,6-Octadiene, 2,6-dimethyl-1.03090.0049inf
5Agarospirol1.03110.0022inf
65,9-Undecadien-2-one, 6,10-dimethyl-1.00030.1224inf
7Naphthalene, 1,6-dimethyl-4-(1-methylethyl)-1.03040.0063inf
8Hexadecane, 2,6,10,14-tetramethyl-1.03120.0014inf
91,6,10-Dodecatriene, 7,11-dimethyl-3-methylene-1.02790.0597inf
10α-Cadinol1.03110.0022inf
11τ-Cadinol1.03110.0022inf
12cis-α-Bisabolene1.03100.0013inf
132,4,6-Cycloheptatrien-1-one, 2-hydroxy-4-(1-methylethyl)-1.03080.0058inf
141-Cyclohexene-1-carboxylic acid, 4-(1-methylethenyl)-1.03120.0014inf
15Dill ether1.03110.0007inf
167-epi-α-Eudesmol1.03120.0004inf
17τ-Muurolol1.03120.0008inf
18Cubenol1.03110.0022inf
193-Buten-2-one, 4-(2,2,6-trimethyl-7-oxabicyclo[4.1.0]hept-1-yl)-1.03110.0023inf
20Benzofuran, 4,5,6,7-tetrahydro-3,6-dimethyl-1.03120.0004inf
21Cyclohexane, 1-ethenyl-1-methyl-2,4-bis(1-methylethenyl)-, [1S-(1.alpha.,2.beta.,4.beta.)]-1.03030.0122inf
22Geranyl tiglate1.03060.0045inf
23β-sesquiphellandrene1.03040.0121inf
24(3S,3aR,3bR,4S,7R,7aR)-4-Isopropyl-3,7-dimethyloctahydro-1H-cyclopenta[1,3]cyclopropa[1,2]benzen-3-ol1.03010.0206inf
25Cyclohexene, 4-[(1E)-1,5-dimethyl-1,4-hexadien-1-yl]-1-methyl-1.03100.0013inf
26Citronellyl tiglate1.03120.0015inf
27cis-β-Farnesene1.02790.0597inf
28α-Farnesene1.03100.0040inf
29(E)-β-Farnesene1.02790.0597inf
302-Cyclohexen-1-ol, 2-methyl-5-(1-methylethenyl)-, cis-1.03120.0003inf
31Cyclohexanol, 5-methyl-2-(1-methylethyl)-, [1S-(1.alpha.,2.alpha.,5.beta.)]-1.03110.0013inf
324-Hexen-1-ol, 5-methyl-2-(1-methylethenyl)-, (R)-1.03120.0004inf
33Isoborneol1.03120.0003inf
34Bicyclo[2.2.1]heptane, 2-chloro-1,7,7-trimethyl-, (1R-endo)-1.02810.0223inf
35Cyclohexanol, 3-ethenyl-3-methyl-2-(1-methylethenyl)-6-(1-methylethyl)-, [1R-(1.alpha.,2.alpha.,3.beta.,6.alpha.)]-1.03040.0059inf
362-Furanmethanol, tetrahydro-.alpha.,.alpha.,5-trimethyl-5-(4-methyl-3-cyclohexen-1-yl)-, [2S-[2.alpha.,5.beta.(R*)]]-1.03010.0073inf
37Benzene, 1-(1,5-dimethyl-4-hexenyl)-4-methyl-1.03120.0013inf
382-Cyclohexen-1-ol, 3-methyl-6-(1-methylethyl)-1.01820.0940inf
39Curcumenol1.03090.0041inf
40β-Caryophyllene Alcohol1.03010.0128inf
41Benzene, 1-methyl-4-(1,2,2-trimethylcyclopentyl)-, (R)-1.03070.0062inf
42Salvial-4(14)-en-1-one1.03070.0074inf
43(R,1E,5E,9E)-1,5,9-Trimethyl-12-(prop-1-en-2-yl)cyclotetradeca-1,5,9-triene1.03010.0095inf
441,7-Dimethyl-4-(propan-2-ylidene)tricyclo[4.4.0.02,7]decan-3-one1.03110.0007inf
45(1R,5S)-1,8-Dimethyl-4-(propan-2-ylidene)spiro[4.5]dec-7-ene1.03080.0029inf
46Geranyl isobutyrate1.03000.0124inf
47Bicyclo[3.2.1]oct-2-ene, 3-methyl-4-methylene-1.03070.0152inf
48EsterPentanoic acid, pentyl ester1.03010.0108inf
