Article(id=1276238238494888949, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1276238094940639467, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-2561.2025.02.019, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1721232000000, receivedDateStr=2024-07-18, revisedDate=1722528000000, revisedDateStr=2024-08-02, acceptedDate=null, acceptedDateStr=null, onlineDate=1782208507417, onlineDateStr=2026-06-23, pubDate=1740412800000, pubDateStr=2025-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1782208507417, onlineIssueDateStr=2026-06-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1782208507417, creator=13701087609, updateTime=1782208507417, updator=13701087609, issue=Issue{id=1276238094940639467, tenantId=1146029695717560320, journalId=1235980609244409860, year='2025', volume='46', issue='2', pageStart='247', pageEnd='489', issueExtLink='null', onlineDate='null', pubDate='1740412800000', pubDateStr='2025-02-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1782208473191, creator='13701087609', updateTime=1782208527160, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1276238321386909890, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1276238094940639467, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1276238321386909891, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1276238094940639467, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=440, endPage=446, ext={EN=ArticleExt(id=1276238238847210487, articleId=1276238238494888949, tenantId=1146029695717560320, journalId=1235980609244409860, language=EN, title=Differences in Volatile Components of Glyptostrobus pensilis Leaves from Different Geographic Distributions, columnId=1236286112713470633, journalTitle=Chinese Journal of Tropical Crops, columnName=Post-harvest Treatment & Quality Safety, runingTitle=null, highlight=null, articleAbstract=

GC-MS method was utilized to determine the volatile components of wild Glyptostrobus pensilis leaves from six geographic distributions in Guangxi (Binyang county, Tiandeng county, Yanshan district, Cangwu county, Pingle county and Qintang district) to investigate the geographic variation patterns of volatile components in the leaves. A total of 139 chemical components were detected in the volatile components of the leaves from different geographic distributions. Terpenes α-pinene and D-limonene had relatively high contents across all geographic distributions, ranging from 18.61% to 28.32% and 16.80% to 49.02%, respectively. Qintang had the fewest volatile species, while Binyang had the most. The relative contents of alcohols, aromatic hydrocarbons, ethers, aldehydes, terpenes, ketones and esters were the lowest in Yanshan, whereas the relative contents of aromatic hydrocarbons, phenols, ethers, aldehydes, acids, terpenes and alkanes were the highest in Tiandeng. Principal component analysis (PCA) showed that the cumulative contribution rate of the first three principal components reached 97.53%, reflecting most of the component information. The absolute values of characteristic vectors for ethers, terpenes, alkanes, aromatic hydrocarbons, acids, olefins, phenols, lipids, ketones, alcohols and other compounds were larger, indicating these are the differential substances distinguishing the different geographic distributions of G. pensilis. Cluster analysis results showed that Qintang, Cangwu and Yanshan clustered into one group, Pingle and Binyang clustered into another group, and Tiandeng formed a separate group. Correlation analysis between volatile components and environmental factors indicated that longitude and altitude had the greatest impact on the content of volatile components. The study would provide reference for the cultivation and resource utilization of G. pensilis.

, authors=null, authorsList=Xiaojuan YANG, Shinan LIU, Biyu DENG, Zhihai LU, Anshu HUANG, Yongyan LIANG, authorCompany=null, correspAuthors=Yongyan LIANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1276238242341064704, articleId=1276238238494888949, tenantId=1146029695717560320, journalId=1235980609244409860, language=CN, title=不同地理分布水松叶挥发性成分差异, columnId=1236286112877048492, journalTitle=热带作物学报, columnName=采后处理与质量安全, runingTitle=null, highlight=null, articleAbstract=

