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May 2006

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Measuring and Imaging the Soil-root-water System with a Light Transmission 2D Technique
利用透光二维技术对土壤-根-水系统进行测定与成像   

Claude DoussanClaude Doussan* Emmanuelle GarriguesEmmanuelle Garrigues* (*共同第一作者)
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Abstract

Improving crops against water deficits requires a better understanding of plant root system functioning. This requires a better knowledge of the water uptake process and to address the influence of root system architecture or root physiological properties on the uptake efficiency. To this end, we describe here a non-destructive system that enables a dynamic, quantitative, functional imaging of the soil water and of the root system, from the single root to the whole root system scale.

This system is based on plants grown in sandy rhizotrons and relies on the modulation, by soil water content, of the intensity of light transmitted through the rhizotron. Images of the transmitted light during plant water uptake (or release) phases are recorded with a CCD camera and water content can be related to the grey level of image pixels with a calibration.

This system is affordable and can be implemented relatively easily without specific equipment. It is scalable and quick to allow the phenotyping of a range of plant genotypes relative to their water uptake pattern. This pattern can then be related with root system properties (soil colonization, root architecture) at different plant stages. Combined with modeling, imaging results help in getting parameters such as root hydraulic conductivity, distributed root water uptake rates or root xylem water potential. Combination of modeling and experiment further helps in testing biological and physiological assumptions and in predicting the uptake behavior of plants in the field.

Keywords: Imaging, Soil water, Roots, Architecture, Water uptake, Rhizotron

Background

During decades, detailed observation of water uptake by plant roots, as well as water flux trough roots and plants, has been technically challenging. Most of water uptake studies have been made by measuring soil water content variation with time. In the field, such measurements are based on the use of moisture sensors distributed in soil such as neutron moisture meter (Hignett and Evett, 2002) or electromagnetic TDR or capacitive sensors (Li et al., 2002). In a controlled condition, with potted plants, the weight of the pot can be used to determine pot water content. However, if these kinds of measurements are well suited to describe macroscopic soil water behavior, they do not give access to detailed distribution of water around roots and to the interactions for water between roots. Also, they do not reveal the distribution and functioning of roots.

Concomitantly to moisture measurements in the field, root distribution can be assessed destructively with core samples, trench wall profiling or less destructively with mini-rhizotron imaging (Smit et al., 2000). This gives access to a root distribution (of length, root impacts, biovolume) with depth. The variability in rooting needs generally to acquire a high number of samples, a difficult task as sampling/measurements are highly time and labor demanding.

Plant and root hydric relationships can be examined with a variety of measuring devices. Sap flow can be estimated in stems and coarse roots with heat balance sap flow meters (Granier, 1987); root hydraulic conductance can be estimated from root segments to root systems with tension induced measurements (North and Nobel, 1995), root pressure probe (Frensch and Steudle, 1989) or pressure cell (Miyamoto et al., 2001). Root water uptake flux at the single root level can be investigated with potometer (Sanderson, 1983), dye tracing (Varney and Canny, 1993).

All these methods deliver complementary information/properties of the water-soil-plant system, but most of the time, measurements have to be conducted on excised root segments, roots or root systems separated from soil, or for plants grown in hydroponics. They also combine information on roots which might not be similar (e.g., root type, age or order, location within the root system).

Imaging techniques allow the observation of living root systems and their interaction with soil without the need of excising or extracting them from soil. They also enable to quantify root architecture and growth, root type and age if measurements are repeated in time. Ideally, imaging technique shall enable not only root imaging but also other parameters such as water content. Different imaging techniques have been used to investigate the water-soil-root system these last years. They differ in their ability to resolve roots or water, the size of samples, the 2D or 3D description, the tractability and accessibility. X-ray scanning was first used in the pioneering work of Hainsworth and Aylmore (1983 and 1986). Since then, X-ray scanners highly increased in resolution, power and scanning speed as did image processing for roots tracking and segmentation in soil columns (Tracy et al., 2010). However, accurately quantifying water and roots in 3D soils is still a challenge (Zappala et al., 2013) as the technique shows almost the same response for water and roots, with a trade-off between resolution and size of the sample (Pierret et al., 2003a and 2003b). X-ray scanners are nowadays more accessible to soil/root researchers, but still not fully accessible and rather expensive. Magnetic resonance imaging (MRI), based on the H spin relaxation in a magnetic field, has shown high potentials for imaging soil and water (Pohlmeier et al., 2008) because of its high sensitivity to water. However, the rather low resolution necessitates relatively small samples. Some natural soils cause artifacts in RMN due to their magnetic properties. A long scanning time is needed for imaging while low accessibility and high price make this technique presently not readily available for soil-root water studies. Neutron radiography (and tomography) has been recently introduced for imaging roots and water (Nakanishi, 2005; Esser et al., 2010). The technique is based on the attenuation of a thermal neutron beam and is highly sensitive to H atoms and water. It enables the imaging of roots and water at high spatial resolution (0.1-0.5 mm) and high precision of the water content (1 to 5 x 10-3 m3.m-3). The technique requires however rather thin and small root boxes (rhizotron ~30 cm). The production of a neutron beam, together with imaging capabilities, is possible only in a few places around the world and makes it hardly available for routine measurements.

A more accessible approach to study the soil-water-root system is the light transmission imaging technique, described in details in Procedure B. Originally set for studying water infiltration instability in coarse sand porous media (Glass et al., 1989), the design has been adapted to allow plant growth in an adequate sandy substrate in rhizotrons and for getting time and spatial variations of soil water. These variations can then be linked to water uptake, in relation with root colonization and root system architecture (Garrigues, 2002; Garrigues et al., 2006). Making use of only rhizotron, camera and a light source, the technique is easily scalable for phenotyping a range of root systems in relation with water uptake properties (Lobet, 2013). Coupled with modeling and complementary data, the technique can give access to plant functions/properties such as the hydraulic properties of the root system, the root growth rate affected by water content…

It shall be noticed that all of the preceding imaging methods are adapted to the scanning of samples in the laboratory. In the field, Electrical resistivity tomography has a high potential for imaging soil water content and water uptake by crops with time (Srayeddin and Doussan, 2009) but presently no method is able to simultaneously image water and the roots in the soil. Root evaluation still mostly relies on destructive sampling for field studies.

Rationale of the technique:
The technique is based on attenuation of the light passing through a rhizotron, in which roots grow and take water up (Figure 1). The light attenuation is directly linked to the water content. The technique uses easily available materials, software programs and standard CCD cameras for imaging and is cost effective. As the measurement time is short, it enables a high temporal resolution. A high spatial resolution can also be achieved, on the order of 0.2-0.5 mm. The technique pipeline can be designed to allow for multiple rhizotrons scanning and monitoring over time, in order to phenotype a range of genotypes in relation with their water uptake/root soil colonization or root architecture properties (Lobet, 2013). The measurements can be qualitative (i.e., quantifying only differences of water through time or between plants) or quantitative with a calibration step.

However, the light imaging technique has also drawbacks: (i) Plant roots grow in a thin slab of soil and is more a 2D than 3D approach. (ii) As the soil volume is rather low and soil hydric properties are those from a sandy medium, processes related to water uptake in soil (e.g., water drawdown near root, water deficit) are accelerated/amplified compared to a natural 3D soil (depending on the climatic demand). (iii) The soil in the rhizotron is specific (sand + clay) to be translucent and the technique cannot be used with a natural, opaque, soil. (iv) Bulk density of the soil is rather high, about 1.5-1.6 g/cm3, lower density results in a repacked soil which is not stable through time. At least for maize, lupine, Arabidopsis the bulk density and soil type did not impede/alter root growth.

To date, most applications with light transmission imaging have been water shortage experiments and analyze the water uptake pattern in relation with root distribution/architecture or root hydraulics (Figure 2). However, this technique can be used to examine water uptake as a function of age/plant stage; to study interaction/competition between plant neighbors; to follow the effects with time of humectation/drying cycles; the interaction between localized irrigation and root growth/water uptake; split-roots or partial root zone drying can also be explored as well as root growth for various heterogeneous water content conditions or induction/regulation of aquaporins. Complementary data, such as leaf water potential, transpiration of leaves, or other physiological measurements can be of interest to examine water relations at the plant level.


Figure 1. Schematic layout of the experimental system for imaging roots and soil water content (reprint from Garrigues et al., 2006 with permission from Plant and Soil)


Figure 2. Examples of results from Light transmission imaging of the soil-root system. A. Variation with time (after the end of irrigation) of the water content in the soil of the rhizotron. The soil is colonized by a 50-days old Lupine whose root system is shown on the left. B. Water uptake rates of the Lupine in the rhizotron, derived from the difference between images of water content (shown in A) in the morning and evening. A downward and lateral spreading of uptake is visible. This spatial-temporal pattern depends on root architecture, root hydraulic conductance distribution in the root system and soil hydric properties. (Panel A is adapted from Doussan et al. 2006)

Theoretical background:
The principle of the technique relies on the fact that the light transmitted through a sandy porous medium (sand + air + water) increases with the water content. This variation in transmitted light intensity with water content is linked to the physical processes of reflection/refraction of light. Indeed, the light passing through the different phases of the porous medium is not only exponentially absorbed, but also reflected and refracted at the interfaces between the phases. For the later processes, the transmitted intensity of the passing light is a function of the refractive index of the two phases and angle incidence. The Fresnel’s law gives the light transmission ratio (; with Iv: intensity of transmitted light, Ii: intensity of the incident light) at the interface of two media for a normal incidence: 



where n is the ratio of the refractive indices of the two phases. When using the refractive index of sand, water and air (1.6, 1.33, 1.0 respectively), the transmission ratio for the sand–air interface is 0.946 while for sand–water interface  it reaches 0.991 (Tidwell and Glass, 1994). Hence, when water replaces air at sand interfaces, the transmitted light increases.
Tidewell and Glass (1994) generalized equation (1) to a whole porous medium, assuming that a pore is full or empty of water:



where Ivd is emergent light intensity of the dry sample, Kw and Ka are the light absorption coefficient for water and air, respectively; dw is the total thickness of water filled pores, S is the water saturation: with volumetric water content and  water content at saturation), k is the average number of pores across the sample.
As Kw and Ka nearly equal, eq. (2) can be approximated by: 



As the dry state for estimating Ivd is not readily attainable after plant growth in the medium and (3) is dependent on the bulk density of the sample, we can make use of the saturated state for normalization between samples. Using the ratio , where , with Ivs the emergent light intensity at water saturation, equation (3) can be transformed to: 



Based on (4), fitting a relationship between S and ln() is the rational for calibration and the conversion of images’ pixel intensity into water content.

