Method for assessing fish health
By acquiring target status monitoring data from multiple environmental data dimensions, calculating evaluation coefficients, and combining them with regression equations to verify values, this approach solves the problems of cumbersome calculations and large errors in existing fish health assessment technologies. It achieves rapid and accurate fish health assessment, providing an important reference for ecological and environmental impact assessments and fish protection measures.
Patent Information
- Application Number
- CN202211480789.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-11-24
- Publication Date
- 2026-01-30
- Estimated Expiration
- 2042-11-24
AI Technical Summary
Existing fish health assessment methods are cumbersome to calculate and prone to errors, making it difficult to quickly and accurately assess environmental impacts. Current technologies are also insufficient to provide effective references in ecological and environmental impact assessments or fish protection measures.
By acquiring target status monitoring data from multiple environmental data dimensions, calculating evaluation coefficients, and combining them with regression equation validation values, a rapid and accurate fish health assessment can be achieved.
It provides rapid and accurate fish health assessment results, offering important references for ecological and environmental impact assessments and fish protection measures.
Smart Images
Figure CN115759851B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of water resource ecological environment protection, in particular to a fish health assessment method. BACKGROUND
[0002] With the development of social economy, water resources are continuously developed and utilized, and the water ecological environment in China is getting serious, especially with the expansion of high dam reservoirs and other water conservancy projects, the total dissolved gas (TDG) supersaturation downstream of the dam, lake and reservoir eutrophication, new pollutants and other water ecological environment problems have not been fundamentally solved, which affects the safe operation of the water ecological system, especially the survival and development of fish. Therefore, studying the fish health assessment method has important ecological environmental significance for the formulation of environmental protection programs and fish protection measures.
[0003] Currently, the existing fish health assessment methods in the prior art usually use the mortality and death time of fish collected under the stress of specific environmental factors to determine the degree of influence or survival ability. Due to the differences between individual fish, some fish show concentrated death, i.e. shorter death time, and some fish have longer death time, so the death situation is quite different, the calculation process is complicated, and the accuracy of the evaluation results is relatively rough.
[0004] To solve the above problems, some people have proposed using the semi-lethal time (using the common logarithm of the death time of fish individuals as the horizontal coordinate, and the probability unit of the mortality rate as the vertical coordinate, and obtaining it through a regression equation) to evaluate fish, but this evaluation method requires half of the fish to die to calculate; therefore, using semi-lethal time as an evaluation index, the calculation is complicated and has certain limitations, and the evaluation results have relatively large errors due to the differences between individual fish, which are not accurate, only a single analysis method or analysis and evaluation based on a single environmental factor can be realized, the efficiency is low, and it is difficult to quickly and effectively distinguish in ecological environment impact assessment or fish protection measures.
[0005] In summary, how to quickly determine the degree of influence of environmental factors on fish has important reference value and practical significance for ecological environment impact assessment or the proposal of fish protection measures, therefore, we propose a fish health assessment method. SUMMARY
[0006] The purpose of the present application is to provide a fish health assessment method to solve the problems of insufficient research, complicated process calculation and certain limitations of the existing fish health assessment methods in the background art, and to quickly determine the evaluation results of fish affected by environmental factors, thereby providing important reference value for ecological environment impact assessment and the proposal of fish protection measures.
[0007] The present application provides a fish health assessment method, the method comprising:
[0008] Obtaining target state monitoring data of at least one target fish species under at least one environmental data dimension;
[0009] Based on the target state monitoring data of at least one environmental data dimension, the evaluation coefficient of the health status of the at least one target fish species under at least one environmental data dimension is obtained respectively;
[0010] Based on the evaluation coefficient, the health status of the target fish species is determined and the initial evaluation result is obtained;
[0011] Obtaining the target fish species health status verification value, based on the verification value, obtaining the final evaluation result of the target fish species.
