Method and system for evaluating body shape of grass carp

Abstract

The application provides a body shape trait evaluation method and system of Procypridium, and relates to the technical field of body shape evaluation; the method comprises the following steps: selecting a plurality of Procypridium that reach a preset weight, implanting PIT chips of different numbers into the bodies of the plurality of Procypridium for individual marking, and continuing to breed the Procypridium according to preset breeding conditions for a set number of days; photographing the plurality of Procypridium that reach the number of breeding days to obtain a plurality of Procypridium images; performing contour processing on the plurality of Procypridium images to obtain a plurality of body shape trait outer contours; performing difference calculation on the plurality of body shape trait outer contours through a Procrustes analysis algorithm to obtain a plurality of Procrustes distances, and converting the plurality of Procrustes distances into indexes for evaluating the body shape of the Procypridium. The body shape trait evaluation of the Procypridium is freed from subjective judgment based on naked eye observation, and scientific evaluation and accurate screening based on quantitative genetics are realized in the breeding process.

Description

TECHNICAL FIELD

[0001] The present application mainly relates to the technical field of body shape evaluation, and particularly relates to a body shape evaluation method and system for Procyprinus. BACKGROUND

[0002] Procyprinus is an artificially bred variety, commonly known as black carp or Procyprinus, and is named after eating rice field Procyprinus. It has a long history and outstanding quality and flavor. Compared with other carp breeding populations, the characteristics of Procyprinus are unique, which are manifested as a round abdomen, an upward arc between the head and back, and a raised back. In the place of origin, whether the body shape meets the above characteristics directly determines the sales price of Procyprinus, and therefore the body shape is also an important economic trait of Procyprinus.

[0003] In the development process of Procyprinus breeding industry, with the development of artificial selection and hybrid improvement aiming at improving growth rate, and the inflow and mixture of external carp germplasm resources, the body shape of the original breeding population has degenerated, and the typical Procyprinus individuals in the breeding population have gradually decreased, which affects the breeding benefit.

[0004] Therefore, it is of great significance to carry out Procyprinus body shape selection and restore the typical characteristics of "round abdomen, upward arc between head and back, and raised back". At present, there are few studies on fish body shape selection and improvement, and there is a lack of evaluation method and parameters for Procyprinus body shape traits. In the process of parent selection, the selection of individuals meeting the requirements is only based on visual observation and subjective judgment, and cannot be statistically and genetically evaluated. SUMMARY

[0005] The present application mainly relates to the technical field of body shape evaluation, and particularly relates to a body shape evaluation method and system for Procyprinus.

[0006] The technical solution of the present application to solve the above technical problems is as follows:

[0007] A body shape evaluation method for Procyprinus, comprising the following steps:

[0008] A plurality of Procyprinus reaching a preset weight are selected, PIT chips of different numbers are implanted into the bodies of the plurality of Procyprinus for individual marking, and the plurality of Procyprinus are further bred under preset breeding conditions for a set number of days;

[0009] The plurality of Procyprinus reaching the number of breeding days are photographed to obtain a plurality of Procyprinus images;

[0010] The plurality of Procyprinus images are subjected to contour processing to obtain a plurality of body shape external contours;

[0011] The plurality of Procrustes distances are converted into indexes for evaluating the body shape of the grass carp.

[0012] Another technical solution of the present application to solve the above technical problems is as follows:

[0013] A body shape trait evaluation system for grass carp, comprising:

[0014] The marking module is configured to select a plurality of grass carps that reach a preset weight, implant PIT chips of different numbers into the plurality of grass carps to mark the individuals, and continue to breed the plurality of grass carps under preset breeding conditions for a set number of days.

[0015] The collection module is configured to take photos of the plurality of grass carps that reach the number of breeding days to obtain a plurality of grass carp images.

[0016] The processing module is configured to perform contour processing on the plurality of grass carp images to obtain a plurality of body shape trait contours.

[0017] The analysis module is configured to perform difference calculation on the plurality of body shape trait contours by using a Procrustes analysis algorithm to obtain a plurality of Procrustes distances, and convert the plurality of Procrustes distances into indexes for evaluating the body shape of the grass carp.

