摘要
浙江楠、紫楠、白楠都是楠属毛花组植物,具有较近的亲缘关系,这3种植物在形态上极为相近,在生产实践中极易混淆。为了正确识别这3种楠属植物,采用光学显微镜、体视显微镜和扫描电镜等手段观察比较植株、叶片等整体形态和显微特征,获得3种楠属植物的鉴别要点。从整体形态来说,这3种楠属植物主要从枝条的被毛情况,叶片的大小、形状,叶柄的长度,宿存花被片是否紧贴以及种子的形状和特征等方面来进行鉴别和区分。从测量和显微观测来说,紫楠叶面积大于白楠和浙江楠,中脉与基部的夹角较浙江楠和白楠更小,表皮毛的长度和数量都高于浙江楠和白楠,白楠叶柄近无毛。研究结果可应用于生产实践,为樟科植物资源的开发利用提供参考。
Phoebe chekiangensis,Ph.sheareri and Ph.neurantha are both belong to Sect.Caniflorae of Phoebe genus.The three plants are easily confused in production practice because they are closely related to each other and very similar in morphology.In order to correctly identify the three species,the morphological and microscopic characteristics of the three plants were observed and compared using light microscope,stereomicroscope and scanning electron microscope(SEM).The results showed that the three species were mainly distinguished from the hair on branches,the size and shape of leaves,the length of petioles,the state of the persistent perianth,and characteristics of seeds.The result of measurement and microscopic observation showed that the leaf area of Ph.sheareri was larger,and the angle between midrib and base was smaller than that of Ph.chekiangensis and Ph.neurantha.The length and number of epidermal hair of Ph.sheareri were higher than that of Ph.chekiangensis and Ph.neurantha,too.The petiole of Ph.neurantha was nearly glabrous.The results can be applied to production practice and provide reference for the development and utilization of Lauraceae resources.
作者
雷昌菊
戴小英
伍艳芳
刘新亮
郑永杰
符潮
Lei Changju;Dai Xiaoying;Wu Yanfang;Liu Xinliang;Zheng Yongjie;Fu Chao(Jiangxi Academy of Forestry,Camphor Engineering Technology Research Center for National Forestry and Grassland Administration,Nanchang Jiangxi 330013,China)
出处
《南方林业科学》
2021年第6期4-7,31,共5页
South China Forestry Science
基金
江西省重点研发计划项目(项目编号:20203BBF62W010)
江西省林业科技创新项目(项目编号:创新专项[2021]15号)
中央财政林业科技推广示范项目(项目编号:JXTG[2021]16号)
江西省重点研发计划项目(项目编号:20181BBF60012)。
关键词
叶片形态
显微特征
浙江楠
紫楠
白楠
扫描电镜
leaf morphology
microscopic characteristics
Phoebe chekiangensis
Phoebe sheareri
Phoebe neurantha
SEM
