Article(id=1321852266265559753, tenantId=1146029695717560320, journalId=1316781310003478668, issueId=1321852178331979976, articleNumber=null, orderNo=null, doi=10.11983/CBB25002, pmid=null, cstr=32102.14.CBB25002, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1736352000000, receivedDateStr=2025-01-09, revisedDate=null, revisedDateStr=null, acceptedDate=1743523200000, acceptedDateStr=2025-04-02, onlineDate=1793083739104, onlineDateStr=2026-10-27, pubDate=1762704000000, pubDateStr=2025-11-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793083739104, onlineIssueDateStr=2026-10-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793083739104, creator=13701087609, updateTime=1793083739104, updator=13701087609, issue=Issue{id=1321852178331979976, tenantId=1146029695717560320, journalId=1316781310003478668, year='2025', volume='60', issue='6', pageStart='859', pageEnd='1035', issueExtLink='null', onlineDate='null', pubDate='1762704000000', pubDateStr='2025-11-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793083718140, creator='13701087609', updateTime=1793083787009, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321852467248223111, tenantId=1146029695717560320, journalId=1316781310003478668, issueId=1321852178331979976, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321852467252417416, tenantId=1146029695717560320, journalId=1316781310003478668, issueId=1321852178331979976, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1005, endPage=1016, ext={EN=ArticleExt(id=1321852266462692042, articleId=1321852266265559753, tenantId=1146029695717560320, journalId=1316781310003478668, language=EN, title=Development and Application of 3D Reconstruction Technology at Different Scales in Plant Research, columnId=1317485676040409248, journalTitle=Chinese Bulletin of Botany, columnName=SPECIAL TOPICS, runingTitle=null, highlight=null, articleAbstract=

3D reconstruction technology involves using computer graphics and image processing technologies to extract the geometric and topological information of the target object from the two-dimensional image data. This information is then used to create a three-dimensional mathematical model that can be processed by a computer, enabling the virtual reconstruction of the target object. In plant science research, the construction of three-dimensional models has become an effective way to study plant growth and development, morphological structure and functional mechanism. These models provide robust support for multi-scale imaging, measurement and analysis, demonstrating significant application potential in the field of agriculture and forestry. In recent years, advancements in plant 3D reconstruction technology have led to diverse applications in botanical research, covering plant morphological structure modeling, growth and development dynamic monitoring, and plant breeding. In this paper, we summarize the development process of 3D reconstruction technology and its application in plant studies across different scales (from organs and tissues to cells). We focus on the basic principles and applications of these technologies, aiming to provide theoretical and technical support for multimodal cross-scale imaging and plant phenotypic and functional research. Additionally, this work offers a novel approach to understand the principles of plant growth and development and the mechanisms underlying their responses to environmental changes.

, authors=Mengsha Huang, Lingdie Kong, Miao Yu, Chang Liu, Siqin Wang, Ruohan Wang^*, authorsList=Mengsha Huang, Lingdie Kong, Miao Yu, Chang Liu, Siqin Wang, Ruohan Wang, authorCompany=null, correspAuthors=Ruohan Wang, authorNote=null, correspAuthorsNote=, 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=1321852267196695247, articleId=1321852266265559753, tenantId=1146029695717560320, journalId=1316781310003478668, language=CN, title=不同尺度三维重建技术在植物研究中的发展及应用, columnId=1317485676191404194, journalTitle=植物学报, columnName=专题论坛, runingTitle=null, highlight=null, articleAbstract=

三维重建技术(3D reconstruction)是利用计算机图形学和图像处理技术, 从二维图像数据中提取目标物体的几何和拓扑信息, 构建计算机可处理的三维数学模型, 从而实现物体的虚拟重建。在植物学研究中, 三维模型的构建已成为研究植物生长发育、形态结构和功能机制的有效手段, 为多尺度成像、测量和分析提供了有力支撑, 并在农业和林业领域展现出巨大的应用潜力。近年来, 随着植物三维重建技术的不断完善, 其在植物学研究中衍生出不同的应用方向, 涵盖植物形态结构建模、生长发育动态监测以及植物育种等多方面。该文综述了三维重建技术的发展历程及常见的三维重建成像技术在植物不同尺度(从器官、组织到细胞)研究中的应用, 重点阐述这些技术的基本原理及应用, 旨在为植物多模态跨尺度成像以及表型与功能研究提供理论和技术支撑, 为揭示植物生长发育规律及响应环境变化的机制提供新途径。

