Vegetable disease and insect pest biological control method and system for preventing insect pests through microorganisms

Abstract

The invention discloses a vegetable pest biological control method and system for microbial pest control, relates to the field of pest control, solves the problem of poor pertinence of a vegetable pest biological control method, and comprises the following steps: S1, respectively obtaining a periodic pest type distribution coefficient, a periodic peak pest quantity ratio and a periodic pest type quantity value; s2, dividing the pest control region into a first type of pest control region to a second type of pest control region by analyzing the pest preliminary collection data, obtaining regional pest preliminary classification data, and performing environment analysis on the second type of pest control region to obtain regional screening data; and S3, according to the insect pest area analysis data, carrying out insect pest control method matching on the insect pest control area, so that the pertinence of the microbial insect pest control method can be improved.

Description

Technical Field

[0001] The invention belongs to the field of pest control and relates to microbial technology, and specifically to a biological control method and system for vegetable diseases and insect pests by using microorganisms to prevent pests. Background Art

[0002] The existing biological control methods for vegetable pests have the following defects when controlling vegetable pests:

[0003] 1. Failure to analyze the species of vegetable pests in the pest control area resulted in unsatisfactory results when using microorganisms for pest control;

[0004] 2. Failure to analyze the soil environment in the pest control area resulted in the lack of environmental specificity of the microorganisms used for pest control, which led to poor pest control results;

[0005] To this end, we propose a biological control method and system for vegetable diseases and insect pests using microorganisms to prevent insect pests. Summary of the invention

[0006] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a biological control method and system for vegetable diseases and insect pests using microorganisms to prevent pests. The present invention is based on respectively obtaining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio and the periodic pest species quantity value, obtaining preliminary pest collection data, obtaining regional pest preliminary classification data and regional screening data by analyzing the preliminary pest collection data, obtaining pest regional analysis data, and matching pest control methods to pest control areas according to the pest regional analysis data.

[0007] In order to achieve the above object, the present invention adopts the following technical scheme: a biological control method for vegetable diseases and insect pests by microbial pest prevention, comprising the following specific steps:

[0008] Step S1: respectively obtaining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio and the periodic pest species quantity value to obtain preliminary pest collection data;

[0009] Step S2: obtaining a regional pest preliminary division coefficient by analyzing the preliminary pest collection data, obtaining a regional pest preliminary division coefficient threshold and performing numerical comparison with the regional pest preliminary division coefficient, dividing the pest control area into a first type of pest control area to a second type of pest control area according to the numerical comparison result, obtaining regional pest preliminary classification data, performing environmental analysis on the second type of pest control area according to the regional pest preliminary classification data, obtaining regional screening data, and defining the regional pest preliminary classification data and the regional screening data as pest regional analysis data;

[0010] Step S3: Match the pest control method to the pest control area according to the pest area analysis data.

[0011] Furthermore, the step S1 further includes the following specific steps:

[0012] Step S11: in the process of performing pest control in the pest control area, marking a pest monitoring cycle, and dividing the pest monitoring cycle into a plurality of pest monitoring sub-cycles of equal duration;

[0013] Step S12: randomly selecting one pest monitoring sub-cycle from the plurality of pest monitoring sub-cycles as a sample pest monitoring sub-cycle;

[0014] Step S13: performing pest sample monitoring within the sample pest monitoring sub-period, and obtaining the pest sample analysis coefficient corresponding to the sample pest monitoring sub-period;

[0015] Step S14: respectively obtaining preliminary pest monitoring data corresponding to each pest monitoring sub-period to obtain a plurality of preliminary pest monitoring data;

[0016] Step S15: obtaining the periodic pest species quantity distribution coefficient corresponding to each sample pest monitoring sub-period according to the plurality of preliminary pest monitoring data, obtaining a plurality of pest species quantity distribution coefficients, and averaging the obtained plurality of pest species quantity distribution coefficients to obtain the periodic pest species distribution coefficient;

[0017] Step S16: obtaining the peak pest quantity ratio corresponding to each sample pest monitoring sub-period according to the plurality of preliminary pest monitoring data, obtaining a plurality of peak pest quantity ratios, averaging the plurality of peak pest quantity ratios, and obtaining the period peak pest quantity ratio;

[0018] Step S17: obtaining the sample pest species quantity values ​​corresponding to each sample pest monitoring sub-period according to the multiple preliminary pest monitoring data, obtaining multiple sample pest species quantity values, and averaging the obtained multiple sample pest species quantity values ​​to obtain the period pest species quantity value;

[0019] Step S18: defining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio and the periodic pest species quantity value as preliminary pest collection data.

