水稻根系三维建模及可视化方法研究进展

吴盼盼; 唐子宗; 杨乐; 彭军; 张欢欢; 施俊林

doi:10.19303/j.issn.1008-0384.2021.08.015

水稻根系三维建模及可视化方法研究进展

doi: 10.19303/j.issn.1008-0384.2021.08.015

吴盼盼^1,,
唐子宗¹,
杨乐^{1, 2, ,},
彭军¹,
张欢欢¹,
施俊林¹

1.
江西农业大学计算机与信息工程学院，江西　南昌　330045
2.
江西省高等学校农业信息技术重点实验室，江西　南昌　330045

基金项目: 国家自然科学基金项目（61862032）；江西省自然科学基金项目（20202BABL202034）；江西省研究生创新专项资金项目（YC2021-S347）

详细信息

作者简介:
吴盼盼（1996−），女，硕士研究生，研究方向：农业信息技术（E-mail：1376068702@qq.com）

通讯作者:
杨乐（1979−），男，副教授，研究方向：深度学习在农业领域的应用研究（E-mail：jxnzhyangle@163.com）

中图分类号: S 511
计量
- 文章访问数: 1511
- HTML全文浏览量: 359
- PDF下载量: 104
- 被引次数: 0
出版历程
- 收稿日期: 2021-04-01
- 修回日期: 2021-07-23
- 网络出版日期: 2021-08-10
- 刊出日期: 2021-08-28

Visualization of Rice Root System by 3D Modeling: A Review

1.
College of Computer Information and Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi　330045, China
2.
Key Laboratory of Information Technology in Agriculture for Colleges and Universities in Jiangxi Province, Jiangxi Agriculture University, Nanchang, Jiangxi　330045, China

摘要

摘要: 根系是水稻获取养分的主要器官，水稻根系三维建模及可视化有助于进一步了解其根系的形态、结构和功能。随着计算机视觉和非侵入性技术的不断发展，根系形态和功能研究已进入数字化和可视化的阶段。近年来许多研究者分别从制作出土根系手绘图、计算机断层扫描（CT）等非侵入性技术、数学建模以及仿真模拟等方面推进水稻根系三维建模及可视化的研究。根系数据的获取是三维建模的有效前提，根据是否破坏根系原有生长环境，根系数据探测被分为破坏性探测和原位探测两类，本文对比分析了两种探测方式的方法和特点。从人工观察测量、机器视觉、光学仪器或断层扫描的三维数字化等方面对水稻根系的三维建模进行了阐述，总结了水稻根系三维建模及可视化的研究进展，并对当下主流三维重构技术进行分类和对比，总结了不同根系三维重构方法在重建效果、成本、操作水平等方面的优劣势。此外，由于根系生长在复杂多变的土壤环境中，不同时期根系的生长发育受土壤紧实度，水分、养分分布等因素的影响而存在差异，且受限于土壤的不透明和不稳定性，更多水稻根系的三维建模研究主要停留在根系基本指标与非环境因素（如土层深度、时间）的统计拟合及单环境因子对水稻根系生理生态的影响上，而根系与多环境因子动态交互方面的研究较少。在高度非结构化的根系数据处理困难的情况下，探究水稻根系与环境的动态转化过程及根系生长与多环境因子的定量关系模型将成为未来根系三维建模研究的重要方向，为构建更具真实意义的可视化模型提供基础。
- 水稻根系 /
- 探测方法 /
- 三维重构 /
- 环境-根系模型
Abstract: As an organ that extracts water and nutrients from the soil, the root system is vital for a rice plant. Establishing a 3D model to visualize the system structure can materially help the studies on the morphology and functional traits of the roots. Recent advancements in the computerized and non-invasive technologies make the information digitization for scientific research increasingly accessible and significant progresses possible. For instance, utilizing hand drawings and computer tomography (CT), mathematical models were built to vividly simulate the configuration of unearthed root system. Since data acquisition that proceeds model building is essential for an accurate and reliable representation, this article compares and analyzes the principles and characteristics of two classes of detection methods for information collection on the root systems. These methods can be either destructive or in-situ in applications depending upon whether or not the original growth environment was interrupted or destroyed. The 3D modeling and visualization of rice root system is explained in this article from the aspects of manual observation and measurement, machinery vision, 3D digitization by optical instruments, and tomography, etc. The mainstream reconstruction technologies are classified, compared, and analyzed with respect to the pros and cons on the resulting effect as well as the cost and ease of operation. Since environmental conditions are ever-changing, the development of a root system is invariably complex and varied. The affecting factors include the firmness, moisture content, and nutrients distribution of the soil a plant grows on. In addition, the non-transparency and instability of soil has so far hindered the related studies and confined to the fundamental and non-environmental elements, such as, depth of layer and time, for statistical analysis. Consequently, few reports dealt with the dynamic interactions among the multi-environmental factors that effect on the root development are available. Evidently, in the foreseeable future, the newly developed modeling and visualization technologies would usher in innovative applications and deep understanding in the field of study.
- Rice root system /
- detection method /
- 3D reconstruction /
- root system-environment model

