Plant invasion risk assessment methods, devices, equipment, storage media and products

Abstract

The present invention provides a plant invasion risk assessment method, device, equipment, storage medium and product. The method comprises: determining the genetic distance between an ITS sequence of a plant to be assessed and an ITS sequence of a target sample; obtaining a target climate factor of the plant to be assessed; inputting the target climate factor of the plant to be assessed into a maximum information entropy model, and obtaining a potential suitable zone prediction result of the plant to be assessed at the location to be assessed output by the maximum information entropy model; determining the invasive risk of the plant to be assessed based on the genetic distance and the potential suitable zone prediction result, thereby using the target climate factor as a model input parameter, reducing the error between the result output by the model and the actual result, and calculating the genetic distance through the ITS sequence of the target sample belonging to the same genus as the plant to be assessed, thereby achieving a more rapid and effective determination of the invasive risk of the plant to be assessed.

Description

Technical Field

[0001] The present invention relates to the field of alien plant risk assessment, and in particular to a plant invasion risk assessment method, device, equipment, storage medium and product. Background Art

[0002] Pest Risk Analysis (PRA) is a requirement of the World Trade Organization's (WTO) Agreement on the Application of Sanitary and Phytosanitary Measures (SPS Agreement), which regulates plant quarantine practices. It mandates that countries (regions) formulate and implement plant quarantine measures to minimize the impact of quarantine measures on trade. The core elements of PRA are risk assessment and risk management. Pest risk assessment refers to determining whether a pest is a quarantine pest and evaluating the likelihood of its introduction. Quarantine pests are plants that pose a significant threat and are not currently distributed in my country, or are distributed only locally.

[0003] Currently, when conducting risk assessments of some invasive plants, most methods used are decision tree models, qualitative evaluation, and AHP. However, because weeds and invasive plants share a series of genetic, physiological, morphological, and life history characteristics, some of which have promoted biological invasions through adaptation and selective evolution, the results of plant invasion assessments using decision tree models, qualitative evaluation, AHP, and other methods deviate significantly from the actual invasion results, which is not conducive to early warning and early deployment of prevention and control work. Summary of the Invention

[0004] The present invention provides a plant invasion risk assessment method, device, equipment, storage medium and product to address the defects of inaccurate invasive plant risk assessment in the prior art and achieve more effective and accurate screening of high-risk invasive plants.

[0005] The present invention provides a plant invasion risk assessment method, comprising:

[0006] Determining the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of a target sample, wherein the ITS sequence of the target sample is selected from ITS sequences of plants of the same genus as the plant to be evaluated;

[0007] Obtaining a target climate factor for the plant to be evaluated, where the target climate factor is selected based on the climate factor of the location to be evaluated;

[0008] Inputting the target climate factor of the plant to be evaluated into the maximum information entropy model, and obtaining the prediction result of the potential suitable growth area of the plant to be evaluated at the location to be evaluated output by the maximum information entropy model;

[0009] The invasive risk of the plant to be evaluated is determined based on the genetic distance and the potential suitable area prediction result.

[0010] According to a plant invasion risk assessment method provided by the present invention, determining the genetic distance between the ITS sequence of the plant to be assessed and the ITS sequence of the target sample specifically includes:

[0011] Performing base comparison on the ITS sequence of the plant to be evaluated with each sample ITS sequence in a preset sample ITS sequence library to obtain a base comparison result, wherein the preset sample ITS sequence library is selected from plant ITS sequences of the same family as the plant to be evaluated;

[0012] Constructing an ITS sequence topology tree according to the base alignment results;

[0013] Based on the ITS sequence topology tree, the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample is determined.

[0014] According to a plant invasion risk assessment method provided by the present invention, determining the genetic distance between the ITS sequence of the plant to be assessed and the ITS sequence of the target sample based on the ITS sequence topological tree specifically includes:

[0015] Determining the congener genetic distance between the ITS sequences of the invasive plants of the same genus in the ITS sequence topology tree and the ITS sequence of the plant to be evaluated, based on the ITS sequence topology tree, wherein the preset sample ITS sequence library includes the target sample ITS sequence;

[0016] The ITS sequence of the invasive plant of the same genus with the smallest genetic distance with plants of the same genus is used as the target sample ITS sequence, and the genetic distance between the ITS sequence of the plant to be evaluated and the target sample ITS sequence is determined.

[0017] According to a plant invasion risk assessment method provided by the present invention, obtaining the target climate factor of the plant to be assessed specifically includes:

[0018] Obtain the geographical distribution areas of the plants to be assessed from the Global Biodiversity Information Platform;

[0019] Obtaining a climate factor dataset of the geographical distribution area of the plant to be evaluated from the World Climate Database;

[0020] Determining the climate factors of the location to be evaluated, and calculating the similarity between each climate factor in the climate factor dataset and the climate factors of the location to be evaluated;

[0021] A target climate factor is selected from the climate factor dataset based on the similarity.

[0022] According to a plant invasion risk assessment method provided by the present invention, determining the invasive risk of the plant to be assessed based on the genetic distance and the potential suitable area prediction result specifically includes:

[0023] When the genetic distance is less than the preset genetic distance and the potential suitable area prediction result shows that the suitability of the suitable area is greater than the preset suitability, it is determined that the plant to be evaluated has an invasive risk.

