Method and system for acquiring information on yellowing, and method for testing plant diseases

Abstract

To provide a method for acquiring information about plant diseases and testing for them more efficiently.SOLUTION: The present invention provides a method for testing plant diseases, including: a selection process S1 in which a two-dimensional image containing optical information for each pixel of an image obtained by photographing a plant leaf is generated and leaves to be tested are selected based on the two-dimensional image; and a testing process S2 in which a PCR test is performed on the leaves selected in the selection process S1.SELECTED DRAWING: Figure 10

Description

[Technical field]

[0001] The present invention relates to a method and system for acquiring information about the yellowing of plant leaves, and a method for inspecting plant diseases. [Background technology]

[0002] A deterioration of the growth environment, pathogen infection, and the like can cause poor plant growth and progress in plant yellowing. In plant cultivation, it is important to accurately grasp and deal with the progress of plant yellowing. For this reason, for example, a pathogen infection diagnostic device has been proposed that irradiates a plant body with excitation light of a wavelength that excites pathogen tissue and grasps the pathogen infection of the plant (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2013-36889 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the pathogen infection diagnostic device described in Patent Document 1 can identify tissues that have already been infected with pathogens and are undergoing yellowing, but it is difficult to identify the early stages of yellowing. In addition, it requires an expensive dedicated device equipped with a light source that irradiates excitation light of a specific wavelength at a specified intensity.

[0005] The present invention has been made in consideration of the above problems, and aims to provide a yellowing information acquisition method and a yellowing information acquisition system that are capable of identifying the yellowing state of a plant from an early stage with a simple configuration.

[0006] Furthermore, the above-mentioned information acquisition method and information acquisition system can acquire other information related to plant diseases from the yellowing information. Therefore, it is a further object of the present invention to provide a method for acquiring information related to plant diseases and more efficiently inspecting plants for diseases. [Means for solving the problem]

[0007] One embodiment of the method for acquiring yellowing information of the present invention is to an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring the red light intensity (hereinafter referred to as "R light intensity"), the green light intensity (hereinafter referred to as "G light intensity"), and the blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding B light intensity of each pixel, and the approximation line or curve of the point group obtained by plotting the R light intensity and the G light intensity of each pixel on the R-G plane as a gauge; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition method includes the steps of:

[0008] Another aspect of the yellowing information acquisition method of the present invention is an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter plot acquisition step of acquiring a two-dimensional scatter plot in which the value of each point, which is an approximate straight line or curve of a point group obtained by plotting the H intensity and V intensity of each pixel on an HV plane, and the corresponding S intensity of each pixel are used as two axes; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition method includes the steps of:

[0009] Another aspect of the yellowing information acquisition method of the present invention is an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring the red light intensity (hereinafter referred to as "R light intensity"), the green light intensity (hereinafter referred to as "G light intensity"), and the blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the R light intensity or G light intensity and the B light intensity of each pixel as two axes; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition method includes the steps of:

[0010] Another aspect of the yellowing information acquisition method of the present invention is an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter plot acquisition step of acquiring a two-dimensional scatter plot having H intensity or V intensity and S intensity of each pixel as two axes; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition method includes the steps of:

[0011] One embodiment of the yellowing information acquisition system of the present invention is as follows: an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit that acquires a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding B light intensity of each pixel, and the approximation line or curve of the point group obtained by plotting the R light intensity and the G light intensity of each pixel on the R / G plane as a gauge; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system is equipped with the above.

[0012] Another aspect of the yellowing information acquisition system of the present invention is an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit that acquires a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding S intensity of each pixel, and the value of each point being an approximate straight line or curve of a point group obtained by plotting the H intensity and V intensity of each pixel on an HV plane; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system is equipped with the above.

[0013] Another aspect of the yellowing information acquisition system of the present invention is an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit that acquires a two-dimensional scatter diagram with the R light intensity or G light intensity and the B light intensity of each pixel as two axes; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system is equipped with the above.

[0014] Another aspect of the yellowing information acquisition system of the present invention is an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit for acquiring a two-dimensional scatter diagram with the H intensity or V intensity and the S intensity of each pixel as two axes; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system is equipped with the above.

[0015] One embodiment of the method for testing a plant disease of the present invention includes: a sorting process for generating a two-dimensional image including light information of each pixel of an image obtained by photographing a plant leaf, and sorting a leaf to be inspected based on the two-dimensional image; An inspection process for performing a PCR test on the leaves selected in the selection process; A method for testing a plant for a disease, comprising: Effect of the Invention

[0016] As described above, the above aspects can provide a method and system for acquiring information on yellowing that can identify the state of yellowing of a plant from an early stage with a simple configuration. Furthermore, the above-mentioned method for inspecting plant diseases can provide a method for inspecting plant diseases more efficiently in a selection process that is performed by acquiring information on plant diseases. [Brief description of the drawings]

[0017] [Figure 1A] 1 is a block diagram showing a configuration of an yellowing information acquisition system according to one embodiment of the present invention. [Figure 1B] FIG. 11 is a block diagram showing a configuration of a yellowing information acquisition system according to another embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram showing an image acquisition section of a plant leaf. [Diagram 3] This is a three-dimensional scatter plot in which the RGB light intensity of each pixel of an acquired image is plotted in three-dimensional space, and is a view of a sheet-like point cloud viewed from a direction opposite to the sheet surface. [Figure 4] This is a three-dimensional scatter plot in which the RGB light intensity of each pixel of an acquired image is plotted in three-dimensional space, and is a view of a sheet-like point cloud viewed in a direction along the sheet surface. [Diagram 5] FIG. 13 is a diagram showing an example of a group of points obtained by plotting the RG light intensity of each pixel of an acquired image on an RG plane, and an example of an approximation straight line thereof. [Figure 6A]FIG. 13 is a diagram showing an example of an approximation straight line of a group of points obtained by plotting the RG light intensity of each pixel of an acquired image on a plane. [Figure 6B] FIG. 13 is a diagram showing an example of an approximation curve of a group of points obtained by plotting the RG light intensity of each pixel of an acquired image on a plane. [Figure 7] FIG. 13 is a diagram showing an example of a two-dimensional scatter diagram acquired based on the RGB light intensity of each pixel of an acquired image. [Figure 8A] FIG. 1 shows an example of a two-dimensional scatter plot of yellowed areas on leaves of a plant infected with a pathogen. [Figure 8B] FIG. 1 shows an example of a two-dimensional scatter plot of yellowed areas on leaves of a plant infected with a pathogen. [Figure 8C] FIG. 1 shows an example of a two-dimensional scatter plot of yellowed areas on leaves of a plant infected with a pathogen. [Figure 8D] FIG. 1 shows an example of a two-dimensional scatter plot of yellowed areas on leaves of a plant infected with a pathogen. [Figure 9] FIG. 1 is a diagram showing an example of a three-dimensional scatter plot in which the HSV intensity of each pixel of an image of a plant leaf is plotted in a three-dimensional space. [Figure 10] 1 is a flowchart showing a method for inspecting a plant for a disease. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] Hereinafter, an embodiment for carrying out the present invention will be described with reference to the drawings. In each drawing, corresponding components having the same function are given the same reference numerals. In consideration of the explanation or ease of understanding of the main points, the embodiments may be shown separately for convenience, but partial replacement or combination of the configurations shown in different embodiments is possible. In the embodiments described below, the description of matters common to the above-mentioned embodiments will be omitted, and only the differences will be described. In particular, similar actions and effects due to similar configurations will not be mentioned in each embodiment.