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(in Chinese), articleTitle=Development and frontier of electron microscopy 3D reconstruction, refAbstract=null), Reference(id=1321852290227618660, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, doi=null, pmid=null, pmcid=null, year=2010, volume=26, issue=null, pageStart=533, pageEnd=559, url=null, language=null, rfNumber=[77], rfOrder=94, authorNames=张凯, 张艳, 胡仲军, 季刚, 孙飞, journalName=生物物理学报, refType=null, unstructuredReference=张凯, 张艳, 胡仲军, 季刚, 孙飞 (2010). 电子显微三维重构技术发展与前沿. 生物物理学报 26, 533-559., articleTitle=电子显微三维重构技术发展与前沿, refAbstract=null), Reference(id=1321852290332476262, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, doi=null, pmid=null, pmcid=null, year=2021, volume=64, issue=null, pageStart=1392, pageEnd=1422, url=null, language=null, rfNumber=[78], rfOrder=95, authorNames=Zhang X, Man Y, Zhuang XH, Shen JB, Zhang Y, Cui YN, Yu M, Xing JJ, Wang GC, Lian N, Hu ZJ, Ma LY, Shen WW, Yang SY, Xu HM, Bian JH, Jing YP, Li XJ, Li RL, Mao TL, Jiao YL, Sodmergen, Ren HY, Lin JX, journalName=Sci China Life Sci, refType=null, unstructuredReference=Zhang X, Man Y, Zhuang XH, Shen JB, Zhang Y, Cui YN, Yu M, Xing JJ, Wang GC, Lian N, Hu ZJ, Ma LY, Shen WW, Yang SY, Xu HM, Bian JH, Jing YP, Li XJ, Li RL, Mao TL, Jiao YL, Sodmergen, Ren HY, Lin JX (2021). Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques. Sci China Life Sci 64, 1392-1422., articleTitle=Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques, refAbstract=null), Reference(id=1321852290680603495, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, doi=null, pmid=null, pmcid=null, year=2023, volume=10, issue=null, pageStart=2461, pageEnd=2466, url=null, language=null, rfNumber=[79], rfOrder=96, authorNames=Zhou N, Sun JS, Zhang RN, Ye R, Li JJ, Bai ZD, Zhou S, Chen Q, Zuo C, journalName=ACS Photonics, refType=null, unstructuredReference=Zhou N, Sun JS, Zhang RN, Ye R, Li JJ, Bai ZD, Zhou S, Chen Q, Zuo C (2023). Quasi-isotropic high-resolution Fourier ptychographic diffraction tomography with opposite illuminations. ACS Photonics 10, 2461-2466., articleTitle=Quasi-isotropic high-resolution Fourier ptychographic diffraction tomography with opposite illuminations, refAbstract=null), Reference(id=1321852290760295272, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, doi=null, pmid=null, pmcid=null, year=2023, volume=16, issue=null, pageStart=1, pageEnd=14, url=null, language=null, rfNumber=[80], rfOrder=97, authorNames=Zhu YY, journalName=Int J Inf Technol Syst Approach, refType=null, unstructuredReference=Zhu YY (2023). 3D reconstruction of ancient building structure scene based on computer image recognition. Int J Inf Technol Syst Approach 16, 1-14., articleTitle=3D reconstruction of ancient building structure scene based on computer image recognition, refAbstract=null)], funds=[Fund(id=1321852272691233540, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, awardId=32370391, language=CN, fundingSource=国家自然科学基金(32370391), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1321852267465130704, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, xref=null, ext=[AuthorCompanyExt(id=1321852267473519313, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, companyId=1321852267465130704, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=State Key Laboratory of Tree Genetics and Breeding, College of Biological Science and Technology, Beijing Forestry University, Beijing 100083, China), AuthorCompanyExt(id=1321852267481907922, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, companyId=1321852267465130704, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=北京林业大学生物科学与技术学院, 林木遗传育种全国重点实验室, 北京 100083)])], figs=[ArticleFig(id=1321852271814623996, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, language=EN, label=Figure 1, caption=Trends in the application scenarios of 3D reconstruction technology in botanical research

The node represents the application scenarios of 3D reconstruction technology in the field of botany, and the flow data is derived from 484 articles on plant 3D reconstruction published from 2011 to 2024, with the diversions indicating shifts in application scenarios over time.

