Prediction method and computer system of meteorological suitability level for wheat scab epidemic

Abstract

The invention discloses a method for predicting the meteorological suitability level of wheat scab epidemic, which mainly includes analyzing the historical meteorological data of wheat scab epidemic samples, determining the meteorological disease-promoting index of each growth stage of wheat, and then establishing a meteorological suitability level prediction model for wheat scab epidemic, wherein the meteorological suitability level prediction model for wheat scab epidemic includes a comprehensive scab index sub-model; inputting future meteorological forecast data within the wheat field area into the meteorological suitability level prediction model for wheat scab epidemic for prediction, and obtaining the meteorological suitability level of future wheat scab epidemic. The invention is based on the comprehensive scab index sub-model, combined with refined grid weather forecast products, to achieve real-time rolling prediction of meteorological suitability levels of scab in various places. According to the prediction results, the meteorological conditions are timely controlled to control the disease occurrence area, occurrence area and occurrence period, seize the best time and dosage of medication, and reduce the harm of chemical pesticides while improving the timeliness of wheat scab disease defense, thereby improving the ecological benefits of wheat production.

Description

Technical Field

[0001] The invention belongs to the technical field of agricultural damage prediction, and particularly relates to a method for predicting meteorological suitability level of wheat scab epidemic. Background Art

[0002] Wheat fusarium head blight is an epidemic disease caused by a variety of Fusarium species. The pathogens infect wheat floral organs, causing necrosis of the conducting tissues, stopping the grain filling process, and affecting wheat yield and quality. In recent years, due to climate change, the frequency of recurrence of fusarium head blight in major wheat-producing areas has increased, with large inter-annual differences. In epidemic years, it can cause a 20% to 50% reduction in wheat production, or even a total crop failure, and has become a major hidden danger affecting high-quality and high-yield wheat.

[0003] The prevalence of wheat fusarium head blight is closely related to meteorological conditions, and the impact is different in different growth stages. The impact of meteorological conditions on wheat fusarium head blight can be divided into three stages: the first stage, before wheat heading, mainly affects the formation and accumulation of asci and ascospores of fusarium head blight fungi; the second stage, during the heading-flowering period, affects the spread and infection of ascospores; the third stage, after flowering, affects the degree of disease development. Using the refined prediction results of meteorological factors to carry out fusarium head blight epidemic level prediction can prevent and control the occurrence of the disease in advance.

[0004] At present, the research on the prediction of meteorological suitability level for wheat fusarium head blight epidemic mainly uses the long-scale meteorological factors and disease observation data in the early stage of heading and flowering, and uses statistical methods to establish a regression model to predict the epidemic trend of wheat fusarium head blight; or based on the impact of heading and flowering meteorology on the disease, an index is established to predict the level of fusarium head blight. In the previous studies, only the impact of heading and flowering meteorology on the disease was considered when predicting the epidemic level of the disease. There were few analyses on the impact of meteorological conditions before and after the critical period of disease susceptibility, and most of them used statistical and deep learning methods. The continuous impact of meteorological conditions on the development of the disease was not considered, lacking mechanism, and it was impossible to make a rolling prediction of the degree of disease occurrence on a daily basis, and there was a certain lag in the grasp of the occurrence and development of the disease. Summary of the invention

[0005] The invention aims at the problems existing in the prior art and proposes a method for predicting the meteorological suitability level of wheat fusarium rust epidemic, which can accurately and in real time predict the weather.

[0006] To achieve the above object, the present invention provides a method for predicting the meteorological suitability level for wheat scab epidemic, which mainly includes:

[0007] Step 1: By analyzing the meteorological data of the historical wheat fusarium head blight epidemic, the meteorological disease-promoting indicators of wheat at each growth stage are determined, and then a meteorological suitability level prediction model for the epidemic of wheat fusarium head blight is established;

[0008] Step 2: Input the future weather forecast data within the wheat field area into the wheat scab epidemic weather suitability level prediction model to predict and obtain the future wheat scab epidemic weather suitability level;

[0009] Among them, the method for constructing the prediction model of meteorological suitability level for wheat scab epidemic is as follows:

[0010] Step 11: Divide the growth stages of wheat;

[0011] Step 12: Determine the meteorological disease-promoting indicators at each growth stage based on the historical meteorological data of wheat fusarium head blight epidemic samples; the meteorological disease-promoting indicators include the average temperature on the disease-promoting day and the relative humidity on the disease-promoting day;

[0012] Step 13: According to the formula:

[0013] j=1,2,3,T i,j >T o,j ,RH i,j >RH o,j ;

[0014] Calculate the suitable amount of meteorological conditions D for each monitoring day in each growth stage of wheat i,j :where i is the monitoring day number; j is the wheat growth stage number, T i,j represents the average temperature of wheat on the ith monitoring day at the jth growth stage; RH i,j represents the relative humidity of wheat on the ith monitoring day at the jth growth stage; T o,j represents the average temperature of disease-promoting days in the jth growth stage of wheat; RH o,j represents the disease-promoting relative humidity of wheat at the jth growth stage; D i,j It represents the suitable meteorological conditions for the epidemic of fusarium head blight on the i-th monitoring day of the j-th growth stage of wheat;

[0015] Step 14: Combine historical meteorological data and formulas for wheat fusarium wilt epidemic samples The comprehensive fusarium head blight index Z sub-model was constructed; n1 represents the total monitoring days of wheat heading-heading stage; n2 represents the total monitoring days of wheat heading-flowering stage; n3 represents the total monitoring days of wheat flowering-milky stage; and are the cumulative suitable meteorological conditions for the epidemic of wheat diseases at each growth stage; α, β, and γ are the weight coefficients of meteorological factors at three different growth stages affecting the final disease occurrence;

[0016] Step 15: Calculate the corresponding comprehensive fusarium scab index Z according to the meteorological data of each wheat fusarium scab epidemic sample; then divide the meteorological suitability level of fusarium scab epidemic according to the final diseased ear rate of each wheat fusarium scab epidemic sample; obtain the range of comprehensive fusarium scab index corresponding to each disease degree; and complete the construction of the meteorological suitability level prediction model for wheat fusarium scab epidemic.

[0017] Further, the method of inputting the future weather forecast data into the established wheat scab epidemic weather suitability grade prediction model for prediction is as follows:

[0018] Step 21: Determine the growth stage according to the growth status of wheat;

[0019] Step 22: According to the formula:

[0020] j=1,2,3,T i,j >T o,j ,RH i,j >RH o,j ;

[0021] Predict the suitable meteorological conditions for the epidemic of Fusarium head blight every day in the future;

[0022] Step 23: Calculate the future comprehensive fusarium head blight index Z according to the comprehensive fusarium head blight index Z sub-model;

[0023] Step 24: According to the daily comprehensive fusarium scab index Z obtained in step 23, the corresponding daily fusarium scab epidemic meteorological suitability level is obtained.

[0024] Furthermore, the growth stage of wheat is divided into three stages, namely: heading-heading, heading-flowering, and flowering-milk maturity. This can effectively avoid the deviation caused by using a single indicator to judge the occurrence of the disease during the entire disease monitoring period.

[0025] Furthermore, the disease-promoting average temperature is the average of the daily average temperatures of the samples with a final diseased ear rate > 1% at each growth stage; the disease-promoting relative humidity is the average of the relative humidity of the samples with a final diseased ear rate > 1% at each growth stage.

[0026] Furthermore, the weight coefficients of the meteorological factors in the three different growth stages affecting the final disease occurrence are determined by: continuously adjusting the values ​​of α, β and γ, wherein the value range of α, β and γ is 0-1, and the constraint condition is α+β+γ=1.0; setting the adjustment step of parameters α, β and γ to 0.01; inputting each wheat scab epidemic sample into the comprehensive scab index Z sub-model to calculate the comprehensive scab index Z respectively, until the correlation coefficient between the comprehensive scab index Z and the final diseased ear rate of the corresponding wheat scab epidemic sample reaches the maximum, and the optimal values ​​of α, β and γ are obtained. Considering the differences in the impact of meteorological factors in different growth stages on the occurrence of diseases and the cumulative effect of disease damage, the dynamic process of continuous occurrence and development of diseases is better reflected.