HTML全文

图 1 根系节间单位模式

Figure 1. Unit pattern of root internodes

下载: 全尺寸图片幻灯片

图 2 水稻根系构成

Figure 2. Schematic root system of rice plant

下载: 全尺寸图片幻灯片

图 3 基于形态参数构建的水稻根系生长30、60 d生长模拟可视化图

Figure 3. Visualization of root growth simulation for 30 and 60 d based on morphological parameters

下载: 全尺寸图片幻灯片

表 1 不同方法在根系数据探测的优缺点

Table 1. Pros and cons of detection methods for data acquisition on rice root system

根系探测方式 Detecting methods	方法名称 Method name	优点 Advantages	缺点 Disadvantages
破坏性探测 Destructive detection	挖掘法 Excavation method^{[15−16 ]}	所获数据真实 Data obtained authentic	难以保证根系的完整性，末梢数据精准度有待考量 Ensure difficultly the integrity of roots, low accuracy of terminal data
	保护挖掘清洗法 Protect the excavation cleaning method ^[17]	一定程度上保证根系的完整性和有序性 Ensure the integrity and order of root system to a certain extent	细节还原度不高，末梢数据精准度有待考量 Low detail reduction, low accuracy of terminal data
	染色扫描图像分析法 Staining scanning image analysis^[18]	可获得细微处的拓扑结构信息 Subtle topology information can be obtained	有设备要求，操作过程繁琐 Equipment requirements, cumbersome operation process
原位探测 In-situ detection	土壤留置法 Soil retention method^[19−20]	可获得连续生长的根系数据 Root data of continuous growth can be obtained	扫描范围有限，仅能获取管壁周围的局部信息 Limited scanning range, only obtained local information around the pipe
	特殊培养环境法 Special culture environment method^[21−24]	根系的生长发育全过程透明可见 The whole process of root growth and development is transparent and visible	根脱离了自然土壤，生长发育可能存在较大差异 The root is separated from the natural soil, and there may be great differences in growth and development
	穿透射线成像法 Penetrating ray imaging ^[25−28]	数据精准，操作方便，效率较高 Accurate data, convenient operation, high efficiency	对设备要求高，成本昂贵 High requirements for equipment and high cost
	作物图像解析法 Crop image analysis^[12−14]	高效、自动和准确性高 High efficiency, automation and accuracy	照片获取过程费时费力，数据量大 Time-consuming and laborious photo acquisition process, large amount of data

下载: 导出CSV

表 2 常见的植物根系三维重建方法的比较

Table 2. Comparison of commonly available 3D reconstruction methods on root system of plants

三维重构方法 3D reconstruction methods	重建效果 Reconstruction effect	材料成本 Material cost	优点 Advantages	缺点 Disadvantages
L-系统 L-System^{[19, 21, 36−38]}	缺乏根系细节描述 Lack of root detail description	低 Low	逼真地描述根系生长过程，可用于模拟根-根、根-环境的相互作用 Describe the root growth process realistically, can be used to simulated the interaction of root-root , root-environment	文法规则与实际有一定偏差 A certain degree of deviation deviation between grammar rules and reality
CT、雷达 CT^{[25, 28]}、Radar ^[48]	较精确 More-precision	高 High	不受外界光照影响，重建精度较高 Not affected by outside light, higher reconstruction accuracy	成本昂贵，数据量大 High cost, large amount of data
结构光 Structural light^{[8, 44]}	较精确 More-precision	高 High	技术成熟，深度图像信息丰富 Technical maturity, rich in depth image information	易受光照影响，识别距离有限 Susceptible to light, limited recognition distance
多视觉图像 Multi-visual images^{[22, 40]}	精度高 High-precision	低 Low	能描述根部细节特征，有真实的色彩纹理 Describe the root detail characteristics, with a real color texture	易受环境影响，结构复杂的根数据获取困难 Susceptible to environment, difficulty in obtaining complex root data
双目立体视觉 Binocular stereo vision^[49−50]	精度一般 Middle-precision	适中 Middle	重建效果稳定 Stable reconstruction effect	相机严格标定，点云数据匹配困难，须根系细节处理效果一般 Camera calibrated strictly, point cloud data matched difficultly, fibrous root system detail processing effect is general

