CN113324927A - Method for preventing and treating pine wilt disease in forest at early stage and monitoring system - Google Patents
Method for preventing and treating pine wilt disease in forest at early stage and monitoring system Download PDFInfo
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Abstract
The invention belongs to the technical field of pest control, and discloses a pine wood nematode disease forest early-stage control method and a monitoring system, wherein visible light/multi/hyperspectral monitoring, unmanned aerial vehicle technology and chemical control means are integrated, and pine forest spectral information is acquired in a forest by hyperspectrum and an unmanned aerial vehicle carrying spectral imager; processing, reading and analyzing hyperspectral and multispectral image data by using remote sensing image processing software indoors, and performing hyperspectral measurement and unmanned aerial vehicle multispectral measurement on susceptible pine trees to obtain accurate geographical positions of the susceptible pine trees; selecting efficient and safe medicaments to guide the accurate control of the woodland, realizing the early discovery and the effective control time of the pine wilt disease in the woodland, and carrying out the accurate control; after the control is finished, the effect of the test is checked. The invention realizes early discovery, early treatment and accurate control of the pine wood nematode disease in forests, strives to change the current passive tree cutting and removing control into active control, and protects the ecological value of pine forests to a greater extent.
Description
Technical Field
The invention belongs to the technical field of pest control, and particularly relates to a forest early-stage control method and a forest early-stage monitoring system for pine wilt disease.
Background
At present, bursaphelenchus xylophilus is an important forestry quarantine pest. 37 areas (counties) in our province occur in different degrees, tens of thousands of mu of pine forest are damaged each year, and over 10 thousands of trees are died of diseases. Pine forest area of Sichuan province is more than 5000 ten thousand mu, pine trees are important dominant tree species in Panxi, Sichuan and North-Chuan areas, and once damaged by pine wilt disease, the pine tree can cause destructive damage to local forest ecological systems. The traditional pine wood nematode disease removing and treating method is in a passive situation, and the wood epidemic treatment cost is high. Therefore, early monitoring, diagnosis and control of the forest are key to deal with the pine wilt disease. In the adult period of monochamus alternatus, the pine wood nematodes are transmitted into the uninfected pine trees, the physiological and biochemical indexes of the plants are changed due to metabolites secreted by the nematodes, the spectral reflection of the plants is changed accordingly, and the pine wood nematodes can be captured sharply through hyperspectrum.
Through the above analysis, the problems and defects of the prior art are as follows:
(1) traditional monitoring means cannot diagnose early stages of pine susceptibility.
(2) The traditional monitoring means for the pine wilt disease is passive, and the processing cost of the wood epidemic is higher.
The difficulty in solving the above problems and defects is: how to capture the corresponding signal sensitively and early after pine tree infection with pine wood nematode disease becomes the key for early monitoring. The pine wood nematodes invade the pine plant, causing a series of physiological changes in the body and gradually appearing in appearance. Research shows that after the nematode invades the plant, the morphology is normal in appearance, and resin secretion is reduced or stopped; part of the needles begin to lose luster and turn grayish green and gradually turn yellow, and the secretion of resin stops; most of the needles turned reddish brown; finally, the coniferous leaves of the whole crown become reddish brown, the diseased tree is withered and dies, but the coniferous leaves do not fall off. The traditional monitoring means generally adopts manual inspection, the early stage of disease onset of a diseased plant cannot be sensed by naked eyes, and the diseased plant cannot be effectively cured by applying the medicine until the physiological performance is found to be abnormal by the naked eyes. When plants are infested by diseases and insect pests, chlorophyll is often reduced or even disappears, so that the intensity of a chlorophyll absorption band is weakened, the reflectivity of the whole visible light is increased and is much higher than that of normal plants, and the emissivity in an infrared region is obviously reduced. It is now necessary to use a tool to detect this change sharply early in the disease. .
The significance of solving the problems and the defects is as follows: according to the invention, visible light/multi/hyperspectral monitoring, unmanned aerial vehicle technology and chemical prevention and control means are integrated, in the early stage that the traditional monitoring means can not observe pine tree diseases, pine forest spectrum information is obtained in the forest through hyperspectrum and an unmanned aerial vehicle carrying a spectrum imager, data is processed, interpreted and analyzed by remote sensing image processing software indoors, the accurate geographical position of the disease-sensitive pine is obtained, efficient and safe medicaments are selected to guide the accurate prevention and control in the forest, the early discovery and the effective prevention and control time in the pine wood nematode disease forest are realized, and the accurate prevention and control are carried out. The passive elimination is changed into active prevention and control, and the economic value and the ecological value of the pine forest are protected.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a forest early prevention and control method and a monitoring system for pine wilt disease.