[0027] Furthermore, the wheat field is divided into grid points, and the future weather forecast of each grid point is obtained respectively. In this way, the prediction result is more accurate. Furthermore, the grid point is a square of 3km×3km.

[0028] The present invention also provides a computer-readable medium storing software, wherein the software includes instructions that can be executed by one or more computers, and the instructions enable the one or more computers to perform operations through such execution, and the operations include the process of the aforementioned method for predicting the meteorological suitability level for the epidemic of wheat fusarium wilt.

[0029] The present invention also provides a computer system, comprising:

[0030] one or more processors;

[0031] A memory stores operable instructions, wherein when the instructions are executed by the one or more processors, the one or more processors perform operations, wherein the operations include the process of the aforementioned method for predicting the meteorological suitability level for the epidemic of wheat fusarium wilt.

[0032] Working principle: The present invention determines disease-promoting indicators according to the climatic characteristics of fusarium head blight occurrence in previous years, combined with the three growth stages of wheat growth, namely, heading-heading, heading-flowering, and flowering-milk maturity. Starting from the meteorological conditions that promote fusarium head blight, the present invention considers the differences in the effects of meteorological factors at different growth stages on the occurrence of the disease and the cumulative effects of the disease on the occurrence of the disease, and constructs a comprehensive fusarium head blight index sub-model. The comprehensive fusarium head blight index sub-model is combined with meteorological forecast data to predict the meteorological suitability level for the epidemic of wheat fusarium head blight.

[0033] Beneficial effects: Compared with the prior art, the present invention is based on a comprehensive fusarium head blight index, combined with refined grid weather forecast products, to achieve real-time rolling predictions of meteorological suitability levels for fusarium head blight in various places. According to the forecast results, the meteorological conditions are timely controlled to control the areas, areas and time periods where the disease occurs, and the best time and dosage for medication are seized. While improving the timeliness of disease prevention, the hazards of chemical pesticides can be reduced, and the ecological benefits of wheat production can be improved; at the same time, the present invention effectively avoids the deviation caused by using a single indicator to judge the occurrence of the disease during the entire disease monitoring period, greatly improving the accuracy of the prediction. Furthermore, considering that the occurrence and development of fusarium head blight is a gradually aggravated process, the comprehensive fusarium head blight index sub-model constructed by the present invention is expressed in the form of a weighted summation of the accumulated suitable meteorological conditions for fusarium head blight in each growth stage of wheat, which can better reflect the trend of the gradual increase in the disease ear rate and the changes in the disease level. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The present invention provides a schematic flow chart of the method. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the examples of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Embodiment: This embodiment discloses a method for predicting the meteorological suitability level for wheat scab epidemic, which mainly includes the following steps:

[0037] Step 1: Establish a prediction model of the meteorological suitability level for wheat fusarium scab epidemics based on the meteorological data of historical wheat fusarium scab epidemics. The specific steps include:

[0038] Step 11: Divide the growth stage. According to the influence of meteorological conditions at different stages on the occurrence of wheat fusarium, the growth stage of wheat is specifically divided into three stages: heading-heading, heading-flowering, and flowering-milk maturity.

[0039] Step 12: Determine the meteorological disease-promoting indexes at each growth stage. Using historical meteorological data, determine the epidemic samples of wheat fusarium scabiei according to the observation results of wheat growth period and final diseased ear rate of fusarium scabiei at different stations and different years. Calculate the mean of daily average temperature and relative humidity of each growth stage of the epidemic samples of wheat fusarium scabiei, analyze the climate background when fusarium scabiei occurs, and determine the meteorological index value T suitable for the occurrence of fusarium scabiei at each growth stage. o,j RH o,j Among them, T o,jrepresents the average temperature of disease-promoting days in the jth growth stage of wheat; RH o,j Represents the disease-promoting relative humidity of wheat in the jth growth stage. In meteorological data, daily temperature values ​​include daily average temperature, daily maximum temperature, daily minimum temperature, etc. Common calculation methods for daily average temperature include the average of daily maximum and minimum temperatures, four scheduled averages (i.e., the average of 02:00, 08:00, 14:00 and 20:00) and the 24-hour average method. The mean of the daily average temperature is the mean of the daily average temperatures of all days in a certain stage. When the plant protection department conducts a systematic survey on the diseased ear rate, it starts from the beginning of heading and observes daily. After the diseased ears are first seen, the survey is conducted every 3 days until the disease stabilizes, which is generally in the waxy stage of wheat. The diseased ear rate surveyed at this time is the final diseased ear rate.

