A method for modeling seed radicle growth based on three-dimensional images
By acquiring three-dimensional image data of maize seed radicles using computed tomography (CT) technology, a coaxial stacked growth model of radicles was constructed, overcoming the shortcomings of traditional detection methods and achieving non-destructive testing and efficient, accurate simulation of seed radicle growth.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTH CHINA AGRICULTURAL UNIVERSITY
- Filing Date
- 2024-09-20
- Publication Date
- 2026-07-21
AI Technical Summary
Traditional methods make it difficult to observe the growth of maize seed radicles without damaging the soil, and the measurement methods are destructive, making it difficult to guarantee the continuity and accuracy of the experiment.
Three-dimensional image data of seeds and surrounding soil were obtained using computed tomography (CT) technology. A growth model of seeds and their radicles was constructed using a coaxial stacking growth method of radicles, and the radicle ring structure was given motion properties to simulate the growth process.
This technology enables non-destructive testing without disrupting the seed growth environment, improving testing efficiency and quality, reducing experimental bias caused by individual differences, and ensuring the accuracy and continuity of simulation.
Smart Images
Figure CN119206071B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of three-dimensional modeling technology for crops, specifically to a method for modeling seed radicle growth based on three-dimensional images. Background Technology
[0002] As one of my country's three major grain crops, corn has significant economic value. However, because it is a seed with cotyledons remaining in the soil, traditional observation methods make it difficult to observe its root growth without damaging the soil. Furthermore, most traditional measurement methods are destructive and cannot guarantee the continuity of experiments.
[0003] With the advent of non-destructive testing technology such as computed tomography (CT), CT offers numerous advantages over traditional destructive testing. The generated tomographic images clearly show the relationships between objects with significantly different densities, such as the relationship between seed radicles and soil. Furthermore, it provides more detailed three-dimensional data, helping us better understand the morphology and structure of seed radicles during soil growth. Moreover, it allows for continuous measurement during crop growth without disrupting the seed growth environment, greatly ensuring experimental consistency. Based on the provided three-dimensional tomographic images, a model can be constructed using a method of coaxial stacking of radicles. Therefore, using tomographic images presented by CT technology provides a highly effective method for modeling seed radicle growth.
[0004] Currently, there is no method that uses computed tomography (CT) to model seed radicle growth. Summary of the Invention
[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a seed radicle growth modeling method based on three-dimensional images. The seed radicle growth modeling method can construct a seed radicle model for simulation without damaging the seed growth environment, which greatly improves the scientific accuracy.
[0006] The technical solution of the present invention to solve the above-mentioned technical problems is:
[0007] A method for modeling seed radicle growth based on 3D images includes the following steps:
[0008] S1: Use tomographic scanning technology to scan the structure and outline of the seeds in the container to obtain three-dimensional image data of the seeds and the surrounding soil;
[0009] S2: Import the scanned 3D image data into computer software to obtain the original image, and reconstruct the original image to obtain the 3D model data of the seed and its radicle.
[0010] S3: Based on the obtained three-dimensional model data of the seed and its radicle, construct a seed model and a radicle model with a continuous ring structure;
[0011] S4: Continuously scan the seed and its radicle during the growth cycle. Based on the growth of the radicle, assign motion properties to each ring structure in the radicle model to construct a growth model of the seed and its radicle to simulate the growth of the radicle.
[0012] Preferably, in step S1, a three-dimensional X-ray emitted by a computed tomography (CT) scanner is used to scan the structure and outline of the seeds in the container to obtain three-dimensional image data of the seeds and the surrounding soil; the specific steps are as follows:
[0013] S101: Plant the seeds in the container and fix the container on the sample stage of the computed tomography scanner.
[0014] S102: Select the scanning mode, set the parameters of the computed tomography scanner, and set the cross-sectional interval according to the required observation accuracy. Use the computed tomography scanner to scan the soil and seeds to obtain all cross-sectional images of the seeds and their radicles.
[0015] Preferably, in step S102, the scanning mode includes eccentric rotation and concentric rotation.
[0016] Preferably, in step S102, the parameters of the computed tomography scanner include voltage, current, rotation step distance, and number of images.
