Analysis method, medium and system for identifying three kinds of takifugu otolith morphologies based on Fourier analysis method

Abstract

The invention relates to the field of takifugu sagittal stone morphology identification methods, and particularly discloses an analysis method for identifying three takifugu sagittal stone morphologies based on a Fourier analysis method.The method comprises the following steps that 1, otolith is placed under a microscope objective lens for image acquisition, and an otolith image is obtained; carrying out Fourier transformation on the image to obtain Fourier harmonic values of three kinds of takifugu sagittal stones; 2, performing principal component analysis on the Fourier harmonic values of the three kinds of takifugu sagittal otolith by using statistical software to obtain characteristic values, contribution rates and the like for describing otolith contours; and step 3, performing discriminant analysis on the three kinds of takifugu sagittal stones by using a step-by-step discriminant analysis method, extracting typical discriminant Fourier harmonics of the three kinds of takifugu sagittal stones through SPSS software to obtain a typical discriminant function, and substituting the typical discriminant function into the typical discriminant function to obtain a discriminant analysis result. According to the method, the elliptical Fourier analysis method is adopted for analysis, the difference among the three kinds of takifugu sagittal otolith is obtained, a research thought is provided for automatic classification of fish otolith in the future, and the method has important theoretical and scientific research significance.

Description

Technical Field

[0001] The present invention relates to the technical field of the analysis method for the morphological differences of the otoliths of Diodon holocanthus, and particularly relates to a method for identifying the morphological analysis methods of the otoliths of three species of Diodon based on Fourier analysis, and also relates to a system for identifying the morphological analysis of the otoliths of three species of Diodon based on Fourier analysis. Background Art

[0002] Diodon holocanthus belongs to Tetraodontiformes, Tetraodontoidei, and Tetraodntoidea. These fish mainly inhabit the seaweed thickets and coral reef areas in the warm and tropical coastal waters. There are 6 species of Diodon holocanthus distributed in the South China Sea and other sea areas, and they mainly feed on small fish, small shrimps, etc. In the past, the research on Diodon holocanthus by the academic community was relatively scarce. When the public talked about the poisonous "pufferfish", they were often easily confused. In fact, Diodon holocanthus and pufferfish belong to different families and genera. With the improvement of human living conditions, people have gradually gained a new understanding of Diodon holocanthus. Diodon holocanthus not only has a delicious taste and rich nutrition, but its fish skin also contains vitamins, various amino acids, and a large amount of collagen. In addition, Diodon holocanthus looks cute and extremely lovely in appearance, and is deeply loved by the public. In view of this, it is particularly crucial to deeply explore the differences between different species of Diodon holocanthus, whether for fishery research, ecological protection, or to meet the public's popular science needs, which can provide strong support for the subsequent reasonable development and utilization, and scientific conservation of Diodon holocanthus resources.

[0003] During the growth process of teleost fish, stones will be deposited and formed in the semicircular canals of the inner ear bony labyrinth, called otoliths, and the main chemical component is calcium carbonate. Along with the growth and development of fish, the otoliths continuously precipitate and accumulate, and finally form a relatively stable state. The otoliths continuously record the fish during the growth of the fish, and form rings of annual rings in the otoliths. In fact, like fish scales, the annual rings of fish otoliths can both be used as important bases for judging the age and growth stage of fish. Fish otoliths have extremely wide applications in the field of ichthyology research. Whether it is to explore the hatching process of fish, the early growth and development mode, or to accurately determine the spawning period, optimize the transportation conditions of juvenile fish, and even to identify the age and species of fish, otoliths play an irreplaceable role. It should be noted that for different species of fish, the morphology of their otoliths is often very different. This significant difference has attracted the attention and favor of scientists, biologists, and relevant researchers, because the more significant the morphological difference is, the more convenient it is to accurately identify different species of fish, which has a profound impact on the fish classification and identification work. However, there is currently little biological research on three species of Diodon holocanthus fish, and no research on the otoliths of Diodon holocanthus has been seen. Summary of the Invention

[0004] In view of this, the present invention provides a method for identifying the morphological analysis of otoliths of three species of pufferfish based on Fourier analysis method. The elliptic Fourier analysis method is used for analysis to obtain the differences among the sagittal otoliths of the three species of pufferfish. To achieve the above object, the basic scheme of the present invention provides a method for identifying the morphological analysis of the sagittal otoliths of three species of pufferfish based on Fourier analysis method, including the following steps: Step 1: Place the otolith under the microscope objective for image acquisition, and obtain the Fourier harmonic values of the sagittal otoliths of the three species of pufferfish through Fourier transform of the image; Step 2: Use statistical software to perform principal component analysis on the Fourier harmonic values of the sagittal otoliths of the three species of pufferfish to obtain the characteristic values, contribution rates and cumulative contribution rates for describing the otolith contour, as well as the principal component scatter plot; Step 3: Use stepwise discriminant analysis method to perform discriminant analysis on the Fourier harmonic values of the sagittal otoliths of the three species of pufferfish. Extract the typical discriminant Fourier harmonics of the sagittal otoliths of the three species of pufferfish through SPSS software to obtain the typical discriminant function, and substitute it to obtain the result of discriminant analysis.