为探究水松(Glyptostrobus pensilis)叶挥发性成分的地理变化规律,本研究采用GC-MS方法测定广西6个地理分布(宾阳县、天等县、雁山区、苍梧县、平乐县和覃塘区)的野生水松叶挥发物成分。结果表明:不同地理分布水松叶挥发性成分共检测出139种化学成分,其中,萜烯类的α-蒎烯和D-柠檬烯在各地理分布中的相对含量均较高,分别为18.61%~28.32%、16.80%~49.02%。通过对比6个地理分布水松叶挥发性成分发现,覃塘区水松叶挥发物种类最少,宾阳县的最多;雁山区的醇类、芳香烃类、醚类、醛类、萜烯类、酮类和酯类相对含量均最低,而天等县的芳香烃类、酚类、醚类、醛类、酸类、萜烯类和烷烃类相对含量均最高。不同地理分布水松叶挥发性成分主成分分析表明,前3个主成分累计贡献率达97.53%,可以反映大部分成分信息,其中,醚类、萜烯类、烷烃类、芳香烃类、酸类、烯烃类、酚类、酯类、酮类、醇类和其他类的特征向量绝对值较大,是区分不同地理分布水松的差异性物质。聚类分析结果显示,覃塘区、苍梧县和雁山区聚为一组,平乐县和宾阳县聚为一组,天等县单独为一组。挥发性成分与环境因子的相关性分析表明,经度和海拔对挥发性成分含量的影响最大。本研究结果可为水松的培育和资源利用提供参考依据。

, authors=

杨晓娟(1999—),女,硕士研究生,研究方向:森林培育。

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* 梁永延(LIANG Yongyan),E-mail:
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杨晓娟(1999—),女,硕士研究生,研究方向:森林培育。

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杨晓娟(1999—),女,硕士研究生,研究方向:森林培育。

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tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276238238494888949, language=EN, label=Tab. 1, caption=

Geographic and climatic information of different sampling locations

, figureFileSmall=null, figureFileBig=null, tableContent=
采样地Sampling location经度Longitude纬度Latitude海拔Altitude/m年均气温Annual average temperature/℃年均降水量Annual average precipitation/mm年均相对湿度Annual average relative humidity/%
覃塘109°40′E23°10′N61.121.81450.677.5
苍梧110°98′E23°49′N26.121.61446.679.2
宾阳108°70′E23°20′N119.121.31490.778.0
雁山110°33′E25°04′N132.819.21767.578.0
平乐110°71′E24°86′N202.820.31382.177.2
天等106°54'E22°54'N483.420.31409.581.9
), ArticleFig(id=1276238252315119678, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276238238494888949, language=CN, label=表1, caption=

不同采样地地理气候信息

, figureFileSmall=null, figureFileBig=null, tableContent=
采样地Sampling location经度Longitude纬度Latitude海拔Altitude/m年均气温Annual average temperature/℃年均降水量Annual average precipitation/mm年均相对湿度Annual average relative humidity/%
覃塘109°40′E23°10′N61.121.81450.677.5
苍梧110°98′E23°49′N26.121.61446.679.2
宾阳108°70′E23°20′N119.121.31490.778.0
雁山110°33′E25°04′N132.819.21767.578.0
平乐110°71′E24°86′N202.820.31382.177.2
天等106°54'E22°54'N483.420.31409.581.9
), ArticleFig(id=1276238252449337407, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276238238494888949, language=EN, label=Tab. 2, caption=

Principal component eigenvectors, eigenvalues and contribution rates

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分Principal component特征向量Eigenvector
其他类Others醚类Ethers萜烯类Terpenes烷烃类Alkanes芳香烃类Aromatic hydrocarbons酸类Acids烯烃类Alkenes酚类Phenols
1–0.3440.3420.3400.3380.3280.327–0.3220.318
2–0.070–0.113–0.064–0.1650.084–0.180–0.046–0.231
30.0830.088–0.1690.026–0.1900.1680.3120.190
主成分Principal component特征向量Eigenvector
醛类Aldehydes酯类Esters酮类Ketones醇类Alcohols特征值Eigenvalue贡献率Contribution rate/%累计贡献率Cumulative contribution rate/%
10.272–0.0110.1990.0388.19068.2568.25
20.2820.6400.4940.3502.21618.4786.71
30.2380.2440.304–0.7421.29810.8297.53
), ArticleFig(id=1276238252579360832, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276238238494888949, language=CN, label=表2, caption=

