A rapid and non-destructive method for evaluating the soft matter weight of bivalve molluscs

Abstract

The present invention provides a method for rapidly and non-destructively evaluating the soft weight of bivalve molluscs, and belongs to the technical field of shellfish breeding. The method comprises: measuring the body size and weight traits of the bivalve molluscs in the training set, calculating the shell surface area of ​​the bivalve molluscs in the training set, constructing a soft weight estimation model based on the bivalve molluscs in the training set by using ridge regression, measuring the body size and full wet weight of the bivalve molluscs in the test set, calculating the shell surface area of ​​the bivalve molluscs in the test set, and estimating the soft weight of the bivalve molluscs in the test set by using the soft weight evaluation model. The present invention can accurately and non-destructively measure the soft weight of bivalve molluscs with high throughput, circumvents the problem that the traditional anatomical measurement method must sacrifice the bivalve molluscs, overcomes the limitations of the evaluation method based on image recognition, which is high cost, low efficiency, and unstable accuracy, and provides a solution to the difficult problem of dynamically monitoring the changes in the soft weight of bivalve molluscs, making it possible to systematically analyze the genetic basis of the regulation of the soft weight of bivalve molluscs and accelerate the cultivation of high-fat bivalve varieties.

Description

Technical Field

[0001] The invention relates to the field of bivalve mollusc economic trait determination and breeding technology development, and in particular to a method for rapidly and non-destructively evaluating the soft weight of bivalve molluscs. Background Art

[0002] Global aquaculture production has grown exponentially over the past few decades. In 2022, the production of aquatic animals from farming surpassed that from fishing for the first time, and aquaculture is becoming an increasingly important way to obtain high-quality protein. Bivalve molluscs are one of the important farmed species, and their soft parts are delicious and nutritious. Therefore, bivalve molluscs with high soft body weight (i.e., high fatness) have extremely high economic value and are one of the goals of shellfish breeding. Accurate, non-destructive and rapid determination of the soft body weight of bivalve molluscs is a prerequisite for obtaining high-soft body weight shellfish: on the one hand, accurate determination of soft body weight can provide information for analyzing the genetic basis of soft body weight regulation and provide a theoretical basis for genetic improvement; on the other hand, dynamic tracking of soft body weight changes can identify potential high-quality individuals in the early growth stages of shellfish for subsequent breeding, thereby improving the efficiency of shellfish breeding.

[0003] The soft part of bivalve molluscs is wrapped in a hard and tightly closed shell. Traditional measurement methods require the shellfish to be dissected before measurement, which makes it impossible to dynamically monitor changes in the soft body weight of the shellfish. Although the soft body weight assessment method based on magnetic resonance imaging and X-ray imaging can achieve non-destructive measurement, it is limited by high cost, low efficiency, and unstable accuracy. The actual application of this method in shellfish breeding and aquaculture still has certain limitations. How to accurately and non-destructively assess the soft body weight with high throughput to provide information for the analysis of shellfish economic traits, genetic improvement, and efficient aquaculture is an urgent problem to be solved in the field of shellfish genetics and breeding research. Summary of the invention

[0004] The purpose of the invention is to establish a method for rapidly and non-destructively evaluating the soft weight of bivalve molluscs to make up for the deficiencies of the prior art.

[0005] The morphological relationship between the body dimensions (such as shell length, shell width, shell height, etc.) and weight (such as soft weight, shell weight, total wet weight, etc.) of bivalve molluscs is complex and changeable, but has certain rules. Therefore, constructing a model based on the body dimensions and weight of bivalve molluscs for soft weight estimation makes it possible to accurately and non-destructively evaluate the soft weight of bivalve molluscs with high throughput.