[0024] According to a plant invasion risk assessment method provided by the present invention, before determining the genetic distance between the ITS sequence of the plant to be assessed and the ITS sequence of the target sample, the method includes:

[0025] Using the DNA of the plant to be evaluated as a template, a forward primer, a reverse primer and a DNA polymerase premix are added in sequence to perform a PCR amplification reaction to obtain the ITS sequence of the plant to be evaluated.

[0026] The present invention also provides a plant invasion risk assessment device, comprising:

[0027] a determining unit, configured to determine a genetic distance between an ITS sequence of the plant to be evaluated and an ITS sequence of a target sample, wherein the ITS sequence of the target sample is selected from ITS sequences of plants of the same genus as the plant to be evaluated;

[0028] an acquisition unit, configured to acquire a target climate factor of the plant to be evaluated, wherein the target climate factor is selected based on the climate factor of the location to be evaluated;

[0029] A prediction unit, configured to input the target climate factor of the plant to be evaluated into a maximum information entropy model, and obtain a prediction result of a potential suitable growth area of the plant to be evaluated at the location to be evaluated outputted by the maximum information entropy model;

[0030] An evaluation unit is used to determine the invasive risk of the plant to be evaluated based on the genetic distance and the potential suitable area prediction result.

[0031] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any of the above-described plant invasion risk assessment methods is implemented.

[0032] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the plant invasion risk assessment methods described above.

[0033] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned plant invasion risk assessment methods.

[0034] The present invention provides a plant invasion risk assessment method, device, equipment, storage medium and product. The method determines the genetic distance between the ITS sequence of the plant to be assessed and the target sample ITS sequence to obtain the target climate factor of the plant to be assessed. The target climate factor of the plant to be assessed is then input into a maximum information entropy model to obtain a potential suitable zone prediction result of the plant to be assessed at the location to be assessed, which is output by the maximum information entropy model. Finally, the invasive risk of the plant to be assessed is determined based on the genetic distance and the potential suitable zone prediction result. Since biological invasion involves the organism itself and the environment in which the organism is located, the two elements complement each other, and weeds and invasive plants have a series of genetic, physiological, morphological and life history characteristics, some of which promote biological invasion through adaptation and selective evolution. Therefore, in the present invention, the target sample ITS sequence is selected based on the ITS sequences of plants of the same genus as the plant to be assessed, and the target climate factor is selected based on the climate factor of the location to be assessed. Therefore, by using the target climatic factors related to the climatic factors of the site to be evaluated as the model input parameters, the error between the potential suitable area prediction results output by the model and the actual results is reduced. By selecting the target sample ITS sequence from the ITS sequences of plants of the same genus as the plant to be evaluated to calculate the genetic distance, more effective screening of high-risk invasive plants is achieved, thereby achieving the purpose of accurately screening high-risk invasive plants. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 This is one of the flow charts of the plant invasion risk assessment method provided by the present invention;

[0037] Figure 2 This is the second flow chart of the plant invasion risk assessment method provided by the present invention;

[0038] Figure 3 This is the third flow chart of the plant invasion risk assessment method provided by the present invention

[0039] Figure 4 Schematic diagram of the structure of the plant invasion risk assessment device provided by the present invention;

[0040] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0041] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0042] The following combination Figure 1-Figure 3 The plant invasion risk assessment method of the present invention is described.

[0043] Figure 1 This is one of the flow charts of the plant invasion risk assessment method provided by the present invention, such as Figure 1 As shown, the method includes:

[0044] Step 100, determining the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of a target sample, wherein the ITS sequence of the target sample is selected from ITS sequences of plants of the same genus as the plant to be evaluated;

[0045] Specifically, in rDNA genes, the intergenic sequence between the 5.8S ribosomal RNA gene (5.8S rDNA) and the 28S ribosomal RNA gene (28S rDNA) is called an ITS. Genetic distance refers to the degree of genetic divergence between different populations or species and is measured as a numerical value, typically determined by a function of gene frequency. It should be noted that weeds and invasive plants share a range of genetic, physiological, morphological, and life history characteristics, some of which have facilitated biological invasion through adaptation and selective evolution. In this paper, the invasive risk of the plants to be assessed is analyzed based on plant classification, phylogenetic analysis, and the principle of similarity, using plants of the same genus as the plant to be assessed as a reference.

[0046] In practical applications, the present invention can first identify and analyze the plant to be evaluated based on the plant database or the Global Biodiversity Information Platform to determine the name, category and ITS sequence information of the plant to be evaluated. Then, based on the category of the plant to be evaluated, the plant database or the Global Biodiversity Information Platform is searched for sample plants of the same genus as the plant to be evaluated, and the ITS sequence of the sample plant is used as the target sample ITS sequence for subsequent risk assessment.

[0047] It should be noted that in order to facilitate the distinction between different plants and their related characteristics, plants are usually classified into kingdom, phylum, class, order, family, genus, and species based on the closeness of their kinship, and the classification is progressive, that is, plants in the same kingdom can continue to be divided into phylum, plants in the same phylum can continue to be divided into class, plants in the same class can continue to be divided into order, and so on. I will not go into details here.

