Scanner-based Time-lapse Root Phenotyping

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Journal of Experimental Botany
May 2014



Non-destructive phenotyping of root system architecture can facilitate breeding for root traits that optimize resource acquisition. This protocol describes the construction of a low-cost, high-resolution root phenotyping platform, requiring no sophisticated equipment and adaptable to most laboratory and glasshouse environments. The phenotyping platform consists of germination paper abutting scanners and open-source image acquisition software which allows live imaging of root systems. The phenotyping platform is scalable, modular and inexpensive.

Keywords: Root system architecture (根系统的体系结构), Phenotyping (表型), Image analysis (图像分析), Brassica rapa (白菜), Soil nutrient (土壤养分)

Materials and Reagents

  1. Seeds of the plants to be investigated
    Note: We used seeds of Brassica rapa L.
  2. Nutrient solution (see Recipes)
    Note: Composition will depend on experimental requirements.


  1. Large (30 x 42 cm) and small (12 x 12 cm) steel blue Anchor seed germination paper (Anchor Paper Company, catalog number: SGB1924B) for phenotyping platform and seed germination, respectively
  2. Duct tape (office DEPOT)
  3. Ferrite magnetic strip with adhesive back (0.75 mm thick) (RS Components, catalog number: 297-9116)
  4. Square bioassay or petri dishes (120 mm x 120 mm x 17 mm) (Sigma-Aldrich, catalog number: Z617679)
    Note: This could be improvised with empty compact disc (CD) cases or any kind of transparent box that meets the specified dimensions.
  5. Black Perspex plates (21.5 x 30.0 cm) custom-made from opaque cast acrylic boards (Perspex Cast 9T30 Black Sheet) (plastock)
  6. Computer
    Note: This should be Windows-based and should have a directory with sufficient space to save images. In our platform, a Canon flatbed scanner imaging a root system at 300 dpi produces a single image of 40.2 MB. With 24 scanners in operation and images taken every 12 h, a minimum free space of approximately 30.0 GB is required for an experiment lasting 14 days. We used a Dell computer Intel® CoreTM i3-4150 Processor- Dual Core, 4 GB 1,600 MHz Memory and 500 GB Hard Drive for our experiments but images were saved on 2 TB WD external hard drive.
  7. Canon flatbed scanners (CanoScan, model: 5600F)
    Note: Any scanner with a TWAIN driver can be used. A TWAIN driver is software that comes as part of the software package of digital imaging devices such as scanners and cameras. The TWAIN driver provides an interface for communication between the software and the hardware of digital imaging devices ( In our platform, the TWAIN driver translated commands from our ArchiScan image acquisition software ( into instructions to control the hardware of the scanners.
    1. Setting up scanners
      1. Remove the cover of the scanner as shown in Figure 1.
      2. Attach magnetic strips to the short-edges of the scanner window (Figure 1B).
        Note: This is optional as duct tape could be used to hold plates to scanners.

        Figure 1. A. Original flatbed scanner. B. Modified flatbed scanner with cover detached.

  8. Support for germination paper
    1. Glue to the edges of the Perspex plates strips of Perspex (0.3 x 0.3 x 30 cm and 0.3 x 0.3 x 21.5 cm for the long-edges and short-edges of the Perspex plate, respectively).
      Note: This is to provide some separation between the plate and the scanners.
    2. Allow two gaps in the Perspex strips, each approximately 3 cm wide, along the long edge of the Perspex plates to allow gas exchange with the surrounding atmosphere and unimpeded shoot growth (Figure 2).
    3.  Fix magnetic strips along the two short-edges of the Perspex plate to aid abutting of the Perspex plate to the scanner window (optional).

