Analysis method, medium and system for distinguishing morphological differences of male and female skull of three kinds of takifugu based on landmark point method

Abstract

The invention relates to the field of fish skull morphological difference analysis methods, and particularly discloses an analysis method for distinguishing morphological differences of three kinds of takifugu male and female skull based on a landmark point method.The method comprises the following steps that 1, coordinate values of feature points on the takifugu skull are extracted through software; 2, performing relative distortion principal component analysis on the obtained data file to obtain characteristic values, contribution rates and relative distortion scores of different principal components; step 3, finally analyzing by using a thin plate strip sample, and visualizing the morphological variation of the skull through a grid deformation graph; according to the method, the difference is researched and analyzed from the perspective of geometric morphology, the morphological difference of the skull of takifugu with different genders is distinguished, a scientific basis is provided for distinguishing the difference of male and female skull, a reference is provided for research of fish skull morphological systematics, a research thought is provided for automatic fish classification in the future, and the method has important theoretical and scientific research significance.

Description

Technical Field

[0001] The invention relates to the technical field of fish skull morphology difference analysis methods, and in particular to a method for distinguishing three types of male and female porcupine fish skull morphology difference analysis based on a landmark point method, and also to a system for distinguishing three types of male and female porcupine fish skull morphology difference analysis based on a landmark point method. Background Art

[0002] The morphological difference between male and female fish is an important aspect of fish morphological research. The most direct way to identify the sex of fish is to start with the primary sexual characteristics, that is, the fundamental difference in reproductive organs. The secondary sexual characteristics of fish are the characteristics that can be used to identify the sex of fish in addition to the primary sexual characteristics. The sex of fish can be determined by the secondary sexual characteristics of fish, such as the nuptial color that appears on the body when the breeding season arrives. Some scholars have also studied Nile tilapia and found that under the same breeding conditions, the growth rate of males is higher than that of females, and the size of males is larger than that of females; in addition to body size, the sex of fish can also be determined by the shape of the fins and the condition of the fin spines. For example, Yin Xiangfu et al. found and studied the sex differences of two species of perciformes in my country. These are simple and reliable methods. Generally speaking, when we distinguish the morphological differences between different species, we can see their differences with the naked eye, or simply measure a few prominent traits and use statistical methods to distinguish them. However, if different sexes of the same species are studied, the morphological differences between male and female fish are very small, and it is difficult to judge the sex by naked eyes. It is necessary to measure multiple traits to extract morphological variables, and achieve the purpose of identification through principal component analysis, discriminant function, etc. There are two main types of research methods in morphological analysis: one is traditional morphological analysis method, and the other is geometric morphometric method. The former emphasizes the linear measurement of structure, and the latter uses the two-dimensional image of the sample to convert the morphological structure into data information and analyze it with special software. In Zhang Lina's study on the sex of sea eels in the Yangtze River estuary, the traditional morphometric method was used to identify the sexes, and the results showed that the accuracy of sex discrimination was 80%. In the comparison of the morphological characteristics of male and female redfin pufferfish by Yue Liang et al., the results of the traditional morphometric method showed that the discrimination accuracy of the two groups of male and female samples was 81.9% and 84.2% respectively; in the analysis of the morphological differences between male and female goldfish by Wu Bo et al., the accuracy of male and female discrimination was 85.96%. Compared with the morphological feature description, the digital analysis process not only shows the differences in sample morphology concisely and clearly, but also includes the feature description, making the morphological difference information more complete.

[0003] The landmark point method has advantages over other methods. It is easy to operate, covers more morphological information, and can also reflect subtle changes in a certain structure on the sample. Therefore, the landmark point method is used by more and more researchers to analyze the morphological differences between samples. After selecting points on the sample, it is converted into data information using special software. At the same time, principal component analysis, eigenvalue, thin plate sample analysis, etc. are introduced into the analysis to make the description of morphological information more comprehensive. The researchers used the landmark point method to analyze the variation between groups of tang fish. After establishing landmark points on the two-dimensional image of tang fish, the analysis results showed that the recognition accuracy of different groups of tang fish was 73%~100%. Some scholars also used the landmark point method to study the effect of exercise on the morphological parameters of young fish. Even if the morphological differences are quite weak, the landmark point method can still achieve good results. The landmark point method is more used in the identification of fish otoliths in ichthyology research. Hou Gang's identification study of sagittal otoliths of four species of golden thread fish has a discrimination accuracy of 89.8%~91.3%; Ou Liguo's study on the morphological classification of sagittal otoliths of four species of croaker fish has an average discrimination accuracy of 100%. Prove the reliability of the landmark method in morphological difference analysis.

[0004] The morphological structure of the skull is stable, which plays a very important role in the identification of organisms within and between species, and can reflect the living environment of organisms to a certain extent. Li Jingbin studied the geographical variation of skull morphology of three species of horseshoe bats and analyzed the intraspecific geographical variation of horseshoe bats, achieving good results. Due to the simple operation and high accuracy of geometric morphological measurement, it has been widely used in research in related fields, and is increasingly favored by researchers, with considerable application prospects. Among them, the landmark method is the most widely used.

[0005] The dense-spotted pufferfish, the big-spotted pufferfish, and the six-spotted pufferfish are all species of the family Porcupinefish. The research on pufferfish is not comprehensive yet, with the six-spotted pufferfish being the most extensive. Some scholars have studied the breeding technology of the six-spotted pufferfish, the effect of open-mouthed bait on the survival rate of six-spotted pufferfish fry, and the protein extraction technology of the dense-spotted pufferfish, but there is no relevant research on the morphological differences of the pufferfish skull in the industry. Summary of the invention

[0006] In view of this, the present invention provides a method for analyzing the morphological differences of skulls of male and female porcupinefish based on a landmark method. The male and female skulls of the three porcupinefish are taken as research objects, and the geometric morphological analysis method and software are used to compare and analyze the morphological characteristics of the skulls of male and female porcupinefish, clarify the differences in morphological characteristics between the skulls of male and female porcupinefish of the same species, study and analyze the differences from the perspective of geometric morphology, identify the morphological differences of skulls of porcupinefish of different sexes, provide a scientific basis for distinguishing the differences between male and female skulls, provide a reference for the study of fish skull morphological systematics, and provide a research idea for future automatic classification of fish, which has important theoretical and scientific research significance.

[0007] In order to achieve the above-mentioned purpose, the basic scheme of the present invention provides a method for analyzing the morphological differences of the skulls of three male and female porcupine pufferfish based on the landmark point method, step 1, using software to extract the coordinate values ​​of the characteristic points on the skull of the porcupine pufferfish; using Tpsdig2 software to establish landmark points on the two-dimensional image of the skull, including the following three types: type I landmark points are the intersections of bones or sutures; type II landmark points are convex or concave points on the skull; type III landmark points are the widest points on the left and right sides of the skull; Step 2: Perform relative distortion principal component analysis on the obtained data file to obtain the eigenvalues ​​and contribution rates of different principal components and relative distortion scores; Step 3. Finally, thin-plate strip analysis was used to visualize the morphological variation of the skull through the grid deformation map, and the discriminant equation was established using the relative distortion score to distinguish the morphological differences between the skulls of male and female porcupine pufferfish, the dense-spotted pufferfish, and the six-spotted pufferfish, and the results of the discriminant analysis were obtained.