[0020] Furthermore, the step S13 further includes the following specific steps:

[0021] Step S131: within the sample pest monitoring sub-period, a fixed number of vegetable pests are randomly captured in the pest control area to obtain periodic pest analysis samples;

[0022] Step S132: obtaining the number of pests in the periodic pest analysis sample to obtain a total number value of the sample pests;

[0023] Step S133: acquiring the pest species of the periodic pest analysis sample to obtain the number of sample pest species;

[0024] Step S134: classifying the pests in the periodic pest analysis sample into first to ath pests according to their types;

[0025] Step S135: respectively obtaining the number values ​​corresponding to the first to a-th pest types, obtaining the first to a-th pest number values, comparing the first to a-th pest number values, and marking the pest number value with the largest value as the peak pest number value;

[0026] Step S136: Calculate the ratio of the peak pest population value to the total sample pest population value to obtain the peak pest population ratio;

[0027] Step S137: Obtaining the number distribution coefficient of periodic pest species;

[0028] Step S138: defining the period pest species quantity distribution coefficient, the peak pest quantity ratio and the sample pest species quantity value as preliminary pest monitoring data corresponding to the sample pest monitoring sub-period.

[0029] Furthermore, the step S2 further includes the following specific steps:

[0030] Step S21: obtaining preliminary pest collection data, and obtaining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio, and the periodic pest species quantity value according to the preliminary pest collection data;

[0031] Step S22: Calculating the periodic pest species distribution coefficient, the periodic peak pest quantity ratio, and the periodic pest species quantity value to obtain the regional pest preliminary division coefficient;

[0032] Calculate the preliminary regional pest classification coefficient;

[0033] Step S23: obtaining a regional pest preliminary division coefficient threshold, performing numerical comparison between the regional pest preliminary division coefficient threshold and the regional pest preliminary division coefficient, and dividing the pest control area into a first type of pest control area and a second type of pest control area according to the numerical comparison result, to obtain regional pest preliminary classification data;

[0034] Step S24: performing regional environmental analysis on the second type of pest control area to obtain regional screening data;

[0035] Step S25: defining the regional pest preliminary classification data and the regional screening data as pest regional analysis data.

[0036] Furthermore, the step S3 further includes the following specific steps:

[0037] Step S31: obtaining pest area analysis data, and obtaining regional pest preliminary classification data and regional screening data according to the pest area analysis data;

[0038] Step S32: When the pest control area is a first type of pest control area, the pest biological control method matched thereto is a pest virus control method;

[0039] Step S33: When the pest control area is a second type of pest control area, further environmental analysis is performed for it according to the area screening data.

[0040] A biological pest control system for vegetables with microbial pest control, the specific working process of each module is as follows:

[0041] Data acquisition module: used to obtain the periodic pest species distribution coefficient, periodic peak pest quantity ratio and periodic pest species quantity value respectively, and obtain preliminary pest collection data;

[0042] Data analysis module: used to obtain preliminary classification data of regional pests and regional screening data by analyzing preliminary pest collection data, and obtain regional pest analysis data;

[0043] Pest control module: used to match pest control methods to pest control areas based on pest area analysis data.

[0044] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0045] 1. The present invention obtains the periodic pest species distribution coefficient, the periodic peak pest quantity ratio and the periodic pest species quantity value to analyze the pest species in the pest control area, collects different control methods for different pest types, and can improve the pertinence of the microbial pest control method;

[0046] 2. The present invention obtains the pest control matching coefficient to match the environment of the microbial control method in the pest control area, which can reduce the control cost while ensuring the control effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0048] Figure 1 It is a diagram of the implementation steps of the present invention;

[0049] Figure 2 is the overall system block diagram of the present invention;

[0050] Figure 3 It is a matching schematic diagram of the pest control method of the present invention. DETAILED DESCRIPTION

[0051] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. 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.

[0052] Embodiment 1

[0053] See also Figure 1 The present invention provides a technical solution: a biological control method for vegetable pests and diseases by microbial pest control, comprising the following specific steps:

[0054] Step S1: respectively obtaining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio and the periodic pest species quantity value to obtain preliminary pest collection data;

[0055] Step S11: in the process of performing pest control in the pest control area, marking a pest monitoring cycle, and dividing the pest monitoring cycle into a plurality of pest monitoring sub-cycles of equal duration;

[0056] Step S12: randomly selecting one pest monitoring sub-cycle from the plurality of pest monitoring sub-cycles as a sample pest monitoring sub-cycle;

[0057] Step S13: performing pest sample monitoring within the sample pest monitoring sub-period, and obtaining the pest sample analysis coefficient corresponding to the sample pest monitoring sub-period;