49Hexanoic acid, 3-hexenyl ester1.03010.0147inf
502,6-Octadien-1-ol, 3,7-dimethyl-, propanoate, (Z)-1.00410.1340inf
51Lauryl acetate1.00290.1300inf
522,4-Hexadienoic acid, ethyl ester, (2E,4E)-1.01530.1108inf
535-Azulenemethanol, 1,2,3,4,5,6,7,8-octahydro-.alpha.,.alpha.,3,8-tetramethyl-, acetate, [3S-(3.alpha.,5.alpha.,8.alpha.)]-1.03090.0026inf
54Benzoic acid, 2-hydroxy-, phenylmethyl ester1.03110.0009inf
55Bicyclo[2.2.1]heptan-2-ol, 1,7,7-trimethyl-, formate, endo-1.03120.0013inf
56cis-3-Hexenyl isovalerate1.03120.0001inf
57Isobutyl isovalerate1.03060.0069inf
58Dodecanoic acid, ethyl ester1.00940.2222inf
59(S)-4-(1-Acetoxyallyl)phenyl acetate1.03110.0019inf
60Octanedioic acid, dimethyl ester1.03110.0035inf
612,6,10-Dodecatrienoic acid, 3,7,11-trimethyl-, methyl ester, (E,E)-1.03100.0057inf
62Hexadecanoic acid, ethyl ester1.03030.0096inf
63Hexyl tiglate1.03040.0135inf
64Hexanoic acid, 3,7-dimethyl-2,6-octadienyl ester, (E)-1.03120.0005inf
65Butanoic acid, 2-methyl-, 2-methylpropyl ester1.03060.0069inf
66Propanoic acid, 2-methyl-, heptyl ester1.03120.0001inf
67Undecanoic acid, ethyl ester1.03110.0019inf
68Isobornyl formate1.03120.0013inf
692(3H)-Furanone, 5-hexyldihydro-1.03100.0051inf
706-Octen-1-ol, 3,7-dimethyl-, propanoate1.03120.0032inf
71Butanoic acid, 3-hexenyl ester, (Z)-1.03120.0007inf
722(3H)-Furanone, dihydro-5-propyl-1.03120.0007inf
73Propanoic acid, pentyl ester1.03100.0030inf
74Pentadecanoic acid, 3-methylbutyl ester1.03120.0007inf
75(Z)-Hex-3-enyl (E)-2-methylbut-2-enoate1.03070.0043inf
76Butanedioic acid, diethyl ester1.03120.0007inf
77Butanoic acid, 2-methyl-, pentyl ester1.03010.0108inf
78.delta.-Nonalactone1.03110.0027inf
79(Z)-3-Butylidene-4,5-dihydroisobenzofuran-1(3H)-one1.03100.0021inf
80Propanoic acid, heptyl ester1.03110.0018inf
81Neryl butyrate1.03030.0126inf
82(3S,3aR)-3-Butyl-3a,4,5,6-tetrahydroisobenzofuran-1(3H)-one1.03120.0014inf
83Butanoic acid, butyl ester1.03060.0084inf
84Butanoic acid, 3-hexenyl ester, (E)-1.03120.0007inf
85Alcohol2-Nonen-1-ol, (Z)-1.03120.0001inf
863,7-Octadiene-2,6-diol, 2,6-dimethyl-1.02960.0281inf
87n-Pentadecanol1.03110.0044inf
881-Undecanol1.00550.2222inf
891,2-Benzenediol, 3,4,5,6-tetrachloro-1.03010.0070inf
90Benzenepropanol, 4-hydroxy-3-methoxy-1.03120.0004inf
91Benzenemethanol, 4-hydroxy-1.03120.0001inf
921-Tetradecanol1.03080.0046inf
932-Tridecen-1-ol, (E)-1.02230.1641inf
942-Nonen-1-ol, (E)-1.03120.0001inf
95Benzenemethanol, α-ethyl-1.03110.0023inf
965-Hexen-1-ol1.03120.0008inf
973-Nonanol1.03120.0002inf
981-Decanol1.03060.0110inf
991-Hexanol, 2-ethyl-1.03060.0061inf
