Marine ranching pest and disease risk assessment method

Abstract

The invention belongs to the technical field of risk assessment systems, and discloses a marine ranch disease and pest risk assessment method, which comprises the following steps: acquiring multiple risk index data influencing marine ranch diseases and pests in real time, and determining the risk level of each risk index according to the multiple risk index data; determining the relative weight of the plurality of risk indexes based on the relative influence among the plurality of risk indexes by adopting an analytic hierarchy process; and according to the risk levels and the relative weights of the plurality of risk indexes, determining a comprehensive risk index of marine ranch diseases and insect pests, and according to the comprehensive risk index, performing marine ranch disease and insect pest risk assessment. According to the invention, through integration of monitoring data and risk indexes, quantitative evaluation of pest and disease damage risks is realized, and risk identification and early warning capabilities are improved. The morbidity, mortality and propagation speed of diseases and insect pests can be analyzed carefully, the risk levels of the whole marine ranch and specific diseases and insect pests are accurately determined, and a clear basis is provided for taking treatment measures or not.

Description

Technical Field

[0001] The invention discloses a marine ranch pest risk assessment method, belonging to the technical field of risk assessment systems. Background Art

[0002] Marine ranching is an important way to sustainably utilize fishery resources. The health and stability of its ecosystem is directly related to the output and quality of fishery resources. However, pests and diseases are one of the main threats to marine ranching, and their risk assessment and management still face many challenges.

[0003] At present, the risk assessment system for marine pests and diseases is not yet mature, and there is a lack of comprehensive and accurate disease and environmental monitoring data, which makes it difficult to build an accurate risk assessment model. Existing monitoring means and methods are often limited by technical level and resource investment, and cannot achieve real-time monitoring and early warning of pests and diseases, thus missing the best prevention and control opportunities.

[0004] At the same time, due to the lack of an effective early warning mechanism, early identification and response to diseases were not timely, causing pests and diseases to spread rapidly in marine ranches, causing serious impacts on the ecosystem. In addition, existing management measures have failed to fully respond to the challenges posed by pests and diseases, lacking specificity and systematization, resulting in limited prevention and control effects.

[0005] The backwardness of technical means also limits the accuracy and efficiency of disease monitoring and early warning. Traditional monitoring methods often rely on manual observation and sampling, which is not only time-consuming and labor-intensive, but also susceptible to interference and errors caused by human factors. Therefore, it is urgent to develop more advanced and efficient technical means to improve the accuracy and efficiency of disease monitoring and early warning. Summary of the invention

[0006] The purpose of the present invention is to provide a method for risk assessment of marine ranch pests and diseases to solve the technical problem that the existing technology cannot realize real-time monitoring and early warning of pests and diseases, thus missing the best prevention and control opportunity. To achieve the above purpose, the present invention proposes a method for risk assessment of marine ranch pests and diseases, and the specific scheme is as follows:

[0007] A method for risk assessment of pests and diseases in marine ranches, comprising:

[0008] Step 1: acquiring multiple risk indicator data of pests and diseases affecting marine ranches in real time, and determining the risk level of each risk indicator according to the multiple risk indicator data;

[0009] Step 2: using the analytic hierarchy process to determine the relative weights of the multiple risk indicators based on the relative influences between the multiple risk indicators;

[0010] Step 3: Determine a comprehensive risk index of marine ranch pests and diseases based on the risk levels and relative weights of the multiple risk indicators, and conduct a marine ranch pest and disease risk assessment based on the comprehensive risk index.

[0011] Preferably, the step 3 further includes:

[0012] Identify the pests and diseases of the marine ranch as specific pests and diseases;

[0013] The corresponding pest and disease management strategy is determined according to the risk index corresponding to the specific pest and disease.

[0014] Preferably, the step 2 specifically includes:

[0015] constructing a comparison matrix according to the relative influences between the multiple risk indicators;

[0016] The comparison matrix is ​​normalized to determine the relative weight of each risk indicator.

[0017] Preferably, after constructing the comparison matrix, the method further includes:

[0018] A consistency check is performed on the comparison matrix to determine whether the comparison matrix meets the consistency requirement.