[0018] The present application has the following beneficial effects: the body shape trait contour is quantified by using the principle of graphic similarity, the problems of lack of evaluation parameters and evaluation indexes are solved, the body shape trait contour is analyzed for difference to breed the grass carp, the evaluation of the body shape trait of the grass carp is freed from subjective judgment based on naked eye observation, and scientific evaluation and accurate screening based on quantitative genetics are realized in the breeding process. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 A flowchart of the body shape trait evaluation method for grass carp provided by the embodiment of the present application is shown.

[0020] Figure 2 A body shape trait contour graph for grass carp provided by the embodiment of the present application is shown.

[0021] Figure 3 A module block diagram of the body shape trait evaluation system for grass carp provided by the embodiment of the present application is shown. DETAILED DESCRIPTION

[0022] The principles and features of the present application are described below in combination with the drawings, and the examples are only used to explain the present application and not to limit the scope of the present application.

[0023] As shown in Figure 1 A body shape trait evaluation method for grass carp (taking the wholezhou grass carp as an example) provided by the embodiment of the present application includes the following steps:

[0024] Selecting a plurality of Procypris merus reaching a preset weight, implanting PIT chips of different numbers into the plurality of Procypris merus to mark individuals, and continuing to breed under preset breeding conditions to a set number of days;

[0025] Taking photos of the plurality of Procypris merus reaching the number of days of breeding to obtain a plurality of Procypris merus images;

[0026] Performing contour processing on the plurality of Procypris merus images to obtain a plurality of body shape contours;

[0027] Performing difference calculation on the plurality of body shape contours by Procrustes analysis algorithm to obtain a plurality of Procrustes distances, and converting the plurality of Procrustes distances into an index for evaluating the body shape of Procypris merus.

[0028] It should be understood that the preset weight can be set to more than 10 grams. The PIT chip adopts a 1.25*7 mm PIT fish chip. The preset breeding condition is to keep the breeding density at 2-4 tails / m 2 , and the pond water depth is 1.5 m. The set number of days for continuing breeding can be set to 120-150 days of age.

[0029] In the embodiment of the application, the body shape contour of Procypris merus is analyzed for difference by using the principle of graphic similarity, and then the difference parameter of the shape contour is converted into an index that can reflect the advantages and disadvantages of the body shape of Procypris merus, so that the evaluation of the body shape of Procypris merus is free from subjective judgment based on naked eye observation, and scientific statistics and accurate evaluation based on quantitative genetics are realized.

[0030] Preferably, the plurality of Procypris merus reaching the number of days of breeding are taken photos to obtain a plurality of Procypris merus images, specifically as follows:

[0031] The plurality of Procypris merus reaching the number of days of breeding are put into anesthetics for anesthesia, and the lateral sides of the plurality of anesthetized Procypris merus are taken photos vertically by a camera to obtain a plurality of Procypris merus images.

[0032] Specifically, the Procypris merus to be measured (the plurality of Procypris merus reaching the number of days of breeding) are put into an MS-222 anesthetic with a mass concentration of 100 mg·L -1 , taken out after the Procypris merus loses balance, placed flat on a pure color background disk, and the Procypris merus body is kept in a natural stretching state (without distortion), and the lateral side of the Procypris merus is taken photos by a digital camera, and the lens direction is kept vertical to the disk plane during the photographing.

[0033] It should be understood that the MS-222 anesthetic (fish tranquilizer) is ethyl 3-amino-4-methylbenzoate methane sulfonate salt, which is the most commonly used, safest and most reliable fish anesthetic at present.

[0034] In the embodiment of the present application, by collecting the morphological images of the natural state of the Ctenopharyngodon idella, intuitive and consistent body shape traits of the Ctenopharyngodon idella are obtained, which is more conducive to converting the contour consistent with the Ctenopharyngodon idella.

[0035] Preferably, after obtaining a plurality of Ctenopharyngodon idella images, the following steps are further performed:

[0036] The corresponding PIT chip of the Ctenopharyngodon idella is scanned by the PIT chip scanner, and the corresponding Ctenopharyngodon idella is numbered by the number in the PIT chip obtained by scanning.