1002-Nonanol1.03120.0003inf
101Bicyclo[3.1.1]hept-2-ene-2-ethanol, 6,6-dimethyl-1.02010.0666inf
1021-Naphthalenemethanol1.02660.0257inf
103n-Tridecan-1-ol1.02880.0195inf
1044a(2H)-Naphthalenol, octahydro-4,8a-dimethyl-,(4.alpha.,4a.alpha.,8a.beta.)-1.00650.1917inf
1052-Octanol1.02920.0259inf
1062-Octanol, (S)-1.02920.0259inf
107Cyclohexanol, 5-methyl-2-(1-methylethyl)-, (1.alpha.,2.beta.,5.beta.)-1.03110.0017inf
108(E)-2,6-Dimethylocta-3,7-diene-2,6-diol1.02960.0281inf
109Triethylene glycol1.03120.0001inf
110Ketone5,9-Undecadien-2-one, 6,10-dimethyl-, (E)-1.00030.1224inf
1115,9-Undecadien-2-one, 6,10-dimethyl-, (Z)-1.00030.1224inf
112Ethanone, 1-(2,4,6-trihydroxyphenyl)-1.02040.1003inf
1132-Piperidinone1.01610.2222inf
1149-Decen-2-one1.00220.2222inf
1152-Nonanone1.03120.0000inf
1162H-Pyran-2-one, tetrahydro-1.03120.0002inf
1174-(N-Nitroso-N-methylamino)-1-(3-pyridyl)-1-butanone1.03110.0023inf
1182-Cyclohexen-1-one, 4-(3-hydroxy-1-butenyl)-3,5,5-trimethyl-1.03120.0009inf
119Tropinone1.03120.0001inf
1207,9-Di-tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione1.03120.0006inf
121Acetophenone, 4′-hydroxy-1.03120.0004inf
1222H-1-Benzopyran-2-one, 4-hydroxy-1.03120.0005inf
1232,4-Imidazolidinedione, 1-methyl-1.03120.0001inf
1243-Butylisobenzofuran-1(3H)-one1.03120.0018inf
1252H-Pyran-2-one, 6-pentyl-1.03120.0009inf
126Furaneol1.03110.0045inf
1272-Undecanone1.03070.0038inf
1282-Butanone, 4-(4-methoxyphenyl)-1.03120.0001inf
1291-Pentanone, 1-(2-furanyl)-1.03120.0005inf
1303,5,9-Undecatrien-2-one, 6,10-dimethyl-1.02960.0136inf
131Ethanone, 2-hydroxy-1-phenyl-1.03120.0004inf
1321-Propanone, 1-(4-methoxyphenyl)-1.03080.0075inf
133Aldehyde2-octenal1.03060.0071inf
134(E)-Tetradec-2-enal1.03080.0038inf
1352-Undecenal, E-1.02910.0122inf
1362-Nonenal1.03120.0007inf
1372-Nonenal, (Z)-1.03120.0007inf
1385-Hydroxymethylfurfural1.03120.0001inf
139Pentadecanal-1.03110.0009inf
1403-p-Menthen-7-al1.03120.0005inf
1412-Undecenal1.02910.0122inf
142Isoneral1.03120.0003inf
1432,6-Nonadienal, (E,Z)-1.03120.0008inf
1442-Nonenal, (E)-1.03120.0007inf
145Tridecanal1.03100.0020inf
146cis-4-Decenal1.03100.0044inf
1472-Octenal, (E)-1.03060.0071inf
148Acid2-Octenoic acid, (E)-1.03080.0041inf
1492,3,4-Trihydroxybenzoic acid1.03020.0084inf
1502-Octenoic acid1.03080.0041inf
151Homovanillic acid1.03120.0009inf
152Benzenepropanoic acid, 4-hydroxy-1.03120.0010inf
153Propanoic acid, 3-(methylthio)-1.03110.0014inf
154Palmitoleic acid1.03090.0029inf
1554-Methyloctanoic acid1.03120.0002inf
156Benzeneacetic acid, α-hydroxy-, (R)-1.03120.0010inf
1573,7,11-Trimethyl-dodeca-2,6,10-trienoic acid1.03080.0070inf
