Method and device for identifying geographic populations of large yellow croaker by combining otolith and morphometric measurements

Abstract

The present application relates to a method for identifying geographical populations of large yellow croaker by combining otolith and morphological measurement, obtaining a large yellow croaker sample to be identified; obtaining morphological measurement data; performing first standardization processing on the morphological measurement data to obtain standardized morphological measurement data, and inputting the standardized morphological measurement data into a pre-established morphological identification model to output a first identification result through the morphological identification model; obtaining a sagitta of the large yellow croaker sample to be identified; obtaining landmark distance measurement data based on pre-set otolith landmarks through the sagitta; performing second standardization processing on the landmark distance measurement data to obtain standardized landmark distance measurement data, inputting the standardized landmark distance measurement data into a pre-established otolith identification model, and outputting a second identification result through the otolith identification model; and performing final identification based on the first identification result and the second identification result. The present application can accurately, simply and in batches identify three geographical populations of the Pseudosciaena crocea hoi, the Pseudosciaena crocea minyuanensis and the Pseudosciaena crocea daiqua.

Description

Technical Field

[0001] This invention relates to the technical field of morphological feature identification, and in particular to a method and apparatus for identifying geographical populations of large yellow croaker by combining otolith and morphological measurements. Background Technology

[0002] Large yellow croaker Larimichthys crocea The large yellow croaker (Croton tigrinosa) belongs to the class Actinopterygii, order Perciformes, and family Sciaenidae. It is a warm-temperate, schooling, migratory fish found in the Northwest Pacific Ocean, including my country. Based on distribution, it can be divided into three geographical groups: the Daiqu group, the Min-Yue Dong group, and the Naozhou group. Differences in growth environment significantly affect the quality of the large yellow croaker, leading to price differences among different geographical groups. However, the market suffers from the phenomenon of low-quality products being passed off as high-quality products, which not only misleads consumers but may also damage the economic value of regional brands. Scientific and simple identification of large yellow croaker populations is crucial for resource conservation and maintaining market order.

[0003] Currently, methods for distinguishing different geographical populations of large yellow croaker include those based on molecular markers, otolith isotopes, and muscle fatty acid content. These methods are mainly used to differentiate between the Daqu and Min-Yue large yellow croaker, or to distinguish between wild and farmed large yellow croaker populations. However, methods for simultaneously identifying three geographical populations of large yellow croaker are lacking. A Chinese patent, titled "Identification Primers and Methods for Different Populations of Large Yellow Croaker" (Patent No.: CN200610135259.2), uses RAPD-PCR technology to identify various populations of large yellow croaker from the Daqu, Min-Yue, Naozhou, and farmed groups. However, this technology requires specialized experimental equipment and technicians, and its limitations, such as high identification costs and complex operation, are significant. Summary of the Invention

[0004] The purpose of this invention is to at least address one of the shortcomings of the prior art by providing a method for identifying geographical populations of large yellow croaker by combining otolith and morphological measurements.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] Specifically, a method for identifying geographical populations of large yellow croaker by combining otolith and morphological measurements is proposed, the method including:

[0007] Obtain samples of large yellow croaker to be identified;

[0008] Obtain morphological measurement data of the large yellow croaker sample to be identified;

[0009] The morphological measurement data is subjected to first standardization processing to obtain standardized morphological measurement data, the standardized morphological measurement data is input into a pre-established morphological discrimination model, and a first discrimination result is output by the morphological discrimination model;

[0010] An otolith of the large yellow croaker to be identified is acquired;

[0011] Otolith landmark distance measurement data is acquired based on preset otolith landmarks through the otolith;

[0012] The otolith landmark distance measurement data is subjected to second standardization processing to obtain standardized otolith landmark distance measurement data, the standardized otolith landmark distance measurement data is input into a pre-established otolith discrimination model, and a second discrimination result is output by the otolith discrimination model;

[0013] The first discrimination result and the second discrimination result are compared, if the first discrimination result and the second discrimination result both show that the large yellow croaker to be identified is of the same geographical population, the large yellow croaker to be identified is determined as the geographical population; wherein the geographical population includes the Naozhou population, the Minyue East population and the Daibu population.

[0014] Further, specifically, the morphological measurement data includes,

[0015] body length SL, distance from snout to dorsal fin starting point Sn-DO, distance from snout to ventral fin starting point Sn-P2O, distance from snout to anal fin starting point Sn-A2O, distance from dorsal fin starting point to ventral fin starting point DO-P2O, distance from dorsal fin starting point to anal fin starting point DO-A2O, body height MBD, half body height at pectoral fin starting point P1-D2I, dorsal fin length HDL, anal fin length HAL, dorsal fin base length LDB, pectoral fin length P1L, pectoral fin base length LPB, ventral fin length P2L, anal fin base length LAB, caudal peduncle length CPL, caudal peduncle height CPD, head length HL, postocular head length PoHL, eye diameter ED, snout length SnL, upper jaw length UjL.

[0016] Further, specifically, the process of the first standardization processing includes,

[0017] The postocular head length PoHL, the eye diameter ED, the snout length SnL and the upper jaw length UjL in the morphological measurement data are divided by the head length HL, and other measurement data are divided by the body length SL for standardization.

[0018] Further, specifically, the process of establishing the morphological discrimination model includes,

[0019] The standardized morphological measurement data is screened by Wilk-Lambda method, and F a Wilk-Lambda value is taken as a reference, when FWhen the value is greater than 3.84, the corresponding variable is introduced into the model. F Values ​​less than 2.71 were removed, and variables were gradually introduced to ultimately select 10 standardized morphological measurement data: distance from snout to dorsal fin origin / body length X1, distance from snout to anal fin origin / body length X2, body height / body length X3, half-body height at pectoral fin origin / body length X4, caudal peduncle length / body length X5, caudal peduncle height / body length X6, eye diameter / head length X7, dorsal fin length / body length X8, dorsal fin base length / body length X9, and pectoral fin base length / body length X10.