[0008] In a possible design, in step 1, the two-dimensional skull image is specifically obtained by placing the obtained complete skull sample on a black background board and taking a photo to obtain a clear and complete two-dimensional skull image, and then using Tpsdig2 software to establish coordinate points on the two-dimensional skull image, and using Tpssmall software to verify the validity of the obtained landmark points.

[0009] In a possible design, in step 2, TpsRelw is used to process and analyze the landmark points of each sample to obtain the average shape diagram of the sample, perform relative distortion principal component analysis, and save the analysis report and relative distortion score generated by the software.

[0010] In a possible design, step 3 is to use TpsRegr software to perform thin plate sample analysis, visualize the deformation, save the mesh deformation diagram of the male and female skulls of the three porcupine pufferfish, and use the relative distortion score data obtained by Tpsrelw; the relative distortion score is processed and imported into SPSS for stepwise discriminant analysis and interactive verification. The Bayes method is used for discrimination, and SPSS23.0 is used for statistical analysis.

[0011] In a possible design, in step 3, the landmark point file is processed using Tpsrelw to obtain the average shape and the overlapping landmark points; Tpsregr is used to perform distortion analysis, regression analysis and permutation test, the grid deformation map generated by the software is saved, and SPSS is used for stepwise discriminant analysis to screen out the relative distortion score variables with large principal component contribution rates, establish discriminant equations for these variables, and obtain the results of the discriminant analysis.

[0012] In a possible design, in step 3, the average shape of the porcupinefish skull morphology is obtained using tpsRelw software, and relative distortion is performed, and an analysis report and a relative distortion score are obtained at the same time, and relative distortion principal component analysis is performed and the relative distortion score is used to perform discriminant analysis on the three types of porcupinefish skull morphologies. The discriminant equation is specifically: Six-spot pufferfish: Y1=353.557RW 1 +174.606RW 2 -86.135RW 3 -231.256RW 4 -0.652RW 6 +47.768RW 7 +156.161RW 8 +33.759RW 14 -13.763 Big spotted pufferfish: Y2=102.017RW 1 -254.039RW 2 +620.319RW 3 -90.799RW 4 -140.701RW 6 +159.768RW 7 -229.571RW 8 -260.498RW 14 -11.452 Porcupine pufferfish: Y3=-276.457RW 1 -88.926RW 2 -243.396RW 3 +176.822RW 4 +68.439RW 6 -88.637RW 7 +3.107RW 8 +125.404RW 14 -8.070 Among them, the relative distortion scores are sorted from high to low, RW 1 For the No. 1 ranking, RW 2 RW ranked No. 2 3 For the No. 3, RW 4 For the No. 4 ranking, RW 6 For the No. 6, RW 7 For the No. 7, RW 8 For the No. 8, RW 14 Ranked 14th; The determination method is to substitute the data of the fish to be determined into formulas Y1, Y2, and Y3. The pufferfish species corresponding to the equation with the largest value is the species of the fish to be determined.

[0013] In one possible design, in step 3, If it is determined to be a six-spot pufferfish, the sex discrimination function is obtained according to the characteristic index: female: Y4=-3202.345RW 1 +4316.864RW 2 +1009.759RW 3 -2045.467RW 5 -889.534RW 6 -3164.462RW 7 -6827.687RW 8 +2343.094RW 10 +5792.814RW 12 +7200.641RW 14 +4881.335RW 16 -1858.721RW 18 +3961.720RW 19 +7748.606RW 20 +14602.211RW 21 -44.681 male: Y5=8539.586RW 1 -11511.638RW 2 -2692.691RW 3 +5454.579RW 5 +2372.089RW 6 +8438.566RW 7 +18207.165RW 8 -6248.250RW 10 -15447.504RW 12 -19201.710RW 14 -13016.893RW 16 +4956.590RW 18 -10564.587RW 19 -20662.949RW 20 -38939.230RW 21 -313.492 Among them, the relative distortion scores are sorted from high to low, RW 1 For the No. 1 ranking, RW2 RW ranked No. 2 3 For the No. 3, RW 4 For the No. 4 ranking, RW 5 For the No. 5, RW 6 For the No. 6, RW 7 For the No. 7, RW 8 For the No. 8, RW 10 For the No. 10, RW 12 For the 12th place, RW 14 RW ranked 14th 16 For the No. 16, RW 18 For the 18th place, RW 19 For the No. 19, RW 20 For the No. 20, RW 21 It ranks 21st; the determination method is to substitute the data of the fish to be determined as the six-spot pufferfish into formulas Y4 and Y5, and the sex of the six-spot pufferfish corresponding to the equation with the largest value is the sex of the fish to be determined; Or if it has been determined to be a big spotted pufferfish, the sex discrimination function obtained based on the characteristic index is: female: Y4=48.224RW 1 -93.587RW 6 -157.970RW 13 +391.177RW 17 -1.430 male: Y5=-53.582RW 1 +103.985RW 6 +175.522RW 13 -434.642RW 17 -1.602 Among them, the relative distortion scores are sorted from high to low, RW 1 For the No. 1 ranking, RW 6 Ranked 6th, RW1 3 is ranked 13th, and RW17 is ranked 17th. The determination method is to substitute the data of the fish to be determined as the big spotted pufferfish into formulas Y4 and Y5. The sex of the big spotted pufferfish corresponding to the equation with the largest value is the sex of the fish to be determined. Or if it has been determined to be a porcupine pufferfish, the sex discrimination function obtained based on the characteristic index is: female: Y4=142.158RW 8 -104.372RW 9 -247.819RW 11 +157.611RW 12+190.725RW 16 -259.171RW 17 +441.071RW 23 -683.944RW 27 -518.182RW 28 -2.143 male: Y5=-162.467RW 8 +119.282RW 9 +283.221RW 11 -180.126RW 12 -217.971RW 16 +296.195RW 17 -504.081RW 23 +781.650RW 27 +592.209RW 28 -2.587 Among them, the relative distortion scores are sorted from high to low, RW 8 For the No. 8, RW 9 For the 9th place, RW 11 For the 11th place, RW 12 For the 12th place, RW 16 For the No. 16, RW 17 For the No. 17, RW 23 RW ranked 23rd 27 For the No. 27, RW 28 It ranks 28th; the determination method is to substitute the data of the fish to be determined as the dense-spotted pufferfish into formulas Y4 and Y5, and the sex of the dense-spotted pufferfish corresponding to the equation with the largest value is the sex of the fish to be determined.

[0014] The present invention provides a system, comprising the aforementioned device for analyzing the skull morphology differences of three types of porcupine pufferfish based on the landmark point method.

[0015] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to implement the aforementioned method for analyzing the differences in skull morphology of three types of porcupine pufferfish based on the landmark point method.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. The landmark method was used to identify the morphological differences of the three porcupine pufferfishes, with a success rate of 100%, proving the effectiveness of the landmark method. The dense-spotted porcupine pufferfish, the large-spotted porcupine pufferfish, and the six-spotted porcupine pufferfish can be effectively classified. The grid deformation diagram shows that the frontal bone of the dense-spotted porcupine pufferfish is more rounded, and the junction between the frontal bone and the external ethmoid bone is smooth without protruding parts; the frontal bone of the large-spotted porcupine pufferfish is slightly concave, and the junction between the frontal bone and the external ethmoid bone is very round; the frontal bone of the six-spotted porcupine pufferfish is slightly concave, and the junction between the frontal bone and the external ethmoid bone is more pointed than that of the other two porcupine pufferfishes.