      Figure 2. (A) Schematic representation of the Perspex plate used as a scanner cover and also to attach germination paper onto scanners. (B) Black Perspex plates used as scanner covers and also to hold germination paper vertically on scanner surfaces


  1. ImageJ (
  2. ArchiScan and ImageJ custom macros for convex hull and particle analyses (Adu et al., 2014; )
  3. SmartRoot (Lobet et al., 2011;


  1. Seed germination
    Note: This procedure was performed in a sterile hood, but the whole process was not necessarily sterile since scanners and tanks were not autoclaved and the experiments were not performed in a sterile room.
    1. Line the bottom of a square petri dish (12 x 12 cm) with paper towel.
      Note: Empty CD cases can be used instead of petri dishes.
    2. Cover the paper towel with a small germination sheet (12 x 12 cm).
    3. Spray the germination papers with deionized water.
    4. Put seeds on top of the wet seed germination paper. Allow each seed as much space as possible.
      Note: Seeds should be surface sterilised prior to germination. Brassica rapa seeds were surface sterilised for 10 min in 10% hydrogen peroxide, followed by 1 min in 70% ethanol, and then rinsed 3 times with deionised water.
    5. Place one layer of paper towels on top of the seeds.
    6. Spray the top layer of paper towels with deionized water.
    7. Place the lid on the petri dish and allow excess water to drain off by holding in a tilted position for about 30 sec.
    8. Cover the petri dish with aluminium foil.
    9. Place the petri dish in a vertical orientation in an incubator at 20 °C.

      Figure 3. Example of Brassica rapa seeds after 3 days of germination

  2. Transferring seedlings onto scanners
    1. Fix the top half of a large germination paper (30 x 42 cm; onto a Perspex plate.
      Note: Scanner surfaces were cleaned with Virkon® disinfectant ( Similarly, tanks and Perspex plates were thoroughly washed with Virkon® disinfectant and dried after each experiment. Slightly moistening the paper enables it to be fixed to the plate easily.
    2. Transfer seedlings of similar size with radicles 2-3 cm in length (Figure 3) to the large (30 x 42 cm) sheets of germination paper fixed to Perspex plates.
      1. Transfer two seedlings per plate.
      2. Ensure that about 0.5 cm of the small germination paper surrounding each radicle is cut and transferred with the seedling to the large germination papers to minimize disturbance during the transfer process. (Figure 21 shows a video of this).
      3. Use a moistened tissue or parafilm tape, just below the cotyledons, to stick the seedlings to the large germination papers.
        Note: Put the small germination paper that has been cut with the seedling on it at the top of the large germination paper and tape both to the large germination paper by putting the parafilm tape just below the cotyledons of the seedling. Alternatively, in the absence of parafilm tape, a damp, narrow strip of tissue paper (about 4 cm long) can be used to affix the seeds plus small germination paper to the large germination paper.
    3. Attach the assemblage of Perspex plate, large germination paper and seedlings to the scanners using magnetic strips fixed to the plates and scanner windows.
      Note: Duct tape can also be used hold the Perspex plate to the scanner (Figure 4).
    4. Position scanners in near-vertical positions 5 cm above 20 L of nutrient solution contained in opaque polyvinyl plastic tanks, each supplying six scanners (Figure 4).
      1. The first scanners put on the tank could lean against a wall to provide support and subsequent scanners can be stacked with each leaning against the previous one (Figure 4).
      2. Allow approximately 10 cm of the large germination paper to be submerged in the nutrient solution (Figure 4).
      3. Connect all scanners to the computer on which the ArchiScan software is installed using a USB hub with multiple ports. Connect scanners, computers and USB ports to a power supply.
        Note: You can use either one computer or multiple computers to control the scanners. The number of scanners per computer depends on the number of plants to be screened, duration of experiment, frequency of scanning and the computers’ storage capacity. In our experiments, there are occasions when up to 24 scanners are managed by one computer but we normally use 2 computers to control 24 scanners. On the latter occasions, each computer managed 12 scanners and scanners were connected to the computer using a D-Link USB Hub;; Misco number: 94282).

        Figure 4. A. Schematic representation of the pouch-and-wick system of a single scanner. Roots grow on the surface of germination paper held between a clear-Perspex plate and the glass window of a scanner. The scanner is fixed in near-vertical position 5 cm above 20 L of nutrient solution contained in opaque polyvinyl plastic tank. Approximately 10 cm of the germination paper is submerged in the nutrient solution (Adu et al., 2014). B. Phenotyping platform composed of a bank of six scanners.