[0017] Preferably, in step S2, when reconstructing the original image, the original image needs to be processed, specifically including the following steps:
[0018] S201: Based on the density range of the seeds and their radicles, software tools are used to segment them, separating the seeds and their radicles from the soil and carrier to form a three-dimensional structural image;
[0019] S202: Extract various physical parameters of the seed and its radicle, including seed burial depth, radicle length, diameter data, relative position coordinates, and relative density.
[0020] Preferably, the three-dimensional structural image includes a grayscale image and a color image.
[0021] Preferably, in step S3, the construction steps of the radicle model are as follows:
[0022] S301: Based on the radicle diameter data obtained in step S202, arrange the radicle diameter data that meet the requirements from largest to smallest and mark them with serial numbers;
[0023] S302: Use simulation software to create radicle ring structures. Based on the arranged diameter data, create a series of radicle ring structures. The ring structure with the largest diameter connects to the seed, and the ring structure with the smallest diameter serves as the tail. Finally, stack all the ring structures on the same plane and embed them into the seed model.
[0024] Preferably, in step S4, the specific steps for constructing the growth model of the seed and its radicle are as follows:
[0025] S401: During the seed rooting growth cycle, repeat steps S1 and S2 at regular intervals to obtain seed radicle growth data at different stages.
[0026] S402: Construct a coordinate system with the connection between the radicle and the seed as the origin, extract the spatial coordinate points of the radicle tip from the three-dimensional image of each time period to calculate the average value of the spatial coordinate points of the dynamic growth of the radicle tip, so as to obtain the average trajectory of the dynamic growth of the radicle, and assign different starting motion behaviors to each radicle annular structure according to the average trajectory.
[0027] S403: All the radicle ring structures are moved sequentially from the end of the radicle with the smallest diameter to the root of the radicle with the largest diameter, respectively, at specific speeds and directions, ultimately achieving the purpose of simulating the dynamic process of seed radicle growth.
[0028] Preferably, in step S4, after the growth model of the seed and its radicle is constructed, the accuracy and reliability of the growth model need to be verified. The specific steps are as follows:
[0029] Seeds and their radicles are removed from the soil, and excess topsoil is cleared. The growth length and direction of the radicle are measured and compared with the output of the seed and radicle growth model. The error between the two measurements is then assessed to determine if it is within the allowable accuracy range, thus evaluating the accuracy and reliability of the seed and radicle growth model. If the error is outside the allowable accuracy range, the seed and radicle growth model needs to be adjusted and corrected until its accuracy and reliability meet the accuracy requirements.
[0030] Preferably, in step S402, the motion behavior includes displacement and rotation along an average trajectory.
[0031] Compared with the prior art, the present invention has the following advantages:
[0032] 1. The seed radicle growth modeling method based on three-dimensional images of the present invention adopts the non-destructive testing method of tomography, which can extract tomographic three-dimensional image data of seed radicles at specified intervals in the soil. Based on this tomographic three-dimensional image data, the growth model of the seed and its radicle is constructed by the method of coaxial stacking growth of radicles. In this way, the growth model of the seed and its radicle can be constructed and simulated without damaging the seed growth environment, which greatly improves the scientificity.
[0033] 2. The seed radicle growth modeling method based on three-dimensional images of the present invention uses a non-destructive testing method, which can continuously acquire the physical parameters of the seed and its radicle and their position in the soil, which can greatly improve the detection efficiency and detection quality, and can observe the growth process of the same seed in the soil throughout the entire process, greatly reducing experimental deviations caused by individual differences.
[0034] 3. The seed and radicle growth model constructed in this invention uses three-dimensional image data to construct multiple ring structures of the radicle, and assigns different motion states to each ring structure of the radicle according to the actual growth situation, thereby ensuring the accuracy of the simulation process. Attached Figure Description
[0035] Figure 1 This is a flowchart illustrating the seed radicle growth modeling method based on three-dimensional images according to the present invention.
[0036] Figure 2 This is a schematic diagram of the growth model of a seed and its radicle.
[0037] Figure 3 This is a schematic diagram of the embryonic root model.
[0038] Figure 4 Three-dimensional images of seed radicles in soil obtained by computed tomography. Detailed Implementation
[0039] The present invention will be further described in detail below with reference to the embodiments and accompanying drawings, but the embodiments of the present invention are not limited thereto.