[0037] In the embodiment of the present application, the collected images are one-to-one corresponding to the PIT chips in the Ctenopharyngodon idella, which avoids errors when selecting Ctenopharyngodon idella that meets the standard.

[0038] Preferably, as shown in the embodiment of the present application, the plurality of Ctenopharyngodon idella images are processed to obtain a plurality of body shape contours, specifically: Figure 2

[0039] The plurality of Ctenopharyngodon idella images are binarized to obtain a plurality of pixel point coordinates corresponding to a plurality of Ctenopharyngodon idella binary images.

[0040] A plurality of contour markers are selected from the plurality of pixel point coordinates corresponding to the plurality of Ctenopharyngodon idella binary images at the same preset interval, and a plurality of body shape contours each composed of a plurality of contour markers are obtained.

[0041] It should be understood that a binary image is an image whose each pixel point has only two possible values, either black or white. Binarization is a process of converting an image into a binary image, which usually sets a threshold value. When the value of a pixel in the original image is greater than the threshold value, the pixel is changed to white (color component is 255), and when the value of a pixel in the original image is less than the threshold value, the pixel is changed to black (color component is 0). After each pixel point in the original image is traversed in this way, a binary image is formed. The binary image is converted into a two-dimensional pixel matrix, where the first dimension represents the X coordinate of the image, and the second dimension represents the Y coordinate of the image.

[0042] In the embodiment of the present application, the image is binarized to obtain the pixel point coordinates corresponding to the traits of the Ctenopharyngodon idella, which is convenient for selecting the contour coordinates.

[0043] Preferably, the plurality of contour markers are selected from the plurality of pixel point coordinates corresponding to the plurality of Ctenopharyngodon idella binary images at the same preset interval, specifically:

[0044] ​According to the same preset interval, starting from the pixel point coordinates of the lower edge of the operculum of the head of the Megalobrama terminalis in the plurality of Megalobrama terminalis binarization images, extending along the outer contour of the trunk part to the pixel point coordinates of the upper edge of the operculum of the head, a preset number of contour markers are selected;Or,

[0045] According to the same preset interval, starting from the pixel point coordinates of the upper edge of the operculum of the head of the Megalobrama terminalis in the plurality of Megalobrama terminalis binarization images, extending along the outer contour of the trunk part to the pixel point coordinates of the lower edge of the operculum of the head, a preset number of contour markers are selected;Wherein, the pixel points of the Megalobrama terminalis fin strip are not included.

[0046] Specifically, the contour is drawn by tpsdig tool, 30-50 points are selected as markers on the outer contour line of the trunk part of the Megalobrama terminalis, which are evenly arranged (that is, the distance between adjacent markers is equal according to the same preset interval), the coordinate values representing the shape of the outer contour of the trunk part are obtained, and the markers start from the lower edge of the operculum of the fish body (that is, the junction of the head and the trunk part) and extend along the outer contour of the trunk part (wherein, the fin strip is not included) to the upper edge of the operculum (that is, the junction of the head and the trunk part).

[0047] In the embodiment of the application, 50 points are evenly arranged as markers on the outer contour line of the trunk part of the Megalobrama terminalis, and the coordinates of the 50 markers of one Megalobrama terminalis can be represented as (721.00000, 921.00000), (836.00000, 881.00000), (950.00000, 841.00000), (1065.00000, 801.00000), …, (671.00000, 1645.00000). All marker coordinates are converted into cvs data, and the cvs data of the 50 marker coordinates of one Megalobrama terminalis can be represented as (721, 921), (836, 881), (950, 841), (1065, 801), …, (671, 1645).

[0048] In the embodiment of the application, the markers are evenly taken on the outer contour in the Megalobrama terminalis image, which facilitates comparison of each contour part with the standard value when calculating the difference, and more accurate analysis of the difference.

[0049] Preferably, the plurality of body shape traits are calculated by the Procrustes analysis algorithm, and a plurality of Procrustes distances are obtained, and the plurality of Procrustes distances are converted into an index for evaluating the body shape of the Megalobrama terminalis, specifically:

[0050] The coordinates of the marker points corresponding to the outer contours of the body shape traits are normalized by the Protodyakonov analysis algorithm. The difference between the standard individual contours selected from the outer contours of the body shape traits obtained by the multiple normalization processes and the outer contours of the body shape traits obtained by the other normalization processes is calculated to obtain multiple Protodyakonov distances.

