Rice stem multi-scale mechanical simulation modeling method, device, equipment and medium

Abstract

The invention discloses a rice stem multi-scale mechanical simulation modeling method, device and equipment and a medium. The method comprises the following steps: selecting a second base node stem of a mature period base of a rice variety to be tested as a sample; microcosmic characteristic parameters of the sample are extracted; based on the extracted microscopic characteristic parameters, material parameter calculation is carried out based on an HP-TS equation, hemicellulose-lignin matrix equivalent calculation, cellulose-matrix composite equivalent calculation, flexibility matrix and initial stiffness matrix construction and microfibril angle correction are completed in sequence, and an engineering constant of each layer of cell wall is obtained; performing image processing on the rice stalk paraffin section; constructing a rice stem tissue three-dimensional shell finite element model based on the cellular morphology contour and topological information obtained through image processing and the cell wall engineering constants obtained through calculation, and executing finite element simulation; actual measurement data are obtained through a rice stem tensile test and compared with a finite element simulation result for verification, and rice stem multi-scale mechanical simulation modeling is completed.

Description

Technical Field

[0001] This invention relates to crop simulation modeling technology, specifically to a method, apparatus, equipment, and medium for multi-scale mechanical simulation modeling of rice stems. Background Technology

[0002] The rice stem, as the core organ supporting the plant and transporting nutrients and water, has mechanical properties that are a key indicator of lodging resistance. Insufficient lodging resistance leads to lodging at maturity, resulting in decreased photosynthetic efficiency, inadequate grain filling, and severely impacting yield and quality. Rice cells are the basic units constituting rice stem tissue, and the cell wall, as the basic cellular framework, bears the main mechanical strength of the rice stem. Therefore, conducting multi-scale mechanical simulation modeling research on rice stems, from the microscopic cellular level to the macroscopic plant level, is of significant practical importance for revealing the lodging resistance mechanism of rice and guiding high-yield, lodging-resistant breeding and cultivation regulation.

[0003] Currently, rice stem mechanics research and modeling techniques still suffer from many technical shortcomings that urgently need to be addressed, making it difficult to meet the needs of actual scientific research and production. These shortcomings are manifested in the following three aspects: First, single-scale modeling has significant limitations and insufficient cross-scale coupling. Existing studies mostly focus on a single scale, either obtaining the overall mechanical parameters of the stem through macroscopic tensile and bending tests, which can only reflect macroscopic mechanical performance and cannot reveal the regulatory mechanism of microscopic structure (such as cell wall thickness and microfibril angle) on macroscopic mechanical properties; or relying solely on transmission electron microscopy, XRD and other methods to obtain microscopic parameters, or extracting cell morphology features through image processing, but failing to establish the correlation between microscopic characteristics and macroscopic mechanical performance. The modeling lacks cross-scale parameter support and cannot achieve full-scale analysis from microscopic cells to tissues and then to macroscopic stems.

[0004] Secondly, the coupling between microscopic features and image processing technology is low, resulting in insufficient modeling accuracy. Existing multi-scale modeling research generally fails to deeply integrate microscopic feature extraction with image processing technology. On the one hand, it does not accurately construct the mechanical parameters of different cell wall layers using the HP-TS equation (Halpin-Tsai equation), leading to a lack of refined parameter assignment for the cell wall skeleton. On the other hand, existing cell skeleton extraction algorithms lack applicability and cannot efficiently preserve key information such as the morphology and distribution of stem cells. This results in poor matching between the established multi-scale mechanical model and the actual structure and mechanical properties of rice stems, making it difficult to guarantee the accuracy and reliability of simulation results.

[0005] Third, the technical chain is incomplete and lacks closed-loop verification. Existing modeling methods have not formed a complete technical chain of "microscopic parameter acquisition - crop modeling - macroscopic simulation verification". The model has weak cross-scale connectivity and cannot accurately analyze the influence of stem micro-characteristics on mechanical properties at the micro-scale. This makes it difficult to support in-depth research on the lodging resistance mechanism of rice stems and the needs of variety improvement.

[0006] In summary, existing rice stem mechanics simulation modeling techniques suffer from limitations such as single-scale constraints, insufficient cross-scale coupling, low coupling between microscopic features and image processing, and incomplete technical chains. These issues lead to low modeling accuracy and unreliable simulation results, failing to meet the needs of scientific research and production. Therefore, there is an urgent need for a multi-scale mechanics simulation modeling method for rice stems that can achieve deep coupling between microscopic features and image processing, smooth cross-scale connections, and a complete technical chain, thereby solving the existing technical challenges. Summary of the Invention

[0007] The purpose of this invention is to overcome the aforementioned problems and provide a multi-scale mechanical simulation modeling method, device, equipment, and medium for rice stems. This method can achieve deep integration of microscopic parameters, cell structure images, and HP-TS equations, accurately construct a finite element model of rice stems that closely matches the real structure, improve the accuracy of simulation results, and verify the reliability of the model through macroscopic mechanical testing. This provides reliable technical support for the study of lodging resistance mechanisms in rice stems and for high-yield, lodging-resistant breeding.