[0020] Next, a morphological discrimination equation is established, where;

[0021] The morphological discrimination function equation for the large yellow croaker of the Naozhou group is as follows:

[0022] F1=-69.842*X1+322.809*X2-1.398*X3+287.120*X4+80.532*X5-306.768*X6+360.181*X7-24.200*X8+47.691*X9+659.578*X10-159.152;

[0023] The morphological discrimination function equation for the large yellow croaker from the eastern Fujian and Guangdong ethnic groups is as follows:

[0024] F2=-212.860*X1+397.793*X2+64.821*X3+297.914*X4+122.172*X5-38 6.188*X6+342.377*X7-124.805*X8+64.601*X9+648.179*X10-175.501;

[0025] The morphological discrimination function equation for the large yellow croaker of the Daiqu group is as follows:

[0026] F3=22.471*X1+313.538*X2-82.082*X3+336.028*X4+114.826*X5-499.833*X6+391.159*X7-90.840*X8+57.577*X9+534.901*X10-165.030;

[0027] The values ​​of F1, F2 and F3 are calculated based on the standardized morphological measurement data. The population to which the morphological discriminant function equation of the maximum value of F1, F2 and F3 belongs is taken as the population of the large yellow croaker sample to be identified in the large yellow croaker population, and recorded as the first discrimination result for output.

[0028] Furthermore, specifically, the preset otolith landmarks include,

[0029] Otolith posterior end vertex 1, Otolith back rear concave point 2, Otolith back rear convex point 3, Otolith back front convex point 4, Otolith anterior end vertex 5, Otolith ventral front convex point 6, Otolith ventral rear concave point 7, Otolith auditory canal rear end point 8, Otolith auditory canal rear and middle upper intersection point 9, Otolith auditory canal front and middle upper intersection point 10, Otolith auditory canal front upper end point 11, Otolith auditory canal front and middle lower intersection point 12, Otolith auditory canal rear and middle lower intersection point 13.

[0030] Further, specifically, the landmark point distance measurement data includes,

[0031] Otolith posterior end vertex to otolith auditory canal rear end point distance (1-8), Otolith back front convex point to otolith ventral front convex point distance (4-6), Otolith auditory canal rear and middle upper intersection point to otolith auditory canal front and middle upper intersection point distance (9-10), Otolith auditory canal front and middle upper intersection point to otolith auditory canal front upper end point distance (10-11), Otolith auditory canal front and middle lower intersection point to otolith auditory canal rear and middle lower intersection point distance (12-13), Otolith back rear concave point to otolith back front convex point distance (2-4), Otolith back rear concave point to otolith anterior end vertex distance (2-5), Otolith back rear convex point to otolith auditory canal rear end point distance (3-8), Otolith back front convex point to otolith anterior end vertex distance (4-5), Otolith back front convex point to otolith ventral rear concave point distance (4-7), Otolith anterior end vertex to otolith ventral rear concave point distance (5-7), Otolith ventral front convex point to otolith ventral rear concave point distance (6-7).

[0032] Further, specifically, the process of the second standardization includes,

[0033] Standardizing the landmark point distance measurement data by dividing by body length respectively.

[0034] Further, specifically, the process of establishing the otolith discrimination model includes,

[0035] Filtering the standardized landmark point distance measurement data by Wilk-Lambda method, taking F distribution value as a reference, when F value is greater than 3.84, introducing the corresponding variable into the model, when F value is less than 2.71, removing the corresponding variable, gradually introducing the variable, and finally screening out four standardized landmark point distance measurement data: Otolith posterior end vertex to otolith auditory canal rear end point distance (1-8) / body length Y1, Otolith back front convex point to otolith ventral front convex point distance (4-6) / body length Y2, Otolith auditory canal front and middle upper intersection point to otolith auditory canal front upper end point distance (10-11) / body length Y3, Otolith ventral front convex point to otolith ventral rear concave point distance (6-7) / body length Y4,

[0036] Then, a discriminant function equation is established, wherein:

[0037] The otolith discriminant function equation of the Naozhou group of Pseudosciaena crocea is as follows:

[0038] G1=-6.489*Y1+141.445*Y2-22.251*Y3-17.939*Y4-186.686;

[0039] The otolith discriminant function equation of the Minyue east group of Pseudosciaena crocea is as follows:

[0040] G2=-6.268*Y1+116.929*Y2-22.289*Y3-13.631*Y4-126.44;

[0041] The otolith discriminant function equation of the Daiqu group of Pseudosciaena crocea is as follows:

[0042] G3=-8.402*Y1+152.36*Y2-24.84*Y3-22.227*Y4-203.392;

[0043] The values of G1, G2 and G3 of the Pseudosciaena crocea sample are calculated based on the standardized landmark distance measurement data, the otolith discriminant function equation corresponding to the maximum value of G1, G2 and G3 is used as the belonging population of the Pseudosciaena crocea sample to be identified in Pseudosciaena crocea, and is recorded as a second discriminant result for output.

[0044] The application also provides a Pseudosciaena crocea geographic population identification device combining otolith and morphological measurement, which applies the steps of the Pseudosciaena crocea geographic population identification method combining otolith and morphological measurement.

[0045] A sample data acquisition module is configured to acquire a Pseudosciaena crocea sample to be identified.

[0046] A morphological measurement data acquisition module is configured to acquire morphological measurement data of the Pseudosciaena crocea sample to be identified.

[0047] A first discriminant result calculation module is configured to obtain standardized morphological measurement data by performing first standardization processing on the morphological measurement data, input the standardized morphological measurement data into a pre-established morphological discriminant model, and output a first discriminant result through the morphological discriminant model.