[0058] The step S13 further includes the following specific steps:

[0059] Step S131: within the sample pest monitoring sub-period, a fixed number of vegetable pests are randomly captured in the pest control area to obtain periodic pest analysis samples;

[0060] Step S132: obtaining the number of pests in the periodic pest analysis sample to obtain a total number value of the sample pests;

[0061] Step S133: acquiring the pest species of the periodic pest analysis sample to obtain the number of sample pest species;

[0062] Step S134: classifying the pests in the periodic pest analysis sample into first to ath pests according to their types;

[0063] Step S135: respectively obtaining the number values ​​corresponding to the first to a-th pest types, obtaining the first to a-th pest number values, comparing the first to a-th pest number values, and marking the pest number value with the largest value as the peak pest number value;

[0064] Step S136: Calculate the ratio of the peak pest population value to the total sample pest population value to obtain the peak pest population ratio;

[0065] Step S137: Obtaining the number distribution coefficient of periodic pest species;

[0066] The step S137 further includes the following specific steps:

[0067] Step S1371: Calculate the average number of pests by averaging the first pest number value to the ath pest number value;

[0068] Step S1372: Calculate the pest species quantity distribution coefficient of the period by combining the first pest quantity value to the ath pest quantity value and the average quantity of the pest species;

[0069] The distribution coefficient of the number of periodic pest species is calculated, and the specific formula is configured as follows:

[0070]

[0071] Among them, Zwf is the number distribution coefficient of periodic pest species, Kz1 to Kza are the number values ​​of the first pest to the number values ​​of the ath pest, Kzp is the average number of pest species, and a is the number value corresponding to the pest species of the periodic pest analysis sample;

[0072] Step S138: defining the period pest species quantity distribution coefficient, the peak pest quantity ratio and the sample pest species quantity value as preliminary pest monitoring data corresponding to the sample pest monitoring sub-period;

[0073] Step S14: respectively obtaining preliminary pest monitoring data corresponding to each pest monitoring sub-period to obtain a plurality of preliminary pest monitoring data;

[0074] Step S15: obtaining the periodic pest species quantity distribution coefficient corresponding to each sample pest monitoring sub-period according to the plurality of preliminary pest monitoring data, obtaining a plurality of pest species quantity distribution coefficients, and averaging the obtained plurality of pest species quantity distribution coefficients to obtain the periodic pest species distribution coefficient;

[0075] Step S16: obtaining the peak pest quantity ratio corresponding to each sample pest monitoring sub-period according to the plurality of preliminary pest monitoring data, obtaining a plurality of peak pest quantity ratios, averaging the plurality of peak pest quantity ratios, and obtaining the period peak pest quantity ratio;

[0076] Step S17: obtaining the sample pest species quantity values ​​corresponding to each sample pest monitoring sub-period according to the multiple preliminary pest monitoring data, obtaining multiple sample pest species quantity values, and averaging the obtained multiple sample pest species quantity values ​​to obtain the period pest species quantity value;

[0077] Step S18: defining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio and the periodic pest species quantity value as preliminary pest collection data;

[0078] Step S2: obtaining a regional pest preliminary division coefficient by analyzing the preliminary pest collection data, obtaining a regional pest preliminary division coefficient threshold and performing numerical comparison with the regional pest preliminary division coefficient, dividing the pest control area into a first type of pest control area to a second type of pest control area according to the numerical comparison result, obtaining regional pest preliminary classification data, performing environmental analysis on the second type of pest control area according to the regional pest preliminary classification data, obtaining regional screening data, and defining the regional pest preliminary classification data and the regional screening data as pest regional analysis data;

[0079] Step S21: obtaining preliminary pest collection data, and obtaining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio, and the periodic pest species quantity value according to the preliminary pest collection data;

[0080] Step S22: Calculating the periodic pest species distribution coefficient, the periodic peak pest quantity ratio, and the periodic pest species quantity value to obtain the regional pest preliminary division coefficient;

[0081] The preliminary regional pest classification coefficient is calculated, and the specific formula is as follows:

[0082]

[0083] Among them, Qcx is the preliminary division coefficient of regional pests, Fbx is the distribution coefficient of periodic pest species, Ksb is the ratio of the number of periodic peak pests, and Zls is the number of periodic pest species;

[0084] Step S23: obtaining a regional pest preliminary division coefficient threshold, performing numerical comparison between the regional pest preliminary division coefficient threshold and the regional pest preliminary division coefficient, and dividing the pest control area into a first type of pest control area and a second type of pest control area according to the numerical comparison result, to obtain regional pest preliminary classification data;

