Pest and disease monitoring and early warning method and system for under-forest economic mode

Abstract

The invention relates to a method and a system for monitoring and early warning diseases and insect pests in an under-forest economic mode. According to the technical scheme, the method comprises the following steps: periodically acquiring spores in the air; photographing and detecting the spores to obtain spore image information; inputting the spore image information into a pre-established spore database, and identifying spore information; generating spore early warning information according to the spore information; periodically acquiring tree image information; identifying the tree image information to obtain tree disease information; the tree disease information comprises leaf surface disease information, trunk disease information and tree pest information; generating disease and pest early warning information according to the tree disease information; generating a comprehensive disease and pest monitoring report according to the spore early warning information and the disease and pest early warning information; according to the application, comprehensive monitoring of two kinds of commercial crops with different heights, namely forest trees and under-forest crops, can be realized so as to meet monitoring and forecasting of plant diseases and insect pests of the forest trees and the under-forest crops.

Description

Technical Field

[0001] The present invention relates to the technical field of plant pest control, and more specifically, it relates to a pest monitoring, early warning method and system for an under-forest economy model. Background Art

[0002] The under-forest economy is an urgent need to promote green growth and an effective way to increase forest land output and farmers' income. Obvious results have been achieved in recent years. However, the implementation sites of the under-forest economy model are mostly mountainous areas where it is inconvenient for people and machinery to enter and exit. The pest monitoring of forest trees and intercropped cash crops is mostly manual monitoring, with high labor costs and low efficiency.

[0003] Existing forest pest monitoring methods, such as the invention patent with the patent application number 201910698772.X, disclose a tree pest monitoring system and method, which require garden management personnel to take pictures of diseased trees on a garden management smart phone and identify them according to the images of the pictures. This monitoring method requires high labor costs, and it is difficult to take pictures of trees in mountainous areas where patrol vehicles and management personnel are difficult to enter, and it is difficult to comprehensively monitor two different heights of economic crops, namely forest trees and under-forest crops. It is very difficult to simultaneously meet the pest monitoring and prediction of two different high-level crops, namely forest trees and under-forest crops. Summary of the Invention

[0004] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a pest monitoring and intelligent prediction method for an under-forest economy model to solve the above technical problems.

[0005] The above technical purpose of the present invention is achieved through the following technical solutions: A pest monitoring and early warning method for an under-forest economy model, including: periodically obtaining spores in the air;

[0006] Taking pictures and detecting the spores to obtain spore image information;

[0007] Inputting the spore image information into a pre-established spore database to identify spore information; generating spore early warning information according to the spore information;

[0008] Periodically obtaining tree image information;

[0009] Identifying the tree image information to obtain tree disease information; the tree disease information includes leaf surface disease information, trunk disease information, and tree pest information;

[0010] Generating pest and disease early warning information according to the tree disease information;

[0011] Generating a comprehensive pest monitoring report according to the spore early warning information and the pest and disease early warning information.

[0012] Specifically, the spore trap automatically captures spores at different heights around the base continuously for 24 hours, takes pictures of the captured spores through a microscope, sends the spore image information to the server through the communication module. The server identifies the spore image information containing the types and quantities of spores according to the information stored in the spore database, and generates spore warning information corresponding to the spore types based on the spore image information. When it is necessary to photograph the understory crops, the height of the spherical camera is adjusted through the telescopic rod so that the spherical camera is at a height slightly lower than the understory crops, and the understory crops are photographed to obtain the tree image information of the understory crops, and the tree image information of the understory crops is identified to obtain the states of the leaves and trunks in the tree image information, and the tree disease information is determined according to the states of the leaves and trunks, and then the corresponding disease warning information is generated based on the tree disease information. When it is necessary to photograph the forest trees, the height of the spherical camera is adjusted through the telescopic rod so that the spherical camera can directly face the forest trees for photographing. At this time, the tree image information of the forest trees is obtained through the spherical camera, and the tree image information of the forest trees is identified to obtain the states of the leaves and trunks in the tree image information of the forest trees, and the tree disease information is determined according to the states of the leaves and trunks, and then the corresponding disease warning information is generated based on the tree disease information. And a comprehensive pest and disease monitoring report of the monitored forest area is generated by combining the spore warning information and the pest and disease warning information. The comprehensive pest and disease monitoring report includes the diseases that spores in the forest area may cause and their prevention and control means and measures, the diseases existing in the forest trees and understory crops and their prevention and control means and measures, and the insect pests that pests in the forest area may cause and their prevention and control means and measures; thus realizing the all-round monitoring of the two different-height cash crops of forest trees and understory crops, and simultaneously meeting the pest and disease monitoring and forecasting of the intercropping of the two different-high crops of forest trees and understory crops.