[0040] The historical data used in this embodiment are: the final diseased ear rate and occurrence area observation data of 8 wheat scab disease observation sites from 2000 to 2015, that is, a total of 128 wheat scab epidemic samples; and the wheat growth period observation data and daily meteorological observation data of the corresponding observation sites from 2000 to 2015, wherein the daily meteorological observation data mainly include the daily average temperature and relative humidity. Select the samples with the final diseased ear rate>1%, and respectively count the mean of the daily average temperature and the mean of the relative humidity of all days in the three wheat growth stages of heading-heading, heading-flowering, and flowering-milk maturity, and obtain the wheat scab disease promotion index at different growth stages as shown in Table 1.

[0041] Table 1 Disease promotion indexes of fusarium head blight in different growth stages of wheat

[0042]

[0043] Step 13: Calculate the suitable meteorological conditions for the epidemic of fusarium smut on each monitoring day in each growth stage sample according to the formula:

[0044]

[0045] Where i is the monitoring day number; j is the wheat growth stage number, i.e. j=1 represents the wheat heading-heading stage, j=2 represents the wheat heading-flowering stage, and j=3 represents the wheat flowering-milky stage; T i,j represents the average temperature on the ith monitoring day during the jth growth stage of wheat; RH i,j represents the relative humidity on the ith monitoring day of the jth growth stage of wheat; D i,j It represents the suitable meteorological conditions for the epidemic of fusarium wilt on the i-th monitoring day during the j-th growth stage of wheat.

[0046] Step 14: Construct a comprehensive fusarium head blight index Z model. Combining the germination, infection, latent growth and symptom manifestation process of the disease pathogen, a single-point comprehensive fusarium head blight index Z is constructed as follows:

[0047]

[0048] Among them, n1 represents the total monitoring days of wheat heading-heading stage; n2 represents the total monitoring days of wheat heading-flowering stage; n3 represents the total monitoring days of wheat flowering-milky stage; and are the cumulative suitable meteorological conditions for disease epidemics at each growth stage of wheat; α, β, and γ are the weight coefficients of meteorological factors at three different growth stages affecting the final occurrence of diseases, which are determined using optimization technology.

[0049] In this embodiment, the optimal values ​​of α, β, and γ are determined based on the meteorological historical data of the samples with a final diseased ear rate of >1%, wherein the value range of α, β, and γ is 0-1, and the constraint condition is α+β+γ=1.0; the adjustment step of the parameters α, β, and γ is set to 0.01; the meteorological historical data sequence of the wheat scab epidemic samples with a final diseased ear rate of >1% is respectively input into the comprehensive scab index Z model, and the adjustment step of the parameters α, β, and γ is adjusted until the correlation coefficient between the comprehensive scab index Z and the corresponding final diseased ear rate reaches the maximum, and the optimal values ​​of α, β, and γ are obtained. Thus, the construction of the comprehensive scab index Z model is completed.

[0050] Step 15: Classification of meteorological suitability for fusarium head blight epidemic. Using historical meteorological observations and paired disease observation data, the comprehensive fusarium head blight index Z of each wheat fusarium head blight epidemic sample is calculated according to the comprehensive fusarium head blight index Z model constructed in step 14, and the comprehensive fusarium head blight index Z of the wheat fusarium head blight epidemic sample is paired with its corresponding final fusarium head blight disease rate; the fusarium head blight disease occurrence degree is divided according to the range of the final fusarium head blight disease rate, and the relationship between the final fusarium head blight rate and its corresponding comprehensive fusarium head blight index Z is combined to obtain the value range of the comprehensive fusarium head blight index Z corresponding to different fusarium head blight disease occurrence degree levels.