  3. Time-lapse imaging of roots
    Run the image acquisition software, ArchiScan. ArchiScan is Windows-based software that provides an interface for managing multiple scanners and for simultaneous scanning of images. ArchiScan must be installed on a computer directory on which there is sufficient space to save images (Extended information on ArchiScan is found in the ‘READ ME’ pdf file at
    1. Input parameters of the new project including:
      Initial scanning time
      Note: This depends on experimental requirements. In this example, we began scanning at Time=0; Figure 5.
      Project duration
      Note: This is indicated by Number of Scans (Figure 5) and depends on the frequency of taking images and duration of experiment. e.g.: If images are taken every 24 hours and the experiment was to last 15 d, the number of scans would be 16.
      Time period between consecutive scans (Time between Scan; Figure 5)
      Note: In most of our experiments images are scanned every 12 h.

      Figure 5. ArchiScan interface for setting experiment parameters

    2. Set desired image parameters including (Figure 6)
      Colour (black and white, greyscale or red green blue-RGB channel images)
      Resolution (dot per inch-dpi)
      Scaling (percent)
      Frame size (x10, inch)
      File format (bmp, jpeg etc.)
      Note: For our experiments, the following parameters were used: Colour=RGB, Resolution = 300 dpi and default settings (Figure 6) were maintained for the remaining parameters.

      Figure 6. ArchiScan interface for setting image parameters

  4. Image segmentation and extraction of root features
    Image segmentation and extraction of root features from single root images or from a stack of time-lapse image sequences can be performed with ImageJ ( using custom macros that can be downloaded from Extraction of root features can also be done with a variety of software including SmartRoot (Lobet et al., 2011;

  5. Segmentation and extraction of root features using ImageJ
    Total root length:
    1. Total root length of a single image
      1. To process and analyse a single root image, open the image with ImageJ (File>Open; Figure 7) and proceed from point 3 below.

        Figure 7. To open a single image, open ImageJ and select File > Open. Navigate to your folder and select the image, then select OK.

    2. Total root length of a time-lapse stacked images to measure the rate of root length increase per unit time
      1. For each plant, import the image stack consisting of image sequences from the beginning to the end of an experiment into ImageJ (File>Import>Image Sequences; Figure 8).

        Figure 8. To import a sequence of images, open ImageJ and select File > Import > Image Sequence. Navigate to your folder and select the first image, then select OK. ImageJ will launch a sequence options dialog. The default values are usually appropriate but images could be resized here. We typically maintain the default 100% but checking the ‘Use Virtual Stack’ box opens images as a read-only virtual stack and allows image sequences too big to fit in RAM to be opened.

      2. Set the scale or images by indicating the correct relationship between distance in pixels and the desired unit of measurement before analyses (Analyse > Set Scale; Figure 9).

        Figure 9. To set the scale for your images, select Analyse > Set Scale (e.g.: for our images, we previously established that 118.5 pixels were equal to 1 cm). Checking the ‘Global’ box ensures that the set scale would apply to all images in the imported images sequences and to all subsequent sequences of images that will be imported as long as ImageJ remains opened.

      3. Convert RGB images to 8-bit greyscale images (depending on the quality of the images, they could also be split into the Red, Green or Blue colour channels and the best colour channel chosen for the analyses; Image>Type>8-bit; Image

        Figure 10. To Convert RGB images to 8-bit greyscale images, select Image>Type>8-bit or select Image<Colour Split Channels to split images into the Red, Green or Blue colour channels

      4. Filter with the median, followed by the Gaussian, filter to remove short range variations on the image (i.e. remove variations introduced by water droplets condensing at the surface of scanners or due to inhomogeneity of the surface of the germination paper; Process>Filter>Median; Process>Filter>Gaussian Blur; Figure 11).
        Note: The range of radii for filtering depends on the quality of the image but we typically use a range of 2-4.

        Figure 11. Select Process>Filter>Median, followed by Process>Filter>Gaussian Blur to remove short range artefacts on your image/images. A Median and Gaussian Blur options dialog box would be lunched for the radius and Sigma radius (Gaussian Blur) to be modified subject to the quality of your images.

      5. Use background subtraction to remove variations in pixel intensity over longer distances than the root diameter (long range variations are artefacts or inhomogeneities in the background that remain after short range variations have been removed and may be caused by non-uniform moisture content of the germination paper; Process>Subtract Background; Figure 12).
        Note: The range of radii for background subtraction depends on the quality of the image but we typically use a range of 40-50.