主成分特征向量、特征值及贡献率

, figureFileSmall=null, figureFileBig=null, tableContent=
主成分Principal component特征向量Eigenvector
其他类Others醚类Ethers萜烯类Terpenes烷烃类Alkanes芳香烃类Aromatic hydrocarbons酸类Acids烯烃类Alkenes酚类Phenols
1–0.3440.3420.3400.3380.3280.327–0.3220.318
2–0.070–0.113–0.064–0.1650.084–0.180–0.046–0.231
30.0830.088–0.1690.026–0.1900.1680.3120.190
主成分Principal component特征向量Eigenvector
醛类Aldehydes酯类Esters酮类Ketones醇类Alcohols特征值Eigenvalue贡献率Contribution rate/%累计贡献率Cumulative contribution rate/%
10.272–0.0110.1990.0388.19068.2568.25
20.2820.6400.4940.3502.21618.4786.71
30.2380.2440.304–0.7421.29810.8297.53
), ArticleFig(id=1276238252717772865, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276238238494888949, language=EN, label=Tab. 3, caption=

Correlation analysis between the relative content of volatile components in G. pensilis leaves and major environmental factors

, figureFileSmall=null, figureFileBig=null, tableContent=
挥发物Volatile component经度Longitude纬度Latitude海拔Altitude年均气温Annual average temperature年均降水量Annual average precipitation年均相对湿度Annual average relative humidity
醇类0.378–0.032–0.4720.3100.396–0.151
芳香烃类–0.680–0.5120.801–0.0800.737–0.614
酚类–0.808–0.3860.945**–0.3120.458–0.315
醚类–0.844*–0.4730.945**–0.2040.492–0.475
醛类–0.818*–0.5200.833*–0.0080.283–0.645
酸类–0.807–0.3180.977**–0.3720.375–0.287
萜烯类–0.881*–0.5130.905*–0.1700.611–0.471
酮类–0.207–0.0380.516–0.1400.038–0.486
烷烃类–0.817*–0.4220.951**–0.2730.502–0.388
烯烃类0.840*0.637–0.766–0.039–0.7030.629
酯类0.2510.345–0.002–0.098–0.497–0.126
其他类0.8070.408–0.919**0.228–0.5160.481
), ArticleFig(id=1276238252839407682, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1276238238494888949, language=CN, label=表3, caption=

水松叶挥发性物质相对含量与主要环境因子的相关性分析

, figureFileSmall=null, figureFileBig=null, tableContent=
挥发物Volatile component经度Longitude纬度Latitude海拔Altitude年均气温Annual average temperature年均降水量Annual average precipitation年均相对湿度Annual average relative humidity
醇类0.378–0.032–0.4720.3100.396–0.151
芳香烃类–0.680–0.5120.801–0.0800.737–0.614
酚类–0.808–0.3860.945**–0.3120.458–0.315
醚类–0.844*–0.4730.945**–0.2040.492–0.475
醛类–0.818*–0.5200.833*–0.0080.283–0.645
酸类–0.807–0.3180.977**–0.3720.375–0.287
萜烯类–0.881*–0.5130.905*–0.1700.611–0.471
酮类–0.207–0.0380.516–0.1400.038–0.486
烷烃类–0.817*–0.4220.951**–0.2730.502–0.388
烯烃类0.840*0.637–0.766–0.039–0.7030.629
酯类0.2510.345–0.002–0.098–0.497–0.126
其他类0.8070.408–0.919**0.228–0.5160.481
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不同地理分布水松叶挥发性成分差异
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杨晓娟 1 , 刘世男 1 , 邓必玉 2, 3 , 卢志海 1 , 黄安书 2, 3 , 梁永延 2, 3, *
热带作物学报 | 采后处理与质量安全 2025,46(2): 440-446
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热带作物学报 |采后处理与质量安全 2025 , 46 (2) : 440 -446
不同地理分布水松叶挥发性成分差异
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杨晓娟(1999—),女,硕士研究生,研究方向:森林培育。