[0048] A sagitta otolith acquisition module is configured to acquire a sagitta otolith of the Pseudosciaena crocea sample to be identified.

[0049] A landmark distance measurement data acquisition module is configured to acquire landmark distance measurement data based on pre-set otolith landmarks through the sagitta otolith.

[0050] The second discrimination result calculation module is configured to perform second standardization processing on the landmark point distance measurement data to obtain standardized landmark point distance measurement data, input the standardized landmark point distance measurement data into a pre-established otolith discrimination model, and output a second discrimination result through the otolith discrimination model.

[0051] The final result determination module is configured to compare the first discrimination result and the second discrimination result, and if the first discrimination result and the second discrimination result both show that the large yellow croaker sample to be identified belongs to the same geographical population, the large yellow croaker sample to be identified is determined as the geographical population.

[0052] The present application has the following advantages:

[0053] The present application provides a large yellow croaker geographical population identification method and device combining otolith and morphological measurement, which can directly identify whether the large yellow croaker sample to be identified belongs to the Chauzhou large yellow croaker population, the Minyue East large yellow croaker population, and the Daibu large yellow croaker population by collecting morphological measurement data and landmark point distance measurement data based on sagittal otolith of the large yellow croaker sample to be identified, and combining a pre-established morphological discrimination model and an otolith discrimination model. The identification method provided by the present application is simple to operate, has good stability, and has strong repeatability, and can identify a large number of large yellow croaker samples at one time. BRIEF DESCRIPTION OF DRAWINGS

[0054] The above and other features of the present disclosure will become more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which like reference numerals denote like elements in the accompanying drawings. As apparent from the following description, the drawings are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative effort based on these drawings. In the drawings:

[0055] Figure 1 The flowchart of the large yellow croaker geographical population identification method combining otolith and morphological measurement is shown.

[0056] Figure 2 The schematic diagram of the morphological measurement data involved in the present application is shown.

[0057] Figure 3 The schematic diagram of the otolith landmark point involved in the present application is shown. DETAILED DESCRIPTION

[0058] The concept, specific structure and generated technical effects of the present application will be described clearly and completely in combination with embodiments and drawings to fully understand the purposes, schemes and effects of the present application. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The same reference signs used in the drawings indicate the same or similar parts.

[0059] Considering the wild population and the cultured population of Pseudosciaena crocea samples of different geographical populations in multiple places, the morphological characteristics are extremely similar, and the commonly used morphological characteristic identification method can only be used to distinguish the cultured population and the wild population, and cannot distinguish the Daiqu population, the Minyuedong population and the Naozhou population, which is not conducive to objectively and accurately judging the source of Pseudosciaena crocea.

[0060] Embodiment 1, refer to Figure 1 The present application proposes a Pseudosciaena crocea geographical population identification method combining otolith and morphological measurement, which comprises the following steps:

[0061] Obtaining a Pseudosciaena crocea sample to be identified;

[0062] Obtaining morphological measurement data of the Pseudosciaena crocea sample to be identified;

[0063] After the morphological measurement data is subjected to first standardization processing, standardized morphological measurement data is obtained, the standardized morphological measurement data is input into a pre-established morphological identification model, and a first identification result is output by the morphological identification model;

[0064] Obtaining a sagitta of the Pseudosciaena crocea sample to be identified;

[0065] Obtaining landmark point distance measurement data based on a pre-set otolith landmark point through the sagitta;

[0066] After the landmark point distance measurement data is subjected to second standardization processing, standardized landmark point distance measurement data is obtained, the standardized landmark point distance measurement data is input into a pre-established otolith identification model, and a second identification result is output by the otolith identification model;

[0067] Comparing the first identification result and the second identification result, if the first identification result and the second identification result both show that the Pseudosciaena crocea sample to be identified is the same geographical population, the Pseudosciaena crocea sample to be identified is determined as the geographical population; wherein the geographical population comprises a Naozhou population, a Minyuedong population and a Daiqu population.

[0068] In this embodiment 1, by collecting morphological measurement data and otolith-based landmark distance measurement data of the large yellow croaker samples to be identified, and combining them with a pre-established morphological discrimination model and otolith discrimination model, it is possible to directly identify whether the large yellow croaker samples belong to the Naozhou group, the Fujian-Guangdong group, or the Daiqu group. The identification method proposed in this invention is simple to operate, has good stability and strong repeatability, and can identify a large number of large yellow croaker samples at once.

[0069] As a preferred embodiment of the present invention, specifically, refer to... Figure 2 Fish morphology was measured using the Mingmei Microscopic Digital Measurement and Analysis System V1.5.1. The morphological measurement data included...

[0070] Body length SL, distance from snout to dorsal fin origin Sn-DO, distance from snout to pelvic fin origin Sn-P2O, distance from snout to anal fin origin Sn-A2O, distance from dorsal fin origin to pelvic fin origin DO-P2O, distance from dorsal fin origin to anal fin origin DO-A2O, body height MBD, half-body height at pectoral fin origin P1-D2I, dorsal fin length HDL, anal fin length HAL, dorsal fin base length LDB, pectoral fin length P1L, pectoral fin base length LPB, pelvic fin length P2L, anal fin base length LAB, caudal peduncle length CPL, caudal peduncle height CPD, head length HL, postocular head length PoHL, eye diameter ED, snout length SnL, maxilla length UjL.

[0071] In a preferred embodiment of the present invention, the first standardization process specifically includes:

[0072] The postocular head length PoHL, eye diameter ED, snout length SnL, and maxillary length UjL in the morphological measurement data were standardized by dividing the head length HL by the other measurement data by the body length SL.