[0008] The objective of this invention is achieved through the following technical solution: A multi-scale mechanical simulation modeling method for rice stems includes the following steps: The second basal segment of the stem at maturity of the tested rice variety was selected as a sample. The sample was cultivated under uniform planting and management conditions to ensure the consistency of the experimental materials. Microscopic feature parameters of the sample are extracted, including the thickness of cell walls of different types and layers of rice stem cells, the angle of microfibrils, and the material composition. Based on the extracted microscopic feature parameters, material parameters are calculated based on the HP-TS equation. The equivalent calculation of hemicellulose-lignin matrix, the equivalent calculation of cellulose-matrix composite, the construction of flexibility matrix and initial stiffness matrix, and the correction of microfibril angle are completed in sequence to obtain the engineering constants of each cell wall layer. Image processing was performed on paraffin sections of rice stems, sequentially completing microscopic image acquisition, binarization, cell centroid coordinate extraction, Delaunay triangulation, and distance-weighted Voronoi triangulation to obtain accurate cell morphological contours and topological information. Based on the cell morphology contours and topological information obtained from image processing and the calculated cell wall engineering constants, a three-dimensional shell finite element model of rice stem tissue was constructed. Material properties and boundary conditions were defined and meshed, and finite element simulation was performed. Measured data were obtained through rice stem tensile tests, and compared with finite element simulation results to verify the model accuracy and complete the multi-scale mechanical simulation modeling of rice stems.

[0009] In a preferred embodiment of the present invention, the step of extracting the cell wall thickness of different types and layers of rice stem cells includes: Rice stem samples were placed in 0.2M phosphate buffer containing 4% glutaraldehyde + 2% paraformaldehyde and left to stand at 4°C for 24 hours. Rinse the sample several times with fresh phosphate buffer; At 25°C, the mixture was left to stand for a specified time in a 1% osmium tetroxide + 1% potassium ferric cyanide solution, and then rinsed several times with the above-mentioned phosphate buffer solution. It is dehydrated by a series of different gradients of ethanol, and then permeated with a series of different ratios of acetone-Spur resin gradient mixtures; At 60℃, the resin was embedded for 24 hours, and 70-100nm ultrathin sections were cut using a microtome. The cells were stained in 2% potassium permanganate for several minutes, and then imaged using a transmission electron microscope to extract cell wall thickness parameters.

[0010] In a preferred embodiment of the present invention, the step of extracting the angles of microfibrils in the cell walls of different types and layers of rice stem cells includes: Rice samples were placed in the test area of ​​an X-ray diffractometer, which was used with a Rigaku rotating anode X-ray tube as the X-ray source. Gaussian multi-peak deconvolution processing was performed on the diffraction pattern using a continuous scanning mode; The angular distribution of microfibers was determined by azimuth intensity scanning, and the grain size was calculated using the Scherrer equation, which is: ; Where D represents the grain size, K represents the Scherrer constant with a value of 0.9, λ represents the wavelength of the incident X-ray, B represents the full width at half maximum (FWHM) of the diffraction peak, and xc represents the Bragg angle.

[0011] In a preferred embodiment of the present invention, the step of extracting cell wall materials of different types and layers from rice stem cells includes: The sample was placed in the Raman electron microscope test area and a laser Raman-photoelectric imaging-fluorescence lifetime imaging system was used in conjunction with a confocal microscope. Set the excitation parameters; the laser diffraction restricts the spot to move line by line in the defined area to obtain the spectrum in the range of 400-2070 cm⁻¹; Root tissue sections were obtained by cryosectioning, and water was used as the embedding agent. The complete sections were placed on a quartz glass slide whose surface was hydrophilicized. Spectral curves were acquired using a confocal microscope. The self-fluorescence properties of the quartz slide were utilized to reduce background fluorescence signals, improve the signal-to-noise ratio of the spectral curves, and extract the composition parameters of the cell wall material.

[0012] In a preferred embodiment of the present invention, the step of calculating material parameters includes: First equivalent calculation: The middle layer and secondary wall matrix are composed of hemicellulose and lignin. They are equivalent to a single matrix material. The longitudinal elastic modulus and Poisson's ratio are calculated using the mixing ratio rule, and the shear modulus is calculated using the Halpin-Tsai equation. Second equivalent calculation: Using the mixed matrix obtained in the first equivalent calculation as the new matrix and cellulose as the reinforcing phase, the longitudinal elastic modulus and longitudinal Poisson's ratio are calculated using the mixing ratio rule, and the transverse elastic modulus and shear modulus are calculated using the Halpin-Tsai equation. Based on the assumption of transverse isotropy, let... Five core elastic constants were obtained; Construction of the Flexibility Matrix and Initial Stiffness Matrix: Based on the assumption of transverse isotropy, a flexibility matrix S is constructed, and the initial stiffness matrix is ​​obtained by inverting the flexibility matrix. A coupling effect correction term is introduced by utilizing the reciprocal relationship of Poisson's ratio; Microfibril angle correction: based on the angle between cellulose microfibrils in each layer of the secondary wall and the stem axis. A transformation matrix T is constructed, and the initial stiffness matrix is ​​transformed from the local coordinate system to the global coordinate system through coordinate transformation to obtain the actual three-dimensional stiffness matrix Q considering the orientation of microfibrils. Finally, the engineering constants of each cell wall layer are obtained.

[0013] In a preferred embodiment of the present invention, the image processing steps include: Imaging of paraffin sections of rice stems using an optical microscope; Median filtering is applied to the original image to remove background noise. The RGB image is converted to grayscale. The Otsu algorithm is used to perform block adaptive threshold segmentation on the sub-blocks. The images are then stitched together to obtain a complete binary image. A connected component analysis algorithm is used to label the binary graph, a noise filtering threshold is set, and the centroid coordinates of each effective connected component are calculated by weighted averaging of pixel coordinates. The centroid set is preprocessed, and the Bowyer-Watson algorithm is used to construct the Delaunay triangulation, ensuring that the minimum interior angle is ≥20°, and the topological information is extracted. Calculate the Euclidean distance between each centroid and its neighboring centroids. Assign weights Using the centroid as the seed point, a weighted Voronoi polygon is generated to obtain the cell morphology outline.