[0048] To improve the accuracy of invasion risk assessment, the present invention directly uses plants of the same genus as a reference for genetic analysis. Furthermore, to facilitate subsequent, more rapid screening of invasive plants, after finding sample plants of the same genus as the plant to be assessed, the invasiveness of each sample plant is analyzed, for example, to determine whether the sample plant is invasive or whether it poses an invasion risk to the site to be assessed. After performing the invasiveness analysis, the ITS sequence of the invasive plant or the sample plant posing an invasion risk to the site to be assessed is used as the target sample ITS sequence.

[0049] In practical applications, after obtaining the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample, the Kimura-2-parameter model in the MAGA 5.1 software can be used to calculate the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample. Before using the Kimura-2-parameter model in the MAGA 5.1 software to output the genetic distance, it is necessary to first set the start site, end site, base reading order, etc. of the analysis, and then input the ITS sequence data in meg format into the Kimura-2-parameter model in the MAGA 5.1 software, obtain and organize the results output by the Kimura-2-parameter model, and thus obtain the genetic distance. It should also be noted that the above-mentioned genetic distance obtained based on the Kimura-2-parameter model in the MAGA5.1 software is only one embodiment of the present invention. In the present invention, the genetic distance can also be obtained according to other analysis methods, such as Clustal X2 software, Dispan software, Ntsyspc2.1 software, etc., which will not be repeated here.

[0050] In another embodiment, when the ITS sequence of the plant to be evaluated cannot be found in a public database, such as NCBI (National Center for Biotechnology Information), the ITS sequence of the plant to be evaluated can be extracted from the DNA of the known plant to be evaluated according to an ITS sequence extraction experiment. Specifically, before determining the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample, the following steps are included:

[0051] Using the DNA of the plant to be evaluated as a template, a forward primer, a reverse primer and a DNA polymerase premix are added in sequence to perform a PCR amplification reaction to obtain the ITS sequence of the plant to be evaluated.

[0052] It is easy to understand that when the ITS sequence of the plant to be assessed cannot be found in the public database, it is necessary to extract the ITS sequence of the plant to be assessed from the DNA of the known plant to be assessed through PCR amplification reaction, thereby completing the subsequent plant invasion risk assessment.

[0053] Specifically, the forward primer refers to the primer located upstream of the DNA double helix, and its main function is to extend continuously along the negative strand, while the reverse primer refers to the primer located downstream of the DNA double helix, and its main function is to extend continuously along the positive strand. Thus, the forward primer is used to extend continuously along the negative strand of the template DNA, and the negative primer is used to extend continuously along the positive strand of the template DNA, thereby completing PCR amplification.

[0054] In practical applications, in order to ensure the smooth completion of the PCR amplification reaction, it is also necessary to add a DNA polymerase premix to the reaction system, wherein the DNA polymerase premix contains Taq DNA polymerase and dNTPs. dNTPs are the raw materials for the PCR amplification reaction. When the concentration is too high, it will cause the DNA polymerase to be incorrectly incorporated, resulting in base pairing errors. The amount of Taq DNA polymerase used is an important factor affecting the PCR amplification reaction. When the concentration of Taq DNA polymerase is too low, amplification cannot be performed, while too high a concentration will cause nonspecific amplification. Therefore, the present invention selects 25μl of 5U / μL DNA polymerase premix to participate in the reaction to ensure the smooth completion of the PCR amplification reaction.

[0055] In addition, except that the archaeal dna polymerase premix affects the pcr amplification reaction, the content of template DNA and the content annealing temperature of primer etc. all can affect the pcr amplification reaction, for example, when the template DNA content was too little, can cause amplified product few, and when the template DNA content was many, can suppress the pcr amplification reaction again, thereby make amplified product few.And in the pcr amplification reaction, when the concentration of primer was too low, primer and template DNA binding rate were low, and when the primer concentration was too high, then can increase the probability of fee specific binding again, cause product impure.Therefore among the present invention in actual applications, the pcr amplification reaction system is with 50 μ l, specifically comprises: the template DNA of 1 μ l, the 10pmol / μ l forward primer and reverse primer of each 2 μ l, the 5U / μ L archaeal dna polymerase premix of 25 μ l, and surplus is then water. After obtaining a 50 μl PCR amplification reaction system, the reaction program was adjusted, the PCR amplification reaction system was briefly centrifuged, and the reaction system was immediately placed on a PCR instrument for amplification. Specifically, a pre-denaturation step was performed at 98°C for 3 minutes, followed by a cyclic amplification step: amplification at 98°C for 10 seconds, annealing and cooling to 54°C and holding for 10 seconds, followed by heating to 72°C and holding for 10 seconds. This process was repeated 38 times, and finally, the reaction was incubated at 72°C for 5 minutes to terminate the reaction and obtain the PCR product. The PCR product was then stored at 4°C. The PCR product was then extracted to obtain the ITS sequence of the plant to be evaluated. In practical applications, because ITS sequences lack conserved primers and have poor stability, the full 16S-23S sequence is usually amplified during PCR amplification. After amplification of the full 16S-23S sequence, the ITS sequence of the plant to be evaluated was extracted.

