Techniques de phénotypage micron-échelle de maïs faisceaux vasculaires issu de tomographie à rayons x Microcomputed

This method can have answer quick questions in the planned micron-scale phenotyping techniques build. Such as micro-CT scanning particles, and the phenotypic analysis method for maize vascular bundles. The main advantage of this technique is to provide new and effective ways to investigate phenotypical traits of maize vascular bundle by sample preparation, CT scanning, and analysis of protocols.

The implications of this technique broadens applications of ordinary micro-CT scanning and other plant sciences. This protocol can be easily modified to accommodate other plant materials, such as dehydration of drying procedure. To begin, collect the stem, leaf, and root from fresh maize plants.

And divide them into three sample groups. Next, use a surgical blade to cut a one to 1.5 centimeter segment of the middle stem internode. Using the same surgical blade, cut a 1/2 to two centimeter segment from the maximum width of the leaf along the vertical direction with the main vein.

Use the surgical blade to cut a 1/2 centimeter segment from the ground root. After this, soak the sample segments in FAA solution for at least three days. Dehydrate the sample segments for 30 minutes in six sequential ethanol gradients.

Then place the plant materials in the corresponding sample baskets. Quickly transfer the baskets to the sample cell of a carbon dioxide critical point drying system. Place the dried plant materials into a 50 milliliter centrifuge tube with two grams of solid iodine.

Then place the tubes in a light-proof room for four to five hours. First, set the CT scanning parameters according to the text protocol. Then, set the scanning ranges according to the different sizes and volumes of the plant materials used.

Next, adjust the imaging pixel sizes as follows:Two micrometers for the root. 6.77 micrometers for the stem. And 10 micrometers for the leaf.

To reconstruct slice images, use imagery construction software to convert the raw CT data into CT slice images with 2K resolution. First, specify the organ type to initialize different algorithm pipelines in the automatic imaging software. Then, click the method parameters button and select maize stem, or maize leaf, in the first drop-down box.

Click the data management button, set the work directory, and import all of slice images in the directory. Then select single or multi-slice images into the image pipelines. Next, determine the pixel size of the image.

Pick the method parameters button and enter the pixel size of the image in the appropriate edit item. After this, click the phenotyping computation button to automatically extract phenotypic traits of the vascular bundles for all of the selected slice images. Click the statistical analysis button to output the results of these analysis as a text or CSV file.

Import the reconstructed images of maize roots, and determine the accurate space parameters. Then use the recursive gaussian tool to smooth the images, and improve image quality. Adjust the threshold parameters to conduct 3D segmentation of metaxylem vessels.

This will create a uniform color label for each connected metaxylem vessel. Then, improve and identify the metaxylem vessels interactively using morphology bitwise, and flood-fill operations. Next, conduct a volume visualization and surface reconstruction of the vessels.

Finally, use the mask statistics tool to count and measure the phenotypic traits of a vessel at the 2D and 3D levels. Using the analysis outlined in the protocol, the phenotypic traits of vascular bundles in maize stems, leaves, and roots were computed. A generated 3D visualization of the root and metaxylem vessels was created, using the results of segmentation, reconstruction, and volume visualization.

The proper sample preparation protocol significantly improves the scanning emitting quality of micro-CT for maize stem, leaf, and root. With the automatic emit pipeline to rapidly extract the phenotypical traits of vascular bundles for maize stem and leaf. And the setup and emit processing scan to analyze the 3D phenotypic traits of vascular bundles for maize root.

This technique provides a practical way for accurate and rapid phenotypic qualification and identification of maize vascular bundles.