, figureFileSmall=cmHz7MfZPuZm5ywxDAyILg==, figureFileBig=C9xAxydf9nNNg2rkIVXt8w==, tableContent=null), ArticleFig(id=1321852271894315773, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, language=CN, label=图1, caption=三维重建技术在植物学研究中的应用场景趋势分析

节点表示三维重建技术在植物学中的应用场景, 流量数据基于2011-2024年植物三维重建相关的484篇文献, 分流表示应用场景的变化。

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The 3D reconstruction based on micro-computed tomography (Micro-CT) imaging technology is used as an example at the organ scale, and the 3D reconstruction based on confocal microscopy is used as an example at the tissue and cell scales.

, figureFileSmall=B3MlP9s5qSLY65K0pRWQzA==, figureFileBig=0AFRLoDfA8nNxDXRTVZFEA==, tableContent=null), ArticleFig(id=1321852272196305663, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, language=CN, label=图2, caption=不同尺度样本的三维重建流程(Jackson et al., 2017; Tracy et al., 2017; Gómez-Felipe and de Folter, 2019)

器官尺度以基于显微CT成像技术(Micro-CT)的三维重建为例, 组织和细胞尺度以基于共聚焦显微成像技术的三维重建为例。

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Three-dimensional reconstruction imaging methods and applications of plants at different scales (organ, tissue, and cell)

, figureFileSmall=null, figureFileBig=null, tableContent=

尺度	植物物种	方法	应用部位	参考文献
器官	水稻(Oryza sativa)	Micro-CT	茎	吴迪, 2019
	银杏(Ginkgo biloba)、拟南芥(Arabidopsis thaliana)和榆树(Ulmus pumila)	Micro-CT、LSFM、Auto CUTS-SEM和X-CT	种子	马灵玉, 2021; 祁晓红, 2022; Ma et al., 2024
	柑橘(Citrus reticulata ‘Bu Zhi Huo’)、苹果(Malus pumila)、梨(Pyrus spp.)、茄子(Solanum melongena)、萝卜(Raphanus sativus)和葡萄(Vitis vinifera)	X-CT	果实	Herremans et al., 2014; Nugraha et al., 2019; Janssen et al., 2020; Van de Looverbosch et al., 2020; 蔡健荣等, 2024
	拟南芥(A. thaliana)和大麦(Hordeum vulgare)	X-CT	花	Ijiri et al., 2014; Tracy et al., 2017; Xiao et al., 2021
组织	雪松(Cedrus deodara)、苹果(M. pumila)和月季(Rosa hybrida)	FIB-SEM和X-CT	输导组织	Herppich et al., 2015; Herremans et al., 2015; Nugraha et al., 2019; 王静等, 2022
	拟南芥(A. thaliana)	CLSM	分生组织	Gómez-Felipe and de Folter, 2019
	橡树(Quercus palustris)	X-CT	保护组织	Morisset et al., 2012
	橡树(Q. palustris)	CLSM和X-CT	营养组织	Fink, 2006; Morisset et al., 2012
细胞	拟南芥(A. thaliana)、狗尾草(Setaria viridis)、青杄(Picea wilsonii)、红松(Pinus densiflora)和黑松(P. thunbergii)	ODT、ssTEM、 FIB-SEM和CLSM	叶肉细胞、花粉粒细胞、下胚轴细胞和雄蕊细胞	Jackson et al., 2017; Kim et al., 2018; Cui et al., 2019; Wang et al., 2020; Silveira et al., 2022; Zechmann et al., 2022; Guo et al., 2023; Yamakawa et al., 2023; Collevatti et al., 2024; Hu et al., 2024

), ArticleFig(id=1321852272359883521, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, language=CN, label=表1, caption=