[0051] In this embodiment, the final diseased ear rate of fusarium scabiei at each site each year, that is, the diseased ear rate of a total of 128 historical samples, is sorted from small to large; the comprehensive fusarium scabiei index Z of each site each year is sorted in combination with the corresponding final diseased ear rate of fusarium scabiei, that is, the comprehensive fusarium scabiei index Z calculated from the 128 historical samples is sorted according to the final diseased ear rate of the corresponding sample; based on the fusarium scabiei disease occurrence degree level divided according to the range of the final diseased ear rate of fusarium scabiei, combined with the relationship between the final diseased ear rate of fusarium scabiei and its corresponding comprehensive fusarium scabiei index Z, the value range of the comprehensive fusarium scabiei index corresponding to different fusarium scabiei disease occurrence degree levels is obtained. Thus, the construction of the meteorological suitability level prediction model for wheat fusarium scabiei epidemic is completed.

[0052] Among them, the division of disease occurrence degree refers to the "Technical Specifications for Wheat Fusarium Scab Monitoring and Reporting". According to the final diseased ear rate thresholds corresponding to the three levels of disease occurrence, the disease occurrence degree is divided into three levels: mild occurrence, moderate occurrence, and severe occurrence. The corresponding final diseased ear rate (DR) ranges are DR≤10%, 10%<DR≤40%, and DR>40%, respectively.

[0053] In this embodiment, the specific division results based on the historical data used are shown in Table 2.

[0054] Table 2 Classification of meteorological suitability for fusarium scurf disease epidemics

[0055]

[0056] Step 2: Input the weather forecast data of the wheat field in the next few days into the established wheat scab epidemic weather suitability level prediction model to predict and obtain the weather suitability level of wheat scab epidemic in the next few days; specifically including:

[0057] Step 21: Determine the growth stage according to the growth status of wheat;

[0058] Step 22: Divide the wheat field into grid points and obtain the future weather forecast for each grid point. j=1,2,3,T i,j >T o,j ,RH i,j >RH o,j Predict the suitable amount of popular meteorological conditions for the future day; in this embodiment, the wheat field is refined into a square of 3km×3km.

[0059] Step 23: Calculate the comprehensive fusarium head blight index Z in the next few days according to the comprehensive fusarium head blight index Z sub-model;

[0060] Step 24: Obtain the corresponding meteorological suitability level for the epidemic of fusarium smut according to the comprehensive fusarium smut index Z obtained in step 23 in the next few days. This completes the forecast of the meteorological suitability level for the epidemic of fusarium smut in the next few days. A rolling forecast of the meteorological suitability level for the occurrence of refined diseases in the region is achieved.

[0061] In actual forecasting, once wheat enters the heading stage, the occurrence of diseases will be monitored and forecasted. Based on the actual observation of meteorological elements and combined with weather forecast products, the actual and predicted results of meteorological elements such as daily average temperature and relative humidity required to determine the disease-causing day are extracted, and the comprehensive fusarium rust index value is calculated, thereby realizing dynamic monitoring of the meteorological suitability level and possible epidemic degree of fusarium rust until the end of monitoring in the milky stage.

[0062] Dynamic monitoring means that the forecast time is updated daily. By continuously accumulating and analyzing the disease-promoting meteorological conditions since the monitoring period, the suitability of meteorological conditions for the occurrence of ergot and its level of occurrence can be judged in the future. At the same time, by continuously replacing and utilizing the latest forecast products and actual observation data, the forecast accuracy of weather forecast products with a period of 7 days can be improved day by day.

[0063] The meteorological suitability level for the epidemic of wheat fusarium scabiei in 2016 was calculated by using the method for predicting the meteorological suitability level for the epidemic of wheat fusarium scabiei provided by the present invention.

[0064] In 2016, Fusarium head blight was generally severe to widespread. It was widespread in most of Huainan and moderately severe in Huaibei. The refined integrated optimal forecast system "RIOF" (Refined Integration Optimal Forecast) of Jiangsu Meteorological Bureau was used to produce a refined forecast product with a spatial resolution of 0.03°.