[0085] The step S23 further includes the following specific steps:

[0086] Step S231: respectively obtaining a periodic pest species distribution coefficient threshold, a periodic peak pest quantity ratio threshold, and a periodic pest species quantity threshold;

[0087] Step S232: Calculating the periodic pest species distribution coefficient threshold, the periodic peak pest quantity ratio threshold, and the periodic pest species quantity threshold to obtain a regional pest preliminary division coefficient threshold;

[0088] Step S233: when the periodic pest species distribution coefficient is greater than or equal to the periodic pest species distribution coefficient threshold, the corresponding pest control area is divided into a first type of pest control area;

[0089] Step S234: when the periodic pest species distribution coefficient is less than the periodic pest species distribution coefficient threshold, the corresponding pest control area is divided into a second type of pest control area;

[0090] Step S24: performing regional environmental analysis on the second type of pest control area to obtain regional screening data;

[0091] The step S24 further includes the following specific steps:

[0092] Step S241: selecting an environmental monitoring period in the process of performing environmental analysis on the second type of pest control area, and selecting a plurality of environmental monitoring points in the environmental monitoring period;

[0093] Step S242: respectively obtaining the regional environmental humidity value corresponding to each environmental monitoring point of the second type of pest control area, obtaining multiple regional environmental humidity values, and averaging the obtained multiple regional environmental humidity values ​​to obtain the regional environmental average humidity value, obtaining the environmental reference humidity value, calculating the difference between the regional environmental average humidity value and the environmental reference humidity value, and taking the absolute value of the obtained difference to obtain the regional humidity absolute difference;

[0094] Step S243: respectively obtaining the regional environmental pH value corresponding to each environmental monitoring point of the second type of pest control area to obtain multiple regional environmental pH values, and averaging the obtained multiple regional environmental pH values ​​to obtain the regional environmental average pH value, obtaining the environmental reference pH value, calculating the difference between the regional environmental average pH value and the environmental reference pH value, and taking the absolute value of the obtained difference to obtain the regional pH absolute difference;

[0095] Step S244: respectively obtaining the regional protein content corresponding to each environmental monitoring point in the second type of pest control area to obtain multiple regional protein contents, and averaging the obtained multiple regional protein contents to obtain the regional average protein content, obtaining the environmental benchmark protein content, calculating the difference between the regional average protein content and the environmental benchmark protein content, and taking the absolute value of the obtained difference to obtain the regional protein content difference;

[0096] Step S245: defining the regional protein content difference, the regional pH absolute difference and the regional humidity absolute difference as regional screening data;

[0097] Step S25: defining the regional pest preliminary classification data and the regional screening data as pest regional analysis data;

[0098] Step S3: Matching pest control methods to pest control areas according to pest area analysis data;

[0099] Step S31: obtaining pest area analysis data, and obtaining regional pest preliminary classification data and regional screening data according to the pest area analysis data;

[0100] Step S32: When the pest control area is a first type of pest control area, the pest biological control method matched thereto is a pest virus control method;

[0101] Step S33: When the pest control area is a second type of pest control area, further environmental analysis is performed for it according to the area screening data;

[0102] The step S33 further includes the following specific steps:

[0103] Step S331: obtaining the regional protein content difference, the regional pH absolute difference and the regional humidity absolute difference respectively according to the regional screening data;

[0104] Step S332: calculating the regional protein content difference, the regional pH absolute difference and the regional humidity absolute difference to obtain the pest control matching coefficient;

[0105] The pest control matching coefficient is calculated as follows:

[0106] Chf=Dbz+Phz+Sjz;

[0107] Among them, Chf is the pest control matching coefficient, Dbz is the regional protein content difference, pHz is the regional pH absolute difference, and Sjz is the regional humidity absolute difference;

[0108] Step S333: obtaining a pest control matching coefficient threshold, and comparing the pest control matching coefficient with the pest control matching coefficient;

[0109] Step S334: When the pest control matching coefficient is greater than or equal to the pest control matching coefficient threshold, a bacterial control method is matched for the pest control area;

[0110] Step S335: if the pest control matching coefficient is less than the pest control matching coefficient threshold, the fungus control method is matched to the pest control area;

[0111] In this application, if corresponding calculation formulas appear, the above calculation formulas are all dimensionless and take their numerical calculations. The weight coefficients, proportional coefficients and other coefficients in the formulas are set to a result value obtained by quantifying each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0112] Embodiment 2