[0019] Preferably, performing a consistency check on the comparison matrix specifically includes:

[0020] Calculating the consistency index of the comparison matrix, and obtaining the average random consistency index corresponding to the comparison matrix;

[0021] Determine a consistency ratio according to the consistency index and the average random consistency index, and judge whether the comparison matrix meets the consistency requirement according to the consistency ratio;

[0022] If not, the relative influences between the multiple risk indicators are redetermined until the comparison matrix meets the consistency requirement.

[0023] Preferably, after performing the marine ranch pest risk assessment according to the comprehensive risk index, the method further includes:

[0024] The comprehensive risk level of pests and diseases in the marine ranch is determined based on the comprehensive risk index.

[0025] Preferably, risk indicators include morbidity, mortality and rate of spread.

[0026] Preferably, a hierarchical matrix model is used to determine the risk index of the specific pests and diseases.

[0027] Preferably, the risk index of the specific pests and diseases is determined based on the morbidity, mortality and propagation speed of the specific pests and diseases acquired in real time.

[0028] Beneficial effects: The marine ranch pest and disease risk assessment method constructed by the present invention has brought significant beneficial effects to marine ranch pest and disease management. This method realizes the quantitative assessment of pest and disease risks by integrating monitoring data and risk indicators, greatly improving the risk identification and early warning capabilities. Specifically, it can carefully analyze the incidence, mortality and transmission rate of pests and diseases, accurately determine the risk level of the marine ranch as a whole and specific pests and diseases, and provide a clear basis for whether to take control measures. On this basis, it can be used to guide the formulation of detailed control strategies, effectively respond to pest and disease threats, reduce their adverse effects on the marine ranch ecosystem, and effectively ensure the sustainable development of marine ranches.

[0029] In addition, this method provides a scientific basis for marine ranch management, making the formulation of management strategies more accurate and effective. By implementing these strategies, the ecological and economic benefits of marine ranches can be significantly improved, and the rational use and protection of fishery resources can be promoted. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 The figure is a schematic diagram of the process of the marine ranch pest and disease risk assessment method of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with specific implementation methods. It should be understood that the specific implementation methods described here are only used to explain the present invention and do not limit the scope of protection of the present invention.

[0032] The present invention proposes a marine ranch pest risk assessment method. The following will take this method as the core and explain its specific application steps in the marine ranch of Nan'ao Island in Shantou.

[0033] Step 1: acquiring multiple risk indicator data of pests and diseases affecting marine ranches in real time, and determining the risk level of each risk indicator according to the multiple risk indicator data;

[0034] Specifically, molecular biological detection technology (such as PCR technology, loop-mediated isothermal amplification technology, etc.) and underwater robots (equipped with high-definition cameras and sensors, which can go deep underwater to observe and collect data on the activities and surface conditions of fish in real time, and promptly detect abnormal behaviors or signs of diseases and pests of fish) can be used to detect diseases and pests. In this embodiment, the key risk indicators that affect the risk level of diseases and pests in marine ranches are first identified, and these indicators specifically include morbidity, mortality, and transmission speed. In order to accurately obtain the data of these risk indicators, advanced data collection and analysis technologies are used, including Internet of Things sensors and computer vision technology (such as convolutional neural network CNN). Internet of Things sensors are deployed in key areas of marine ranches to monitor water quality parameters (such as temperature, salinity, dissolved oxygen, etc.) and the activity status of organisms in real time; at the same time, computer vision technology, especially convolutional neural networks, is used to efficiently and accurately identify and analyze images of aquatic organisms. This technology can accurately distinguish the types of diseases and pests, and quantify the key risk indicators such as morbidity, mortality, and transmission speed of specific diseases and pests, thereby providing detailed data support for subsequent specific disease and pest risk indicators. In addition, the convolutional neural network is also used to obtain the current overall incidence, mortality and spread rate of pests and diseases in the marine ranch in real time, and determine the risk level of each risk indicator based on the overall pest and disease risk indicator data of the marine ranch.