[0019] In the description of the embodiments of the present invention, first, a system and a method for acquiring information on plant yellowing will be described using an example of acquiring information on plant yellowing. Next, a method for more efficiently inspecting plants for disease by acquiring information on plant disease using the system and the method for acquiring information on plant yellowing will be described.

[0020] (Yellowing Information Acquisition System) First, a yellowing information acquisition system according to an embodiment of the present invention will be described with reference to Fig. 1A and Fig. 1B. Fig. 1A is a block diagram showing the configuration of a yellowing information acquisition system according to one embodiment of the present invention. Fig. 1B is a block diagram showing the configuration of a yellowing information acquisition system according to another embodiment of the present invention.

[0021] 1A and 1B each include an image acquisition unit 10 that acquires images of plant leaves, a control unit 80, and a display device 50 that displays the information acquired by the control unit 80. In order to control the implementation of a etiolation information acquisition method described below, the control unit 80 includes a light information acquisition unit 20, a scatter diagram acquisition unit 30, and an etiolation information acquisition unit 40. Image data of plant leaves acquired by the image acquisition unit 10 can be transmitted to the control unit 80, and the information acquired under the control of the control unit 80 can be transmitted to the display device 50 for display.

[0022] In the etiolation information acquisition system shown in FIG. 1A, the image acquisition unit 10 and the display device 50 are provided in the mobile terminal 70. The mobile terminal 70 and a server having a control unit 80 are connected by wireless or wired two-way communication. The user photographs the leaves of the plant with the image acquisition unit (camera) 10 of the mobile terminal 70 and transmits the photographed image data to a server having a remote control unit 80 by wireless or wired communication. The control unit 80 performs control processing based on the image data received from the mobile terminal 70, and transmits to the mobile terminal 70 a two-dimensional scatter diagram and etiolation information based on the two-dimensional scatter diagram acquired in the control processing. The two-dimensional scatter diagram and the etiolation information based on the two-dimensional scatter diagram will be described in detail later. The user can accurately grasp the state of etiolation of the plant by displaying the received two-dimensional scatter diagram and etiolation information on the display device 50 of the mobile terminal 70.

[0023] In the etiolation information acquisition system 100 shown in FIG. 1B, an image acquisition section 10, a control section 80, and a display device 50 are provided in one etiolation information acquisition device 90. A user photographs a plant leaf with the image acquisition section (camera) 10 of the etiolation information acquisition device 90. The photographed image data is transmitted to the control section 80. Based on the image data transmitted from the image acquisition section 10, the control section 80 acquires a two-dimensional scatter diagram and etiolation information based on the two-dimensional scatter diagram, and transmits the acquired data to the display device 50. The transmitted two-dimensional scatter diagram and etiolation information are displayed on the display device 50. The information displayed on the display device 50 allows the user to accurately grasp the etiolation state of the plant.

[0024] The yellowing information acquisition system of the present invention is not limited to the above configuration, and the image acquisition unit 10, the control unit 80, and the display device 50 may all be separate devices, or some of the elements may be provided in the same device.

[0025] (Method of acquiring yellowing information according to the first embodiment) Next, with reference to FIG. 2 to FIG. 7, the etiolation information acquisition method according to the first embodiment of the present invention, which is implemented in the above-mentioned etiolation information acquisition system 100, will be described. FIG. 2 is a diagram showing an image acquisition portion of a plant leaf. FIG. 3 is a three-dimensional scatter diagram in which the RGB light intensity of each pixel of an acquired image is plotted in a three-dimensional space, and is a diagram showing a sheet-like point cloud viewed from a direction opposite to the sheet surface. FIG. 4 is a three-dimensional scatter diagram in which the RGB light intensity of each pixel of an acquired image is plotted in a three-dimensional space, and is a diagram showing a sheet-like point cloud viewed from a direction along the sheet surface. FIG. 5 is a diagram showing an example of a point cloud in which the RG light intensity of each pixel of an acquired image is plotted on an RG plane, and an example of an approximate straight line thereof. FIG. 6A is a diagram showing an example of an approximate straight line of a point cloud in which the RG light intensity of each pixel of an acquired image is plotted on a plane. FIG. 6B is a diagram showing an example of an approximate curve of a point cloud in which the RG light intensity of each pixel of an acquired image is plotted on a plane. FIG. 7 is a diagram showing an example of a two-dimensional scatter diagram acquired based on the RGB light intensity of each pixel of an acquired image.

[0026] In the first embodiment, the light intensity of red light (hereinafter referred to as "R light intensity"), the light intensity of green light (hereinafter referred to as "G light intensity"), and the light intensity of blue light (hereinafter referred to as "B light intensity") for each pixel are obtained from the acquired image of a plant leaf, and control processing is performed.

[0027] <Image acquisition process> An image acquisition step is performed by the image acquisition unit 10 to acquire images of plant leaves. In FIG. 2, the leaf image acquisition portion is shown surrounded by a rectangle. Any image capture device, including a commercially available camera or a camera provided in a mobile terminal, can be used as the image acquisition unit 10. Leaves illuminated by natural light may be photographed, or leaves illuminated by white light from a light source may be photographed. When a light source is used, it is preferable to use a surface light source.

[0028] Next, the light information acquiring unit 20 of the control unit 80 performs a light information acquiring step of acquiring the R light intensity, the G light intensity, and the B light intensity of each pixel based on the image of the leaf region (see FIG. 2) acquired by the image acquiring unit 10. This allows data on the R light intensity, the G light intensity, and the B light intensity of each pixel of the leaf image to be obtained.

[0029] <Scatter plot acquisition process> The inventors have found, through repeated testing and analysis, that when the R light intensity, G light intensity, and B light intensity of each pixel are plotted in a three-dimensional space with the R axis, the G axis, and the B axis as the three axes, at least a part of the point cloud corresponding to each pixel is distributed in a sheet-like shape. Figure 3 is a diagram of the sheet-like point cloud as viewed from a direction opposite to the sheet surface, and Figure 4 is a diagram of the sheet-like point cloud as viewed from a direction along the sheet surface. That is, Figures 3 and 4 are diagrams as viewed from directions that are approximately perpendicular to each other.