[0040] See Figures 1-4 The seed radicle growth modeling method based on three-dimensional images of the present invention includes the following steps:
[0041] S1: Use tomographic scanning technology to scan the structure and outline of the seeds in the container to obtain three-dimensional image data of the seeds and the surrounding soil;
[0042] In this embodiment, a three-dimensional X-ray emitted by a computed tomography (CT) scanner is used to scan the structure and outline of the seeds in the container to obtain three-dimensional image data of the seeds and the surrounding soil; the specific steps are as follows:
[0043] S101: Plant the seeds in the container and fix the container on the sample stage of the computed tomography scanner.
[0044] S102: Select the scanning mode according to the actual situation. The scanning mode includes eccentric rotational scanning and concentric rotational scanning. Set the parameters of the computed tomography scanner, including voltage, current, rotation step distance and number of images. Set the tomographic interval according to the required observation accuracy. Use the computed tomography scanner to scan the soil and seeds to ensure that the soil around the seeds and their radicles (including the top, bottom and sides) is covered, and finally obtain all tomographic images of the seeds and their radicles.
[0045] S2: Import the scanned 3D image data into computer software to obtain the original image, and reconstruct the original image to obtain the 3D model data of the seed and its radicle, so as to present the complete and clear 3D structure of the entire seed and radicle. At the same time, use the supporting software to fully display the 3D spatial distribution of the seed and radicle inside the soil.
[0046] In the above process, the original image data needs to be processed to remove interference and irrelevant parts of the soil in order to obtain accurate three-dimensional model data of the seed and its radicle. The specific steps include:
[0047] S201: Based on the density range of the seeds and their radicles, software tools are used to segment them, separating the seeds and their radicles from the soil and carrier to form a three-dimensional structural image, wherein the three-dimensional structural image includes a grayscale image and a color image.
[0048] S202: Extract various physical parameters of the seed and its radicle, including seed burial depth, radicle length, diameter data, relative position coordinates, and relative density.
[0049] Furthermore, 3D image data consists of X-ray images acquired from different angles. To reconstruct these 3D image data into a 3D image, mathematical methods of tomographic reconstruction are required. These methods generally employ backprojection and filtered backprojection. The former involves backprojecting each 3D image data along the original acquisition direction and accumulating these projections to obtain a preliminary reconstructed image. The mathematical principle of backprojection is to use the projection theorem to inversely transform 2D projection data back into 3D space. Therefore, the latter is an improvement on the basic backprojection method. It first applies a filter (usually a Langios filter or Hanning filter) to each 3D image data to enhance the image's edges and details, and then performs backprojection. The purpose of filtering is to eliminate the blurring effect generated during the backprojection process, thereby improving the clarity of the reconstructed image. The accompanying computer software automatically completes the reconstruction using both methods.
[0050] S3: Based on the obtained three-dimensional model data of the seed and its radicle, construct a seed model and a radicle model with a continuous ring structure; wherein, the construction steps of the radicle model are as follows:
[0051] S301: Based on the radicle diameter data obtained in step S202, arrange the radicle diameter data that meet the requirements from largest to smallest and mark them with serial numbers;
[0052] S302: Use simulation software to create radicle ring structures. Based on the arranged diameter data, create a series of radicle ring structures. The ring structure with the largest diameter connects to the seed, and the ring structure with the smallest diameter serves as the tail. Finally, stack all the ring structures on the same plane and embed them into the seed model.