[0006] The present invention is based on the morphological relationship of bivalve molluscs. By constructing a model with the surface area and total wet weight of bivalve molluscs as independent variables, the soft weight of bivalve molluscs is estimated, thereby achieving a leap from lossy, inefficient, high-cost, and unstable accuracy in soft weight assessment of shellfish to non-destructive, efficient, low-cost, stable and accurate assessment. By dynamically monitoring the soft weight, information is provided for achieving genetic improvement of shellfish and enhancing shellfish farming efficiency.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] A method for rapidly and non-destructively evaluating the soft weight of bivalve molluscs, the method comprising the following steps: measuring the body size, total wet weight, and soft weight of the bivalve molluscs in a training set, calculating the shell surface area of ​​the bivalve molluscs in the training set, constructing a soft weight evaluation model with the shell surface area and total wet weight as independent variables and the soft weight as a dependent variable based on the bivalve molluscs in the training set by using ridge regression, measuring the body size and total wet weight of the bivalve molluscs in a test set, calculating the shell surface area of ​​the bivalve molluscs in the test set, and estimating the soft weight of the bivalve molluscs in the test set by using a soft weight estimation model.

[0009] Furthermore, the method for rapidly and non-destructively evaluating the soft weight of bivalve molluscs specifically comprises the following steps:

[0010] (1) Collect bivalve mollusc samples for the training set and bivalve mollusc samples to be evaluated (i.e., bivalve mollusc samples for the test set);

[0011] (2) Determine the body size and weight of bivalve samples in the training set;

[0012] (3) Calculate the shell surface area of ​​bivalve samples in the training set;

[0013] (4) Using the shell surface area and total wet weight of the bivalve samples in the training set as independent variables and the soft weight of the bivalve samples in the training set as the dependent variable, a soft weight assessment model was constructed using ridge regression;

[0014] (5) Determine the body size and weight of the bivalve mollusc samples to be evaluated;

[0015] (6) Calculate the shell surface area of ​​the bivalve mollusc sample to be evaluated;

[0016] (7) Estimate the soft weight of the bivalve mollusc sample to be evaluated using the soft weight assessment model.

[0017] Furthermore, in steps (3) and (6), the formula for calculating the shell surface area is as follows:

[0018] ;

[0019] ;

[0020] ;

[0021] ;

[0022] in, is the approximate ellipsoidal surface area of ​​the bivalve shell, is the approximate cone surface area of ​​the bivalve shell, is the surface area of ​​the bivalve shell ear, is the length of the bivalve shell, The shell height of bivalve molluscs, and The widths of the upper and lower shells of bivalve molluscs, and They are the height of the upper and lower shell bottoms of bivalve molluscs, which are approximately trapezoidal in shape. and are the lengths of the upper and lower bases of the trapezoidal bottom of the bivalve shell, and They are respectively the lengths of the upper and lower bases of the trapezoidal bottom of the bivalve shell.

[0023] Furthermore, in step (4), the software weight evaluation model is: ,in, For the soft weight of bivalve molluscs, is the total wet weight of bivalve molluscs, is the shell surface area of ​​the bivalve molluscs, and a, b, c are coefficients.

[0024] Furthermore, in steps (2) and (5), the body size traits include shell length, shell width, and shell height.

[0025] The above method can realize high-throughput, accurate and non-destructive evaluation of the soft body weight of bivalve molluscs. The soft body weight can be used as a criterion for parent selection and screening of cultured individuals, providing a basis for genetic improvement and efficient breeding of bivalve molluscs.

[0026] Compared with the prior art, the present invention has the following advantages:

[0027] (1) This method can perform high-throughput, accurate and non-destructive evaluation of the soft body mass of bivalve molluscs, thereby achieving dynamic monitoring of the soft body mass of bivalve molluscs. (2) Rapid, efficient and non-destructive determination of the soft body mass of bivalve molluscs can provide information for analyzing the genetic basis of soft body mass regulation and cultivating bivalve molluscs with high fatness. (3) Dynamic tracking of changes in the soft body mass of bivalve molluscs can screen potential high-fat individuals in the early growth stages of bivalve molluscs, thereby improving the efficiency of shellfish farming. (4) The body size and weight measurement tools required for this method are simple and the operation method is simple and easy. The constructed soft body mass assessment model is accurate, stable and has a wide range of applications. It can provide necessary information for the breeding of high-quality bivalve molluscs with regular and strictly symmetrical shell shapes and the improvement of farming efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 Schematic diagram of the measurement of body size traits of bivalve molluscs in Example 1 of the present invention.