[0017] 2. Use the landmark method to identify the morphological differences between the skulls of male and female porcupine pufferfish. Through principal component analysis and deformation visualization, the female skull of the dense-spotted pufferfish is wider and larger; the snout of the large-spotted pufferfish and the six-spotted pufferfish is more prominent in the female than in the male. Since the gender differences of pufferfish are not significant, the differences reflected in the skull morphology are also very small, and it is difficult to distinguish the male and female skulls with the naked eye.

[0018] 3. The frontal bone contour of the porcupine pufferfish. Because there are no points on it that meet the landmark point selection principle, sliding landmark points are used to simulate the changes in the frontal bone contour. The results show that sliding landmark points can better explain the morphological changes in the frontal bone contour of the porcupine pufferfish. In comparison with the three porcupine pufferfish, the frontal bone contour of the dense-spotted pufferfish is more rounded and convex, while the frontal bone contours of the large-spotted pufferfish and the six-spotted pufferfish are slightly concave.

[0019] 4. The landmark method is effective for both inter-species identification and gender distinction of the same species. Combined with SPSS statistical analysis, it can fully present the morphological differences of organisms. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 33 landmarks of the skull in the embodiment of the present application are shown, among which a is the dense-spotted pufferfish, b is the big-spotted pufferfish, and c is the six-spotted pufferfish; Figure 2 The scatter diagrams of the first and second main components in the embodiment of the present application are shown; Figure 3 Schematic diagram of the average shape of the skull in the embodiment of the present application is shown, wherein a is the dense-spotted pufferfish, b is the big-spotted pufferfish, c is the six-spotted pufferfish, and d is the overlapping landmark points of the skulls of the three pufferfish; Figure 4 Schematic diagrams of mesh deformation of three types of porcupinefish skulls in the embodiments of the present application are shown, wherein a is a dense-spotted porcupinefish, b is a large-spotted porcupinefish, c is a six-spotted porcupinefish, and d is an average mesh shape; Figure 5 Schematic diagrams of sliding landmarks on the skulls of three porcupine pufferfish in the embodiments of the present application are shown, wherein a is a dense-spotted porcupine pufferfish, b is a large-spotted porcupine pufferfish, and c is a six-spotted porcupine pufferfish; Figure 6 The figure shows the average shape of the skull of the dense-spotted pufferfish in the embodiment of the present application, wherein a is the average shape of male and female, b is female, and c is male; Figure 7 A schematic diagram of superimposed landmarks of Porcupine pufferfish in an embodiment of the present application is shown; Figure 8 The diagram shows the deformation diagram and variation visualization diagram of the grid of the dense-spotted pufferfish in the embodiment of the present application, where a is female, b is male, and c is the average shape of the grid; Fig. 9 The schematic diagram of the average shape of the skull of the giant pufferfish in the embodiment of the present application is shown, wherein a is the average shape of male and female, b is female, and c is male; Fig.10 A schematic diagram of superimposed landmarks of a giant pufferfish in an embodiment of the present application is shown; Fig.11 The diagram shows the deformation diagram and variation visualization diagram of the grid of the great spotted pufferfish in the embodiment of the present application, where a is female, b is male, and c is the average shape of the grid; Fig.12 The figure shows the average shape of the skull of the six-spotted pufferfish in the embodiment of the present application, wherein a is the average shape of male and female, b is female, and c is male; Fig.13 A schematic diagram of superimposed landmarks of a six-spotted pufferfish in an embodiment of the present application is shown; Fig.14 The diagram shows the deformation diagram and variation visualization diagram of the grid of the six-spotted pufferfish in the embodiment of the present application, where a is female, b is male, and c is the average shape of the grid; Fig.15 The scatter plots of the first and second main components of the skull morphology of different sexes of Porcupine pufferfish in the examples of the present application are shown. DETAILED DESCRIPTION

[0022] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention and are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, ordinary technicians in the field should be able to understand other possible implementations and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0023] The landmark point method is to select some easily identifiable points on the structure of the organism, reflect the morphological variation of the sample structure by studying the position difference of the landmark points, and convert this position difference into a mathematical function. The landmark points are generally selected as the sharp protrusions of the structural organization or the depressions on the structure. After obtaining the electronic image, the landmark points are extracted using professional software, converted into data containing XY coordinate axes, and the data is processed. There are generally three types of landmark point selection methods according to Bookstein: Type I landmarks mainly refer to the intersections of some tissues, organs or bone sutures, such as the intersections of fish fins and their body parts; Type II landmarks are protruding or concave points in the structure, such as the protrusions of fish bones, notches on otoliths, or points with high recognition in the structure; Type III landmark points are the extreme points of the structure, and the longest point, widest point, etc. are selected in the structure. The first two types of landmark points are often selected during the research process because they are easy to find accurately from the morphological characteristics of each sample and have strong repeatability. Standards to be followed when selecting landmark points: (1) The selected landmarks have homology in biological structure; (2) The relative position in the structure cannot be moved; (3) It can reflect the whole organism to the greatest extent possible; (4) The sample can be repeatedly selected; (5) All points must be in the same plane.

[0024] In this example, 30 skulls of Porcupine pufferfish were collected, including 16 females and 14 males. 19 skulls of Porcupine pufferfish were collected, including 10 females and 9 males. 22 skulls of Porcupine pufferfish were collected, including 16 females and 6 males.

[0025] A method for analyzing the skull morphology differences of three species of porcupine pufferfish based on a landmark point method comprises the following steps: Place the complete skull sample on a black background and take a photo to obtain a clear and complete two-dimensional image of the skull. Use the Tpsdig2 software to establish coordinate points on the two-dimensional image of the skull. Use the Tpssmall software to verify the validity of the landmark points. Use TpsRelw to process and analyze the landmark points of each sample to obtain the average shape diagram of the sample, perform relative distortion principal component analysis, and save the analysis report and relative distortion score generated by the software. Use TpsRegr software to perform thin plate regulation sample analysis, visualize the deformation, and save the grid deformation diagram of the male and female skulls of the three types of pufferfish. The relative distortion score data obtained by Tpsrelw was imported into SPSS after processing for stepwise discriminant analysis and interactive verification. The Bayes method was used for discrimination, and SPSS23.0 was used for statistical analysis. It specifically includes the following parts: 1.1 Selection of landmark points Landmark points were established using Tpsdig2 software, and a total of 33 landmark points were extracted. Type I landmark points are: 1, 2, 3, 7, 9, 12, 22, 25, 27, 31, 32, 33, which are the intersections of bones or sutures; Type II landmark points are: 4, 5, 6, 8, 10, 13, 14, 15, 16, 17, 18, 19, 20, 21, 24, 26, 28, 29, 30, which are convex or concave points on the skull; Type III landmark points are: 11, 23, which are the widest points on the left and right sides of the skull. The obtained data file was saved for the next step of analysis. Figure 1 As shown; 1.2 Analysis of skull morphology differences among three species of female porcupinefish 1.2.1 Least Squares Regression Analysis The least squares regression analysis was performed in Tpssmall. The results showed that the regression coefficient of the Pugh distance and the tangent space distance was 0.999646, which was close to 1, indicating that the selected landmark points were effective and could be used for the next statistical analysis.