The invention is realized in such a way, and provides a method for early prevention and control of pine wilt disease in forests, which comprises the following steps:
integrating visible light/multi/hyperspectral monitoring, unmanned aerial vehicle technology and chemical prevention and control means, and acquiring spectral information of pine forest in a forest by hyperspectral and unmanned aerial vehicle-mounted spectral imagers;
processing, reading and analyzing hyperspectral and multispectral image data by using remote sensing image processing software indoors, and performing hyperspectral measurement and unmanned aerial vehicle multispectral measurement on susceptible pine trees to obtain accurate geographical positions of the susceptible pine trees;
step three, selecting efficient and safe medicaments to guide the accurate control of the woodland, realizing the early discovery and the effective control time of the pine wood nematode disease in the woodland, and performing the accurate control; after the control is finished, the effect of the test is checked.
Further, in the second step, when the hyperspectral measurement is performed on the susceptible pine, the specific process of data acquisition is as follows:
in the middle and late ten days of 5 months, selecting healthy pine trees (Pinus massoniana and Pinus tabulaeformis) in the field by combining the biological characteristics of Monochamus alternatus to carry out artificial inoculation on pine wood nematodes;
and continuously measuring the spectral information of the experimental sample plant by using a handheld hyperspectral imager from the middle ten days of 6 months to the beginning of 9 months, and collecting the spectral information once every 7-10 days.
Further, the specific process of the remote sensing image processing software for processing the hyperspectral data is as follows:
acquiring an ideal spectral curve by using remote sensing image processing software through removing interference wave band influence, correcting distortion and image correction;
according to the change of the spectrum wave band in different time periods, a prediction model is established, the effective monitoring wave band at the early stage of disease attack is extracted, a multispectral imager aiming at early monitoring of the pine wood nematode disease woodland is developed, and the optimal early monitoring time point of the pine wood nematode disease woodland is determined.
Further, in the second step, the specific process of acquiring multispectral images of the unmanned aerial vehicle is as follows:
carrying a multispectral imager on a fixed-wing unmanned aerial vehicle for image acquisition; and (3) flying under the condition of good weather condition at the optimal early monitoring time point of the pine wood nematode disease, and performing RTK measurement in the process.
Further, in the second step, the specific process of the remote sensing image processing software for processing the multispectral data is as follows:
data are analyzed and processed indoors through remote sensing image processing software, image splicing, mosaic, atmospheric correction and the like, and accurate positioning of the positions of suspected infected pine trees is achieved based on a prediction model and autonomous recognition.
Further, in the third step, the specific process of medicament screening is as follows:
selecting abamectin, emamectin benzoate and other medicament screening tests, preparing a raw medicament into missible oil indoors by using methanol and an emulsifier, and adding the pine wood nematode suspension into each hole of a 96-hole plate;
adding different agents according to the set agent concentration, judging the unmovable insect body to be dead if the unmovable insect body is J-shaped or C-shaped or the insect body is stiff and the body wall has no refractivity, calculating the mortality and correcting the mortality.
Further, mixing and blending raw medicines according to a certain proportion, determining the toxicity of different medicament combinations to the pine wood nematodes by using an immersion method, screening out the optimal medicament combination, performing forest control effect tests by combining measures such as forest medicament injection, medium insect control and the like, determining medicament varieties and using methods suitable for early forest control, and formulating corresponding control technical specifications.
Further, in the third step, after the prevention and treatment are completed, the effect process of the test is as follows:
the multi-rotor unmanned aerial vehicle with visible light is utilized to monitor the control effect, and the morbidity of a control area and a test group is compared.
Further, the process that many rotor unmanned aerial vehicle of visible light prevented and control the effect monitoring does:
acquiring corresponding spectral data, and performing spectral data processing indoors by using remote sensing processing software ENVI, image splicing, embedding and atmospheric correction; and the research effect monitoring is completed in time, and a later-stage test plan and arrangement are made.
Another object of the present invention is to provide a pine wood nematode forests early monitoring system for implementing the method for controlling pine wood nematode forests early, which includes:
the hyperspectral imager is used for collecting spectral information of the test specimen by utilizing the handheld hyperspectral imager; starting in the first 6 th of the year 2020, selecting clear weather for hyperspectral image acquisition every 7-10 days at noon of 12: 00-14: 00. Picking up pine needles randomly from four directions of a sample plant by using high branch shears, wherein the collection amount of the needles is generally more than 50, cleaning the surfaces of the pine needles, erecting a spectrometer for collection, and correcting by using a barium sulfate white board. During the measurement process, the researchers are prevented from walking on two sides of the target area. The imaging instrument can be fixed on a tripod, and the barium sulfate plate and the sample plant are placed in the same image for collection. The collection time is up to the point where the masson pine shows obvious symptoms of injury, and healthy masson pine is selected for control experiments.