        Figure 12. Select Process>Subtract Background to remove long range artefacts on your images. A Subtract Background dialog box would be lunched. We normally modified the ‘Rolling ball’ radius to optimise the background subtraction.

      6. Auto-threshold with the Moment-preserving threshold algorithm.
        Note: depending on the quality of the image this algorithm may be suboptimal compared to other auto-threshold algorithms in ImageJ. Other algorithms could be tried or a second algorithm could be added; Image>Adjust>Auto threshold; Figure 13).

        Figure 13. Select Image>Adjust>Auto threshold to threshold images. An Auto Threshold dialog box will be lunched. We typically use the ‘Moments’ threshold method but other algorithms could be tried to select the most optimal for your images.

      7. Convert processed image to mask (Process>Binary>Convert to Mask; Figure 14, Figure 19).

        Figure 14. Select Process>Binary>Convert to convert processed image/images to mask

      8. Run particle analyses to measure root features of interest including the root perimeter from which the total root length can be calculated. Note: different size and circularity options might be tried to get the best results. Selecting Show>Outlines in the Particle Analyses pop up box will show the root perimeter and ticking the Display results box will show the measurement of all of the particles; Analyse>Analyse particles; Figure 15).

        Figure 15. Select Analyse>Analyse particles to measure root traits of interest. An Analyse Particles dialog box will be lunched for the Size and Circularity to be modified Note: circularity is a dimensionless shape descriptor which is a function of the object perimeter and the area and gives a measure of similarity between a given shape and a perfect circle. It ranges between 0-1. We typically used Size = 0.2 and Circularity = 0.00 -0.2. The results will be for a single image (if only one image was opened) or for sequence of images (if time-lapse stacked images were imported into ImageJ) from which rate of change in total root length per unit time can be calculated. 50% of the root perimeter = total root length.

        Area of roots:
      9. From #6, run Gaussian Blur filter again (Figure 11).
      10. Find the local maxima to select root pixels on the image (Process>Find Maxima; Figure 16).
        Note: This could be modified to optimise it for your images but we typically used noise=0 output=Point Selection and exclude edges.

        Figure 16. Select Process>Find Maxima to select root pixels on the image. A Find Maxima dialog box will be lunched. The Noise tolerance can be modified and we typically use the Point Selection Option.

      11. Fit Convex Hull (Edit>Selection>Convex Hull; Figure 17; Figure 19).

        Figure 17. Select Edit>Selection>Convex Hull to fit convex hull around images
        Note: Convex hulls are the smallest polygon whose vertices are all points in the image and define a rectangular selection that is the same size as the root system image.

      12. Measure the area of the hull (Analyse>Measure; Figure 18).

        Figure 18. Select Analyse>Measure to measure the area of the hull (Surface area of the root system)

        Figure 19. Sample image showing original root RGB image, segmented root image, perimeter or root for measuring root length and convex hull for measuring root area

        Figure 20. Representative data showing animated video of time-lapse segmented root system


  1. Nutrient solution

    Company (Catalogue No.)
    1 L Stock Solution
    20 L Nutrient Solution
    Reagent to add (g/L)
    Conc. (M)
    Volume of Stock to add (ml)
    Final Conc. (mM)
    VWR International (22388.292)
    VWR International (21278.295)
    VWR International (25165.292)
    VWR International (26668.296)

    VWR International (26936.293)
    VWR International (280233V)
    VWR International (22317.260)

    VWR International (20185.260)
    VWR International (27937.236)
    VWR International (29253.236)
    VWR International (ALFAB22081.22)
    VWR International (23174.233)

    Make up nutrient solution in 20 L deionised water and adjust to pH 6 using H2SO4.
    Note: Nutrient solution could be replaced or changed depending on experimental requirements. In our experiments we did not replace our solution for experiments that lasted up to 14 day. Nutrient solutions should ideally be changed for experiments of longer duration as there could be depletion of nutrients and/or growth of microorganisms in the solution. We also experienced fungal growth on the germination papers occasionally.
  2. Growth room requirements
    Day/night cycle: 16/8 h
    Temperature: 15 °C
    Light intensity during the day at plant height: 100 μmol/m2/s
    Relative humidity: 60%


This protocol was adapted from previous work Adu, 2014 and Adu et al., 2014. This work was supported by the Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government through Work Package 3.3, ‘The soil, water and air interface and its response to climate and land use change’ (2011-2016). Funding for this study was provided by a BBSRC Professorial Fellowship (to M. J. B.). M.O.A. was supported by the University of Nottingham Vice-Chancellor’s Scholarship for Research Excellence.