[0026] 1.2.2 Principal Component Analysis The data file obtained by Tpsdig was imported into Tpsrelw, and the required results were obtained by software processing. A total of 62 principal components were extracted by relative distortion principal component analysis, with contribution rates of 40.04% for the first principal component and 13.13% for the second principal component. The cumulative contribution rate of the first two principal component analyses of the three pufferfish was 53.18% (see Table 1), which exceeded 50%, indicating that the selection of landmark points was reasonable and effective. The scatter plot drawn based on the first and second principal components is shown in Figure 1. Figure 2 As shown, the three types of pufferfish can each form a relatively concentrated area, indicating that the skull morphology of dense-spotted pufferfish, big-spotted pufferfish, and six-spotted pufferfish is quite different.

[0027] Table 1 Eigenvalues ​​and contribution rates of the first 10 principal components

[0028] 1.2.3 Visualization Analysis See Figure 3 Use Tpsrelw to process the landmark point file to obtain the average shape and overlapping landmark points; use Tpsregr to perform distortion analysis, regression analysis and permutation test, and save the grid deformation map generated by the software. Figure 4As shown in the figure. By comparing the generated average shape and mesh deformation map, it is found that the differences between the three pufferfish are mainly reflected in the degree of concavity of the frontal bone and the structure of the external ethmoid bone. The frontal bone of the dense-spotted pufferfish is more rounded, and the junction between the frontal bone and the external ethmoid bone is smooth without protrusions; the frontal bone of the large-spotted pufferfish is slightly concave, and the junction between the frontal bone and the external ethmoid bone is very rounded; the frontal bone of the six-spotted pufferfish is slightly concave, and the junction between the frontal bone and the external ethmoid bone is more pointed than that of the other two pufferfish.

[0029] 1.2.4 Discriminant Analysis SPSS was used to perform stepwise discriminant analysis to screen out the relatively distorted score variables with large principal component contribution rates. Discriminant equations were established for these variables to obtain the results of the discriminant analysis (see Table 2).

[0030] The discriminant equation is specifically: Six-spot pufferfish: Y1=353.557RW 1 +174.606RW 2 -86.135RW 3 -231.256RW 4 -0.652RW 6 +47.768RW 7 +156.161RW 8 +33.759RW 14 -13.763 Big spotted pufferfish: Y2=102.017RW 1 -254.039RW 2 +620.319RW 3 -90.799RW 4 -140.701RW 6 +159.768RW 7 -229.571RW 8 -260.498RW 14 -11.452 Porcupine pufferfish: Y3=-276.457RW 1 -88.926RW 2 -243.396RW 3 +176.822RW 4 +68.439RW 6 -88.637RW 7 +3.107RW 8 +125.404RW 14 -8.070 Among them, the relative distortion scores are sorted from high to low, RW 1 For the No. 1 ranking, RW2 RW ranked No. 2 3 For the No. 3, RW 4 For the No. 4 ranking, RW 6 For the No. 6, RW 7 For the No. 7, RW 8 For the No. 8, RW 14 Ranked 14th; The determination method is to substitute the data of the fish to be determined into formulas Y1, Y2, and Y3. The pufferfish species corresponding to the equation with the largest value is the species of the fish to be determined.

[0031] The results showed that the accuracy of the identification of the skull samples of Porcupine pufferfish, Porcupine pufferfish and Porcupine pufferfish was 93.3%, 100% and 95.5% respectively. Therefore, the geometric morphological measurement based on landmark points can effectively distinguish the skull morphological differences of Porcupine pufferfish, Porcupine pufferfish and Porcupine pufferfish.

[0032] Table 2 Discrimination results

[0034]

[0035] In order to quantify the differences between porcupinefish groups, canonical variable analysis of external morphology was performed on different groups, and Mahalanobis distance and Protzsprung distance were calculated (see Table 2-1 and Table 2-2). The first two canonical variables explained 100% of the variation, of which the first canonical variable (CV1) explained 57.842% and the second canonical variable (CV2) explained 42.158%. The difference test results based on Mahalanobis distance showed (Table 2-1) that the differences between the skulls of the three porcupinefish species were statistically significant (P<0.001), among which the Mahalanobis distance of the skulls of the big spot porcupinefish and the dense spot porcupinefish was the largest (28.8336), and the Mahalanobis distance of the skulls of the six-spot porcupinefish and the big spot porcupinefish was the smallest (26.5026). The distance between the average skull morphologies of the three porcupinefish species was expressed by the Prokström distance. The differences in the Prokström distance between the skull morphologies of the three porcupinefish species were statistically significant (P<0.001), among which the distance between the six-spot porcupinefish and the big-spot porcupinefish was the shortest.

[0036] Table 2-1 Comparison of Mahalanobis distance of skull morphology of three porcupinefish

[0037] 1.2.5 Sliding landmark points The concept of semilandmarks was first proposed by Bookstein (1991). The function of semi-landmarks is to use a series of punctuation points to describe the outline and shape information of the morphological structure. Then the shape of the organism is analyzed by the Prusty superimposition method. The landmark points of the frontal bone contours of three porcupine fish were extracted using Tpsdig software, and the frontal bone contours were supplemented with sliding landmark points.

[0038] The selection of sliding landmarks for three types of porcupinefish is as follows: Figure 5 and Fig.10 As shown, landmarks 1 to 5 of the dense-spotted pufferfish show that the edge of the frontal bone is a convex arc; landmarks 16 to 20 show that the intersection of the frontal bone and the external ethmoid bone is not obviously concave, and the frontal bone is relatively smooth. Landmarks 1 to 5 of the large-spotted pufferfish show that the edge of the frontal bone is relatively rounded, and from landmarks 6 to 12, there is a slight concave on the outline of its frontal bone; landmarks 16 to 20 show that the intersection of the frontal bone and the external ethmoid bone is obviously concave. Landmarks 1 to 5 of the six-spotted pufferfish show that the edge of the frontal bone is sharp; from landmarks 9 to 15, the outline of the frontal bone is smooth and slightly protrudes outward, and landmarks 18 to 20 show that the intersection of the frontal bone and the external ethmoid bone is obviously concave, and the degree of concave is the largest.

[0039] 1.3 Porcupine pufferfish 1.3.1 Least Squares Regression Analysis The least squares regression analysis showed that the regression coefficient of the Pusto distance and the tangent space distance was 0.999646, close to 1, indicating that the selected landmark points were effective and could be used for the next statistical analysis.

[0040] The average shape of the male and female porcupine pufferfish calculated by tpsRelw software based on the coordinate data of the landmark points, as well as the superimposition effect of all landmark points are shown in the figure below. Figure 1 and Figure 2 As shown. Through relative distortion analysis, the contribution rate of each landmark point in reflecting the difference in skull morphology is clarified. The contribution rate results of 33 landmark points in relative distortion principal component analysis are shown in Table 3. Among them, the contribution rate of landmark point 19 is the largest (0.15694%), followed by landmark points 13 and 15.

[0041] Table 3 Relative distortion contribution rate of each landmark point

[0042] 1.3.3 Visual analysis of morphological differences like Figure 8As shown in the figure, the landmark points were visualized and analyzed using TpsRegr software. Compared with the average shape of the grid, the landmark points 1, 9, 14, 20, 25, and 33 of the male and female P. fasciatus have larger deformations. The landmark points 7, 27, 12, and 22 of the female have expanded; the landmark points 1 and 33 of the male have sunk. The skull of the female is wider and larger.