158Heterocyclic compoundThiophene, 2-ethyl-1.03120.0010inf
1591,3,5-Triazine-2,4,6-triamine1.03100.0022inf
160Pyrazine, 2-ethyl-3,5-dimethyl-1.03120.0001inf
161Pyrazine, 3-ethyl-2,5-dimethyl-1.03120.0001inf
1625,6-Dihydro-5-methyluracil1.02940.0221inf
1631H-Pyrazole1.03100.0025inf
1642-n-Butyl furan1.03020.0063inf
165Esculetin1.03110.0023inf
1662,3-Dimethyl-5-ethylpyrazine1.03120.0001inf
1672-Acetyl-3-methylpyrazine1.03110.0022inf
1687-Oxabicyclo[4.1.0]heptane1.03120.0014inf
169Quinoline, 2,4-dimethyl-1.03120.0024inf
170Hydrocarbons1-Heptadecene1.02910.0207inf
171Dodecane1.03050.0117inf
172Fucoserratene1.03110.0023inf
173Hexadecane, 2-methyl-1.03050.0048inf
174Heptadecane, 7-methyl-1.03090.0021inf
175Heptadecane, 2-methyl-1.03120.0011inf
176Phenol2-Methoxy-5-methylphenol1.03110.0015inf
177trans-Isoeugenol1.03120.0006inf
178Phenol, 2-methoxy-4-(1-propenyl)-1.03120.0006inf
179Creosol1.03110.0015inf
180Phenol, 4-(3-hydroxy-1-propenyl)-2-methoxy-1.03120.0021inf
1811-Naphthalenol1.03090.0057inf
182EtherBenzene, 1,3-dimethoxy-1.03120.0005inf
183Benzene, 1,1′-[oxybis(methylene)]bis-1.03120.0007inf
1841,3-Benzodioxole, 4-methoxy-6-(2-propenyl)-1.03050.0200inf
185Asarone1.03110.0019inf
186Benzene, 1-ethenyl-4-methoxy-1.03120.0016inf
Column FC, ‘inf’ means infinity.
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Li, D.; Zhang, J.; Sun, Y.; Chai, C.; Wang, F.; Fan, B.; Li, L.; Gao, S.; Wang, H.; Yang, C.; et al. The Utilization Value of Condensate Water from the Drying Process of Lonicera japonica via Metabolomics Analysis. Metabolites 2025, 15, 569. https://doi.org/10.3390/metabo15090569

AMA Style

Li D, Zhang J, Sun Y, Chai C, Wang F, Fan B, Li L, Gao S, Wang H, Yang C, et al. The Utilization Value of Condensate Water from the Drying Process of Lonicera japonica via Metabolomics Analysis. Metabolites. 2025; 15(9):569. https://doi.org/10.3390/metabo15090569

Chicago/Turabian Style

Li, Da, Jiaqi Zhang, Yining Sun, Chongchong Chai, Fengzhong Wang, Bei Fan, Long Li, Shuqi Gao, Hui Wang, Chunmei Yang, and et al. 2025. "The Utilization Value of Condensate Water from the Drying Process of Lonicera japonica via Metabolomics Analysis" Metabolites 15, no. 9: 569. https://doi.org/10.3390/metabo15090569

APA Style

Li, D., Zhang, J., Sun, Y., Chai, C., Wang, F., Fan, B., Li, L., Gao, S., Wang, H., Yang, C., & Sun, J. (2025). The Utilization Value of Condensate Water from the Drying Process of Lonicera japonica via Metabolomics Analysis. Metabolites, 15(9), 569. https://doi.org/10.3390/metabo15090569

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