Stable Isotope-Based Identification Model for Wild Sea Cucumbers in Seaweed Beds and Its Construction Method

Abstract

The present invention relates to a recognition model for wild sea cucumbers in seaweed beds based on stable isotopes and a method for constructing the same. The model of the present invention can identify a large number of sea cucumber samples through stable isotope detection and in combination with the parameter calculation method provided in this patent. The model and recognition method of the present invention can be applied to the direction of large-scale, rapid and accurate recognition of wild sea cucumbers in seaweed beds in the aquatic product market, are more easily promoted, and are conducive to the productized development of the wild sea cucumber market standardization.

Description

Technical Field

[0001] The present invention relates to the technical field of traceability of seafood products, and in particular, to a recognition model of wild sea cucumbers in seaweed beds based on stable isotopes and a method for constructing the same. Background Art

[0002] With the development of society and the improvement of living standards, consumers pay more attention to the quality and reliability of food, and have higher requirements for the transparency and traceability of high-quality food, especially various aquatic products and agro-ecological products. Wild sea cucumbers are unique ecological seafood products in the offshore ecosystem. Although they have natural advantages, there are still obstacles to realizing their own ecological product brand value due to the lack of a standardized certification and traceability system.

[0003] Not only in China, mislabeling of international seafood and agricultural and sideline products is also a relatively common phenomenon. According to statistics, 80% of the seafood imported into the United States has problems with sales label errors; a large number of seafood products in Australia, such as fish, shrimps, and shellfishes, are often mislabeled as other species. The World Wildlife Fund is seeking ways to use stable isotopes as a means to determine the ecological labels of seafood products and certify the traceable components of seafood products through research. The demand for certification and traceability of agricultural and sideline products has also prompted the European Union to formulate traceability regulations (178 / 2002 / EC). The Implementing Regulation (1337 / 2013) of the European Commission requires that at each stage of the production and distribution of agricultural and sideline products, operators must label traceable signs, and the labeling requirements include Protected Geographic Indication, Protected Designation of Origin, and Traditional Specialties Guarantee. In addition, international organizations such as the Global Aquaculture Alliance are also exploring ways to certify seafood products using similar means.

[0004] At present, the traceability and identification of ecological seafood such as wild sea cucumbers are generally in the initial exploration stage. There are still various problems to be overcome, and no feasible and targeted specific traceability and identification methods have been formed. The top priority to solve this problem is to seek reliable technical means to identify the "identity" of ecological products such as wild sea cucumbers. As the "natural fingerprint" shaped by various specific habitats during the growth process of various food sources for humans, the stable isotope abundance has attracted much attention from relevant researchers in identifying the authenticity and traceability of agricultural and sideline products and aquatic products. In recent years, more and more research on tracing aquatic products and agricultural and sideline ecological products using stable isotope analysis has emerged and gradually matured. The stable isotope analysis method has gradually become a very promising reliable tool for identifying the authenticity and traceability of agricultural and sideline ecological products. According to theoretical research, stable isotope fingerprints may be able to achieve the identification of the geographical origin, origin, and production method of biological products, such as identifying wild or farmed origin, "organic" free-range or intensive scale production. Based on the above situation, developing a practical fingerprint identification method based on stable isotopes can not only reduce information asymmetry and improve consumers' trust, but also become a reliable guarantee and promotion foundation for building ecological seafood brands.

[0005] In the seaweed bed, wild sea cucumbers mainly feed on large algae. Large algae include various large seaweeds in the Phylum Rhodophyta, Phylum Phaeophyta, and Phylum Chlorophyta, such as kelp, laver, ulva lactuca, and sargassum. Sea cucumbers in the seaweed bed usually prefer large algae and their debris first. Here, large algae are abundant as a food source and are usually of better quality than other foods (Wang Xiaoyan et al., 2019). Our analysis of the contribution of food sources based on programs such as IsoSource, SIAR, and SIBER also shows that the average contribution of large algae in the seaweed bed to local wild sea cucumbers statistically reaches 76.6%, which is higher than that of other food sources.