[0005] In a possible design, in step 1, the elliptic Fourier analysis method is adopted. The sagittal otoliths of the three species of pufferfish are used to depict the otolith contour through SHAPE software, and then 80 groups of Fourier harmonic values are obtained through the CHC2ENF program. After screening by the Princomp program, finally, the three groups of harmonic values with A1 = 1, B1 = C1 = 0 are removed to obtain 77 groups of Fourier harmonic values. In a possible design, step 1 is specifically as follows: The Fourier harmonic values of the sagittal otoliths of the three species of pufferfish are obtained through Fourier transform of the image. The extraction of Fourier harmonic values mainly adopts three programs in the "SHAPE" software, namely "Chaincoder", "Chc2Nef" and "Princomp" programs. Insert the otolith picture into the program, and use "Chaincoder" to take the overall contour outside the otolith to describe the external morphology of the otolith, and obtain the area of each otolith and the 0-7 digital information chain code, which are stored in a file with the format of "CHC"; the "Chc2Nef" program, insert the "CHC" file to establish a file with the format of "NEF". After analysis by the "Chc2Nef" program, the overall external morphology image of the otolith described by the first program is converted into Fourier harmonic values. Each otolith obtains 80 Fourier coefficients, which are stored in the "NEF" file; 20 Fourier harmonics can describe the external morphology of the otolith. Each group of Fourier coefficients is composed of 4 Fourier harmonic values A, B, C, and D. Use the "Princomp" program to perform standardization processing on the obtained Fourier coefficients. After analysis, the constants with A1 = 1, B1 = C1 = 0 should be removed. Finally, 77 Fourier harmonic numbers are used to describe the entire external contour of the otolith. The "Princomp" program can also reconstruct the graph of the otolith to better distinguish different otoliths.

[0006] In a possible design, in step 2, 77 Fourier coefficients of the left and right sagittal otoliths of three species of pufferfish are statistically summarized, and the mean difference test is used to examine the differences between the left and right otoliths of the three species of pufferfish; through the "Princomp" program, the otoliths of the three species of pufferfish are reconstructed graphically. The conversion is performed with 20 harmonics. Starting from the first harmonic, the Fourier coefficients obtained are used for graphical reconstruction up to the 20th harmonic, and the coincidence analysis of the graphical reconstructions of the otoliths of the three species of pufferfish is carried out.

[0007] In a possible design, in step 2, the principal component analysis of 77 Fourier harmonic values of the otoliths of three species of pufferfish is performed using the spss19.0 statistical software to obtain the eigenvalue, contribution rate, cumulative contribution rate, and the principal component scatter plot describing the otolith contour.

[0008] In a possible design, in step 3, 77 Fourier coefficients are converted from the overall contours of the otoliths of three species of pufferfish obtained by the SHAPE series software. Through stepwise discriminant analysis using spss19.0, the discriminant scatter plot and discriminant results of the otoliths of the three species of pufferfish are obtained.

[0009] In a possible design, the stepwise discriminant analysis method is used to screen 77 Fourier characteristic coefficients of the otoliths of three species of pufferfish. Finally, A9, A13, A16, C2, C9, C15, D3, and D16 are selected. A9, A13, and A16 respectively represent the amplitudes of the fundamental frequencies in the 9th, 13th, and 16th groups of Fourier harmonic values. C2, C9, and C15 respectively represent the amplitudes of the second harmonics in the 2nd, 9th, and 15th groups of Fourier harmonic values. D3 and D16 respectively represent the phases of the second harmonics in the 3rd and 16th groups of Fourier harmonic values. The discriminant equations for the 8 Fourier characteristic coefficients are specifically as follows: Torquigener pleurogrammus Y 1 = 0.359X A9 - 0.166X A13 - 0.144X A16 + 0.251X C2 - 0.150X C9 - 0.252X C15 - 0.342X D3 + 0.199X D16 - 2.067 Torquigener oblongus Y 2 = 0.122X A9 - 0.274X A13 + 0.204X A16 + 0.243X C2 - 0.507X C9 + 0.132X C15-0.155X D3 +0.373X D16 -4.251 Six-spot porcupinefish Y 3 =0.379X A9 +0.185X A13 +0.229X A16 -0.198X C2 +0.120X C9 +0.299X C15 +0.474X D3 -0.134X D16 -3.256 The determination method is to substitute the data of the fish to be discriminated into the formula Y 1 、Y 2 、Y 3 After that, the porcupinefish species corresponding to the equation with the largest value is the species of the fish to be discriminated.

[0010] The present invention provides a device, including a memory, a control processor, and a computer program stored on the memory and executable on the control processor. The control processor executes the program to implement the method for analyzing the otolith morphology of three porcupinefish based on the Fourier analysis method as described above.

[0011] The present invention provides a system, including the device for analyzing the otolith morphology of three porcupinefish based on the Fourier analysis method as described above.

[0012] The present invention further provides a computer-readable storage medium, which stores computer-executable instructions for enabling a computer to implement the method for analyzing the otolith morphology of three porcupinefish based on the Fourier analysis method as described above.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The Fourier analysis method of the present invention discriminates and analyzes the sagittal otoliths of three porcupinefish, and obtains 77 Fourier harmonic values of the sagittal otoliths of the three porcupinefish, and performs principal component analysis. The cumulative contribution rate of the first 27 principal components with eigenvalues >1 is 88.039%. The contribution rate of the first principal component with the highest contribution rate is 6.542%. From the principal component scatter plot obtained by the first principal component factor and the second principal component factor, the distributions of the sagittal otoliths of the three porcupinefish are relatively scattered. There is more overlap between the Dense-spot porcupinefish and the Large-spot porcupinefish, and the distinction is not particularly obvious. There is only a small amount of overlap between the Dense-spot porcupinefish and the Six-spot porcupinefish, and the distinction is obvious.

[0014] (2) By using discriminant analysis on the sagittal otoliths of three species of pufferfish, the present invention shows that the discrimination success rate for *Diodon hystrix* is 100%, for *Diodon liturosus* it reaches 87.5%, and for *Arothron hispidus* it reaches 90.0%. The average success rate for the initial discrimination of the three species of pufferfish is 92.5%. In the discriminant scatter plot obtained from the first and second characteristic values, *Arothron hispidus* and *Diodon hystrix* are clearly distinguishable, while the discrimination effect between *Diodon liturosus* and *Arothron hispidus*, as well as *Diodon hystrix*, is not particularly good, with a small amount of overlap. This indicates that the Fourier analysis method has good discriminability for the identification of fish otoliths.