[0053] In this embodiment, the principle of radicle modeling is to generate a series of ring-shaped structures using simulation software. These ring-shaped structures are arranged in descending order of diameter, stacked on the same plane, and embedded inside the seed model. This process is based on accurate 3D model data obtained from 3D X-ray scanning and data reconstruction to simulate the growth and structure of the radicle. Information extracted after data reconstruction is used to input the diameter data of each ring-shaped structure (e.g., the initial length of each ring-shaped structure is 0.1 mm, but the diameters of the ring-shaped structures are 0.5 mm, 1 mm, 2 mm, 1.3 mm, 2.4 mm, etc.). This data determines the size and arrangement order of the ring-shaped structures. A series of ring-shaped structures are generated using this data. According to preset arrangement rules and logic, these ring-shaped structures are arranged in sequence. Since the ring-shaped structures of the radicle are usually arranged in a certain order in nature, stacking them on the same plane can better simulate this natural arrangement. Furthermore, this arrangement can also increase the stability of the entire structure, avoiding morphological instability caused by the dispersion of the ring-shaped structures. In addition, embedding the ring-shaped structures inside the seed model facilitates subsequent growth simulation and analysis, ensuring the consistency and integrity of the model. Furthermore, the purpose of this design principle is to reproduce the natural growth process of the radicle as much as possible and to provide a stable and accurate model for the next step of assigned growth research.
[0054] S4: Continuously scan the seed and its radicle during the growth cycle. Based on the growth of the radicle, assign motion properties to each ring structure in the radicle model to construct a growth model of the seed and its radicle to simulate the growth of the radicle.
[0055] In this embodiment, the specific steps for constructing a growth model of a seed and its radicle are as follows:
[0056] S401: During the seed rooting growth cycle, repeat steps S1 and S2 at regular intervals to obtain seed radicle growth data at different stages.
[0057] S402: Construct a coordinate system with the connection between the radicle and the seed as the origin. Extract the spatial coordinate points of the radicle tip from the three-dimensional image of each time period to calculate the average value of the spatial coordinate points of the dynamic growth of the radicle tip, so as to obtain the average trajectory of the dynamic growth of the radicle. According to the average trajectory, assign different motion behaviors to each radicle annular structure, including displacement and rotation along the average trajectory.
[0058] S403: All the radicle ring structures are moved sequentially from the end of the radicle with the smallest diameter to the root of the radicle with the largest diameter, respectively, at specific speeds and directions, so as to achieve the purpose of simulating the dynamic process of seed radicle growth.
[0059] In this embodiment, the assigned speed is calculated based on the average growth rate of the radicle tip within the time cycle of radicle growth. Specifically, the displacement of the radicle tip within each time cycle is calculated, and the average displacement within each time cycle is taken as the elongation speed of the annular structure; that is, speed = ∑(displacement) / number of time cycles. The assigned direction is determined based on the direction of change of the spatial coordinates of the radicle tip. Specifically, the spatial coordinate change vector of the radicle tip within each time cycle is calculated, and the average value of the change vector within each time cycle is taken as the translation or rotation direction of the annular structure; that is, direction = ∑(change vector) / number of time cycles.
[0060] S405: After the growth model of the seed and its radicle is constructed, the accuracy and reliability of the growth model need to be verified. The specific steps are as follows:
[0061] Seeds and their radicles are removed from the soil, and excess topsoil is cleared. The growth length and direction of the radicle are measured and compared with the output of the seed and radicle growth model. The error between the two measurements is then assessed to determine if it is within the allowable accuracy range, thus evaluating the accuracy and reliability of the seed and radicle growth model. If the error is outside the allowable accuracy range, the seed and radicle growth model needs to be adjusted and corrected until its accuracy and reliability meet the accuracy requirements.
[0062] In this embodiment, after the growth model of the seed and its radicle is established, the growth of the seed root system can be calculated using the following data: (1) Spatial coordinate data: three-dimensional spatial coordinate data of the radicle tip at different time points obtained by repeated scanning; (2) Growth length: the growth length of the radicle in each time period is obtained by calculating the change in the position of the radicle tip; (3) Growth rate: the growth rate of the radicle in different growth stages is calculated based on the growth length and time interval; (4) Growth direction: the growth direction of the radicle is obtained by analyzing the change in the position of the radicle tip; (5) Physical parameters: such as radicle diameter, seed burial depth, relative density, etc. Through the above data, the growth morphology and structural changes of the radicle can be further analyzed. Through the comprehensive analysis of the above data, the growth of the seed root system can be fully calculated and evaluated, and the dynamic process and law of radicle growth can be obtained.
[0063] The above are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above content. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.