[0051] By performing deviation standardization calculations on multiple Protodyako distances, multiple corresponding indicators for evaluating the body size of the rice flower carp are obtained.

[0052] To be understood, Procrustes analysis is an algorithm that compares the consistency of two sets of data by analyzing shape distribution. Mathematically, it iterates continuously to find a canonical shape and uses the least squares method to find the affine transformation of each object's shape to this canonical shape. It is based on matching corresponding points (coordinates) in two datasets, translating, rotating, and scaling the coordinates of points in one dataset to match the coordinates of corresponding points in the other dataset. Furthermore, during the translation, rotation, and scaling, the same operation is performed on all sample points; therefore, although the position of the points changes, the projected (affine transformation) shape of the dataset remains unchanged.

[0053] Specifically, the normalization process is as follows:

[0054] 1) A sample set Ω = {X1, X2, ..., X...} is formed by the coordinates of the marker points corresponding to the outer contours of multiple body shape traits. N}, and a standard individual profile pre-selected from the multiple outer contours of the described body shape characteristics;

[0055] 2) Find the mean of sample point i (i = 1, 2, ..., n) of each sample in the sample set across N images;

[0056] 3) Subtract the mean from each sample point in the sample set to obtain multiple decentralized data points;

[0057] 4) Calculate the centroid of the corresponding image based on multiple decentralized data sets, and obtain the centroid coordinates for each image. The centroid coordinates are represented as follows:

[0058]

[0059] Where N represents the outer contour of multiple body shape traits, x ji The x-coordinate of the i-th marker point in the outer contour of the j-th individual body type trait is represented by y. ji The ordinate represents the ordinate of the i-th marker point in the outer contour of the j-th individual's physical characteristics;

[0060] 5) Calculate each body shape trait outline (sample shape) and standard body shape outline (standard shape) by least square method based on multiple barycentric coordinates to obtain rotation change parameters of sample shape to standard shape;

[0061] 6) Rotate sample shape according to rotation change parameters to obtain new shape coordinates aligned with standard shape, thereby forming normalized body shape trait outline.

[0062] It should be understood that the body shape outline is quantified by using the principle of graphic similarity, and the problem of lacking evaluation parameters is solved. Similarity refers to the complete similarity of the shapes of two graphics. If there are two sets of points, one graphic can be changed into another graphic by means of enlargement, reduction, translation or rotation.

[0063] In the embodiment of the present application, the normalized shape indexes of the 47 full-state grass carp can be represented as 0.793201728, 0.191005747, 0.244760965, 0.743426133, …, 0.743911936 respectively.

[0064] Specifically, the standard body shape outline (normalized standard shape) and the body shape trait outline (normalized sample shape) obtained by the normalization process are calculated for difference, and multiple Procrustes distances are obtained. The calculation expression of the Procrustes distance is:

[0065]

[0066] Wherein, P d represents the Procrustes distance, x i1 represents the horizontal coordinate of the i-th mark point of the normalized sample shape, x i2 represents the horizontal coordinate of the i-th mark point of the normalized standard shape, y i1 represents the vertical coordinate of the i-th mark point of the normalized sample shape, y i2 represents the vertical coordinate of the i-th mark point of the normalized standard shape, and the multiple Procrustes distances can be represented as 0.031524406, 0.007591187, 0.009727594, 0.029546163, …, 0.02956547 respectively.

[0067] It should be understood that the difference between two individual shapes is usually measured by the square of the Procrustes distance. The larger the Procrustes distance, the greater the difference from the standard body shape.

[0068] Specifically, the multiple Procrustes distances are calculated by deviation standardization to obtain multiple body shape indexes corresponding to the full-state grass carp, and the deviation standardization calculation expression is:

[0069]

[0070] wherein, X' i represents the i-th body shape index, X i represents the i-th Procrustes distance, min represents the minimum value of the plurality of Procrustes distances, and max represents the maximum value of the plurality of Procrustes distances.