[0030] As is clear from Figures 3 and 4, the point cloud is distributed to show a sheet shape standing on the RG plane. In the illustrated example, the sheet-like point cloud is distributed extending in a direction approximately perpendicular to the RG plane. However, this is not limited to this, and the sheet-like point cloud may be slightly inclined compared to the illustrated example. The sheet-like point cloud may have a certain thickness and may be curved, wavy, etc.

[0031] The inventors have found, through repeated testing and analysis, that when the sheet-like point cloud is viewed from a direction substantially perpendicular to the sheet surface, the difference between healthy and unhealthy parts of the leaf is clearly visible. FIG. 3 shows a view from a direction nearly perpendicular to the sheet surface. On the other hand, in a view from a direction along the sheet surface as shown in FIG. 4, the difference between healthy and unhealthy parts of the leaf cannot be grasped. As will be described later, the parts where the point cloud spreads vertically and horizontally and gathers in a planar shape, as indicated by arrow P in FIG. 3, are healthy parts, and the parts where the point cloud stretches out in an elongated shape, as indicated by arrow Q in FIG. 3, are unhealthy yellowed parts.

[0032] Regardless of the initial color difference of the plant leaves, at least a part of the point cloud corresponding to each pixel of the image is distributed in a sheet shape standing on the RG plane, as shown in Figures 3 and 4. For example, green leaves in the initial stage are distributed in a position away from the R axis where the G light intensity value is large on the RG plane. Red leaves in the initial stage are distributed in a position away from the G axis where the R light intensity value is large on the RG plane.

[0033] Therefore, the inventors have found that a two-dimensional scatter diagram that clearly shows the difference between healthy and unhealthy parts of a leaf can be obtained by the following method, without handling a three-dimensional scatter diagram that requires a large amount of data processing. Specifically, a two-dimensional scatter diagram that clearly shows the difference between healthy and unhealthy parts of a leaf can be obtained by a plan view with two axes, the value obtained from the projection of the light intensity of each pixel onto the RG plane and the corresponding B light intensity. Since the point cloud is distributed in a sheet-like state upright on the RG plane, the two-dimensional scatter diagram obtained in this way is a plan view similar to that when viewed from a direction approximately perpendicular to the sheet-like distribution of the point cloud shown in the three-dimensional scatter diagram.

[0034] In the scatter diagram acquisition step, the R light intensity and the G light intensity of each pixel are plotted on the RG plane to obtain an RG plane diagram as shown in FIG. 5. This RG plane diagram is equivalent to an RG projection diagram of the point cloud shown in the three-dimensional scatter diagram. Then, an approximation line or an approximation curve of the point cloud plotted on this RG plane is formed. To obtain the approximation line or the approximation curve, any known linear regression method or nonlinear regression method such as the least squares method can be adopted.

[0035] Then, the scatter diagram acquisition unit 30 plots the values ​​of each point using the obtained approximate line or curve as a gauge and the B light intensity corresponding to the point on a plane to acquire a two-dimensional scatter diagram as shown in Fig. 7. "Using an approximate line or curve as a gauge" will be explained below with reference to the approximate line shown in Fig. 6A and the approximate curve shown in Fig. 6B.

[0036] In Fig. 6A and Fig. 6B, the approximation line and the approximation curve are shown extending from the origin. If the approximation line and the approximation curve do not pass through the origin, the offset can be adjusted to correct them so that they pass through the origin. An example of a value determined using the approximation line or the approximation curve as a gauge is the distance from the origin to each point along the approximation line or the approximation curve. If the coordinates of each point in Fig. 6A and Fig. 6B are X and Y, then in the case of the approximation line shown in Fig. 6A, the value determined using the approximation line as a gauge is X. 2 +Y 2 It can be expressed as the square root of

[0037] However, this is not limited to this. In the case of an approximate straight line, the sum of the R intensity and the G intensity of each point (i.e., X+Y) can be used, or the sum of squares (X 2 +Y 2 In the case of an approximation curve, it can be, for example, the value of a line integral expressed as the distance from the origin. Furthermore, any method relating to variance and distribution, such as the Mahalanobis distance, can be used to determine a value using an approximation line or curve as a gauge.

[0038] As described above, in the scatter diagram acquisition process, the R light intensity and G light intensity of each pixel are plotted on the RG plane, and the value of each point is plotted on the plane using the approximate straight line or curve of the point group as a gauge, and the corresponding B light intensity of each pixel is plotted. In this way, a two-dimensional scatter diagram as shown in FIG. 7 is acquired.

[0039] The two-dimensional scatter diagram shown in Fig. 7 clearly shows the difference between healthy and unhealthy parts of the leaves, similar to the three-dimensional scatter diagram shown in Fig. 3, which shows the sheet-like point cloud from a direction substantially perpendicular to the sheet surface. When dealing with a three-dimensional scatter diagram, for example, a large amount of data processing is required when tilting or rotating the point cloud in three-dimensional space. In this embodiment, a two-dimensional scatter diagram can be obtained with simple control processing that requires less data processing than when dealing with a cubic scatter diagram.

[0040] Furthermore, in the two-dimensional scatter plot obtained in this way, the area on the surface spreading left and right as indicated by the arrow P in Figure 7 indicates the healthy part, and the elongated angular area extending to the right as indicated by the arrow Q indicates the unhealthy part where yellowing has occurred. Even in the early stage when yellowing begins, the angular area extending from the planar area spreading left and right of the point cloud can be confirmed. Therefore, the state of yellowing of the plant can be grasped from the early stage by using the two-dimensional scatter plot.

[0041] As will be described later, the elongated, angular region indicated by arrow Q tends to have a specific shape depending on the pathogen that has infected it, and the shape can also be used to identify the pathogen that caused the yellowing.

[0042] As described above, the inventors have discovered that at least a portion of the points shown in the three-dimensional scatter plot are distributed in a sheet-like manner standing up from the RG plane, and the following is thought to be the cause of this.

[0043] In the initial state, the distribution of each dot in the image of the plant leaf is not scattered, and as time passes, yellowing areas appear, but each dot in the captured image does not reverse in either direction of the RGB axis, but changes in a certain direction. Therefore, each dot generally draws a straight or curved trajectory, and the direction of change of each dot tends to be the same. For this reason, at least a part of the dot group shown in the three-dimensional scatter diagram is considered to be distributed in a sheet shape.

[0044] For the same leaf, even over time, a sheet-like distribution of points on the same RG plane will be obtained. Therefore, without creating a three-dimensional scatter diagram using three-dimensional data, by creating a two-dimensional scatter diagram with the values ​​obtained from the approximate straight line or approximate curve of the points plotted on the RG plane and the B light intensity as the two axes, as described above, it is possible to grasp the changes over time between healthy and unhealthy parts of the leaf.

[0045] In this way, since there is no need to process huge amounts of data and display and handle three-dimensional data, the processing time can be significantly shortened and the memory capacity required for processing can be reduced.In addition, by using two-dimensional dispersion images, which clearly show the difference between healthy and unhealthy parts, users can distinguish healthy and unhealthy parts visually without the need for black box analysis using AI, or they can distinguish healthy and unhealthy parts using a simpler algorithm.