[0006] References: Wang Xiaoyan, Qiao Hongjin, Huang Bingshan, Wang Chengqiang, Li Peiyu, Li Baoshan, Wang Jiying. Application research of 5 kinds of seaweeds in the feed of juvenile sea cucumbers. Progress in Fishery Sciences, 2019, 40(3): 160–167 Summary of the Invention

[0007] To solve the above problems, the present invention provides a wild sea cucumber identification model in the seaweed bed based on stable isotopes, specifically as follows:

[0008]

[0009] Wherein:

[0010] δ 15 N x is the nitrogen stable isotope limit value of wild sea cucumbers in the target seaweed bed;

[0011] δ 15 N Y is the nitrogen stable isotope value of the sea cucumber to be identified;

[0012] δ 15 N j is the nitrogen stable isotope value of the macroalgae in the target seaweed bed;

[0013] Y j is the trophic level of the macroalgae in the target seaweed bed.

[0014] Specifically, (1) when the model output result has no solution, the sample to be identified does not belong to the wild sea cucumbers in the target seaweed bed; (2) when the model output result has a solution and Y>2, the sample to be identified does not belong to the wild sea cucumbers in the target seaweed bed; (3) when the model output result has a solution and Y≤2, it is necessary to further analyze and confirm based on the value of the carbon stable isotope.

[0015] The above method for further analyzing and confirming based on the value of the carbon stable isotope is as follows:

[0016] Compare the carbon stable isotope of the sample to be identified with the statistical threshold range of the carbon stable isotope of the wild sea cucumbers in the target seaweed bed;

[0017] If the carbon stable isotope of the sample to be identified is outside these two thresholds, the sample to be identified does not belong to the wild sea cucumbers in the target seaweed bed;

[0018] If the carbon stable isotope of the sample to be identified is within these two thresholds, it belongs to the wild sea cucumbers in the target seaweed bed.

[0019] Based on the above model, the present application also provides a method for constructing the model. When constructing the model,

[0020] By collecting and detecting multiple wild sea cucumber samples in the target seaweed bed, the upper limit value δ 15 N eigenvalue of these samples is obtained; 15 N x ;

[0021] The meta-analysis method can also be used to collect the historical data of the stable isotopes of the wild sea cucumbers in the target seaweed bed, and statistically analyze to obtain the upper limit value of the δ 15 N eigenvalue of the wild sea cucumbers in the target seaweed bed.

[0022] By statistically analyzing multiple samples of the macroalgae in the target seaweed bed, the average value δ 15 N of the nitrogen stable isotope of the macroalgae in the target seaweed bed is calculated; j .

[0023] The above model can be used for the identification of wild sea cucumbers in the target seaweed bed.

[0024] A method for identifying wild sea cucumbers in seaweed beds based on stable isotopes. When identifying, the nitrogen stable isotope value of the sea cucumber to be identified is tested and calculated through a model formula;

[0025] (1) When the model output result has no solution, the sample to be identified does not belong to the wild sea cucumbers in the target seaweed bed;

[0026] (2) When the model output result has a solution and Y > 2, the sample to be identified does not belong to the wild sea cucumbers in the target seaweed bed;

[0027] (3) When the model output result has a solution and Y ≤ 2, further analysis and confirmation based on the value of carbon stable isotope are required.

[0028] The above method for further analysis and confirmation based on the value of carbon stable isotope is as follows:

[0029] Compare the carbon stable isotope of the sample to be identified with the statistical threshold range of the carbon stable isotope of wild sea cucumbers in the target seaweed bed;

[0030] If the carbon stable isotope of the sample to be identified is outside these two thresholds, the sample to be identified does not belong to the wild sea cucumbers in the target seaweed bed;

[0031] If the carbon stable isotope of the sample to be identified is within these two thresholds, it belongs to the wild sea cucumbers in the target seaweed bed.

[0032] Compared with the traditional method for identifying wild sea cucumbers, the present invention is based on the indication of stable isotopes, greatly improving the accuracy and operability of identifying wild sea cucumbers in seaweed beds. This patent makes various identification indicators specific and standardized.