Materials and Reagents

  1. Growing media for plant
    1. Filter paper
    2. Petri dishes
    3. Sand: “Fontainebleau sand” (VWR, catalog number: 27460.364, 5kg)
    4. Clay: hectorite (Elementis specialties: Bentone MA®)
    5. Coarse sand/gravel (2-3 mm diameter, such aquarium sand)
    6. Detergent: TFD4 (Dutscher, catalog number: 711169B)
    7. Nutrient solution: modified Hoagland solution (see Recipes, chemicals available from VWR, Fisher Scientific, Sigma-Aldrich, …) made with:
      1. KNO3
      2. Ca(NO3)2·4H2O
      3. Fe-EDTA
      4. MgSO4·7H2O
      5. NH4NO3
      6. KH2PO4
      7. H3BO3
      8. MnCl2·4H2O
      9. ZnSO4·7H2O
      10. CuSO4
      11. H3MoO4 or Na2MoO4·2H2O
      12. KOH 

  2. Construction of Rhizotrons (height x width from 30 x 30 to 100 x 50 cm)
    1. PMMA (Plexiglas/Perspex) sheets: Transparent and colourless, 5 mm thick (minimum) 
    2. PVC rod: 1 cm high, 4 mm thick
    3. Aluminum flat bars: 4 mm thick, 1 cm width (see Notes)
    4. Corner shaped aluminum bar, 1 x 1 cm
    5. Stainless steel and nylon bolts (and nuts): 20 mm long x 3 mm diameter
    6. Black matt tape
    7. Plastics (PVC, PPMA, Altuglass) (is easily available from local retailers, e.g., Gaches Chimie, abaqueplast: abaqueplast.fr)
    8. Aluminum bars (available from local DIY stores)

  3. Construction of Light source and colorimetric scale (if needed)
    1. Fluorescent tubes (e.g., Philips TLD 18W/840–Cool white color)
    2. Wood or other materials for constructing the frame of the light illuminating box
    3. Light diffusing sheet of PMMA: 4 mm thick, white colored (Altuglass, catalog number: 100 27018)

Equipment

  1. CCD Camera: 6 to 12 Mpixels, 8 to 14 bit depth for colors, RAW format available, computer driven interface for remotely shooting the picture and transferring the image file, manual adjustment possible
  2. Camera lens: 50 to 120 mm focal length, aperture ~f2-f22
  3. Tripod for camera
  4. Balance for weighing rhizotrons (20 kg range for the larger 1 x 0.5 m rhizotron)

Software

  1. Image processing Software: Fiji (Schindelin et al., 2012, open-source software based on ImageJ, https://imagej.net/Fiji
  2. For processing imaged root systems: SmartRoot (Lobet et al., 2011, Open-source, based on ImageJ, https://smartroot.github.io/) or for simple segmentation of root system (and length, diameter of roots): IJ_Rhizo (Pierret et al., 2013, Open-source, based on ImageJ, http://www.plant-image-analysis.org/software/IJ_Rhizo)

Procedure

Note: Depending on the material, equipment already available, not all of the steps below need to be completed. In particular, the first step (construction of equipment) can be skipped if already available or alternatives are available in the laboratory.

  1. Construction of the equipment (rhizotrons, light source and water content calibration cells)
    1. Building of the rhizotrons:
      The rhizotron is a transparent box in which the soil is filled and the plant is grown. The faces of rhizotron are made of 2 transparent PMMA (Plexiglas) sheets. Height and width can be adapted to the root system of the plant studied. We used 100 x 50 cm for blue lupine and maize, 30 x 30 cm for Arabidopsis. The thickness of plexiglass sheet is 5 mm to be sufficiently rigid. As an example of rhizotron design (Figure 3):
      1. The 2 Plexiglas faces are separated on left and right by rigid aluminum bars (width = 1 cm, thickness = 4 mm, see Notes, length = length of Plexiglas face). A corner shaped aluminum bar on each side increases the rigidity of the assembly (Figure 3). 
      2. Some silicone grease is applied along the aluminum bars to make them watertight.
      3. For the bottom, a rectangular plastic (PVC) rod is used: ~1 cm high, thickness = 4 mm, width = width of plexiglass–2 cm (2 cm is the sum of the widths of the 2 aluminum bars) and perforated with 3 mm holes for drainage. 
      4. Use 20 mm long x 3 mm diameter bolts (and nuts) made from stainless steel and nylon (~20 stainless and 16 nylon for 100 x 50 cm rhizotron) to assemble the rhizotron. 
      5. For each nylon bolt, a spacer is made by cutting a small PVC pipe (length = 4 mm, external diameter = 7 mm, internal diameter = 4.5 mm). These internal spacers are needed to inhibit lateral movement of Plexiglas sheets with time (particularly for large ones). We used a spacing of about 12 x 12 cm, vertical and horizontal directions, for internal spacers along the PMMA sheet for 100 x 50 cm rhizotron.
      6. Aeration holes (2 mm) are drilled into one face of the Plexiglas sheet.
      7. Black, matt, tape is put along the edges of the rhizotron
      Figure 3 shows assembling of rhizotron. The top of rhizotron can be enlarged by drilling in the 2 Plexiglas to accommodate positioning of large seeds. An alternative design of rhizotrons can be found at files.figshare.com/224189/rhizotron_blueprints.pdf, from Lobet and Draye (UCL).


      Figure 3. Rhizotron. Schematic assembling of a 100 x 50 cm transparent rhizotron (Left) and a picture of the assembled rhizotron (Right), with the installed coarse sand and gravel draining layer at the bottom.

    2. Constructing the light source (if not already done/available):
      A light source is needed to produce the light that will cross through the rhizotron and will be registered by the camera. The light box is made from a frame whose size accommodates the size of rhizotrons (Figure 4). We found it convenient to use wood to construct the frame. For example, for a large rhizotron 100 x 50 cm, the wood frame is 130 x 80 cm.
      1. Within the wood frame, the light is emitted by fluorescent tubes. For a large rhizotron, 19 fluorescent tubes, 56 cm length, 18 W (Philips TLD 18W/840–Cool white color) are aligned along 116 cm height. For smaller rhizotrons, e.g., 30 x 30 cm, 4 fluorescent tubes are sufficient for illuminating a 45 x 40 cm surface area. 
      2. The inner walls of the wood box shall be white to increase the light efficiency. 
      3. For aeration and limiting heat, holes (~5-7 mm diameter) are drilled on the top, left and right side, of the wood box. 
      4. Affix on the side of the light box facing the rhizotron a white, light diffusing, sheet of PMMA (4 mm thick), to homogenize the light from fluorescent tubes. It can be fixed with screws on the wood box.
    3. Setting a colorimetric scale
      Variations with time of the intensity of the light emitted by the light box or captured by the camera (because of variation in exposure time or thermal noise for example) might happen. To get rid of these variations not linked with water content in the rhizotron, a light transmission grey scale, acting as a reference for image adjustment, is needed. The grey scale also accounts for possible nonlinearity of CCD or camera built in process over the light intensity range recorded. The scale can be constructed from more or less transparent PMMA materials. We found a better way to construct it by using 8 known grey values printed on normal paper by imaging software (ImageJ, paint…). The grey levels are: 10, 25, 50, 100, 150, 205, 233, 255, as coded for an 8 bit-grey scale image. The zero level (black) is taken from a black side of the light box. Each paper printed grey-values is sandwiched between 2 white diffusing PMMA light diffusing sheets, as above. PMMA and paper hold together with matt black adhesive tape. This results in rectangular blocks which are placed on a side of the light box with adhesive tape, setting a light transmission grey scale (Figure 4).


      Figure 4. Light box. Schematic assembling of the light box for back illuminating rhiztrons (Left) and a picture of the assembled light box, with colorimetric grey scale and a filled rhizotron, with narrow leaf lupine. During experiment the rhizotron was installed on the balance in front of the light box (right).