[0113] See also Figure 2 , based on another concept of the same invention, a biological pest control system for vegetables with microbial pest control is now proposed, the system comprises a data acquisition module, a data analysis module, a pest control module and a server, the data acquisition module, the data analysis module and the pest control module are respectively connected to the server, and the server controls the data acquisition module, the data analysis module and the pest control module respectively;

[0114] The data acquisition module obtains the periodic pest species distribution coefficient, the periodic peak pest quantity ratio and the periodic pest species quantity value respectively, and obtains the preliminary pest collection data;

[0115] In the process of pest control in the pest control area, a pest monitoring cycle is marked and the pest monitoring cycle is divided into a number of pest monitoring sub-cycles of equal duration;

[0116] Randomly select one pest monitoring sub-cycle from multiple pest monitoring sub-cycles as a sample pest monitoring sub-cycle;

[0117] Conduct pest sample monitoring within the sample pest monitoring sub-period to obtain the pest sample analysis coefficient corresponding to the sample pest monitoring sub-period;

[0118] The details are as follows:

[0119] During the sample pest monitoring sub-period, a fixed number of vegetable pests are randomly captured in the pest control area to obtain periodic pest analysis samples;

[0120] The number of pests in the periodic pest analysis samples is obtained to obtain the total number of sample pests;

[0121] The pest species of the periodic pest analysis samples are obtained to obtain the number of sample pest species;

[0122] The pests in the periodic pest analysis samples are divided into the first type of pests to the ath type of pests according to their types;

[0123] It should be noted here that:

[0124] The a involved here is the quantity value corresponding to the pest species of the periodic pest analysis sample, and a is an integer greater than 0;

[0125] The number values ​​corresponding to the first type of pests to the ath type of pests are obtained respectively to obtain the first pest number value to the ath pest number value, and the first pest number value to the ath pest number value are compared in numerical value, and the pest number value with the largest numerical value is marked as the peak pest number value;

[0126] Calculate the ratio of the peak pest population value to the total sample pest population value to obtain the peak pest population ratio;

[0127] Get the distribution coefficient of the number of periodic pest species, as follows:

[0128] The average number of pest species is calculated by averaging the first pest number value to the ath pest number value;

[0129] The number distribution coefficient of pest species in a period is obtained by calculating the number of pests from the first pest number value to the ath pest number value and the average number of pest species;

[0130] The distribution coefficient of the number of periodic pest species is calculated, and the specific formula is configured as follows:

[0131]

[0132] Among them, Zwf is the number distribution coefficient of periodic pest species, Kz1 to Kza are the number values ​​of the first pest to the number values ​​of the ath pest, Kzp is the average number of pest species, and a is the number value corresponding to the pest species of the periodic pest analysis sample;

[0133] The period pest species quantity distribution coefficient, peak pest quantity ratio and sample pest species quantity value are defined as the preliminary pest monitoring data corresponding to the sample pest monitoring sub-period;

[0134] Repeat the process of obtaining the preliminary pest monitoring data corresponding to the sample pest monitoring sub-period, respectively obtain the preliminary pest monitoring data corresponding to each pest monitoring sub-period, and obtain multiple preliminary pest monitoring data;

[0135] According to a plurality of preliminary pest monitoring data, the periodic pest species quantity distribution coefficient corresponding to each sample pest monitoring sub-period is obtained respectively, and a plurality of pest species quantity distribution coefficients are obtained, and the average of the obtained plurality of pest species quantity distribution coefficients is calculated to obtain the periodic pest species distribution coefficient;

[0136] According to a plurality of preliminary pest monitoring data, the peak pest quantity ratio corresponding to each sample pest monitoring sub-period is obtained respectively to obtain a plurality of peak pest quantity ratios, and the average of the obtained plurality of peak pest quantity ratios is calculated to obtain the period peak pest quantity ratio;

[0137] According to the multiple preliminary pest monitoring data, the sample pest species quantity values ​​corresponding to each sample pest monitoring sub-period are respectively obtained to obtain multiple sample pest species quantity values, and the obtained multiple sample pest species quantity values ​​are averaged to obtain the period pest species quantity value;

[0138] The periodic pest species distribution coefficient, periodic peak pest population ratio and periodic pest species population value are defined as preliminary pest collection data;

[0139] The data acquisition module acquires preliminary pest data and transmits it to the data analysis module;

[0140] The data analysis module obtains the regional pest preliminary division coefficient by analyzing the preliminary pest collection data, obtains the regional pest preliminary division coefficient threshold and compares the regional pest preliminary division coefficient numerically, divides the pest control area into the first type pest control area to the second type pest control area according to the numerical comparison result, obtains the regional pest preliminary classification data, and performs environmental analysis on the second type pest control area according to the regional pest preliminary classification data to obtain the regional screening data, and defines the regional pest preliminary classification data and the regional screening data as the pest regional analysis data;