下载: 导出CSV

参考文献(61)

[1]	SAMYOR D, DAS A B, DEKA S C. Pigmented rice a potential source of bioactive compounds: A review [J]. International Journal of Food Science & Technology, 2017, 52(5): 1073−1081.
[2]	SMITH S, DE SMET I. Root system architecture: Insights from Arabidopsis and cereal crops [J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2012, 367(1595): 1441−1452. doi: 10.1098/rstb.2011.0234
[3]	KRESZIES T, SCHREIBER L, RANATHUNGE K. Suberized transport barriers in Arabidopsis, barley and rice roots: From the model plant to crop species [J]. Journal of Plant Physiology, 2018, 227: 75−83. doi: 10.1016/j.jplph.2018.02.002
[4]	赵春江, 陆声链, 郭新宇, 等. 数字植物研究进展: 植物形态结构三维数字化 [J]. 中国农业科学, 2015, 48(17):3415−3428. doi: 10.3864/j.issn.0578-1752.2015.17.009 ZHAO C J, LU S L, GUO X Y, et al. Advances in research of digital plant: 3D digitization of plant morphological structure [J]. Scientia Agricultura Sinica, 2015, 48(17): 3415−3428.(in Chinese) doi: 10.3864/j.issn.0578-1752.2015.17.009
[5]	黄伟. 基于植物生长过程仿真的虚拟植物建模研究[D]. 重庆: 重庆大学, 2011. HUANG W. Study on growth modeling of virtual plant based on simulation of growth process[D]. Chongqing: Chongqing University, 2011. (in Chinese).
[6]	温维亮, 郭新宇, 赵春江, 等. 作物根系构型三维探测与重建方法研究进展 [J]. 中国农业科学, 2015, 48(3):436−448. doi: 10.3864/j.issn.0578-1752.2015.03.04 WEN W L, GUO X Y, ZHAO C J, et al. Crop roots configuration and visualization: A review [J]. Scientia Agricultura Sinica, 2015, 48(3): 436−448.(in Chinese) doi: 10.3864/j.issn.0578-1752.2015.03.04
[7]	尤号田, 邢艳秋, 彭涛, 等. LiDAR不同强度校正法对樟子松叶面积指数估测的影响 [J]. 测绘学报, 2018, 47(2):170−179. doi: 10.11947/j.AGCS.2018.20170515 YOU H T, XING Y Q, PENG T, et al. Effects of different LiDAR intensity normalization methods on Scotch pine forest leaf area index estimation [J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(2): 170−179.(in Chinese) doi: 10.11947/j.AGCS.2018.20170515
[8]	梁欢, 顾庆毅. 一种基于结构光的运动补偿3D测量方法: CN106595502A[P]. 2017-04-26.
[9]	周静静, 郭新宇, 吴升, 等. 基于多视角图像的植物三维重建研究进展 [J]. 中国农业科技导报, 2019, 21(2):9−18. ZHOU J J, GUO X Y, WU S, et al. Research progress on plant three-dimensional reconstruction based on multi-view images [J]. Journal of Agricultural Science and Technology, 2019, 21(2): 9−18.(in Chinese)
[10]	翁杨, 曾睿, 吴陈铭, 等. 基于深度学习的农业植物表型研究综述 [J]. 中国科学: 生命科学, 2019, 49(6):698−716. doi: 10.1360/SSV-2019-0020 WENG Y, ZENG R, WU C M, et al. A survey on deep-learning-based plant phenotype research in agriculture [J]. Scientia Sinica (Vitae), 2019, 49(6): 698−716.(in Chinese) doi: 10.1360/SSV-2019-0020
[11]	DIEVART A, COUDERT Y, GANTET P, et al. Dissecting the biological bases of traits of interest in rice: Architecture and development of the root system [J]. Cahiers Agricultures, 2013, 22(5): 475−483. doi: 10.1684/agr.2013.0651
[12]	STEFANELLI D, FRIDMAN Y, PERRY RL. DigiRoot^TM: New software for root studies [J]. European Journal of Horticultural Science, 2009, 74(4). doi: 10.2307/24126478
[13]	DELORY B M, BAUDSON C, BROSTAUX Y, et al. archiDART: an R package for the automated computation of plant root architectural traits [J]. Plant and Soil, 2016, 398(1/2): 351−365.