  1. Adu, M. O. (2014). Variations in root system architecture and root growth dynamics of Brassica rapa genotypes using a new scanner-based phenotyping system. Ph.D. Thesis. University of Nottingham: U.K.
  2. Adu, M. O., Chatot, A., Wiesel, L., Bennett, M. J., Broadley, M. R., White, P. J. and Dupuy, L. X. (2014). A scanner system for high-resolution quantification of variation in root growth dynamics of Brassica rapa genotypes. J Exp Bot 65(8): 2039-2048.
  3. Lobet, G., Pages, L. and Draye, X. (2011). A novel image-analysis toolbox enabling quantitative analysis of root system architecture. Plant Physiol 157(1): 29-39.


根系统结构的非破坏性表型可以促进优化资源获取的根性状的育种。 该协议描述了低成本,高分辨率根表型平台的构建,不需要复杂的设备,适应大多数实验室和温室环境。 表型平台包括发芽纸邻接扫描仪和开源图像采集软件,允许根系统的实时成像。 表型平台是可扩展的,模块化的和廉价的。

关键字:根系统的体系结构, 表型, 图像分析, 白菜, 土壤养分


  1. 待调查植物的种子
    注意:我们使用了Brassica rapa L.的种子。
  2. 营养液(见配方)


  1. 分别用于表型平台和种子发芽的大(30×42cm)和小(12×12cm)钢蓝色锚固种子发芽纸(Anchor Paper Company,目录号:SGB1924B)
  2. 胶带(办公室DEPOT
  3. 具有粘合剂背面(0.75 mm厚)的铁氧体磁条(RS组件,目录号:297-9116)
  4. 方形生物测定或培养皿(120mm×120mm×17mm)(Sigma-Aldrich,目录号:Z617679)
  5. 由不透明浇铸丙烯酸板(Perspex Cast 9T30黑色板)(plastock)定制的黑色有机玻璃板(21.5 x 30.0厘米)
  6. 电脑
    注意:这应该是基于Windows的,并且应该有一个目录具有足够的空间来保存图像。在我们的平台中,以300 dpi的根系统成像的佳能平板扫描仪产生40.2 MB的单个图像。使用24个扫描仪进行操作,每12小时拍摄一次图像,实验持续14天需要最少可用空间约30.0 GB。我们使用Dell计算机Intel ® Core TM i3-4150处理器双核,4 GB 1,600 MHz内存和500 GB硬盘驱动器进行实验,但图像保存在2 TB WD外部硬盘驱动器。
  7. 佳能平板扫描仪(CanoScan,型号:5600F)
    注意:可以使用具有TWAIN驱动程序的任何扫描仪。 TWAIN驱动程序是作为数字成像设备(例如扫描仪和相机)的软件包的一部分的软件。 TWAIN驱动程序为软件和数字成像设备的硬件之间的通信提供了一个接口( http: // )。在我们的平台中,TWAIN驱动程序将命令从我们的ArchiScan图像采集软件( http: / )转换为控制扫描仪硬件的指令。
    1. 设置扫描仪
      1. 如图1所示,取下扫描仪的盖子。
      2. 将磁条连接到扫描仪窗口的短边(图1B)。

        图1。 A.原始平板扫描仪。 B.改装平板扫描仪,盖子拆下。

  8. 支持发芽纸
    1. 对有机玻璃的有机玻璃板条的边缘进行胶粘(0.3 x 0.3 x 30厘米和0.3×0.3×21.5厘米的长边和短边 Perspex板)。
    2. 允许有机玻璃条中的两个间隙,每个约3厘米宽, 沿着Perspex板的长边,以允许与气体交换   周围大气和不受阻碍的枝条生长(图2)
    3.  沿着Perspex板的两个短边固定磁条 帮助将Perspex板连接到扫描仪窗口(可选)。