[0014] In a preferred embodiment of the present invention, the steps of establishing and verifying the simulation model include: Based on the image of the cytoskeleton after image processing, a three-dimensional shell model is created, and the shell thickness is set according to the actual thickness of the cell wall. The cross-section of the three-dimensional shell model is divided into epidermal thin-walled tissue, outer cortex thick-walled tissue, and intermediate cortex thin-walled tissue. Material properties are assigned based on cell wall engineering constants, composite layers are created, and differentiated layup sequences are set according to cell type. Constrain all 6 degrees of freedom of the lower surface reference point RP-2, and constrain the other 5 degrees of freedom of the upper surface reference point RP-1 except for the Z-axis translation. Apply a fixed displacement of 10 μm in the Z-axis direction of RP-1. Use 20-node quadratic hexahedral elements to generate the mesh, with the mesh size set to 0.1, and locally refine the mesh in the region of abrupt change in cell wall thickness. Create a static general analysis step, submit the finite element model for solution, extract the tensile force-displacement curve and calculate the longitudinal elastic modulus; conduct tensile tests using an electronic universal testing machine to measure the effective cross-sectional area, compare the measured results with the simulation results, and confirm the model's reliability if the error is controlled within 10%.

[0015] A multi-scale mechanical simulation modeling device for rice stems includes: Sample selection module: used to select the second basal segment of the stem at maturity of the tested rice variety as a sample, and to control the consistency of the planting and management conditions of the sample; Microscopic feature extraction module: used to extract the thickness of cell walls of different types and layers of rice stem cells, microfibril angles, and material composition parameters; Material parameter calculation module: used to perform two equivalent calculations, construct flexibility and stiffness matrices and correct microfibril angles based on microscopic characteristic parameters to obtain cell wall engineering constants; Image processing module: used for microscopic imaging, binarization, centroid extraction, triangulation and Voronoi sectioning of rice stem paraffin sections to obtain cell morphology contours; Simulation modeling module: used to construct a three-dimensional shell finite element model based on cell morphology contours and engineering constants, set material properties, boundary conditions and mesh generation, and perform finite element simulation; Verification module: Used to obtain measured data through rice stem tensile tests, compare it with simulation results, and verify the accuracy of the model.

[0016] An electronic device includes a central processing unit and a memory, wherein the central processing unit is used to invoke and run a computer program stored in the memory to perform the steps of the multi-scale mechanical simulation modeling method for rice stems.

[0017] A computer-readable storage medium is characterized in that it stores a computer program implemented by the multi-scale mechanical simulation modeling method for rice stems in the form of computer-readable instructions, wherein the computer program is called by a computer and executed to perform the steps included in the corresponding method.

[0018] Compared with the prior art, the present invention has the following advantages: This invention achieves deep integration of microscopic parameters, cell structure images, and HP-TS equations, accurately constructing a finite element model of rice stems that closely matches the real structure, improving the accuracy of simulation results. At the same time, the reliability of the model is verified by macroscopic mechanical testing, providing reliable technical support for the study of lodging resistance mechanism of rice stems and high-yield lodging-resistant breeding. It can also serve as a reference for modeling similar dicotyledonous plants like rice. Attached Figure Description

[0019] Figure 1 This is a flowchart of the multi-scale mechanical simulation modeling method for rice stems according to the present invention.

[0020] Figure 2 Transmission electron microscopy images of rice stem cells with different wall layer thicknesses, as presented in this invention.

[0021] Figure 3 This is a paraffin section image of a rice stalk from the present invention.

[0022] Figure 4 This is a binary image of rice stems from the present invention.

[0023] Figure 5 This is an image of the extracted rice stalk skeleton from the present invention.

[0024] Figure 6 This is a schematic diagram of the Delaunay triangulation of rice cells according to the present invention.

[0025] Figure 7 These are schematic diagrams of the conventional Voronoi partitioning and the cell-optimized Voronoi partitioning of the present invention.

[0026] Figure 8 This is a Voronoi reconstruction of a paraffin section of rice stem, as presented in this invention.

[0027] Figure 9 This is a DXF format image of a paraffin section of rice stem from the present invention.

[0028] Figure 10This is an Abques format image of a paraffin section of rice stem from the present invention.

[0029] Figure 11 The abques model of rice stem paraffin sections is the subject of this invention.

[0030] Figure 12 This invention defines the cross-sectional properties of each region of the rice stalk model and the laminated plate model.

[0031] Figure 13 This is a simulation image of the rice stalk model of the present invention. Detailed Implementation

[0032] To enable those skilled in the art to fully understand the technical solutions of the present invention, the present invention will be further described below in conjunction with embodiments and accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0033] Combination Figures 1-13 The multi-scale mechanical simulation modeling method for rice stems in this embodiment includes the following steps: S1. The indica rice varieties “Teyou 638” and “Liangguang Xiangzhan 3” were selected as test varieties, and the second basal segment of the rice stem at the maturity stage was taken as the sample. Both rice varieties were planted in the planting base of Zhanjiang City, Guangdong Province, China. All test materials were planted in the same experimental field with uniform soil fertility, in the same growing season, and with the same irrigation scheme and pest and disease control management to ensure that the growth conditions of the samples were consistent and to reduce experimental errors.

[0034] S2. Extract microscopic characteristic parameters of cell walls from different types and layers of rice stem cells. These microscopic characteristic parameters include cell wall thickness, microfibril angle, and material composition. Specific steps are as follows: S21, Cell wall thickness extraction: Rice stem samples were placed in 0.2M phosphate buffer (pH 7.2) containing 4% glutaraldehyde + 2% paraformaldehyde and fixed at 4°C for 24 hours. Rinse the sample four times with fresh phosphate buffer, 20 minutes each time; At 25°C, the sample was fixed for 4 hours with a mixture of 1% osmium tetroxide and 1% potassium ferricyanide, and then washed 4 times with the above buffer solution. The solution was dehydrated sequentially with 25%, 50%, 75%, 90%, and 100% ethanol (10 minutes per step), and then permeated with a gradient mixture of acetone and Spur resin (5:1, 3:1, 1:1, 1:3, and 1:5) (2 hours per step). At 60°C, the resin was embedded for 24 hours, and 70-100 nm ultrathin sections were cut using a Leica UC7 ultrathin microtome. Stain in 2% potassium permanganate for 15 minutes and image using a FEI F200S field emission transmission electron microscope (200 kV).