[0033] The present invention uses various indicators based on stable isotopes as the identification basis. Compared with the traditional sensory identification methods such as appearance, color, smell, and taste, the accuracy has been greatly improved, and at the same time, the operability of large-scale commodity identification has been realized. That is, through the method of stable isotope detection and combined with the parameter calculation method provided by this patent, a large number of sea cucumber samples can be identified. Correspondingly, the stable isotope analysis and testing technology required by the method of the present invention has been gradually promoted internationally, and the test accuracy meets the requirements, with the characteristics of accurate and fast batch testing of sea cucumbers. Combining the above detection basis, analysis basis and identification indicators, this patent can be applied to the direction of large-scale, rapid and accurate identification of wild sea cucumbers in seaweed beds in the aquatic product market, is more conducive to promotion, and is beneficial to the productized development of the wild sea cucumber market standard. Specific implementation mode

[0034] Next, in combination with the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0035] Embodiment 1

[0036] A recognition model of wild sea cucumbers in seaweed beds based on stable isotopes is as follows:

[0037]

[0038] Wherein:

[0039] δ 15 N x is the nitrogen stable isotope limit value of wild sea cucumbers in the target seaweed bed;

[0040] δ 15 N Y is the nitrogen stable isotope value of the sea cucumber to be recognized;

[0041] δ 15 N j is the nitrogen stable isotope value of large algae in the target seaweed bed;

[0042] Y j is the trophic level of large algae in the target seaweed bed.

[0043] During recognition, (1) when the model output result has no solution, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed bed; (2) when the model output result has a solution and Y>2, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed bed; (3) when the model output result has a solution and Y≤2, it is necessary to further analyze and confirm based on the value of the carbon stable isotope.

[0044] As a specific implementation, the method for further analyzing and confirming based on the value of the carbon stable isotope is as follows:

[0045] Compare the carbon stable isotope of the sample to be recognized with the statistical threshold range of the carbon stable isotope of wild sea cucumbers in the target seaweed bed;

[0046] If the carbon stable isotope of the sample to be recognized is outside these two thresholds, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed bed;

[0047] If the carbon stable isotope of the sample to be recognized is within these two thresholds, it belongs to the wild sea cucumbers in the target seaweed bed.

[0048] The present application provides a method for constructing the above model. Specifically, when constructing the model,

[0049] By collecting multiple wild sea cucumber samples from the target seaweed bed for detection, the upper limit value of the δ 15 N eigenvalue, δ 15 N x ;

[0050] The meta-analysis method can also be used to collect historical data on the stable isotopes of wild sea cucumbers in the target seaweed bed, and through statistical analysis, the upper limit value of the δ 15 N eigenvalue of wild sea cucumbers in the target seaweed bed is obtained.

[0051] By statistically analyzing multiple samples of macroalgae in the target seaweed bed, the average value of the nitrogen stable isotope of macroalgae in the target seaweed bed, δ 15 N j is calculated.

[0052] After the recognition model for a certain target seaweed bed is constructed, relevant recognition can be carried out. During recognition, the nitrogen stable isotope value of the sea cucumber to be recognized is tested and calculated through the model formula;

[0053] (1) When the model output result has no solution, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed bed;

[0054] (2) When the model output result has a solution and Y > 2, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed bed;

[0055] (3) When the model output result has a solution and Y ≤ 2, further analysis and confirmation based on the value of the carbon stable isotope are required.

[0056] The above method for further analysis and confirmation based on the value of the carbon stable isotope is as follows:

[0057] Compare the carbon stable isotope of the sample to be recognized with the statistical threshold range of the carbon stable isotope of wild sea cucumbers in the target seaweed bed;

[0058] If the carbon stable isotope of the sample to be recognized is outside these two thresholds, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed bed;

[0059] If the carbon stable isotope of the sample to be recognized is within these two thresholds, it belongs to the wild sea cucumbers in the target seaweed bed.

[0060] Example 2

[0061] Based on the content of Example 1, this application provides a specific method for constructing an identification model of wild sea cucumbers in a seaweed bed based on stable isotopes, and the solution is as follows:

[0062] 1. Sea cucumber sample preparation

[0063] Select sampling sites for wild sea cucumber in seaweed beds. Collect 30 sea cucumber samples at each sampling point, ensuring that all samples are adult individuals that have reached sexual maturity and have a wet weight of over 200 g. After collection, store them in sterile food-grade plastic bags and preserve them at -20 °C before testing.