[0056] Step 200, obtaining a target climate factor of the plant to be evaluated, wherein the target climate factor is selected based on the climate factor of the location to be evaluated;

[0057] It should be noted that, in practical applications, it is usually to study whether a certain plant poses an invasion threat to a certain country or a certain region. Therefore, in the present invention, the climate factors of the current distribution status of the plant to be evaluated in various distribution areas around the world are evaluated based on the climate factors of the location to be evaluated. The climate factors are selected by similar climate assessment. In other words, the similarity between the target climate factors in the present invention and the climate factors of the location to be evaluated is within a pre-set similarity range. Therefore, based on the target climate factors that are similar to the climate factors of the location to be evaluated, it can be ensured that the invasive risk of the plant to be evaluated is evaluated more effectively.

[0058] Specifically, we can first obtain the geographical distribution area of the plants to be evaluated, then obtain the climatic factors in each geographical distribution area, and finally select from the climatic factors in each geographical distribution area the target climatic factors whose similarity with the climatic factors of the location to be evaluated is within a pre-set similarity range.

[0059] Step 300: Inputting the geographical distribution information of the plant to be evaluated and the target climate factor into a maximum information entropy model, and obtaining a prediction result of the potential suitable growth area of the plant to be evaluated at the location to be evaluated outputted by the maximum information entropy model;

[0060] Specifically, the main principle of the maximum information entropy model is to predict the relative probability of plant existence by finding the maximum entropy of the plant probability distribution. In the present invention, in order to ensure the accuracy of the output results of the maximum information entropy model, before obtaining the prediction results of the potential suitable habitats of the plants to be evaluated at the locations to be evaluated based on the maximum information entropy model, the maximum information entropy model can also be optimized to make its prediction results closer to the actual results. Specifically, in practical applications, the geographical distribution area information of known plants, such as the geographical distribution data of water hyacinth, can be obtained from the Global Biodiversity Information Platform, and then the climate factors of various places in the areas where water hyacinth is currently distributed can be obtained from the World Climate Database. In addition, in order to avoid overfitting of the model due to an excessive number of climate factors, 19 climate factors can be selected from the climate factors of various places corresponding to 70% of the training data as training parameters for model training in the present invention. Specifically, the geographical distribution data of water hyacinth is randomly divided into 70% of training data and 30% of test data, and the 19 climate factors corresponding to 70% of the training data are input into the maximum information entropy model. The parameters of the maximum information entropy model are updated and adjusted based on the prediction results output by it and the actual results corresponding to 70% of the training data until the maximum information entropy model training is completed. The maximum information entropy model is then verified based on 30% of the test data.

[0061] It should be noted that the maximum information entropy model outputs the probability distribution of all grid cells, that is, the maximum information entropy model outputs all potential suitable areas of the plant to be evaluated under the target climate factor and the suitability probability of each potential suitable area. In the present invention, after obtaining the prediction results output by the maximum information entropy model, the potential suitable areas of the plant to be evaluated at the location to be evaluated and the suitability probability of each potential suitable area are obtained from the prediction results.

[0062] Step 400: Determine the invasiveness risk of the plant to be assessed based on the genetic distance and the potential suitable habitat prediction result.

[0063] It should be noted that, when examining the ecosystem in the dimension of time, it is not difficult to find that the two major parts that constitute the ecosystem: organisms and the environment, both change over time, but this change does not occur in isolation. In nature, plants are functional units in the ecosystem. Any plant is within the framework of a certain ecosystem. There are no isolated plants that are separated from the ecosystem in nature, nor are there isolated plant evolutions. The complex relationship between organisms within the ecosystem and between organisms and their environment constitutes the background of plant evolution. The evolution of a certain plant is restricted by other plants and environmental factors within the ecosystem. Therefore, the evolution of plants within the ecosystem is manifested as the co-evolution of the plant and other related plants and the environment. Therefore, in order to facilitate the subsequent more effective assessment of the risk of plant invasion, in addition to using plants of the same genus as a reference to conduct genetic distance analysis, the present invention also assesses the invasive risk of the plant to be assessed based on the potential suitable area of the plant to be assessed at the location to be assessed and the adaptability probability of the potential suitable area, making the risk assessment method more effective.

[0064] Specifically, in the present invention, when determining the invasiveness risk of the plant to be assessed based on the genetic distance and potential suitable habitat prediction results, it specifically includes:

[0065] When the genetic distance is less than the preset genetic distance and the potential suitable area prediction result shows that the suitability of the suitable area is greater than the preset suitability, it is determined that the plant to be evaluated has an invasive risk.

[0066] It should be noted that suitability refers to the probability of success in a potential suitable area. In practical applications, the predicted genetic distance can be 0.0500 and the suitability can be 0.5900. In other words, when the genetic distance of a plant to be evaluated is between 0 and 0.0500 and its suitability is between 0.5900 and 1.0000, the plant is considered invasive in the location being evaluated. Furthermore, the closer the genetic distance is to 0 and the closer the suitability is to 1, the greater the invasiveness of the plant, meaning that the threat it poses to the location being evaluated is greater.

