CN113218898A - Plant disease remote sensing feature extraction method based on spectral analysis - Google Patents
Plant disease remote sensing feature extraction method based on spectral analysis Download PDFInfo
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- CN113218898A CN113218898A CN202110491614.4A CN202110491614A CN113218898A CN 113218898 A CN113218898 A CN 113218898A CN 202110491614 A CN202110491614 A CN 202110491614A CN 113218898 A CN113218898 A CN 113218898A
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
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- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
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- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
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- G01N2021/1765—Method using an image detector and processing of image signal
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- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
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Abstract
The invention relates to the technical field of plant disease monitoring, and discloses a plant disease remote sensing feature extraction method based on spectral analysis, which comprises the following steps: step 1: establishing an indoor spectral imaging system; step 2: collecting sample spectral images of the same plant in different spectral bands, and establishing a sample spectral image database; and step 3: collecting a spectral image of a plant to be detected; and 4, step 4: comparing the collected spectral image of the tested plant with a sample spectral image database; and 5: the health condition of the tested plant is effectively analyzed. According to the invention, the spectral image of the plant detected by the spectrometer is input into the database and compared with the spectral image database of the sample, the area value of the plant spectral analysis is found out, and whether the plant has a disease trend can be judged according to the specific area value of the plant to be detected, so that whether the plant is healthy can be rapidly known.
Description
Technical Field
The invention relates to the technical field of plant disease monitoring, in particular to a plant disease remote sensing feature extraction method based on spectral analysis.
Background
The pathological features of the affected plants occur in physiology, tissue structure and morphology under the interference of pathogens or adverse environmental conditions. Lesions directly observable to the naked eye, known as macrosymptoms; microscopic lesions are known as microscopic symptoms. The microscopic symptoms are mostly applied in the research range of diseased cells or diseased tissues, and only have certain reference values in the diagnosis of viral diseases of plants, such as the observation of the existence of necrotic cells in phloem, the existence of hyperplasia structures in sieve tubes and catheters, the shapes and types of various inclusion bodies appearing in diseased cells infected with viral diseases, and the like. In order to prevent plant diseases, stems and leaves of plants need to be detected in advance to judge whether the plants are healthy, so a remote sensing feature extraction method for the plant diseases based on spectral analysis is provided.
Disclosure of Invention
The invention aims to provide a plant disease remote sensing feature extraction method based on spectral analysis, and solves the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: a plant disease remote sensing feature extraction method based on spectral analysis comprises the following steps:
step 1: establishing an indoor spectral imaging system;
step 2: collecting sample spectral images of the same plant in different spectral bands, and establishing a sample spectral image database;
and step 3: collecting a spectral image of a plant to be detected;
and 4, step 4: comparing the collected spectral image of the tested plant with a sample spectral image database;
and 5: the health condition of the tested plant is effectively analyzed.
In a preferred embodiment of the present invention, in step 2, samples of healthy and infected plants are collected on days 3, 6, 9, 12 and 15, respectively, and hyperspectral images of healthy and infected stalks are collected in real time before the extent of disease is measured, and a database is built.
In a preferred embodiment of the present invention, in step 3, the spectral image of the plant to be tested is detected by a spectrometer.
In a preferred embodiment of the present invention, in step 4, the spectral image of the plant detected by the spectrometer is input into the database, and compared with the sample spectral image database to find the region value of the plant spectral analysis.
In a preferred embodiment of the present invention, the plant is judged to have a tendency to be diseased or not based on the value of the specific region of the plant to be tested.
As a preferred embodiment of the present invention, the peak in the spectral image is the most sensitive of all wavelengths in the test data.
As a preferred embodiment of the invention, the visible spectral wavelengths of the infected sample are more sensitive than those of a healthy sample
Compared with the prior art, the invention provides a plant disease remote sensing feature extraction method based on spectral analysis, which has the following beneficial effects:
according to the plant disease remote sensing feature extraction method based on spectral analysis, the spectral image of the plant to be detected through the spectrometer is input into the database and compared with the spectral image database of the sample, the area value of plant spectral analysis is found out, whether the plant has a disease trend can be judged according to the specific area value of the plant to be detected, and whether the plant is healthy can be rapidly known.