[0046] Discoloration caused by natural phenomena has at least one or more stages and one or more characteristic parts, and when a particular characteristic part is at a particular discoloration stage, the color before and after discoloration is fixed, and the direction of the color change is considered to be the same. Taking a leaf that is green in the early stages as an example, there are two stages mentioned above: the stage where it turns from green to yellow, and the stage where it turns from yellow to withering and dying. In addition, there are two types of specific parts: the leaf pulp part, which includes yellowing, and the leaf vein part. Furthermore, perforations may occur as specific parts due to withering or insect damage.

[0047] For leaves that are dead and yellowed, a three-dimensional scatter plot may give a sheet-like distribution of points for each of the four clusters: yellowed mesophyll, vein, dead mesophyll, and dead vein. In this case, two-dimensional scatter plots for each cluster can be obtained. These two-dimensional scatter plots can be evaluated individually, or some characteristic relationship can be found between the two-dimensional scatter plots for evaluation.

[0048] Depending on the condition of the leaf, the mesophyll and vein parts may not show distinct sheet-like distributions, and the point cloud distributed in a single sheet may tend to have a slightly larger variation in the thickness direction of the sheet. To grasp the condition of the plant leaves more accurately, it is preferable that the point cloud distributed in a sheet-like manner shown in the three-dimensional scatter plot has less variation in the thickness direction of the sheet. Therefore, the vein part is identified from the captured image using image software, and the light intensity data of the vein part is removed as necessary, thereby obtaining a sheet-like distribution of the point cloud with less variation in the thickness direction.

[0049] For this reason, it is preferable to process the image obtained in the image acquisition step so that the veins of the plant are clear and uniform, and then carry out the light information acquisition step. This makes it possible to remove the veins, for example, by binarization or the like.

[0050] By obtaining images in which the veins of a plant's leaves are clearly visible and uniform, it becomes possible to distinguish and analyze the veins from other parts of the leaf, such as the leaf pulp, and thus to grasp the state of yellowing more accurately.

[0051] Furthermore, in the scatter diagram acquisition step, it is preferable to acquire the two-dimensional scatter diagram in a state where at least one of the mesophyll portion, discolored portion, dead portion, vein portion, and perforated portion of the plant leaves is removed, thereby making it possible to obtain a two-dimensional scatter diagram that allows a more accurate understanding of the state of yellowing.

[0052] <Yellowing information acquisition process> Even when yellowing appears to be the same to the naked eye, by using the two-dimensional scatter diagram, it is possible to identify whether the yellowing is natural or caused by a specific disease or injury. Next, the yellowing information acquisition process performed by the yellowing information acquisition unit 40 will be described with reference to Figs. 8A to 8D. Figs. 8A to 8D are each a diagram showing an example of a two-dimensional scatter diagram of the yellowing area of ​​the leaves of a plant infected with a pathogen.

[0053] FIG. 8A shows an example where the shape of the horn-like extension of the etiolated area is distorted. FIG. 8B shows an example where two horn-like extensions appear in the etiolated area. FIG. 8C shows an example where the tip of the horn-like extension of the etiolated area has a vertically elongated shape. FIG. 8D shows an example where the tip of the horn-like extension of the etiolated area has a white spot cluster.

[0054] As shown in Figures 8A to 8D, in the yellowing information acquisition process performed by the yellowing information acquisition unit 40, the cause of yellowing can be identified mainly by analyzing the shape of the angular extensions of the yellowed area, but it is also important to identify the cause of yellowing by analyzing the shape of the entire point cloud including other parts.

[0055] To achieve this, it is effective to photograph leaves whose cause of yellowing has been analyzed by another test, obtain a two-dimensional scatter diagram, and use the two-dimensional scatter diagram as a standard two-dimensional scatter diagram to obtain yellowing information. In the yellowing information obtaining step, the cause of yellowing can be easily and reliably identified by comparing the two-dimensional scatter diagram obtained by actually photographing the leaves of a plant with the standard two-dimensional scatter diagram.

[0056] When the determination is made by comparing the shape of the angular extensions of the yellowed areas, there is no need to perform a black box analysis using AI, and the user can easily identify the cause of the yellowing.

[0057] Furthermore, it is also effective to obtain the time series changes of the same leaf as the change in the shape of the dots in the two-dimensional scatter plot. This makes it possible to accurately identify the progress of the yellowing. By accumulating the data of the two-dimensional scatter plot that changes over time and reflects the progress of the yellowing, it is possible to accurately determine the current state of the plant and take prompt action.

[0058] Furthermore, it is also effective to identify the feature values ​​of the two-dimensional scatter diagram using a statistical method or the like. For example, the cause of yellowing can be identified according to a certain standard by a threshold value set based on the accumulated feature value data. Thus, in this embodiment, in the yellowing information acquisition step, the cause and progress of yellowing can be diagnosed based on the shape and feature values ​​of the two-dimensional scatter diagram. This makes it possible to grasp the condition of the plant at an early stage, understand the cause, and realize an appropriate and prompt response.

[0059] In addition, in the yellowing information acquisition step, shape information on the real plane of each point corresponding to a specific cluster in the two-dimensional scatter diagram can also be acquired. Examples of the specific cluster here include a healthy area of ​​the mesophyll portion, a yellowed area of ​​the mesophyll portion, a healthy area of ​​the vein portion, and a yellowed area of ​​the vein portion. This makes it possible to add yellowing information to an actual leaf image as shown in FIG. 2 and notify the user. By acquiring shape information on the real plane of each point corresponding to a specific cluster, it becomes possible to efficiently notify the user of yellowing information in accordance with the convenience of the user. In addition, machine learning of a two-dimensional scatter plot or the shapes on a real plane of each point corresponding to a specific cluster in the two-dimensional scatter plot is also effective in obtaining yellowing information.

[0060] The two-dimensional scatter diagram obtained by the scatter diagram acquisition unit 30 and the yellowing information obtained by the yellowing information acquisition unit 40 can be displayed on the display device 50 to provide feedback to the user. Feedback to the user can be provided not only by display on the display device 50, but also by any known notification means including printing on paper and notifying the yellowing information by voice.

[0061] As described above, the etiolation information acquisition method according to the first embodiment of the present invention includes an image acquisition step of acquiring an image of a plant leaf, a light information acquisition step of acquiring the red light intensity (hereinafter referred to as "R light intensity"), the green light intensity (hereinafter referred to as "G light intensity"), and the blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image, and a scatter plot acquisition step of acquiring a two-dimensional scatter plot with the value of each point as a gauge, using an approximate straight line or curve of a point cloud obtained by plotting the R light intensity and G light intensity of each pixel on an RG plane, and the corresponding B light intensity of each pixel as the two axes. a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; Includes.