[0067] The plant invasion risk assessment method proposed in the present invention obtains the target climate factor of the plant to be assessed by determining the genetic distance between the ITS sequence of the plant to be assessed and the target sample ITS sequence. The target climate factor of the plant to be assessed is then input into a maximum information entropy model to obtain the potential suitable area prediction result of the plant to be assessed at the location to be assessed output by the maximum information entropy model. Finally, the invasive risk of the plant to be assessed is determined based on the genetic distance and the potential suitable area prediction result. Since biological invasion involves the organism itself and the environment in which the organism is located, the two elements complement each other, and weeds and invasive plants have a series of genetic, physiological, morphological and life history characteristics, some of which promote biological invasion through adaptation and selective evolution. Therefore, in the present invention, the target sample ITS sequence is selected based on the ITS sequences of plants of the same genus as the plant to be assessed, and the target climate factor is selected based on the climate factor of the location to be assessed. Therefore, by using the target climatic factors related to the climatic factors of the site to be evaluated as the model input parameters, the error between the potential suitable area prediction results output by the model and the actual results is reduced. By selecting the target sample ITS sequence from the ITS sequences of plants of the same genus as the plant to be evaluated to calculate the genetic distance, more effective screening of high-risk invasive plants is achieved, thereby achieving the purpose of accurately screening high-risk invasive plants.

[0068] Alternatively, in another embodiment disclosed in the present invention, referring to Figure 2 , Figure 2 The second flow chart of the plant invasion risk assessment method provided by the present invention is as follows: Figure 2 As shown: the determination of the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample specifically includes:

[0069] Step 1001, performing base alignment between the ITS sequence of the plant to be evaluated and each sample ITS sequence in a preset sample ITS sequence library to obtain a base alignment result, wherein the preset sample ITS sequence library is selected from plant ITS sequences of the same family as the plant to be evaluated, and the preset sample ITS sequence library includes the target sample ITS sequence;

[0070] Step 1002: construct an ITS sequence topology tree based on the base alignment results;

[0071] Step 1003: Determine the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample based on the ITS sequence topology tree.

[0072] Specifically, each sample in the preset sample ITS sequence library belongs to the same family as the plant to be evaluated, and the target sample belongs to the same genus as the plant to be evaluated in the preset sample ITS sequence library. The main function of the ITS sequence topological tree is to show the kinship relationship between plants. Starting from the root of the plant, its branches from the main branch to the lower branch are in the same family, then the same family is further divided into the same genus, and the same genus is further divided into the same species. This can clearly show the closeness of the relationship between species from the ITS sequence topological tree. In addition, the branch length of the ITS sequence topological tree depicts the evolutionary distance, that is, the genetic distance between species.

[0073] In practical applications, when calculating the genetic distance between ITS sequences, the base differences between the ITS sequences are actually compared. Specifically, the base comparison results include the coverage of the comparison and the similarity of the compared sequences. Coverage refers to the percentage of the total number of bases measured during sequencing to the length of the ITS sequence. Based on the base comparison results, an ITS sequence topology tree is constructed. In the present invention, the ITS sequence of the plant to be evaluated can be base-aligned with each sample ITS sequence in a preset sample ITS sequence library using Clustal Omega software to obtain the base comparison results.

[0074] It should be noted that genetic distance refers to the degree of genetic difference between different populations or species. Based on plant classification and phylogenetic analysis, the closer the genetic distance between plants, the smaller the genetic difference between them, and therefore the closer their characteristics of introduction, colonization, and spread behavior. Therefore, the present invention, based on the ITS sequence topological tree, determines the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample, specifically including:

[0075] Based on the ITS sequence topology tree, determining the congener genetic distance between the ITS sequence of each congener invasive plant in the ITS sequence topology tree and the ITS sequence of the plant to be evaluated;

[0076] The ITS sequence of the invasive plant of the same genus with the smallest genetic distance with plants of the same genus is used as the target sample ITS sequence, and the genetic distance between the ITS sequence of the plant to be evaluated and the target sample ITS sequence is determined.

[0077] It is easy to understand that since the ITS sequence topology tree is constructed based on plants belonging to the same family as the plant to be evaluated, and in order to facilitate the distinction between different plants and their related characteristics, plants are usually classified based on the closeness of their kinship, and the classification is progressive, that is, plants of the same family can continue to be divided according to the same genus. Therefore, in order to ensure the effectiveness and rapidity of the basis for judging the invasive risk, the present invention determines the genetic distance from plants of the same genus as the plant to be evaluated. In addition, it is easy to understand that there may be more than one plant of the same genus as the plant to be evaluated. Therefore, in order to simplify the subsequent evaluation steps and quickly obtain the evaluation results, the ITS sequence of the invasive plant of the same genus with the smallest genetic distance from the plants of the same genus is used as the target sample ITS sequence, that is, the genetic distance between the ITS sequence of the invasive plant of the same genus with the smallest genetic distance from the plants of the same genus and the ITS sequence of the plant to be evaluated is used as the basis for judging the invasive risk of the plant to be evaluated.

[0078] In the present invention, the ITS sequence of the plant to be evaluated is base-aligned with the ITS sequences of each sample in a preset sample ITS sequence library to obtain a base alignment result. Then, an ITS sequence topology tree is constructed based on the base alignment result. Finally, based on the ITS sequence topology tree, the genetic distance between the ITS sequence of the plant to be evaluated and the target sample ITS sequence is determined. In this way, the genetic distance between the ITS sequence of the invasive plant of the same genus with the smallest genetic distance among plants of the same genus and the ITS sequence of the plant to be evaluated is used as the basis for judging the invasive risk of the plant to be evaluated, thereby more quickly and effectively deriving the invasive risk of the plant to be evaluated.