[14]	GONZÁLEZ A, SEVILLANO X, BETEGÓN-PUTZE I, et al. MyROOT 2.0: An automatic tool for high throughput and accurate primary root length measurement [J]. Computers and Electronics in Agriculture, 2020, 168: 105125. doi: 10.1016/j.compag.2019.105125
[15]	TRACHSEL S, KAEPPLER S M, BROWN K M, et al. Shovelomics: high throughput phenotyping of maize (Zea mays L.) root architecture in the field [J]. Plant and Soil, 2011, 341(1/2): 75−87.
[16]	胡琪娟, 王霖娇, 盛茂银. 植物细根生产和周转研究进展 [J]. 世界林业研究, 2019, 32(2):29−34. HU Q J, WANG L J, SHENG M Y. Research progress of plant fine root production and turnover [J]. World Forestry Research, 2019, 32(2): 29−34.(in Chinese)
[17]	管建慧, 郭新宇, 王纪华, 等. 玉米不同部位根系生长发育规律的研究 [J]. 玉米科学, 2007, 15(6):82−85, 88. doi: 10.3969/j.issn.1005-0906.2007.06.019 GUAN J H, GUO X Y, WANG J H, et al. Study on growth and development rule of different parts of maize root [J]. Journal of Maize Sciences, 2007, 15(6): 82−85, 88.(in Chinese) doi: 10.3969/j.issn.1005-0906.2007.06.019
[18]	WU J, GUO Y. An integrated method for quantifying root architecture of field-grown maize [J]. Annals of Botany, 2014, 114(4): 841−851. doi: 10.1093/aob/mcu009
[19]	杨乐, 彭军, 杨红云, 等. 基于微分L-系统的水稻根系三维生长模型研究 [J]. 农业机械学报, 2019, 50(10):208−214. doi: 10.6041/j.issn.1000-1298.2019.10.023 YANG L, PENG J, YANG H Y, et al. Three dimensional growth modeling of rice root based on differential L-system [J]. Transactions of the Chinese Society for Agricultural Machinery, 2019, 50(10): 208−214.(in Chinese) doi: 10.6041/j.issn.1000-1298.2019.10.023
[20]	牛学礼, 南志标. 运用微根管技术研究草地植物细根的进展 [J]. 草业学报, 2017, 26(11):205−215. doi: 10.11686/cyxb2017041 NIU X L, NAN Z B. Review of minirhizotron applications for study of fine roots in grassland [J]. Acta Prataculturae Sinica, 2017, 26(11): 205−215.(in Chinese) doi: 10.11686/cyxb2017041
[21]	YANG L, WU P P, YANG S Y, et al. Research on the construction and visualization of a three-dimensional model of rice root growth [J]. Applied Engineering in Agriculture, 2020, 36(6): 847−857. doi: 10.13031/aea.13543
[22]	HAN T H, KUO Y F. Developing a system for three-dimensional quantification of root traits of rice seedlings [J]. Computers and Electronics in Agriculture, 2018, 152: 90−100. doi: 10.1016/j.compag.2018.07.001
[23]	FANG S Q, YAN X L, LIAO H. 3D reconstruction and dynamic modeling of root architecture in situ and its application to crop phosphorus research [J]. The Plant Journal, 2009, 60(6): 1096−1108. doi: 10.1111/j.1365-313X.2009.04009.x
[24]	ROGERS E D, MONAENKOVA D, MIJAR M, et al. X-ray computed tomography reveals the response of root system architecture to soil texture [J]. Plant Physiology, 2016, 171(3): 2028−2040. doi: 10.1104/pp.16.00397
[25]	TERAMOTO S, TAKAYASU S, KITOMI Y, et al. High-throughput three-dimensional visualization of root system architecture of rice using X-ray computed tomography [J]. Plant Methods, 2020, 16: 66. doi: 10.1186/s13007-020-00612-6