[0062] Similarly, the etiolation information acquisition system 100 according to the first embodiment of the present invention, which implements the etiolation information acquisition method according to the first embodiment described above, includes an image acquisition unit 10 that acquires images of plant leaves, a light information acquisition unit 20 that acquires the red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image acquired by the image acquisition unit 10, a scatter plot acquisition unit 30 that acquires a two-dimensional scatter plot with the value of each point as a gauge, using an approximation line or curve of a point cloud obtained by plotting the R light intensity and G light intensity of each pixel on an RG plane, and the corresponding B light intensity of each pixel as the two axes, and an etiolation information acquisition unit 40 that acquires etiolation information of the plant based on the two-dimensional scatter plot.

[0063] The etiolation information acquisition system 100 according to the first embodiment of the present invention does not require a light source for irradiating excitation light, and can acquire two-dimensional scatter diagrams and etiolation information with a simple configuration of an image acquisition unit 10 for photographing plant leaves and a control unit 80. In addition, the control unit 80 can obtain a two-dimensional dispersion image in which the difference between healthy and unhealthy parts of the leaves is clearly shown without requiring a large amount of control processing for forming and analyzing three-dimensional images. In the early stage of etiolation, healthy areas and etiolated unhealthy areas are mixed together and difficult to distinguish from the image of the leaves alone. However, in this embodiment, by acquiring a two-dimensional dispersion image, it is possible to specify the state of etiolation of the plant from the early stage, and various etiolation information as described above can be obtained. Note that the two axes used to acquire the two-dimensional dispersion diagram may not be orthogonal.

[0064] As a result, it is possible to provide a method for acquiring information about etiolation and a system for acquiring information about etiolation 100 that can specify the state of etiolation of a plant from an early stage with a simple configuration.

[0065] (Method of acquiring yellowing information according to the second embodiment) In the first embodiment, a two-dimensional scatter diagram is obtained in which the R light intensity and G light intensity of each pixel are plotted on the RG plane, and the value of each point is measured as a gauge using an approximate straight line or curve of a group of points, and the corresponding B light intensity of each pixel is measured as two axes. In other words, a two-dimensional scatter diagram viewed from a direction approximately perpendicular to the approximate straight line shown on the RG plane shown in FIG. 5 is obtained.

[0066] The approximation line shown in FIG. 5 extends obliquely to the R axis and the G axis, so when viewed from the R axis direction or the G axis direction, the approximation line is viewed obliquely. However, even if a two-dimensional scatter diagram viewed from the R axis direction or the G axis direction, which is a diagonal view of this sheet-like distribution, is obtained, it is possible to distinguish healthy parts of the leaves from unhealthy parts. Regardless of the angle of the approximation line to the R axis and the G axis, it is possible to distinguish healthy parts of the leaves from unhealthy parts in the two-dimensional scatter diagram viewed from at least one of the R axis direction and the G axis direction. However, the accuracy is inferior to that of the first embodiment viewed from a direction approximately perpendicular to the approximation line shown on the RG plane.

[0067] In that case, in the light information acquisition step, a two-dimensional scatter diagram can be formed simply by taking the R light intensity or G light intensity of each pixel as one axis and the B light intensity as the other axis.

[0068] As described above, the etiolation information acquisition method according to the second embodiment of the present invention includes an image acquisition step of acquiring an image of a plant leaf, a light information acquisition step of acquiring the red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image, a scatter plot acquisition step of acquiring a two-dimensional scatter plot with the R light intensity or G light intensity and the B light intensity of each pixel as the two axes, and an etiolation information acquisition step of acquiring plant etiolation information based on the two-dimensional scatter plot.

[0069] Similarly, the etiolation information acquisition system 100 according to the second embodiment of the present invention, which implements the etiolation information acquisition method according to the second embodiment described above, includes an image acquisition unit 10 that acquires images of plant leaves, a light information acquisition unit 20 that acquires the red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image acquired by the image acquisition unit, a scatter plot acquisition unit 30 that acquires a two-dimensional scatter plot with the R light intensity or G light intensity and the B light intensity of each pixel as the two axes, and an etiolation information acquisition unit 40 that acquires plant etiolation information based on the two-dimensional scatter plot.

[0070] The yellowing information acquisition method and the yellowing information acquisition system 100 according to the second embodiment are particularly effective in cases where high speed and large volume processing is desired.

[0071] (Method of acquiring yellowing information according to the third embodiment) In the above first and second embodiments, RGB light intensity is used as light information, but H intensity (hue), S intensity (saturation) and V intensity (brightness) can also be used instead of RGB light intensity. Next, a method for acquiring yellowing information according to a third embodiment of the present invention using HSV intensity will be described with reference to Fig. 9. Fig. 9 is a diagram showing an example of a three-dimensional scatter diagram in which the HSV intensity of each pixel of an image of a plant leaf is plotted in a three-dimensional space.

[0072] As is clear from Fig. 9, even when HSV intensity is used, a sheet-like distribution of points standing on the HV plane is obtained, as in the case of using RGB light intensity shown in Fig. 3. In Fig. 9, too, the area on the surface extending to the left and right indicated by arrow P indicates a healthy part, and the elongated angular area extending to the right indicated by arrow Q indicates an unhealthy part where yellowing has occurred.

[0073] Therefore, a two-dimensional scatter diagram can be obtained with the value of each point, which is the approximate straight line or curve of the point group obtained by plotting the H intensity and V intensity of each pixel on the HV plane, as the gauge, and the corresponding S intensity of each pixel as the two axes. In other words, by replacing the RGB light intensity in the first embodiment with the HV intensity and the B light intensity with the S intensity, an analysis similar to that in the first embodiment can be performed.

[0074] As described above, the yellowing information acquisition method according to the third embodiment of the present invention includes an image acquisition step of acquiring an image of a plant leaf, a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image, a scatter plot acquisition step of acquiring a two-dimensional scatter plot with the values ​​of each point as a gauge, using an approximate straight line or curve of a point cloud obtained by plotting the H intensity and V intensity of each pixel on an HV plane, and the corresponding S intensity of each pixel as the two axes, and a yellowing information acquisition step of acquiring plant yellowing information based on the two-dimensional scatter plot.

[0075] Similarly, the etiolation information acquisition system 100 according to the third embodiment of the present invention, which implements the etiolation information acquisition method according to the third embodiment described above, includes an image acquisition unit 10 that acquires images of plant leaves, a light information acquisition unit 20 that acquires the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image acquired by the image acquisition unit 10, a scatter plot acquisition unit 30 that acquires a two-dimensional scatter plot with the value of each point as a gauge, using an approximation straight line or curve of a point cloud obtained by plotting the H intensity and V intensity of each pixel on an HV plane, and the corresponding S intensity of each pixel as the two axes, and an etiolation information acquisition unit 40 that acquires plant etiolation information based on the two-dimensional scatter plot.