[0043] 1.3.4 Principal Component Analysis The data file obtained by Tpsdig was imported into MorphoJ, and the required results were obtained after software processing. Relative distortion principal component analysis extracted a total of 26 principal components, with contribution rates: the first principal component was 20.17%, the second principal component was 16.40%, the third principal component was 8.28%, and the fourth principal component was 7.12%. The cumulative contribution rate of the first four principal components reached 51.93% (Table 3-1), which can better explain the morphological variation. The scatter plot of PC1 and PC2 is shown in Fig.15 There is a small amount of overlap between the scattered points of male and female individuals, forming two relatively concentrated areas, indicating that the main component scatter plot has a good distinguishing effect.

[0044] Table 3-1 Eigenvalues ​​and contribution rates of the first 10 principal components

[0045] 1.3.5 Discriminant Analysis SPSS was used to conduct stepwise discriminant analysis. The results showed that when conducting stepwise discriminant analysis, RW 8 , RW 9 , RW 11 , RW 12 , RW 16 , RW 17 , RW 23 , RW 27 , RW 28 A total of 9 variables were included in the discriminant function, and 30 porcupine pufferfish were sexed. The results showed that the accuracy of female discrimination was 100%, and the accuracy of male discrimination was 92.9%; the cross-validation results showed that 2 of the 16 females were misjudged, with an accuracy of 93.8%; 2 of the 14 males were misjudged, with an accuracy of 85.7% (Table 3-2). Although the accuracy of cross-validation was lower than that of stepwise discriminant analysis, both remained at a high level, indicating that the model had a good prediction effect and good generalization performance.

[0046] The standard discriminant function formula obtained according to the characteristic index is: female: Y4=142.158RW 8 -104.372RW 9-247.819RW 11 +157.611RW 12 +190.725RW 16 -259.171RW 17 +441.071RW 23 -683.944RW 27 -518.182RW 28 -2.143 male: Y5=-162.467RW 8 +119.282RW 9 +283.221RW 11 -180.126RW 12 -217.971RW 16 +296.195RW 17 -504.081RW 23 +781.650RW 27 +592.209RW 28 -2.587 The determination method is as follows: after substituting the data of the fish to be determined as the dense-spotted pufferfish into formulas Y4 and Y5, the sex of the dense-spotted pufferfish corresponding to the equation with the largest value is the sex of the fish to be determined.

[0047] Table 3-2 Results of discrimination analysis of male and female porcupine pufferfish

[0048] 1.4 Porcupine pufferfish 1.4.1 Least Squares Regression Analysis The least squares regression analysis showed that the regression coefficient of the Pugh distance and the tangent space distance was 0.999668, close to 1, indicating that the selected landmarks are effective and can be used for the next statistical analysis. The average shape of the male and female porcupinefish calculated by the tpsRelw software based on the landmark coordinate data, as well as the superimposition effect of all landmarks are shown in Figure 2. Figure 1 and Figure 2 As shown. Through relative distortion analysis, the contribution rate of each landmark point in reflecting the difference in skull morphology is clarified. The contribution rate results of 33 landmark points in relative distortion principal component analysis are shown in Table 4-1. Among them, the contribution rate of landmark point 19 is the largest (0.12576%), followed by landmark points 15 and 22.

[0049] Table 4-1 Relative distortion contribution rate of each landmark point

[0050] 1.4.2 Principal Component Analysis like Fig. 9 As shown in the figure, the data file obtained by Tpsdig was imported into MorphoJ, and the Prsdig overlay was performed. The required results were obtained after the software processing. Relative distortion principal component analysis extracted a total of 18 principal components, with contribution rates: the first principal component was 24.49%, the second principal component was 17.95%, and the third principal component was 14.83%. The cumulative contribution rate of the first three principal components reached 57.26 (Table 4), which can better explain the morphological variation. All landmark points are superimposed as shown in the figure. Fig.10 As shown. Fig.11 As shown in the figure, there is a small amount of overlap between the scattered points of male and female individuals, forming two relatively concentrated areas, indicating that the main component scatter plot has a good discrimination effect.

[0051] Table 4 Eigenvalues ​​and contribution rates of the first 10 principal components

[0052] 1.4.3 Visual analysis of morphological differences Use TpsRegr software to visualize and analyze landmark points, such as Figure 1 , Figure 4 , Fig.11 As shown in the figure. Compared with the average shape of the grid, the deformation of the landmarks of male and female porcupine pufferfish at points 9, 13, 25, and 21 is more obvious. The landmarks 9, 25, 13, and 21 of the female individual have sunk; the landmarks 9 and 25 of the male individual have risen. Compared with the male individual, the snout of the female individual is slightly protruding.

[0053] 1.4.4 Discriminant Analysis SPSS was used to conduct stepwise discriminant analysis. The results showed that when conducting stepwise discriminant analysis, RW 1 , RW 6 , RW 13 , RW 17 A total of 4 variables were included in the discriminant function, and the sex of 19 big spotted pufferfish was determined. The results showed that 2 out of 10 females were misidentified, with an accuracy rate of 80%, and the accuracy rate of males was 100%. The cross-validation results showed that 3 out of 10 females were misidentified, with an accuracy rate of 70%, and 1 out of 9 males was misidentified, with an accuracy rate of 88.9% (Table 4-2).

[0054] The standard discriminant function formula obtained according to the characteristic index is: Female: Y4=48.224RW 1 -93.587RW 6 -157.970RW 13 +391.177RW 17 -1.430 Male: Y5=-53.582RW 1 +103.985RW 6 +175.522RW 13 -434.642RW 17 -1.602 The determination method is as follows: after substituting the data of the fish to be determined as the giant pufferfish into formulas Y4 and Y5, the sex of the giant pufferfish corresponding to the equation with the largest value is the sex of the fish to be determined.

[0055] Table 4-2 Results of discrimination analysis of male and female pufferfish

[0056] 1.5 Six-spot pufferfish 1.5.1 Least Squares Regression Analysis The least squares regression analysis showed that the regression coefficient of the Pugh distance and the tangent space distance was 0.999646, close to 1, indicating that the selected landmarks were effective and could be used for the next statistical analysis. The average shape of the male and female six-spot porcupinefish calculated by the tpsRelw software based on the landmark coordinate data, as well as the superimposition effect of all landmarks are shown in Figure 2. Figure 1 and Figure 2 As shown. Through relative distortion analysis, the contribution rate of each landmark point in reflecting the difference in skull morphology is clarified. The contribution rate results of 33 landmark points in relative distortion principal component analysis are shown in Table 5-1. Among them, the contribution rate of landmark point 19 is the largest (0.12576%), followed by landmark points 15 and 22.

[0057] Table 5-1 Relative distortion contribution rate of each landmark point

[0058] 1.5.2 Principal Component Analysis like Fig.12 As shown, the data file obtained by Tpsdig was imported into MorphoJ, and the Prospectus overlay was performed. The required results were obtained after the software processing. A total of 21 principal components were extracted by relative distortion principal component analysis, with contribution rates: the first principal component was 24.42%, the second principal component was 13.58%, the third principal component was 8.59%, and the fourth principal component was 6.93%. The cumulative contribution rate of the first four principal components reached 53.52% (Table 5), which can better explain the morphological variation; the contribution rates of points 9 and 25 in type I landmark points are large, and the contribution rates of points 13 and 21 in type II landmark points are large. The overlay map of all landmark points is shown in the figure below. Fig.13 As shown in the figure, there is a small amount of overlap between the scattered points of male and female individuals, forming two relatively concentrated areas, indicating that the main component scatter plot has a good discrimination effect.