Claims
1. A method for modeling seed radicle growth based on three-dimensional images, characterized in that, Includes the following steps: S1: Use tomographic scanning technology to scan the structure and outline of the seeds in the container to obtain three-dimensional image data of the seeds and the surrounding soil; S2: Import the scanned 3D image data into computer software to obtain the original image, and reconstruct the original image to obtain the 3D model data of the seed and its radicle. S3: Based on the obtained three-dimensional model data of the seed and its radicle, construct a seed model and a radicle model with a continuous ring structure; wherein, the construction steps of the radicle model are as follows: S301: Based on the radicle diameter data obtained in step S202, arrange the radicle diameter data that meet the requirements from largest to smallest and mark them with serial numbers; S302: Using simulation software, create a series of radicle ring structures. Based on the pre-arranged diameter data, the largest diameter ring connects to the seed, and the smallest diameter ring serves as the tail. Finally, stack all the ring structures on the same plane and embed them inside the seed model. S4: Continuously scan the seed and its radicle during the growth cycle. Based on the radicle growth, assign motion attributes to each ring structure in the radicle model to construct a growth model of the seed and its radicle to simulate radicle growth. The specific steps for constructing the seed and its radicle growth model are as follows: S401: During the seed rooting growth cycle, repeat steps S1 and S2 at regular intervals to obtain seed radicle growth data at different stages. S402: Construct a coordinate system with the connection between the radicle and the seed as the origin, extract the spatial coordinate points of the radicle tip from the three-dimensional image of each time period to calculate the average value of the spatial coordinate points of the dynamic growth of the radicle tip, so as to obtain the average trajectory of the dynamic growth of the radicle, and assign different starting motion behaviors to each radicle annular structure according to the average trajectory. S403: All the radicle ring structures are moved sequentially from the end of the radicle with the smallest diameter to the root of the radicle with the largest diameter, respectively, at specific speeds and directions, ultimately achieving the purpose of simulating the dynamic process of seed radicle growth.
2. The seed radicle growth modeling method based on three-dimensional images according to claim 1, characterized in that, In step S1, a three-dimensional X-ray scanner is used to scan the structure and outline of the seeds in the container to obtain three-dimensional image data of the seeds and the surrounding soil; the specific steps are as follows: S101: Plant the seeds in the container and fix the container on the sample stage of the computed tomography scanner. S102: Select the scanning mode, set the parameters of the computed tomography scanner, and set the cross-sectional interval according to the required observation accuracy. Use the computed tomography scanner to scan the soil and seeds to obtain all cross-sectional images of the seeds and their radicles.
3. The seed radicle growth modeling method based on three-dimensional images according to claim 2, characterized in that, In step S102, the scanning mode includes eccentric rotation and concentric rotation.
4. The seed radicle growth modeling method based on three-dimensional images according to claim 2, characterized in that, In step S102, the parameters of the computed tomography scanner include voltage, current, rotation step distance, and number of images.
5. The seed radicle growth modeling method based on three-dimensional images according to claim 1, characterized in that, In step S2, when reconstructing the original image, the original image needs to be processed, specifically including the following steps: S201: Based on the density range of the seeds and their radicles, software tools are used to segment them, separating the seeds and their radicles from the soil and carrier to form a three-dimensional structural image; S202: Extract various physical parameters of the seed and its radicle, including seed burial depth, radicle length, diameter data, relative position coordinates, and relative density.
6. The seed radicle growth modeling method based on three-dimensional images according to claim 5, characterized in that, The three-dimensional structural image includes grayscale images and color images.
7. The seed radicle growth modeling method based on three-dimensional images according to claim 1, characterized in that, In step S4, after the growth model of the seed and its radicle is constructed, it is necessary to verify the accuracy and reliability of the growth model. The specific steps are as follows: Seeds and their radicles are removed from the soil, and excess topsoil is cleared. The growth length and direction of the radicle are measured and compared with the output of the seed and radicle growth model. The error between the two measurements is then assessed to determine if it is within the allowable accuracy range, thus evaluating the accuracy and reliability of the seed and radicle growth model. If the error is outside the allowable accuracy range, the seed and radicle growth model needs to be adjusted and corrected until its accuracy and reliability meet the accuracy requirements.
8. The seed radicle growth modeling method based on three-dimensional images according to claim 7, characterized in that, In step S402, the motion behavior includes displacement and rotation along an average trajectory.