[0035] S22, Microfiber Angle Extraction: Rice samples were placed in the X-ray diffractometer test area. The Rigaku rotating anode X-ray tube (Cu target Ka) of the Rigaku-Ultima IV X-ray diffractometer (Japan) was used as the X-ray source, with a wavelength λ of 0.154178 nm, a test voltage of 4 kV, and a test current of 40 mA. A continuous scanning mode was used, with a scanning range from 10° to 60°, a step size of 0.02°, and a scanning speed of 2° / min. Gaussian multi-peak deconvolution processing was applied to the diffraction pattern. The angular distribution of microfibrils was determined by azimuth intensity scanning, while the grain size was calculated using the Stolele equation.

[0036] ; D represents the grain size, K represents the Scherrer constant (0.9), λ represents the wavelength of the incident X-rays (0.15406 nm), B represents the half-width at half maximum (FWHM) of the diffraction peak (in radians), and xc represents the Bragg angle.

[0037] S23, Material Composition Extraction: The sample was placed in the Raman electron microscope test area. The experimental instrument was the WLTEC ALPHA300R laser Raman-photoelectric imaging-fluorescence lifetime imaging system, paired with a confocal microscope. A laser power of 335mW was selected as the exciter laser power, and a high numerical aperture (NA>1) microscope objective lens was used. The laser excitation wavelength was 785nm. The laser diffraction confined the spot to move line by line in the defined area to obtain the spectrum in the range of 400-2070cm-1.

[0038] Root tissue sections were obtained using the cryosection method.

[0039] Water was chosen as the embedding adhesive and quartz slides were used to place the complete tissue sections. The quartz slides have the self-fluorescence properties of the substrate, which can effectively reduce the background fluorescence signal and improve the signal-to-noise ratio of the Raman spectrum under confocal microscopy. At the same time, the surface of the slides was hydrophilized, which can better fix the rice tissue samples, improve the adhesion between the two, and reduce the background signal interference caused by the gap between the tissue samples and the quartz slides, so as to make the obtained spectral curves more stable and accurate.

[0040] S3. Based on the microscopic feature parameters extracted in step S2, the engineering constants (including 3 elastic moduli, 3 shear moduli, and 3 Poisson's ratios) of each cell wall layer are obtained through two equivalent calculations, construction of flexibility and stiffness matrices, and correction of microfibril angles. The specific steps are as follows: S31. First equivalent calculation: hemicellulose-lignin matrix equivalence; The intercellular layer and secondary wall matrix are composed of hemicellulose and lignin. They are first treated as equivalent to a single matrix material, laying the foundation for subsequent compounding with cellulose.

[0041] The longitudinal elastic modulus is obtained by using the mixing ratio rule (ROM) and weighted average according to the volume percentage of the components: ; in, The elastic modulus of hemicellulose, The elastic modulus of lignin. These represent the volume content of each.

[0042] Poisson's ratio is obtained by using the mixing ratio rule and a volume-weighted average: ; in, These are the Poisson's ratios of hemicellulose and lignin, respectively.

[0043] The Halpin-Tsai equation (applicable to short fiber composites) is adopted, and empirical constants are introduced. (Assuming the fiber cross-section is circular), the shear modulus is obtained: , ; in, , These are the shear moduli of hemicellulose and lignin, respectively. To enhance the performance ratio of the phase relative to the matrix.

[0044] S32. Second equivalent calculation (cellulose-matrix composite equivalence): Using the first equivalent mixed matrix as the new matrix and cellulose as the reinforcing phase, the overall mechanical parameters of the secondary wall were obtained, and five core elastic constants were acquired. The longitudinal elastic modulus (along the cellulose microfibrils, direction 1) was obtained by weighted averaging using the mixing ratio rule: ; in, The elastic modulus of cellulose, This refers to the volume content of cellulose. This refers to the volume content of the mixed matrix; The longitudinal Poisson's ratio (in the 1-2 direction, where the 2 direction is transverse) is obtained by weighted averaging using the mixing ratio rule: ; in, is the Poisson's ratio of cellulose.

[0045] The lateral elastic modulus (in two directions) reflecting the lateral stress performance is calculated using the Halpin-Tsai equation: , ; The shear modulus (in directions 1-2) reflecting shear deformation performance is calculated using the Halpin-Tsai equation: , ; in, This is the shear modulus of cellulose.

[0046] Due to the assumption of transverse isotropy (consistent performance in directions 2 and 3), the Poisson's ratio in directions 1-3 is: .

[0047] S33. Construction of the Flexibility Matrix and Initial Stiffness Matrix: Elastic constants need to be expressed in matrix form to represent the stress-strain relationship. The compliance matrix describes the strain produced by a unit stress, and the stiffness matrix is ​​its inverse matrix, describing the stress required for a unit strain.

[0048] Therefore, based on the assumption of transverse isotropy (ignoring coupling terms), the compliance matrix S is constructed as follows: ; In the matrix, the diagonal elements are normal strain coefficients (e.g., The strain in one direction is the strain produced by a unit stress in one direction; the off-diagonal elements are Poisson strain coefficients (e.g., (This represents the strain in two directions produced by a unit stress in one direction; the negative sign indicates contraction).