[0071] It should be understood that the Procrustes distance is subjected to Min-max normalization conversion to 0-1 data, that is, the body shape index is obtained; if the body shape is more standard, the parameter is closer to 1, if the body shape is less standard, the parameter is closer to 0, and the greater the value after Min-max normalization conversion, the smaller the difference between the individual and the standard body shape (that is, the better the body shape parameter is greater).

[0072] In the embodiment of the present application, by performing Procrustes analysis on the evaluation parameters (contour landmark point coordinates), an evaluation index that can evaluate the body shape difference is obtained, which can be used to carry out genetic evaluation analysis of the morphological traits of the grass carp in the whole province, such as the calculation of parameters such as body shape heritability and genetic progress.

[0073] As shown in the method for evaluating the body shape traits of the grass carp according to the embodiment of the present application, the method comprises the steps of: Figure 3 As shown in the system for evaluating the body shape traits of the grass carp according to the embodiment of the present application, the system comprises:

[0074] The marking module is configured to select a plurality of grass carps that reach a preset weight, implant PIT chips with different numbers into the plurality of grass carps to mark the individuals, and continue to breed the plurality of grass carps under preset breeding conditions for a set number of days.

[0075] The collecting module is configured to take photos of the plurality of grass carps that reach the number of breeding days to obtain a plurality of images of the grass carps.

[0076] The processing module is configured to perform contour processing on the plurality of images of the grass carps to obtain a plurality of body shape trait outer contours.

[0077] The analysis module is configured to perform difference calculation on the plurality of body shape trait outer contours by using a Procrustes analysis algorithm to obtain a plurality of Procrustes distances, and convert the plurality of Procrustes distances into indexes for evaluating the body shape of the grass carp.

[0078] The system for evaluating the body shape traits of the grass carp described above can refer to the specific description of the method for evaluating the body shape traits of the grass carp and the beneficial effects thereof, which will not be described here again.

[0079] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0081] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for evaluating the body shape of Megalobrama amblycephala, characterized in that, The method comprises the following steps: selecting a plurality of grass carp reaching a preset weight, implanting PIT chips of different numbers into the plurality of grass carp for individual marking, and continuing to breed under preset breeding conditions for a set number of days; photographing the plurality of grass carp reaching the number of breeding days to obtain a plurality of grass carp images; contour processing the plurality of grass carp images to obtain a plurality of body shape contours, specifically: performing binaryzation processing on the plurality of grass carp images to obtain a plurality of pixel point coordinates corresponding to the plurality of grass carp binaryzation images; selecting a preset number of contour marker points from the plurality of pixel point coordinates corresponding to the plurality of grass carp binaryzation images at the same preset interval to obtain a plurality of body shape contours each composed of a plurality of contour marker points; performing difference calculation on the plurality of body shape contours by Procrustes analysis algorithm to obtain a plurality of Procrustes distances, and converting the plurality of Procrustes distances into indexes for evaluating the body shape of the grass carp, specifically: performing normalization processing on the marker point coordinates corresponding to the plurality of body shape contours by Procrustes analysis algorithm, and performing difference calculation on a standard individual contour selected in advance from the plurality of body shape contours obtained by the normalization processing and other body shape contours obtained by the normalization processing to obtain a plurality of Procrustes distances, and the calculation expression of the Procrustes distance is: ， in, Represents the Pythagorean distance. The first normalized sample shape represents the shape of the sample. The x-coordinates of the marker points The first normalized standard shape The x-coordinates of the marker points The first normalized sample shape represents the shape of the sample. The ordinates of the marker points The first normalized standard shape The ordinate of each marker point, where N represents the number of samples; performing dispersion standardization calculation on the plurality of Procrustes distances to obtain a plurality of corresponding indexes for evaluating the body shape of the grass carp.

2. The method of claim 1, wherein the body shape of the grass carp is evaluated by the following formula: 1.0 < (L / SL) < 1.5, wherein L is the length of the fish, and SL is the standard length of the fish. The photographing the plurality of grass carp reaching the number of breeding days to obtain a plurality of grass carp images, specifically: putting the plurality of grass carp reaching the number of breeding days into anesthetics for anesthesia, and photographing the lateral sides of the plurality of anesthetized grass carp vertically by a camera to obtain a plurality of grass carp images.