      图2.(A)用作a的有机玻璃板的示意图 扫描仪盖以及将发芽纸附接到扫描仪上。 (B) 黑色有机玻璃板用作扫描仪盖子和也举行发芽   纸张在扫描仪表面上垂直


  1. ImageJ(
  2. ArchiScan和ImageJ自定义宏用于凸包和粒子分析(Adu等人,2014;
  3. SmartRoot(Lobet 等人,2011;


  1. 种子发芽
    1. 线用方形培养皿(12×12厘米)的底部用纸巾。
    2. 用小发芽片(12 x 12厘米)盖住纸巾。
    3. 用去离子水喷洒发芽纸。
    4. 将种子放在湿的种子发芽纸的顶部。 允许每个种子尽可能多的空间。
      注意:种子应在萌发前进行表面灭菌。 芸苔属   芜菁种子在10%过氧化氢中表面灭菌10分钟,   然后在70%乙醇中1分钟,然后用3次冲洗 去离子水。
    5. 将一层纸巾放在种子的顶部。
    6. 用去离子水喷涂纸巾的顶层。
    7. 将盖子放在培养皿上,并在倾斜的位置保持约30秒钟以排出多余的水。
    8. 用铝箔覆盖培养皿。
    9. 将培养皿以垂直方向放置在20℃的培养箱中。

      图3. <3>发芽3天后的芸苔种子示例

  2. 将苗木转移到扫描仪上
    1. 将大发芽纸的上半部分(30 x 42厘米;固定到 有机玻璃板。 )。 同样,坦克和有机玻璃板也 用Virkon ® 消毒剂彻底清洗, 实验。 稍微润湿纸张使其能够固定在纸张上 板容易。
    2. 用幼根转移相似大小的幼苗 长度为2-3cm(图3)至大(30×42cm)片 发芽纸固定到Perspex板上。
      1. 每板转移两棵幼苗。
      2. 确保约0.5厘米的小发芽纸周围 每个胚根被切割并用秧苗转移至大 以减少转移过程中的干扰。 (图21显示了此视频)。
      3. 使用湿润的组织或parafilm胶带,紧挨着子叶,以将幼苗粘在大发芽的文件。
        注意:放入已切割的小发芽纸 幼苗在它的大发芽纸和磁带的顶部 通过将石蜡胶带放置在大的发芽纸上 幼苗的子叶。 或者,在不存在时 parafilm带,潮湿的窄条棉纸(约4cm长) 可用于将种子加小萌发纸贴在大块   发芽纸。
    3. 连接有机玻璃板的组合, 大发芽纸和幼苗使用磁性的扫描仪 固定到板和扫描仪窗口的条。
    4. 位置扫描仪在近垂直位置20厘米以上5厘米 营养液包含在不透明聚乙烯塑料罐中,每个 供应六台扫描仪(图4)
      1. 第一个扫描仪穿上 罐可以靠在墙上以提供支撑和随后 扫描仪可以堆叠,每个都倾斜前一个 (图4)。
      2. 使大约10cm的大发芽纸浸没在营养液中(图4)
      3. 将所有扫描仪连接到安装有ArchiScan软件的计算机 使用具有多个端口的USB集线器安装。连接扫描仪, 计算机和USB端口连接到电源。
        注意:您可以使用  一个计算机或多个计算机来控制扫描仪。号码 每台计算机的扫描器数量取决于要筛选的植物数量,  实验持续时间,扫描频率, 存储容量。在我们的实验中,有时候达24 扫描仪由一台计算机管理,但我们通常使用2台计算机 控制24台扫描仪。在后一种情况下,每台电脑管理12 扫描仪和扫描仪使用D-Link USB连接到计算机 枢纽;; Misco数:94282)。

        图4。 A. 单个袋和芯的系统的示意图 扫描器。根生长在萌发纸的表面上, clear-perspex板和扫描仪的玻璃窗。扫描仪 固定在接近垂直位置20厘米营养液5厘米 包含在不透明的聚乙烯塑料罐中。大约10厘米的 发芽纸浸没在营养液中(Adu等人, 2014)。 B.由六个扫描器的银行组成的表型平台。

  3. 根的延时成像
    运行图像采集软件 ArchiScan 。 ArchiScan 是基于Windows的软件,提供用于管理多个扫描仪和同时扫描图像的界面。 ArchiScan 必须安装在有足够空间保存图片的计算机目录上( ArchiScan 的扩展信息位于 )。
    1. 新项目的输入参数包括:
      注意:这取决于实验要求。在这个例子中,我们在时间= 0开始扫描;图5。
      注意:这由 扫描数量(图5)表示,取决于 拍摄图像的频率和实验的持续时间。 例如:If 图像每24小时拍摄,实验持续15天,   扫描次数为16.