[0015] (3) The present invention uses the Princomp program to reconstruct the graphs of the Fourier coefficients of the three species of pufferfish. It is found that the lower the Fourier harmonic order, the greater the contribution rate and the more obvious the amplitude. When reaching the 10th harmonic order, the basic outline of the otolith is completely described. As the harmonic order increases, the graph does not change significantly. Therefore, 20 groups of harmonic orders are selected for analysis in this paper to better describe the integrity of the sagittal otoliths of the three species of pufferfish. The graph reconstruction allows us to verify the Fourier coefficients obtained by the Fourier analysis method again, that is, whether the Fourier coefficients can completely describe the outline of the otolith. Therefore, using the Fourier analysis method can not only accurately obtain the otolith morphological parameter values, but also convert the numerical values into graphs for re-verification, further demonstrating the accuracy of the Fourier analysis method for the discrimination of fish otoliths. Description of the Drawings

[0016] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] Figure 1 Shows the schematic diagram of the extraction of the left sagittal otolith morphology and contour line of three species of pufferfish in the embodiments of the present application, where a is *Arothron hispidus*; b is *Diodon liturosus*; c is *Diodon hystrix*; Figure 2 Shows the schematic diagram of the graph reconstruction of the sagittal otolith of *Diodon liturosus* using the Fourier harmonic order in the embodiments of the present application; Figure 3 Shows the schematic diagram of the reconstructed graphs of the three species of pufferfish with the change of the Fourier harmonic order of the amplitude, where a is *Arothron hispidus*; b is *Diodon liturosus*; c is *Diodon hystrix*; Figure 4 Shows the schematic diagram of the otolith contour simulation of the three species of pufferfish in the embodiments of the present application. The red line represents *Diodon liturosus*, the green line represents *Diodon hystrix*, and the black line represents *Arothron hispidus*; Figure 5The schematic diagrams of the first and second principal component scatter plots of three species of pufferfish in the embodiments of the present application are shown; Figure 6 The discriminant analysis scatter plot based on the Fourier analysis method in the embodiments of the present application is shown. Specific embodiments

[0018] To further illustrate the embodiments, the present invention provides accompanying drawings, which are part of the disclosure of the present invention. They are mainly used to illustrate the embodiments and can be combined with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, those of ordinary skill in the art should be able to understand other possible embodiments and the advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are usually used to represent similar components.

[0019] A method for identifying the otolith morphology of three species of pufferfish based on the Fourier analysis method includes the following parts 1.2.1 Otolith sample collection After fully thawing the three species of pufferfish that were originally frozen, basic biological measurements were performed on the three species of pufferfish, mainly measuring body weight, body length, and gender. The body length was accurate to 1 mm, and the body weight was accurate to 1 g. The gonads were removed to distinguish between males and females. After dissecting and opening the osseous labyrinth of the pufferfish, the sample otoliths were taken out with forceps under a dissecting microscope, carefully cleaned with deionized water and then ultrasonically cleaned twice to remove the surface mucosa and organic substances. After numbering them, they were stored in 1.5 ml centrifuge tubes containing 95% alcohol.

[0020] 1.2.2 Fourier analysis method based on otolith morphology 1.2.2.1 Acquisition of two-dimensional images The cleaned otoliths were placed under a 40x objective lens of an Olympus optical microscope for image acquisition. When taking pictures, the left otoliths were uniformly selected (if the left otoliths were missing, the right otoliths were used instead), and they were vertically photographed after being placed horizontally. Both sides of the otoliths were photographed, and the scale was 100 mm. After the image acquisition was completed, due to the influence of the otolith placement position and shooting brightness, it was necessary to use Photoshop CS5 to process the otolith images to ensure the integrity of the otolith contour.

[0021] 1.2.2.2 Extraction of Fourier harmonic values The Fourier harmonic values of the sagittal otoliths of three species of pufferfish were obtained through Fourier transform. The extraction of Fourier harmonic values mainly used three programs in the "SHAPE" software, namely the "Chaincoder", "Chc2Nef", and "Princomp" programs. Insert the otolith image (the image can only be in BMP format) into this program. The overall contour of the otolith exterior was obtained through the "Chaincoder" to describe the external morphology of the otolith, and the area of each otolith and the digital information chain code from 0 to 7 were obtained, which were stored in a file with the "CHC" format. For the "Chc2Nef" program, insert the "CHC" file to create a file with the "NEF" format. After analysis by the "Chc2Nef" program, the overall external morphology image of the otolith described by the first program was converted into Fourier harmonic values. Each otolith obtained a total of 80 Fourier coefficients, which were stored in the "NEF" file. Generally, it is considered that 20 Fourier harmonics can describe the external morphology of the otolith. Each set of Fourier coefficients consists of 4 Fourier harmonic values A, B, C, and D. Using the "Princomp" program, the obtained Fourier coefficients were standardized. After analysis, the constants A1 = 1, B1 = C1 = 0 should be removed, and finally 77 Fourier harmonic numbers were used to describe the entire external contour of the otolith. The "Princomp" program can also reconstruct the otolith graphics to better distinguish different species of otoliths.

[0022] 1.2.2.3 Conversion of Fourier coefficients (1) For the morphological analysis of the sagittal otoliths of three species of pufferfish, the sagittal otoliths of three species of pufferfish were used for analysis. The otoliths were divided into left and right ones. In this experiment, the left sagittal otoliths were used. Therefore, it is necessary to analyze the left and right sagittal otoliths to determine whether there are differences, and whether the left and right can be substituted for each other in case some otoliths are damaged during the extraction process. The 77 Fourier coefficients of the left and right sagittal otoliths of three species of pufferfish were statistically summarized, and the mean difference test (t-test) was used to analyze the differences between the left and right sagittal otoliths of three species of pufferfish. Through the "Princomp" program, the sagittal otoliths of three species of pufferfish were reconstructed graphically. Starting from the 1st harmonic, the Fourier coefficients obtained were used for graphical reconstruction up to the 20th harmonic, and the coincidence analysis of the graphical reconstructions of the sagittal otoliths of three species of pufferfish was carried out.

[0023] (2) Using the spss19.0 statistical software, the principal component analysis was carried out on the 77 Fourier harmonic values of the sagittal otoliths of three species of pufferfish to obtain the eigenvalue, contribution rate, and cumulative contribution rate for describing the otolith contour, as well as the principal component scatter plot.