[0073] In a preferred embodiment of the present invention, the process of establishing the morphological discrimination model specifically includes:

[0074] The standardized morphological measurement data were filtered using the Wilk-Lambda method. F Using the type distribution value as a benchmark, when F When the value is greater than 3.84, the corresponding variable is introduced into the model. F Values ​​less than 2.71 were removed, and variables were gradually introduced to ultimately select 10 standardized morphological measurement data: distance from snout to dorsal fin origin / body length X1, distance from snout to anal fin origin / body length X2, body height / body length X3, half-body height at pectoral fin origin / body length X4, caudal peduncle length / body length X5, caudal peduncle height / body length X6, eye diameter / head length X7, dorsal fin length / body length X8, dorsal fin base length / body length X9, and pectoral fin base length / body length X10.

[0075] Then, a morphological discrimination equation is established, wherein;

[0076] The morphological discrimination function equation of the P. olivaceus in the Zhoushan population is as follows:

[0077] F1=-69.842*X1+322.809*X2-1.398*X3+287.120*X4+80.532*X5-306.768*X6+360.181*X7-24.200*X8+47.691*X9+659.578*X10-159.152;

[0078] The morphological discrimination function equation of the P. olivaceus in the Min and Yue populations is as follows:

[0079] F2=-212.860*X1+397.793*X2+64.821*X3+297.914*X4+122.172*X5-386.188*X6+342.377*X7-124.805*X8+64.601*X9+648.179*X10-175.501;

[0080] The morphological discrimination function equation of the P. olivaceus in the Daiqu population is as follows:

[0081] F3=22.471*X1+313.538*X2-82.082*X3+336.028*X4+114.826*X5-499.833*X6+391.159*X7-90.840*X8+57.577*X9+534.901*X10-165.030;

[0082] The values of F1, F2 and F3 are calculated based on the standardized morphological measurement data, the population corresponding to the morphological discrimination function equation to which the maximum value of F1, F2 and F3 belongs is taken as the population to which the P. olivaceus sample to be identified belongs in the P. olivaceus, and is recorded as the first discrimination result and output.

[0083] Referring to Figure 3 As a preferred embodiment of the present application, specifically, the preset otolith landmarks include,

[0084] Otolith posterior end vertex 1, otolith back concave point 2, otolith back convex point 3, otolith back convex point 4, otolith front end vertex 5, otolith anterior convex point 6, otolith posterior concave point 7, otolith auditory canal posterior end point 8, otolith auditory canal posterior and middle upper intersection point 9, otolith auditory canal anterior and middle upper intersection point 10, otolith auditory canal anterior upper end point 11, otolith auditory canal anterior and middle lower intersection point 12, otolith auditory canal posterior and middle lower intersection point 13.

[0085] In a preferred embodiment of the present invention, specifically, the distance between otolith landmarks is measured using the Mingmei Microscopic Digital Measurement and Analysis System V1.5.1, and the distance measurement data includes...

[0086] Distance from the posterior vertex of the otolith to the posterior end of the otolithal canal (1-8); distance from the anterior convex point of the otolith to the anterior convex point of the otolith's ventral side (4-6); distance from the intersection of the posterior and upper middle parts of the otolithal canal to the intersection of the anterior and upper middle parts of the otolithal canal (9-10); distance from the intersection of the anterior and upper middle parts of the otolithal canal to the upper anterior end of the otolithal canal (10-11); distance from the lower intersection of the anterior and lower middle parts of the otolithal canal to the intersection of the posterior and lower middle parts of the otolithal canal (12-13); posterior concave point of the otolith. The distance to the anterior convex point of the otolith (2-4), the distance from the posterior concave point of the otolith to the apex of the anterior point of the otolith (2-5), the distance from the posterior convex point of the otolith to the posterior end point of the otolith groove (3-8), the distance from the anterior convex point of the otolith to the apex of the anterior point of the otolith (4-5), the distance from the anterior convex point of the otolith to the posterior concave point of the otolith (4-7), the distance from the apex of the anterior point of the otolith to the posterior concave point of the otolith (5-7), and the distance from the anterior convex point of the otolith to the posterior concave point of the otolith (6-7).

[0087] In a preferred embodiment of the present invention, the second standardization process specifically includes:

[0088] The distance measurement data of the landmarks are standardized by dividing each data point by the body length.

[0089] In a preferred embodiment of the present invention, the process of establishing the otolith discrimination model specifically includes,

[0090] The standardized landmark distance measurement data were filtered using the Wilk-Lambda method. F Using the type distribution value as a benchmark, when F When the value is greater than 3.84, the corresponding variable is introduced into the model. F If the value is less than 2.71, the corresponding variable is removed. Variables are then gradually introduced, and finally, four standardized distance measurement data points are selected: distance from the posterior vertex of the otolith to the posterior end of the otolith groove (1-8) / body length Y1; distance from the anterior dorsal protrusion of the otolith to the anterior ventral protrusion of the otolith (4-6) / body length Y2; distance from the intersection of the anterior and middle upper parts of the otolith groove to the upper anterior end of the otolith groove (10-11) / body length Y3; and distance from the anterior ventral protrusion of the otolith to the posterior ventral concave point of the otolith (6-7) / body length Y4.

[0091] Next, a discriminant equation is established, where:

[0092] The otolith discrimination function equation for the large yellow croaker of the Naozhou group is as follows:

[0093] G1 = -6.489*Y1 + 141.445*Y2 - 22.251*Y3 - 17.939*Y4 - 186.686;

[0094] The otolith discriminant function equation of the Pescennia minyiyue group of large yellow croaker is as follows:

[0095] G2 = -6.268*Y1 + 116.929*Y2 - 22.289*Y3 - 13.631*Y4 - 126.44;

[0096] The otolith discriminant function equation of the Pescennia daibu group of large yellow croaker is as follows:

[0097] G3 = -8.402*Y1 + 152.36*Y2 - 24.84*Y3 - 22.227*Y4 - 203.392;

[0098] The values of G1, G2 and G3 of the large yellow croaker sample are calculated based on the standardized landmark distance measurement data, the otolith discriminant function equation corresponding to the maximum value of G1, G2 and G3 is taken as the belonging population of the large yellow croaker sample to be identified in the large yellow croaker, and is recorded as the second identification result and output.