[0059] Table 5 Eigenvalues ​​and contribution rates of the first 10 principal components

[0060] 1.5.3 Visual analysis of morphological differences like Fig.14 As shown in the figure, the landmark points were visualized and analyzed using TpsRegr software. Compared with the average shape of the grid, the landmark points 9, 13, 21, and 25 of the male and female six-spot pufferfish have larger deformations. The landmark points 9, 25, 13, and 21 of the female individual have sunk; therefore, the snout of the female individual is more prominent than that of the male.

[0061] 1.5.4 Discriminant Analysis SPSS was used for stepwise discriminant analysis. The results showed that 15 variables were included in the discriminant function when the stepwise discriminant analysis was performed. The sex of 22 porcupine pufferfish was discriminated. The results showed that the correct rate of sex discrimination was 100%, as shown in Table 5-2. The cross-validation results also showed that the correct rate of sex discrimination was 100%, indicating that the model had good prediction effect and good generalization performance.

[0062] The standard discriminant function formula obtained according to the characteristic index is: female: Y4=-3202.345RW 1 +4316.864RW 2 +1009.759RW 3 -2045.467RW 5 -889.534RW 6 -3164.462RW 7 -6827.687RW 8 +2343.094RW 10 +5792.814RW 12 +7200.641RW 14 +4881.335RW 16 -1858.721RW 18 +3961.720RW 19 +7748.606RW 20 +14602.211RW 21 -44.681 male: Y5=8539.586RW 1 -11511.638RW 2 -2692.691RW 3 +5454.579RW 5 +2372.089RW 6+8438.566RW 7 +18207.165RW 8 -6248.250RW 10 -15447.504RW 12 -19201.710RW 14 -13016.893RW 16 +4956.590RW 18 -10564.587RW 19 -20662.949RW 20 -38939.230RW 21 -313.492 The determination method is as follows: after substituting the data of the fish to be determined as the six-spot pufferfish into formulas Y4 and Y5, the sex of the six-spot pufferfish corresponding to the equation with the largest value is the sex of the fish to be determined.

[0063] Table 5-2 Results of the discriminant analysis of the sex of Porcupine pufferfish

[0064] 2.1 Identification effect of landmark method 2.1.1 Identification effect of landmark method on three pufferfish The landmark method was used to study the skull morphological differences of three types of porcupine pufferfish: dense-spotted pufferfish, large-spotted pufferfish, and six-spotted pufferfish. The principal component analysis showed that the cumulative contribution rate of the first three principal components reached 60.71%, indicating the effectiveness of the selected landmark points. The principal components can better show the morphological differences of the three types of pufferfish. This experiment used SPSS to establish a discriminant function and conduct discriminant analysis on dense-spotted pufferfish, large-spotted pufferfish, and six-spotted pufferfish. The results showed that the discrimination success rate was between 93.3% and 100%.

[0065] 2.1.2 Effect of landmark method on identification of male and female individuals Landmarks can be used to identify the morphological differences between male and female skulls of Porcupine pufferfish, Porcupine pufferfish and Porcupine pufferfish. The results of principal component analysis show that the cumulative contribution rate of the first four principal components in the analysis of male and female differences of Porcupine pufferfish is 52.0%; the cumulative contribution rate of the first three principal components in the analysis of male and female differences of Porcupine pufferfish is 57.27%; the cumulative contribution rate of the first four principal components in the analysis of male and female differences of Porcupine pufferfish is 53.53%. In the study of interspecies identification of oceanic cephalopods in Suzhou and Hangzhou, the contribution rate of the first two principal components of the principal component analysis of the traditional morphometric method is 52.30%, the cumulative contribution rate of the first five principal components of the Fourier method is 49.49%, and the contribution rate of the first three principal components of the principal component analysis of the landmark method is 74.63%. It shows that the selection analysis results are affected by the analysis object and the selected morphological measurement method. The deformation of the organism can be visualized by the thin plate sampling method. By analyzing the grid deformation diagram, it was found that the skull of female Porcupine pufferfish is wider and larger; the snout of female Porcupine pufferfish and Porcupine pufferfish is more prominent than that of male Porcupine pufferfish.

[0066] 2.2 Application prospects of landmark method in fish skull analysis This experiment used geometric morphometrics based on the landmark method to study the morphological differences between the dense-spotted pufferfish, the big-spotted pufferfish, and the six-spotted pufferfish, as well as the intraspecific sexual differences of the three pufferfish. The landmark method can effectively distinguish the morphological differences between the three pufferfish, and the grid deformation map generated by the software can also analyze the subtle differences in the skulls of male and female pufferfish.

[0067] With the continuous development of geometric morphometric software, a large number of researchers have begun to pay attention to geometric morphometric methods based on software analysis, which has prompted more and more researchers and experts in this field to discuss at the exchange meeting, further promoting the popularization of geometric morphometric methods in the field of biology. As a kind of geometric morphometric method, the landmark method has been widely used in various fields, such as insect classification, fish otolith identification, snail classification, etc. Some researchers have also combined CT scanning to study and analyze the morphology of fish, and have achieved good results. The sex of fish can be distinguished by marriage color, body size, etc., but the difference in appearance between male and female individuals of some fish is not very obvious, which brings many inconveniences to the work of breeders. At present, some scholars have studied the automatic identification of rodents. In the future, with the development of artificial intelligence and automation industry, the automatic classification of fish will also become a research hotspot. At that time, geometric morphometric measurement based on the landmark method will have a bigger stage, and there will be more in-depth research on the automatic identification and classification of fish.

[0068] 2.3 Selection of analytical methods Traditional morphometric methods have the disadvantages of being cumbersome and having large errors during use. Compared with geometric morphometric methods, they are slightly insufficient. With the continuous improvement of geometric morphometric methods, geometric morphometric methods based on landmark points have been applied by more and more scholars to the intra-species and inter-species identification of aquatic organisms. The skull morphology is stable and has strong inter-species specificity. It has been included in the study of inter-species differences by many scholars. For example, the relationship between the geometric morphology of the skull and lower molars of the Chinese Burmese tree shrew and the environment, and the geometric morphometric analysis of the head contour shape and variation of the plateau naked splittail fish, all show the superiority of the landmark method. However, there are also those whose accuracy of landmark method is lower than that of traditional morphometric method. For example, Feng Bo et al. studied different local populations of short-nosed mullets. The results showed that the traditional morphometric method was better than the landmark method. It is speculated that this may be related to improper selection of landmark points.

[0069] The skull structure of porcupinefish is relatively complex. Compared with the Fourier method, the landmark method can reflect more skull morphological information by analyzing the position differences of each landmark point, so the landmark method is the best choice. At the same time, the selection of landmark points should pay attention to factors such as homology, repeatability, and integrity, otherwise it may affect the final classification and identification results.