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Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a schematic flow chart of a plant disease remote sensing feature extraction method based on spectral analysis.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
In the description of the present invention, it should be noted that unless otherwise explicitly stated or limited, the terms "mounted," "connected," and "disposed" are to be construed broadly, e.g., as meaning fixedly connected, disposed, detachably connected, disposed, or integrally connected and disposed; the type of the electrical appliance provided by the invention is only used for reference. For those skilled in the art, different types of electrical appliances with the same function can be replaced according to actual use conditions, and for those skilled in the art, the specific meaning of the above terms in the present invention can be understood in specific situations.
Referring to fig. 1, the present invention provides a technical solution: a plant disease remote sensing feature extraction method based on spectral analysis comprises the following steps:
step 1: establishing an indoor spectral imaging system;
step 2: collecting sample spectral images of the same plant in different spectral bands, and establishing a sample spectral image database;
and step 3: collecting a spectral image of a plant to be detected;
and 4, step 4: comparing the collected spectral image of the tested plant with a sample spectral image database;
and 5: the health condition of the tested plant is effectively analyzed.
In this embodiment, in step 2, samples of healthy and infected plants are collected on days 3, 6, 9, 12 and 15, respectively, and hyperspectral images of healthy and infected stalks are collected in real time before the extent of disease is measured, and a database is established.
In this embodiment, in step 3, the spectral image of the plant to be detected is detected by a spectrometer.
In this embodiment, in step 4, the spectral image of the plant detected by the spectrometer is input into the database, and compared with the spectral image database of the sample, and the region value of the plant spectral analysis is found.
In this embodiment, whether a plant has a tendency to be damaged or not is determined based on the value of a specific region of the plant to be tested.
In this embodiment, in step 5, in the test data, the peak in the spectral image is the most sensitive of all wavelengths.
In this embodiment, the visible spectral wavelength of the infected sample is more sensitive than the healthy sample.
When the plant disease detection device works, firstly, samples of healthy and infected plants are collected on the 3 rd, 6 th, 9 th, 12 th and 15 th days respectively, hyperspectral images of healthy and infected stalks are collected in real time before disease degree is measured, a database is established, then, a spectrometer is used for detecting the spectral images of the plants to be detected and inputting the spectral images into the database, the spectral images are compared with the sample spectral image database to find out the region value of plant spectral analysis, and whether the plants have the disease trend or not is judged when the plants to be detected are in the specific region value.
While there have been shown and described what are at present considered the fundamental principles and essential features of the invention and its advantages, it will be apparent to those skilled in the art that the invention is not limited to the details of the foregoing exemplary embodiments, but is capable of other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (7)
1. A plant disease remote sensing feature extraction method based on spectral analysis is characterized by comprising the following steps: the method comprises the following steps:
step 1: establishing an indoor spectral imaging system;
step 2: collecting sample spectral images of the same plant in different spectral bands, and establishing a sample spectral image database;
and step 3: collecting a spectral image of a plant to be detected;
and 4, step 4: comparing the collected spectral image of the tested plant with a sample spectral image database;
and 5: the health condition of the tested plant is effectively analyzed.
2. The method for extracting the remote sensing characteristic of the plant diseases based on the spectral analysis as claimed in claim 1, which is characterized in that: in the step 2, samples of healthy and infected plants are collected on days 3, 6, 9, 12 and 15 respectively, hyperspectral images of healthy and infected stalks are collected in real time before the disease degree is measured, and a database is established.
3. The method for extracting the remote sensing characteristic of the plant diseases based on the spectral analysis as claimed in claim 1, which is characterized in that: and in the step 3, detecting the spectral image of the plant to be detected through a spectrometer.
4. The method for extracting the remote sensing characteristic of the plant diseases based on the spectral analysis as claimed in claim 1, which is characterized in that: and 4, inputting the spectral image of the plant detected by the spectrometer into the database, comparing the spectral image with the spectral image database of the sample, and finding out the region value of the plant spectral analysis.
5. The method for extracting the remote sensing characteristic of the plant diseases based on the spectral analysis as claimed in claim 1, which is characterized in that: and judging whether the plant has a disease trend or not according to the specific region value of the tested plant.
6. The method for extracting the remote sensing characteristic of the plant diseases based on the spectral analysis as claimed in claim 4, characterized in that: in the test data, the peak in the spectral image is the most sensitive of all wavelengths.
7. The method for extracting the remote sensing characteristic of the plant diseases based on the spectral analysis as claimed in claim 4, characterized in that: the visible spectral wavelengths of infected samples are more sensitive than healthy samples.
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