[0141] Obtain preliminary pest collection data, and obtain period pest species distribution coefficients, period peak pest quantity ratios, and period pest species quantity values ​​according to the preliminary pest collection data;

[0142] The periodic pest species distribution coefficient, periodic peak pest quantity ratio and periodic pest species quantity value are calculated to obtain the regional pest preliminary division coefficient;

[0143] The preliminary regional pest classification coefficient is calculated, and the specific formula is as follows:

[0144]

[0145] Among them, Qcx is the preliminary division coefficient of regional pests, Fbx is the distribution coefficient of periodic pest species, Ksb is the ratio of the number of periodic peak pests, and Zls is the number of periodic pest species;

[0146] Obtaining a regional pest preliminary division coefficient threshold, performing numerical comparison between the regional pest preliminary division coefficient threshold and the regional pest preliminary division coefficient, and dividing the pest control area into a first type pest control area and a second type pest control area according to the numerical comparison result, to obtain preliminary regional pest classification data;

[0147] The details are as follows:

[0148] Obtaining the periodic pest species distribution coefficient threshold, the periodic peak pest quantity ratio threshold, and the periodic pest species quantity threshold respectively;

[0149] The periodic pest species distribution coefficient threshold, periodic peak pest quantity ratio threshold and periodic pest species quantity threshold involved here are respectively the maximum periodic pest species distribution coefficient, the maximum periodic peak pest quantity ratio and the maximum periodic pest species quantity corresponding to the second type of pest control area;

[0150] The threshold of the distribution coefficient of periodic pest species, the threshold of the ratio of the number of periodic peak pests and the threshold of the number of periodic pest species are calculated to obtain the threshold of the preliminary division coefficient of regional pests;

[0151] The threshold of the preliminary regional pest classification coefficient is calculated, and the specific formula is as follows:

[0152]

[0153] Among them, Qcxy is the threshold of the preliminary division coefficient of regional pests, Fbxy is the threshold of the distribution coefficient of periodic pest species, Ksby is the threshold of the ratio of the number of periodic peak pests, and Z l sy is the threshold of the number of periodic pest species;

[0154] When the periodic pest species distribution coefficient is greater than or equal to the periodic pest species distribution coefficient threshold, the corresponding pest control area is divided into a first type of pest control area;

[0155] When the periodic pest species distribution coefficient is less than the periodic pest species distribution coefficient threshold, the corresponding pest control area is divided into a second type of pest control area;

[0156] Conduct regional environmental analysis on the second type of pest control area to obtain regional screening data;

[0157] The details are as follows:

[0158] In the process of conducting environmental analysis on the second type of pest control area, an environmental monitoring period is selected, and a number of environmental monitoring points are selected in the environmental monitoring period;

[0159] It should be noted here that:

[0160] Several environmental monitoring points involved here are soil areas in the second type of pest control areas;

[0161] Respectively obtain the regional environmental humidity value corresponding to each environmental monitoring point of the second type of pest control area to obtain multiple regional environmental humidity values, and average the obtained multiple regional environmental humidity values ​​to obtain the regional environmental average humidity value, obtain the environmental reference humidity value, calculate the difference between the regional environmental average humidity value and the environmental reference humidity value, and take the absolute value of the obtained difference to obtain the regional humidity absolute difference;

[0162] It should be noted here that:

[0163] In this application, the ambient reference humidity value is specifically 25 degrees Celsius;

[0164] The regional environmental pH value corresponding to each environmental monitoring point in the second type of pest control area is obtained respectively to obtain multiple regional environmental pH values, and the average of the obtained multiple regional environmental pH values ​​is calculated to obtain the regional environmental average pH value, and the environmental reference pH value is obtained, and the difference between the regional environmental average pH value and the environmental reference pH value is calculated, and the absolute value of the obtained difference is taken to obtain the regional pH absolute difference;

[0165] It should be noted here that:

[0166] The pH value involved here is the pH value of the regional environment;

[0167] In this application, the environmental baseline pH value is specifically 6.0;

[0168] Respectively obtaining the regional protein content corresponding to each environmental monitoring point in the second type of pest control area to obtain multiple regional protein contents, and averaging the obtained multiple regional protein contents to obtain the regional average protein content, obtaining the environmental benchmark protein content, calculating the difference between the regional average protein content and the environmental benchmark protein content, and taking the absolute value of the obtained difference to obtain the regional protein content difference;

[0169] The regional protein content difference, regional pH absolute difference, and regional humidity absolute difference were defined as regional screening data;