[0024] (3)Convert the overall outlines of the otoliths of three species of pufferfish obtained by the SHAPE series software into 77 Fourier coefficients, and perform stepwise discriminant analysis using spss19.0 to obtain the discriminant scatter plots and discriminant results of the otoliths of the three species of pufferfish.

[0025] 1.3 Data processing (1)The data of this experiment were processed using Excel.

[0026] (2)Use the mean T-test method in SPSS software to compare the left and right differences of the left and right otoliths of the three species of pufferfish, and obtain the significance of the left and right otoliths.

[0027] (2)Use the Princomp program in SHAPE software to reconstruct the graphics of the NEF files in the otoliths of the three species of pufferfish. (The NEF file mainly describes the Fourier coefficients obtained from the overall outline of the otolith).

[0028] (3)Use the spss19.0 statistical software to perform principal component analysis and discriminant analysis on the parameter values of the otoliths.

[0029] (4)Use the stepwise discriminant analysis method (stepwisediscriminantanalysis, SDA) to perform discriminant analysis on the otoliths of the three species of pufferfish, extract the typical discriminant Fourier harmonics of the otoliths of the three species of pufferfish through SPSS software, and obtain the typical discriminant function table.

[0030] 2.1 Morphology of the otoliths of three species of pufferfish The morphological outlines of the otoliths of the three species of pufferfish are extracted as Figure 1 shown. As the fish otoliths continue to develop and grow, the external morphological characteristics of the otoliths will change. a is *Takifugu sexmaculatus*, b is *Takifugu oblongus*, and c is *Takifugu poecilonotus*. Among the three species of pufferfish, the external characteristics of the otoliths of *Takifugu poecilonotus* and *Takifugu sexmaculatus* are not particularly obvious compared to *Takifugu oblongus*. The overall characteristics of *Takifugu oblongus* are prominent, and the otolith deposition characteristics on the abdominal surface are obvious. The abdomens of the otoliths of *Takifugu sexmaculatus* and *Takifugu poecilonotus* are relatively smooth.

[0031] 2.2 Left and right discrimination of the otoliths of three species of pufferfish Perform Fourier analysis on the left and right otoliths of the three species of pufferfish through SHAPE software to obtain 77 Fourier harmonic values. Perform a mean difference test (t-test) on the obtained Fourier harmonic values through SPSS software. The consistency deviation between the left and right otoliths (P>0.05), and uniformly select the left otoliths as the research materials (see Table 1).

[0032] Table 1 Comparison of the left and right otoliths of three species of pufferfish

[0033]

[0034]

[0035] 2.3 Fourier Analysis of the Morphology of the Sagittal Otoliths of Three Species of Porcupinefish Using the NEF file obtained from the SHAPE software, it was substituted into the Princomp program to reconstruct the graphics for the data of 20 harmonics. The characteristics of the 11-14th and 16-19th harmonics were not obvious, so 12 reconstructed graphics of 1-10, 15, and 20 were selected for plotting, as Figure 2 shown Figure 2 indicating that the lower harmonics contribute more to the graphic reconstruction and play a key role in the discrimination of the sagittal otolith species of the three species of porcupinefish. The role of the higher harmonics is reflected in the fine parts of the otolith morphology. As the number of harmonics increases, the contribution rate to describing the external contour of the otolith becomes lower and lower. It only plays a decorative role in some tiny places. Therefore, this paper only selects the Fourier coefficients of 20 harmonics to analyze the sagittal otoliths of the three species of porcupinefish.

[0036] The relationship between the Fourier harmonic numbers and amplitudes of the three species of porcupinefish is as Figure 3 shown. It can be seen from the figure that the amplitudes of the first five Fourier harmonic numbers are relatively high, indicating that the first five Fourier harmonic numbers have a higher contribution rate to the description of the contour morphology of the otolith. As the number of Fourier harmonic numbers increases, the corresponding amplitudes decrease, indicating that the contribution rate of the subsequent Fourier harmonic numbers to the description of the otolith contour is smaller. Combining with Figure 2 it can better illustrate that the first nine Fourier harmonic numbers contribute to the description of the overall contour of the otolith, and the subsequent eleven otoliths describe the tiny parts of the otolith. The amplitudes of the first seven Fourier harmonic numbers of the sagittal otoliths of the three species of porcupinefish are (0.0001 < F < 0.005). Starting from the tenth Fourier harmonic number, the fluctuations of the amplitudes become smaller and smaller, indicating that the contribution rate of the Fourier harmonic numbers becomes less and less. Therefore, this paper uses 20 groups of Fourier harmonic numbers to describe and analyze the sagittal otoliths of the three species of porcupinefish.

[0037] Performing Fourier analysis on the sagittal otoliths of the three species of porcupinefish, through the "Princomp" program in the SHAPE software, the otoliths were reconstructed graphically, and the overlapping reconstructed graphics of the sagittal otoliths of the three species of porcupinefish were obtained, as Figure 4As shown in the figure, it can be seen that the overall shape of *Diodon holocanthus* has not many unevennesses. Based on *Diodon holocanthus*, the outer side of *Diodon liturosus* is relatively more inwardly curved compared to *Diodon holocanthus*, and the outer side of *Diodon hystrix* bulges outward compared to *Diodon holocanthus*. On the inner side, it can be seen that the outline of *Diodon liturosus* is more outward, and the outline of *Diodon holocanthus* is inward. There are obvious unevennesses on the outer sides of the otoliths of the three species of pufferfish, and the otolith outlines on the inner sides are relatively smoother. Therefore, the differences among the three species of pufferfish are reflected in the outer sides of the overall outlines of the sagittal otoliths.