[0029] Figure 2 Schematic diagram of bivalve shell segmentation and shell surface area calculation in Example 1 of the present invention.

[0030] Figure 3This is a schematic diagram comparing the shell length, shell width, shell height, and total wet weight of the scallops in the training set and the test set in Example 2 of the present invention.

[0031] Figure 4 Schematic diagram of the comparison between the actual observed soft mass of Chlamys farreri and the soft mass estimated by the model in Example 2 of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] Embodiment 1:

[0034] A method for rapid and non-destructive assessment of the soft matter weight of bivalve molluscs, comprising the following steps:

[0035] (1) Collect bivalve mollusc samples as training set and collect bivalve mollusc samples to be evaluated (i.e., test set bivalve mollusc samples). The bivalve molluscs must have shells with regular shapes and strict symmetry;

[0036] (2) Use electronic vernier calipers to measure the body size traits (shell length, shell width, shell height, etc.) of the bivalve molluscs in the training set, and use electronic balances to measure the weight traits (total wet weight, shell weight, soft weight), such as Figure 1 As shown;

[0037] (3) The shell surface area of ​​the bivalve samples in the training set was calculated using the following formula: Figure 2 As shown;

[0038] :

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[0054] ② FK and CF;

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[0056] ③ BF and DF;

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[0094] in, is the surface area of ​​the bivalve shell, is the approximate ellipsoidal surface area of ​​the bivalve shell, is the approximate cone surface area of ​​the bivalve shell, is the surface area of ​​the bivalve shell ear, is the length of the bivalve shell, The shell height of bivalve molluscs, and The widths of the upper and lower shells of bivalve molluscs, and They are the height of the upper and lower shell bottoms of bivalve molluscs, which are approximately trapezoidal in shape. and are the lengths of the upper and lower bases of the trapezoidal bottom of the bivalve shell, and They are respectively the lengths of the upper and lower bases of the trapezoidal bottom of the bivalve shell.

[0095] (4) The shell surface area and total wet weight of the bivalve molluscs in the training set were used as independent variables, and the soft weight of the bivalve molluscs in the training set was used as the dependent variable. Ridge regression was used to fit the soft weight assessment model: , calculate the model coefficients: , construct a soft weight assessment model;

[0096] (5) Determine the body dimensions (shell length, shell width, shell height, etc.) and total wet weight of the bivalve mollusc sample to be evaluated, such as Figure 1 As shown;

[0097] (6) Calculate the shell surface area of ​​the bivalve mollusc sample to be evaluated using the formula in (3), as follows: Figure 2 As shown;

[0098] (7) Use the soft matter weight assessment model constructed in (4) to assess the soft matter weight of the bivalve mollusc sample to be assessed.

[0099] Embodiment 2:

[0100] Chlamys farreri population 1 (Cf1, including 627 chlamys farreri) was selected as the training set, and Chlamys farreri population 2 (Cf2, including 498 chlamys farreri) was selected as the population to be evaluated. According to the method in Example 1, the body size (shell length, shell width, shell height, etc.) and body weight (total wet weight, shell weight, soft body weight) traits of the training set Cf1 were measured, the shell surface area was calculated, and a soft body weight evaluation model was constructed using Cf1 as the training set. The body size (shell length, shell width, shell height, etc.) and full wet weight of the population to be evaluated Cf2 were measured, and the soft body weight of Cf2 was calculated using the soft body weight evaluation model. The results showed that although the shell length, shell width, shell height, and full wet weight of Cf1 and Cf2 were significantly different (such as Figure 3As shown in Table 1, the soft weight of Cf2 estimated by the soft weight evaluation model based on Cf1 is highly correlated with the real soft weight of Cf2 (as shown in Table 1, Table 2, and Table 3). Compared with other models (taking traditional model 1 and traditional model 2 as examples; as shown in Table 1 and Table 2), the model constructed by the present invention can effectively remove the estimation system deviation and obtain the estimated soft weight that is highly consistent with the actual soft weight (as shown in Table 1, Figure 4 ), indicating that the present invention can accurately and efficiently evaluate the soft body weight of Chlamys farreri under non-destructive conditions, and provide a standard for parent selection and candidate breeding population selection.