[0170] The regional pest preliminary classification data and regional screening data are defined as pest regional analysis data;

[0171] The data analysis module acquires the pest area analysis data and transmits it to the pest control module;

[0172] The pest control module matches pest control methods to pest control areas based on pest area analysis data;

[0173] Obtain pest area analysis data, and obtain regional pest preliminary classification data and regional screening data based on the pest area analysis data;

[0174] See also Figure 3 , when the pest control area is a first type of pest control area, the pest biological control method matched thereto is a pest virus control method;

[0175] When the pest control area is a second type pest control area, further environmental analysis is performed for it based on the regional screening data;

[0176] The details are as follows;

[0177] According to the regional screening data, the regional protein content difference, regional pH absolute difference and regional humidity absolute difference are obtained respectively;

[0178] The pest control matching coefficient is obtained by calculating the regional protein content difference, regional pH absolute difference and regional humidity absolute difference;

[0179] The pest control matching coefficient is calculated as follows:

[0180] Chf=Dbz+Phz+Sjz;

[0181] Among them, Chf is the pest control matching coefficient, Dbz is the regional protein content difference, pHz is the regional pH absolute difference, and Sjz is the regional humidity absolute difference;

[0182] Obtain a pest control matching coefficient threshold, and compare the pest control matching coefficient with the pest control matching coefficient;

[0183] See also Figure 3 , when the pest control matching coefficient is greater than or equal to the pest control matching coefficient threshold, the pest control area is matched with the bacterial control method;

[0184] If the pest control matching coefficient is less than the pest control matching coefficient threshold, the fungus control method is matched to the pest control area;

[0185] The pest control matching coefficient threshold is obtained as follows:

[0186] Obtain the regional protein content difference threshold, the regional pH absolute difference threshold, and the regional humidity absolute difference threshold respectively;

[0187] It should be noted here that:

[0188] The regional protein content difference threshold, regional pH absolute difference threshold, and regional humidity absolute difference threshold involved here are respectively the minimum regional protein content difference, the minimum regional pH absolute difference, and the minimum regional humidity absolute difference of the control area corresponding to the fungus control method;

[0189] The regional protein content difference threshold, the regional pH absolute difference threshold and the regional humidity absolute difference threshold are calculated to obtain the pest control matching coefficient threshold;

[0190] The pest control matching coefficient threshold is calculated, and the specific formula is as follows:

[0191] Chfy=Dbzy+Phzy+Sjzy;

[0192] Among them, Chfy is the pest control matching coefficient threshold, Dbzy is the regional protein content difference threshold, pHzy is the regional pH absolute difference threshold, and Sjzy is the regional humidity absolute difference threshold.

[0193] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for biological control of vegetable pests and diseases by using microorganisms to prevent pests, characterized in that: The specific steps include: Step S1: respectively obtaining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio and the periodic pest species quantity value to obtain preliminary pest collection data; Step S2: obtaining a regional pest preliminary division coefficient by analyzing the preliminary pest collection data, obtaining a regional pest preliminary division coefficient threshold and performing numerical comparison with the regional pest preliminary division coefficient, dividing the pest control area into a first type of pest control area to a second type of pest control area according to the numerical comparison result, obtaining regional pest preliminary classification data, performing environmental analysis on the second type of pest control area according to the regional pest preliminary classification data, obtaining regional screening data, and defining the regional pest preliminary classification data and the regional screening data as pest regional analysis data; Step S3: Match the pest control method to the pest control area according to the pest area analysis data.

2. The method for biological control of vegetable pests and diseases by using microorganisms to prevent pests according to claim 1, characterized in that: The step S1 further includes the following specific steps: Step S11: in the process of performing pest control in the pest control area, marking a pest monitoring cycle, and dividing the pest monitoring cycle into a plurality of pest monitoring sub-cycles of equal duration; Step S12: randomly selecting one pest monitoring sub-cycle from the plurality of pest monitoring sub-cycles as a sample pest monitoring sub-cycle; Step S13: performing pest sample monitoring within the sample pest monitoring sub-period to obtain the pest sample analysis coefficient corresponding to the sample pest monitoring sub-period.

3. The method for biological control of vegetable diseases and insect pests by using microorganisms to prevent insect pests according to claim 2, characterized in that: The step S1 further includes the following specific steps: Step S14: respectively obtaining preliminary pest monitoring data corresponding to each pest monitoring sub-period to obtain a plurality of preliminary pest monitoring data; Step S15: obtaining the periodic pest species quantity distribution coefficient corresponding to each sample pest monitoring sub-period according to the multiple preliminary pest monitoring data, obtaining multiple pest species quantity distribution coefficients, and averaging the obtained multiple pest species quantity distribution coefficients to obtain the periodic pest species distribution coefficient.