[0099] Significance test is performed on the above multiple discriminant functions, and the results show that P <0.01, indicating that the discriminant function reaches a significant level and can effectively distinguish large yellow croakers of the Naozhou group, the Minyue group and the Daibu group.

[0100] The following verification experiment is designed to demonstrate the feasibility of the method proposed in the present application, and the steps are as follows:

[0101] 1) Collect large yellow croaker samples to be identified.

[0102] 2) Perform preliminary morphological identification, morphological measurement and gross dissection on the samples, weigh the body weight with an electronic balance, take a photo of the left side of the fish body with a camera, extract the sagitta of the sample, take a photo of the auditory canal surface of the sagitta with a microscope and mark the otolith landmarks, and then measure the distance between the fish body shape and the otolith landmarks by using the Mingmei micro-digital measurement analysis system V1.5.1 to obtain the following data, including,

[0103] Morphometric data: Standard length (SL), snout to dorsal fin origin (Sn-DO), snout to pelvic fin origin (Sn-P2O), snout to anal fin origin (Sn-A2O), dorsal fin origin to pelvic fin origin (DO-P2O), dorsal fin origin to anal fin origin (DO-A2O), Mid-body depth (MBD), half-body depth at pectoral fin origin (P1-D2I), dorsal fin length (HDL), pectoral fin length (P1L), pelvic fin length (P2L), anal fin length (HAL), dorsal fin base length (LDB), pectoral fin base length (LPB), anal fin base length (LAB), caudal peduncle length (CPL), caudal peduncle depth (CPD), head length (HL), postorbital head length (PoHL), eye diameter (ED), snout length (SnL), upper jaw length (UjL);

[0104] Otolith data: distance between the posterior end of the otolith and the top of the posterior end of the otolith canal (1-8), distance between the dorsoposterior hump of the otolith and the ventroposterior hump of the otolith (4-6), distance between the posterior and the upper intersection of the posterior and middle of the otolith canal and the anterior and upper intersection of the anterior and middle of the otolith canal (9-10), distance between the anterior and upper intersection of the anterior and middle of the otolith canal and the top of the anterior end of the otolith canal (10-11), distance between the anterior and lower intersection of the anterior and middle of the otolith canal and the posterior and lower intersection of the posterior and middle of the otolith canal (12-13), distance between the dorsoposterior hump of the otolith and the dorsanterior hump of the otolith (2-4), distance between the dorsoposterior hump of the otolith and the top of the anterior end of the otolith (2-5), distance between the dorsoposterior hump of the otolith and the posterior end of the otolith canal (3-8), distance between the dorsanterior hump of the otolith and the top of the anterior end of the otolith (4-5), distance between the dorsanterior hump of the otolith and the ventroposterior hump of the otolith (4-7), distance between the top of the anterior end of the otolith and the ventroposterior hump of the otolith (5-7), distance between the ventranterior hump of the otolith and the ventroposterior hump of the otolith (6-7).

[0105] 3) Standardize the postorbital head length (PoHL), eye diameter (ED), snout length (SnL), upper jaw length (UjL) by head length, and other measurements by standard length, using the morphometric data obtained in step 2).

[0106] 4) Use Wilk-Lambda method to construct statistical model for the data in step 3), and use F-type distribution value as the benchmark. When F the value is greater than 3.84, the corresponding variable is introduced into the model, and when FThe morphological variables were introduced step by step, and the variables with low contribution rate were removed according to the contribution rate of the variables to the model, and finally 10 standardized morphological measurement data were screened out: the distance from snout to the beginning of dorsal fin / standard length, the distance from the beginning of dorsal fin to the beginning of anal fin / standard length, body height / standard length, caudal peduncle depth / standard length, head length / standard length, eye diameter / head length, snout length / head length, upper jaw length / head length, dorsal fin length / standard length, and dorsal fin base length / standard length, which were represented by X1, X2, X3, X4, X5, X6, X7, X8, X9 and X10 respectively, and the morphological discriminant function equation was established.

[0107] The morphological discriminant function equation of Pseudosciaena crocea in Naozhou population is as follows:

[0108] F1=-69.842*X1+322.809*X2-1.398*X3+287.120*X4+80.532*X5-306.768*X6+360.181*X7-24.200*X8+47.691*X9+659.578*X10-159.152;

[0109] The morphological discriminant function equation of Pseudosciaena crocea in Minyue East population is as follows:

[0110] F2=-212.860*X1+397.793*X2+64.821*X3+297.914*X4+122.172*X5-386.188*X6+342.377*X7-124.805*X8+64.601*X9+648.179*X10-175.501;

[0111] The morphological discriminant function equation of Pseudosciaena crocea in Daiqu population is as follows:

[0112] F3=22.471*X1+313.538*X2-82.082*X3+336.028*X4+114.826*X5-499.833*X6+391.159*X7-90.840*X8+57.577*X9+534.901*X10-165.030.

[0113] 5) The landmark point distance data obtained in step 2) were standardized by dividing by the standard length respectively.