[26]	GERTH S, CLAUßEN J, EGGERT A, et al. Semiautomated 3D root segmentation and evaluation based on X-ray CT imagery [J]. Plant Phenomics, 2021, 2021: 1−13.
[27]	向子云, 罗锡文, 周学成, 等. 多层螺旋CT三维成像技术观测植物根系的实验研究 [J]. CT理论与应用研究, 2006, 15(3):1−5. doi: 10.3969/j.issn.1004-4140.2006.03.001 XIANG Z Y, LUO X W, ZHOU X C, et al. Experimental study on observation of original shape of crop root system with multi helical CT technology [J]. Computerized Tomography Theory and Applications, 2006, 15(3): 1−5.(in Chinese) doi: 10.3969/j.issn.1004-4140.2006.03.001
[28]	周学成, 罗锡文, 严小龙, 等. 基于遗传算法的原位根系CT图像的模糊阈值分割 [J]. 中国图象图形学报, 2009, 14(4):681−687. doi: 10.11834/jig.20090418 ZHOU X C, LUO X W, YAN X L, et al. A fuzzy thresholding segmentation for plant root CT images based on genetic algorithm [J]. Journal of Image and Graphics, 2009, 14(4): 681−687.(in Chinese) doi: 10.11834/jig.20090418
[29]	TOPP C N, IYER-PASCUZZI A S, ANDERSON J T, et al. 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture [J]. PNAS, 2013, 110(18): E1695−E1704. doi: 10.1073/pnas.1304354110
[30]	KUTSAHERA L. Wurzelatlas mitteleuropaischer ackerunkrauter und kulturpflanzen [J]. Economic Botany, 1963, 17(2): 158−159. doi: 10.2307/4252435
[31]	PAGÈS L, VERCAMBRE G, DROUET J L, et al. Root Typ: A generic model to depict and analyse the root system architecture [J]. Plant and Soil, 2004, 258(1): 103−119. doi: 10.1023/B:PLSO.0000016540.47134.03
[32]	PAGES L, MOREAU D, SARLIKIOTI V, et al. ArchiSimple: A parsimonious model of the root system architecture[C]. //Plant Growth Modeling, Simulation, Visualization and Applications.:Institute of Electrical and Electronics Engineers, 2012:297-303.
[33]	徐其军, 汤亮, 顾东祥, 等. 基于形态参数的水稻根系三维建模及可视化 [J]. 农业工程学报, 2010, 26(10):188−194. doi: 10.3969/j.issn.1002-6819.2010.10.032 XU Q J, TANG L, GU D X, et al. Architectural parameter-based three dimensional modeling and visualization of rice roots [J]. Transactions of the Chinese Society of Agricultural Engineering, 2010, 26(10): 188−194.(in Chinese) doi: 10.3969/j.issn.1002-6819.2010.10.032
[34]	房燕. 基于人工生命的骆驼刺根系的模型构建与研究[D]. 长春: 东北师范大学, 2011. FANG Y. Construction and research of Alhagi roots model based on artificial life[D]. Changchun: Northeast Normal University, 2011. (in Chinese).
[35]	GE Y, GE Z Y, YI H F, et al. Visual simulation of upland rice root as related to soil compaction[C]//2011 Second International Conference on Digital Manufacturing & Automation. August 5-7, 2011, Zhangjiajie, China. IEEE, 2011: 1392−1394.
[36]	LEITNER D, KLEPSCH S, BODNER G, et al. A dynamic root system growth model based on L-Systems [J]. Plant and Soil, 2010, 332(1/2): 177−192.
[37]	钟南, 罗锡文, 秦琴. 基于微分L系统理论的植物根系生长模拟的算法 [J]. 系统仿真学报, 2006, 18(S2):138−139, 143. ZHONG N, LUO X W, QIN Q. Simulation arithmetic of root systems growth with differential L-systems [J]. Journal of System Simulation, 2006, 18(S2): 138−139, 143.(in Chinese)
[38]	彭英, 张素兰. 基于L系统的水稻根系建模与可视化 [J]. 计算机系统应用, 2020, 29(6):22−28. PENG Y, ZHANG S L. L-system-based modeling and visualization of rice root system [J]. Computer Systems & Applications, 2020, 29(6): 22−28.(in Chinese)