[0013] Optionally, the periodically obtaining spores in the air includes:

[0014] Capturing spores in the air through the spore trap at preset time intervals, so that the spores fall on the microscope carrier.

[0015] Specifically, the spore trap has an air collection component that can suck the air around the spore trap, filter the spores, and make the spores fall on the carrier, thereby capturing the spores in the air. The air collection component has an air inlet and an air outlet. The air inlet is connected to the outside, the air outlet is facing the carrier, and there is a fan in the air collection component, and the air inlet and the air outlet are connected through the fan.

[0016] Optionally, the inputting the spore image information into a pre-established spore database to identify spore information includes:

[0017] Input the spore image information into a pre-established spore database, identify the spore image information, and obtain spore species information and spore proportion information.

[0018] Specifically, the spore database stores the species and characteristics of various spores. By identifying the spore image information, the characteristics of each spore in the spore image information are obtained, and the characteristics of the spores are input into the spore database for comparison to obtain the spore species information; then, in combination with the species of spores identified in the spore image information and their corresponding quantities, the spore proportion information of various types of spores is calculated.

[0019] Optionally, the generating spore warning information according to the spore information includes:

[0020] Generate corresponding spore warning information according to the spore species information and spore proportion information.

[0021] Specifically, judge whether there are pathogenic spores according to the spore species information. If so, judge the concentration of pathogenic spores according to the spore proportion information, and generate corresponding spore warning information according to the concentration of pathogenic spores.

[0022] Optionally, the periodically obtaining tree image information includes:

[0023] Periodically obtain the leaf surface image information, trunk image information, and insect trap point image information of the tree.

[0024] Specifically, photograph the forest canopy, under-canopy leaf layer, forest seedlings, and inter-forest crops respectively. By only adjusting the height of the telescopic rod, the height of the spherical camera can be adjusted, and through the spherical camera, timed and fixed-point image acquisition of the forest canopy, under-canopy leaf layer, forest seedlings, and inter-forest crops at corresponding heights can be carried out respectively, and the leaf surface image information, trunk image information, and insect trap point image information of the forest canopy, under-canopy leaf layer, forest seedlings, and inter-forest crops can be obtained.

[0025] Optionally, the identifying the tree image information to obtain tree disease information includes:

[0026] Identify the leaf surface image information, judge the lesion condition of the leaf surface, and generate leaf surface disease information;

[0027] Identify the trunk image information, judge the lesion condition of the trunk, and generate trunk disease information;

[0028] Identify the insect trap point image information, judge the pest situation on the tree, and generate tree pest information.

[0029] Specifically, by separately identifying the forest canopy, the under-canopy leaf layer, forest seedlings, and the leaf surfaces, tree trunks, and insect-trapping points of the interplanted crops, and identifying the leaf surface image information, it is possible to identify the size of the leaf surface and whether there are lesions on the leaf surface. If there are lesions, the proportion of the lesion area to the leaf surface area is obtained, and leaf surface disease information is generated based on the lesion characteristics. By identifying the tree trunk image information, it is possible to identify whether there are lesions in the tree trunk area. If there are lesions, the length of the lesion is identified according to the focal length, and the corresponding tree trunk disease information is generated. By identifying the insect-trapping point image information, the pest species information of the insect-trapping point is obtained, and tree pest information is generated based on the pest species and the proportion of pest quantity.

[0030] Optionally, the identification of the leaf surface image information, the judgment of the lesion condition of the leaf surface, and the generation of the leaf surface disease information include:

[0031] Cropping the leaf outline from the leaf surface image information;

[0032] Identifying the disease characteristics in the leaf outline;

[0033] Generating the leaf surface disease information based on the type of the disease characteristics and the proportion of the disease characteristics in the leaf area.

[0034] Specifically, by identifying the leaf surface image information, cropping the leaf outline from the leaf surface image information, retaining the complete leaf outline, identifying whether there are diseases on the leaf surface from the complete leaf outline, identifying the disease type, obtaining the disease characteristics in the leaf outline, then identifying the proportion of the disease characteristics in the leaf area, and generating the leaf surface disease information based on the type and proportion of the disease characteristics.