[0012] Further, based on the target state monitoring data of at least one environmental data dimension, the evaluation coefficient of the health status of the at least one target fish species under at least one environmental data dimension is obtained respectively, which further comprises:
[0013] Based on at least one environmental data dimension, at least two groups of target working condition data corresponding to the target fish species and target state monitoring data corresponding to the two groups of target working condition data are determined and obtained;
[0014] Obtaining the evaluation coefficient under the comparison of the two groups of target state monitoring data.
[0015] Further, the calculation formula of the evaluation coefficient of the health status of the target fish species under any target working condition data in the environmental data dimension is:
[0016]
[0017] Wherein, A i is the evaluation coefficient, C0is the first target working condition data corresponding to at least one environmental data; T0is the target state monitoring data corresponding to the first target working condition data; C i is the second target working condition data corresponding to at least one environmental data dimension; T i is the target state monitoring data corresponding to the second target working condition data.
[0018] Further, based on the evaluation coefficient, the health status of the target fish species is determined and the initial evaluation result is obtained, which specifically comprises:
[0019] Based on the evaluation coefficient under the comparison of the two groups of target state monitoring data, the initial evaluation result is obtained by the following formula:
[0020]
[0021] The evaluation coefficient Ai Input the value into formula (2) to determine the impact of environmental data dimensions on the health status of the target fish species and obtain the initial assessment results.
[0022] Furthermore, obtaining the health status verification value of the target fish species specifically includes:
[0023] Using the logarithm of the target state monitoring data as the independent variable x, and pre-setting a dependent variable y, a regression equation is established, and the slope and slant distance of the regression equation line are obtained.
[0024] Furthermore, the formula for calculating the health status verification value of the target fish species is as follows:
[0025] P(C) = R(c) e )×lgT+J(c e ), formula (3);
[0026] Where P(C) is the probability unit of the validation value; R(c) e J(c) is the slope of the regression equation line; T is the preset time (h) for the target fish species to be under the target working conditions; J(c) is the slope of the regression equation line. e ) is the slope distance of the regression equation line; c e It is the numerical value of the target operating condition data.
[0027] Furthermore, based on the verification value, obtaining the final evaluation result for the target fish species also includes:
[0028] The final evaluation result for the target fish species is obtained by analyzing and comparing the initial evaluation results with the verification values.
[0029] Furthermore, the environmental data dimensions include at least: environmental TDG saturation data, environmental sediment content data, environmental temperature data, and environmental pollutant content data.
[0030] Furthermore, the target monitoring data includes at least: the average lethal time of the target fish species, the number of target fish species killed, and the fatigue time of the target fish species during exercise.
[0031] Furthermore, the environmental pollutant content data includes at least: inorganic pollutant content and organic pollutant content.
[0032] The beneficial effects of this invention include:
[0033] 1.The present application realizes health assessment of fish for multiple environmental data dimensions, multiple target state monitoring data and multiple fish species by obtaining target state monitoring data under multiple environmental data dimensions, and can quickly calculate the evaluation coefficient of fish under environmental data dimensions through the calculation formula of the evaluation coefficient, further assesses the initial assessment result of the influence of environmental data dimension change on fish health through the evaluation coefficient, and verifies it through the verification value to ensure the accuracy of the initial assessment result, and provides valuable reference basis for ecological environmental impact assessment and fish protection measures. BRIEF DESCRIPTION OF DRAWINGS
[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly introduced as follows. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.
[0035] Figure 1 The flowchart of the fish health assessment method provided by the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION
[0036] The technical solutions in the embodiments of the present application will be described in detail below with reference to the drawings in the embodiments of the present application.
[0037] It should be noted that: similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present application, the terms "first", "second" and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.