[39]	刘慧, 汤亮, 张文宇, 等. 基于模型的可视化水稻生长系统的构建与实现 [J]. 农业工程学报, 2009, 25(9):148−154, 362. doi: 10.3969/j.issn.1002-6819.2009.09.027 LIU H, TANG L, ZHANG W Y, et al. Construction and implementation of model-based visual rice growth system [J]. Transactions of the Chinese Society of Agricultural Engineering, 2009, 25(9): 148−154, 362.(in Chinese) doi: 10.3969/j.issn.1002-6819.2009.09.027
[40]	初广丽, 张伟, 王延杰, 等. 基于机器视觉的水果采摘机器人目标识别方法 [J]. 中国农机化学报, 2018, 39(2):83−88. CHU G L, ZHANG W, WANG Y J, et al. A method of fruit picking robot target identification based on machine vision [J]. Journal of Chinese Agricultural Mechanization, 2018, 39(2): 83−88.(in Chinese)
[41]	徐超, 李乔. 基于计算机视觉的三维重建技术综述 [J]. 数字技术与应用, 2017(1):54−56. XU C, LI Q. 3D reconstruction technology based on computer vision: A Review [J]. Digital Technology and Application, 2017(1): 54−56.(in Chinese)
[42]	LOOMIS J J, LIU X W, DING Z H, et al. Visualization of plant growth[C]//Proceedings of Visualization '97 (Cat. No. 97CB36155). October 24-24, 1997, Phoenix, AZ, USA. IEEE, 1997: 475-478.
[43]	TERAMOTO S, UGA Y. A deep learning-based phenotypic analysis of rice root distribution from field images [J]. Plant Phenomics (Washington, D C), 2020, 2020: 3194308.
[44]	吴丹, 叶军立, 王康, 等. 基于轮廓投影的盆栽水稻三维重建方法研究 [J]. 中国农业科技导报, 2020, 22(9):87−95. WU D, YE J L, WANG K, et al. Three-dimension reconstruction method based on silhouette for pot rice [J]. Journal of Agricultural Science and Technology, 2020, 22(9): 87−95.(in Chinese)
[45]	SCHULZ H, POSTMA J A, VAN DUSSCHOTEN D, et al. Plant root system analysis from MRI images[M]//Communications in Computer and Information Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013: 411-425.
[46]	VAN DUSSCHOTEN D, METZNER R, KOCHS J, et al. Quantitative 3D analysis of plant roots growing in soil using magnetic resonance imaging [J]. Plant Physiology, 2016, 170(3): 1176−1188. doi: 10.1104/pp.15.01388
[47]	AHMED M A, ZAREBANADKOUKI M, KAESTNER A, et al. Measurements of water uptake of maize roots: The key function of lateral roots [J]. Plant and Soil, 2016, 398(1/2): 59−77.
[48]	刘秀位, 谷慧杰, 韩洁, 等. 基于探地雷达和电容法的作物根系原位无损测量技术研究进展 [J]. 农业工程学报, 2020, 36(20):226−237. doi: 10.11975/j.issn.1002-6819.2020.20.027 LIU X W, GU H J, HAN J, et al. Research progress of ground penetrating radar and electrical capacitance for in situ non-destructive measurement of crop roots [J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(20): 226−237.(in Chinese) doi: 10.11975/j.issn.1002-6819.2020.20.027
[49]	王传宇, 赵明, 阎建河, 等. 基于双目立体视觉技术的玉米叶片三维重建 [J]. 农业工程学报, 2010, 26(4):198−202. doi: 10.3969/j.issn.1002-6819.2010.04.033 WANG C Y, ZHAO M, YAN J H, et al. Three-dimensional reconstruction of maize leaves based on binocular stereovision system [J]. Transactions of the Chinese Society of Agricultural Engineering, 2010, 26(4): 198−202.(in Chinese) doi: 10.3969/j.issn.1002-6819.2010.04.033