[0038] 2.4 Principal component analysis results of the sagittal otoliths of three species of pufferfish By selecting 20 harmonics through the shape software, 80 groups of Fourier harmonic values are obtained. After the standardization of the Fourier harmonic value coefficients, where A1 = 1, B1 = C1 = 0 are constants that should be removed, the external morphology of each otolith is finally composed of 77 Fourier coefficients. Through data processing and statistics in exce and using the spss software, principal component analysis is performed on the sagittal otoliths of the three species of pufferfish. The results show that the cumulative contribution rate of the first 27 principal component eigenvalues of the otolith parameter values of the three species of pufferfish is 88.039% when greater than 1. Among them, the first 11 principal components explain 52.903% of the external outline of the sagittal otolith, and the first 18 principal components explain 72.321% of the external outline of the sagittal otolith (see Table 2).

[0039] According to the 77 Fourier characteristic coefficient indicators of the sagittal otolith morphology of the three species of pufferfish, factor scatter plots of the first principal component and the second principal component are made, specifically as Figure 5 shown. *Diodon hystrix*, *Diodon liturosus*, *Diodon holocanthus*, as shown by the factor scatter plot of the principal components, the distributions of the sagittal otoliths of the three species of pufferfish are relatively scattered. There is more overlap between *Diodon hystrix* and *Diodon liturosus*, and the distinction is not particularly obvious. There is only a small amount of overlap between *Diodon hystrix* and *Diodon holocanthus*, and the distinction is obvious.

[0040] Table 2 Principal component analysis results of the Fourier analysis method

[0041] 3.2 Discriminant analysis results of the sagittal otoliths of three species of pufferfish Using stepwise discriminant analysis to screen 77 Fourier characteristic coefficients of the sagittal otoliths of three species of pufferfish, finally A9, A13, A16, C2, C9, C15, D3, and D16 were selected. A9, A13, and A16 represent the amplitudes of the fundamental frequencies in the 9th, 13th, and 16th groups of Fourier harmonics respectively, C2, C9, and C15 represent the amplitudes of the second harmonics in the 2nd, 9th, and 15th groups of Fourier harmonics respectively, and D3 and D16 represent the phases of the second harmonics in the 3rd and 16th groups of Fourier harmonics respectively; in Fourier analysis, for a periodic function (here the outline of the otolith can be regarded as an approximation of a periodic shape), it can be decomposed into the sum of a series of sine and cosine functions. Fourier coefficients (here A, B, C, D) are parameters used to describe these sine and cosine functions.

[0042] Generally speaking, in the Fourier descriptors of two-dimensional shapes, A, B, C, and D may represent the amplitude and phase information of different frequency components respectively. For example, A may represent the amplitude of the fundamental frequency, B may be related to the phase of the fundamental frequency, C may be the amplitude of the second harmonic, D may be the phase of the second harmonic, etc. These coefficients can be combined to reconstruct or describe the shape of the otolith outline.

[0043] For the external outline of the otolith, these 4 Fourier harmonics (A, B, C, D) are the basic elements that make up its shape description. They are related to geometric features such as the degree of curvature and concavity-convexity of the otolith outline. Through these coefficients, the general outline of the otolith can be mathematically reconstructed and used to compare the morphological differences between different otoliths.

[0044] Since each group of Fourier coefficients contains 4 values, 80 Fourier coefficients can provide enough information to describe the complex shape of the otolith in detail. And it is considered that 20 Fourier harmonics can describe the external morphology of the otolith because the lower-order Fourier coefficients often contain the main characteristic information of the shape, and this information is sufficient to distinguish the morphological differences between different species or individuals of otoliths.

[0045] 8 Fourier characteristic coefficients for the discriminant equation (see Table 3) Table 3 Coefficients of the canonical discriminant equation for the sagittal otolith traits of three species of pufferfish

[0046] Torquigener pleurogrammus Y 1 =0.359X A9 -0.166X A13 -0.144X A16 +0.251X C2 -0.150XC9 -0.252X C15 -0.342X D3 +0.199X D16 -2.067 Diodon holocanthus Y 2 =0.122X A9 -0.274X A13 +0.204X A16 +0.243X C2 -0.507X C9 +0.132X C15 -0.155X D3 +0.373X D16 -4.251 Diodon liturosus Y 3 =0.379X A9 +0.185X A13 +0.229X A16 -0.198X C2 +0.120X C9 +0.299X C15 +0.474X D3 -0.134X D16 -3.256 In specific applications, when obtaining an otolith randomly, it is also necessary to select and extract a two-dimensional image, convert it to obtain Fourier harmonic values, and use the corresponding interpolation data for discrimination. The discrimination method is to substitute the data of the fish to be discriminated into the formula Y 1 、Y 2 、Y 3 After that, the species of pufferfish corresponding to the equation with the largest value is the species of the fish to be discriminated. For the otolith to be discriminated, extract a two-dimensional image, create Fourier harmonic values in sequence using Fourier transform, and use the A, B, C, and D Fourier shape coefficients (Fourier descriptors) of the corresponding group in the corresponding formula according to the order, and substitute them into the discrimination equation for judgment.

[0047] The discriminant analysis results show that among the 47 sagittal otolith individuals of three species of pufferfish, none of the 19 sagittal otoliths of *Diodon hystrix* were misjudged, and the discrimination success rate was 100%. One of the 8 sagittal otoliths of *Diodon liturosus* was misjudged as *Diodon hystrix*, and the discrimination success rate was 87.5%. Two of the 20 sagittal otoliths of *Arothron hispidus* were misjudged as *Diodon hystrix* and *Diodon liturosus*, and the discrimination success rate was 90.0%. The results obtained through initial discrimination and cross-validation were the same (see Table 4). By performing stepwise discriminant analysis on 77 Fourier eigenvalues, it can be seen from the scatter plot that there is only a small amount of overlap between the three species of pufferfish, and they are clearly separated from each other. From function 1, there is no overlap between *Diodon hystrix* and *Arothron hispidus*. *Diodon hystrix* is mainly between 0 - (-4), *Arothron hispidus* is between 0 - 4, and *Diodon liturosus* is relatively scattered. From function 2, both *Arothron hispidus* and *Diodon hystrix* are between 2 - (-2) with no obvious difference, and *Diodon liturosus* is mainly between 0 - 4, showing an obvious difference compared with the former two, such as Figure 6 shown