[0065] According to the dynamic forecast results of meteorological suitability level for scab on May 20, 2016:

[0066] In late May, the meteorological conditions were very suitable for the rapid development and aggravation of wheat fusarium head blight. According to the results of the meteorological suitability classification for fusarium head blight epidemics in Table 2, as of May 27, the comprehensive fusarium head blight index in the western region between southern Jiangsu and Jianghuai along the coast was greater than 9, and the meteorological suitability level was level 3, indicating severe wheat fusarium head blight.

[0067] According to the investigation of the Provincial Plant Protection Station: In early May, diseased ears were found in southern Jiangsu and along the Yangtze River; in mid-May, diseased ears were generally found in all wheat-growing areas of the province, with a diseased ear rate of 10% to 15%; in late May, the wheat-filling areas south of the Huaihe River in our province experienced multiple rainfall processes, which was very conducive to the spread of fusarium head blight. The disease rate increased rapidly. On May 30, the system monitoring and investigation of field and seedling determination showed that the diseased ear rate rose to 50% to 65%. In the observation fields and experimental fields in southern Jiangsu and along the Yangtze River, the diseased ear rate of fusarium head blight exceeded 70%.

[0068] It can be seen that the meteorological suitability levels for fusarium head blight determined by the method provided by the present invention are basically consistent with the actual occurrence of fusarium head blight in wheat.

[0069] The present invention also provides a computer-readable medium storing software, wherein the software includes instructions that can be executed by one or more computers, and the instructions enable the one or more computers to perform operations through such execution, and the operations include the process of the aforementioned method for predicting the meteorological suitability level for the epidemic of wheat fusarium wilt.

[0070] The present invention also provides a computer system, comprising: one or more processors; a memory storing operable instructions, wherein when the instructions are executed by the one or more processors, the one or more processors perform operations, wherein the operations include the process of the aforementioned method for predicting the meteorological suitability level for the epidemic of wheat fusarium wilt.

[0071] It should be understood that the example of the above-mentioned wheat scab epidemic weather suitability level prediction method of the present invention can be in any computer system including data storage and data processing, and the above-mentioned computer system can be at least one electronic processing system or electronic device including a processor and a memory, such as a PC, whether it is a personal PC, a commercial PC, or a PC for graphics processing, or a server-level PC. These PCs realize wired and / or wireless data transmission by having a data interface and / or a network interface.

[0072] In other embodiments, the computer system may also be a server, especially a cloud server, having data storage, processing and network communication functions.

[0073] An exemplary computer system generally includes at least one processor, a memory, and a network interface connected by a system bus. The network interface is used to communicate with other devices / systems.

[0074] The processor is used to provide computation and control of the system.

[0075] The memory includes non-volatile memory and cache.

[0076] Non-volatile memory generally has a massive storage capacity and can store operating systems and computer programs. These computer programs may include operable instructions that, when executed by one or more processors, enable the one or more processors to execute the process of the method for predicting the meteorological suitability level for the epidemic of wheat fusarium wilt of the aforementioned embodiment of the present invention.

[0077] In necessary or reasonable implementations, the aforementioned computer system, whether a PC device or a server, may also include more or fewer components than those shown in the diagram, or a combination, or use different hardware, software or other components or different deployment methods.

[0078] Although the present invention has been disclosed as above with preferred embodiments, it is not intended to limit the present invention. A person with ordinary knowledge in the technical field to which the present invention belongs may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be determined by the definition of the claims.