3. The method of claim 1, wherein the body shape of the grass carp is evaluated by the following formula: 0.5 x (body length) + 0.3 x (body height) + 0.2 x (body depth) = 1. After the plurality of grass carp images are obtained, the following step is further performed: scanning the PIT chip corresponding to the grass carp by a PIT chip scanner, and naming the corresponding grass carp by the number in the PIT chip obtained by the scanning.

4. The method of claim 1, wherein the body shape of the grass carp is evaluated by the following formula: 0.5 x (body length) + 0.3 x (body height) + 0.2 x (body depth) = 1. The selecting a preset number of contour marker points from the plurality of pixel point coordinates corresponding to the plurality of grass carp binaryzation images at the same preset interval, specifically: starting from the pixel point coordinates of the lower edge of the gill cover of the head of the grass carp in the plurality of grass carp binaryzation images, extending along the contour of the trunk part to the pixel point coordinates of the upper edge of the gill cover of the head, and selecting a preset number of contour marker points at the same preset interval; or, starting from the pixel point coordinates of the upper edge of the gill cover of the head of the grass carp in the plurality of grass carp binaryzation images, extending along the contour of the trunk part to the pixel point coordinates of the lower edge of the gill cover of the head, and selecting a preset number of contour marker points at the same preset interval; wherein, the pixel points of the fin strips of the grass carp are not included.

5. A system for evaluating the size traits of grass carp, for implementing the steps of the method according to any one of claims 1 to 4, characterized in that, It comprises: a marking module for selecting a plurality of grass carp reaching a preset weight, implanting PIT chips of different numbers into the plurality of grass carp for individual marking, and continuing to breed under preset breeding conditions for a set number of days; a collection module for photographing the plurality of grass carp reaching the number of breeding days to obtain a plurality of grass carp images; The processing module is configured to perform contour processing on the plurality of images of the Procypridium, to obtain a plurality of body shape outlines, specifically: The plurality of images of the Procypridium are binarized to obtain a plurality of pixel point coordinates corresponding to a plurality of binary images of the Procypridium; A preset number of outline marker points are selected from the plurality of pixel point coordinates corresponding to the plurality of binary images of the Procypridium at the same preset interval, to obtain the plurality of body shape outlines each composed of the plurality of outline marker points; The analysis module is configured to perform difference calculation on the plurality of body shape outlines by using a Procrustes analysis algorithm, to obtain a plurality of Procrustes distances, and to convert the plurality of Procrustes distances into indexes for evaluating the body shape of the Procypridium, specifically: The marker point coordinates corresponding to the plurality of body shape outlines are normalized by using the Procrustes analysis algorithm, and a standard individual outline selected from the plurality of normalized body shape outlines is subjected to difference calculation with other normalized body shape outlines, to obtain the plurality of Procrustes distances, and a calculation expression of the Procrustes distance is: ， wherein, denotes the Mahalanobis distance, denotes the horizontal coordinate of the i-th landmark point of the normalized sample shape, denotes the horizontal coordinate of the i-th landmark point of the normalized standard shape, denotes the horizontal coordinate of the i-th landmark point of the normalized sample shape, denotes the horizontal coordinate of the i-th landmark point of the normalized standard shape, denotes the vertical coordinate of the i-th landmark point of the normalized sample shape, denotes the vertical coordinate of the i-th landmark point of the normalized standard shape, denotes the vertical coordinate of the i-th landmark point of the normalized sample shape, denotes the vertical coordinate of the i-th landmark point of the normalized standard shape, and N denotes the number of samples. The plurality of Procrustes distances are subjected to dispersion standardization calculation, to obtain a plurality of corresponding indexes for evaluating the body shape of the Procypridium.

6. The Oncomelania hupensis body shape trait evaluation system according to claim 5, characterized in that, The collection module is specifically configured to: The plurality of Procypridium reaching the number of days of cultivation are narcotized in a narcotic agent, and the lateral sides of the plurality of narcotized Procypridium are vertically photographed by using a camera, to obtain a plurality of images of the Procypridium.

Images