[0035] Optionally, the identification of the insect-trapping point image information, the judgment of the pest situation on the tree, and the generation of the tree pest information include:

[0036] Identifying the pest species information and the pest proportion information of the insect-trapping point from the insect-trapping point image information;

[0037] Calculating the pest occurrence base according to the pest species information and the pest proportion information;

[0038] Generating the disease index of the pest and disease occurrence according to the pest occurrence base;

[0039] Analyzing the development trend and severity of the pest and disease situation according to the disease indexes corresponding to the multiple insect-trapping point picture information of the same insect-trapping point.

[0040] Specifically, by identifying the insects at the insect-trapping points, information on the types of pests is obtained, and the proportion of each type of pest is calculated based on the number of insects in the insect-trapping point image information; subsequently, the occurrence base number of pests in the regional area is measured according to the pest type information and the pest proportion information. Based on the pest proportion information and pest type information of the regional area, the number of pests in the regional area can be obtained, and then the occurrence base number of pests in the regional area is measured according to the number of pests; and the corresponding disease index of the pest and disease occurrence is matched according to the occurrence base number of pests and diseases; multiple identifications are performed on the same insect-trapping point at preset time intervals to obtain multiple disease indexes sorted by time, and a curve is fitted according to the multiple disease indexes to obtain the development trend and severity of the pest and disease situation.

[0041] Optionally, the generating of the disease warning information according to the tree disease information includes:

[0042] Generating corresponding pest and disease warning information according to the development trend and severity of the pest and disease situation.

[0043] Specifically, according to the development trend and severity of the pest and disease situation, warning information corresponding to the development trend and severity of the pest and disease is issued, and corresponding prevention and control means and measures are pushed.

[0044] The present application also provides a pest and disease monitoring and warning system for an under-forest economic model, including: a base; a telescopic rod is provided on the base; a rotating disk is provided at the top of the telescopic rod; a spherical camera is provided on the rotating disk; a spore trap is also provided on the telescopic rod; the spore trap includes an air collection component and a microscope; a communication module is provided on the base; the spherical camera, the telescopic rod, and the microscope are all electrically connected to the communication module.

[0045] Specifically, the telescopic rod is an electric telescopic rod, with a maximum height of 10 meters and a minimum height of 2.5 meters. When the telescopic rod is retracted to the minimum height, the spherical camera can take pictures of forest crops and forest seedlings. When the telescopic rod is extended to the maximum height, the spherical camera can take pictures of the forest canopy and the under-canopy leaf layer. The rotating disk can drive the spherical camera to rotate to achieve 360-degree monitoring by the spherical camera. The spore trap can move with the telescopic rod to capture spores at different heights. Among them, the air collection component has an air inlet and an air outlet. The air inlet is connected to the outside, and the air outlet is facing the carrier. There is a fan in the air collection component, and the air inlet and the air outlet are connected through the fan. The fan sucks in outside air, and the spores in the air fall on the carrier, and then the spores on the carrier are observed through the microscope. The spherical camera and the microscope send the captured images to the server through the communication module, and the communication module controls the telescopic rod to extend and retract after receiving the adjustment signal sent by the server.

[0046] Among them, for areas where the mains power can be connected, the mains power can be directly used to supply power to the pest monitoring and early warning system for the underforest economy model. Since there is generally a lack of power sources in mountainous areas, energy storage batteries are usually installed in the base, and solar panels are installed on the base; in the case of sufficient sunlight, the solar panels generate electrical energy, which on the one hand directly supplies power to the telescopic rod, the rotating disk, the spherical camera, the spore trap, and the communication module, and on the other hand stores the surplus electrical energy in the energy storage battery; when the sunlight is insufficient, the energy storage power supply directly supplies power to the telescopic rod, the rotating disk, the spherical camera, the spore trap, and the communication module.

[0047] The communication module can select communication modules such as 4G, 5G, WiFi, satellite communication, GPRS, LoRa, etc., send the images captured by the spherical camera and the microscope to the cloud server, and receive the adjustment signals sent by the cloud server to control the telescopic rod to extend and retract.