[0079] Alternatively, in another embodiment disclosed in the present invention, referring to Figure 3 , Figure 3 The third flow chart of the plant invasion risk assessment method provided by the present invention is as follows: Figure 3 As shown: the obtaining of the target climate factor of the plant to be evaluated specifically includes:

[0080] Step 2001: obtaining the geographical distribution area of the plant to be evaluated from the Global Biodiversity Information Platform;

[0081] Step 2002: Acquire a climate factor dataset of the geographical distribution area of the plant to be evaluated from the world climate database;

[0082] Step 2003, determining the climate factors of the location to be evaluated, and calculating the similarity between each climate factor in the climate factor dataset and the climate factors of the location to be evaluated;

[0083] Step 2004: Select a target climate factor from the climate factor dataset based on the similarity.

[0084] Specifically, the geographical distribution area of the plant to be evaluated refers to the current distribution status of the plant to be evaluated around the world. In practical applications, when obtaining the geographical distribution area information of the plant to be evaluated, the longitude and latitude information of the location of the plant to be evaluated is specifically accurate. When the longitude and latitude information cannot be accurately obtained, the coordinates of the place name of the location of the plant to be evaluated can also be accurately obtained through the satellite system. In addition, in order to avoid excessive data duplication and model overfitting, the present invention can also retain only one distribution data within the 2km environmental grid data. For example, when it is found that there are 10 distribution data within the 2km environmental grid data, the distribution data located at the center of the 10 distribution data can represent the 10 distribution data.

[0085] In another application scenario, when the number of climate factors is too large, it will affect the accuracy of the model prediction results. Therefore, the present invention needs to first calculate the similarity between each climate factor in the climate factor data set and the climate factors of the location to be evaluated, and finally sort the climate factors in the climate factor data set from large to small based on the similarity, and finally select the climate factor with a ranking in the front preset ranking as the target climate factor. For example, when 19 climate factors are required for model prediction, the climate factors ranked in the top 19 in the climate factor data set are used as the target climate factors.

[0086] In the present invention, the geographical distribution areas of the plants to be evaluated are obtained from the Global Biodiversity Information Platform, and the climate factor data set of the geographical distribution areas of the plants to be evaluated is obtained from the World Climate Database. Then, the climate factors of the location to be evaluated are determined, and the similarity between each climate factor in the climate factor data set and the climate factors of the location to be evaluated is calculated. Finally, based on the similarity, the target climate factor is selected from the climate factor data set, thereby making the model prediction results more accurate, and only the target climate factors ranked in the front preset ranking are input into the model, which simplifies the model input parameters and further improves the model prediction speed, thereby ensuring that the invasive risk of the plants to be evaluated can be evaluated more quickly and accurately.

[0087] The plant invasion risk assessment device provided by the present invention is described below. The plant invasion risk assessment device described below and the plant invasion risk assessment method described above can be referenced to each other.

[0088] refer to Figure 4 , Figure 4 Schematic diagram of the plant invasion risk assessment device provided by the present invention. Figure 4As shown, the plant invasion risk assessment device includes: a determination unit 410, an acquisition unit 420, a prediction unit 430, and an evaluation unit 440. The determination unit 410 is used to determine the genetic distance between the ITS sequence of the plant to be evaluated and the target sample ITS sequence, wherein the target sample ITS sequence is selected from the ITS sequences of plants of the same genus as the plant to be evaluated; the acquisition unit 420 is used to obtain the target climate factor of the plant to be evaluated, wherein the target climate factor is selected based on the climate factor of the location to be evaluated; the prediction unit 430 is used to input the target climate factor of the plant to be evaluated into the maximum information entropy model to obtain the potential suitable habitat prediction result of the plant to be evaluated at the location to be evaluated output by the maximum information entropy model; and the evaluation unit 440 is used to determine the invasive risk of the plant to be evaluated based on the genetic distance and the potential suitable habitat prediction result.

[0089] The plant invasion risk assessment device proposed in the present invention obtains the target climate factor of the plant to be assessed by determining the genetic distance between the ITS sequence of the plant to be assessed and the target sample ITS sequence. The target climate factor of the plant to be assessed is then input into a maximum information entropy model to obtain the potential suitable zone prediction result of the plant to be assessed at the location to be assessed output by the maximum information entropy model. Finally, the invasive risk of the plant to be assessed is determined based on the genetic distance and the potential suitable zone prediction result. Since biological invasion involves the organism itself and the environment in which the organism is located, the two elements complement each other, and weeds and invasive plants have a series of genetic, physiological, morphological and life history characteristics, some of which promote biological invasion through adaptation and selective evolution. Therefore, in the present invention, the target sample ITS sequence is selected based on the ITS sequences of plants of the same genus as the plant to be assessed, and the target climate factor is selected based on the climate factor of the location to be assessed. Therefore, by using the target climatic factors related to the climatic factors of the site to be evaluated as the model input parameters, the error between the potential suitable area prediction results output by the model and the actual results is reduced. By selecting the target sample ITS sequence from the ITS sequences of plants of the same genus as the plant to be evaluated to calculate the genetic distance, more effective screening of high-risk invasive plants is achieved, thereby achieving the purpose of accurately screening high-risk invasive plants.