[0070] In summary, the advantages of the present invention are: 1. The landmark method was used to identify the morphological differences of the three pufferfishes, with a success rate of 93.3% to 100%, proving the effectiveness of the landmark method, which can effectively classify the dense-spotted, large-spotted, and six-spotted pufferfishes. The grid deformation map shows that the frontal bone of the dense-spotted pufferfish is more rounded, and the junction between the frontal bone and the external ethmoid bone is smooth without protruding parts; the frontal bone of the large-spotted pufferfish is slightly concave, and the junction between the frontal bone and the external ethmoid bone is very round; the frontal bone of the six-spotted pufferfish is slightly concave, and the junction between the frontal bone and the external ethmoid bone is more pointed than that of the other two pufferfishes.

[0071] 2. Use the landmark method to identify the morphological differences between the skulls of male and female porcupine pufferfish. Through principal component analysis and deformation visualization, the female skull of the dense-spotted pufferfish is wider and larger; the snout of the large-spotted pufferfish and the six-spotted pufferfish is more prominent in the female than in the male. Since the gender differences of pufferfish are not significant, the differences reflected in the skull morphology are also very small, and it is difficult to distinguish the male and female skulls with the naked eye.

[0072] 3. The frontal bone contour of the porcupine pufferfish. Because there are no points on it that meet the landmark point selection principle, sliding landmark points are used to simulate the changes in the frontal bone contour. The results show that sliding landmark points can better explain the morphological changes in the frontal bone contour of the porcupine pufferfish. In comparison with the three porcupine pufferfish, the frontal bone contour of the dense-spotted pufferfish is more rounded and convex, while the frontal bone contours of the large-spotted pufferfish and the six-spotted pufferfish are slightly concave.

[0073] 4. The landmark method is effective for both inter-species identification and gender distinction of the same species. Combined with SPSS statistical analysis, it can fully present the morphological differences of organisms.

[0074] The present invention also provides a system for analyzing the morphological differences of the skulls of three species of porcupine fish based on a landmark point method, comprising a memory, a control processor, and a computer program stored in the memory and executable on the control processor. The control processor executes the program to implement the aforementioned method for analyzing the morphological differences of the skulls of three species of porcupine fish based on a landmark point method.

[0075] The present invention also provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to enable a computer to implement the aforementioned method for analyzing the differences in skull morphology of male and female porcupine fish based on the landmark point method.

[0076] Although the above methods are illustrated and described as a series of actions for simplicity of explanation, it should be understood and appreciated that these methods are not limited by the order of the actions, because according to one or more embodiments, some actions may occur in different orders and / or concurrently with other actions from the illustrations and descriptions herein or not illustrated and described herein but understandable to those skilled in the art. It will be further appreciated by those skilled in the art that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or a combination of the two. To clearly explain this interchangeability of hardware and software, various illustrative components, frames, modules, circuits, and steps are generally described in the form of their functionality above. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. The technical staff can implement the described functionality in different ways for each specific application, but such implementation decisions should not be interpreted as resulting in a departure from the scope of the present invention. The various illustrative logic blocks, modules, and circuits described in conjunction with the embodiments disclosed herein may be implemented or executed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in an alternative, the processor may be any conventional processor, a battery compartment control board, a micro-battery compartment control board, or a state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in cooperation with a DSP core, or any other such configuration. The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read and write information from / to the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and the storage medium may reside in a user terminal as discrete components. In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented as a computer program product in software, each function may be stored on a computer-readable medium or transmitted therefrom as one or more instructions or codes.Computer-readable media include both computer storage media and communication media, including any media that facilitates a computer program to be transferred from one place to another. Storage media can be any available media that can be accessed by a computer. As an example and not limitation, such computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage or other magnetic storage devices, or any other media that can be used to carry or store the agreed program code in the form of instructions or data structures and can be accessed by a computer. Any connection is also properly referred to as computer-readable media. For example, if software is transmitted from a web site, a central control computer, or other remote sources using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of medium. Disk and disc as used herein include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, wherein disk often reproduces data magnetically, while disc reproduces data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0077] Although the above methods are illustrated and described as a series of actions for simplicity of explanation, it should be understood and appreciated that these methods are not limited by the order of the actions, because according to one or more embodiments, some actions may occur in a different order and / or concurrently with other actions from those illustrated and described herein or not illustrated and described herein but understandable to those skilled in the art.

[0078] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A method for analyzing the skull morphology differences of three species of porcupinefish based on the landmark method, characterized in that: The following steps are involved: Step 1: Use software to extract the coordinate values ​​of feature points on the skull of porcupinefish; use Tpsdig2 software to establish landmark points on the two-dimensional image of the skull, including the following three types: Type I landmark points are the intersections of bones or sutures; Type II landmark points are convex or concave points on the skull; Type III landmark points are the widest points on the left and right sides of the skull; Step 2: Perform relative distortion principal component analysis on the obtained data file to obtain the eigenvalues ​​and contribution rates of different principal components and relative distortion scores; Step 3. Finally, thin-plate strip analysis was used to visualize the morphological variation of the skull through the grid deformation map, and the discriminant equation was established using the relative distortion score to distinguish the morphological differences between the skulls of male and female porcupine pufferfish, the dense-spotted pufferfish, and the six-spotted pufferfish, and the results of the discriminant analysis were obtained.

2. The method for analyzing the skull morphology differences of three species of pufferfish based on the landmark method according to claim 1, characterized in that: In step 1, the skull two-dimensional image is specifically obtained by placing the obtained complete skull sample on a black background board and taking a photo to obtain a clear and complete skull two-dimensional image, and then using Tpsdig2 software to establish coordinate points on the skull two-dimensional image, and using Tpssmall software to verify the validity of the obtained landmark points.

3. A method for analyzing the skull morphology differences of three species of porcupine pufferfish based on a landmark method according to claim 1 or 2, characterized in that: In step 2, TpsRelw is used to process and analyze the landmark points of each sample to obtain the average shape diagram of the sample, perform relative distortion principal component analysis, and save the analysis report and relative distortion score generated by the software.

4. The method for analyzing the skull morphology differences of three species of porcupine pufferfish based on the landmark method according to claim 3, characterized in that: Specifically, step 3 uses TpsRegr software to perform thin-plate strip analysis, visualizes the deformation, saves the mesh deformation diagrams of the male and female skulls of the three porcupine pufferfish, and imports the relative distortion score data obtained by Tpsrelw into SPSS after processing for stepwise discriminant analysis and interactive validation. The Bayes method is used for discriminant analysis, and SPSS26.0 is used for statistical analysis.

5. The method for analyzing the skull morphology differences of three species of porcupine pufferfish based on the landmark method according to claim 4, characterized in that: In step 3, the landmark point file is processed using Tpsrelw to obtain the average shape and the overlapping landmark points; distortion analysis, regression analysis and permutation test are performed using Tpsregr, the grid deformation map generated by the software is saved, the variables with large relative distortion contribution rate are screened out, stepwise discriminant analysis is performed using SPSS, discriminant equations are established for these variables, and the results of the discriminant analysis are obtained.