Selecting a multispectral imager containing sensitive wave bands, and carrying the multispectral imager on a fixed-wing unmanned aerial vehicle for image acquisition; in the 6 th last ten days of 2021, a fixed-wing unmanned aerial vehicle is selected to acquire spectral images by using a multispectral imager with inherent wave bands. The unmanned aerial vehicle adopts the constant-height cruising flight mode (the flight height is controlled at 700m), the camera lens always keeps vertical downward, and one-time repeated acquisition is needed for ensuring the scientificity and reliability of data. When the flight control line is arranged, the course is overlapped by more than 75 percent, and the side direction is overlapped by more than 70 percent. The RTK measurement is done simultaneously.
The data processing module is used for processing data by utilizing ENVI remote sensing image processing software, eliminating the influence of interference wave bands, correcting distortion, image correction and the like through dimension reduction processing, and acquiring an ideal spectrum curve; establishing a wave spectrum library for interference wave bands possibly caused by interference tree species and site conditions in an epidemic area, so that sensitive wave bands can be extracted at a later stage conveniently; and performing various index calculations on the multispectral, including a normalized vegetation index, a ratio vegetation index, a difference vegetation index and the like. For multispectral images of the unmanned aerial vehicle, preprocessing data by using unmanned aerial vehicle image processing software and remote sensing image processing software, wherein the preprocessing comprises image splicing, embedding and atmospheric correction; and extracting the spectral reflectivity of the sensitive waveband, obtaining an ROI value extracted from the susceptible pine, autonomously identifying the susceptible pine in the imaging region based on the ROI value, and obtaining the accurate geographical position of the susceptible pine through geographical registration.
And the data interpretation and analysis module is used for selecting different spectral indexes and analysis methods to establish a prediction model for the hyperspectral image according to the changes of the spectral reflectances in different time periods and different wave bands. Extracting an effective monitoring waveband at the early stage of disease attack, developing a multispectral imager aiming at early monitoring of the pine wood nematode disease forest, and determining the optimal early monitoring time point of the pine wood nematode disease forest; and for the multispectral image, based on a prediction model and autonomous identification, the position of the suspected infected pine is accurately positioned.
By combining all the technical schemes, the invention has the advantages and positive effects that: according to the invention, visible light/multi/hyperspectral monitoring, unmanned aerial vehicle technology and chemical prevention and control means are integrated, in the early stage that the traditional monitoring means can not observe pine tree diseases, pine forest spectrum information is obtained in forests through hyperspectrum and an unmanned aerial vehicle carrying a spectrum imager, data is processed, interpreted and analyzed by remote sensing image processing software indoors, the accurate geographical position of the pine tree suffering from the diseases is obtained, efficient and safe medicaments are selected to guide the accurate prevention and control in the forests, the early discovery, early treatment and accurate prevention and control in the pine tree diseases are realized, the current passive tree cutting and removing treatment is changed into active prevention and control, and the ecological value of the pine forest is protected to a greater extent.
According to the method, healthy pine trees (Pinus massoniana and Pinus tabulaeformis) are selected in the wild in the middle and late ten days of 5 months for artificial inoculation of pine wood nematodes by spectrum determination of susceptible pine trees in combination with biological characteristics of Monochamus alternatus. And continuously measuring the spectral information of the experimental sample plant by using a handheld hyperspectral imager from the middle ten days of 6 months to the beginning of 9 months, and collecting the spectral information once every 7-10 days. And (3) acquiring an ideal spectral curve by using remote sensing image processing software and removing the influence of interference wave bands, correction distortion, image correction and the like. According to the change of the spectrum wave band in different time periods, a prediction model is established, the effective monitoring wave band at the early stage of disease attack is extracted, a multispectral imager aiming at early monitoring of the pine wood nematode disease woodland is developed, and the optimal early monitoring time point of the pine wood nematode disease woodland is determined. The spectrum measurement of the unmanned aerial vehicle improves the monitoring efficiency of the pine wood nematode disease, reduces the monitoring cost, adapts to the requirement of large-area prevention and control in forests, and carries the multispectral imager on the fixed-wing unmanned aerial vehicle for image acquisition. And (3) flying under the condition of good weather condition at the optimal early monitoring time point of the pine wood nematode disease, and performing RTK measurement in the process. Data are analyzed and processed indoors through remote sensing image processing software, image splicing and embedding, atmospheric correction and the like are achieved, accurate positioning of suspected susceptible pine positions is achieved based on a prediction model and autonomous recognition, so that a medicament prevention and control test is conducted at a later stage, and data are provided for accurate prevention and control of the next step.