[0035] In order to determine the risk level of each risk indicator, it is necessary to first clarify the definition of the risk level. Since each organism is adapted to a different environment, technicians in this field can preset the level definition standard according to the grazing type. Specifically, in this embodiment, the main farmed organisms in the Nan'ao Island Marine Ranch are fish and shellfish, among which fish specifically include yellowtail and grouper. The fish and shellfish in the ranch are affected by a variety of pathogens and produce different diseases and insect pests; in this embodiment, each risk indicator can be divided into different risk levels according to its specific data. Specifically, in this embodiment, the incidence rate, mortality rate and transmission rate are divided into five levels: very low (level 1), low (level 2), medium (level 3), high (level 4) and very high (level 5). Each level corresponds to a specific numerical range, such as the incidence rate of level 1 corresponds to 0%-1%, and so on, as shown below:

[0036] Morbidity (I) risk level definition: grade 1 (0%-1%), grade 2 (1%-3%), grade 3 (3%-5%), grade 4 (5%-10%), grade 5 (>10%);

[0037] Mortality (M) risk level definition: grade 1 (0%-0.5%), grade 2 (0.5%-1%), grade 3 (1%-2%), grade 4 (2%-5%), grade 5 (>5%);

[0038] Transmission speed (S) risk level definition: Level 1 (extremely slow, 0-1 unit / day), Level 2 (slow, 1-5 units / day), Level 3 (moderate, 5-10 units / day), Level 4 (fast, 10-20 units / day), Level 5 (extremely fast, >20 units / day).

[0039] In the Nan'ao Island embodiment, when obtaining the risk indicator data of the overall pests and diseases, namely the incidence rate, mortality rate and transmission rate, the risk indicator is divided into its corresponding risk level according to each risk indicator data. For example, in this embodiment, the current overall incidence rate of pests and diseases in the marine ranch is obtained in real time as 2%, the mortality rate is 0.5%, and the transmission rate is 8 units / day. According to the above risk level classification rules, the risk level of the incidence rate is 2, the risk level of the mortality rate is 2, and the risk level of the transmission rate is 3.

[0040] Step 2: using the analytic hierarchy process to determine the relative weights of the multiple risk indicators based on the relative influences between the multiple risk indicators;

[0041] Since morbidity, mortality and transmission rate usually affect each other, for example, morbidity may affect mortality and transmission rate, because high morbidity usually means that the disease spreads faster, resulting in high mortality and higher transmission rate. Mortality is affected by morbidity and transmission rate, especially when the disease spreads faster, the mortality rate is usually higher. Transmission rate affects the spread of the disease and its impact on other factors (such as mortality and morbidity).

[0042] Therefore, it is necessary to construct the relative influences among multiple risk indicators. In this embodiment, the relative influences among the three are specifically set as follows:

[0043] Impact of morbidity:

[0044] The impact of morbidity on mortality: When the morbidity is higher, it usually means a higher mortality rate, because people with more infections usually have a higher risk of death. A score of 3 means that the morbidity has a strong impact on the mortality rate, but not an absolute one.

[0045] Effect of morbidity on transmission speed: Pests and diseases with high morbidity tend to spread more quickly. High morbidity usually means that the pathogen has spread rapidly in the population, and the transmission speed will also increase accordingly. A score of 4 means that the morbidity has a greater impact on the transmission speed.

[0046] Impact of mortality:

[0047] Effect of mortality on morbidity: High mortality is usually due to high morbidity. High mortality often occurs in the early stages of a disease, especially when environmental or host resistance is weak. A score of 1 / 3 indicates that mortality has a relatively small effect on morbidity.

[0048] Effect of mortality on spread rate: Pests and diseases with higher mortality rates usually spread more slowly, because high mortality means fewer hosts for the pathogen, which in turn limits the spread of the disease. Therefore, a score of 2 means that mortality has some effect on spread rate, but it is not as significant as the effect of morbidity on spread rate.

[0049] The influence of propagation speed:

[0050] The impact of transmission speed on morbidity: Pests and diseases that spread faster will quickly expand the source of disease, causing more individuals to be infected, thereby increasing the morbidity. Therefore, the transmission speed has a greater impact on morbidity, with a score of 1 / 4, indicating that its impact is relatively small, but still exists.

[0051] The impact of transmission speed on mortality: Pests and diseases that spread faster usually cause large-scale deaths, because the disease spreads quickly and the number of infected individuals increases rapidly, resulting in a higher mortality rate. Therefore, the impact of transmission speed on mortality is greater, and the score is 1 / 2.

