植物叶脉标本简单制作方法及基于Image J软件的叶脉图像分析

doi:10.3969/j.issn.1009-7791.2022.05.011

亚热带植物科学 ›› 2022, Vol. 51 ›› Issue (5): 397-404.DOI: 10.3969/j.issn.1009-7791.2022.05.011

植物叶脉标本简单制作方法及基于Image J软件的叶脉图像分析

全昌彬，姚玉仙*，莫光友

(黔南民族师范学院生物科学与农学院，贵州都匀 558000)

收稿日期:2022-08-30 接受日期:2022-09-27 出版日期:2022-10-15 发布日期:2023-01-17
通讯作者: 姚玉仙
基金资助:
贵州省教育厅自然科学基金项目(黔教合KY字[2019]211)；贵州省科技计划项目(黔科合基础[2020]1Y120)；黔南民族师范学院生物学一流学科专项建设经费(学科建设专项)

A Simple Method of Making Leaf Vein Specimens and Using Image J Software to Analyze the Characteristics of Leaf Vein

QUAN Chang-bin, YAO Yu-xian*, MO Guang-you

(College of Biological Science and Agriculture, Qiannan Normal University for Nationalities, Duyun 558000, Guizhou China)

Received:2022-08-30 Accepted:2022-09-27 Online:2022-10-15 Published:2023-01-17
Contact: YAO Yu-xian

摘要/Abstract

摘要： 采用5%氢氧化钾沸水浴对12种植物叶片进行处理，结合超声波清洗使叶肉及表皮脱离，经漂白、染色制成叶脉标本。使用数码相机及显微镜对标本进行成像，利用Image J软件MINA工具宏的分析步骤对图像进行分析，测定12种植物叶脉的密度、分支密度、交点密度、端点密度，并通过手动追踪验证测量结果的准确性。结果表明，该方法可快速获得清晰完整的叶脉网络结构图，并且可以运用Image J软件MINA工具宏的分析步骤对叶脉进行分析。与传统的氢氧化钠组织透明法比较，该方法处理时间短，叶脉网络结构完整清晰，用Image J软件可准确测量叶脉密度。

关键词: 5%氢氧化钾, 超声波清洗, 叶脉网络结构, 叶脉密度, Image J 软件

Abstract: The leaves of 12 species of plants were treated with 5% potassium hydroxide boiling water bath, and the mesophyll and epidermis were separated by ultrasonic cleaning. The leaf vein was prepared by bleaching and dyeing. The specimens were imaged using digital camera and microscope, and the images were analyzed using the macro analysis steps of Image J software MINA tool. The density, branches density, junction density and end-point voxels density of leaf veins of 12 plants were measured, and the accuracy of the measurement results was verified by manual tracking. The results showed that the experimental method could quickly obtain clear and complete vein network structure, and use Image J software MINA tool macro analysis steps to analyze the vein. Compared with the traditional sodium hydroxide tissue transparency method, this experimental method had shorter processing time, complete and clear leaf vein network structure, and the leaf vein density could be accurately measured by Image J software.

Key words: 5% potassium hydroxide, ultrasonic cleaning, leaf vein network structure, leaf vein density, Image J

中图分类号:

Q94-34

全昌彬, 姚玉仙, 莫光友. 植物叶脉标本简单制作方法及基于Image J软件的叶脉图像分析[J]. 亚热带植物科学, 2022, 51(5): 397-404.

QUAN Chang-bin, YAO Yu-xian, MO Guang-you. A Simple Method of Making Leaf Vein Specimens and Using Image J Software to Analyze the Characteristics of Leaf Vein[J]. Subtropical Plant Science, 2022, 51(5): 397-404.

参考文献

[1] Katifori E. The transport network of a leaf[J]. Comptes Rendus Physique, 2018, 19: 244–252.

[2] Sharon E, Sahaf M. The mechanics of leaf growth on large scales[J]. Plant Biomechanics, 2018, 1: 109–126.

[3] 李乐, 曾辉, 郭大立. 叶脉网络功能性状及其生态学意义[J]. 植物生态学报, 2013, 37(7): 691–698.

[4] Larese M G, Craviotto R M, Arango M R, Gallo C, Granitto P M. Legume identification by leaf vein images classification[J]. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2012, 7441(1): 447–454.

[5] Tan J W, Chang S W, Abdul-Kareem S, Yap H J, Yong K T. Deep learning for plant species classification using leaf vein morphometric[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020 ,17(1): 82–90.

[6] 王永, 何顺志. 贵州小檗属植物(小檗科)叶脉序研究[J]. 广西植物, 2015, 35(4): 476–486.

[7] 王博强, 刘潘莲, 沈坤, 王宇坤, 姜悦, 王磊, 杨文权. 陕西小檗属14种植物叶脉序式样的研究[J]. 陕西林业科技, 2021, 49(2): 1–7.

[8] 黄文鑫, 吴保欢, 石文婷, 羊海军, 崔大方. 广义李属植物叶脉序特征及其分类学意义[J]. 植物资源与环境学报, 2019, 28(4): 11–23.