[0076] As a result, in the third embodiment using HSV intensity as well, as in the first embodiment using RGB light intensity, it is possible to provide a etiolation information acquisition method and an etiolation information acquisition system 100 that can identify the etiolation state of a plant from an early stage with a simple configuration.

[0077] (Yellowing information acquisition method according to the fourth embodiment) Even when HSV intensity is used, similarly to the above third embodiment, even if a two-dimensional scatter diagram is obtained as viewed from the H-axis or V-axis direction, which is a sheet-like distribution as shown in Fig. 9 viewed from an oblique direction, it is possible to distinguish healthy and unhealthy parts of the leaves. Regardless of the angle of the approximation line with respect to the H-axis and V-axis, it is possible to distinguish healthy and unhealthy parts of the leaves in a two-dimensional scatter diagram viewed from at least one of the H-axis and V-axis directions. However, the accuracy is inferior to that of the third embodiment, which is viewed from a direction approximately perpendicular to the approximation line shown on the HV plane.

[0078] Therefore, in the yellowing information acquisition method according to the fourth embodiment of the present invention, in the scatter plot acquisition step, a two-dimensional scatter plot can be simply formed by using the H intensity or V intensity of each pixel as one axis and the S intensity as the other axis.

[0079] As described above, the yellowing information acquisition method according to the fourth embodiment of the present invention includes an image acquisition step of acquiring an image of a plant leaf, a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image, a scatter plot acquisition step of acquiring a two-dimensional scatter plot with the H intensity or V intensity and the S intensity of each pixel as the two axes, and a yellowing information acquisition step of acquiring plant yellowing information based on the two-dimensional scatter plot.

[0080] Similarly, the etiolation information acquisition system 100 according to the fourth embodiment of the present invention, which implements the etiolation information acquisition method according to the above-mentioned fourth embodiment, includes an image acquisition unit 10 that acquires images of plant leaves, a light information acquisition unit 20 that acquires the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image acquired by the image acquisition unit 10, a scatter plot acquisition unit 30 that acquires a two-dimensional scatter plot with the H intensity or V intensity and the S intensity of each pixel as the two axes, and a etiolation information acquisition unit 40 that acquires plant etiolation information based on the two-dimensional scatter plot.

[0081] The yellowing information acquisition method and the yellowing information acquisition system 100 according to the fourth embodiment are particularly effective in cases where high speed and large volume processing is desired.

[0082] In any of the first to fourth embodiments, evaluation is not only performed for each axis of RGB or HSV, but also highly sensitive evaluation can be performed including how the respective quantities are related. A plurality of elements (RGB or HSV) can be accurately evaluated including their respective relationships. Furthermore, in any of the first to fourth embodiments, the two axes used to obtain a two-dimensional scatter diagram may not be orthogonal.

[0083] (Methods for testing plants for diseases) In the above-described etiolation information acquisition methods according to the first to fourth embodiments, plant etiolation information is acquired using the etiolation information acquisition system 100. However, based on the two-dimensional scatter diagram obtained by such an etiolation information acquisition system 100, various other pieces of information related to plant diseases can also be obtained from the plant etiolation information. In other words, the above-described etiolation information acquisition system 100 can also be called a plant disease information acquisition system 100.

[0084] For example, information about citrus greening can be obtained by photographing the leaves of citrus plants and then using a two-dimensional scatter diagram obtained from the image, allowing pre-screening before detailed testing for citrus greening.

[0085] Next, an overview of a plant disease inspection method using the plant disease-related information acquisition system 100 will be described with reference to Fig. 10. Fig. 10 is a flowchart showing the plant disease inspection method. In the flowchart shown in Fig. 10, a selection process S1 for pre-screening before detailed inspection is performed, and then an inspection process S2 for detailed inspection is performed.

[0086] <Selection process> Specifically, the selection process S1 includes an image acquisition step S10, a light information acquisition step S12, a scatter diagram acquisition step S14, an information acquisition step S16, and a selection step S18, in that order. The sorting process S1 can be carried out in a similar manner to any of the yellowing information acquisition methods according to the first to fourth embodiments described above. First, a case in which the sorting process S1 is carried out in a similar manner to the first embodiment will be described.

[0087] First, in an image acquisition step S10, a leaf of a citrus plant is photographed to acquire an image of the leaf. Next, in a light information acquisition step S12, the red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel are acquired from the acquired image. Then, in a scatter diagram acquisition step, a two-dimensional scatter diagram is acquired with the value of each point, which is a gauge of an approximate straight line or curve of a point group obtained by plotting the R light intensity and G light intensity of each pixel on an RG plane, and the corresponding B light intensity of each pixel as two axes.

[0088] Then, in an information acquisition step S16, information about a plant disease is acquired based on the two-dimensional scatter diagram. Here, information about citrus greening disease is acquired. In a selection step S18, leaves to be subjected to PCR testing are selected based on the acquired information. As described above, the selection process S1 is performed in a manner similar to the yellowing information acquisition method according to the first embodiment described above, except for the selection step S18.

[0089] As described above, when the selection process S1 is carried out in a manner similar to that of the first embodiment, the selection process S1 is an image acquisition step S10 for acquiring an image of a plant leaf; a light information acquisition step S12 of acquiring the red light intensity (hereinafter referred to as "R light intensity"), the green light intensity (hereinafter referred to as "G light intensity"), and the blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step S14 for acquiring a two-dimensional scatter diagram with the values ​​of each point on the two axes being the values ​​of the corresponding B light intensity of each pixel, and the approximation line or curve of the point group obtained by plotting the R light intensity and the G light intensity of each pixel on the R-G plane as a gauge; an information acquisition step S16 of acquiring information about plant diseases based on the two-dimensional scatter diagram; A sorting step S18 of sorting leaves to be subjected to PCR testing based on the acquired information; Includes.

[0090] Similarly, when the selection process S1 is carried out in a manner similar to that of the second embodiment, the selection process S1 is an image acquisition step S10 for acquiring an image of a plant leaf; a light information acquisition step S12 of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter diagram acquisition step S14 for acquiring a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding S intensity of each pixel, and the approximation line or curve of the point group obtained by plotting the H intensity and V intensity of each pixel on the HV plane as a gauge; an information acquisition step S16 of acquiring information about plant diseases based on the two-dimensional scatter diagram; A sorting step S18 of sorting leaves to be subjected to PCR testing based on the acquired information; Includes.

[0091] Similarly, when the selection process S1 is carried out in a manner similar to that of the third embodiment, the selection process S1 is an image acquisition step S10 for acquiring an image of a plant leaf; a light information acquisition step S12 of acquiring the red light intensity (hereinafter referred to as "R light intensity"), the green light intensity (hereinafter referred to as "G light intensity"), and the blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step S14 of acquiring a two-dimensional scatter diagram with the R light intensity or G light intensity and the B light intensity of each pixel as two axes; an information acquisition step S16 of acquiring information about plant diseases based on the two-dimensional scatter diagram; A sorting step S18 of sorting leaves to be subjected to PCR testing based on the acquired information; Includes.