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杨晓娟(1999—),女,硕士研究生,研究方向:森林培育。

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杨晓娟1, 刘世男1, 邓必玉2, 3, 卢志海1, 黄安书2, 3, 梁永延2, 3, *
作者信息
  • 1.广西大学林学院/广西高校亚热带人工林培育与利用重点实验室,广西南宁 530004
  • 2.广西壮族自治区森林资源与生态环境监测中心,广西南宁 530028
  • 3.广西北海湿地生态系统国家定位观测研究站,广西北海 536000
通讯作者:
* 梁永延(LIANG Yongyan),E-mail:
Differences in Volatile Components of Glyptostrobus pensilis Leaves from Different Geographic Distributions
Xiaojuan YANG1, Shinan LIU1, Biyu DENG2, 3, Zhihai LU1, Anshu HUANG2, 3, Yongyan LIANG2, 3, *
Affiliations
  • 1.College of Forestry, Guangxi University / Guangxi Colleges and Universities Key Laboratory for Cultivation and Utilization of Subtropical Forest Plantation, Nanning, Guangxi 530004, China
  • 2.Guangxi Forest Resources and Environment Monitoring Center, Nanning, Guangxi 530028, China
  • 3.Guangxi Beihai Wetland Ecosystem National Observation and Research Station, Beihai, Guangxi 536000, China
出版时间: 2025-02-25 doi: 10.3969/j.issn.1000-2561.2025.02.019
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为探究水松(Glyptostrobus pensilis)叶挥发性成分的地理变化规律,本研究采用GC-MS方法测定广西6个地理分布(宾阳县、天等县、雁山区、苍梧县、平乐县和覃塘区)的野生水松叶挥发物成分。结果表明:不同地理分布水松叶挥发性成分共检测出139种化学成分,其中,萜烯类的α-蒎烯和D-柠檬烯在各地理分布中的相对含量均较高,分别为18.61%~28.32%、16.80%~49.02%。通过对比6个地理分布水松叶挥发性成分发现,覃塘区水松叶挥发物种类最少,宾阳县的最多;雁山区的醇类、芳香烃类、醚类、醛类、萜烯类、酮类和酯类相对含量均最低,而天等县的芳香烃类、酚类、醚类、醛类、酸类、萜烯类和烷烃类相对含量均最高。不同地理分布水松叶挥发性成分主成分分析表明,前3个主成分累计贡献率达97.53%,可以反映大部分成分信息,其中,醚类、萜烯类、烷烃类、芳香烃类、酸类、烯烃类、酚类、酯类、酮类、醇类和其他类的特征向量绝对值较大,是区分不同地理分布水松的差异性物质。聚类分析结果显示,覃塘区、苍梧县和雁山区聚为一组,平乐县和宾阳县聚为一组,天等县单独为一组。挥发性成分与环境因子的相关性分析表明,经度和海拔对挥发性成分含量的影响最大。本研究结果可为水松的培育和资源利用提供参考依据。

