Three-dimensional modeling method for vascular bundle of corn stalk node

Abstract

An embodiment of the invention provides a three-dimensional modeling method for a vascular bundle of a corn stalk node, and relates to the field of botany. The method comprises the steps of S1, performing iodine staining processing on a corn stalk node sample to obtain a stained corn stalk node sample; and S2, based on the stained corn stalk node sample, performing Micro-CT scanning to obtain a three-dimensional model of the vascular bundle of the corn stalk node sample. The three-dimensional model of the vascular bundle of the corn stalk node is built through the Micro-CT scanning; paraffin sections are prepared without destroying the shape structure of the corn stalk node; the workload is small; obtained CT scanning image features are consistent; a unified image reconstruction algorithm can be used; and the precision of the obtained three-dimensional model is high.

Description

technical field [0001] The embodiments of the present invention relate to the field of botany, and more specifically, relate to a three-dimensional modeling method for vascular bundles of corn stem nodes. Background technique [0002] The stem vascular bundle system connecting the "source" and "sink" of maize is the key transport organization for plant water transportation. The vascular bundle is mainly divided into phloem and xylem. The former includes sieve tubes and companion cells, which are mainly responsible for the transport of assimilates in a dissolved state. ; The latter is dominated by conduits, which are responsible for transporting water and inorganic salts, and play an important role in plants adapting to drought and water-scarce environments. The morphological structure of crop stems with high potential adaptability to the environment often has strong plasticity, which enables them to increase the transport capacity of water and substances through changes in t...

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Problems solved by technology

[0004] However, in the above-mentioned 3D modeling method based on sequential slice images, the process of making paraffin slices in the early stage is relatively cumbersome, and multiple sequential slice images need to be registered during image reconstruction in the later stage, resulting in a large workload and low efficiency in the entire 3D modeling process. And because the characteristics of each sequence slice image are different, the corresponding image segmentation algorithm is also different, resulting in low precision of the final 3D model

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