[0048] In summary, the present invention has the following beneficial effects:

[0049] The spore trap automatically captures spores at different heights around the base continuously for 24 hours, takes pictures of the captured spores through a microscope, and sends the spore image information to the server through the communication module. The server identifies the spore image information containing the types and quantities of spores according to the information stored in the spore database, and generates spore early warning information corresponding to the spore types according to the spore image information. When it is necessary to photograph the underforest crops, the height of the spherical camera is adjusted by the telescopic rod so that the spherical camera is at a height slightly lower than the underforest crops, and the underforest crops are photographed to obtain the tree image information of the underforest crops, and the tree image information of the underforest crops is identified to obtain the states of the leaves and trunks in the tree image information, and the tree disease information is determined according to the states of the leaves and trunks, and then the corresponding disease early warning information is generated according to the tree disease information. When it is necessary to photograph forest trees, the height of the spherical camera is adjusted by the telescopic rod so that the spherical camera can directly face the forest trees for photographing. At this time, the tree image information of the forest trees is obtained through the spherical camera, and the tree image information of the forest trees is identified to obtain the states of the leaves and trunks in the tree image information of the forest trees, and the tree disease information is determined according to the states of the leaves and trunks, and then the corresponding disease early warning information is generated according to the tree disease information. Thus, it realizes the all-round monitoring of economic crops at two different heights of forest trees and underforest crops, and simultaneously meets the pest monitoring and forecasting of two different high-level crop intercropping of forest trees and underforest crops. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is the flowchart of the method of the present invention;

[0051] Figure 2 is the structural schematic diagram of the present invention;

[0052] Figure 3 It is a schematic cross-sectional structure diagram of the spore trap in the present invention.

[0053] In the figure: 1, base; 2, telescopic rod; 3, rotating disk; 4, spherical camera; 5, spore trap; 51, air collection component; 52, microscope. Specific embodiments

[0054] To make the objectives, features, and advantages of the present invention more obvious and understandable, the following provides a detailed description of the specific embodiments of the present invention with reference to the accompanying drawings. Several embodiments of the present invention are shown in the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein.

[0055] In the present invention, unless otherwise clearly defined and limited, terms such as "installation", "connection", "linkage", "fixation", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features.

[0056] The following combines the accompanying drawings and embodiments to describe the present invention in detail.

[0057] Embodiment 1

[0058] This embodiment provides a method for monitoring and warning of pests and diseases in an underforest economy model, as Figure 1 shown, including: periodically obtaining spores in the air;

[0059] taking pictures and detecting the spores to obtain spore image information;

[0060] inputting the spore image information into a pre-established spore database to identify spore information; generating spore warning information according to the spore information;

[0061] periodically obtaining tree image information;

[0062] identifying the tree image information to obtain tree disease information; the tree disease information includes leaf surface disease information, trunk disease information, and tree pest information;

[0063] generating pest and disease warning information according to the tree disease information;

[0064] Generate a comprehensive pest and disease monitoring report based on the spore warning information and pest and disease warning information.

[0065] Specifically, the spore trap continuously and automatically captures spores at different heights around the base 1 for 24 hours, and the captured spores are photographed by the microscope 52. The spore image information is sent to the server through the communication module. The server identifies the spore image information containing the type and quantity of spores according to the information stored in the spore database, and generates spore warning information corresponding to the spore types based on the spore image information. When it is necessary to photograph the understory crops, the height of the spherical camera 4 is adjusted by the telescopic rod 2 so that the spherical camera 4 is at a height slightly lower than the understory crops, and the understory crops are photographed to obtain the tree image information of the understory crops. The tree image information of the understory crops is identified to obtain the states of the leaves and trunks in the tree image information, and the tree disease information is determined according to the states of the leaves and trunks. Subsequently, the corresponding disease warning information is generated based on the tree disease information. When it is necessary to photograph the forest trees, the height of the spherical camera 4 is adjusted by the telescopic rod 2 so that the spherical camera 4 can directly face the forest trees for photographing. At this time, the tree image information of the forest trees is obtained through the spherical camera 4, and the tree image information of the forest trees is identified to obtain the states of the leaves and trunks in the tree image information of the forest trees, and the tree disease information is determined according to the states of the leaves and trunks. Subsequently, the corresponding disease warning information is generated based on the tree disease information. And a comprehensive pest and disease monitoring report of the monitored forest area is generated by combining the spore warning information and the pest and disease warning information. The comprehensive pest and disease monitoring report includes the diseases that spores in the forest area may cause and their prevention and control means and measures, the diseases existing in the forest trees and understory crops and their prevention and control means and measures, and the insect pests that pests in the forest area may cause and their prevention and control means and measures. Thus, it realizes the all-round monitoring of two different heights of economic crops, namely forest trees and understory crops, and simultaneously meets the pest and disease monitoring and forecasting of the intercropping of two different high-level crops, namely forest trees and understory crops.

[0066] Optionally, the periodically obtaining spores in the air includes:

[0067] Capturing spores in the air through the spore trap 5 at preset time intervals, so that the spores fall on the carrier of the microscope 52.