[0048] Table 4 Discrimination results of three species of pufferfish

[0049] 3.1 Feasibility analysis of using Fourier analysis method for otolith species identification Otoliths are good materials for species identification research due to their stable morphological structure and are widely used. However, the external characteristics of otoliths of different fish species vary, and there are slight changes in the size and shape of otoliths of different genders or different age groups, which will all cause errors in traditional measurements. Therefore, the elliptical Fourier analysis method is used. The outlines of the sagittal otoliths of three species of pufferfish are depicted through the SHAPE software, and then 80 groups of Fourier harmonic values are obtained through the CHC2ENF program. After screening by the Princomp program, the three groups of harmonic values with A1 = 1, B1 = C1 = 0 are finally removed, and 77 groups of Fourier harmonic values are obtained. The Fourier analysis method is to convert the outline into harmonic values, so that more accurate values can be obtained for discrimination. The values are statistically summarized and compared and analyzed through the SPSS software, and the discrimination results of otoliths, the principal component results, the one-way ANOVA results, etc. can be directly obtained. Using the sagittal otolith outlines of three species of pufferfish for graphic reconstruction, the first 8 harmonics basically describe the general outline of the otolith, and the subsequent harmonics mainly describe the unevenness of the otolith. The 20th harmonic describes the overall outline of the sagittal otolith. The otolith images are collected by a microscope and converted through Fourier analysis. The overall image of the external outline of the otolith morphology is converted into values for discrimination, and then the values are used for graphic reconstruction to test the results, which more accurately and intuitively describes the morphology of the otolith.

[0050] 3.2 Selection of Fourier analysis method and its influence on otolith identification effect In the study of otolith recognition by Fourier analysis method, the contribution rates of the previous harmonics, from 1st to 8th harmonics, are greater than those of the subsequent harmonics. The previous harmonics mainly describe the overall outline of the otolith. As can be seen from the Fourier harmonics and amplitude diagram, the amplitude of the subsequent harmonics is lower. Therefore, the recognition of otoliths by Fourier analysis method mainly depends on the Fourier coefficients of the previous harmonics. In the principal component analysis table, the cumulative contribution rate of the first 8 principal components reaches 41.9%. The contribution rate of the first principal component reaches 6.542% and the eigenvalue reaches 5.037. The contribution rates and eigenvalues of the subsequent principal components become smaller and smaller. The differences among the sagittal otoliths of three species of pufferfish are also reflected in the contribution rates of the previous Fourier harmonics and Fourier coefficients. Fourier analysis method mainly describes the external outline of the otolith. Therefore, in the aspect of otolith contour image acquisition, the overall peripheral contour of the otolith should be collected. Of course, some otoliths are not flat. So, unnecessary information should be avoided in image acquisition to prevent differences in the contour described by Fourier analysis, making it difficult to discriminate.

[0051] 3.3 Application Prospect of Fourier Analysis Method in Otolith Morphology Analysis Discriminant analysis was carried out on the sagittal otoliths of three species of pufferfish using the Fourier analysis method, and the results were ideal. The discriminant success rate of *Diodon hystrix* was 100%, that of *Diodon liturosus* reached 87.5%, and that of *Arothron hispidus* reached 90.0%. Therefore, using the Fourier analysis method to discriminate the sagittal otoliths of three species of pufferfish has very good application prospects. The morphological differences of otoliths vary greatly, and otoliths record the growth cycle of fish. Both the principal component analysis and discriminant analysis using the Fourier coefficients obtained by the Fourier analysis method can provide effective help for the subsequent research on fish classification statistics and evolution. As a new method for studying fish taxonomy in this era, the Fourier analysis method can reconstruct the otolith graph using the external outline of the otolith, enabling a better and clearer view of the overall area of the otolith and the differences between otoliths. By converting the graph into numerical values, the differences of otoliths can be analyzed more precisely. Compared with the traditional morphological measurement method and landmark method, the Fourier analysis method has a broader application prospect in distinguishing otolith differences and identifying different species of fish.

[0052] 3.4 Selection and Comparative Analysis of Otolith Morphology Analysis Methods Discriminant analysis was carried out on the sagittal otoliths of three species of pufferfish using the Fourier analysis method. The results showed that *Diodon hystrix* The discrimination success rates of puffers, Diodon hystrix, and Chilomycterus sexmaculatus are 100%, 87.5%, and 90.0% respectively, and the discrimination effect is good. The sagittal otoliths of three species of pufferfish are selected in this paper. Compared with asteriscus otoliths and lapillus otoliths, the morphological characteristics of sagittal otoliths are more obvious and the outline is clearer. Therefore, the Fourier analysis method is used. In the principal component analysis, the contribution rate of the first 11 eigenvalues reaches about 50%, and the contribution rate of the first 27 eigenvalues in this paper reaches 88.039%. There are relatively few relevant reports on the research of fish otolith morphology. Most scholars will use traditional morphological measurement methods to analyze the morphology of fish otoliths. The traditional morphological measurement method mainly measures the length, width, perimeter, area, etc. of otoliths, and obtains the morphological indexes of otoliths through these parameters and conducts otolith description analysis. Li Huihua et al. compared the recognition effects of traditional morphological measurement method and Fourier method in the interspecies of Coilia nasus and Coilia mystus, as well as the migratory ecological type and freshwater sedentary type of Coilia nasus in 2013, and believed that both methods had good discrimination effects in interspecies discrimination, but in population differentiation, the Fourier method was better. In the geometric morphometric method, there is also the landmark method. The landmark method mainly conducts point analysis on special parts of otoliths. In the selection of landmark points, it is necessary to cover the morphological characteristics of otoliths and avoid selecting too many landmark points, which will cause difficulties in otolith discrimination analysis. Xu Shengyong et al. studied the population of Sebastes schlegelii ( Sebastesschlegelii ), and the research confirmed that the discrimination rate of Fourier otolith analysis method is higher than that of shape index method. Different methods need to be adopted to obtain the most ideal results for different species and different populations. For traditional morphological method, Fourier analysis method, and landmark method, no matter which method is selected, their variables need to be measured, such as the variables of otolith size, the variables of otolith outline, and the selected punctuation variables. For fish otoliths with relatively flat, smooth and less obvious characteristics, the Fourier analysis method can be selected, which can more accurately discriminate different species of fish. For fish otoliths with obvious characteristics and unique features, the landmark method can be selected to obtain better discrimination results. Which method to use depends on the researcher and otolith materials.