水松  /  挥发性成分  /  GC-MS  /  地理变化

GC-MS method was utilized to determine the volatile components of wild Glyptostrobus pensilis leaves from six geographic distributions in Guangxi (Binyang county, Tiandeng county, Yanshan district, Cangwu county, Pingle county and Qintang district) to investigate the geographic variation patterns of volatile components in the leaves. A total of 139 chemical components were detected in the volatile components of the leaves from different geographic distributions. Terpenes α-pinene and D-limonene had relatively high contents across all geographic distributions, ranging from 18.61% to 28.32% and 16.80% to 49.02%, respectively. Qintang had the fewest volatile species, while Binyang had the most. The relative contents of alcohols, aromatic hydrocarbons, ethers, aldehydes, terpenes, ketones and esters were the lowest in Yanshan, whereas the relative contents of aromatic hydrocarbons, phenols, ethers, aldehydes, acids, terpenes and alkanes were the highest in Tiandeng. Principal component analysis (PCA) showed that the cumulative contribution rate of the first three principal components reached 97.53%, reflecting most of the component information. The absolute values of characteristic vectors for ethers, terpenes, alkanes, aromatic hydrocarbons, acids, olefins, phenols, lipids, ketones, alcohols and other compounds were larger, indicating these are the differential substances distinguishing the different geographic distributions of G. pensilis. Cluster analysis results showed that Qintang, Cangwu and Yanshan clustered into one group, Pingle and Binyang clustered into another group, and Tiandeng formed a separate group. Correlation analysis between volatile components and environmental factors indicated that longitude and altitude had the greatest impact on the content of volatile components. The study would provide reference for the cultivation and resource utilization of G. pensilis.