[0068] Specifically, the spore trap 5 has an air collection component 51, which can suck the air around the spore trap 5 and filter the spores, so that the spores fall on the carrier, thereby capturing the spores in the air. And the air collection component 51 has an air inlet and an air outlet. The air inlet is communicated with the outside, and the air outlet is directly opposite to the carrier. There is a fan in the air collection component 51, and the air inlet and the air outlet are connected through the fan.

[0069] Optionally, inputting the spore image information into a pre-established spore database to identify spore information includes:

[0070] Inputting the spore image information into a pre-established spore database, identifying the spore image information, and obtaining spore species information and spore proportion information.

[0071] Specifically, the spore database stores the species and characteristics of various spores. By identifying the spore image information, the characteristics of each spore in the spore image information are obtained, and the characteristics of the spores are input into the spore database for comparison to obtain the spore species information; then, the spore proportion information of various spores is calculated by combining the identified spore species and their corresponding quantities in the spore image information.

[0072] Optionally, generating spore warning information based on the spore information includes:

[0073] Generating corresponding spore warning information based on the spore species information and spore proportion information.

[0074] Specifically, it is judged whether there are pathogenic spores according to the spore species information. If so, the concentration of pathogenic spores is judged according to the spore proportion information, and corresponding spore warning information is generated according to the concentration of pathogenic spores.

[0075] Optionally, periodically obtaining tree image information includes:

[0076] Periodically obtaining the leaf surface image information, trunk image information, and insect trap image information of the tree.

[0077] Specifically, photographing the forest canopy, understory leaf layer, forest seedlings, and intercropped crops in the forest respectively. Only by adjusting the height of the telescopic rod 2 can the height of the spherical camera 4 be adjusted, and the spherical camera 4 is used to collect timed and fixed-point images of the forest canopy, understory leaf layer, forest seedlings, and intercropped crops at corresponding heights respectively, and obtain the leaf surface image information, trunk image information, and insect trap image information of the forest canopy, understory leaf layer, forest seedlings, and intercropped crops.

[0078] Optionally, identifying the tree image information to obtain tree disease information includes:

[0079] Identifying the leaf surface image information, judging the lesion condition of the leaf surface, and generating leaf surface disease information;

[0080] Identifying the trunk image information, judging the lesion condition of the trunk, and generating trunk disease information;

[0081] Identifying the insect trap image information, judging the pest situation on the tree, and generating tree pest information.

[0082] Specifically, by separately identifying the forest canopy, the understory leaf layer, forest seedlings, and the leaf surfaces, tree trunks, and insect-trapping points of the interplanted crops, and by identifying the leaf surface image information, it is possible to identify the size of the leaf surface and whether there are any lesions on the leaf surface. If there are lesions, the proportion of the lesion area to the leaf surface area is obtained, and leaf surface disease information is generated based on the lesion characteristics. By identifying the tree trunk image information, it is possible to identify whether there are any lesions in the tree trunk area. If there are lesions, the length of the lesion is identified based on the focal length, and corresponding tree trunk disease information is generated. By identifying the insect-trapping point image information, the pest species information of the insect-trapping point is obtained, and tree pest information is generated based on the pest species and the proportion of the pest quantity.

[0083] Embodiment Two

[0084] This embodiment provides a method for monitoring, warning of, and preventing diseases and pests in an under-forest economic model, as Figure 1 shown, including: periodically obtaining spores in the air;

[0085] taking a photo and detecting the spores to obtain spore image information;

[0086] inputting the spore image information into a pre-established spore database to identify spore information; generating spore warning information based on the spore information;

[0087] periodically obtaining tree image information;

[0088] identifying the tree image information to obtain tree disease information; the tree disease information includes leaf surface disease information, tree trunk disease information, and tree pest information;

[0089] generating diseases and pests warning information based on the tree disease information;

[0090] generating a comprehensive diseases and pests monitoring report based on the spore warning information and the diseases and pests warning information.