[0049] Initial stiffness matrix (Obtained by inverting the matrix): ; in, (Poisson's ratios are reciprocal, satisfying the basic principles of elasticity), denominator This is a correction term for coupling effects.

[0050] S34. Microfibril angle correction: Based on the angle between the cellulose microfibrils of each layer of the secondary wall and the axial direction (direction 1) of the stem. A transformation matrix T is constructed, and the initial stiffness matrix is ​​transformed from the local coordinate system (microfibril direction) to the global coordinate system through coordinate transformation to obtain the actual three-dimensional stiffness matrix Q considering the microfibril orientation. Finally, the nine engineering constants of each cell wall layer are obtained, specifically: Transformation matrix T (describes the relationship between the microfiber orientation and the global coordinate system): ; in, Let be the angle of the i-th layer of microfiber (the angle between 1 and the direction 1). The matrix elements are derived from trigonometric function relationships to realize the transformation between the local coordinate system (microfiber direction) and the global coordinate system.

[0051] Actual three-dimensional stiffness matrix : ; in, The transformation matrix is ​​the transpose of the inverse matrix. This formula is used to transform the initial stiffness matrix from the local coordinate system to the global coordinate system, resulting in the actual stiffness matrix considering the orientation of microfibrils. Finally, the engineering constants of each cell wall layer are obtained.

[0052] S4. Rice Stalk Image Processing: A series of image processing steps are performed on paraffin sections of rice stalks to obtain accurate cell morphology contours and topological information, providing a geometric basis for subsequent simulation modeling. The specific steps are as follows: S41. Acquisition of Microscopic Images: Paraffin sections of rice stems were imaged using an optical microscope. A 20× objective lens was selected to balance the field of view with the resolution of cell details, and a 24-bit RGB image with a resolution of 2048×2048 pixels was obtained. The actual size of a single pixel is about 0.23μm, ensuring that the image contains complete cell morphology and distribution characteristics.

[0053] S42. Binarization of Microscopic Images: S421. Image preprocessing: Perform 3×3 median filtering on the original image, and remove background noise by sorting the neighboring pixels and taking the median value to avoid noise interfering with cell contour extraction. S422. Grayscale Conversion: To address the characteristic of green cell walls after staining, the RGB image is converted to grayscale at an R:G:B ratio of 1:3:1 to enhance the contrast between the cell wall and the cell lumen. The conversion formula is: ,in, , , RGB images at pixels The grayscale values ​​of the red, green, and blue channels at that location. The converted grayscale value; S423, Block-based adaptive thresholding: Divide the grayscale image into 64×64 pixel sub-blocks, and calculate the optimal threshold for each sub-block using the Otsu algorithm. (Maximize the inter-class variance between the target and the background within the sub-block); adjust the grayscale values ​​in the sub-block. The pixel is marked as the target (cell wall, pixel value set to 255), grayscale value The pixels are marked as background (cell cavity, pixel value set to 0); finally, the complete binary image is obtained by stitching the sub-blocks together.

[0054] S43. Extraction of cell centroid coordinates: S431. Connected Component Labeling: The binary image is labeled using the 8-neighbor connected component analysis algorithm. All pixels in the image are traversed, and adjacent (top and bottom, left and right, diagonal) target pixels are classified into the same connected component. Each connected component corresponds to an independent cell. A noise filtering threshold is set to exclude connected components with an area of ​​less than 50 pixels (considered as background noise). S432. Centroid Calculation: For each valid connected component, calculate the centroid coordinates by weighted averaging of pixel coordinates. The formula is as follows: Where N is the total number of target pixels within the connected region. Let be the coordinates of the i-th target pixel within the connected region.

[0055] S44, Delaunay triangulation: S441. Virtual segmentation optimization: Preprocess the point set composed of all cell centroids, calculate the Euclidean distance between any two points, and if the distance is less than 5 pixels, retain the point that is closer to other point sets and delete redundant points to avoid generating excessively small triangles in subsequent subdivision. S442, Delaunay Triangulation Algorithm Implementation: The Bowyer-Watson algorithm is used to construct a Delaunay triangulation network. The core steps include: constructing a super triangle containing all centroids; sequentially inserting each centroid into the triangulation network to find the triangle containing that point; deleting the three edges of the triangle to form a new polygonal hole; connecting the inserted point to all vertices of the hole to generate a new triangle; checking whether all newly generated triangles satisfy the Delaunay condition (the circumcircle does not contain other centroids), and if not, making local adjustments; finally, a Delaunay triangulation network satisfying a minimum interior angle ≥ 20° is obtained. S443. Topology Information Extraction: Extract the vertex coordinates (corresponding centroid numbers) and the start and end coordinates of the edges of each triangle in the triangulation, and generate a list of triangles and an adjacency matrix of edges to provide a topological basis for subsequent Voronoi decomposition.

[0056] S45. Voronoi partitioning based on distance weights: S451, Distance Weight Calculation: For each centroid point Traverse its adjacent centroids in the Delaunay triangulation. Calculate the Euclidean distance between two points. and assign weights (The closer the distance, the greater the weight, and the stronger the representation of the degree of interaction between cells.) S452. Weighted Voronoi Diagram Generation: Using the centroid as the seed point, the influence region of each seed point is calculated based on distance weights, generating a weighted Voronoi polygon (each polygon corresponds to the outline of a cell). The polygon boundary is the weighted perpendicular bisector of adjacent seed points, satisfying the formula: Where P is any point on the boundary, , From point P to the centroid respectively , The Euclidean distance is used to control the polygon boundary precision to 1 pixel.