[9] 杨容, 刘全儒, 何毅, 王珊, 王立成. 中国沟瓣属植物叶脉序特征观测研究[J]. 北京师范大学学报(自然科学版), 2017, 53(6): 663–667.

[10] 曹明, 曹丽敏, 张奠湘, 张瑞泉. 中国花椒属(广义)叶结构研究[J]. 广西植物, 2009, 29(2): 163–170.

[11] 曹丽敏, 王志新, 曹明, 刘健晖, 林琼, 夏念和. 中国无患子科植物的叶脉形态及其系统学意义[J]. 植物分类与资源学报, 2014, 36(4): 419–432.

[12] Zhang L F, Yang J, Huang Y, Jia Z Y, Fang Y M. Leaf venation variation and phenotypic plasticity in response to environmental heterogeneity in Parrotia subaequalis (H. T. Chang) R. M. Hao et H. T. Wei, an endemic and endangered tree species from China[J]. Forests, 2018, 9(5): 247.

[13] Wang X L , Wang Z X , Li R Y, Deng P, Ma L , Sun B N . Vein density of angiosperms as a paleoclimate proxy: A case study using fossil leaves of Zelkova, and Machilus[J]. Palaeo world, 2016, 25(1): 60–66.

[14] Li X P, Li Y P, Zhang Z, Li X G. Influences of environmental factors on leaf morphology of Chinese jujubes[J]. PLoS ONE, 2015, 10(5): 1–16.

[15] Rodríguez-Ramírez E C, García-Morales L J, Alcántara-Ayala O, Vázquez-García J A, Luna-Vega I I. Leaf vein morphological variation in four endangered neotropical magnolia species along an elevation gradient in the Mexican tropical montane cloud forests[J]. Plants (Basel), 2021, 10(12): 2595.

[16] Blonder B, Enquist B J. Inferring climate from angiosperm leaf venation networks[J]. New Phytology, 2014, 204(1): 116–126.

[17] James S C, Paolo R, Sarah B, Paul W. The extraction of venation from leaf images by evolved vein classifiers and ant colony algorithms[J]. Lecture Notes in Computer Science, 2010, 6474(1): 135–144.

[18] Gan Y, Rong Y, Huang F, Hu L, Yu X, Duan P, Xiong S, Liu H, Peng J, Yuan X. Automatic hierarchy classification in venation networks using directional morphological filtering for hierarchical structure traits extraction[J]. Computational Biology and Chemistry, 2019, 80: 187–194.

[19] 韩玲, 赵成章, 徐婷, 冯威, 段贝贝. 不同土壤水分条件下洪泛平原湿地芨芨草叶片厚度与叶脉性状的关系[J]. 植物生态学报, 2017, 41(5): 529–538.

[20] 张亚, 杨石建, 孙梅, 曹坤芳. 基部被子植物气孔性状与叶脉密度的关联进化[J]. 植物科学学报, 2014, 32(4): 320–328.

[21] Pérez-Harguindeguy N, Díaz S, Garnier E. New handbook for standardised measurement of plant functional traits worldwide[J]. Australian Journal of Botany, 2013, 61(3): 167–234.

[22] Zhu J, Yao J, Yu Q, He W, Xu C, Qin G, Zhu Q, Fan D, Zhu H. A fast and automatic method for leaf vein network extraction and vein density measurement based on object-oriented classification[J]. Frontiers in Plant Science, 2020, 11: 499.

[23] Xu H, Blonder B, Jodra M, Malhi Y, Fricker M. Automated and accurate segmentation of leaf venation networks via deep learning[J]. New Phytologist, 2021, 229(1): 631–648.

[24] Blonder B, Salinas N, Bentley L P, Shenkin A. Structural and defensive roles of angiosperm leaf venation network reticulation across an Andes-Amazon elevation gradient[J]. Journal of Ecology, 2018, 106(4): 1683–1699.

[25] Schneider J V, Rabenstein R, Wesenberg J, Wesche K, Zizka G, Habersetzer J. Improved non-destructive 2D and 3D X-ray imaging of leaf venation[J]. Plant Methods, 2018, 14: 7.

[26] Ellis B, Daly D C. 叶结构手册[M]. 北京: 北京大学出版社, 2012: 72–110.

[27] Valente A J, Maddalena L A, Robb M F, Stuart J A. A simple Image J macro tool for analyzing mitochondrial network morphology in mammalian cell culture[J]. Acta Histochemistry, 2017, 119(3): 315–326.

[28] Sack L, Scoffoni C. Leaf venation: structure, function, development, evolution, ecology and applications in the past, present and future[J]. New Phytologist, 2013, 198(4): 983–1000.

编辑推荐

Metrics

闽ICP备11008787号-5　

植物叶脉标本简单制作方法及基于Image J软件的叶脉图像分析

A Simple Method of Making Leaf Vein Specimens and Using Image J Software to Analyze the Characteristics of Leaf Vein

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 1

编辑推荐

Metrics