[0101] Table 1 Comparative evaluation of the actual soft weight and the soft weight estimated by the model of the present invention

[0102] .

[0103] Table 2 Comparative evaluation of the actual soft weight and the soft weight estimated by traditional model 1

[0104] .

[0105] Table 3 Comparative evaluation of the actual soft weight and the soft weight estimated by traditional model 2

[0106] .

[0107] The present invention aims to break through the bottlenecks of traditional soft body weight assessment methods, such as lossy, inefficient, high-cost, and poor accuracy and stability. By constructing a soft body weight assessment model based on shell surface area, the soft body weight of bivalve molluscs can be accurately, non-destructively and efficiently assessed, providing a means for the determination and evaluation of economic traits of bivalve molluscs, and providing information for genetic analysis of economic traits of bivalve molluscs, breeding of improved varieties, and improvement of aquaculture efficiency.

[0108] Finally, although this specification is described according to implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A method for rapidly and non-destructively evaluating the soft matter weight of bivalve molluscs, characterized in that: The method comprises the following steps: measuring the body size, full wet weight and soft body weight of bivalve molluscs in a training set, and calculating the shell surface area of ​​the bivalve molluscs in the training set; constructing a soft body weight evaluation model with shell surface area and full wet weight as independent variables and soft body weight as dependent variable based on the bivalve molluscs in the training set by using ridge regression; measuring the body size and full wet weight of bivalve molluscs in a test set, calculating the shell surface area of ​​the bivalve molluscs in the test set, and estimating the soft body weight of the bivalve molluscs in the test set by using a soft body weight estimation model; and specifically comprising the following steps: (1) collecting bivalve mollusc samples of the training set and bivalve mollusc samples to be evaluated, i.e., bivalve mollusc samples of the test set; (2) Determine the body size and weight of bivalve samples in the training set; (3) Calculate the shell surface area of ​​bivalve samples in the training set; (4) The shell surface area and total wet weight of the bivalve molluscs samples in the training set were used as independent variables, and the The soft weight of the product was taken as the dependent variable, and the soft weight evaluation model was constructed using ridge regression; (5) Determine the body size and weight of the bivalve mollusc samples to be evaluated; (6) Calculate the shell surface area of ​​the bivalve mollusc sample to be evaluated; (7) using the soft matter weight assessment model to estimate the soft matter weight of the bivalve mollusc sample to be assessed; In the steps (3) and (6), the formula for calculating the shell surface area is as follows: S she =S ellipsoid +S shellear +S cone ; Among them, S ellipsoid is the approximate ellipsoidal surface area of ​​the bivalve shell, S cone is the approximate cone surface area of ​​the bivalve shell, S shelear is the surface area of ​​the bivalve shell, SL is the length of the bivalve shell, SH is the height of the bivalve shell, SW1 and SW2 are the widths of the upper and lower shells of the bivalve, respectively, and H sb With H sb2 are the height of the upper and lower shell bottoms of the bivalve molluscs, respectively, and L sb11 With L sb21 are the lengths of the upper and lower bases of the trapezoidal bottom of the bivalve shell, L sb12 With L sb22 They are respectively the lengths of the upper and lower bases of the trapezoidal bottom of the bivalve shell.

2. The method for rapid non-destructive evaluation of the soft weight of bivalve molluscs according to claim 1, characterized in that: In step (4), the software weight evaluation model is: log 10 W soft =alog 10 W wet +blog 10 S shell +c, where W soft is the soft weight of bivalve molluscs, W wet is the total wet weight of bivalve molluscs, S shell is the shell surface area of ​​the bivalve molluscs, and a, b, c are coefficients.

3. The method for rapid non-destructive evaluation of the soft weight of bivalve molluscs according to claim 1, characterized in that: In the steps (2) and (5), the body size traits include shell length, shell width, and shell height.

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