植物不同尺度(器官、组织和细胞)三维重建成像方法与应用

, figureFileSmall=null, figureFileBig=null, tableContent=

尺度	植物物种	方法	应用部位	参考文献
器官	水稻(Oryza sativa)	Micro-CT	茎	吴迪, 2019
	银杏(Ginkgo biloba)、拟南芥(Arabidopsis thaliana)和榆树(Ulmus pumila)	Micro-CT、LSFM、Auto CUTS-SEM和X-CT	种子	马灵玉, 2021; 祁晓红, 2022; Ma et al., 2024
	柑橘(Citrus reticulata ‘Bu Zhi Huo’)、苹果(Malus pumila)、梨(Pyrus spp.)、茄子(Solanum melongena)、萝卜(Raphanus sativus)和葡萄(Vitis vinifera)	X-CT	果实	Herremans et al., 2014; Nugraha et al., 2019; Janssen et al., 2020; Van de Looverbosch et al., 2020; 蔡健荣等, 2024
	拟南芥(A. thaliana)和大麦(Hordeum vulgare)	X-CT	花	Ijiri et al., 2014; Tracy et al., 2017; Xiao et al., 2021
组织	雪松(Cedrus deodara)、苹果(M. pumila)和月季(Rosa hybrida)	FIB-SEM和X-CT	输导组织	Herppich et al., 2015; Herremans et al., 2015; Nugraha et al., 2019; 王静等, 2022
	拟南芥(A. thaliana)	CLSM	分生组织	Gómez-Felipe and de Folter, 2019
	橡树(Quercus palustris)	X-CT	保护组织	Morisset et al., 2012
	橡树(Q. palustris)	CLSM和X-CT	营养组织	Fink, 2006; Morisset et al., 2012
细胞	拟南芥(A. thaliana)、狗尾草(Setaria viridis)、青杄(Picea wilsonii)、红松(Pinus densiflora)和黑松(P. thunbergii)	ODT、ssTEM、 FIB-SEM和CLSM	叶肉细胞、花粉粒细胞、下胚轴细胞和雄蕊细胞	Jackson et al., 2017; Kim et al., 2018; Cui et al., 2019; Wang et al., 2020; Silveira et al., 2022; Zechmann et al., 2022; Guo et al., 2023; Yamakawa et al., 2023; Collevatti et al., 2024; Hu et al., 2024

), ArticleFig(id=1321852272456352514, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, language=EN, label=Table 2, caption=

Comparative analysis of six common 3D reconstruction imaging methods in plants

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方法	分辨率	成像速度	样品制备	定位水平	参考文献
LSCM	200-500 nm	秒级/分级, 快	需荧光标记和透明化处理	细胞、亚细胞和分子水平	李叶等, 2015; 李成辉等, 2020; 路姣等, 2023
X-CT	250 μm以下	分级, 较快	需稳定固定	器官、组织、细胞和亚细胞水平	Du et al., 2019; Piovesan et al., 2021; Karahara et al., 2023
Micro-CT	50 μm以下	分级/小时级, 较快, 越精细越慢且越清晰	采用冷冻或化学固定	器官、组织、细胞和亚细胞水平	Wang et al., 2018; Karahara et al., 2023
ODT	200-600 nm	秒级/分级, 快	无需荧光标记, 透明化处理	器官、组织、细胞和亚细胞水平	He et al., 2023; Zhou et al., 2023
FIB-SEM	1-10 nm	小时级, 慢	制备方法复杂, 常温树脂包埋方法、高压冷冻及冷冻等	细胞及亚细胞水平	Heymann et al., 2006; Wei et al., 2012; 贾星等, 2022
TEM	0.1-2 nm	小时级, 慢	化学固定、常温脱水、包埋、切片、染色后观察	细胞、亚细胞、分子和原子水平	Drummy et al., 2004; 李斗星, 2004

), ArticleFig(id=1321852272577987331, tenantId=1146029695717560320, journalId=1316781310003478668, articleId=1321852266265559753, language=CN, label=表2, caption=

植物中6种常见的三维重建成像方法比较分析

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方法	分辨率	成像速度	样品制备	定位水平	参考文献
LSCM	200-500 nm	秒级/分级, 快	需荧光标记和透明化处理	细胞、亚细胞和分子水平	李叶等, 2015; 李成辉等, 2020; 路姣等, 2023
X-CT	250 μm以下	分级, 较快	需稳定固定	器官、组织、细胞和亚细胞水平	Du et al., 2019; Piovesan et al., 2021; Karahara et al., 2023
Micro-CT	50 μm以下	分级/小时级, 较快, 越精细越慢且越清晰	采用冷冻或化学固定	器官、组织、细胞和亚细胞水平	Wang et al., 2018; Karahara et al., 2023
ODT	200-600 nm	秒级/分级, 快	无需荧光标记, 透明化处理	器官、组织、细胞和亚细胞水平	He et al., 2023; Zhou et al., 2023
FIB-SEM	1-10 nm	小时级, 慢	制备方法复杂, 常温树脂包埋方法、高压冷冻及冷冻等	细胞及亚细胞水平	Heymann et al., 2006; Wei et al., 2012; 贾星等, 2022
TEM	0.1-2 nm	小时级, 慢	化学固定、常温脱水、包埋、切片、染色后观察	细胞、亚细胞、分子和原子水平	Drummy et al., 2004; 李斗星, 2004

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