[0064] Pretreatment: Dissect the sea cucumber samples, remove the internal organs, select the body wall, and wash it thoroughly with pure water. After the treated samples are stored at -20 °C for 24 h until completely frozen, place them in a -50 °C freeze dryer and freeze-dry for 48 h. After drying, powder them with a grinder, pass through an 80-μm sieve, and store them dry for sample injection and detection on a stable isotope ratio mass spectrometer.

[0065] 2. Stable isotope detection of sea cucumber samples

[0066] Standard substances used for stable isotope detection of sea cucumber samples: IAEA-600: δ 13 C = -27.71‰; δ 15 N = 1‰; Acetanilide #1: δ 13 C = -26.85‰; δ 15 N = -4.21‰; USGS-40: δ 13 C = -36.39‰; δ 15 N = -4.52‰.

[0067] Instrument conditions include: Temperature of the oxidation tube (packing from top to bottom: quartz crucible, corundum beads, copper oxide, silver wire, quartz debris): 950 °C, temperature of the reduction tube (packing from top to bottom: silver wire, high-purity reduced copper): 600 °C; helium pressure: 0.12 MPa; helium flow rate: 200 mL / min; oxygen passing time: 20 s; oxygen flow rate: 40 mL / min;

[0068] Detection process of nitrogen stable isotope (δ 15 N) of wild sea cucumber:

[0069] Accurately weigh about 0.5 mg of freeze-dried powder sample of sea cucumber, wrap the sample with a 4×6 tin cup, and connect it to a stable isotope ratio mass spectrometer (Delta Q Advantages, Thermo Fisher TM ) to measure the total organic nitrogen (TON) and the total organic nitrogen stable isotope ratio (δ 15 N TON ) in the sample. Helium is used as the carrier gas with a flow rate of 90 mL / min, the reaction tube temperature is 950 °C, and the chromatographic column temperature is 50 °C. Calculate the nitrogen content in the sample based on the ratio of the peak area of nitrogen in the sample to the peak area of nitrogen in the standard sample, and its test accuracy is STD < 0.6‰. The nitrogen index is the percentage of organic nitrogen and the nitrogen isotope ratio with atmospheric nitrogen as the reference standard. The stable isotope ratio result is expressed as δ 15N represents that the precision STD < 0.3‰, and the calculation formula is as follows:

[0070]

[0071] 15 N / 14 N sample is the actual nitrogen isotope ratio of the sample; 15 N / 14 N air is the nitrogen isotope ratio of standard atmospheric nitrogen.

[0072] Table 1 δ 15 N TON Determination item index

[0073]

[0074] The detection process of the carbon stable isotope (δ 13 C) of wild sea cucumbers:

[0075] Accurately weigh about 10 mg of the powdered sample, wrap the sample with a 4×6 tin cup, and use a stable isotope mass spectrometer (DeltaQ Advantages, Thermo) to measure the total organic carbon content (TOC) and the total organic carbon stable isotope ratio (δ 13 C TOC ). Helium is used as the carrier gas with a flow rate of 90 mL / min, the reaction tube temperature is 950 °C, and the chromatographic column temperature is 50 °C. The carbon index is the percentage of organic carbon and the carbon isotope ratio based on VPDB (Vienna Peedee Belemnite); the stable isotope ratio result is expressed by δ 13 C, and its test precision is STD < 0.2‰. The formula is as follows:

[0076]

[0077] 13 C / 12 C sample is the actual carbon isotope ratio of the sample, 13 C / 12 C VPDB is the carbon isotope ratio of the international standard substance VPDB.

[0078] Table 2 δ 13 C TOC Determination item index

[0079]

[0080]

[0081] 3. Construction and Analysis of the Identification Model for Wild Sea Cucumbers

[0082] The process of identifying wild sea cucumbers is the core part of this patent, mainly divided into two steps: First, an identification model for wild sea cucumbers applicable to this seaweed bed is constructed using the nitrogen stable isotope values of wild sea cucumbers in the target seaweed bed and large algae in the seaweed bed, and then the model is used for identification. When identifying, it is mainly divided into two steps. One is to substitute the nitrogen stable isotope value of the sample to be identified into the model for calculation, and determine whether the sample belongs to the wild sea cucumbers in this seaweed bed according to the calculation result; if so, then further judgment is made by comparing the carbon stable isotope of the sample to be identified with the statistical threshold range of the carbon stable isotope of wild sea cucumbers in the target seaweed bed.