[0090] According to a plant invasion risk assessment device provided by the present invention, the determination unit 410 is further configured to perform base comparison between the ITS sequence of the plant to be assessed and each sample ITS sequence in a preset sample ITS sequence library, to obtain a base comparison result, wherein the preset sample ITS sequence library is selected from ITS sequences of plants of the same family as the plant to be assessed; construct an ITS sequence topological tree based on the base comparison result; and determine the genetic distance between the ITS sequence of the plant to be assessed and the target sample ITS sequence based on the ITS sequence topological tree. The determination unit 410 is further configured to determine, based on the ITS sequence topological tree, the conspecific genetic distance between the ITS sequences of each conspecific invasive plant in the ITS sequence topological tree and the ITS sequence of the plant to be assessed, wherein the preset sample ITS sequence library includes the target sample ITS sequence; select the ITS sequence of the conspecific invasive plant with the smallest conspecific genetic distance as the target sample ITS sequence, and determine the genetic distance between the ITS sequence of the plant to be assessed and the target sample ITS sequence. Furthermore, the prediction unit 430 is further configured to determine that the plant to be evaluated has an invasive risk if the genetic distance is less than a preset genetic distance and the potential suitable zone prediction result indicates that the suitability of the suitable zone is greater than a preset suitability. The determination unit 410 is further configured to perform a PCR amplification reaction using the DNA of the plant to be evaluated as a template, sequentially adding a forward primer, a reverse primer, and a DNA polymerase premix, to obtain an ITS sequence of the plant to be evaluated.

[0091] The plant invasion risk assessment device proposed in the present invention performs base comparison between the ITS sequence of the plant to be assessed and each sample ITS sequence in a preset sample ITS sequence library to obtain a base comparison result. Then, based on the base comparison result, an ITS sequence topological tree is constructed. Finally, based on the ITS sequence topological tree, the genetic distance between the ITS sequence of the plant to be assessed and the target sample ITS sequence is determined. In this way, the genetic distance between the ITS sequence of the invasive plant of the same genus with the smallest genetic distance among plants of the same genus and the ITS sequence of the plant to be assessed is used as the basis for judging the invasive risk of the plant to be assessed, thereby more quickly and effectively determining the invasive risk of the plant to be assessed.

[0092] According to a plant invasion risk assessment device provided by the present invention, the acquisition unit 420 is further used to obtain the geographical distribution area of the plant to be assessed from the Global Biodiversity Information Platform; obtain a climate factor dataset of the geographical distribution area of the plant to be assessed from the World Climate Database; determine the climate factors of the location to be assessed, and calculate the similarity between each climate factor in the climate factor dataset and the climate factor of the location to be assessed; and select a target climate factor from the climate factor dataset based on the similarity.

[0093] The plant invasion risk assessment device proposed in the present invention obtains the geographical distribution areas of the plants to be assessed from the Global Biodiversity Information Platform, obtains the climate factor data set of the geographical distribution areas of the plants to be assessed from the World Climate Database, then determines the climate factors of the location to be assessed, and calculates the similarity between each climate factor in the climate factor data set and the climate factors of the location to be assessed. Finally, based on the similarity, the target climate factor is selected from the climate factor data set, thereby making the model prediction results more accurate, and only inputting the target climate factors ranked in the front preset ranking into the model, simplifying the model input parameters and further improving the model prediction speed, thereby ensuring that the invasive risk of the plants to be assessed can be assessed more quickly and accurately.

[0094] Figure 5 An example of a physical structure diagram of an electronic device is shown below. Figure 5 As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530, and a communication bus 540, wherein the processor 510, the communication interface 520, and the memory 530 communicate with each other via the communication bus 540. The processor 510 may call logic instructions in the memory 530 to execute a plant invasion risk assessment method, which includes: determining the genetic distance between the ITS sequence of the plant to be assessed and the target sample ITS sequence, wherein the target sample ITS sequence is selected from the ITS sequences of plants of the same genus as the plant to be assessed; obtaining a target climate factor for the plant to be assessed, wherein the target climate factor is selected based on the climate factor of the location to be assessed; inputting the target climate factor of the plant to be assessed into a maximum information entropy model to obtain a potential suitable habitat prediction result of the plant to be assessed at the location to be assessed, output by the maximum information entropy model; and determining the invasive risk of the plant to be assessed based on the genetic distance and the potential suitable habitat prediction result.

[0095] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0096] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the plant invasion risk assessment method provided by the above-mentioned methods, which includes: determining the genetic distance between the ITS sequence of the plant to be evaluated and the target sample ITS sequence, wherein the target sample ITS sequence is selected from the ITS sequences of plants of the same genus as the plant to be evaluated; obtaining the target climate factor of the plant to be evaluated, wherein the target climate factor is selected based on the climate factor of the location to be evaluated; inputting the target climate factor of the plant to be evaluated into the maximum information entropy model, and obtaining the potential suitable area prediction result of the plant to be evaluated at the location to be evaluated output by the maximum information entropy model; and determining the invasive risk of the plant to be evaluated based on the genetic distance and the potential suitable area prediction result.