Screening the pesticide, preparing the pesticide into missible oil indoors by using methanol and an emulsifier through a pesticide screening test such as abamectin and emamectin benzoate, adding the pine wood nematode suspension into each hole of a 96-hole plate, adding different pesticides according to the set pesticide concentration, judging that the non-moving pest is J-shaped or C-shaped or stiff and does not have refractivity on the body wall, and calculating the mortality and correcting the mortality. Mixing and blending the raw medicines according to a certain proportion, determining the toxicity of different medicament combinations to the pine wood nematodes by an immersion method, screening out the optimal medicament combination, carrying out forest control effect tests by combining measures such as forest medicament injection, medium insect control and the like, determining medicament varieties and using methods suitable for early forest control, and formulating corresponding control technical rules.
And (3) standard demonstration land construction, namely, 1 test forest of 200 mu is selected from north and south of Chuandong to construct a standard demonstration forest for early prevention and treatment research of the pine wilt disease in forests. The sample plot for early prevention and treatment research is used as a test group, 200 mu of pine forest for conventional traditional (modes of pine monochamus trap, dead pine timely cut off and destroyed and the like) removal operation is randomly selected as a control group, and the incidence rates of the dead pine in the control group and the test group are compared. Striving to reduce the incidence of dead pine trees to below 5%.
Monitoring of operation prevention and control effects, in order to check test effects, the multi-rotor unmanned aerial vehicle with visible light is utilized to monitor prevention and control effects, and the morbidity of a control area and a test group is compared. And (3) performing spectral data processing, image splicing and mosaic, atmospheric correction and the like indoors by using remote sensing processing software ENVI. The monitoring of research effect is completed in time, and the method has an important effect on later-stage test planning and arrangement.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a flow chart of a method for early prevention and control of pine wilt disease in a forest according to an embodiment of the invention.
Fig. 2 is a schematic structural diagram of a pine wilt disease forest early monitoring system provided by the embodiment of the invention.
In the figure: 1. a hyperspectral imager; 2. a multispectral imager; 3. a central processing module; 4. a data processing module; 5. and the data interpretation and analysis module.
Fig. 3 is a flow chart of an implementation of the early-stage prevention and control method for pine wilt disease in forest according to the embodiment of the invention.
Fig. 4 is a graph showing that the spectral change curve of masson pine in each period follows the reflectivity curve characteristic of vegetation, namely, a green light region has a low reflection peak, and a near infrared region has a high reflection peak.
FIG. 5 is a schematic diagram of spectrum analysis of a diseased plant provided by an embodiment of the present invention.
Fig. 6 is a diagram illustrating a change in a value based on a sensitive spectral channel according to an embodiment of the present invention.
FIG. 7 is a schematic diagram of an inverted index model provided by an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a method for early prevention and control of pine wilt disease in forest and a monitoring system, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the method for early prevention and control of pine wilt disease in forest provided by the embodiment of the invention comprises the following steps:
s101: the method integrates visible light/multi/hyperspectral monitoring, unmanned aerial vehicle technology and chemical prevention and control means, and acquires pine forest spectral information in a forest through hyperspectrum and an unmanned aerial vehicle carried spectral imager.
S102: and processing, reading and analyzing hyperspectral and multispectral image data by using remote sensing image processing software indoors, and performing hyperspectral measurement and unmanned aerial vehicle multispectral measurement on susceptible pine trees to obtain accurate geographical positions of the susceptible pine trees.
S103: selecting efficient and safe medicaments to guide the accurate control of the woodland, realizing the early discovery and the effective control time of the pine wilt disease in the woodland, and carrying out the accurate control; after the control is finished, the effect of the test is checked.
In S102 provided by the embodiment of the present invention, when performing hyperspectral measurement on a susceptible pine tree, a specific process of collecting data is as follows:
in the middle and late ten days of 5 months, selecting healthy pine trees (Pinus massoniana and Pinus tabulaeformis) in the field by combining the biological characteristics of Monochamus alternatus to carry out artificial inoculation on pine wood nematodes;
and continuously measuring the spectral information of the experimental sample plant by using a handheld hyperspectral imager from the middle ten days of 6 months to the beginning of 9 months, and collecting the spectral information once every 7-10 days.