[0091] Specifically, the spore trap automatically and continuously captures spores at different heights around the base 1 for 24 hours, and the captured spores are photographed by the microscope 52. The spore image information is sent to the server through the communication module. The server identifies the spore image information containing the types and quantities of spores based on the information stored in the spore database, and generates spore warning information corresponding to the spore types according to the spore image information. When it is necessary to photograph the understory crops, the height of the spherical camera 4 is adjusted by the telescopic rod 2 so that the spherical camera 4 is at a height slightly lower than the understory crops, and the understory crops are photographed to obtain the tree image information of the understory crops. The tree image information of the understory crops is identified to obtain the states of the leaves and trunks in the tree image information, and the tree disease information is determined according to the states of the leaves and trunks. Subsequently, the corresponding disease warning information is generated according to the tree disease information. When it is necessary to photograph the forest trees, the height of the spherical camera 4 is adjusted by the telescopic rod 2 so that the spherical camera 4 can directly face the forest trees for photographing. At this time, the tree image information of the forest trees is obtained through the spherical camera 4, and the tree image information of the forest trees is identified to obtain the states of the leaves and trunks in the tree image information of the forest trees, and the tree disease information is determined according to the states of the leaves and trunks. Subsequently, the corresponding disease warning information is generated according to the tree disease information. The comprehensive pest and disease monitoring report of the monitored forest area is generated by combining the spore warning information and the pest and disease warning information. The comprehensive pest and disease monitoring report includes the diseases that spores in the forest area may cause and their prevention and control means and measures, the diseases existing in the forest trees and understory crops and their prevention and control means and measures, and the pests in the forest area that may cause pest infestations and their prevention and control means and measures. Thus, the economic crops at two different heights of the forest trees and understory crops are comprehensively monitored, and at the same time, the pest and disease monitoring and forecasting of the two different high-layer crop intercropping of the forest trees and understory crops are satisfied.

[0092] Optionally, the periodically obtaining spores in the air includes:

[0093] Capturing spores in the air by the spore trap 5 at preset time intervals, so that the spores fall on the carrier of the microscope 52.

[0094] Specifically, the spore trap 5 has an air collection component 51, which can suck the air around the spore trap 5 and filter the spores so that the spores fall on the carrier, thereby capturing the spores in the air. The air collection component 51 has an air inlet and an air outlet. The air inlet is communicated with the outside, and the air outlet is facing the carrier. There is a fan in the air collection component 51, and the air inlet and the air outlet are connected through the fan.

[0095] Optionally, the inputting the spore image information into a pre-established spore database to identify spore information includes:

[0096] Input the spore image information into a pre - established spore database, identify the spore image information, and obtain spore species information and spore proportion information.

[0097] Specifically, the spore database stores the species and characteristics of various spores. By identifying the spore image information, the characteristics of each spore in the spore image information are obtained, and the characteristics of the spores are input into the spore database for comparison to obtain the spore species information; then, in combination with the species of spores identified in the spore image information and their corresponding quantities, the spore proportion information of various types of spores is calculated.

[0098] Optionally, generating spore warning information based on the spore information includes:

[0099] Generate corresponding spore warning information based on the spore species information and spore proportion information.

[0100] Specifically, determine whether there are pathogenic spores based on the spore species information. If so, determine the concentration of pathogenic spores based on the spore proportion information, and generate corresponding spore warning information according to the concentration of pathogenic spores.

[0101] Optionally, periodically obtaining tree image information includes:

[0102] Periodically obtain the leaf surface image information, trunk image information, and insect - attracting point image information of the tree.

[0103] Specifically, photograph the forest canopy, under - canopy leaf layer, forest seedlings, and inter - forest crops respectively. By simply adjusting the height of the telescopic rod 2, the height of the spherical camera 4 can be adjusted, and through the spherical camera 4, timed and fixed - point image acquisition of the forest canopy, under - canopy leaf layer, forest seedlings, and inter - forest crops at corresponding heights is carried out respectively, and the leaf surface image information, trunk image information, and insect - attracting point image information of the forest canopy, under - canopy leaf layer, forest seedlings, and inter - forest crops are obtained.

[0104] Optionally, identifying the tree image information to obtain tree disease information includes:

[0105] Identify the leaf surface image information, judge the lesion condition of the leaf surface, and generate leaf surface disease information;

[0106] Identify the trunk image information, judge the lesion condition of the trunk, and generate trunk disease information;

[0107] Identify the insect - attracting point image information, judge the pest situation on the tree, and generate tree pest information.

[0108] Specifically, by separately identifying the forest tree canopy, the under-canopy leaf layer, forest tree seedlings, and the leaf surfaces, tree trunks, and insect-trapping points of the inter-forest crops, and identifying the leaf surface image information, it is possible to identify the size of the leaf surface and whether there are lesions on the leaf surface. If there are lesions, the proportion of the lesion area to the leaf surface area is obtained, and leaf surface disease information is generated based on the lesion characteristics. By identifying the tree trunk image information, it is possible to identify whether there are lesions in the tree trunk area. If there are lesions, the length of the lesion is identified based on the focal length, and corresponding tree trunk disease information is generated. By identifying the insect-trapping point image information, the pest species information of the insect-trapping point is obtained, and tree pest information is generated based on the pest species and the proportion of the pest quantity.