[0083] Specifically as follows:

[0084] 3.1 Identification of Wild Sea Cucumbers

[0085] 3.1.1 Identification Model of Wild Sea Cucumbers Relative to Large Algae in the Seaweed Bed

[0086] The model of the present invention is mainly based on the trophic level of wild sea cucumbers in the seaweed bed. For the identification process of the trophic level of wild sea cucumbers in the seaweed bed, first, the trophic level of the sea cucumber sample relative to the large algae in the seaweed bed is calculated. The calculation of the trophic level of the sea cucumber sample refers to the segmented trophic level formula, and the actual situation of wild sea cucumbers in the seaweed bed is mainly considered, and the calculation range is limited within the nitrogen stable isotope limit value (δ 15 N x ) of wild sea cucumbers in the seaweed bed based on statistical data, and the nitrogen stable isotope value (δ 15 N j ) of large algae in the seaweed bed is used as the calculation benchmark for the special calculation of identifying wild sea cucumbers in the seaweed bed.

[0087] The above-mentioned segmented trophic level formula can refer to: Hussey et al., 2014; Reum et al., 2015.

[0088] Specifically, through the hierarchical meta-analysis of experimental data, it is found that the fractionation coefficient Δδ 15 N has a linear relationship with the food source, and the formula is as follows:

[0089] Δδ 15 N = 5.92 - 0.27 × δ 15 N s ①

[0090] Among them, δ 15 N sis the nitrogen stable isotope value of the food source. The 95% highest posterior median (HPM) uncertainty intervals for the intercept (β0) and slope (β1) of the formula coefficients are [4.55, 7.33] and [-0.41, -0.14], respectively. This formula can be used to predict the δ 15 N value of the feeder from the food source and can further model the trophic level formula with the feeder trophic level as a function of δ 15 N.

[0091] To simulate and predict the δ 15 N value of the feeder, based on Equation ① and combined with the improved model of von Bertalanffy's δ 15 N enrichment model, we obtained Equation ②:

[0092]

[0093] where δ 15 N x is the saturated δ 15 N value increasing with the trophic level, δ 15 N j is the δ 15 N value of the baseline organism, k is the rate at which δ 15 N approaches δ 15 N x in each trophic level interval, and Y ss is the feeder trophic level relative to the baseline organism.

[0094] To solve for the absolute value Y ss of Y i , based on Equation ②, we added the Y j parameter and obtained the feeder trophic level Y i Equation ③ based on Equation ②:

[0095]

[0096] where δ 15 N lim and the k value are calculated using the following Equations ④ and ⑤ based on the aforementioned β0 and β1 values:

[0097]

[0098]

[0099] For further calculations specific to the identification of wild sea cucumbers in seaweed beds, we made targeted improvements based on Equation ③, using the large seaweeds in the seaweed bed as the baseline organisms, i.e., the δ 15The N value is used as the reference value δ 15 N j , the recognition model formula ⑥ for wild sea cucumbers in the seaweed field is obtained:

[0100]

[0101] Where:

[0102] δ 15 N x is the nitrogen stable isotope limit value of wild sea cucumbers in the target seaweed field;

[0103] δ 15 N x can be obtained by collecting wild sea cucumbers (at least 30 samples) in the target seaweed field for detection, and obtaining the upper limit value δ 15 N 15 N x of the N eigenvalue of these samples; in addition to this method, a meta-analysis method can also be used, that is, collecting historical data on the stable isotopes of wild sea cucumbers in the target seaweed field and statistically analyzing to obtain the upper limit value of the δ 15 N eigenvalue of wild sea cucumbers in the target seaweed field;

[0104] δ 15 N TL is the nitrogen stable isotope value of the sea cucumber to be recognized;

[0105] δ 15 N base is the nitrogen stable isotope value of the large algae in the target seaweed field;

[0106] This isotope value is the average nitrogen stable isotope of the large algae in the seaweed field, which is obtained by statistically analyzing at least 30 samples of the large algae in the target seaweed field.

[0107] Y j is the trophic level of the large algae in the target seaweed field. In the seaweed field, the large algae are the main nutrients of wild sea cucumbers. The large algae are primary producers and belong to the first trophic level. Therefore, the value of Y j is 1.