Acquiring an ideal spectral curve by using remote sensing image processing software through removing influences of interference wave band, correcting distortion, image correction and the like;
according to the change of the spectrum wave band in different time periods, a prediction model is established, the effective monitoring wave band at the early stage of disease attack is extracted, a multispectral imager aiming at early monitoring of the pine wood nematode disease woodland is developed, and the optimal early monitoring time point of the pine wood nematode disease woodland is determined.
In S102 provided by the embodiment of the present invention, the specific process of acquiring the multispectral image of the unmanned aerial vehicle is as follows:
carrying a multispectral imager on a fixed-wing unmanned aerial vehicle for image acquisition; selecting a condition with a better weather condition to fly at the optimal early monitoring time point of the pine wood nematode disease, and performing RTK measurement in the process;
data are analyzed and processed indoors through remote sensing image processing software, image splicing and embedding, atmospheric correction and the like are achieved, accurate positioning of the position of the suspected infected pine is achieved based on a prediction model and autonomous recognition, so that a medicament prevention and control test is conducted at a later stage, and data are provided for accurate prevention and control of the next step. The unmanned aerial vehicle spectral measurement improves the monitoring efficiency of the pine wilt disease, reduces the monitoring cost and meets the requirement of large-area prevention and control in woodlands.
In S103 provided by the embodiment of the present invention, the specific process of medicament screening is as follows:
the method comprises the steps of selecting abamectin, emamectin benzoate and other medicament screening tests, preparing a raw medicament into missible oil indoors by using methanol and an emulsifier, adding pine wood nematode suspension into each hole of a 96-hole plate, adding different medicaments according to set medicament concentrations, judging that dead insects exist when the unmovable insects are J-shaped or C-shaped or the insects are stiff and the body walls have no refractivity, and calculating the death rate and correcting the death rate.
Mixing and blending the raw medicines according to a certain proportion, determining the toxicity of different medicament combinations to the pine wood nematodes by an immersion method, screening out the optimal medicament combination, carrying out forest control effect tests by combining measures such as forest medicament injection, medium insect control and the like, determining medicament varieties and using methods suitable for early forest control, and formulating corresponding control technical rules.
In S103 provided by the embodiment of the present invention, after the prevention and treatment are completed, the effect test process is performed as follows:
the multi-rotor unmanned aerial vehicle with visible light is utilized to monitor the control effect, and the morbidity of a control area and a test group is compared. And (3) performing spectral data processing, image splicing and mosaic, atmospheric correction and the like indoors by using remote sensing processing software ENVI. The monitoring of research effect is completed in time, and the method has an important effect on later-stage test planning and arrangement.
As shown in fig. 2, an early monitoring system for pine wilt disease forest provided by the embodiment of the present invention includes:
the hyperspectral imager 1 is used for collecting spectral information of the experimental specimen by using the handheld hyperspectral imager.
And the multispectral imager 2 is carried on the fixed-wing unmanned aerial vehicle for image acquisition.
And the central processing module 3 is used for coordinating the normal operation of each module.
The data processing module 4 is used for acquiring an ideal spectrum curve for the highlight image by utilizing remote sensing image processing software and removing the influence of interference wave bands, correcting distortion, image correction and the like; and analyzing and processing data of the multispectral image by using remote sensing image processing software, wherein the data comprises image splicing, mosaic, atmospheric correction and the like.
The data interpretation and analysis module 5 is used for establishing a prediction model and extracting an effective monitoring wave band at the initial stage of disease attack for the highlight image according to changes of the spectrum wave band at different time periods, developing a multispectral imager aiming at early monitoring of the pine wood nematode disease forest and determining the optimal early monitoring time point of the pine wood nematode disease forest; and for the multispectral image, based on a prediction model and autonomous identification, the position of the suspected infected pine is accurately positioned.
The technical solution of the present invention is further described with reference to the application examples.
Spectrum determination of susceptible pine
In the middle and late ten days of 5 months, healthy pine trees (Pinus massoniana and Pinus tabulaeformis) are selected in the field to be artificially inoculated with pine wood nematodes by combining the biological characteristics of Monochamus alternatus. And continuously measuring the spectral information of the experimental sample plant by using a handheld hyperspectral imager from the middle ten days of 6 months to the beginning of 9 months, and collecting the spectral information once every 7-10 days. And (3) acquiring an ideal spectral curve by using remote sensing image processing software and removing the influence of interference wave bands, correction distortion, image correction and the like. According to the change of the spectrum wave band in different time periods, a prediction model is established, the effective monitoring wave band at the early stage of disease attack is extracted, a multispectral imager aiming at early monitoring of the pine wood nematode disease woodland is developed, and the optimal early monitoring time point of the pine wood nematode disease woodland is determined.