[0109] Optionally, the identifying the leaf surface image information, judging the lesion condition of the leaf surface, and generating leaf surface disease information includes:

[0110] Cropping out the leaf contour from the leaf surface image information;

[0111] Identifying the disease characteristics in the leaf contour;

[0112] Generating leaf surface disease information based on the type of the disease characteristics and the proportion of the disease characteristics to the leaf area.

[0113] Specifically, by identifying the leaf surface image information, cropping out the leaf contour from the leaf surface image information, retaining the complete leaf contour, identifying whether there are diseases on the leaf surface from the complete leaf contour, identifying the disease type, obtaining the disease characteristics in the leaf contour, then identifying the proportion of the disease characteristics to the leaf area, and generating leaf surface disease information based on the type and proportion of the disease characteristics.

[0114] Optionally, the identifying the insect-trapping point image information, judging the pest situation on the tree, and generating tree pest information includes:

[0115] Identifying the pest species information and the pest proportion information of the insect-trapping point from the insect-trapping point image information;

[0116] Calculating the pest occurrence base number based on the pest species information and the pest proportion information;

[0117] Generating the disease index of the occurrence of pests and diseases based on the pest occurrence base number;

[0118] Analyzing the development trend and severity of the pest and disease situation based on the disease indexes corresponding to the multiple insect-trapping point picture information of the same insect-trapping point.

[0119] Specifically, by identifying the insects at the insect-trapping points, the information on the types of pests is obtained, and the proportion information of each type of pest is calculated based on the number of insects in the insect-trapping point image information; subsequently, the occurrence base number of pests in the regional area is measured according to the pest type information and the pest proportion information. The number of pests in the regional area can be obtained based on the pest proportion information and the pest type information of the regional area, and then the occurrence base number of pests in the regional area is measured according to the number of pests; and the corresponding disease index of the occurrence of plant diseases and insect pests is matched according to the occurrence base number of pests. Multiple identifications are carried out on the same insect-trapping point at preset time intervals to obtain multiple disease indexes sorted by time, and a curve is fitted according to the multiple disease indexes to obtain the development trend and severity of the plant diseases and insect pests.

[0120] Optionally, the generating of the disease warning information according to the tree disease information includes:

[0121] Generating corresponding plant disease and insect pest warning information according to the development trend and severity of the plant diseases and insect pests.

[0122] Specifically, according to the development trend and severity of the plant diseases and insect pests, warning information corresponding to the development trend and severity of the plant diseases and insect pests is issued, and corresponding prevention and control means and measures are pushed.

[0123] Embodiment III

[0124] This embodiment provides a plant disease and insect pest monitoring and warning system for an under-forest economy model, as Figure 2 and Figure 3 shown, including: a base 1; a telescopic rod 2 is arranged on the base 1; a rotating disk 3 is arranged at the top of the telescopic rod 2; a spherical camera 4 is arranged on the rotating disk 3; a spore trap 5 is further arranged on the telescopic rod 2; the spore trap 5 includes an air collection component 51 and a microscope 52; a communication module is arranged on the base 1; the spherical camera 4, the telescopic rod 2 and the microscope 52 are all electrically connected to the communication module.

[0125] Specifically, the telescopic rod 2 is an electric telescopic rod 2 with a maximum height of 10 meters and a minimum height of 2.5 meters. When the telescopic rod 2 is retracted to the minimum height, the spherical camera 4 can take pictures of forest crops and forest tree seedlings. When the telescopic rod 2 is extended to the maximum height, the spherical camera 4 can take pictures of the forest canopy and the understory leaf layer. The turntable 3 can drive the spherical camera 4 to rotate to achieve 360-degree monitoring of the spherical camera 4. The spore trap 5 can move with the telescopic rod 2 to capture spores at different heights. Among them, the air collection component 51 has an air inlet and an air outlet. The air inlet is connected to the outside, and the air outlet faces the carrier. There is a fan in the air collection component 51, and the air inlet and the air outlet are connected through the fan. The outside air is sucked in by the fan, and the spores in the air fall on the carrier, and then the spores on the carrier are observed through the microscope 52. The spherical camera 4 and the microscope 52 send the captured images to the server through the communication module. After receiving the adjustment signal sent by the server, the communication module controls the telescopic rod 2 to extend and retract.