[0038] The present application provides a fish health assessment method, which comprises:
[0039] Step S1: obtaining target state monitoring data of at least one target fish species under at least one environmental data dimension;
[0040] At least one target fish species can be, for example, freshwater fish such as rosy bitterling, carp, crucian carp, sturgeon, etc.; at least one environmental data dimension can be, for example, environmental TDG saturation data, environmental temperature data, environmental silt content data, and environmental pollutant content data, which can be, for example, heavy metals, microplastics, inorganic salts, and other inorganic pollutants, and can also be, for example, phenols, halogenated hydrocarbons, benzene compounds, and other organic pollutants; the target monitoring data can be, for example, average lethal time of target fish species, target fish species death number, target fish species half lethal time, target fish species movement fatigue time, target fish species mortality, and other data parameters related to fish health, wherein the average lethal time of target fish species refers to the average lethal time of several experimental fish under a certain working condition of the target fish species under the environmental data dimension, the half lethal time of the target fish species refers to the half death time of the experimental fish under a certain working condition of the target fish species under the environmental data dimension, and the movement fatigue time of the target fish species refers to the time of swimming to a fatigue state under a certain working condition of the target fish species under the environmental data dimension; the target fish species mortality refers to the proportion of the number of experimental fish deaths to the total number of experimental fish under a certain working condition of the target fish species under the environmental data dimension; it should be noted that the present disclosure is not limited to the above target fish species, environmental data dimension and target monitoring data, and can be other target fish species that can be evaluated by the fish health evaluation method of the present disclosure, other environmental data dimensions affecting fish health evaluation method, and other target monitoring data as reference data for fish health, which will not be described here.
[0041] Step S2: obtaining evaluation coefficients of the health status of the at least one target fish species under at least one environmental data dimension based on the target state monitoring data of the at least one environmental data dimension;
[0042] In step S2, the following steps are further included:
[0043] Step S2.1: determining and obtaining at least two groups of target working condition data corresponding to the target fish species and target state monitoring data corresponding to the two groups of target working condition data based on at least one environmental data dimension;
[0044] Step S2.2: obtaining evaluation coefficients under comparison of the two groups of target state monitoring data.
[0045] Step S3: determining the health status of the target fish species based on the evaluation coefficients and obtaining an initial evaluation result;
[0046] Step S4: obtaining a target fish health status verification value, and obtaining a final evaluation result of the target fish species based on the verification value.
[0047] For example, the calculation formula of the evaluation coefficient of the health status of the target fish species under any target working condition data in the environmental data dimension is:
[0048]
[0049] Among them, A i These are evaluation coefficients. C0 represents the first target operating condition data corresponding to at least one environmental data point; T0 represents the target status monitoring data corresponding to the first target operating condition data; C i It is the second target operating condition data corresponding to at least one environmental data dimension; T i It is the target status monitoring data corresponding to the second target working condition data.
[0050] For example, determining the health status of a target fish species and obtaining initial assessment results based on evaluation coefficients specifically includes:
[0051] Based on the evaluation coefficients obtained from comparing two sets of target status monitoring data, the initial evaluation result is then obtained using the following formula:
[0052]
[0053] Evaluation coefficient A i Input the value into formula (2) to determine the impact of environmental data dimensions on the health status of the target fish species and obtain the initial assessment results; the specific discrimination method is as follows: when A i When A > 0, the impact on fish health decreases under the environmental data dimension; when A i When A = 0, there is no impact on the health status of fish under the environmental data dimension; when A i When the value is less than 0, the impact of environmental data on the health status of fish increases.
[0054] For example, obtaining the health status verification value of the target fish species specifically includes:
[0055] Using the logarithm of the target state monitoring data as the independent variable x, and pre-setting a dependent variable y, a regression equation is established, and the slope and slant distance of the regression equation line are obtained.
[0056] For example, the formula for calculating the health status verification value of the target fish species is:
[0057] P(C) = R(c) e )×lgT+J(c e ), formula (3);
[0058] Where P(C) is the probability unit of the validation value; R(ce) is the slope of the regression equation line; T is the preset time (h) for the target fish species to be under the target working conditions; J(c e ) is the slope distance of the regression equation line; c e It is the numerical value of the target working condition data; the larger the value of the verification value, the smaller the impact on the health status of the fish.