Glyptostrobus pensilis  /  volatile components  /  GC-MS  /  geographical variation
杨晓娟, 刘世男, 邓必玉, 卢志海, 黄安书, 梁永延. 不同地理分布水松叶挥发性成分差异. 热带作物学报, 2025 , 46 (2) : 440 -446 . DOI: 10.3969/j.issn.1000-2561.2025.02.019
Xiaojuan YANG, Shinan LIU, Biyu DENG, Zhihai LU, Anshu HUANG, Yongyan LIANG. Differences in Volatile Components of Glyptostrobus pensilis Leaves from Different Geographic Distributions[J]. Chinese Journal of Tropical Crops, 2025 , 46 (2) : 440 -446 . DOI: 10.3969/j.issn.1000-2561.2025.02.019
植物在生长发育过程中会释放大量的次生代谢物,其中,挥发性有机物具有抗氧化、抗菌、抗癌等特性[1],能净化空气、改善身心健康,目前已被广泛用于食品、饮料、药品、香水和化妆品行业[2]。据报道,挥发性成分对植物的生长发育也起到了至关重要的作用,挥发性有机物作为生长发育的调控信号,有助于植物抵抗外界胁迫并保护植物自身[3]。如在环境压力下,植物能在几秒内迅速释放有机物,并在重复受伤等特殊情况下持续释放多日,以触发和诱导植物作出防御[4];通过信号传导,这些挥发性有机物还能改变植物激素的动态平衡,对生物和非生物胁迫作出响应[5]。近年来,人们发现挥发性有机物的释放受海拔、湿度、温度等影响[6]。任瑞芬等[7]研究了百里香(Thymus mongolicus)挥发性物质种源变化差异,发现其萜烯类物质与经纬位置、海拔、生态环境因子以及土壤酸碱度存在显著相关性;陈亚菲等[8]认为温度和相对湿度对地钱(Marchantia polymorpha)的挥发性成分影响最大;刘圆圆等[9]研究发现不同地区的山胡椒(Litsea cubeba)叶挥发物种类和含量相差较大,可能是当地特殊气候所致。由此可见,不同地理分布下植物挥发物存在差异,探究其差异来源对植物的保护和利用具有重要意义。
水松(Glyptostrobus pensilis)为柏科(Cupressaceae)水松属(Glyptostrobus Endl)植物,是我国的特有树种,属国家一级保护植物,被称为植物界的“活化石”,在我国主要分布于珠江三角洲和福建中部以及闽江下游海拔1000 m以下地区,在广西、江西、四川、南京、武汉、庐山、上海、杭州和云南等地也有少量分布[10]。该植物常见于温暖湿润地区以及水湿环境,多生长在池塘、河流、湖畔等地。其树干、树皮常作为中药治疗类风湿性关节炎、高血压、皮炎和烫伤等,叶中存在的萜类物质可用于治疗慢性粒细胞性白血病和预防新型冠状病毒肺炎[11-12],是开发利用前景较大的珍贵树种。当前,水松植株主要以天然林零散分布,多呈孤立木,数量较少[13]。为了加快对水松的保护和利用进程,需在其现有资源的基础上进行人工栽植和定向培育。目前,有关外部条件变化对水松挥发物释放规律的研究较少。因此,本研究采用GC-MS方法测定广西6个不同地理分布(宾阳县、天等县、雁山区、苍梧县、平乐县和覃塘区)水松叶挥发物成分,探讨地理变化对水松挥发物的影响,为保护和培育水松提供理论支撑。
试验材料采自广西境内6个不同地区,均为成熟林木,林下植被相似,采样地分别是贵港覃塘、南宁宾阳、梧州苍梧、桂林雁山、桂林平乐、崇左天等,具体采样地位置及2023年气候环境见表1
于2023年8月进行样品采集,从树体中上部不同方向随机取样,样品采集后,置于80 ℃烘箱中,烘干至恒重,粉碎,备用。
采用TDS-GC/MS联用技术[14]测定水松叶片挥发物的成分。采用HP-5MS型色谱柱(30 m×250 μm×0.25 μm),初始温度为40 ℃,持续4 min,以6 ℃/min的速率升温至250 ℃,250 ℃保持3 min,然后以10 ℃/min升温至270 ℃,保持5 min。MS工作条件:电子能量在70 eV的EI模式下对原子质量进行扫描,范围为28~450 m/z,设离子温度为230 ℃,接口温度为280 ℃,四极杆为150 ℃。采用NIST2008谱库分析质谱数据,结合人工检索匹配解谱,采用峰面积表示相对峰面积。
采用Excel 2016软件对水松叶挥发物种类和含量变化进行统计,采用SPSS 25.0软件对不同地理分布水松叶挥发性成分进行主成分分析、聚类分析和相关性分析。