    4. Adjusting the light source to rhizotrons
      The light box shall be greater than rhizotrons, incorporating the colorimetric scale for getting homogenous light trough samples. It is necessary to create a mask of the size of the rhizotron fixed over the white diffusing PMMA sheet of the light box. The mask needs to be also adapted to the colorimetric scale, next to the rhizotron (Figure 4). This mask can be made from cardboard or be a wooden frame painted black. A black foam ribbon between the mask and the rhizotron will occult light there. If the rhizotron does not stay on front of the light box during the experiment, being removed after each picture, the rigid wooden frame can be adapted to serve also as rhizotron holder. It is indeed important that the rhizotron stays at the same place for each imaging experiment to get the best spatial precision in the images and in the geometric registration. A slide on the wood frame with wing bolts that press the rhizotron against the frame and foam ribbon will hold the rhizotron at the same position for successive imaging sequences. 
    5. Construction of water content calibration cells
      A calibration cell enables to fit equation (4) in the form



      where a and b are to be fitted.
      The calibration cell is made from the same materials as rhizotrons. Aluminum bars (4 mm thick, 1 cm wide, 14 cm length) are glued on to a transparent PMMA sheet (50 cm length, 14 cm high, 5 mm thickness) to delimit 7 compartments, 6-cm width (Figure 5). These compartments will be filled with the sandy soil prepared in Step B1 at 0, 2, 5, 7, 10, 15, 20% gravimetric water content (g water/g dry soil). The water used is tap water. The front face of the calibration cell is another, removable, PMMA transparent sheet and holds in place with screws or clips. Black, matt, adhesive tape is put along the edges of the cell when finished and filled. Crosses (4) drawn on PMMA with a fine permanent marker serve as a spatial reference for image geometric registration.


      Figure 5. Scheme of the water content calibration cell. A frame of flat aluminum bars, 4 mm thick, is sandwiched between 2 transparent PMMA sheets. The aluminum frame delimitates cells which are filled with sandy soil of known gravimetric water content.

  2. Experimental procedure
    1. Preparation the soil growing medium
      The soil used for growing plants in rhizotrons is a sand-clay mix. The sand is “Fontainebleau sand”, a clear, pure, silica sand with a mean diameter of about 200 µm. The clay is the hectorite (swelling) clay, which is transparent when mixed with water. Sand hydraulic properties may depend on how the sand is clean at the beginning of the experiment (because of dust, grease residues…). It is recommended to wash the sand to obtain a reproducible initial state. The procedure is:
      1. Put the sand in a 0.5% dilute solution of TFD4 detergent and boil for 30-40 min.
      2. Rinse the sand under hot tap water for 15 min, and then boil for another 15 min.
      3. Rinse the sand with tap water first and demineralized water afterward.
      4. Dry the sand in an oven at 60 °C for 24 h.
      5. Prepare the sand and clay mix: Mix 98.5% of dried sand and 1.5% clay (by weight). 
      6. To stabilize the sand-clay association, the mixture is saturated with tap water and oven-dry at 105 °C. 
      7. After mixing and drying, this sand-clay mix is stored in closed containers.
        Hydric properties that we have determined of this sandy-clay soil are shown Figure 6 (see Garrigues, 2002 for more details) and can be used for converting water content to matric potential and for soil-root water modeling purposes. 


      Figure 6. Retention curve (A) and hydraulic conductivity, expressed in a logarithmic scale (B) of the sand clay mix (98.5% sand-1.5% hectorite clay). The soil matric potential is expressed in hydraulic head units (meters).

    2. Rhizotron filling and plant culture
      1. The filling of rhizotron with the sand-clay mix is an important step in obtaining reproducible results. A layer of coarse sand (2-3 mm diameter), acting as a draining layer and preventing fine sand to leak out, is first poured into the rhizotron to achieve a height of about 2 cm. This height is recorded (hcoarse). The rhizotron is then weighted: this “empty” weight is recorded (Me).
          A mass of sandy soil is prepared. This mass can be estimated from 1.7*Vrhizo, where 1.7 g/cm3 is an upper bound of the bulk density of the final sand packing and Vrhizo is the inner volume of the rhizotron, estimated from width, length and thickness dimensions.
          The mass (in excess) of sand is put into the rhizotron once. This can be achieved with a homemade funnel (with trapezoidal shape), which aperture and length fit the rhizotron. The funnel is adapted and fixed to the top of rhizotron mouth. The sand is poured and accumulated into the funnel at about the same height along the rhizotron, while a paper sheet closes the funnel’s aperture. Removing the sheet causes a regular fall of the sand. During the fall, sand is redistributed by collisions with the inner spacers enhancing homogeneity of the packing.
          Always with the funnel containing the remaining sand on the rhizotron, the sand is compacted by tapping along the 2 aluminum edge spacers with a small plastic hammer. The number of strokes shall be the same between each rhizotron made (~15-20). The weight of the dry, filled, rhizotron is recorded (Mdf) and the dry bulk density as well as an approximation of porosity are given by:



        where Vcoarse is the volume of coarse sand in the rhizotron (= hcoarse x Widthrhizo x Thicknessrhizo) and = 2.65 g/cm3 is the solid density of sand grains.
        The rhizotron is labeled and in order to get spatial references in images of the rhizotron for geometrical registration, crosses are drawn with a fine permanent marker at the corners of the rhizotron. 
      2. The rhizotrons are water saturated by placing them vertically in a container large enough to accommodate them and rising slowly the water level in the container. Before saturating the rhizotron, aeration holes in the Plexiglas need to be covered by adhesive tape to avoid the sand to escape. The weight after saturation can be recorded to get a first measure of the saturated water content.
        Note: At dry state and once saturated, rhizotrons shall be handled precautiously in order to not change soil compaction. After drainage occurred, the sand inside the rhizotron will be more stable. 
      3. Large seeds (e.g., maize) are pre-germinated on moist filter paper in Petri dishes and transplanted in rhizotron when radicle is about 1 cm long. A potting mix is added and moistened on top and side of the seed to maintain a favorable medium for seed development. Smaller seeds (e.g., Arabidopsis) are put directly on a moist potting mix layer (about 3-4 mm high). 
      4. To limit evaporation from top soil in rhizotron, a layer of coarse sand (or expanded clay) is added at the top of the rhizotron (the mass added is recorded). Rhizotron are covered on top and sides with opaque plastic sheets to protect them from light (root growth, algal growth) and evaporation. 
      5. During plant growth in a growth chamber, rhizotrons are irrigated with a nutrient solution adapted to the plant. Frequent irrigation is necessary in order to not water stress the plant in the thin sandy medium. The irrigation can be done by automated drip irrigation to maintain the soil at field capacity (for example ~10-15 ml each 4 h during the day period). When plants are developed, transpiration may reach 1-10 g/h depending on the plant, its age and potential evapotranspiration. During this cropping phase, water lost by transpiration needs to be replaced by irrigation. Evaluation of transpiration can be done by weighing the rhizotrons regularly.
        Note: A modified Hoagland is often used (see Recipes–Table 1).
      6. The rhizotrons can be installed vertically, but if one wants to follow root growth, rhizotrons can be tilted approx. 30-35° to get roots growing along a PMMA face. Roots can be followed through time by manually tracing with permanent markers on a transparency film fixed on the rhizotron face, or by taking a picture with a further process of root segmentation, if contrast/resolution are good enough. 
      7. At the end of the whole experiment, the rhizotron is laid horizontally, a PMMA face removed and roots can be exposed (possibly using a brush) for root recording (manually with a transparency film or by taking a picture). 
    3. Imaging of rhizotrons
      Timing of an imaging experiment:
      For a water shortage experiment or following a rewetting, the rhizotrons are imaged regularly. For a drying experiment, an imaging frequency of 2 h is enough. Depending on the plant type, age and climatic conditions in the growth chamber, the water shortage experiment may last from 3 days (e.g., maize, lupine) to 8-10 days (e.g., Arabidopsis) before water in the rhizotron is nearly completely depleted.
      Warmup, location of light box and camera:
      Light emission of fluorescent tubes of the light box will increase after switching on and a warm-up of about 10 min of the lamps is recommended before the first image is recorded. The light box and camera can be placed ideally in the growth chamber where the rhizotron stays, minimizing transport, or in a dedicated room. In either case, to avoid undesirable light reflection on the walls, black sheets/tarps are put on side walls between rhizotron and camera. A specific casing can also be made protecting from outside light, black inside, with a rectangular or truncated pyramidal shape enclosing the camera and arriving at the light box. To avoid at most geometric errors, the camera and rhizotrons (cf. Step A4) shall stay at the same place between images, and the camera needs to be fixed and not moving. Typical distances between rhizotron and camera are from 60 cm to 2 m, depending on the size of rhizotron and camera lens used.
      Camera adjustments:
      In a typical water shortage experiment, the first image of the time sequence would be the reference image at (near) saturation of the series. This can be done by increasing irrigation a few hours before starting the experiment. The water saturated image is the brightest image in the experiment, and the camera parameters are set at this step (aperture and possibly shutter speed) for the whole experiment in order to get a bright but not saturating image (i.e., pixels values lower than 255 for 8-bit image). This can be verified with Fiji/ImageJ software (Schindelin et al., 2012) with the threshold function. Typical settings are aperture f/4 to f/8, shutter speed 1/125 to 1/20 second. In order to minimize noise and light variation effects, at each measurement time, 3-4 images are taken successively which will be averaged later.
      Note: Full saturation can also be done at the end or beginning of the experiment by rising water level slowly in a container with the rhizotron. Care should be taken to close lateral aeration holes (with tape).
      Weighing of rhizotron:
      Just before each image acquisition, the rhizotron is weighed to estimate the transpiration and mean soil water content. 
    4. Establishing a water content calibration with the water content calibration cells
      1. Sandy soil samples are prepared at different values of gravimetric water content (0, 2, 5, 7, 10, 15, 20%). To this end, a dry mass of soil (Ms) is prepared in excess to fill each cell (cf. Step A5; about 80 g for each cell described in Step A5). A mass of water (Mw) is prepared to get the desired gravimetric water content percentage W: . The dry soil is distributed over a dish in a thin layer and the amount of water is spread over the soil with a spray. The soil and water are thoroughly mixed, transferred into a plastic or glass container, which is sealed and stored in a cool place for 48 h (to get moisture equilibrium). 
      2. With the front side of the calibration cell removed, a mass of moist soil (Mm) is weighed to reach a bulk density of 1.65 g/cm3 in each cell. This mass can be calculated with:



        where,  , and V is the volume of the cell to be filled.
        The soil is deposited along the cell, pressed and leveled (using the aluminum bars) to fill the entire cell. This is repeated for each calibration cell. Cares need to be taken to not leave sand on aluminum bars.
        Note: It is useful to train before making the final calibrated cells in order to obtain as most homogenous filling as possible. Another option is to fill cell from the top and to compact from the top each 3 cm. However, this results in heterogeneous layered medium but, from images, the mean pixel intensity over the cell is representative of the mean water content.
      3. Unused sand in excess is collected to determine the actual gravimetric water content. To this end, the moist soil sample is weighed, then dried for 24 h at 105 °C and reweighed. The gravimetric water content is the ratio of water mass (the difference between moist and dry soil) to the dry soil mass.
      4. Silicon grease is added along aluminum bars and the calibration box closed with black tape around the edges of the box. A picture of the calibration cell with the light box is taken in the same conditions as rhizotrons (cf. Step B3). 
      5. As for rhizotron and image processing, the calibration cell is brought to saturation. This is done by adding water slowly with a micropipette in each cell. The range of mass of water (Mw) to be added can be estimated with:



        where, 0.38 is the theoretical volumetric water content at saturation for a medium having a bulk dry density of 1.65 g/cm3. The saturated calibration cell is let to equilibrate for a few hours and then a picture of the saturated calibration cell with the light box is taken again. 
      6. The calibration is opened and the sand of each cell is completely sampled. Weigh these moist soils, and then dry in an oven for 24 h at 105 °C and reweigh. The gravimetric water content approximating saturation can then be calculated as well as the dry bulk density of each cell, if the volume of the cell is determined.

Data analysis

  1. Processing of the images of rhizotron for water content
    Once acquired in the light transmission experiment, the images are processed: 
    1. If needed: conversion of raw images to uncompressed tiff file (software supplied with camera).
    2. Averaging image replicates: using Fiji (using stacks: File → Import → image sequence; and then Image → Stacks → ZProject → Average Intensity–A macro can be recorded) or with homemade software.
    3. Conversion of RGB images to grey levels, with Fiji (Image → Type → 8 or 16 bits, depending on color depth of image) or using Netpbm (Linux software).
    4. Geometrical registration of the images of the time series. The first image of the time series acts as a reference. With Fiji the StackReg plugin can be used (Plugins → Registration → StackReg) or other registration capable program (e.g., homemade program makes use of marks in the image: written crosses and screws for example, with polynomial rectification and resampling with interpolation). The true size of pixel can be calculated from a known length in the image (it will be the same for each image) and camera (x, y) number of pixels.
    5. Adjusting images according to a grey scale reference. Images of the time series can be referenced either to the grey values of the colorimetric scale (from 0 to 255 see Step A3 in Procedure) or to the intensity value of the grey colorimetric scale of the first, water saturated, image. Sampling the intensity of grey values of the colorimetric scale in each image can be done in Fiji by defining masks on each of the colorimetric cells with the rectangular selection tool (cf. http://imagej.nih.gov/ij/docs/guide/146-29.html to create binary masks). These masks are used along with the ROI manager (Analyze → Tools → ROI manager) where masks can be applied to each image and measured (i.e., getting the mean pixel value, standard deviation in the region of the mask). For each image, the correspondence between the mean pixel intensity of the greys of the studied image and the reference value (i.e., the 0 to 255 eight colorimetric values defined in Step A3 or intensities of the colorimetric cells of the water saturated image) can be established using the calibrate function (Analyze → Calibrate) or the LUT editor plugin in Fiji. Alternatively, homemade programs which make average of the defined colorimetric zones and adjust the studied image with a cubic spline to the reference colorimetric scale are available.
    6. Calculating the water content of pixels in images with the fitted calibration equation (5): S= (cf. below “2. Processing of calibration cell” for fitting). This calculation can be done with Fiji using the image calculator and Math functions (Process → Image Calculator, or Math) and selecting 32 bit images type (float values for water content) for the result. For each image of the time series:
      1. Calculate the saturation ratio of images: Iv/Ivs, where Iv is grey levels of pixels of the image of rhizotron at a given time and Ivs those of the image of the rhizotron at saturation (with Image Calculator in Fiji, using the Divide function).
      2. Calculate image of water saturation with Log, Multiply, Add functions of Math in Fiji (or alternatively use the macro function of Math to code the equation directly).
      3. Calculate water content image  from saturation with  with  the mean value of water content at saturation of the rhizotron determined from weight measurements (see Steps B2 and B3)
      4. The rhizotron part of the result image is cropped and saved in tiff (and text file if needed), for further calculation/processing. Again, homemade programs can do that calculation part.
    7. Post-processing of the water content image series includes the calculation over the rhizotron of the mean water content, which will be compared to estimated water content from weight measurements. Specific treatment related to water variations includes conversion of water content into water potential, calculation of images water uptake rate with time (time image differences), estimation of the maximum depth/width of uptake, 1D mean profiles (and standard deviation) of water content, water uptake along the rhizotron. If images of the root system are co-registered with water content images, then processes at the soil-root interface (for water) can be examined, such as local or mean drawdown with distance to root, root type or age. The relationship between root density and uptake or between root growth and water content or potential can also be obtained.

  2. Processing of the calibration cell
    The calibration cell enables to fit a, b in equation (5): .
    The images of the calibration cell are processed as for the rhizotrons (cf. above step 1), except that the value of  ln are estimated from mean values over the same region of interest in each calibration cells for initial and saturated images. The (a, b) coefficients of the calibration function in eq. 5 are estimated from linear regression between water saturation and ln (Figure 7). As the regression changes at low water contents, a second set of parameters is needed in the low saturation range (lower than about 3% volumetric water content, Figure 7).
    The colorimetric scale adjustment of the calibration cell is referenced to the first image of the time series of each rhizotron, resulting in a slightly different calibration equation for each rhizotron. 


    Figure 7. Calibration derived from images of calibration cells between water saturation and ln. The equation of calibration is (see eq.5) where a and b are fitted by linear regression. Two regressions are needed.

  3. Validation of estimated water content of rhizotron from image processing
    To get rid of possible residual effects of variations in compaction between calibration cell and rhizotrons a final test consists in comparing mean volumetric water of rhizotrons estimated from calibrated images and from weighing of rhizotron trough time. This normally results in a regression line with R2 > 0.99, but if the slope is nearly equal to 1, a small bias (about 1% in volumetric water content) may appear. In that case, the water content estimated from images can be converted to “true” water content (from weight measurements) by this regression equation. 
  4. Processing images of root systems
    If the root system was traced on a transparency film on front of the rhizotron, the film can be scanned and the resulting image segmented with IJ_Rhizo software (Pierret et al., 2013) for example. A way for vectorizing complex root systems when the rhizotron is disassembled and root system exposed can be found in Lobet and Draye (2013). If following root growth either from transparency film drawings or images of rhizotron trough time is of interest, the SmartToot software (Lobet et al., 2011) would be usefully used as it enables semi-automated tracing of roots on an image series. Outputs such as growth, topology, lateral density, diameters can be obtained.
    Whatever the root processing software, if the root system in rhizotron is segmented from an image at the same time as the imaging experiment for water content, coregistration of the images of the segmented root system and of the water content in the rhizotron enables to relate root parameters (root density, root age, root types, growth...) and water content or uptake in soil. 
  5. Going a step further: Use of imaging experiment in modeling
    Light transmission imaging of plant water uptake has been designed initially to verify the consistency of detailed modeling of root water uptake. This modeling couples root system architecture, regulation of water flow into and along the root system, mechanistic water transfer in the soil (Doussan et al., 1998; Doussan et al., 2006). This modeling approach has been extended since (Javaux et al., 2008; Schneider et al., 2010). The modeling of light transmission imaging, in the case of more or less tap rooted Lupine root systems, showed that uptake is driven by local soil-root interactions at the single root scale, linked to variation in soil hydraulic conductivity near the root and root radial conductivity. These interactions are modulated at the root system scale by the water distribution and the root axial conductance (Doussan et al., 2006). Variations in root system architecture and distribution of root hydraulic conductance, defining different root systems phenotypes, will give rise to variations in water uptake pattern. Testing these various phenotypes with detailed water uptake models in combination with imaging results of water content, can give access to estimations of hardly measurable parameters such as root hydraulic conductivity, distributed root water uptake rates or root xylem water potential. Combination of modeling and experiment may also help in testing biological and physiological assumptions, such as ABA production and regulation of water fluxes (Lobet, 2013). With the modeling, supported by imaging experiments, plant behavior (e.g., for different root phenotypes) can be extrapolated to other soil/climate conditions (e.g., for looking at the water uptake efficiency), guiding experimental verifications (in the field or controlled conditions) in a later step.