[0059] For example, based on the verification value, obtaining the final evaluation result of the target fish species further includes:
[0060] Based on the initial evaluation result and the verification value, the final evaluation result of the target fish species is obtained by analysis and comparison.
[0061] The following describes the evaluation method for the three target fish species of rosy bitterling, common carp, and sturgeon under the TDG saturation environment data dimension using the fish health evaluation method provided by the present disclosure. In this embodiment, TDG saturation of 125%, 130%, 135%, and 140% are selected as the target working condition data of the TDG environment data dimension, and TDG saturation of 130% is selected as the control group (which can be any one of the four target working condition data). If it is used for other target fish species or other environment data dimensions or other target working condition data, only the obtained experimental data needs to be changed, and details are not described here. The following describes the embodiment in detail:
[0062] Step 1: As shown in Tables 1 and 3, the target state monitoring data of the three target fish species of rosy bitterling, common carp, and sturgeon under the above four target working condition data of the TDG environment data dimension for the death time is obtained.
[0063] Table 1 is a table of death data of rosy bitterling under different TDG saturation conditions.
[0064]
[0065] Table 1 is a table of death data of rosy bitterling under different TDG saturation conditions.
[0066] Table 2 is a table of death data of common carp under different TDG saturation conditions.
[0067]
[0068] Table 2 is a table of death data of common carp under different TDG saturation conditions.
[0069] Table 3 is a table of death data of sturgeon under different TDG saturation conditions.
[0070]
[0071] Table 3 is a table of death data of sturgeon under different TDG saturation conditions.
[0072] Step 2: According to the target state monitoring data provided in Tables 1-3, the average mortality time of the three target fish species under the four target working conditions is calculated, and the above formula (1) is inputted, and the evaluation coefficient is obtained by calculation as shown in Table 4:
[0073] Table 4 A of target fish species under four working conditions i value
[0074] 125％ 130％ 135％ 140％ i 0.475 0 -0.265 -0.870 Carp (A i Values) 0.358 0 -0.657 -0.680 sturgeon (A i values)]]> 0.028 0 -0.220 -0.633
[0075] Table 4 is the evaluation coefficient value of the rosy fish, carp and sturgeon under the four target working conditions;
[0076] Step 3: The evaluation coefficient A i value calculated in Table 4 in step 2 is inputted into the above formula (3), and the initial evaluation result is obtained. It can be understood that the A i value of the three target fish species is greater than 0 when the TDG saturation is 125%, and the working condition has a reduced impact on the health status of the three target fish species; it can also be understood that the A i value of the three target fish species is equal to 0 when the TDG saturation is 130%, and the working condition has no impact on the health status of the three target fish species; it can also be understood that the A i value of the three target fish species is less than 0 when the TDG saturation is 135% and 140%, and the working condition has an increased impact on the health status of the three target fish species; and the initial evaluation result of the three target fish species under the four working conditions is obtained;
[0077] Step 4: The verification value is calculated by the above formula (3) based on the mortality time data in Tables 1-3, which is specifically:
[0078] Step 4.1: Convert the mortality time data of the target fish species into logarithm;
[0079] Step 4.2: Calculate the mortality rate of the target fish species and convert it through Table 5 to obtain the converted value, and then calculate through formula (3) to obtain the data in Table 6;
[0080] Table 5 Conversion relationship table of mortality rate and probability unit
[0081]
[0082] Table 5 is the conversion relationship table of mortality rate and probability unit;
[0083] Table 6 Verification value of three target fish species under four working conditions
[0084] 125％ 130％ 135％ 140％ Amur pike 27.47 14.9 10.01 5.16 Common carp 22.49 14.03 5.96 5.33 Sturgeon 22.17 21.20 15.60 5.80
[0085] Table 6 is the verification value of the health status of rosy fish, carp and sturgeon under four working conditions;
[0086] According to Table 6, it can be understood that the verification values of the three target fish species are obviously increased compared with the control group (TDG saturation 130%) when the TDG saturation is 125%, and the working condition reduces the influence on the health status of the three target fish species; it can also be understood that the verification values of the three target fish species are obviously reduced compared with the control group (TDG saturation 130%) when the TDG saturation is 135% and 140%, and the working condition increases the influence on the health status of the three target fish species; further, it can be understood that after comparing the initial evaluation results with the verification results of the above verification values, the evaluation results of the initial evaluation results and the verification values are consistent, so as to determine the final evaluation results;