[0053] Compared with the prior art, the advantages of the present invention are as follows: (1) The Fourier analysis method of the present invention conducts identification and analysis on the sagittal otoliths of three species of pufferfish, and obtains 77 Fourier harmonic values of the sagittal otoliths of three species of pufferfish. Through principal component analysis, the cumulative contribution rate of the first 27 principal components with eigenvalues > 1 is 88.039%. The contribution rate of the first principal component with the highest contribution rate is 6.542%. From the principal component scatter plot obtained by the first principal component factor and the second principal component factor, the distributions of the sagittal otoliths of three species of pufferfish are relatively scattered. There is more overlap between Diodon hystrix and Diodon holocanthus, and the distinction is not particularly obvious. There is only a small amount of overlap between Diodon hystrix and Chilomycterus sexmaculatus, and the distinction is obvious.

[0054] (2)The discriminant analysis of the sagittal otoliths of three species of pufferfish in the present invention shows that the discrimination success rate of *Diodon hystrix* is 100%, that of *Arothron maculatus* reaches 87.5%, and that of *Arothron hispidus* reaches 90.0%. The average success rate of discriminating the three species of pufferfish in the initial discrimination is 92.5%. In the discriminant scatter plot obtained from the first characteristic value and the second characteristic value, *Arothron hispidus* and *Diodon hystrix* are clearly distinguishable. The discrimination effect between *Arothron maculatus* and *Arothron hispidus*, and *Diodon hystrix* is not particularly good, with a small amount of overlap. This shows that the Fourier analysis method has good discriminability for the identification of fish otoliths.

[0055] (3)The present invention uses the Princomp program to reconstruct the graphics of the Fourier coefficients of three species of pufferfish, and it is found that the lower the Fourier harmonic order, the greater the contribution rate and the more obvious the amplitude. When reaching the 10th harmonic order, the basic contour of the otolith is completely described. As the harmonic order increases, the graphics do not change significantly. Therefore, 20 groups of harmonic orders are selected for analysis in this paper to better describe the integrity of the sagittal otoliths of the three species of pufferfish. The graphic reconstruction enables us to verify the Fourier coefficients obtained by the Fourier analysis method again, that is, whether the Fourier coefficients completely describe the contour of the otolith. Therefore, using the Fourier analysis method can not only accurately obtain the otolith morphological parameter values, but also convert the numerical values into graphics for re-verification, further verifying the accuracy of the Fourier analysis method for the discrimination of fish otoliths.

[0056] The present invention also provides a system for analyzing the otolith morphology of three species of pufferfish based on the Fourier analysis method, including a memory, a control processor, and a computer program stored on the memory and executable on the control processor. The control processor executes the program to implement the aforementioned method for analyzing the otolith morphology of three species of pufferfish based on the Fourier analysis method.

[0057] The present invention also provides a computer-readable storage medium storing computer-executable instructions for causing a computer to implement the aforementioned method for analyzing the otolith morphology of three species of pufferfish based on the Fourier analysis method.

[0058] Although the methods described above are illustrated and described as a series of acts for simplicity of explanation, it should be understood and appreciated that the methods are not limited by the order of the acts, since according to one or more embodiments, some acts may occur in a different order and / or concurrently with other acts not illustrated and described herein or other acts that would be understood by those skilled in the art. Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability of hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and the design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention. The various illustrative logical blocks, modules, and circuits described in connection with the embodiments disclosed herein may be implemented using 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 gates 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 the alternative, the processor may be any conventional processor, battery compartment control board, micro battery compartment control board, or 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 cooperating with a DSP core, or any other such configuration. The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of both. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read from, and write to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal. In one or more exemplary embodiments, the described functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted via a computer readable medium as one or more instructions or code.Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. The storage media can be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable media. For example, if the software is transmitted from a web site, a central control computer, or other remote source using a coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of the medium. As used herein, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and Blu-ray disc, where disk generally reproduces data magnetically, while disc reproduces data optically with a laser. Combinations of the above should also be included within the scope of computer-readable media.

[0059] Although the methods described above have been illustrated and described as a series of acts, it should be understood and appreciated that the methods are not limited by the order of the acts, as some acts may occur in a different order and / or concurrently with other acts from those illustrated and described herein or not illustrated and described herein but understood by those skilled in the art, in accordance with one or more embodiments.

[0060] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention in any form. Although the present invention has been disclosed as above with the preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or variations equivalent to the equivalent embodiments within the scope of the technical solution of the present invention without departing from the technical solution of the present invention. However, any brief modification, equivalent change and modification 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 still fall within the scope of the technical solution of the present invention.

Claims

1. A method for identifying the morphology of three types of pufferfish otoliths based on Fourier analysis, characterized in that: The following steps are involved: Step 1, placing the otolith under a microscope objective to collect images, and obtaining the Fourier harmonic values ​​of the three types of pufferfish otoliths by Fourier transforming the images; Step 2: Use statistical software to perform principal component analysis on the Fourier harmonics of the three pufferfish otoliths. Output the characteristic values ​​describing the otolith outline, contribution rate and cumulative contribution rate, as well as the main component scatter plot; Step 3, use the stepwise discriminant analysis method to perform discriminant analysis on the Fourier harmonics of the three types of pufferfish otoliths, extract the typical discriminant Fourier harmonics of the three types of pufferfish otoliths through SPSS software, obtain the typical discriminant function, and substitute it into the discriminant analysis result.