[0052] Comprehensive analysis of the above data, we can draw the following conclusions:

[0053] Morbidity plays a central role in influencing the entire process of pest and disease transmission. Higher morbidity not only leads to higher mortality, but may also accelerate disease transmission.

[0054] Although mortality is mainly determined by morbidity, the speed of spread also has an impact on mortality to a certain extent. Pests and diseases that spread faster usually result in higher mortality.

[0055] The speed of transmission acts as an "accelerator" among these three indicators. Rapidly spreading pests and diseases can significantly increase the incidence and mortality rates, although it itself may not be the most important influencing factor in some cases.

[0056] Finally, based on the above relative influence scores, the following comparison matrix can be constructed:

[0057]

[0058] Furthermore, the step 2 specifically includes: constructing a comparison matrix according to the relative influences between the multiple risk indicators; normalizing the comparison matrix to determine the relative weight of each risk indicator.

[0059] Specifically, the comparison matrix is ​​processed and the sum of each column is calculated; the sum of the first column: 1+1 / 3+1 / 4=1.5833, the sum of the second column: 3+1+1 / 2=4.5, the sum of the third column: 4+2+1=7. Divide each parameter of the matrix by the sum of its column;11 =1 / 1.5833=0.6316, a 12 =3 / 4.5=0.6667, a 13 =4 / 7=0.5714, a 21 =0.3333 / 0.5833=0.2105, a 22 =1 / 4.5=0.2222, a 23 =2 / 7=0.2857, a 31 =0.25 / 1.5833=0.1579, a 32 =0.5 / 4.5=0.1111, a 33 =1 / 7=0.1429. Where a xy It represents the normalized value of the element in the xth row and yth column of the comparison matrix. This value reflects the relative influence of the xth risk indicator on the yth risk indicator.

[0060] Construct the contrast matrix after column normalization as follows:

[0061]

[0062] Furthermore, after constructing the comparison matrix, the method further includes: performing a consistency check on the comparison matrix to determine whether the comparison matrix meets the consistency requirement.

[0063] Furthermore, a consistency check is performed on the comparison matrix, specifically including: calculating the consistency index of the comparison matrix, obtaining the average random consistency index corresponding to the comparison matrix; determining the consistency ratio according to the consistency index and the average random consistency index, and judging whether the comparison matrix meets the consistency requirement according to the consistency ratio; if not, redefining the relative influence between the multiple risk indicators until the comparison matrix meets the consistency requirement.

[0064] In this embodiment, after the comparison matrix is ​​constructed, a consistency check is performed to ensure its accuracy and reliability. The purpose of the consistency check is to verify whether the comparison matrix meets the consistency requirement, that is, to determine whether the relative influences of various risk indicators are coordinated and consistent.

[0065] First, we need to calculate the maximum eigenvalue λ max :

[0066] According to the definition of eigenvalue and linear algebra formula, we first construct the characteristic polynomial of the comparison matrix A in the form of λ E-A , where E is the identity matrix and A is the contrast matrix.

[0067] Then, the solution when the characteristic polynomial is equal to zero is calculated, which is the eigenvalue of the comparison matrix. Through calculation, the three eigenvalues ​​of the comparison matrix are obtained: 1 =3.01538,λ 2 =-0.00769,λ 3 =-0.00769. Among them, the largest eigenvalue λ max =λ 1 =3.01538.

[0068] Calculate the consistency index CI:

[0069] The consistency index CI is used to measure the consistency of the comparison matrix. Its calculation formula is CI = (λ max –n) / (n–1), where n is the matrix order (in this case n = 3), λ max is the maximum eigenvalue of the matrix. Substituting the known values ​​into the formula, we get CI = (3.01538–3) / (3–1) = 0.00769.

[0070] Find the corresponding average random consistency index RI:

[0071] The average random consistency index RI is a reference standard for measuring the consistency of randomly generated comparison matrices. According to literature or empirical data, when the matrix order n = 3, the corresponding RI = 0.58.