[0087] In summary, the embodiment realizes the health evaluation of the target fish species under the environment data dimension by obtaining the target state monitoring data of the death time under the TDG environment data dimension, the evaluation coefficient of the fish under the environment data dimension can be quickly calculated through the calculation formula of the evaluation coefficient, the initial evaluation result of the influence of the change of the environment data dimension on the health of the fish is further evaluated, the accuracy of the initial evaluation result is further verified through the verification value, and valuable important reference basis is provided for the development of the environmental protection scheme and the fish protection measures.
[0088] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.
Claims
1. A method for assessing the health of fish, characterized in that, The method comprises: acquiring target state monitoring data of at least one target fish species in at least one environmental data dimension; acquiring evaluation coefficients of the health state of the at least one target fish species in at least one environmental data dimension based on the target state monitoring data of at least one environmental data dimension, specifically comprising: determining and acquiring at least two groups of target working condition data and target state monitoring data corresponding to the two groups of target working condition data of the corresponding target fish species based on at least one environmental data dimension; acquiring evaluation coefficients under comparison of two groups of target state monitoring data, and the calculation formula of the evaluation coefficients is: , equation (1); wherein, is an evaluation coefficient; is target state monitoring data corresponding to the first target working condition data; is second target working condition data corresponding to at least one environmental data dimension; is target state monitoring data corresponding to the second target working condition data; judging the health state of the target fish species based on the evaluation coefficients and acquiring an initial evaluation result; acquiring a verification value of the health state of the target fish species, acquiring a final evaluation result of the target fish species based on the verification value, and specifically comprising: taking the logarithm of the target state monitoring data as the independent variable x, presetting a dependent variable y, establishing a regression equation and obtaining the slope of the regression equation straight line and the slope distance of the regression equation straight line; the calculation formula of the verification value of the health state of the target fish species is: , equation (3); wherein, is a probability unit of the verification value; is a slope of a straight line of the regression equation; is a preset time (h) of the target fish species under the target working condition data; is a slope distance of the straight line of the regression equation; is a numerical value of the target working condition data.
2. The fish health assessment method according to claim 1, characterized in that, judging the health state of the target fish species based on the evaluation coefficients and acquiring an initial evaluation result specifically comprises: acquiring an initial evaluation result based on the evaluation coefficients under comparison of two groups of target state monitoring data and through the following formula: , equation (2); The evaluation coefficient The value is input into formula (2), the influence of the environmental data dimension on the health status of the target fish species is judged, and an initial evaluation result is obtained.
3. The fish health assessment method of claim 1, wherein, acquiring a final evaluation result of the target fish species based on the verification value further comprises: analyzing and comparing the initial evaluation result and the verification value to acquire the final evaluation result of the target fish species.
4. The fish health assessment method according to any one of claims 1 to 3, characterized in that, The environmental data dimensions at least include: environmental TDG saturation data, environmental silt content data, environmental temperature data, and environmental pollutant content data.
5. The fish health assessment method according to claim 4, wherein The target monitoring data at least includes: target fish species average lethal time, target fish species lethal number, and target fish species movement fatigue time.
6. The fish health assessment method according to claim 4, wherein, The environmental pollutant content data at least includes: inorganic pollutant content and organic pollutant content.