[0092] Similarly, when the selection process S1 is carried out in a manner similar to that of the fourth embodiment, the selection process S1 is an image acquisition step S10 for acquiring an image of a plant leaf; a light information acquisition step S12 of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter plot acquisition step S14 for acquiring a two-dimensional scatter plot having the H intensity or V intensity and the S intensity of each pixel as two axes; an information acquisition step S16 of acquiring information about plant diseases based on the two-dimensional scatter diagram; A sorting step S18 of sorting leaves to be subjected to PCR testing based on the acquired information; Includes.

[0093] By using the above-described sorting process S1, information about plant diseases (e.g., citrus greening) that cannot be detected by visual inspection can be obtained, and leaves that should be subjected to detailed testing such as PCR testing can be accurately selected.

[0094] However, the selection process S1 is not limited to the method corresponding to the above-mentioned first to fourth embodiments. For example, in the selection process S1, a red image (R image) and a blue image (B image) may be acquired from an image of a plant leaf, and a difference image representing the difference between the acquired R image and B image may be acquired. The leaves to be subjected to PCR testing can be selected based on the shape (e.g., width) of the histogram of the acquired difference image.

[0095] <Inspection process> In the inspection process S2, a PCR test is performed on the leaves selected in the selection process S1. This makes it possible to accurately test whether or not the plant is infected with a plant disease (citrus greening) and the extent of the disease. It also makes it possible to quickly and accurately determine a treatment method for the infected plant. In the selection process S1, only leaves that are likely to be infected with the plant disease (citrus greening) are selected and subjected to a PCR test, thereby achieving efficient testing.

[0096] As described above, the plant disease inspection method of this embodiment includes a sorting process S1 in which a two-dimensional image containing optical information for each pixel of an image obtained by photographing a plant leaf is generated and leaves to be inspected are selected based on the two-dimensional image, and an inspection process S2 in which PCR testing is performed on the leaves selected in the sorting process S1.

[0097] This allows the selection process S1, which involves acquiring information about plant diseases, to more efficiently test for plant diseases.

[0098] In particular, when the plant disease being inspected is citrus greening, accurate inspection of the plant disease can be achieved based on knowledge gained from the analysis of various two-dimensional maps.

[0099] Furthermore, by analyzing the two-dimensional map, it is expected that the selection process S1 using images of plant leaves can be effectively applied to various plant diseases other than citrus greening.

[0100] (General Description) (Section 1) a sorting process for generating a two-dimensional image including light information of each pixel of an image obtained by photographing a plant leaf, and sorting a leaf to be inspected based on the two-dimensional image; An inspection process for performing a PCR test on the leaves selected in the selection process; A method for testing plants for diseases, comprising: (Section 2) Item 2. The method for testing a plant disease according to Item 1, wherein the plant disease to be tested is citrus greening disease. (Section 3) The screening process comprises: an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring the red light intensity (hereinafter referred to as "R light intensity"), the green light intensity (hereinafter referred to as "G light intensity"), and the blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding B light intensity of each pixel, and the approximation line or curve of the point group obtained by plotting the R light intensity and the G light intensity of each pixel on the R-G plane as a gauge; an information acquisition step of acquiring information about a plant disease based on the two-dimensional scatter diagram; A sorting process for selecting leaves for PCR testing based on the acquired information; Item 3. The method for testing a plant for a disease according to Item 1 or 2. (Section 4) The screening process comprises: an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter plot acquisition step of acquiring a two-dimensional scatter plot in which the value of each point, which is an approximate straight line or curve of a point group obtained by plotting the H intensity and V intensity of each pixel on an HV plane, and the corresponding S intensity of each pixel are used as two axes; an information acquisition step of acquiring information about a plant disease based on the two-dimensional scatter diagram; A sorting process for selecting leaves for PCR testing based on the acquired information; Item 3. The method for testing a plant for a disease according to Item 1 or 2. (Section 5) The screening process comprises: an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring the red light intensity (hereinafter referred to as "R light intensity"), the green light intensity (hereinafter referred to as "G light intensity"), and the blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the R light intensity or G light intensity and the B light intensity of each pixel as two axes; an information acquisition step of acquiring information about a plant disease based on the two-dimensional scatter diagram; A sorting process for selecting leaves for PCR testing based on the acquired information; Item 3. The method for testing a plant for a disease according to Item 1 or 2. (Section 6) The screening process comprises: an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter plot acquisition step of acquiring a two-dimensional scatter plot having H intensity or V intensity and S intensity of each pixel as two axes; an information acquisition step of acquiring information about a plant disease based on the two-dimensional scatter diagram; A sorting process for selecting leaves for PCR testing based on the acquired information; Item 3. The method for testing a plant for a disease according to Item 1 or 2.

[0101] (Section 7) an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring the red light intensity (hereinafter referred to as "R light intensity"), the green light intensity (hereinafter referred to as "G light intensity"), and the blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding B light intensity of each pixel, and the approximation line or curve of the point group obtained by plotting the R light intensity and the G light intensity of each pixel on the R-G plane as a gauge; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The method for acquiring yellowing information includes: (Section 8) an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter plot acquisition step of acquiring a two-dimensional scatter plot in which the value of each point, which is an approximate straight line or curve of a point group obtained by plotting the H intensity and V intensity of each pixel on an HV plane, and the corresponding S intensity of each pixel are used as two axes; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The method for acquiring yellowing information includes: (Section 9) an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring the red light intensity (hereinafter referred to as "R light intensity"), the green light intensity (hereinafter referred to as "G light intensity"), and the blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the R light intensity or G light intensity and the B light intensity of each pixel as two axes; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The method for acquiring yellowing information includes: (Section 10) an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter plot acquisition step of acquiring a two-dimensional scatter plot having H intensity or V intensity and S intensity of each pixel as two axes; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The method for acquiring yellowing information includes: (Section 11) Item 11. The method for acquiring information on etiolation according to any one of items 7 to 10, further comprising processing the image obtained in the image acquiring step so that the veins of the plant are clear and uniform, and then carrying out the light information acquiring step. (Section 12) Item 12. The method for acquiring information on yellowing according to any one of items 7 to 11, wherein in the scatter diagram acquisition step, the two-dimensional scatter diagram is acquired in a state in which at least one of mesophyll parts, discolored parts, dead parts, vein parts, and perforated parts on the plant leaves is removed. (Section 13) Item 13. The method for acquiring information on yellowing according to any one of items 7 to 12, wherein in the yellowing information acquiring step, a cause and a degree of progress of yellowing are diagnosed based on a shape and feature values ​​of the two-dimensional scatter diagram. (Section 14) Item 14. The method for acquiring information on yellowing according to any one of items 7 to 13, wherein in the yellowing information acquisition step, shape information on a real plane of each point corresponding to a specific cluster in the two-dimensional scatter diagram is acquired.