Notes

The 4 mm void, filled with soil, thickness is a good compromise to get enough light through the rhizotron and enables a good contrast between dry/wet states of the sandy soil used. Slightly larger thickness can be used to accommodate thicker roots (up to 6 mm) but at the expense of lower contrast.

Recipes

  1. Modified Hoagland solution (Table 1)

    Table 1. Composition of modified Hoagland solution. The Iron content is doubled in this solution (adapted from Lobet and Draye, 2013) 

Acknowledgments

This work benefited from a grant INSU-CNRS “Programme National de Recherche en Hydrologie (PNRH)” 99-PNRH-39 and support from Agropolis foundation.

Competing interests

The authors declare no conflict of interest.

References

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简介

改善作物的水分亏缺需要更好地了解植物根系的功能。这需要更好地了解吸水过程并解决根系结构或根系生理特性对吸收效率的影响。为此,我们在此描述了一种非破坏性系统,该系统能够对土壤水和根系进行动态,定量,功能成像,从单根到整个根系统。

该系统基于在沙质根茎中生长的植物,并且依赖于通过土壤含水量调节通过根际电子管传播的光的强度。使用CCD相机记录植物吸水(或释放)阶段期间透射光的图像,并且水含量可以通过校准与图像像素的灰度级相关。

该系统价格合理,无需特定设备即可相对轻松地实施。它具有可扩展性和快速性,允许对一系列植物基因型的表型进行相对于其吸水模式的表型分析。然后,该模式可以与不同植物阶段的根系统特性(土壤定殖,根构造)相关。结合建模,成像结果有助于获得根水力传导率,分布根系吸水率或根木质部水势等参数。建模和实验的结合进一步有助于测试生物学和生理学假设以及预测植物在田间的摄取行为。
【背景】几十年来,详细观察植物根系吸水以及根系和植物的水通量,在技术上具有挑战性。大多数的水吸收研究都是通过测量土壤含水量随时间的变化来进行的。在现场,这种测量是基于分布在土壤中的湿度传感器的使用,如中子水分仪(Hignett和Evett,2002)或电磁TDR或电容传感器(Li et al。,2002) 。在盆栽植物的受控条件下,盆的重量可用于确定盆栽水含量。然而,如果这些测量非常适合描述宏观土壤水的行为,它们就无法获得根周围水的详细分布以及根之间水的相互作用。而且,它们没有揭示根的分布和功能。

与现场水分测量同时进行,可以使用岩心样本,沟壁分析或使用迷你rhizotron成像破坏性地评估根分布(Smit et al。,2000)。这样可以访问具有深度的根分布(长度,根影响,生物体积)。生根的可变性通常需要获得大量样本,这是一项艰巨的任务,因为采样/测量需要高度的时间和劳动力。

可以使用各种测量装置检查植物和根系与氢的关系。用热平衡液流量计可以在茎和粗根中估算树液流量(Granier,1987);可以根据张力诱导测量从根段到根系估计根系导水率(North和Nobel,1995),根压力探针(Frensch和Steudle,1989)或压力细胞(Miyamoto 等。, 2001)。可以用电位计(Sanderson,1983),染料示踪(Varney和Canny,1993)研究单根水平的根系吸水通量。

所有这些方法都提供了水 - 土 - 植物系统的补充信息/特性,但大多数情况下,必须对切除的根段,从土壤中分离的根或根系,或在水栽法中生长的植物进行测量。它们还结合了可能不相似的根的信息(例如,根类型,年龄或顺序,根系统中的位置)。

成像技术允许观察活的根系及其与土壤的相互作用,而无需从土壤中切除或提取它们。如果及时重复测量,它们还可以量化根架构和增长,根类型和年龄。理想情况下,成像技术不仅可以实现根成像,还可以实现其他参数,如含水量。最近几年,不同的成像技术被用于研究水土根系。它们在分辨根或水的能力,样品的大小,2D或3D描述,易处理性和可访问性方面各不相同。 X射线扫描首先用于Hainsworth和Aylmore(1983和1986)的开创性工作。从那时起,X射线扫描仪的分辨率,功率和扫描速度都大大提高,土壤柱中的根跟踪和分割的图像处理也是如此(Tracy et al。,2010)。然而,准确量化三维土壤中的水和根仍然是一个挑战(Zappala et al。,2013),因为该技术对水和根的反应几乎相同,在分辨率和样本的大小(Pierret et al。,2003a和2003b)。如今,土壤/根系研究人员更容易接触到X射线扫描仪,但仍然无法完全获取并且相当昂贵。磁共振成像(MRI),基于磁场中的H自旋弛豫,已显示出对土壤和水成像的高潜力(Pohlmeier et al。,2008),因为它对水具有高度敏感性。然而,相当低的分辨率需要相对较小的样本。由于其磁性,一些天然土壤会在RMN中造成伪影。成像需要很长的扫描时间,而低可达性和高价格使得该技术目前不容易用于土壤根水研究。最近引入了中子射线照相(和断层扫描)用于成像根和水(Nakanishi,2005; Esser 等人,,2010)。该技术基于热中子束的衰减,并且对H原子和水高度敏感。它能够以高空间分辨率(0.1-0.5 mm)和水含量的高精度(1至5 x 10 -3 m 3 成像根和水。米 -3 )。然而,该技术需要相当薄且小的根箱(rhizotron~30cm)。中子束的生产以及成像能力只能在世界上的一些地方使用,并且几乎不能用于常规测量。研究土壤 - 水 - 根系统的一种更容易获得的方法是光透射成像技术,详见程序B.最初用于研究粗砂多孔介质中的水渗透不稳定性(Glass et al。,1989),该设计已经过调整,以允许植物在根茎中的适当沙质基质中生长,并获得土壤水的时间和空间变化。然后,这些变化可以与根系定殖和根系结构相关的水吸收相关联(Garrigues,2002; Garrigues et al。,2006)。该技术仅利用根茎,照相机和光源,可轻松扩展,用于表征与水吸收特性相关的一系列根系(Lobet,2013)。结合建模和补充数据,该技术可以获得植物功能/特性,例如根系的水力特性,受水含量影响的根系生长速率......

应注意,所有前述成像方法都适合于在实验室中扫描样品。在该领域,电阻率层析成像具有很高的成像土壤含水量和作物随时间吸水的潜力(Srayeddin和Doussan,2009),但目前没有方法能够同时对水和土壤中的根进行成像。根评估仍然主要依赖于野外研究的破坏性抽样。

技术的基本原理:
该技术基于通过根茎的光的衰减,其中根生长并吸水(图1)。光衰减与水含量直接相关。该技术使用易于获得的材料,软件程序和标准CCD相机进行成像,并且具有成本效益。由于测量时间短,因此可以实现高时间分辨率。还可以实现高空间分辨率,大约0.2-0.5mm。可以设计技术管道以允许多个rhizotrons扫描和随时间监测,以便表现出与其吸水/根系土壤定殖或根构造特性相关的一系列基因型(Lobet,2013)。测量可以是定性的(即,仅量化水随时间或植物之间的差异)或定量与校准步骤。

然而,光成像技术也有缺点:(i)植物根生长在薄土壤中,并且更像2D而不是3D方法。 (ii)由于土壤体积相当低,土壤含水性质来自沙质介质,因此与土壤中水分吸收相关的过程(例如,根部附近的水分下降,缺水)会加速/放大与天然3D土壤相比(取决于气候需求)。 (iii)根茎中的土壤是特定的(沙子+粘土)是半透明的,并且该技术不能与天然的,不透明的土壤一起使用。 (iv)土壤的堆积密度相当高,约1.5-1.6g / cm 3 ,较低的密度导致重新包装的土壤随时间不稳定。至少对于玉米,羽扇豆,拟南芥,体积密度和土壤类型不会阻碍/改变根系生长。

迄今为止,大多数采用光透射成像的应用都是缺水试验,并分析了与根分布/结构或根系水力学相关的吸水模式(图2)。然而,该技术可用于检查作为年龄/植物阶段的函数的水吸收;研究植物邻居之间的互动/竞争;跟随湿润/干燥周期的影响;局部灌溉与根系生长/水分吸收之间的相互作用;还可以探索分根或部分根区干燥以及各种异质水含量条件的根生长或水通道蛋白的诱导/调节。可以研究补充数据,例如叶水势,叶片蒸腾或其他生理测量,以检查植物水平的水关系。
图1.用于成像根和土壤含水量的实验系统的示意图(来自Garrigues的再版 et al。,2006获得植物和土壤的许可 EM>)


图2.土壤根系光透射成像结果示例 A.根际土壤中含水量随时间的变化(灌溉结束后)。土壤被50日龄的羽扇豆定植,其根系显示在左侧。 B.在根茎中的羽扇豆的吸水率,来自早晨和晚上的含水量图像(在A中显示)之间的差异。可以看到向下和横向的摄取扩散。这种时空模式取决于根系结构,根系中的根系水力传导分布和土壤水化特性。 (A组改编自Doussan et al。 2006)

理论背景:
该技术的原理依赖于透过沙质多孔介质(沙子+空气+水)的光随着含水量增加的事实。透射光强度随水含量的这种变化与光的反射/折射的物理过程有关。实际上,穿过多孔介质的不同相的光不仅被指数吸收,而且在相之间的界面处反射和折射。对于后面的过程,通过的光的透射强度是两相的折射率和角度入射的函数。菲涅耳定律给出了透光率(; I v :透射光强度, I i :强度事件发生在两个媒体界面的正常发生率: 