[0072] Calculate the consistency ratio CR:

[0073] The consistency ratio CR is used to further verify the consistency of the comparison matrix. Its calculation formula is CR = CI / RI. Substituting the known values ​​into the formula, we get CR = 0.00769 / 0.58 = 0.013258.

[0074] Determine consistency requirements:

[0075] According to the calculation results of the consistency ratio, it can be judged whether the contrast matrix meets the consistency requirements. Generally speaking, when CR<0.1, it is considered that the contrast matrix meets the consistency requirements. In this example, CR=0.013258<0.1, so the contrast matrix meets the consistency requirements.

[0076] If the comparison matrix does not meet the consistency requirement (ie, CR ≥ 0.1), it is necessary to redefine the relative influences between multiple risk indicators and reconstruct the comparison matrix until it meets the consistency requirement.

[0077] Through the above steps, the accuracy and reliability of the comparison matrix can be ensured, providing strong support for the subsequent determination of weights.

[0078] Steps to determine relative weights:

[0079] Compute the sum of each row:

[0080] The sum of the first row (i.e., the sum of the normalized values ​​corresponding to the incidence rate I): 0.6316 (normalized value of incidence rate to incidence rate) + 0.6667 (normalized value of incidence rate to mortality rate) + 0.5714 (normalized value of incidence rate to transmission rate) = 1.8697;

[0081] The sum of the second row (i.e., the sum of the normalized values ​​corresponding to the mortality rate M): 0.2105 (normalized value of mortality rate to morbidity rate) + 0.2222 (normalized value of mortality rate to mortality rate) + 0.2857 (normalized value of mortality rate to transmission rate) = 0.7184;

[0082] The sum of the third row (i.e., the sum of the normalized values ​​corresponding to the propagation speed S): 0.1579 (normalized value of propagation speed to incidence rate) + 0.1111 (normalized value of propagation speed to mortality rate) + 0.1429 (normalized value of propagation speed to propagation speed) = 0.4119.

[0083] Calculate the relative weight of each indicator:

[0084] Divide the sum of each row by the order of the matrix (i.e. the number of risk indicators, which is 3 here) to get the weight of each risk indicator.

[0085] The weight w of the incidence rate (I) 1 = sum of the first row / 3 = 1.8697 / 3 = 0.6232

[0086] The weight w of the mortality rate (M) 2 = the sum of the second row / 3 = 0.7184 / 3 = 0.2395 The weight w of the propagation speed (S) 3 = sum of the third row / 3 = 0.4119 / 3 = 0.1373

[0087] In the above calculation, Wx (where x is 1, 2, or 3) represents the weight of the x-th risk indicator. Specifically, w1 represents the weight of the incidence rate (I), w2 represents the weight of the mortality rate (M), and w3 represents the weight of the transmission speed (S).

[0088] According to the weights obtained above, the following table is obtained:

[0089]

[0090] These weights represent the relative importance of each risk indicator on the marine ranch. Among them, the relative weight of incidence is 0.6232, indicating that the incidence has the greatest impact on the marine ranch, while the relative weight of transmission speed is 0.1373, indicating that its impact is relatively small.

[0091] Step 3: Determine a comprehensive risk index of marine ranch pests and diseases based on the risk levels and relative weights of the multiple risk indicators, and conduct a marine ranch pest and disease risk assessment based on the comprehensive risk index.

[0092] Specifically, after the relative weights of the risk indicators are determined, the comprehensive risk index of marine ranch pests and diseases can be further calculated based on these results. This index can comprehensively reflect the impact of pests and diseases on marine ranches and provide an important basis for risk assessment and management.

[0093] Specifically, in step 1, the specific risk level is determined according to the risk indicator data; the classification results of this embodiment are specifically that the risk level of incidence rate is 2, the risk level of mortality rate is 2, and the risk level of transmission speed is 3.

[0094] The comprehensive risk index (R) is calculated using the following formula:

[0095] R=w 1 ×I+w 2 ×M+w 3 ×S

[0096] In the formula, w 1 、w 2 、w 3 are the relative weights of morbidity, mortality and transmission speed, which are obtained through comparison matrix; I, M and S are the risk levels corresponding to morbidity, mortality and transmission speed, respectively.