6. The method for analyzing the skull morphology differences of three species of porcupine pufferfish based on the landmark method according to claim 5, characterized in that: In step 3, the average shape of the porcupine skull morphology is obtained by using tpsRelw software, and relative distortion is performed, and an analysis report and a relative distortion score are obtained at the same time, and relative distortion principal component analysis is performed and the relative distortion score is used to perform discriminant analysis on the three types of porcupine skull morphologies. The discriminant equation is specifically: Six-spot pufferfish: <h2 style=";text-align:left;direction:ltr">Y1=353.557RW1+174.606RW2-86.135RW3-231.256RW4-0.652RW6+47.768RW7+156.161RW8+33.759RW<h2 style=";text-align:left;direction:ltr"> 14 <h2 style=";text-align:left;direction:ltr"> -13.763 Big spotted pufferfish: <h2 style=";text-align:left;direction:ltr">Y2=102.017RW1-254.039RW2+620.319RW3-90.799RW4-140.701RW6+159.768RW7-229.571RW8-260.498RW<h2 style=";text-align:left;direction:ltr"> 14 <h2 style=";text-align:left;direction:ltr"> -11.452 Porcupine pufferfish: <h2 style=";text-align:left;direction:ltr">Y3=-276.457RW1-88.926RW2-243.396RW3+176.822RW4+68.439RW6-88.637RW7+3.107RW8+125.404RW<h2 style=";text-align:left;direction:ltr"> 14 <h2 style=";text-align:left;direction:ltr"> -8,070 Among them, according to the relative distortion score from high to low, RW1 ranks first, RW2 ranks second, RW3 ranks third, RW4 ranks fourth, RW6 ranks sixth, RW7 ranks seventh, RW8 ranks eighth, and RW 14 Ranked 14th; The determination method is to substitute the data of the fish to be determined into formulas Y1, Y2, and Y3. The pufferfish species corresponding to the equation with the largest value is the species of the fish to be determined.

7. The method for analyzing the skull morphology differences of three species of porcupine pufferfish based on the landmark method according to claim 6, characterized in that: In step 3, If it is determined to be a six-spot pufferfish, the sex discrimination function is obtained according to the characteristic index: female: <h2 style=";text-align:left;direction:ltr">Y4=-3202.345RW1+4316.864RW2+1009.759RW3-2045.467RW5-889.534RW6-3164.462RW7-6827.687RW8+2343.094RW<h2 style=";text-align:left;direction:ltr"> 10 <h2 style=";text-align:left;direction:ltr"> +5792.814RW<h2 style=";text-align:left;direction:ltr"> 12 <h2 style=";text-align:left;direction:ltr"> +7200.641RW<h2 style=";text-align:left;direction:ltr"> 14 <h2 style=";text-align:left;direction:ltr"> +4881.335RW<h2 style=";text-align:left;direction:ltr"> 16 <h2 style=";text-align:left;direction:ltr"> -1858.721RW<h2 style=";text-align:left;direction:ltr"> 18 <h2 style=";text-align:left;direction:ltr"> +3961.720RW<h2 style=";text-align:left;direction:ltr"> 19 <h2 style=";text-align:left;direction:ltr"> +7748.606RW<h2 style=";text-align:left;direction:ltr"> 20 <h2 style=";text-align:left;direction:ltr"> +14602.211RW<h2 style=";text-align:left;direction:ltr"> 21 <h2 style=";text-align:left;direction:ltr"> -44.681 male: Y5=8539.586RW1-11511.638RW2-2692.691RW3+5454.579RW5+2372.089RW6+8438.566RW7+18207.165RW8-6248.250RW 10 -15447.504RW 12 -19201.710RW 14 -13016.893RW 16 +4956.590RW 18 -10564.587RW 19 -20662.949RW 20 -38939.230RW 21 -313.492 Among them, according to the relative distortion score from high to low, RW1 ranks first, RW2 ranks second, RW3 ranks third, RW4 ranks fourth, RW5 ranks fifth, RW6 ranks sixth, RW7 ranks seventh, RW8 ranks eighth, and RW9 ranks eighth. 10 For the No. 10, RW 12 For the 12th place, RW 14 RW ranked 14th 16 For the No. 16, RW 18 For the 18th place, RW 19 For the No. 19, RW 20 For the No. 20, RW 21 It ranks 21st; the determination method is to substitute the data of the fish to be determined as the six-spot pufferfish into formulas Y4 and Y5, and the sex of the six-spot pufferfish corresponding to the equation with the largest value is the sex of the fish to be determined; Or if it has been determined to be a big spotted pufferfish, the sex discrimination function obtained based on the characteristic index is: female: Y4=48.224RW1-93.587RW6-157.970RW 13 +391.177RW 17 -1.430 male: <h2 style=";text-align:left;direction:ltr">Y5=-53.582RW1+103.985RW6+175.522RW<h2 style=";text-align:left;direction:ltr"> 13 <h2 style=";text-align:left;direction:ltr"> -434.642RW<h2 style=";text-align:left;direction:ltr"> 17 <h2 style=";text-align:left;direction:ltr"> -1.602 Among them, they are sorted from high to low according to the relative distortion score, with RW1 ranking first, RW6 ranking sixth, RW13 ranking thirteenth, and RW17 ranking seventeenth. The determination method is to substitute the data of the fish to be determined as the big spot pufferfish into formulas Y4 and Y5, and the big spot pufferfish sex corresponding to the equation with the largest value is the sex of the fish to be determined; Or if it has been determined to be a porcupine pufferfish, the sex discrimination function obtained based on the characteristic index is: female: Y4=142.158RW8-104.372RW9-247.819RW 11 +157.611RW 12 +190.725RW 16 -259.171RW 17 +441.071RW 23 -683.944RW 27 -518.182RW 28 -2.143 male: Y5=-162.467RW8+119.282RW9+283.221RW 11 -180.126RW 12 -217.971RW 16 +296.195RW 17 -504.081RW 23 +781.650RW 27 +592.209RW 28 -2.587 Among them, according to the relative distortion score from high to low, RW8 is ranked 8th, RW9 is ranked 9th, and RW 11 For the 11th place, RW 12 For the 12th place, RW 16 For the No. 16, RW 17 For the No. 17, RW 23 For the No. 23, RW 27 For the No. 27, RW 28 It ranks 28th; the determination method is to substitute the data of the fish to be determined as the dense-spotted pufferfish into formulas Y4 and Y5, and the sex of the dense-spotted pufferfish corresponding to the equation with the largest value is the sex of the fish to be determined.

8. A system, characterized in that: The invention comprises a memory, a control processor and a computer program stored in the memory and executable on the control processor, wherein the control processor executes the program to implement the method for analyzing the skull morphology differences of three types of porcupine pufferfish based on the landmark point method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to implement the method for analyzing the morphological differences of the skulls of three male and female porcupine fishes based on the landmark point method according to any one of claims 1 to 7. A method for analyzing the morphological differences of the skulls of three male and female porcupine fishes based on the landmark point method is characterized in that it comprises the following steps: Step 1: Use software to extract the coordinate values ​​of feature points on the skull of porcupinefish; use Tpsdig2 software to establish landmark points on the two-dimensional image of the skull, including the following three types: Type I landmark points are the intersections of bones or sutures; Type II landmark points are convex or concave points on the skull; Type III landmark points are the widest points on the left and right sides of the skull; Step 2: Perform relative distortion principal component analysis on the obtained data file to obtain the eigenvalues ​​and contribution rates of different principal components and relative distortion scores; Step 3. Finally, thin-plate strip analysis was used to visualize the morphological variation of the skull through the grid deformation map, and the discriminant equation was established using the relative distortion score to distinguish the morphological differences between the skulls of male and female porcupine pufferfish, the dense-spotted pufferfish, and the six-spotted pufferfish, and the results of the discriminant analysis were obtained.

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