Claims

1. A method for predicting the meteorological suitability level for wheat scab epidemic, characterized in that: Mainly include: Step 1: By analyzing the meteorological data of the historical wheat fusarium head blight epidemic, the meteorological disease-promoting indicators of wheat at each growth stage are determined, and then a meteorological suitability level prediction model for the epidemic of wheat fusarium head blight is established; Step 2: Input the future weather forecast data within the wheat field area into the wheat scab epidemic weather suitability level prediction model to predict and obtain the future wheat scab epidemic weather suitability level; Among them, the method for constructing the prediction model of meteorological suitability level for wheat scab epidemic is as follows: Step 11: Divide the growth stages of wheat; Step 12: Determine the meteorological disease-promoting indicators at each growth stage based on the historical meteorological data of wheat fusarium head blight epidemic samples; the meteorological disease-promoting indicators include the average temperature on the disease-promoting day and the relative humidity on the disease-promoting day; Step 13: According to the formula: ； Calculate the suitable amount of prevailing meteorological conditions for each monitoring day in each growth stage of wheat D i,j :in, i Number the monitoring day; j Number the wheat growth stages. T i,j Indicates that wheat j The first reproductive stage i The average temperature of the monitoring day; RH i,j Indicates that wheat j The first reproductive stage i Relative humidity on each monitoring day; T o,j Wheat j The average temperature on disease-promoting days during each growth stage; RH o,j Wheat j Disease-promoting relative humidity at each growth stage; D i,j Wheat j The reproductive stage i Suitable meteorological conditions for the epidemic of fusarium head blight on each monitoring day; Step 14: Combine historical meteorological data and formulas for wheat fusarium wilt epidemic samples ； The comprehensive fusarium head blight index Z sub-model was constructed; n 1 indicates the total monitoring days of wheat booting-heading stage; n 2 indicates the total monitoring days during the heading-flowering stage of wheat; n 3 represents the total number of monitoring days in the flowering-milky stage of wheat; , and are the cumulative suitable meteorological conditions for the epidemic of fusarium head blight at each growth stage of wheat; α, β, and γ are the weight coefficients of meteorological factors affecting the final disease occurrence at three different growth stages; Step 15: Calculate the corresponding comprehensive fusarium head blight index Z according to the meteorological data of each wheat fusarium head blight epidemic sample; then divide the meteorological suitability level of fusarium head blight epidemic according to the final diseased ear rate of each wheat fusarium head blight epidemic sample; obtain the range of comprehensive fusarium head blight index corresponding to each disease degree; and complete the construction of the meteorological suitability level prediction model for wheat fusarium head blight epidemic; The disease-promoting daily average temperature is the average of the daily average temperatures of the samples with a final diseased ear rate of >1% at each growth stage; the disease-promoting relative humidity is the average of the relative humidity of the samples with a final diseased ear rate of >1% at each growth stage; The method for determining the weight coefficient of the meteorological factors in the three different growth stages affecting the final disease occurrence is as follows: continuously adjusting the values ​​of α, β and γ, wherein the value range of α, β and γ is 0-1, and the constraint condition is α + β + γ = 1.0; setting the adjustment step of parameters α, β, γ to 0.01; inputting each wheat fusarium scaly epidemic sample into the comprehensive fusarium scaly index Z sub-model to calculate the comprehensive fusarium scaly index respectively. Z , until the comprehensive fusarium index Z When the correlation coefficient with the final diseased ear rate of the corresponding wheat fusarium epidemic sample reaches the maximum, the optimal values ​​of α, β, and γ are obtained.

2. The method for predicting meteorological suitability grade for wheat scab epidemic according to claim 1, characterized in that: The growth stage of wheat is divided into three stages, namely: heading-heading, heading-flowering, and flowering-milk maturity.

3. The method for predicting meteorological suitability grade for wheat scab epidemic according to claim 1, characterized in that: The wheat field is divided into grid points, and the future weather forecast for each grid point is obtained.

4. The method for predicting meteorological suitability grade for wheat scab epidemic according to claim 3, characterized in that: The grid points are 3km×3km squares.

5. A computer-readable medium storing software, characterized in that: The software includes instructions that can be executed by one or more computers, and the instructions enable the one or more computers to perform operations through such execution, and the operations include the process of the method for predicting the meteorological suitability level for the epidemic of wheat fusarium as described in any one of claims 1-4.

6. A computer system, characterized in that: include: one or more processors; A memory storing operable instructions, wherein when the instructions are executed by the one or more processors, the one or more processors perform operations, wherein the operations include the process of the method for predicting the meteorological suitability level for the epidemic of wheat fusarium wilt as described in any one of claims 1 to 4.

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