[0097] In this embodiment, R = w 1 ×I+w 2 ×M+w 3 ×S=0.6232×2+0.2395×2+0.1373×3=2.1373

[0098] Furthermore, after conducting the marine ranch pest and disease risk assessment according to the comprehensive risk index, it also includes: determining the comprehensive risk level of the marine ranch pest and disease according to the comprehensive risk index.

[0099] According to the calculated comprehensive risk index R, it is necessary to further determine the comprehensive risk level of pests and diseases based on the index. This step is crucial for understanding and taking corresponding risk management measures. Generally, risks are divided into four levels: low risk, medium risk, high risk and extreme risk.

[0100] The specific classification criteria of this embodiment are as follows:

[0101] When 1≤R≤2, it is a low risk, which indicates that pests and diseases have little impact on marine ranches and conventional management measures can be taken to prevent and control them.

[0102] When 2<R≤3, it is a medium risk. At this time, the impact of pests and diseases begins to appear, and it is necessary to strengthen monitoring and early warning, and consider taking more active prevention and control measures.

[0103] When 3<R≤4, it is a high risk, which indicates that pests and diseases have had a significant impact on the marine ranch and immediate action is needed to control and manage it to prevent further spread and loss.

[0104] When 4<R≤5, it is an extreme risk. At this time, the impact of pests and diseases is extremely serious, and urgent measures need to be taken to deal with it, and external support and resources should be considered.

[0105] The calculated comprehensive risk index R is compared with these standards to determine the comprehensive risk level of marine ranch pests and diseases. For example, the R value calculated in this embodiment is 2.1373, then according to the classification standard, the comprehensive risk level of the pests and diseases is medium risk.

[0106] Furthermore, after step 3, the method further includes: identifying the pests and diseases of the marine ranch as specific pests and diseases; and determining a corresponding pest and disease management strategy according to a risk index corresponding to the specific pest and disease.

[0107] Furthermore, a hierarchical matrix model is used to determine the risk index of the specific pests and diseases.

[0108] Furthermore, the risk index of the specific pests and diseases is determined based on the morbidity, mortality and propagation speed of the specific pests and diseases obtained in real time.

[0109] Specifically, since the comprehensive risk of marine ranches cannot guide specific pest control measures, if the comprehensive risk is high, if there is no risk index for specific pests, it is impossible to determine which specific pests cause the comprehensive risk to be high, and it is also impossible to determine which specific pests need to be controlled, and it is impossible to formulate more effective and targeted control strategies. At the same time, identifying the risk level of specific pests can also determine the severity and urgency of pest treatment, and better guide the designation of control strategies, so it is necessary to accurately identify the pests and diseases that appear in marine ranches. Specifically, advanced data collection and analysis technologies are used, including IoT sensors and computer vision technology (such as convolutional neural networks CNN). IoT sensors are deployed in key areas of marine ranches to monitor water quality parameters (such as temperature, salinity, dissolved oxygen, etc.) and the activity status of organisms in real time; at the same time, computer vision technology, especially convolutional neural networks, is used to efficiently and accurately identify and analyze images of aquatic organisms. This technology can accurately distinguish the types of pests and diseases, and quantify key risk indicators such as the incidence, mortality and spread rate of specific pests and diseases.

[0110] After identifying specific pests and diseases, a hierarchical matrix model is used to more accurately assess the risk level of specific pests and diseases. This model assesses the risk level of specific pests and diseases by comprehensively considering the spread rate (S), incidence (I) and mortality (M) of specific pests and diseases.

[0111] Specifically include:

[0112] Based on the real-time specific pest and disease risk index data, determine the current spread rate level (1-5), incidence rate (1-5) and mortality level (1-5) of specific pests and diseases.

[0113] Based on the hierarchical matrix model, a risk assessment scale matrix was constructed to determine the risk level of specific pests and diseases. The matrix takes into account the impact of morbidity and mortality on the risk level under different transmission speeds.

[0114] The risk assessment scale matrix is ​​constructed as follows:

[0115]

[0116]

[0117] Then, according to the determined transmission speed S level, the corresponding risk assessment matrix of morbidity and mortality is selected, and the corresponding risk level R is found in the matrix according to the values ​​of I and M.