[0108] 3.1.2 Specific recognition process

[0109] Based on the above model formula, according to the nitrogen stable isotope value δ 15 N TL of the sea cucumber to be recognized: Calculate the specific TL value.

[0110] (1) When the output result of the model has no solution, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed field;

[0111] (2) When the output result of the model has a solution and Y > 2, the sample to be identified does not belong to the wild sea cucumber in the target seaweed bed;

[0112] (3) When the output result of the model has a solution and Y ≤ 2, further analysis and confirmation based on the value of carbon stable isotope are required;

[0113] (3-1) Compare the carbon stable isotope of the sample to be identified with the statistical threshold range of the carbon stable isotope of the wild sea cucumber in the target seaweed bed.

[0114] If the value of the carbon stable isotope of the sample to be identified is outside the statistical threshold range of the carbon stable isotope of the wild sea cucumber in the target seaweed bed, the sample to be identified does not belong to the wild sea cucumber in the target seaweed bed;

[0115] If the value of the carbon stable isotope of the sample to be identified is within the statistical threshold range of the carbon stable isotope of the wild sea cucumber in the target seaweed bed, the sample to be identified belongs to the wild sea cucumber in the target seaweed bed.

[0116] During the identification process, due to testing, human interference, accidental factors, etc., a certain error rate will be caused. However, since the samples in this identification process are in large quantities, individual escaped ones can be ignored. If the identification rate of the whole batch of samples of wild sea cucumbers in the seaweed bed reaches more than 95%, the whole batch of samples can be considered to be wild in the seaweed bed according to probability. If individual adulteration problems are considered, the identification and certification levels can be further divided for batches with an identification rate of more than 95%. For example, 95% is the third level, 95%-98% is the second level, 98%-100% is the first level, and so on.

[0117] Based on the above model construction method, an identification model applicable to the wild sea cucumbers in a certain area can be constructed. For example, the identification model of wild sea cucumbers applicable to the seaweed beds near Changshan Archipelago constructed below in this application.

[0118] Specific experimental example:

[0119] Based on the models and methods of Example 1 and Example 2, this application constructs an identification model of wild sea cucumbers applicable to the seaweed beds near Changshan Archipelago and conducts identification based on this model.

[0120] 1. Sea cucumber sample preparation

[0121] In this case, 50 wild sea cucumber samples collected from the seaweed beds near Changshan Archipelago were randomly selected to establish the basic model for the target sea area. The samples were respectively collected from 4 sampling sites in Changshan Archipelago: 10 samples from Daqin Island, 10 samples from Cheyou Island, 20 samples from Tuoji Island, and 10 samples from Gaoshan Island.

[0122] All samples were adult individuals that had reached sexual maturity, with an individual wet weight of over 200 g. After collection, they were stored in sterile food-grade plastic bags and cryopreserved at -20 °C before testing. Pretreatment: By dissecting the sea cucumber samples, the viscera were removed, and the body wall was selected, then washed clean with pure water. The processed samples were placed at -20 °C for 24 h until completely frozen, then placed in a -50 °C freeze dryer and freeze-dried for 48 h. After drying, they were powdered with a grinder, passed through an 80-μm sieve, and stored dry for loading and testing on a stable isotope ratio mass spectrometer.

[0123] 2. Detect the stable isotopes of sea cucumber samples according to the method of Example 1 or 2, and the detection results are shown in Table 1.3.

[0124] After detection, the carbon and nitrogen stable isotope data of 50 wild sea cucumber samples in the nearshore seaweed beds of Changshan Archipelago were obtained, as shown in Table 3, and this data was used as the basis for modeling and identification.

[0125] Table 3 Stable Isotope Detection Data of Wild Sea Cucumber Samples in the Seaweed Beds of Changshan Archipelago

[0126]

[0127]

[0128] 3.1 Construction of an Identification Model for Wild Sea Cucumbers in the Seaweed Beds of Changshan Archipelago Based on Stable Isotopes

[0129] Based on the statistical data of 50 wild sea cucumber samples in the nearshore waters of Changshan Archipelago, the relevant parameters required for constructing the model formula were obtained.