经GC-MS分析,得到6个地理分布水松叶挥发性成分(图1),结果表明,在不同地理分布水松叶挥发性成分中共检测出139种化学成分,包括烯烃类30种、醇类30种、酯类24种、萜烯类16种、醛类10种、酮类7种、芳香烃类5种、酸类3种、烷烃类2种、醚类2种、酚类1种、其他类9种。其中,萜烯类的α-蒎烯和D-柠檬烯的相对含量分别为18.61%~28.32%、16.80%~49.02%,二者在各地理分布中的相对含量均较高。
各地理分布水松叶挥发性成分种类均以醇类、烯烃类、酯类为多,其次是萜烯类,而酚类、醚类、酸类和烷烃类较少(图2)。挥发性成分相对含量显示,6个地理分布中萜烯类的相对含量均明显高于其他挥发物,相对含量在59.67%~79.40%之间,相对含量较高的还有酯类、烯烃类、其他类(图3)。不同地理分布水松叶挥发性成分存在差异,各地理分布挥发物种类中,宾阳(120种)>苍梧(119种)=平乐(119种)>雁山(118种)=天等(118种)>覃塘(116种),其中,天等的水松叶挥发物以醇类种类较多,其余5个分布区均以烯烃类种类较多。在各地理分布挥发物的相对含量中,雁山的醇类、芳香烃类、醚类、醛类、萜烯类、酮类和酯类的相对含量均最低,而天等的芳香烃类、酚类、醚类、醛类、酸类、萜烯类和烷烃类的相对含量均最高。主要挥发物成分中,各地理分布中的α-蒎烯相对含量为覃塘(18.61%)<天等(19.20%)<雁山(22.62%)<苍梧(23.38%)<平乐(23.86%)<宾阳(28.32%),D-柠檬烯相对含量为平乐(16.80%)<雁山(18.94%)<苍梧(19.35%)<宾阳(19.55%)<覃塘(22.44%)<天等(49.02%),可见,覃塘和天等的α-蒎烯相对含量较低,但其D-柠檬烯相对含量较高,其中,天等的D-柠檬烯明显高于其他地理分布。此外,还发现对位薄荷-1(7),8-二烯-2-醇、香芹醇和芳樟醇氧化物A仅存在于天等水松中。
不同地理分布水松叶挥发性成分的主成分分析结果表明,前3个主成分的累计贡献率达97.53%,大于80%,说明前3个主成分可基本反映水松叶挥发性成分的大部分信息,因此可以用前3个主成分来评价水松叶挥发性成分质量。由表2可知,第1主成分贡献率为68.25%,其中,其他类、醚类、萜烯类、烷烃类、芳香烃类、酸类、烯烃类和酚类的特征向量绝对值均大于0.3,明显高于其他类别;第2主成分贡献率为18.47%,其中,酯类和酮类的特征向量绝对值较大,均大于0.4;第3主成分贡献率为10.82%,其中,醇类的特征向量绝对值大于0.7,显著高于其他类别(表2)。
基于水松叶挥发性成分含量,采用欧式聚类对6个地理分布水松叶挥发性成分进行聚类,结果如图4所示,在欧式距离为5处,6个地理分布被分为3组,其中覃塘、苍梧和雁山为一组,平乐和宾阳为一组,天等单独为一组。
通过对水松叶内的12类挥发性物质含量与环境因子进行相关性分析发现,经度与醚类、醛类、萜烯类和烷烃类呈显著负相关(P<0.05),与烯烃类呈显著正相关;海拔与其他类呈极显著负相关(P<0.01);,与酚类、醚类、醛类、酸类、萜烯类和烷烃类呈显著或极显著正相关纬度、年均气温、年均降水量和年均相对湿度与水松挥发性物质相对含量的相关性不显著(表3)。
采用GC-MS法对水松叶挥发性成分进行检测发现,水松叶挥发物类型以烯烃类化合物为主,且以萜烯类相对含量最高,这与前人对落基山刺柏水杉(Metasequoia glyptostroboides[14]、落基山圆柏(Juniperus scopulorum[15]和侧柏(Platycladus orientalis[16]的研究结果具有一致性。此外,THAI等[17]曾报道水松精油的组成以α-蒎烯(18.9%)和柠檬烯(23.9%)为主,HUY等[18]认为水松叶中分离出的精油中富含单萜烯,主要含有柠檬烯(33.3%)、α-蒎烯(23.4%)和乙酸冰片酯(9.2%)。本研究中,水松叶挥发性成分中的α-蒎烯相对含量(18.61%~28.32%)和D-柠檬烯相对含量(16.80%~49.02%)明显高于其他化合物,这与前人研究结果一致。据报道,萜烯类物质能有效刺激自律神经,促进内分泌,还具安定性情、调整感觉系统的功效,是药理活性较强的化合物[19]。其中,α-蒎烯具抗炎、抗肿瘤、镇静、抗菌和抗抑郁的功效[20],D-柠檬烯具抗氧化、抗糖尿病、抗癌、保护心脏、保护胃、保护肝脏、免疫调节等功效[21],对人体身心健康具有重要作用。因此,水松具有一定的保健价值。