其中 n 是两相折射率的比值。当使用沙子,水和空气的折射率(分别为1.6,1.33,1.0)时,沙尘的透射率界面为0.946而沙水界面  达到0.991(Tidwell and Glass,1994)。因此,当水替换砂界面处的空气时,透射光增加。
Tidewell和Glass(1994)将等式(1)推广到整个多孔介质,假设孔隙充满或没有水:



其中 I vd 是干样品的出射光强度, K w 和 K a 分别是水和空气的光吸收系数; d w 是充水孔的总厚度, S 是水饱和度:体积含水量  饱和时含水量”, k 是样品中的平均孔数。
当 K w 和 K a 几乎相等时,eq。 (2)可以近似为: 

由于在培养基中植物生长后不能轻易获得估算 I vd 的干燥状态,并且(3)取决于样品的堆积密度,我们可以使用样本之间归一化的饱和状态。使用比率,其中, I vs 水饱和时的出射光强度,方程(3)可以转换为: 



基于(4),拟合 S 和ln之间的关系(”是校准和图像像素强度转换为含水量的理性选择。

关键字

材料和试剂

  1. 为植物种植媒体
    1. 过滤纸
    2. 培养皿
    3. 沙:“枫丹白露沙”(VWR,目录号:27460.364,5kg)
    4. 粘土:锂蒙脱石(Elementis专业:Bentone MA ®)
    5. 粗砂/砂砾(直径2-3毫米,如水族箱砂)
    6. 洗涤剂:TFD4(Dutscher,目录号:711169B)
    7. 营养液:改良的Hoagland解决方案(参见食谱,化学品,可从VWR,Fisher Scientific,Sigma-Aldrich,...获得)制作:
      1. KNO 3
      2. 的Ca(NO 3 ) 2 ·4H 2 0
      3. 铁EDTA
      4. 硫酸镁 4 ·7H 2 0
      5. NH 4 NO 3
      6. KH 2 PO 4
      7. ħ 3 BO 3
      8. 的MnCl 2 ·4H 2 0
      9. 的ZnSO 4 ·7H 2 0
      10. 硫酸铜 4
      11. H 3 MoO 4 或Na 2 MoO 4 ·2H 2 O
      12. KOH 

  2. Rhizotrons的构造(高度x宽度从30 x 30到100 x 50 cm)
    1. PMMA(Plexiglas / Perspex)板材:透明和无色,5毫米厚(最小) 
    2. PVC棒:高1厘米,厚4毫米
    3. 铝扁条:4毫米厚,1厘米宽(见注释)
    4. 角形铝条,1 x 1厘米
    5. 不锈钢和尼龙螺栓(和螺母):20毫米长x 3毫米直径
    6. 黑色亚光胶带
    7. 塑料(PVC,PPMA,Altuglass)(很容易从当地零售商那里获得,例如,Gaches Chimie,abaqueplast:abaqueplast.fr)
    8. 铝条(可从当地的DIY商店购买)

  3. 建造光源和比色尺度(如果需要)
    1. 荧光灯管(例如,飞利浦TLD 18W / 840-冷白色)
    2. 用于构造光照箱的框架的木材或其他材料
    3. PMMA光漫射板:4毫米厚,白色(Altuglass,目录号:100 27018)

设备

  1. CCD相机:6至12 Mpixels,8至14位深度的颜色,RAW格式,计算机驱动的界面,用于远程拍摄图像和传输图像文件,可手动调整
  2. 相机镜头:焦距50至120毫米,光圈~f2-f22
  3. 相机三脚架
  4. 称重根瘤的平衡(对于较大的1 x 0.5米的根茎,20公斤范围)

软件

  1. 图像处理软件:斐济(Schindelin et al。,2012,基于ImageJ的开源软件, https ://imagej.net/Fiji ) 
  2. 用于处理成像的根系统:SmartRoot(Lobet 等。,2011,开源,基于ImageJ, https://smartroot.github.io/ )或根系统的简单分割(以及长度,根的直径):IJ_Rhizo(Pierret et al。,2013,Open -source,基于ImageJ, http://www.plant-image-analysis.org/ software / IJ_Rhizo )

程序

注意:根据材料,已有的设备,不需要完成以下所有步骤。特别是,如果已经可以使用,或者在实验室中有替代品,则可以跳过第一步(设备构造)。

  1. 设备的构造(rhizotrons,光源和含水量校准单元)
    1. 建立rhizotrons:
      根茎是一个透明的盒子,土壤被填充,植物生长。根茎的面由2个透明的PMMA(树脂玻璃)片制成。高度和宽度可以适应所研究植物的根系。我们使用100 x 50厘米的蓝色羽扇豆和玉米,30 x 30厘米的拟南芥。有机玻璃板的厚度为5mm,足够刚性。作为rhizotron设计的一个例子(图3):
      1. 2个有机玻璃表面左右分开由刚性铝条(宽度= 1厘米,厚度= 4毫米,参见注释,长度=树脂玻璃表面的长度)。每侧的角形铝条增加了组件的刚性(图3)。 
      2. 沿着铝条施加一些硅脂以使它们不透水。
      3. 对于底部,使用矩形塑料(PVC)杆:约1厘米高,厚度= 4毫米,宽度=有机玻璃的宽度-2厘米(2厘米是2个铝条的宽度的总和)和穿孔3毫米的排水孔。 
      4. 使用由不锈钢和尼龙制成的20毫米长×3毫米直径的螺栓(和螺母)(约20不锈钢和16尼龙用于100 x 50厘米的根茎)组装根茎。 
      5. 对于每个尼龙螺栓,通过切割小PVC管(长度= 4mm,外径= 7mm,内径= 4.5mm)制成间隔件。需要这些内部隔离物来抑制树脂玻璃片材随时间的横向移动(特别是对于大的树脂片材)。我们使用了大约12 x 12 cm的垂直和水平方向的间距,用于沿PMMA板的内部垫片,用于100 x 50 cm的rhizotron。
      6. 在树脂玻璃板的一个面上钻有曝气孔(2毫米)。
      7. 沿着rhizotron的边缘放置黑色,亚光,胶带
      图3显示了根茎的组装。通过在2个有机玻璃中钻孔可以扩大根茎的顶部,以适应大种子的定位。可以在 files.figshare.com/224189/rhizotron_blueprints.pdf找到另一种rhizotrons设计,来自Lobet和Draye(UCL)。


      图3. Rhizotron。 100 x 50 cm透明rhizotron(左)的示意图组装和组装的rhizotron(右)的图片,底部安装了粗砂和砾石排水层。 br />
    2. 构建光源(如果尚未完成/可用):
      需要光源来产生将穿过根茎的光并且将由相机记录。灯箱由一个框架制成,框架的大小适应rhizotrons的大小(图4)。我们发现使用木材构造框架很方便。例如,对于100 x 50 cm的大型rhizotron,木框架为130 x 80 cm。
      1. 在木框架内,光由荧光管发射。对于大型rhizotron,19个荧光灯管,56 cm长,18 W(Philips TLD 18W / 840-Cool白色)沿116 cm高度对齐。对于较小的rhizotrons,例如,30 x 30 cm,4个荧光灯管足以照亮45 x 40 cm的表面区域。 
      2. 木盒的内壁应为白色,以提高光效。 
      3. 为了通风和限制热量,在木箱的顶部,左侧和右侧钻孔(直径约5-7毫米)。 
      4. 在面向rhizotron的灯箱侧面粘贴一层白色,光线漫射的PMMA(4毫米厚)薄片,以均匀化荧光灯管的光线。它可以用木箱上的螺丝固定。
    3. 设置比色尺度
      可能发生由灯箱发出或由相机捕获的光强度随时间的变化(例如,由于曝光时间或热噪声的变化)。为了摆脱与根茎中的水含量无关的这些变化,需要作为图像调整的参考的透光灰度级。灰度也考虑了在记录的光强度范围内内置CCD或相机的可能的非线性。标尺可以由或多或少透明的PMMA材料构成。我们通过使用成像软件(ImageJ,paint ...)在普通纸上打印的8个已知灰度值找到了更好的构造方法。灰度级为:10,25,50,100,150,205,233,255,编码为8位灰度图像。零电平(黑色)取自灯箱的黑色侧面。如上所述,每个纸张打印的灰度值夹在2个白色漫射PMMA光漫射板之间。 PMMA和纸张与亚光黑色胶带固定在一起。这导致矩形块用胶带放置在灯箱的一侧,设置透光灰度(图4)。


      图4.灯箱。用于背照式根茎的灯箱(左)和组装灯箱的图片的示意性组装,具有比色灰度和填充的根茎,具有窄叶羽扇豆。在实验过程中,rhizotron安装在灯箱前面的天平上(右)。

    4. 调整光源到rhizotrons
      灯箱应大于rhizotrons,结合比色标度,以获得均匀的光槽样品。有必要创建一个固定在灯箱的白色漫射PMMA片上的根瘤的大小的掩模。面膜需要也适应比色尺度,靠近根茎(图4)。这种面具可以用纸板制成,也可以是漆成黑色的木制框架。面具和rhizotron之间的黑色泡沫带会在那里隐藏光线。如果在实验过程中根茎没有停留在灯箱的前面,在每张照片之后被移除,刚性木制框架也可以适合作为根茎支架。确实重要的是,根据每个成像实验,rhizotron停留在相同位置,以在图像和几何配准中获得最佳空间精度。带有翼形螺栓的木框架上的滑动装置将根瘤管压在框架和泡沫带上,将根茎管保持在相同的位置,以便连续成像序列。 
    5. 水含量校准细胞的构建
      校准单元能够以(/)形式拟合等式(4)