Unmanned aerial vehicle spectrometry
In order to improve the monitoring efficiency of the pine wilt disease, reduce the monitoring cost and meet the requirement of large-area prevention and control in forests, the multispectral imager is carried on the fixed-wing unmanned aerial vehicle for image acquisition. And (3) flying under the condition of good weather condition at the optimal early monitoring time point of the pine wood nematode disease, and performing RTK measurement in the process. Data are analyzed and processed indoors through remote sensing image processing software, image splicing and embedding, atmospheric correction and the like are achieved, accurate positioning of suspected susceptible pine positions is achieved based on a prediction model and autonomous recognition, so that a medicament prevention and control test is conducted at a later stage, and data are provided for accurate prevention and control of the next step.
Drug screening
According to comprehensive literature data investigation, the research is to select and select abamectin, emamectin benzoate and other medicament screening tests, prepare raw medicaments into missible oil indoors by using methanol and an emulsifier, add pine wood nematode suspension into each hole of a 96-hole plate, add different medicaments according to set medicament concentration, judge the unmoving insect as dead insect if the unmoving insect is J-shaped or C-shaped or stiff and the body wall has no refractivity, and calculate the death rate and correct the death rate. Mixing and blending the raw medicines according to a certain proportion, determining the toxicity of different medicament combinations to the pine wood nematodes by an immersion method, screening out the optimal medicament combination, carrying out forest control effect tests by combining measures such as forest medicament injection, medium insect control and the like, determining medicament varieties and using methods suitable for early forest control, and formulating corresponding control technical rules.
Construction of standard demonstration land
And 1 test forest of 200 mu is selected from north Chuandong and south Chuannan respectively to build a standard demonstration forest for early prevention and treatment research of the pine wilt disease in the forest. The sample plot for early prevention and treatment research is used as a test group, 200 mu of pine forest for conventional traditional (modes of pine monochamus trap, dead pine timely cut off and destroyed and the like) removal operation is randomly selected as a control group, and the incidence rates of the dead pine in the control group and the test group are compared. Striving to reduce the incidence of dead pine trees to below 5%.
Monitoring of work control effects
For the experimental effect of inspection, utilize many rotor unmanned aerial vehicle of visible light to prevent and treat the effect monitoring, the morbidity of comparison district and test group. And (3) performing spectral data processing, image splicing and mosaic, atmospheric correction and the like indoors by using remote sensing processing software ENVI. The monitoring of research effect is completed in time, and the method has an important effect on later-stage test planning and arrangement.
Collecting susceptible pine trees from 3-month middle ten days of 2020 to a pine wood nematode disease occurrence place, taking the sample back to a laboratory for pine wood nematode separation, optionally carrying out a Bellman funnel method, putting the corn seeds soaked and swelled in water into a triangular flask, carrying out high-temperature sterilization, then inoculating Botrytis cinerea (Botrytis cinerea Pers.), culturing for 6-7 days under a dark condition at 25 ℃, taking 1mL of nematode suspension, dropwise adding the nematode suspension onto the cushion-shaped hyphae, culturing for 5-7 days under the same condition, stopping culturing after a large amount of nematodes climb over the wall of the triangular flask, and placing the container in a refrigerator at 8 ℃ for later use.
Selecting a test sample plot from south China and north China, inoculating pine wood nematodes on selected healthy pine trees in the middle and late 5 months, grouping the test sample strains, namely a blank control group, a susceptible pine tree spectral image acquisition group, a medicament screening test group and the like, wherein the test time is from the middle ten days of 6 months to the late 8 months, strictly preventing the diffusion of the pine wood nematodes in the process, and timely cutting off dead trees and intensively destroying the dead trees after the experiment in the current period is finished. The remote sensing image processing software is used for reading and analyzing forest test data, a monitoring model is established, and the optimal monitoring time point of the wild susceptible pine trees, the forest effective test medicament and the matched use technology are determined. Combining autumn and spring general survey, selecting a 200-mu standard sample plot in 2021 and 4 months, collecting remote sensing images of pine in the sample plot at the optimal early monitoring time point of the pine with an unmanned aerial vehicle to perform multispectral imaging, performing indoor analysis to determine the accurate geographical position of the suspected disease-susceptible pine, and performing early control on the pine suspected to be infected with the pine wilt disease by using the selected optimal forest medicament in different time periods. Checking the control effect and clearing the epidemic trees in the sample plot, perfecting the monitoring model, analyzing the medication time and the control effect, clearing the optimal medication time, collecting the remote sensing image of the pine in the sample plot by using the unmanned aerial vehicle multispectral imager again in the next year, analyzing indoors to determine the accurate geographical position of the suspected pine infected with the pine wilt disease, and performing early-stage medicament control on the pine suspected to be infected with the pine wilt disease. Finally, carrying a visible light camera by using an unmanned aerial vehicle in the middle and last ten days of 2022 months for detecting the control effect, and completing 2 early-stage control standard demonstration land construction of the pine wood nematode disease; compiling 1 item of technical regulation for early woodland prevention and control of the pine wilt disease and local standard; compiling materials, preparing a field and checking and accepting the project.