[0114] 6) The data in step 5) were screened by Wilk-Lambda method, and the chi-square distribution value was taken as the benchmark, when F the value is greater than 3.84, the corresponding variable is introduced into the model, and when F the value is less than 2.71, the corresponding variable is removed. FThe variables are removed if the value is less than 2.71, and the variables are gradually introduced, and finally four standardized measurement data are screened out: the distance from the top point of the back end of the otolith to the end point of the back of the otolith (1-8) / body length, the distance from the front convex point of the back of the otolith to the front convex point of the abdomen of the otolith (4-6) / body length, the distance from the upper intersection point of the front and middle of the otolith groove to the front upper end point of the otolith groove (10-11) / body length, and the distance from the front convex point of the abdomen of the otolith to the back concave point of the abdomen of the otolith (6-7) / body length, which are represented by Y1, Y2, Y3 and Y4 respectively, and an otolith discriminant equation is established.

[0115] The otolith discriminant function equation of the Pseudosciaena crocea in the Naozhou population is as follows:

[0116] G1=-6.489*Y1+141.445*Y2-22.251*Y3-17.939*Y4-186.686;

[0117] The discriminant function equation of the Pseudosciaena crocea in the Minyue East population is as follows:

[0118] G2=-6.268*Y1+116.929*Y2-22.289*Y3-13.631*Y4-126.44;

[0119] The discriminant function equation of the Pseudosciaena crocea in the Daiqu population is as follows:

[0120] G3=-8.402*Y1+152.36*Y2-24.84*Y3-22.227*Y4-203.392;

[0121] 7) The 10 morphological measurement data of each Pseudosciaena crocea are substituted into the morphological discriminant function equation (step 4), and the category corresponding to the discriminant function with the larger function value is the category to which it belongs, which is recorded as the first discriminant result.

[0122] 8) The four otolith measurement data of each Pseudosciaena crocea are substituted into the morphological discriminant function equation (step 4), and the category corresponding to the discriminant function with the larger function value is the category to which it belongs, which is recorded as the second discriminant result.

[0123] 9) The discriminant results of steps 7) and 8) are compared, if the first discriminant result is consistent with the second discriminant result, the Pseudosciaena crocea sample to be identified is determined as the geographical population identified.

[0124] The above verification experiment steps are implemented to identify Pseudosciaena crocea of known geographical populations, including 83 Pseudosciaena crocea in the Naozhou population, 26 Pseudosciaena crocea in the Minyue East population, and 59 Pseudosciaena crocea in the Daiqu population. The specific verification process is as follows,

[0125] 1. The fish's weight was measured using an electronic balance. The left side of the fish was photographed using a camera. The otoliths were removed, and the otolith canal surface was photographed and marked using a microscope. The following data was obtained using the Mingmei Microscopic Digital Measurement and Analysis System V1.5.1:

[0126] Body length (SL), distance from snout to origin of dorsal fin (Sn-DO), distance from snout to origin of pelvic fin (Sn-P2O), distance from snout to origin of anal fin (Sn-A2O), distance from origin of dorsal fin to origin of pelvic fin (DO-P2O), distance from origin of dorsal fin to origin of anal fin (DO-A2O), body depth (MBD), half-body depth at the origin of pectoral fin (P1-D2I), dorsal fin length (HDL), pectoral fin length (P1L), pelvic fin length (P2L), anal fin length (HAL), dorsal fin base length (LDB), pectoral fin base length (LPB), anal fin base length (LAB), caudal peduncle length (CPL), caudal peduncle depth (CPD), head length (HL), postocular head length (PoHL), eye diameter (ED), snout length (SnL), maxilla length (UjL); distance from the posterior apex of the otolith to the posterior end of the otolith canal (1-8), anterior dorsal apex of the otolith Distance from the convex point to the anterior convex point of the otolith (4-6); Distance from the upper intersection of the posterior and middle parts of the otolith groove to the upper intersection of the anterior and middle parts of the otolith groove (9-10); Distance from the upper intersection of the anterior and middle parts of the otolith groove to the upper end point of the anterior part of the otolith groove (10-11); Distance from the lower intersection of the anterior and middle parts of the otolith groove to the lower intersection of the posterior and middle parts of the otolith groove (12-13); Distance from the concave point behind the otolith to the anterior convex point of the otolith (2-4); Distance from the concave point behind the otolith to the apex of the anterior part of the otolith (2-5); Distance from the convex point behind the otolith to the posterior end point of the otolith groove (3-8); Distance from the anterior convex point of the otolith to the apex of the anterior part of the otolith (4-5); Distance from the anterior convex point of the otolith to the concave point behind the otolith (4-7); Distance from the apex of the anterior part of the otolith to the concave point behind the otolith (5-7); Distance from the anterior convex point of the otolith to the concave point behind the otolith (6-7).

[0127] 2. Substitute the 10 morphological measurement data of each rhubarb to be identified into the morphological discrimination function equation. The function with the larger calculation result is the category to which it belongs, and is recorded as the first discrimination result.

[0128] 3. Substitute the four otolith measurement data of each large yellow croaker into the otolith discrimination function equation, and record it as the second discrimination result.

[0129] 4. Combining morphological analysis (step 2) and otolith analysis (step 3), the functions with larger calculated results from both methods belong to the same category, indicating that the sample to be identified belongs to that category. The discrimination results show (see Table 1 below) that the discrimination accuracy rate for *Cyprinus naanensis* is 88.0%, for *Cyprinus fusillimansis* is 80.8%, for *Cyprinus dauricus* is 78.0%, and the overall discrimination accuracy rate is 82.3%.