[0118] In this embodiment, it is determined that the current specific pests and diseases in the ocean ranch are enteritis, and its transmission speed (S): slow (S=2), morbidity risk level (I): medium (I=3), and mortality risk level (M): high (M=4).

[0119] According to the risk assessment scale matrix, when S = 2, I = 3, and M = 4, the risk level of enteritis is extreme risk. Therefore, immediate action is needed to prevent the pest from causing greater losses to the marine ranch.

[0120] The marine ranch pest and disease risk assessment method constructed by the present invention has brought significant beneficial effects to marine ranch pest and disease management. This method realizes the quantitative assessment of pest and disease risks by integrating monitoring data and risk indicators, greatly improving the risk identification and early warning capabilities. Specifically, it can carefully analyze the morbidity, mortality and transmission rate of pests and diseases, accurately determine the risk level of the marine ranch as a whole and specific pests and diseases, and provide a clear basis for whether to take control measures. On this basis, it can be used to guide the formulation of detailed control strategies, effectively respond to pest and disease threats, reduce their adverse effects on the marine ranch ecosystem, and effectively ensure the sustainable development of marine ranches.

[0121] In addition, this method provides a scientific basis for marine ranch management, making the formulation of management strategies more accurate and effective. By implementing these strategies, the ecological and economic benefits of marine ranches can be significantly improved, and the rational use and protection of fishery resources can be promoted.

[0122] The above are only several embodiments of the present invention and are not intended to limit the present invention in any form. Although the present invention is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any technician familiar with the profession, without departing from the scope of the technical solution of the present invention, using the above disclosed technical content to make slight changes or modifications are equivalent to equivalent implementation cases and fall within the scope of the technical solution.

Claims

1. A method for risk assessment of marine ranch pests and diseases, characterized in that: include: Step 1: acquiring multiple risk indicator data of pests and diseases affecting marine ranches in real time, and determining the risk level of each risk indicator according to the multiple risk indicator data; Step 2: using the analytic hierarchy process to determine the relative weights of the multiple risk indicators based on the relative influences between the multiple risk indicators; Step 3: Determine a comprehensive risk index of marine ranch pests and diseases based on the risk levels and relative weights of the multiple risk indicators, and conduct a marine ranch pest and disease risk assessment based on the comprehensive risk index.

2. The marine ranch pest risk assessment method according to claim 1, characterized in that: The step 3 further includes: Identify the pests and diseases of the marine ranch as specific pests and diseases; A corresponding pest and disease management strategy is determined according to the risk index corresponding to the specific pest and disease.

3. The marine ranch pest risk assessment method according to claim 1, characterized in that: The step 2 specifically includes: constructing a comparison matrix according to the relative influences between the multiple risk indicators; The comparison matrix is ​​normalized to determine the relative weight of each risk indicator.

4. The marine ranch pest risk assessment method according to claim 3 is characterized in that: After constructing the contrast matrix, it also includes: A consistency check is performed on the comparison matrix to determine whether the comparison matrix meets the consistency requirement.

5. The marine ranch pest risk assessment method according to claim 4, characterized in that: Performing a consistency check on the comparison matrix specifically includes: Calculating the consistency index of the comparison matrix, and obtaining the average random consistency index corresponding to the comparison matrix; Determine a consistency ratio according to the consistency index and the average random consistency index, and judge whether the comparison matrix meets the consistency requirement according to the consistency ratio; If not, the relative influences between the multiple risk indicators are redetermined until the comparison matrix meets the consistency requirement.

6. The marine ranch pest risk assessment method according to claim 1, characterized in that: The marine ranch pest risk assessment based on the comprehensive risk index also includes: The comprehensive risk level of pests and diseases in the marine ranch is determined based on the comprehensive risk index.

7. The marine ranch pest risk assessment method according to claim 1, characterized in that: Risk indicators include morbidity, mortality and rate of spread.

8. The marine ranch pest risk assessment method according to claim 2, characterized in that: A hierarchical matrix model is used to determine the risk index of the specific pests and diseases.

9. The marine ranch pest risk assessment method according to claim 8, characterized in that: The risk index of the specific pests and diseases is determined based on the morbidity, mortality and propagation speed of the specific pests and diseases obtained in real time.

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