Spectral image processing: the previous study started in 6 months of 2019, and 5 field hyperspectral image acquisitions (19 days of 6 months, 19 days of 7 months, 16 days of 8 months, 8 days of 9 months and 30 days of 9 months) were performed in total. The acquired image is processed by ENVI to obtain a smooth spectral curve. From the spectrum curve, it can be seen that the spectrum change curve of healthy masson pine in each period follows the reflectivity curve characteristic of vegetation, namely, a low reflection peak exists in a green light region, and a high reflection peak exists in a near infrared region (see fig. 3).
And (3) spectrum image processing result: the spectrum curve difference of the affected plants in each period is obvious, compared with a control group, the difference is not obvious in the early period of the affected plants, the reflection peak of a green light area gradually weakens until the affected plants completely die, and the reflection peak or absorption valley characteristics on the spectrum change curve obviously disappear.
Spectrum analysis of infected plants: through long-time field monitoring test, find that 3 # appearance trunk appears withered and yellow phenomenon when 2 nd field collection, the spectral difference of healthy plant and infected plant shows: the reflection peak in the green region gradually weakens until disappearing, the wide and flat reflection region in the near infrared region is gradually replaced by a straight line, namely the reflection spectrum is gradually changed into a straight line in the late period of infection until death, and all the reflection peaks and absorption valleys gradually weaken and disappear (see figure 4).
And (3) comparing the spectrum of the infected plant with the experimental plant: the spectrum curve difference of the pinus massoniana infected plant in each period is obvious, compared with a contrast, the spectrum curve difference is shown to be that the difference is not obvious in the early stage of the disease, the reflection peak in a green light area is gradually weakened until the diseased plant is completely withered, and the reflection peak or absorption valley characteristic on the spectrum change curve obviously disappears.
Through a plurality of spectrum combination parameter screens, the ratio spectrum index (K) of two wave bands of 760nm and 675nm can be used for determining whether the pine is infected with the disease. When K is less than 8, the disease-sensitive plants can be determined to have reached the middle and later stages (the disease-sensitive time exceeds 60 days); when K is more than 13, the infected plant is known to be in the early stage of infection (within 15 days), and the color and the tree vigor of the coniferous trees are not changed at all; when K is more than 8 and less than 13, quantitative calculation must be carried out on the spectrum to accurately judge the disease susceptibility state of the pine tree. As shown in fig. 5.
The spectrum data is used for spectrum extraction, the performances of different wave bands at different vegetation indexes are analyzed, and the fact that the condition of masson pine between half month and two months after illness can be better reflected under the condition that the vegetation indexes are normalized at the wave bands of 810nm and 450nm is found (see figure 6).
Changing the inverse prediction model to "-15.13 × NDVI(810,450)]2+27.96*NDVI(810,450)11.36 ". The method has a certain effect on guiding forests to carry out early monitoring and prevention.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. The early prevention and control method for the pine wilt disease in the forest is characterized by comprising the following steps of:
integrating visible light, multi-spectrum and hyperspectral monitoring, unmanned aerial vehicle technology and chemical prevention and control means, and acquiring spectral information of pine forest in a forest by hyperspectrum and a spectral imager carried by an unmanned aerial vehicle;
processing, reading and analyzing hyperspectral and multispectral image data by using remote sensing image processing software indoors, and performing hyperspectral measurement and unmanned aerial vehicle multispectral measurement on susceptible pine trees to obtain accurate geographical positions of the susceptible pine trees;
selecting efficient and safe medicaments to guide the accurate control of the woodland, realizing the early discovery and the effective control time of the pine wilt disease in the woodland, and carrying out the accurate control; after the control is finished, the effect of the test is checked.