      其中 a 和 b 将被安装。
      校准单元由与rhizotrons相同的材料制成。将铝条(4mm厚,1cm宽,14cm长)粘合到透明PMMA片(50cm长,14cm高,5mm厚)上以限定7个隔室,6cm宽(图5)。这些隔室将填充步骤B1中制备的砂质土壤,重量含水量为0,2,5,7,10,15,20%(g水/ g干土)。使用的水是自来水。校准单元的正面是另一个可拆卸的PMMA透明板,并用螺钉或夹子固定到位。完成并填充后,黑色,亚光,胶带沿着电池的边缘放置。在具有精细永久性标记的PMMA上绘制的十字(4)用作图像几何配准的空间参考。


      图5.水含量校准单元的方案。 4毫米厚的扁铝条框架夹在2个透明PMMA板之间。铝框架限定了填充有已知重量含水量的砂土的细胞。

  2. 实验步骤
    1. 准备土壤生长介质
      用于在rhizotrons中种植植物的土壤是砂 - 粘土混合物。沙子是“枫丹白露沙”,是一种透明,纯净的硅砂,平均直径约为200微米。粘土是锂蒙脱石(膨胀)粘土,当与水混合时是透明的。砂的水力特性可能取决于实验开始时沙子的清洁方式(因为灰尘,油脂残留......)。建议清洗沙子以获得可重现的初始状态。程序是:
      1. 将沙子放入0.5%稀释的TFD4洗涤剂溶液中,煮沸30-40分钟。
      2. 在热自来水下冲洗沙子15分钟,然后再煮沸15分钟。
      3. 首先用自来水冲洗沙子,然后用软化水冲洗。
      4. 将沙子在60°C的烘箱中干燥24小时。
      5. 准备沙子和粘土混合物:混合98.5%的干沙和1.5%的粘土(按重量计)。 
      6. 为了稳定砂 - 粘土缔合,将混合物用自来水饱和并在105℃下烘箱干燥。 
      7. 混合并干燥后,将该砂 - 粘土混合物储存在密闭容器中。
        我们已经确定了这种砂质粘土土壤的氢性质如图6所示(详见Garrigues,2002),可用于将含水量转化为基质潜力和土壤 - 根水建模目的。 


      图6.保留曲线(A)和水力传导率,以砂粘土混合物(98.5%砂 - 1.5%锂蒙脱石粘土)的对数标度(B)表示。土壤基质势表示为液压头单元(米)。

    2. Rhizotron灌装和植物栽培
      1. 用砂粘土混合物填充根茎是获得可重复结果的重要步骤。首先将一层粗砂(2-3毫米直径)用作排水层并防止细砂泄漏,然后将其倒入根茎中以达到约2厘米的高度。记录此高度(h 粗)。然后对根茎进行加权:记录该“空”重量(M e )。
         准备了大量的沙土。该质量可以从1.7 * V rhizo 估算,其中1.7 g / cm 3 是最终砂填料和V rhizo的堆积密度的上限。 是根据宽度,长度和厚度尺寸估算的根茎的内部体积。
         沙子的质量(过量)一次放入根茎中。这可以通过自制漏斗(具有梯形形状)来实现,其漏洞和长度适合于根茎。漏斗适应并固定在rhizotron口的顶部。将沙子倒入并沿着根茎的大约相同的高度累积到漏斗中,同时纸张关闭漏斗的孔。移除片材会导致沙子经常掉落。在秋季,沙子通过与内部隔离物的碰撞而重新分布,从而增强了填料的均匀性。
         始终使用漏斗中含有剩余沙子的漏斗,通过用小塑料锤沿着2个铝边缘垫片敲击来压实沙子。每个根茎的行程数(~15-20)应相同。记录干燥,填充的根茎的重量(M df )和干堆积密度以及孔隙度的近似值通过:



        其中V 粗是rhizotron中粗砂的体积(= h 粗 x宽 rhizo x Thickness rhizo )和 = 2.65 g / cm 3 是固体沙粒密度。
        标记了rhizotron,并且为了在几何登记的rhizotron的图像中获得空间参考,在rhizotron的角落处绘制具有精细永久标记的十字架。 
      2. 通过将它们垂直放置在足够容纳它们的容器中并使容器中的水位缓慢上升,将水分饱和。在使根瘤菌饱和之前,树脂玻璃中的通气孔需要用胶带覆盖以避免沙子逸出。可以记录饱和后的重量以获得饱和水含量的第一测量值。
        注意:在干燥状态下,一旦饱和,应谨慎处理根腐菌,以免改变土壤压实。排水后,根茎内的沙子会更稳定。
      3. 大种子(例如,玉米)在培养皿中的潮湿滤纸上预发芽,并且当胚根约1cm长时移植到根茎中。添加灌封混合物并在种子的顶部和侧面上润湿以维持用于种子发育的有利介质。将较小的种子(例如,拟南芥)直接放在潮湿的盆栽混合层(约3-4毫米高)上。 
      4. 为了限制根茎中顶部土壤的蒸发,在根茎的顶部添加一层粗砂(或膨胀粘土)(记录添加的质量)。 Rhizotron的顶部和侧面覆盖有不透明的塑料薄片,以保护它们免受光照(根部生长,藻类生长)和蒸发。 
      5. 在生长室中的植物生长期间,用适合于植物的营养液灌溉根瘤菌。为了不对薄沙质培养基中的植物施加水压,必须经常进行灌溉。灌溉可以通过自动滴灌来完成,以保持土壤的田间容量(例如在白天期间每4小时约10-15毫升)。当植物发育时,蒸腾可能达到1-10克/小时,取决于植物,其年龄和潜在的蒸发蒸腾。在这个种植阶段,蒸腾损失的水需要用灌溉取代。蒸腾作用的评估可以通过定期称量根瘤菌来完成。
        注意:经常使用经过修改的Hoagland(参见食谱表1)。
      6. 根茎可以垂直安装,但如果想要跟随根生长,可以将根瘤菌倾斜约。 30-35°使根部沿PMMA面生长。如果对比度/分辨率足够好,可以通过在固定在rhizotron面上的透明胶片上手动跟踪永久性标记,或者通过进行根分割的进一步过程拍摄照片来跟踪时间。 
      7. 在整个实验结束时,水平放置根茎,移除PMMA面,并且可以暴露根(可能使用刷子)进行根记录(手动使用透明胶片或拍照)。 
    3. 根瘤菌的成像
      成像实验的时间安排:
      对于缺水试验或再润湿后,定期对rhizotrons进行成像。对于干燥实验,2小时的成像频率就足够了。根据生长室中的植物类型,年龄和气候条件,缺水试验可持续3天(例如,玉米,羽扇豆)至8-10天(例如,拟南芥)。
      预热,灯箱和相机的位置:
      接通电灯后荧光灯管的发光会增加,建议在记录第一张图像之前预热大约10分钟的灯。灯箱和摄像机可以理想地放置在rhizotron所在的生长室中,从而最大限度地减少运输,或者在专用房间内。在任何一种情况下,为了避免在墙壁上产生不希望的光反射,在红宝石和照相机之间的侧壁上放置黑色薄片/防水布。还可以制造特定的外壳,以防止外部光线,内部黑色,具有包围相机并到达灯箱的矩形或截头金字塔形状。为了避免最多的几何误差,相机和rhizotrons(参见步骤A4)应保持在图像之间的相同位置,并且相机需要固定而不是移动。 rhizotron和相机之间的典型距离为60厘米至2米,具体取决于所用的根茎和相机镜头的大小。
      相机调整:
      在典型的缺水实验中,时间序列的第一个图像将是系列(接近)饱和的参考图像。这可以通过在开始实验前几小时增加灌溉来完成。水饱和图像是实验中最亮的图像,并且在该步骤(光圈和可能的快门速度)下为整个实验设置相机参数,以获得明亮但不饱和的图像(即,8位图像的像素值低于255)。这可以通过具有阈值功能的斐济/ ImageJ软件(Schindelin 等人,2012)进行验证。典型设置为光圈f / 4至f / 8,快门速度为1/125至1/20秒。为了使噪声和光变化效应最小化,在每个测量时间连续拍摄3-4张图像,这些图像将在稍后进行平均。
      注意:也可以在实验结束时或开始时通过在带有rhizotron的容器中缓慢升高水位来完全饱和。应注意关闭侧向通风孔(带胶带)。
      根茎的称重:
      在每次图像采集之前,对根茎进行称重以估算蒸腾量和平均土壤含水量。 
    4. 用水含量校准单元建立水含量校准
      1. 以不同的重量含水量(0,2,5,7,10,15,20%)制备砂土样品。为此,过量制备干燥质量的土壤( Ms )以填充每个细胞(参见步骤A5;对于步骤A5中描述的每个细胞约80g)。准备大量的水( M w )以获得所需的重量含水率百分比W:。干燥的土壤以薄层分布在盘子上,并且用喷雾将水量分散在土壤上。将土壤和水彻底混合,转移到塑料或玻璃容器中,密封并在阴凉处保存48小时(以达到水分平衡)。 
      2. 取下校准单元的正面,称量一团潮湿的土壤( M m ),使其堆积密度达到1.65 g每个细胞中/ cm 3 。该质量可以用以下公式计算:



        where,  , V 是要填充的单元格的体积。
        土壤沿着细胞沉积,压制和平整(使用铝条)以填充整个细胞。对每个校准单元重复这一过程。需要注意不要在铝条上留下沙子。
        注意:在制作最终校准细胞之前进行训练是有用的,以便获得尽可能最均匀的填充物。另一种选择是从顶部填充细胞并从顶部压缩每3厘米。然而,这导致异质分层介质,但是从图像中,细胞上的平均像素强度代表平均含水量。
      3. 收集过量的未使用的沙子以确定实际的重量水含量。为此,称重潮湿的土壤样品,然后在105℃下干燥24小时并重新称重。重量含水量是水质量(潮湿和干燥土壤之间的差异)与干燥土壤质量的比率。
      4. 沿着铝条添加硅润滑脂,校准盒用盒子边缘的黑色胶带封闭。带有灯箱的校准单元的图片在与根茎相同的条件下拍摄(参见步骤B3)。 
      5. 对于rhizotron和图像处理,使校准单元达到饱和。这通过在每个细胞中用微量移液管缓慢加入水来完成。要添加的水的质量范围( M w )可以通过以下方式估算:



        其中,0.38是体积干密度为1.65g / cm 3的介质在饱和时的理论体积水含量。使饱和的校准单元平衡几个小时,然后再次拍摄带有灯箱的饱和校准单元的图片。 
      6. 打开校准并完全取样每个单元的沙子。称量这些潮湿的土壤,然后在105°C的烘箱中干燥24小时并重新称重。如果确定了细胞的体积,则可以计算近似饱和度的重量水含量以及每个细胞的干堆积密度。

数据分析

  1. 用于含水量的根茎的图像处理
    一旦在光传输实验中获得,图像就会被处理: 
    1. 如果需要:将原始图像转换为未压缩的tiff文件(随相机提供的软件)。
    2. 平均图像复制:使用斐济(使用堆栈:文件→导入→图像序列;然后图像→堆栈→ZProject→平均强度 - 可以记录宏)或使用自制软件。
    3. 使用斐济(图像→类型→8或16位,取决于图像的颜色深度)或使用Netpbm(Linux软件)将RGB图像转换为灰度级。
    4. 时间序列图像的几何登记。时间序列的第一个图像充当参考。使用斐济可以使用StackReg插件(插件→注册→StackReg)或其他可注册程序(例如,自制程序利用图像中的标记:例如书写十字和螺钉,多项式修正和插值重新采样)。可以根据图像中的已知长度(对于每个图像将是相同的)和相机(x,y)像素数来计算像素的真实尺寸。
    5. 根据灰度参考调整图像。时间序列的图像可以参考比色标度的灰度值(从0到255参见过程中的步骤A3)或者参考第一个水饱和图像的灰度色度标度的强度值。通过使用矩形选择工具在每个比色单元上定义掩模,可以在斐济完成对每个图像中比色尺度的灰度值的采样的采样(参见http://imagej.nih.gov/ij/docs/guide) /146-29.html创建二进制掩码)。这些掩模与ROI管理器(分析→工具→ROI管理器)一起使用,其中可以将掩模应用于每个图像并进行测量(即,获得平均像素值,区域内的标准偏差面具)。对于每个图像,研究图像的灰度的平均像素强度与参考值(即,步骤A3中定义的0至255八个比色值或比色单元的强度之间的对应关系)可以使用斐济的校准功能(Analyze→Calibrate)或LUT编辑器插件建立水饱和图像。或者,可以使用自制程序,其使得定义的比色区域平均并且使用三次样条调整所研究的图像到参考比色尺度。
    6. 使用拟合的校准公式(5)计算图像中像素的含水量:S = (参见下面的“2.校准单元的处理”以进行安装)。可以使用图像计算器和数学函数(处理→图像计算器或数学)和斐济选择32位图像类型(水含量的浮点值)来完成此计算。对于时间序列的每个图像:
      1. 计算图像的饱和度: I v / I vs ,其中 I v 是rhizotron图像在给定时间的灰度级像素 I vs 饱和的根茎的图像(使用Divide函数在斐济使用Image Calculator)。
      2. 计算水饱和度的图像使用Log,Multiply,在斐济添加数学函数(或或者使用Math的宏函数直接编码方程式)。
      3. 从饱和度计算水含量图像  <> with  根据重量测量确定的根际土壤饱和水含量的平均值(见步骤B2和B3)
      4. 结果图像的rhizotron部分被裁剪并保存在tiff(和文本文件,如果需要)中,以便进一步计算/处理。同样,自制程序可以做那个计算部分。
    7. 水含量图像系列的后处理包括对平均含水量的根际结构的计算,其将与来自重量测量的估计含水量进行比较。与水变化相关的具体处理包括将水含量转换为水势,图像水摄取率随时间的计算(时间图像差异),最大摄取深度/宽度的估计,水含量的1D平均曲线(和标准偏差) ,沿着根茎的水吸收。如果根系统的图像与水含量图像共同登记,则可以检查土壤 - 根界面(对于水)的过程,例如与根,根类型或年龄的距离的局部或平均值。还可以获得根密度和摄取之间或根生长与水含量或潜力之间的关系。

  2. 校准单元的处理
    校准单元能够在等式(5)中拟合a,b:。
    校正细胞的图像按照rhizotrons进行处理(参见上面的步骤1),除了值为  ln 是根据初始和饱和图像的每个校准单元中相同感兴趣区域的平均值估算的。方程式中校准函数的(a,b)系数。从水饱和度和ln (图7)之间的线性回归估计图5。随着回归在低含水量下变化,在低饱和度范围内需要第二组参数(低于约3%体积含水量,图7)。
    校准单元的比色尺度调整参考每个根茎的时间序列的第一个图像,导致每个根际结构的校准方程略有不同。 


    图7.从水饱和度之间的校准单元图像得到的校准和ln .校准方程为(见方程式5)其中a和b通过线性回归拟合。需要两个回归。
  3. 通过图像处理验证根瘤菌的估计含水量
    为了消除校准细胞和根瘤菌之间压实变化的可能残余影响,最终测试包括比较从校准图像估计的根瘤菌的平均体积水和从根瘤谷时间的称重。这通常导致R 2 的回归线。 0.99,但如果斜率几乎等于1,则可能出现小的偏差(体积含水量约为1%)。在这种情况下,通过该回归方程,可以将根据图像估计的含水量转换为“真实”含水量(来自重量测量)。 
  4. 处理根系统的图像
    如果根系统在根瘤子前面的透明胶片上描绘,则可以扫描胶片并且例如用IJ_Rhizo软件(Pierret 等人,2013)分割所得到的图像。当rizet和Draye(2013)中可以找到一种在分解rhizotron并暴露根系统时对复杂根系进行矢量化的方法。如果从透明胶片图或rhizotron槽时间图像中追随根生长是有意义的话,SmartToot软件(Lobet et al。,2011)将被有效地使用,因为它可以实现根的半自动跟踪在图像系列。可以获得诸如生长,拓扑,横向密度,直径的输出。
    无论根处理软件是什么,如果在水分含量的成像实验的同时将根茎中的根系统从图像中分割出来,则分段根系统的图像和根状茎中的水含量的配准使得能够关联根参数(根密度,根龄,根类型,生长...)和土壤中的含水量或吸收量。 
  5. 更进一步:在建模中使用成像实验
    最初设计了植物吸水的光透射成像,以验证根系吸水的详细模型的一致性。这种建模结合了根系统结构,水流进入和沿着根系统的调节,土壤中的机械水转移(Doussan et al。,1998; Doussan et al。 ,2006)。自(Javaux et al。,2008; Schneider et al。,2010)以来,这种建模方法得到了扩展。光照传播成像的模型,在或多或少的根茎羽扇豆根系统的情况下,表明摄取是由单根尺度的局部土 - 根相互作用驱动的,与根和根径向附近的土壤水力传导率的变化有关。电导率。这些相互作用在根系统尺度上通过水分布和根轴向传导进行调节(Doussan et al。,2006)。根系统结构的变化和根系水力传导的分布,定义不同的根系表型,将引起水吸收模式的变化。使用详细的吸水模型结合水含量的成像结果测试这些不同的表型,可以获得难以测量的参数的估计,例如根水力传导率,分布的根水吸收速率或根木质部水势。建模和实验的结合也可以帮助测试生物学和生理学假设,例如ABA生产和水通量的调节(Lobet,2013)。通过成像实验支持的建模,可以将植物行为(例如,针对不同的根表型)外推到其他土壤/气候条件(例如,用于观察水面)摄取效率),在后续步骤中指导实验验证(在现场或受控条件下)。

笔记

4毫米的空隙,充满土壤,厚度是一个很好的折衷方案,通过rhizotron获得足够的光线,并使沙土的干/湿状态之间的良好对比。稍大的厚度可用于容纳较厚的根(最多6毫米),但代价是较低的对比度。

食谱

  1. 改良Hoagland解决方案(表1)

    表1.改良Hoagland溶液的组成。此溶液中的铁含量翻了一番(改编自Lobet and Draye,2013) 

致谢

这项工作得益于INSU-CNRS“国家水文计划(PNRH)”99-PNRH-39和Agropolis基金会的支持。

利益争夺

作者宣称没有利益冲突。

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引用:Doussan, C. and Garrigues, E. (2019). Measuring and Imaging the Soil-root-water System with a Light Transmission 2D Technique. Bio-protocol 9(6): e3190. DOI: 10.21769/BioProtoc.3190.
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