[0130] Table 1 Discrimination accuracy of P. major populations of the Hoi Zhou group, the Min-Yue East group and the Hoi Zhou group

[0131]

[0132] The application further provides a device for identifying the geographic population of P. major by combining the otolith and morphological measurement, which applies the steps of the method for identifying the geographic population of P. major by combining the otolith and morphological measurement, and the device comprises:

[0133] a sample data acquisition module, which is configured to acquire a P. major sample to be identified;

[0134] a morphological measurement data acquisition module, which is configured to acquire morphological measurement data of the P. major sample to be identified;

[0135] a first discrimination result calculation module, which is configured to perform first standardization on the morphological measurement data to obtain standardized morphological measurement data, input the standardized morphological measurement data into a pre-established morphological discrimination model, and output a first discrimination result through the morphological discrimination model;

[0136] a sagitta acquisition module, which is configured to acquire a sagitta of the P. major sample to be identified;

[0137] a landmark distance measurement data acquisition module, which is configured to acquire landmark distance measurement data based on a preset otolith landmark through the sagitta;

[0138] a second discrimination result calculation module, which is configured to perform second standardization on the landmark distance measurement data to obtain standardized landmark distance measurement data, input the standardized landmark distance measurement data into a pre-established otolith discrimination model, and output a second discrimination result through the otolith discrimination model;

[0139] a final result determination module, which is configured to compare the first discrimination result and the second discrimination result, and if the first discrimination result and the second discrimination result both show that the P. major sample to be identified is of the same geographic population, the P. major sample to be identified is determined as the geographic population; wherein the geographic population comprises the Hoi Zhou group, the Min-Yue East group and the Daiqu group.

[0140] While the description of the application has been presented in terms of preferred embodiments and illustrative figures, it is not intended that the application be limited to any one form of the application as described in the application and the figures. Rather, the scope of the application is to be considered limited only by the following claims. Furthermore, the application is described in the context of embodiments that are presently foreseen, and which are intended to provide a useful description. Non-essential changes to the application that are not presently foreseen can nevertheless represent equivalent adaptations of the application.

[0141] The above description is only preferred embodiments of the present application, and the present application is not limited to the above-described embodiments, but any technical solutions and / or embodiments within the protection scope of the present application should belong to the protection scope of the present application. The technical solutions and / or embodiments within the protection scope of the present application can have various modifications and changes.

Claims

1. A method for identifying geographical populations of Pseudosciaena crocea by combining otolith and morphometric measurements, characterized in that, The method comprises: obtaining a sample of Pseudosciaena crocea to be identified; obtaining morphological measurement data of the sample of Pseudosciaena crocea to be identified; performing first standardization processing on the morphological measurement data to obtain standardized morphological measurement data, inputting the standardized morphological measurement data into a pre-established morphological discrimination model, and outputting a first discrimination result through the morphological discrimination model; obtaining a statolith of the sample of Pseudosciaena crocea to be identified; obtaining landmark point distance measurement data based on pre-set statolith landmark points through the statolith; performing second standardization processing on the landmark point distance measurement data to obtain standardized landmark point distance measurement data, inputting the standardized landmark point distance measurement data into a pre-established statolith discrimination model, and outputting a second discrimination result through the statolith discrimination model; comparing the first discrimination result and the second discrimination result, if the first discrimination result and the second discrimination result both show that the sample of Pseudosciaena crocea to be identified is the same geographical population, then the sample of Pseudosciaena crocea to be identified is determined as the geographical population; wherein the geographical population comprises the Naozhou population, the Minyue East population and the Daibu population; Specifically, the process of establishing the morphological discrimination model comprises, The standardized morphological measurement data were filtered using the Wilk-Lambda method. F Using the type distribution value as a benchmark, when F When the value is greater than 3.84, the corresponding variable is introduced into the model. F Values ​​less than 2.71 were removed, and variables were gradually introduced to ultimately select 10 standardized morphological measurement data: distance from snout to dorsal fin origin / body length X1, distance from snout to anal fin origin / body length X2, body height / body length X3, half-body height at pectoral fin origin / body length X4, caudal peduncle length / body length X5, caudal peduncle height / body length X6, eye diameter / head length X7, dorsal fin length / body length X8, dorsal fin base length / body length X9, and pectoral fin base length / body length X10. Then, a morphological discrimination equation is established, wherein The morphological discrimination function equation of Pseudosciaena crocea of the Naozhou population is as follows: F1 = -69.842 X1 + 322.809 X2 - 1.398 X3 + 287.120 X4 + 80.532 X5 - 306.768 X6 + 360.181 X7 - 24.200 X8 + 47.691 X9 + 659.578 X10 - 159.152; The morphological discrimination function equation of Pseudosciaena crocea of the Minyue East population is as follows: F2 = -212.860 X1 + 397.793 X2 + 64.821 X3 + 297.914 X4 + 122.172 X5 - 386.188 X6 + 342.377 X7 - 124.805 X8 + 64.601 X9 + 648.179 X10 - 175.501; The morphological discrimination function equation of Pseudosciaena crocea of the Daibu population is as follows: F3 = 22.471 X1 + 313.538 X2 - 82.082 X3 + 336.028 X4 + 114.826 X5 - 499.833 X6 + 391.159 X7 - 90.840 X8 + 57.577 X9 + 534.901 X10 - 165.030; The values of F1, F2 and F3 are calculated based on the standardized morphological measurement data respectively, and the population corresponding to the morphological discrimination function equation to which the maximum value of the values of F1, F2 and F3 belongs is taken as the population of Pseudosciaena crocea to which the sample to be identified belongs, and is recorded as the first discrimination result for output. Specifically, the process of establishing the statolith discrimination model comprises, The standardized landmark distance measurement data were filtered using the Wilk-Lambda method. F Using the type distribution value as a benchmark, when F When the value is greater than 3.84, the corresponding variable is introduced into the model. F If the value is less than 2.71, the corresponding variable is removed. Variables are then gradually introduced, and finally, four standardized distance measurement data points are selected: distance from the posterior vertex of the otolith to the posterior end of the otolith groove (1-8) / body length Y1; distance from the anterior dorsal protrusion of the otolith to the anterior ventral protrusion of the otolith (4-6) / body length Y2; distance from the intersection of the anterior and middle upper parts of the otolith groove to the upper anterior end of the otolith groove (10-11) / body length Y3; and distance from the anterior ventral protrusion of the otolith to the posterior ventral concave point of the otolith (6-7) / body length Y4. Then, a discrimination equation is established, wherein The statolith discrimination function equation of Pseudosciaena crocea of the Naozhou population is as follows: G1 = -6.489 Y1 + 141.445 Y2 - 22.251 Y3 - 17.939 Y4 - 186.686; The statolith discrimination function equation of Pseudosciaena crocea of the Minyue East population is as follows: G2 = -6.268 Y1 + 116.929 Y2 - 22.289 Y3 - 13.631 Y4 - 126.44; The statolith discrimination function equation of Pseudosciaena crocea of the Daibu population is as follows: G3 = -8.402 Y1 + 152.36 Y2 - 24.84 Y3 - 22.227 Y4 - 203.392; The values of G1, G2 and G3 of the sample of Pseudosciaena crocea are calculated based on the standardized landmark point distance measurement data respectively, and the population corresponding to the statolith discrimination function equation to which the maximum value of the values of G1, G2 and G3 belongs is taken as the population of Pseudosciaena crocea to which the sample to be identified belongs, and is recorded as the second discrimination result for output.