[50]	殷悦, 张慧春, 郑加强. 基于双目立体视觉的植物三维重建系统 [J]. 中国农机化学报, 2021, 42(3):129−135. YIN Y, ZHANG H C, ZHENG J Q. Three dimensional reconstruction system of plant based on binocular stereo vision [J]. Journal of Chinese Agricultural Mechanization, 2021, 42(3): 129−135.(in Chinese)
[51]	SOMMA F, HOPMANS J W, CLAUSNITZER V. Transient three-dimensional modeling of soil water and solute transport with simultaneous root growth, root water and nutrient uptake [J]. Plant and Soil, 1998, 202(2): 281−293. doi: 10.1023/A:1004378602378
[52]	ZAPPALA S, MAIRHOFER S, TRACY S, et al. Quantifying the effect of soil moisture content on segmenting root system architecture in X-ray computed tomography images [J]. Plant and Soil, 2013, 370(1/2): 35−45.
[53]	DUNBABIN V M, POSTMA J A, SCHNEPF A, et al. Modelling root-soil interactions using three-dimensional models of root growth, architecture and function [J]. Plant and Soil, 2013, 372(1/2): 93−124.
[54]	张玉, 秦华东, 黄敏, 等. 水稻根系空间分布特性的数学模拟及应用 [J]. 华南农业大学学报, 2013, 34(3):304−308. doi: 10.7671/j.issn.1001-411X.2013.03.005 ZHANG Y, QIN H D, HUANG M, et al. Mathematical simulation of rice root spatial distribution and its application [J]. Journal of South China Agricultural University, 2013, 34(3): 304−308.(in Chinese) doi: 10.7671/j.issn.1001-411X.2013.03.005
[55]	刘永霞, 岳延滨, 刘岩, 等. 不同品种和氮肥条件下水稻根系主要几何参数动态量化 [J]. 中国农业科学, 2010, 43(9):1782−1790. doi: 10.3864/j.issn.0578-1752.2010.09.003 LIU Y X, YUE Y B, LIU Y, et al. Quantitative research of dynamic models of the main geometric parameters of rice root system of different varieties under different nitrogen conditions [J]. Scientia Agricultura Sinica, 2010, 43(9): 1782−1790.(in Chinese) doi: 10.3864/j.issn.0578-1752.2010.09.003
[56]	李娟, 章明清, 林琼, 等. 水稻根系氮磷钾吸收特性及其模拟模型研究 [J]. 土壤通报, 2011, 42(1):117−122. LI J, ZHANG M Q, LIN Q, et al. Studies on N, P and K absorption characteristics of rice root system and its simulation model [J]. Chinese Journal of Soil Science, 2011, 42(1): 117−122.(in Chinese)
[57]	LI T, ANGELES O, MARCAIDA M III, et al. From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments [J]. Agricultural and Forest Meteorology, 2017, 237/238: 246−256. doi: 10.1016/j.agrformet.2017.02.025
[58]	蒋艳娜, 肖伯祥, 郭新宇, 等. 植物建模与动画合成研究 [J]. 系统仿真学报, 2015, 27(4):881−892. JIANG Y N, XIAO B X, GUO X Y, et al. Study in plant modeling and animation [J]. Journal of System Simulation, 2015, 27(4): 881−892.(in Chinese)
[59]	贾全全, 杨晓杰. 根系分形维数及其研究进展 [J]. 安徽农业科学, 2011, 39(2):652−653, 656. doi: 10.3969/j.issn.0517-6611.2011.02.009 JIA Q Q, YANG X J. Fractal dimension and it's study extension to root systems [J]. Journal of Anhui Agricultural Sciences, 2011, 39(2): 652−653, 656.(in Chinese) doi: 10.3969/j.issn.0517-6611.2011.02.009
[60]	CLARK R T, MACCURDY R B, JUNG J K, et al. Three-dimensional root phenotyping with a novel imaging and software platform [J]. Plant Physiology, 2011, 156(2): 455−465. doi: 10.1104/pp.110.169102
[61]	ADELEKE E, MILLAS R, MCNEAL W, et al. Assessing root system architecture of wheat seedlings using A high-throughput root phenotyping system [J]. bioRxiv, 2019. doi: 10.1101/677955