[0126] Among them, for areas where the mains power can be connected, the mains power can be directly used to supply power to the pest control monitoring and early warning system of the underforest economy model. Since there is generally a lack of power sources in mountainous areas, an energy storage battery is usually arranged in the base, and a solar panel is arranged on the base; in the case of sufficient sunlight, the electric energy generated by the solar panel directly supplies power to the telescopic rod, turntable, spherical camera, spore trap, and communication module on the one hand, and stores the surplus electric energy in the energy storage battery on the other hand; when the sunlight is insufficient, the energy storage power directly supplies power to the telescopic rod, turntable, spherical camera, spore trap, and communication module.

[0127] The communication module can be selected from communication modules such as 4G, 5G, WiFi, satellite communication, GPRS, and LoRa. The spherical camera and the microscope send the captured images to the cloud server and receive the adjustment signal sent by the cloud server to control the telescopic rod to extend and retract.

[0128] The above is only the preferred implementation mode of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention. It should be pointed out that for those of ordinary skill in the art in this technical field, several improvements and refinements made without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for monitoring and early warning of pests and diseases in a forest economy model, characterized in that: include: Periodically acquires airborne spores; Taking photos of the spores to obtain spore image information; Inputting the spore image information into a pre-established spore database to identify the spore information; generating spore warning information according to the spore information; Periodically obtain tree image information; Identify the tree image information to obtain tree disease information; the tree disease information includes leaf disease information, trunk disease information, and tree insect pest information; Generate pest and disease warning information according to the tree disease information; A comprehensive pest and disease monitoring report is generated based on the spore warning information and the pest and disease warning information.

2. The method for monitoring and early warning of pests and diseases in a forest economy model according to claim 1, characterized in that: The periodic acquisition of spores in the air includes: At preset time intervals, spores in the air are captured by a spore capture device, and the spores are made to fall onto a microscope carrier.

3. The method for monitoring and early warning of pests and diseases in a forest economy model according to claim 2, characterized in that: The step of inputting the spore image information into a pre-established spore database to identify the spore information includes: The spore image information is input into a pre-established spore database, the spore image information is identified, and spore type information and spore ratio information are obtained.

4. The method for monitoring and early warning of pests and diseases in a forest economy model according to claim 3, characterized in that: Generating spore warning information according to the spore information includes: Corresponding spore warning information is generated according to the spore type information and the spore proportion information.

5. The method for monitoring and early warning of pests and diseases in a forest economy model according to claim 1, characterized in that: The periodic acquisition of tree image information includes: Periodically obtain leaf image information, trunk image information, and insect attraction point image information of trees.

6. The method for monitoring and early warning of pests and diseases in a forest economy model according to claim 5, characterized in that: The tree image information is identified to obtain tree disease information, including: Identify leaf surface image information, determine leaf surface pathological conditions, and generate leaf surface disease information; Identify the trunk image information, determine the trunk pathological condition, and generate trunk disease information; Identify the image information of the insect attraction points, determine the insect pest situation on the trees, and generate tree pest information.

7. The method for monitoring and early warning of pests and diseases in a forest economy model according to claim 6, characterized in that: The identifying of leaf surface image information, determining the pathological condition of the leaf surface, and generating leaf surface disease information includes: Cut out the leaf outline from the leaf surface image information; Identify disease signatures in leaf outlines; Leaf disease information is generated according to the type of the symptom characteristics and the proportion of the symptom characteristics to the leaf area.

8. The method for monitoring and early warning of pests and diseases in a forest economy model according to claim 6, characterized in that: The method of identifying the image information of the insect attracting points, determining the insect pest situation on the trees, and generating tree insect pest information includes: Identify the image information of the insect trapping point to obtain the pest species information and pest proportion information of the insect trapping point; Calculate the pest occurrence base based on the pest species information and pest proportion information; Generate a disease index for the occurrence of pests and diseases based on the pest occurrence base; The development trend and severity of the pest and disease situation are analyzed based on the disease index corresponding to multiple insect attraction point image information of the same insect attraction point.

9. The method for monitoring and early warning of pests and diseases in a forest economy model according to claim 8, characterized in that: The generating of disease warning information according to the tree disease information comprises: Generate corresponding pest and disease early warning information based on the development trend and severity of the pest and disease situation.

10. A pest monitoring and early warning system for forest economic model, characterized in that: include: Pedestal; A telescopic rod is arranged on the base; a rotating disk is arranged on the top of the telescopic rod; a spherical camera is arranged on the rotating disk; a spore capture device is also arranged on the telescopic rod; the spore capture device includes an air collection component and a microscope; a communication module is arranged on the base; the spherical camera, the telescopic rod and the microscope are all electrically connected to the communication module.

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