    2. 设置所需的图像参数,包括(图6)
      颜色(黑白,灰度或红绿蓝 - RGB通道图像)
      文件格式(bmp,jpeg 等)
      注意:对于我们的实验,使用以下参数: 颜色= RGB,分辨率= 300 dpi和默认设置(图6) 维持其余参数。


  4. 根特征的图像分割和提取
    可以使用ImageJ (使用可从 http: 。根特征的提取也可以用包括 SmartRoot (Lobet 等人,2011; )。

  5. 使用 ImageJ
    分割和提取根功能 根总长度:
    1. 单个图像的总根长度
      1. 要处理和分析单个根图像,请使用ImageJ打开图像(文件>打开;图7),然后从以下第3点开始。

        图7.要打开单个图像,请打开ImageJ,然后选择文件> 打开。 导航到您的文件夹并选择图片,然后选择确定
    2. 延时堆积图像的总根长度以测量每单位时间的根长度增加的速率
      1. 对于每个植物,导入由图像序列组成的图像堆栈 从实验的开始到结束 ImageJ (文件>导入>图像序列;图8)。

        图8.要导入  图像序列,打开ImageJ并选择文件>导入>图片 序列。导航到您的文件夹,然后选择第一个图像 选择"确定"。 ImageJ将启动序列选项对话框。默认值 值通常是合适的,但图像可以在这里调整大小。我们 通常保持默认100%,但检查"使用虚拟堆栈"  框打开图像作为只读虚拟堆栈,并允许图像 序列太大,不适合打开RAM。

      2. 通过指示之间的正确关系来设置比例或图像 距离(以像素为单位)和分析前的所需测量单位 (分析>设置刻度;图9)

        图9.设置缩放 您的图片,选择分析>设置缩放(例如:对于我们的图片,我们 先前建立的118.5像素等于1厘米)。检查 "全局"框确保设置的比例将应用于中的所有图像  导入的图像序列以及只要ImageJ保持打开状态,将导入的所有后续图像序列
      3. 将RGB图像转换为8位灰度图像(取决于质量 的图像,它们也可以分为红色,绿色或蓝色 颜色通道和选择用于分析的最佳颜色通道; 图像>类型> 8位;图片

        图10.要将RGB图像转换为8位灰度图像,请选择图像>类型> 8位或选择图像<颜色分割通道将图像分割成红色,绿色或蓝色通道 />
      4. 用中值滤波,随后是高斯滤波,以去除短路   图像上的范围变化(即删除引入的变化) 水滴在扫描仪表面聚集或由于 发芽纸表面的不均匀性; 过程>过滤器>中间; 过程>过滤器>高斯模糊; 数字 11)。

        图11.选择过程>过滤器>中位数,后跟 过程>过滤器>高斯模糊以消除短程假象 您的图片/图片。一个中值和高斯模糊选项对话框 为半径和Sigma半径(高斯模糊)为午 根据您的图像质量进行修改。

      5. 使用背景减除来消除像素亮度的变化 比根直径更长的距离(长距离变化 人工制品或背景中的不均匀性 范围变化已经被去除并且可能由不均匀引起 发芽纸的水分含量; Process> Subtract 背景;图12)。

        图12.选择Process> Subtract Background删除远程 人工制品。 将减去背景对话框 午餐。我们通常修改"滚球"半径以优化 背景扣除。

      6. 使用保持时间阈值算法的自动阈值。
        注意:根据此算法可能的图像质量 与ImageJ中的其他自动阈值算法相比次优。其他 可以尝试算法或可以添加第二算法; 图像>调整>自动阈值; 图13)。