[0130]

[0131] Among them:

[0132] (1) δ 15 N x is the nitrogen stable isotope limit value of wild sea cucumbers in the target seaweed bed. Through the statistical data of 50 wild sea cucumber samples, the upper limit of the statistical value of the nitrogen stable isotope data of wild sea cucumbers in the target seaweed bed, 8.96‰, is adopted here;

[0133] (2) δ 15 N y is the nitrogen stable isotope value of the sea cucumber to be identified;

[0134] (3) δ 15 N j is the nitrogen stable isotope value of the macroalgae in the target seaweed bed; that is, the average nitrogen stable isotope value of the macroalgae in the Changdao seaweed bed, which is obtained by calculating the average value of 117 samples of the macroalgae in the target seaweed bed through statistical analysis as 8.13‰;

[0135] (4) Yj is the trophic level of macroalgae in the target seaweed bed; that is, the trophic level of macroalgae in the Changdao seaweed bed. The algae are primary producers and belong to the first trophic level, so Y j is set to 1.

[0136] Through parameter supplementation based on the statistical data of wild sea cucumbers, the following model formula is obtained:

[0137]

[0138] Based on the above model formula, the value of Y can be obtained through the nitrogen stable isotope value δ 15 N y of the sea cucumber to be identified, and then the following method is used for identification.

[0139] (1) When the model output result has no solution, the sample to be identified does not belong to the wild sea cucumbers in the target seaweed bed;

[0140] (2) When the model output result has a solution and Y > 2, the sample to be identified does not belong to the wild sea cucumbers in the target seaweed bed;

[0141] (3) When the model output result has a solution and Y ≤ 2, further analysis and confirmation based on the value of carbon stable isotope are required;

[0142] (3-1) Compare the carbon stable isotope of the sample to be identified with the statistical threshold range of the carbon stable isotope of wild sea cucumbers in the target seaweed bed.

[0143] If the carbon stable isotope of the sample to be identified is outside these two thresholds, the sample to be identified does not belong to the wild sea cucumbers in the target seaweed bed;

[0144] If the carbon stable isotope of the sample to be identified is within these two thresholds, it belongs to the wild sea cucumbers in the target seaweed bed.

[0145] 4. Verification of identification results

[0146] In this case, 50 bottom-sown sea cucumber samples, 39 cultured sea cucumber samples, and 30 wild sea cucumber samples collected from the offshore area of the Changshan Archipelago were randomly selected to conduct reverse verification on the identification accuracy of this patent.

[0147] When verifying the identification, the δ 13 C(‰) and δ 15 N(‰) of the samples were detected respectively, and the Y value of each sea cucumber sample was obtained from the model constructed above. The specific results are shown in the following table:

[0148] Table 4 Stable isotope detection and Y value of samples to be identified

[0149]

[0150]

[0151]

[0152]

[0153] As can be seen from the above table, for the recognition model constructed based on this patent, corresponding to the nitrogen stable isotope value (δ 15 N) of the sea cucumber samples, the recognition results of 50 bottom-sown sea cucumber samples in the Changshan Archipelago show that reasonable values could not be calculated for 43 samples (i.e., these 43 samples do not belong to the wild sea cucumbers in the Changdao seaweed bed). Among the 7 samples for which the Y value was calculated, 2 had Y ≤ 2 (i.e., the other 5 also do not belong to the wild sea cucumbers in the Changdao seaweed bed). Among the 50 bottom-sown sea cucumber samples, a total of 2 temporarily meet the recognition criteria for wild sea cucumbers in the seaweed bed of this patent, numbered CDHG 02 and CDHG 06, and enter the next recognition process.

[0154] Among the 39 cultured samples, reasonable values could not be calculated for 33 samples (i.e., these 33 samples do not belong to the wild sea cucumbers in the Changdao seaweed bed). Among the 6 samples for which the results were calculated, 3 had Y ≤ 2 (i.e., the other 3 also do not belong to the wild sea cucumbers in the Changdao seaweed bed); among the 39 cultured sea cucumber samples, a total of 3 temporarily meet the recognition criteria for wild sea cucumbers in the seaweed bed of this patent, numbered CDMDYZ 01, CDMDYZ 16, and CDMDYZ 29, and enter the next recognition process.