[0057] S5. Simulation Model Establishment and Verification: Based on cell morphology contours and topological information obtained through image processing, and engineering constants calculated from material parameters, a multi-scale finite element simulation model of rice stems is constructed. Tensile tests are then used to verify the model's accuracy, forming a closed-loop technology. Specific steps are as follows: S51. Construction of geometric model of rice stem tissue: S511. Cytoskeleton extraction and preservation: Extract the cytoskeleton curve from the cell contour image obtained in step S45 and save it as a PDF format. S512. Coordinate Data Conversion and Import: Open the PDF format cell skeleton curve in AutoCAD software, identify and extract the coordinate data of the cell wall contour skeleton curve, convert the coordinate data to DXF format through a format converter, and import it into ABAQUS / CAE software. S513. Creation of the three-dimensional shell model: In the sketch mode of ABAQUS / CAE software, import the coordinate data in DXF format to generate a two-dimensional contour consistent with the real cell morphology; extrude the two-dimensional contour along the axial direction (Z-axis) to create a three-dimensional shell geometry model. Set the extrusion length to 40mm (consistent with the effective length of the subsequent tensile test), and set the shell thickness according to the actual cell wall thickness extracted in step S21.

[0058] S52. Definition of Sectional Partitions and Material Properties: S521. Tissue Section Division: Based on the morphological distribution characteristics of the cortex and epidermal tissue of rice stem, the cross section of the three-dimensional shell model is divided into three independent regions: epidermal parenchyma (outermost layer, cells are tightly arranged), outer cortex thick-walled tissue (inner side of the epidermis, cell walls are thick), and intermediate cortex parenchyma (radial inner layer, cells are loosely arranged). S522, Assigning material properties to the cell wall layer: (1) Assignment of material parameters: Based on the nine engineering constants (three elastic moduli) of the cell wall in each region calculated in step S34. 3 shear moduli And 3 Poisson ratios ), and sequentially assign the corresponding three-dimensional shell models to the regions; (2) Creation of composite layers: Referring to the average thickness of each layer of the cell wall in rice stems, a laminate model was used to create composite layers in the ABAQUS attribute module; among them, the layup sequence of thick-walled cells (4 shells) is p-s1-s2-s3, thin-walled cells (1 shell) contain only the p layer, and the layup sequence of vascular cells (4 shells) is p-s1-s2-s3; different cell adjacency combinations correspond to specific layup: thick-walled-thick-walled combination (shell) Number 8) is s3-s2-s1-p-ml-p-s1-s2-s3, thick-walled-thin-walled combination (shell number 6) is s3-s2-s1-p-ml-p, thick-walled-catheter combination (shell number 9) is s3-s2-s1-p-m1-p-s1-s2-s3, thin-walled-thin-walled combination (shell number 3) is p-ml-p, thin-walled-catheter combination (shell number 6) is p-ml-p-s1-s2-s3; (3) Attribute assignment: The calculated cell wall engineering constants of each region are associated with the composite layer, and the corresponding material properties are assigned to the three-dimensional shell model according to the partition to ensure the mechanical properties of thick-walled and thin-walled structures are matched differently.

[0059] S523. Boundary Condition Setting and Mesh Generation: S5231, Boundary Condition Setting: Create reference points RP-1 (upper surface) and RP-2 (lower surface) on the upper and lower surfaces of the 3D shell model, respectively. Establish constraint relationships between the reference points and all nodes on the corresponding surfaces using the node coupling function; constrain all 6 degrees of freedom of RP-2. Constrain RP-1 on the remaining 5 degrees of freedom, excluding Z-axis translation. A fixed displacement of 10 μm was applied in the Z-axis direction of RP-1 to simulate the longitudinal tensile loading condition of rice stalks. S5232. Mesh Generation: The 3D shell model was meshed using 20-node quadratic hexahedral elements (C3D20), with a mesh size of 0.1. Local mesh refinement was performed in areas where the cell wall thickness changed abruptly (such as the boundary between layers S2 and S1). The final mesh had a total of 130,315 elements and 158,623 nodes, ensuring that the mesh quality met the simulation accuracy requirements (mesh distortion rate <0.1).

[0060] S53. Finite Element Simulation and Result Analysis: S531. Simulation Solution: Create a static general analysis step in the ABAQUS analysis module, set the analysis step time to 1 second, turn on the geometric nonlinearity switch, and submit the finite element model for solution; monitor the convergence of the model in real time during the solution process. If non-convergence occurs, adjust the mesh size or boundary condition parameters and solve again. S532. Obtaining the mechanical response curve: After the solution is completed, the tensile force-displacement curve of RP-1 and the reaction force curve of RP-2 are extracted in the ABAQUS post-processing module. Outliers are removed by data smoothing to obtain the mechanical response curve of the model in the linear elastic stage. S533. Calculation of elastic modulus: Based on Hooke's law, combined with tensile force (F), cross-sectional area of ​​the model (A), effective length (L=40mm) and elongation (ΔL=10μm), the longitudinal elastic modulus of the rice stem cortex and epidermal tissue is calculated using the formula E=(F×L) / (A×ΔL).

[0061] S54. Tensile Testing and Model Validation: S541. Tensile Test: Tensile tests were conducted on rice stem samples according to ASTM C1557-03. A Qixiang OX-W500 electronic universal testing machine (Shanghai) was used, with a load range of 1-10000 Newtons and a constant crosshead movement speed of 10 mm / min. Samples were fixed to PVC boards with wood glue (Wilo series, Yancheng Disheng Building Materials Co., Ltd.), with the glue applied only to the ends outside the effective tensile length. The effective tensile length was set to 30 mm. After sample fracture, the cross-sectional area was measured at three equidistant longitudinal positions using a Leica M165 FC stereomicroscope (40x magnification). The area was measured using Image Pro Plus (v.7.0) software, and the average value was taken as the effective cross-sectional area. S542. Result Comparison and Verification: The measured longitudinal elastic modulus obtained from the tensile test is compared with the elastic modulus calculated by the finite element simulation. The measured error is controlled within 10%, confirming that the simulation model constructed by the method of the present invention has high accuracy and strong reliability, and the modeling closed loop is completed.