2. The method according to claim 1, wherein, Specifically, the morphological measurement data comprises, body length SL, distance from snout to dorsal fin Sn-DO, distance from snout to ventral fin Sn-P2O, distance from snout to anal fin Sn-A2O, distance from dorsal fin to ventral fin DO-P2O, distance from dorsal fin to anal fin DO-A2O, body depth MBD, half body depth at the origin of pectoral fin P1-D2I, dorsal fin length HDL, anal fin length HAL, dorsal fin base length LDB, pectoral fin length P1L, pectoral fin base length LPB, ventral fin length P2L, anal fin base length LAB, caudal peduncle length CPL, caudal peduncle depth CPD, head length HL, postorbital head length PoHL, eye diameter ED, snout length SnL, upper jaw length UjL.

3. The method according to claim 2, wherein the otoliths are measured by the method of claim 1. Specifically, the process of the first standardization processing comprises, The postorbital head length PoHL, eye diameter ED, snout length SnL, maxillary length UjL in the morphological measurement data are divided by the head length HL, and other measurement data are divided by the body length SL for standardization.

4. The method for identifying geographical populations of large yellow croaker by combining otolith and morphological measurements according to claim 1, characterized in that, Specifically, the preset landmark points of the otolith include, an otolith posterior end vertex (1), an otolith back rear concave point (2), an otolith back rear convex point (3), an otolith back front convex point (4), an otolith anterior end vertex (5), an otolith ventral front convex point (6), an otolith ventral rear concave point (7), an otolith auditory canal rear end point (8), an otolith auditory canal rear and middle upper intersection point (9), an otolith auditory canal front and middle upper intersection point (10), an otolith auditory canal front upper end point (11), an otolith auditory canal front and middle lower intersection point (12), and an otolith auditory canal rear and middle lower intersection point (13).

5. The method according to claim 4, wherein the otoliths are measured by the method of claim 1. Specifically, the landmark point distance measurement data include, an otolith posterior end vertex to otolith auditory canal rear end point distance (1-8), an otolith back front convex point to otolith ventral front convex point distance (4-6), an otolith auditory canal rear and middle upper intersection point to otolith auditory canal front and middle upper intersection point distance (9-10), an otolith auditory canal front and middle upper intersection point to otolith auditory canal front upper end point distance (10-11), an otolith auditory canal front and middle lower intersection point to otolith auditory canal rear and middle lower intersection point distance (12-13), an otolith back rear concave point to otolith back front convex point distance (2-4), an otolith back rear concave point to otolith anterior end vertex distance (2-5), an otolith back rear convex point to otolith auditory canal rear end point distance (3-8), an otolith back front convex point to otolith anterior end vertex distance (4-5), an otolith back front convex point to otolith ventral rear concave point distance (4-7), an otolith anterior end vertex to otolith ventral rear concave point distance (5-7), and an otolith ventral front convex point to otolith ventral rear concave point distance (6-7).

6. The method according to claim 5, wherein the otoliths are measured by the method of claim 1. Specifically, the process of the second standardization processing includes, standardizing the landmark point distance measurement data by dividing by the body length respectively.

7. The device for identifying geographical populations of Pseudosciaena crocea by combining otolith and morphometric measurements, characterized in that, The device includes the steps of the method in any one of claims 1-6. a sample data acquisition module configured to acquire a sample of Pseudosciaena crocea to be identified; a morphological measurement data acquisition module configured to acquire morphological measurement data of the Pseudosciaena crocea sample to be identified; a first discrimination result calculation module configured to obtain standardized morphological measurement data by performing first standardization processing on the morphological measurement data, input the standardized morphological measurement data into a pre-established morphological discrimination model, and output a first discrimination result through the morphological discrimination model; an otolith acquisition module configured to acquire an otolith of the Pseudosciaena crocea sample to be identified; a landmark point distance measurement data acquisition module configured to acquire landmark point distance measurement data based on preset otolith landmark points through the otolith; a second discrimination result calculation module configured to obtain standardized landmark point distance measurement data by performing second standardization processing on the landmark point distance measurement data, input the standardized landmark point distance measurement data into a pre-established otolith discrimination model, and output a second discrimination result through the otolith discrimination model; and a discrimination result output module configured to output a final discrimination result of the Pseudosciaena crocea sample to be identified based on the first discrimination result and the second discrimination result. A final result judging module is configured to compare the first judging result and the second judging result, and if the first judging result and the second judging result both show that the large yellow croaker sample to be identified is of the same geographical population, the large yellow croaker sample to be identified is determined as the geographical population; wherein the geographical population includes the Naozhou population, the Minyue East population and the Daiqu population.

Images