2. The method for identifying the morphology of three types of pufferfish otoliths based on Fourier analysis according to claim 1, characterized in that: In step 1, the elliptical Fourier analysis method was used to draw the otolith contours of the three types of pufferfish sagitta using the SHAPE software, and then 80 groups of Fourier harmonic values ​​were obtained through the CHC2ENF program. After screening by the Princomp program, the three groups of harmonic values ​​of A1=1 and B1=C1=0 were finally removed, resulting in 77 groups of Fourier harmonic values.

3. The method for identifying the morphology of three types of pufferfish otoliths based on Fourier analysis according to claim 2, characterized in that: Step 1 is specifically to obtain the Fourier harmonic values ​​of the three types of pufferfish otoliths by Fourier transforming the image. The Fourier harmonic values ​​are mainly extracted by using three programs in the "SHAPE" software, namely, "Chaincoder", "Chc2Nef" and "Princomp". The otolith image is inserted into the program, and the overall outline of the outside of the otolith is taken by "Chaincoder", the external morphology of the otolith is described, and the area of ​​each otolith and the 0-7 digital information chain code are obtained and stored in a file in the format of "CHC"; the "Chc2Nef" program is inserted into the "CHC" file to create a file in the format of "NEF". After the "Chc2Nef" program is used, the "CHC" file is generated. "Program analysis, the overall external morphology image of the otolith described by the first program is converted into Fourier harmonic values, and a total of 80 Fourier coefficients are obtained for each otolith, which are stored in the "NEF" file; 20 Fourier harmonics can describe the external morphology of the otolith, and each group of Fourier coefficients consists of 4 Fourier harmonic values ​​A, B, C, and D. The "Princomp" program is used to standardize the obtained Fourier coefficients. After analysis, A1=1, B1=C1=0 are constants that should be removed. Finally, 77 Fourier harmonics are used to describe the entire external contour of the otolith. The "Princomp" program can also reconstruct the otolith to better distinguish different types of otoliths.

4. The method for identifying three types of pufferfish otolith morphology based on Fourier analysis according to claim 2 or 3, characterized in that: In the step 2, 77 Fourier coefficients of the left and right sagittal otoliths of the three porcupine fish are statistically summarized, and the difference between the left and right sagittal otoliths of the three porcupine fish is tested by using the mean difference; The "Princomp" program was used to reconstruct the images of the three porcupine otoliths. The images were converted from 20 groups of harmonics. The Fourier coefficients were reconstructed from the first harmonic to the 20th harmonic, and the overlap analysis of the reconstruction images of the three porcupine otoliths was performed.

5. The method for identifying the morphology of three types of pufferfish otoliths based on Fourier analysis according to claim 4, characterized in that: In step 2, SPSS 19.0 statistical software was used to perform principal component analysis on 77 Fourier harmonics of the three pufferfish otoliths to obtain the characteristic values, contribution rates and cumulative Contribution rate, and scatter plot of main components.

6. The method for identifying the morphology of three types of pufferfish otoliths based on Fourier analysis according to claim 5, characterized in that: In the step 3, the overall contours of the three types of pufferfish otoliths obtained by the SHAPE series software are converted into 77 Fourier coefficients, and stepwise discriminant analysis is performed using spss19.0 to obtain the discriminant scatter plots and discrimination results of the three types of pufferfish otoliths.

7. The method for identifying the morphology of three types of pufferfish otoliths based on Fourier analysis according to claim 6, characterized in that: The 77 Fourier characteristic coefficients of the three pufferfish otoliths were screened by stepwise discriminant analysis, and finally A9, A13, A16, C2, C9, C15, D3, and D16 were selected. A9, A13, and A16 represent the amplitude of the fundamental frequency in the 9th, 13th, and 16th groups of Fourier harmonic values, respectively. C2, C9, and C15 represent the amplitude of the second harmonic in the 2nd, 9th, and 15th groups of Fourier harmonic values, respectively. D3 and D16 represent the phase of the second harmonic in the 3rd and 16th groups of Fourier harmonic values, respectively. The discriminant equations of the eight Fourier characteristic coefficients are as follows: Porcupine pufferfish Y1=0.359X A9 -0.166X A13 -0.144X A16 +0.251X C2 -0.150X C9 -0.252X C15 -0.342X D3 +0.199X D16 -2.067 Big spotted pufferfish Y2=0.122X A9 -0.274X A13 +0.204X A16 +0.243X C2 -0.507X C9 +0.132X C15 -0.155X D3 +0.373X D16 -4.251 Six-spot pufferfish <h2 style=";text-align:left;direction:ltr">Y3=0.379X<h2 style=";text-align:left;direction:ltr"> A9 <h2 style=";text-align:left;direction:ltr"> +0.185X<h2 style=";text-align:left;direction:ltr"> A13 <h2 style=";text-align:left;direction:ltr"> +0.229X<h2 style=";text-align:left;direction:ltr"> A16 <h2 style=";text-align:left;direction:ltr"> -0.198X<h2 style=";text-align:left;direction:ltr"> C2 <h2 style=";text-align:left;direction:ltr"> +0.120X<h2 style=";text-align:left;direction:ltr"> C9 <h2 style=";text-align:left;direction:ltr"> +0.299X<h2 style=";text-align:left;direction:ltr"> C15 <h2 style=";text-align:left;direction:ltr"> +0.474X<h2 style=";text-align:left;direction:ltr"> D3 <h2 style=";text-align:left;direction:ltr"> -0.134X<h2 style=";text-align:left;direction:ltr"> D16 <h2 style=";text-align:left;direction:ltr"> -3.256; 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.

8. A device for analyzing the morphology of three types of pufferfish otoliths based on Fourier analysis, 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 identifying three types of pufferfish otolith morphologies based on Fourier analysis as described in any one of claims 1 to 7.

9. A system, characterized in that: It includes the device for analyzing the morphology of otoliths of three species of pufferfish based on Fourier analysis as described in claim 8.

10. 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 identifying three types of pufferfish otolith morphologies based on Fourier analysis as described in any one of claims 1 to 7.

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