[0062] S6. Model Application: The validated multi-scale mechanical simulation model of rice stems will be applied to the study of lodging resistance mechanism of rice, high-yield lodging-resistant breeding and cultivation regulation, and can also provide a reference for multi-scale mechanical modeling of dicotyledonous plants similar to rice.

[0063] The rice stem multi-scale mechanical simulation modeling device of this embodiment includes: a sample selection module, a micro-feature extraction module, a material parameter calculation module, an image processing module, a simulation modeling module, and a verification module; wherein, the sample selection module is used to select the second basal segment of the stem at maturity of the tested rice variety as a sample, and control the consistency of the planting and management conditions of the sample; the micro-feature extraction module is used to extract the thickness of the cell wall, the microfibril angle, and the material composition parameters of different types and layers of rice stem cells; the material parameter calculation module is used to perform two equivalent calculations, construct the flexibility and stiffness matrix, and correct the microfibril angle based on the micro-feature parameters to obtain the cell wall engineering constants; the image processing module is used to perform microscopic imaging, binarization, centroid extraction, triangulation, and Voronoi sectioning on the paraffin sections of rice stems to obtain the cell morphology contour; the simulation modeling module is used to construct a three-dimensional shell finite element model based on the cell morphology contour and engineering constants, set material properties, boundary conditions, and mesh generation, and perform finite element simulation; the verification module is used to obtain measured data through rice stem tensile tests, compare it with the simulation results, and verify the accuracy of the model.

[0064] This embodiment also provides an electronic device, which can be implemented by a computer device. The computer device includes a processor, a computer-readable storage medium, a memory, and a network interface connected via a system bus. The computer-readable storage medium stores an operating system, a database, and computer-readable instructions. The database may store control information sequences. When the computer-readable instructions are executed by the processor, the processor can implement a multi-scale mechanical simulation modeling method for rice stems. The processor of the computer device provides computational and control capabilities to support the operation of the entire computer device. The memory of the computer device may store computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor can execute the multi-scale mechanical simulation modeling method for rice stems of this application. The network interface of the computer device is used for communication with a terminal. Specifically, the structure of the computer device can refer to existing technologies.

[0065] 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 multi-scale mechanical simulation modeling method for rice stems, characterized in that, Includes the following steps: The second basal segment of the stem at maturity of the tested rice variety was selected as a sample. The sample was cultivated under uniform planting and management conditions to ensure the consistency of the experimental materials. Microscopic feature parameters of the sample are extracted, including the thickness of cell walls of different types and layers of rice stem cells, the angle of microfibrils, and the material composition. Based on the extracted microscopic feature parameters, material parameters are calculated based on the HP-TS equation. The equivalent calculation of hemicellulose-lignin matrix, the equivalent calculation of cellulose-matrix composite, the construction of flexibility matrix and initial stiffness matrix, and the correction of microfibril angle are completed in sequence to obtain the engineering constants of each cell wall layer. Image processing was performed on paraffin sections of rice stems, sequentially completing microscopic image acquisition, binarization, cell centroid coordinate extraction, Delaunay triangulation, and distance-weighted Voronoi triangulation to obtain accurate cell morphological contours and topological information. Based on the cell morphology contours and topological information obtained from image processing and the calculated cell wall engineering constants, a three-dimensional shell finite element model of rice stem tissue was constructed. Material properties and boundary conditions were defined and meshed, and finite element simulation was performed. Measured data were obtained through rice stem tensile tests, and compared with finite element simulation results to verify the model accuracy and complete the multi-scale mechanical simulation modeling of rice stems.

2. The multi-scale mechanical simulation modeling method for rice stems according to claim 1, characterized in that, The steps for extracting the cell wall thickness of different types and layers of rice stem cells include: Rice stem samples were placed in 0.2M phosphate buffer containing 4% glutaraldehyde + 2% paraformaldehyde and left to stand at 4°C for 24 hours. Rinse the sample several times with fresh phosphate buffer; At 25°C, the mixture was left to stand for a specified time in a 1% osmium tetroxide + 1% potassium ferric cyanide solution, and then rinsed several times with the above-mentioned phosphate buffer solution. It is dehydrated by a series of different gradients of ethanol, and then permeated with a series of different ratios of acetone-Spur resin gradient mixtures; At 60℃, the resin was embedded for 24 hours, and 70-100nm ultrathin sections were cut using a microtome. The cells were stained in 2% potassium permanganate for several minutes, and then imaged using a transmission electron microscope to extract cell wall thickness parameters.

3. The multi-scale mechanical simulation modeling method for rice stems according to claim 1, characterized in that, The steps for extracting the angles of microfibrils from different cell wall layers of rice stem cells include: Rice samples were placed in the test area of ​​an X-ray diffractometer, which was used with a Rigaku rotating anode X-ray tube as the X-ray source. Gaussian multi-peak deconvolution processing was performed on the diffraction pattern using a continuous scanning mode; The angular distribution of microfibers was determined by azimuth intensity scanning, and the grain size was calculated using the Scherrer equation, which is: ； Where D represents the grain size, K represents the Scherrer constant with a value of 0.9, λ represents the wavelength of the incident X-ray, B represents the full width at half maximum (FWHM) of the diffraction peak, and xc represents the Bragg angle.