        图13.选择 图像>调整>自动阈值到阈值图像。 自动阈值   对话框将被午餐。 我们通常使用"时刻"阈值 方法,但其他算法可以尝试选择最优 为您的图像。

      7. 将处理的图像转换为掩码(处理>二进制>转换为掩码;图14,图19)。


      8. 运行粒子分析来测量感兴趣的根特征,包括  根周长,从中可以计算总根长度。 注意:可能会尝试使用不同的大小和圆形选项 最佳效果。在"粒子分析"弹出窗口中选择显示>轮廓  框将显示根周长,并勾选显示结果框 将显示所有颗粒的测量;分析>分析 粒子;图15)。

        图15.选择分析>分析 颗粒来测量感兴趣的根性状。 分析粒子 对话框将被清空以修改大小和圆形度 注意:圆度是一个无量纲形状描述符,它是一个 函数的对象周长和面积并给出一个度量 给定形状和正圆之间的相似性。它的范围  0-1。我们通常使用Size = 0.2和Circularity = 0.00 -0.2。的 结果将用于单个图像(如果只打开一个图像)或for  图像序列(如果延时堆叠图像导入 ImageJ),从每单位时间的总根长度的变化率  计算。根周长的50%=总根长度
      9. 从#6,再次运行高斯模糊滤波器(图11)。
      10. 找到局部最大值以选择图像上的根像素(过程>查找最大值;图16)。
        注意:这可以修改为优化它为您的图像,但我们 通常使用noise = 0 output =点选择和排除边缘。

        图16.选择Process> Find Maxima以选择根像素 。将显示"查找最大值"对话框。 噪声容差可以   修改,我们通常使用点选择选项
      11. Fit Corvex Hull(Edit> Selection> Convex Hull;图17;图19)。

        注意:凸包是顶点全为最小的多边形 点,并定义一个相同的矩形选择 大小作为根系统映像。

      12. 测量船体的面积(分析>测量;图18)。

        图18.选择Analyze> Measure来测量船体的面积(根系统的表面面积)

        图19.示例图像显示原始根RGB图像,分段根  图像,周长或根,用于测量根长度和凸包 测量根面积



  1. 营养液

    1 L库存解决方案
    20 L营养素溶液
    浓缩。 (M)
    Final Conc。 (mM)
    Ca(NO 3)/2。
    NH 4 3
    MgSO 4 4 / VWR国际(25165.292)

    KH 2 PO 4
    CaCl <2>

    H 3 BO 3
    Na MoO 4
    ZnSO 4
    MnSO 4
    CuSO 4

    补充营养溶液在20L去离子水中,并使用H 2 SO 4调节至pH 6。
    注意:营养液可以根据实验要求进行更换或更换。 在我们的实验中,我们没有替换我们的解决方案的实验,持续了14天。 对于更长持续时间的实验,营养物溶液应理想地改变,因为可能存在营养物的消耗和/或溶液中微生物的生长。 我们也偶尔遇到发芽纸上的真菌生长。
  2. 成长室要求
    日/夜周期:16/8 h
    白天在植物高度的光强度:100μmol/m 2 /s


该协议改编自以前的工作Adu,2014和Adu 等人,2014。这项工作由苏格兰政府通过工作包3.3的农村和环境科学和分析服务司(RESAS) ,"土壤,水和空气界面及其对气候和土地利用变化的反应"(2011-2016年)。这项研究的资金由BBSRC教授奖学金(给M. J. B.)提供。 M.O.A.由诺丁汉大学副校长奖学金为研究卓越的支持。


  1. Adu,M.O。(2014)。使用新的基于扫描仪的表型系统的根系统结构和根茎生长动力学的变化。博士论文。 University of Nottingham:U.K。
  2. Adu,M.O.,Chatot,A.,Wiesel,L.,Bennett,M.J.,Broadley,M.R.,White,P.J.and Dupuy,L.X。(2014)。 一种扫描仪系统,用于高分辨率量化芸苔根生长动力学的变化,/em>基因型。 65(8):2039-2048。
  3. Lobet,G.,Pages,L.and Draye,X。(2011)。 一种新颖的图像分析工具箱,可对根系统架构进行定量分析。 厂 Physiol 157(1):29-39。
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引用:Adu, M. O., Wiesel, L., Bennett, M. J., Broadley, M. R., White, P. J. and Dupuy, L. X. (2015). Scanner-based Time-lapse Root Phenotyping. Bio-protocol 5(6): e1424. DOI: 10.21769/BioProtoc.1424.