[0097] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the plant invasion risk assessment method provided by the above-mentioned methods, the method comprising: determining the genetic distance between the ITS sequence of the plant to be evaluated and the target sample ITS sequence, wherein the target sample ITS sequence is selected from the ITS sequences of plants of the same genus as the plant to be evaluated; obtaining the target climate factor of the plant to be evaluated, wherein the target climate factor is selected based on the climate factor of the location to be evaluated; inputting the target climate factor of the plant to be evaluated into a maximum information entropy model, and obtaining the potential suitable area prediction result of the plant to be evaluated at the location to be evaluated output by the maximum information entropy model; and determining the invasive risk of the plant to be evaluated based on the genetic distance and the potential suitable area prediction result.

[0098] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0099] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A plant invasion risk assessment method, characterized in that: include: Determining the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of a target sample, wherein the ITS sequence of the target sample is selected from ITS sequences of plants of the same genus as the plant to be evaluated; Obtaining a target climate factor for the plant to be evaluated, where the target climate factor is selected based on the climate factor of the location to be evaluated; Inputting the target climate factor of the plant to be evaluated into the maximum information entropy model, and obtaining the prediction result of the potential suitable growth area of the plant to be evaluated at the location to be evaluated output by the maximum information entropy model; Determining the invasiveness risk of the plant to be assessed based on the genetic distance and the potential suitable area prediction result; The step of obtaining the target climate factor of the plant to be evaluated specifically includes: Obtain the geographical distribution areas of the plants to be assessed from the Global Biodiversity Information Platform; Obtaining a climate factor dataset of the geographical distribution area of the plant to be evaluated from the World Climate Database; Determining the climate factors of the location to be evaluated, and calculating the similarity between each climate factor in the climate factor dataset and the climate factors of the location to be evaluated; A target climate factor is selected from the climate factor dataset based on the similarity.

2. The plant invasion risk assessment method according to claim 1, characterized in that: Determining the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample specifically includes: Performing base comparison on the ITS sequence of the plant to be evaluated with each sample ITS sequence in a preset sample ITS sequence library to obtain a base comparison result, wherein the preset sample ITS sequence library is selected from plant ITS sequences of the same family as the plant to be evaluated; Constructing an ITS sequence topology tree according to the base alignment results; Based on the ITS sequence topology tree, the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample is determined.

3. The plant invasion risk assessment method according to claim 2, characterized in that: Determining the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample based on the ITS sequence topology tree specifically includes: Determining the congener genetic distance between the ITS sequences of the invasive plants of the same genus in the ITS sequence topology tree and the ITS sequence of the plant to be evaluated, based on the ITS sequence topology tree, wherein the preset sample ITS sequence library includes the target sample ITS sequence; The ITS sequence of the invasive plant of the same genus with the smallest genetic distance with plants of the same genus is used as the target sample ITS sequence, and the genetic distance between the ITS sequence of the plant to be evaluated and the target sample ITS sequence is determined.

4. The plant invasion risk assessment method according to claim 1, characterized in that: The determining of the invasiveness risk of the plant to be assessed based on the genetic distance and the potential suitable habitat prediction result specifically includes: When the genetic distance is less than the preset genetic distance and the potential suitable area prediction result shows that the suitability of the suitable area is greater than the preset suitability, it is determined that the plant to be evaluated has an invasive risk.

5. The plant invasion risk assessment method according to any one of claims 1 to 4, characterized in that: Before determining the genetic distance between the ITS sequence of the plant to be evaluated and the ITS sequence of the target sample, the method includes: Using the DNA of the plant to be evaluated as a template, a forward primer, a reverse primer and a DNA polymerase premix are added in sequence to perform a PCR amplification reaction to obtain the ITS sequence of the plant to be evaluated.

6. A plant invasion risk assessment device, characterized in that: include: a determining unit, configured to determine a genetic distance between an ITS sequence of the plant to be evaluated and an ITS sequence of a target sample, wherein the ITS sequence of the target sample is selected from ITS sequences of plants of the same genus as the plant to be evaluated; an acquisition unit, configured to acquire a target climate factor of the plant to be evaluated, wherein the target climate factor is selected based on the climate factor of the location to be evaluated; A prediction unit, configured to input the target climate factor of the plant to be evaluated into a maximum information entropy model, and obtain a prediction result of a potential suitable growth area of the plant to be evaluated at the location to be evaluated outputted by the maximum information entropy model; An evaluation unit, configured to determine the invasiveness risk of the plant to be evaluated based on the genetic distance and the potential suitable habitat prediction result; The step of obtaining the target climate factor of the plant to be evaluated specifically includes: Obtain the geographical distribution areas of the plants to be assessed from the Global Biodiversity Information Platform; Obtaining a climate factor dataset of the geographical distribution area of the plant to be evaluated from the World Climate Database; Determining the climate factors of the location to be evaluated, and calculating the similarity between each climate factor in the climate factor dataset and the climate factors of the location to be evaluated; A target climate factor is selected from the climate factor dataset based on the similarity.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the plant invasion risk assessment method according to any one of claims 1 to 5 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the plant invasion risk assessment method according to any one of claims 1 to 5 is implemented.

9. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the plant invasion risk assessment method according to any one of claims 1 to 5 is implemented.

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