4. The multi-scale mechanical simulation modeling method for rice stems according to claim 1, characterized in that, The steps for extracting cell wall materials of different types and layers from rice stem cells include: The sample was placed in the Raman electron microscope test area and a laser Raman-photoelectric imaging-fluorescence lifetime imaging system was used in conjunction with a confocal microscope. Set the excitation parameters; the laser diffraction restricts the spot to move line by line in the defined area to obtain the spectrum in the range of 400-2070 cm⁻¹; Root tissue sections were obtained by cryosectioning, and water was used as the embedding agent. The complete sections were placed on a quartz glass slide whose surface was hydrophilicized. Spectral curves were acquired using a confocal microscope. The self-fluorescence properties of the quartz slide were utilized to reduce background fluorescence signals, improve the signal-to-noise ratio of the spectral curves, and extract the composition parameters of the cell wall material.

5. The multi-scale mechanical simulation modeling method for rice stems according to claim 1, characterized in that, The steps for calculating material parameters include: First equivalent calculation: The middle layer and secondary wall matrix are composed of hemicellulose and lignin. They are equivalent to a single matrix material. The longitudinal elastic modulus and Poisson's ratio are calculated using the mixing ratio rule, and the shear modulus is calculated using the Halpin-Tsai equation. Second equivalent calculation: Using the mixed matrix obtained in the first equivalent calculation as the new matrix and cellulose as the reinforcing phase, the longitudinal elastic modulus and longitudinal Poisson's ratio are calculated using the mixing ratio rule, and the transverse elastic modulus and shear modulus are calculated using the Halpin-Tsai equation. Based on the assumption of transverse isotropy, let... Five core elastic constants were obtained; Construction of the Flexibility Matrix and Initial Stiffness Matrix: Based on the assumption of transverse isotropy, a flexibility matrix S is constructed, and the initial stiffness matrix is ​​obtained by inverting the flexibility matrix. A coupling effect correction term is introduced by utilizing the reciprocal relationship of Poisson's ratio; Microfibril angle correction: based on the angle between cellulose microfibrils in each layer of the secondary wall and the stem axis. A transformation matrix T is constructed, and the initial stiffness matrix is ​​transformed from the local coordinate system to the global coordinate system through coordinate transformation to obtain the actual three-dimensional stiffness matrix Q considering the orientation of microfibrils. Finally, the engineering constants of each cell wall layer are obtained.

6. The multi-scale mechanical simulation modeling method for rice stems according to claim 1, characterized in that, Image processing steps include: Image of paraffin sections of rice stems was obtained using an optical microscope; Median filtering is applied to the original image to remove background noise. The RGB image is converted to grayscale. The Otsu algorithm is used to perform block adaptive threshold segmentation on the sub-blocks. The images are then stitched together to obtain a complete binary image. A connected component analysis algorithm is used to label the binary graph, a noise filtering threshold is set, and the centroid coordinates of each effective connected component are calculated by weighted averaging of pixel coordinates. The centroid set is preprocessed, and the Bowyer-Watson algorithm is used to construct the Delaunay triangulation, ensuring that the minimum interior angle is ≥20°, and the topological information is extracted. Calculate the Euclidean distance between each centroid and its neighboring centroids. Assign weights Using the centroid as the seed point, a weighted Voronoi polygon is generated to obtain the cell morphology outline.

7. The multi-scale mechanical simulation modeling method for rice stems according to claim 6, characterized in that, The steps for establishing and validating a simulation model include: Based on the image of the cytoskeleton after image processing, a three-dimensional shell model is created, and the shell thickness is set according to the actual thickness of the cell wall. The cross-section of the three-dimensional shell model is divided into epidermal thin-walled tissue, outer cortex thick-walled tissue, and intermediate cortex thin-walled tissue. Material properties are assigned based on cell wall engineering constants, composite layers are created, and differentiated layup sequences are set according to cell type. Constrain all 6 degrees of freedom of the lower surface reference point RP-2, and constrain the other 5 degrees of freedom of the upper surface reference point RP-1 except for the Z-axis translation. Apply a fixed displacement of 10 μm in the Z-axis direction of RP-1. Use 20-node quadratic hexahedral elements to generate the mesh, with the mesh size set to 0.1, and locally refine the mesh in the region of abrupt change in cell wall thickness. Create a static general analysis step, submit the finite element model for solution, extract the tensile force-displacement curve and calculate the longitudinal elastic modulus; conduct tensile tests using an electronic universal testing machine to measure the effective cross-sectional area, compare the measured results with the simulation results, and confirm the model's reliability if the error is controlled within 10%.

8. A modeling apparatus for applying the multi-scale mechanical simulation modeling method for rice stems according to any one of claims 1-7, characterized in that, include: Sample selection module: used to select the second basal segment of the stem at maturity of the tested rice variety as a sample, and to control the consistency of the planting and management conditions of the sample; Microscopic feature extraction module: used to extract the thickness of cell walls of different types and layers of rice stem cells, microfibril angles, and material composition parameters; Material parameter calculation module: used to perform two equivalent calculations, construct flexibility and stiffness matrices and correct microfibril angles based on microscopic characteristic parameters to obtain cell wall engineering constants; Image processing module: used for microscopic imaging, binarization, centroid extraction, triangulation and Voronoi sectioning of rice stem paraffin sections to obtain cell morphology contours; Simulation modeling module: used to construct a three-dimensional shell finite element model based on cell morphology contours and engineering constants, set material properties, boundary conditions and mesh generation, and perform finite element simulation; Verification module: Used to obtain measured data through rice stem tensile tests, compare it with simulation results, and verify the accuracy of the model.

9. An electronic device, characterized in that, It includes a central processing unit and a memory, wherein the central processing unit is used to call and run a computer program stored in the memory to perform the steps of the multi-scale mechanical simulation modeling method for rice stems according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores, in the form of computer-readable instructions, a computer program implementing the multi-scale mechanical simulation modeling method for rice stems as described in any one of claims 1-7. When the computer program is called and executed by a computer, it performs the steps included in the corresponding method.

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