4. The method for biological control of vegetable pests and diseases by using microorganisms to prevent pests according to claim 3, characterized in that: The step S1 further includes the following specific steps: Step S16: obtaining the peak pest quantity ratio corresponding to each sample pest monitoring sub-period according to the plurality of preliminary pest monitoring data, obtaining a plurality of peak pest quantity ratios, averaging the plurality of peak pest quantity ratios, and obtaining the period peak pest quantity ratio; Step S17: obtaining the sample pest species quantity values ​​corresponding to each sample pest monitoring sub-period according to the multiple preliminary pest monitoring data, obtaining multiple sample pest species quantity values, and averaging the obtained multiple sample pest species quantity values ​​to obtain the period pest species quantity value; Step S18: defining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio and the periodic pest species quantity value as preliminary pest collection data.

5. The method for biological control of vegetable pests and diseases by using microorganisms to prevent pests according to claim 4, characterized in that: The step S13 further includes the following specific steps: Step S131: within the sample pest monitoring sub-period, a fixed number of vegetable pests are randomly captured in the pest control area to obtain periodic pest analysis samples; Step S132: obtaining the number of pests in the periodic pest analysis sample to obtain a total number value of the sample pests; Step S133: Acquire the pest species of the periodic pest analysis sample to obtain the sample pest species quantity value.

6. The method for biological control of vegetable pests and diseases by using microorganisms to prevent pests according to claim 5, characterized in that: The step S13 further includes the following specific steps: Step S134: classifying the pests in the periodic pest analysis sample into first to ath pests according to their types; Step S135: respectively obtaining the number values ​​corresponding to the first to a-th pest types, obtaining the first to a-th pest number values, comparing the first to a-th pest number values, and marking the pest number value with the largest value as the peak pest number value; Step S136: Calculate the ratio of the peak pest population value to the total sample pest population value to obtain the peak pest population ratio; Step S137: Obtaining the number distribution coefficient of periodic pest species; Step S138: defining the period pest species quantity distribution coefficient, the peak pest quantity ratio and the sample pest species quantity value as preliminary pest monitoring data corresponding to the sample pest monitoring sub-period.

7. The method for biological control of vegetable pests and diseases by using microorganisms to prevent pests according to claim 1, characterized in that: The step S2 further includes the following specific steps: Step S21: obtaining preliminary pest collection data, and obtaining the periodic pest species distribution coefficient, the periodic peak pest quantity ratio, and the periodic pest species quantity value according to the preliminary pest collection data; Step S22: Calculating the periodic pest species distribution coefficient, the periodic peak pest quantity ratio, and the periodic pest species quantity value to obtain the regional pest preliminary division coefficient; Calculate the preliminary regional pest classification coefficient.

8. The method for biological control of vegetable pests and diseases by using microorganisms to prevent pests according to claim 7, characterized in that: The step S2 further includes the following specific steps: Step S23: obtaining a regional pest preliminary division coefficient threshold, performing numerical comparison between the regional pest preliminary division coefficient threshold and the regional pest preliminary division coefficient, and dividing the pest control area into a first type of pest control area and a second type of pest control area according to the numerical comparison result, to obtain regional pest preliminary classification data; Step S24: performing regional environmental analysis on the second type of pest control area to obtain regional screening data; Step S25: defining the regional pest preliminary classification data and the regional screening data as pest regional analysis data.

9. The method for biological control of vegetable pests and diseases by using microorganisms to prevent pests according to claim 1, characterized in that: The step S3 further includes the following specific steps: Step S31: obtaining pest area analysis data, and obtaining regional pest preliminary classification data and regional screening data according to the pest area analysis data; Step S32: When the pest control area is a first type of pest control area, the pest biological control method matched thereto is a pest virus control method; Step S33: When the pest control area is a second type of pest control area, further environmental analysis is performed for it according to the area screening data.

10. A biological pest control system for vegetables with microbial pest control, applicable to a biological pest control method for vegetables with microbial pest control as claimed in any one of claims 1 to 9, characterized in that: The prevention system includes: Data acquisition module: used to obtain the periodic pest species distribution coefficient, periodic peak pest quantity ratio and periodic pest species quantity value respectively, and obtain preliminary pest collection data; Data analysis module: used to obtain preliminary classification data of regional pests and regional screening data by analyzing preliminary pest collection data, and obtain regional pest analysis data; Pest control module: used to match pest control methods to pest control areas based on pest area analysis data.

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