2. The method for early prevention and control of pine wilt disease in woodland according to claim 1, wherein when sensing pine hyperspectral survey, the specific process of collecting data is as follows:
combining the biological characteristics of Monochamus alternatus, and selecting healthy pine trees in the middle and late ten days of 5 months for artificial inoculation of pine wood nematodes in the field;
from the middle ten days of 6 months to the beginning of 9 months, the spectrum information of the experimental sample is continuously measured by using a handheld hyperspectral imager, and the experimental sample is generally collected once every 7-10 days.
3. The method for early prevention and control of pine wilt disease in woodland according to claim 1, wherein the specific process of the remote sensing image processing software for processing the hyperspectral data is as follows:
acquiring an ideal spectral curve by using remote sensing image processing software through removing interference wave band influence, correcting distortion and image correction;
according to the change of the spectrum wave band in different time periods, a prediction model is established, the effective monitoring wave band at the early stage of disease attack is extracted, a multispectral imager aiming at early monitoring of the pine wood nematode disease woodland is developed, and the optimal early monitoring time point of the pine wood nematode disease woodland is determined.
4. The method for early prevention and treatment of pine wilt disease in woodland as claimed in claim 1, wherein in said second step, the specific process of collecting multispectral image of unmanned aerial vehicle is: carrying a multispectral imager on a fixed-wing unmanned aerial vehicle for image acquisition; and (3) flying under the condition of good weather condition at the optimal early monitoring time point of the pine wood nematode disease, and performing RTK measurement in the process.
5. The method for early prevention and treatment of pine wilt disease in woodland according to claim 1, wherein the specific process of multispectral data processing by the remote sensing image processing software is as follows: data are analyzed and processed indoors through remote sensing image processing software, image splicing, mosaic, atmospheric correction and the like, and accurate positioning of the positions of suspected infected pine trees is achieved based on a prediction model and autonomous recognition.
6. The method for early prevention and control of pine wilt disease in woodland as claimed in claim 1, wherein the specific process of screening the medicament is as follows: selecting abamectin, emamectin benzoate and other medicament screening tests, preparing a raw medicament into missible oil indoors by using methanol and an emulsifier, and adding the pine wood nematode suspension into each hole of a 96-hole plate;
adding different agents according to the set agent concentration, judging the unmovable insect body to be dead if the unmovable insect body is J-shaped or C-shaped or the insect body is stiff and the body wall has no refractivity, calculating the mortality and correcting the mortality.
7. The method according to claim 6, wherein the raw pesticides are mixed and matched according to a certain proportion, the toxicity of different drug combinations to the pine wood nematodes is determined by a dipping method, the optimal drug combination is screened out, a forest control effect test is performed by combining means of forest drug injection, medium insect control and the like, drug varieties and using methods suitable for forest early control are determined, and corresponding control technical rules are formulated.
8. The method for early prevention and control of pine wilt disease in woodland as claimed in claim 1, wherein after the prevention and control is completed, the effect process of the inspection test is carried out as follows: the multi-rotor unmanned aerial vehicle with visible light is utilized to monitor the control effect, and the morbidity of a control area and a test group is compared.
9. The early pine wilt disease forest control method of claim 8, wherein the monitoring of control effect by the visible light multi-rotor unmanned aerial vehicle comprises: acquiring corresponding spectral data, and performing spectral data processing indoors by using remote sensing processing software ENVI, image splicing, embedding and atmospheric correction; and the research effect monitoring is completed in time, and a later-stage test plan and arrangement are made.
10. A bursaphelenchus xylophilus forest early-stage monitoring system for implementing the bursaphelenchus xylophilus forest early-stage control method according to claims 1 to 9, wherein the bursaphelenchus xylophilus forest early-stage monitoring system comprises:
the hyperspectral imager is used for collecting spectral information of the experimental specimen by utilizing the handheld hyperspectral imager;
the multispectral imager is carried on the fixed-wing unmanned aerial vehicle for image acquisition;
the central processing module coordinates the normal operation of each module;
the data processing module is used for acquiring an ideal spectral curve for the highlight image by utilizing remote sensing image processing software through removing the influence of interference wave bands, correcting distortion, image correction and the like; analyzing and processing data of the multispectral image by using remote sensing image processing software, wherein the data comprises image splicing, embedding and atmospheric correction;
the data interpretation and analysis module is used for establishing a prediction model and extracting an effective monitoring wave band at the initial disease attack stage for the highlight image according to the change of the spectrum wave band at different time periods, developing a multispectral imager aiming at early monitoring of the pine wood nematode disease forest and determining the optimal early monitoring time point of the pine wood nematode disease forest; and for the multispectral image, based on a prediction model and autonomous identification, the position of the suspected infected pine is accurately positioned.
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