[0155] Reasonable values were calculated for all 30 wild samples. Among the 29 samples for which the results were calculated, 29 had Y ≤ 2 (i.e., only 1 was identified as not belonging to the wild sea cucumbers in the Changdao seaweed bed); among the 30 wild sea cucumber samples, a total of 29 temporarily meet the recognition criteria for wild sea cucumbers in the seaweed bed of this patent. The numbers are shown in Table 5 and enter the next recognition process.

[0156] Table 5 Sea cucumber samples that need further confirmation are as follows

[0157]

[0158]

[0159] 4.2 Compare the carbon stable isotope of the sample to be recognized with the statistical threshold range of the carbon stable isotope of wild sea cucumbers in the target seaweed bed;

[0160] The statistical threshold range of the carbon stable isotope (δ 13 C) of wild sea cucumbers in the Changdao seaweed bed is from -22.04‰ to -18.05‰ (from Table 1.3). Through the carbon stable isotope (δ 13C) Comparison of values. Samples numbered CDHG02, CDMDYZ01, CDMDYZ16, CDMDYZ29, CDYS02, and CDYS03 were determined not to be wild sea cucumbers from the seaweed beds in Changdao. Finally, the samples determined to be wild sea cucumbers from the seaweed beds in Changdao are shown in the following table.

[0161] Table 6 Samples of Wild Sea Cucumbers from the Seaweed Beds in Changdao

[0162]

[0163]

[0164] 4.3 Statistical Results of Identification

[0165] In this case, the sea cucumbers in the seaweed beds near the Changshan Archipelago were identified and verified. The results showed that the identification accuracy rate of 50 bottom-sown sea cucumber samples was 98%; the identification accuracy rate of 39 cultured samples was 100%; the identification accuracy rate of 30 wild sea cucumber samples from the Changshan Archipelago was 90.0%. Combining a total of 119 samples from the three sources of sea cucumbers, 115 samples were accurately identified, and the comprehensive identification accuracy rate was 96.6%.

[0166] As mentioned above, it is only a preferred embodiment of the present invention and does not impose any formal restrictions on the present invention. Although the present invention has been disclosed as above with a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to the above-disclosed technical content to form equivalent embodiments with equivalent changes within the scope of the technical solution of the present invention. However, as long as it does not depart from the content of the technical solution of the present invention, any brief modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for identifying wild sea cucumbers in seaweed beds based on stable isotopes, characterized in that, Use A recognition model for wild sea cucumbers in seaweed beds based on stable isotopes, characterized in that the model is as follows: Where: δ 15 N x is the upper limit of the nitrogen stable isotope characteristic value of wild sea cucumbers in the target seaweed bed; δ 15 N Y is the nitrogen stable isotope value of the sea cucumber to be identified; δ 15 N j is the average value of the nitrogen stable isotope of the large algae in the target seaweed bed; Y j is the trophic level of macroalgae in the target seaweed bed; During recognition, test the nitrogen stable isotope value of the sea cucumber to be recognized and calculate through the model formula; (1) When the model output result has no solution, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed bed; (2) When the model output result has a solution and Y > 2, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed bed; (3) When the model output result has a solution and Y ≤ 2, further analysis and confirmation based on the value of carbon stable isotope are required; The above method for further analysis and confirmation based on the value of carbon stable isotope is: Compare the carbon stable isotope value of the sample to be recognized with the statistical threshold range of the carbon stable isotope of wild sea cucumbers in the target seaweed bed; If the carbon stable isotope of the sample to be recognized is outside these two thresholds, the sample to be recognized does not belong to the wild sea cucumbers in the target seaweed bed; If the carbon stable isotope of the sample to be recognized is within these two thresholds, it belongs to the wild sea cucumbers in the target seaweed bed.

2. The recognition method according to claim 1, characterized in that, When constructing the model, By collecting multiple wild sea cucumber samples from the target seaweed bed for detection, the upper limit value δ 15 N eigenvalue δ 15 N x ; The meta-analysis method can also be used to collect historical data on the stable isotopes of wild sea cucumbers in the target seaweed bed, and statistically analyze to obtain the upper limit value of the δ 15 N x eigenvalue of wild sea cucumbers in the target seaweed bed.

3. The recognition method according to claim 2, wherein When constructing the model, By statistically analyzing multiple samples of macroalgae in the target seaweed bed, the average value of the nitrogen stable isotope of macroalgae in the target seaweed bed, δ 15 N j , is calculated.

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