植物叶挥发性成分因地理分布的变化而异[22]。通过对不同地理分布水松叶挥发性成分差异研究发现,天等的水松叶挥发性成分与其他地理分布存在明显差异,具体表现为天等的水松叶挥发物以醇类为主,其他地理分布的以烯烃类为主;其次,相比于其他地理分布,天等的水松叶多数挥发物成分含量较高,主要化合物中,天等的水松叶中α-蒎烯含量虽较低,而D-柠檬烯含量较高,此外,对位薄荷-1(7),8-二烯-2-醇、香芹醇和芳樟醇氧化物A仅在天等水松叶中发现。天等作为本研究中最南部的采样点,与其他地理分布相比,其经度较低,海拔较高,地理分布可能是导致其挥发物存在明显差异的重要原因。已有研究表明,植物释放的挥发性成分能调节植物生长发育,并在胁迫条件下稳定光合机制,增强植物耐受性[23-24]。因此,研究叶内挥发性成分对濒危树种水松的育种和栽培具有重要意义。本研究通过对比6个地理分布野生水松叶挥发性成分发现,覃塘水松叶挥发物种类最少,宾阳最多,此外,雁山的醇类、芳香烃类、醚类、醛类、萜烯类、酮类和酯类相对含量最低,而天等的芳香烃类、酚类、醚类、醛类、酸类、萜烯类和烷烃类相对含量最高。可见,天等和宾阳可以进一步作为后续种质资源的筛选。
为进一步探究不同地理分布水松叶挥发性成分的差异,对6个地理分布水松叶挥发性成分进行主成分分析、聚类分析和相关性分析。结果表明,主成分分析中,前3个主成分累计贡献率达97.53%,可以反映大部分成分信息。值得注意的是,醚类、萜烯类、烷烃类、芳香烃类、酸类、酚类与第1主成分呈高度正相关,其他类和烯烃类与第1主成分呈高度负相关,酯类和酮类与第2主成分呈高度正相关,醇类与第3主成分呈高度负相关,说明这些类别对水松叶挥发性成分影响较大,可以作为区分不同地理分布水松的差异性物质。此外,醛类在3个主成分中的特征向量值均较小,可见,醛类对总体特征的贡献度较低,在不同地理区域中具有稳定性,推测醛类不是影响水松叶挥发性成分地理分布差异的主要因素。
同一植物不同地理分布挥发性成分的差异可能归因于该植物对特定生境的适应[25]。聚类分析表明,覃塘、苍梧和雁山聚为一组,平乐和宾阳聚为一组,天等单独为一组。已有研究证实,气候和地理环境是导致植物挥发性成分产生差异的主要因素,如WALIA等[26]对不同海拔印加孔雀草(Tagetes minuta)9种挥发性成分进行研究发现,高海拔地区的Z-β-香柠烯含量较高,而二氢薄荷酮则相反。FERNÁNDEZ-SESTELO等[27]通过研究认为年降水量大,穗薰衣草(Lavandula latifolia)精油高质高产,高海拔能获得高质量精油,而低纬度可得到高产量精油。然而,KARIMI等[28]认为百日草(Zataria multiflora)精油含量与海拔呈负相关,与温度呈正相关。因此,我们推测水松叶挥发性成分的形成和积累差异,可能是由于不同的气候、土壤或生态环境引起的。为探讨水松叶挥发性成分在不同地理区域的适应机制,本研究进行挥发性成分与地理气候因子的关联分析,结果表明,水松叶多数挥发性成分与经度呈显著负相关,与海拔呈显著正相关,而与纬度和气候因素(年均降水量、年均气温和年均相对湿度)无显著相关性。这也意味着,经度和海拔是影响水松叶挥发性成分的主要因子,随经度降低,海拔升高,挥发性成分含量越高。因此,在进行水松培育时,应考虑栽植地的经度和海拔等环境因子。
  • 中央财政林业草原生态保护恢复资金国家重点野生保护植物保护补助项目(502039202309)
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2025年第46卷第2期
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doi: 10.3969/j.issn.1000-2561.2025.02.019
  • 接收时间:2024-07-18
  • 首发时间:2026-06-23
  • 出版时间:2025-02-25
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  • 收稿日期:2024-07-18
  • 修回日期:2024-08-02
基金
中央财政林业草原生态保护恢复资金国家重点野生保护植物保护补助项目(502039202309)
广西林业科技推广示范项目(2024GXLK20)
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    1.广西大学林学院/广西高校亚热带人工林培育与利用重点实验室,广西南宁 530004
    2.广西壮族自治区森林资源与生态环境监测中心,广西南宁 530028
    3.广西北海湿地生态系统国家定位观测研究站,广西北海 536000

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* 梁永延(LIANG Yongyan),E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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