[0102] (Section 15) an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit that acquires a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding B light intensity of each pixel, and the approximation line or curve of the point group obtained by plotting the R light intensity and the G light intensity of each pixel on the R / G plane as a gauge; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system includes: (Section 16) an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit that acquires a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding S intensity of each pixel, and the value of each point being an approximate straight line or curve of a point group obtained by plotting the H intensity and V intensity of each pixel on an HV plane; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system includes: (Section 17) an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit that acquires a two-dimensional scatter diagram with the R light intensity or G light intensity and the B light intensity of each pixel as two axes; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system includes: (Section 18) an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit for acquiring a two-dimensional scatter diagram with the H intensity or V intensity and the S intensity of each pixel as two axes; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system includes: (Section 19) Item 19. The yellowing information acquisition system according to any one of items 15 to 18, wherein the image obtained by the image acquisition unit is processed so that the veins of the plant are clear and uniform, and then processing is performed by the light information acquisition unit. (Section 20) 20. The yellowing information acquisition system according to any one of items 15 to 19, wherein the scatter diagram acquisition unit acquires the two-dimensional scatter diagram in a state in which at least one of mesophyll parts, discolored parts, dead parts, vein parts, and perforated parts on the plant leaves is removed. (Section 21) Item 21. The yellowing information acquisition system according to any one of items 15 to 20, wherein the yellowing information acquisition unit diagnoses a cause and a degree of progress of the yellowing based on the shape and feature values ​​of the two-dimensional scatter diagram. (Section 22) Item 22. The yellowing information acquisition system according to any one of items 15 to 21, wherein the yellowing information acquisition unit acquires shape information on a real plane of each point corresponding to a specific cluster in the two-dimensional scatter diagram.

[0103] Although the embodiments and modes of implementation of the present invention have been described, the disclosed contents may vary in details of the configuration, and changes in the combination and order of elements in the embodiments and modes of implementation may be realized without departing from the scope and spirit of the claimed invention. [Explanation of symbols]

[0104] 10 Image acquisition section 20 Optical information acquisition section 30 Scatter Plot Special Section 40 Yellowing Information Acquisition Department 50 Display device 70 Mobile Devices 80 Control section 90 Yellowing information acquisition device 100 Yellowing information acquisition system (system for acquiring information on plant diseases)

Claims

1. a sorting process for generating a two-dimensional image including light information of each pixel of an image obtained by photographing a plant leaf, and sorting a leaf to be inspected based on the two-dimensional image; An inspection process for performing a PCR test on the leaves selected in the selection process; A method for testing plants for diseases, comprising:

2. 2. The method for testing a plant for a disease according to claim 1, wherein the plant disease to be tested is citrus greening disease.

3. The screening process comprises: an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding B light intensity of each pixel, and the approximation line or curve of the point group obtained by plotting the R light intensity and the G light intensity of each pixel on the RG plane as a gauge; an information acquisition step of acquiring information about a plant disease based on the two-dimensional scatter diagram; A selection step of selecting leaves to be subjected to PCR testing based on the acquired information; The method for testing a plant for a disease according to claim 1 or 2, comprising:

4. The screening process comprises: an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding S intensity of each pixel, and the value of each point being gauged as an approximation line or curve of a group of points obtained by plotting the H intensity and the V intensity of each pixel on an HV plane; an information acquisition step of acquiring information about a plant disease based on the two-dimensional scatter diagram; A selection step of selecting leaves to be subjected to PCR testing based on the acquired information; The method for testing a plant for a disease according to claim 1 or 2, comprising:

5. The screening process comprises: an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the R light intensity or G light intensity and the B light intensity of each pixel as two axes; an information acquisition step of acquiring information about a plant disease based on the two-dimensional scatter diagram; A selection step of selecting leaves to be subjected to PCR testing based on the acquired information; The method for testing a plant for a disease according to claim 1 or 2, comprising:

6. The screening process comprises: an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter diagram acquisition step of acquiring a two-dimensional scatter diagram having H intensity or V intensity and S intensity of each pixel as two axes; an information acquisition step of acquiring information about a plant disease based on the two-dimensional scatter diagram; A selection step of selecting leaves to be subjected to PCR testing based on the acquired information; The method for testing a plant for a disease according to claim 1 or 2, comprising:

7. an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding B light intensity of each pixel, and the approximation line or curve of the point group obtained by plotting the R light intensity and the G light intensity of each pixel on the RG plane as a gauge; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The method for acquiring yellowing information includes:

8. an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the value of each point on the two axes being the value of the corresponding S intensity of each pixel, and the value of each point being gauged as an approximation line or curve of a group of points obtained by plotting the H intensity and the V intensity of each pixel on an HV plane; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The method for acquiring yellowing information includes:

9. an image acquisition step of acquiring an image of a plant leaf; a light information acquiring step of acquiring red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image; a scatter diagram acquisition step of acquiring a two-dimensional scatter diagram with the R light intensity or G light intensity and the B light intensity of each pixel as two axes; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The method for acquiring yellowing information includes:

10. an image acquisition step of acquiring an image of a plant leaf; a light information acquisition step of acquiring the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image; A scatter diagram acquisition step of acquiring a two-dimensional scatter diagram having H intensity or V intensity and S intensity of each pixel as two axes; a step of acquiring information on the etiolation of a plant based on the two-dimensional scatter diagram; The method for acquiring yellowing information includes:

11. 11. The method for acquiring information on etiolation according to claim 7, further comprising processing the image obtained in the image acquiring step so that leaf veins of the plant are clear and uniform, and then carrying out the light information acquiring step.

12. 11. The method for acquiring information on yellowing according to claim 7, wherein in the scatter diagram acquisition step, the two-dimensional scatter diagram is acquired in a state in which at least one of mesophyll portions, discolored portions, dead portions, vein portions, and perforated portions on the plant leaves is removed.

13. The yellowing information acquiring method according to claim 7 , wherein in the yellowing information acquiring step, a cause and a degree of progress of the yellowing are diagnosed based on a shape and feature values ​​of the two-dimensional scatter diagram.

14. The yellowing information acquisition method according to claim 7 , wherein in the yellowing information acquisition step, shape information on a real plane of each point corresponding to a specific cluster in the two-dimensional scatter diagram is acquired.

15. an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit that acquires a two-dimensional scatter diagram with the value of each point, which is an approximate straight line or curve of a point group obtained by plotting the R light intensity and the G light intensity of each pixel on an RG plane, as a gauge, and the corresponding B light intensity of each pixel as two axes; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system includes:

16. an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit that acquires a two-dimensional scatter diagram with the value of each point, which is an approximate straight line or curve of a point group obtained by plotting the H intensity and V intensity of each pixel on an HV plane, as a gauge, and the corresponding S intensity of each pixel as two axes; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system includes:

17. an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires red light intensity (hereinafter referred to as "R light intensity"), green light intensity (hereinafter referred to as "G light intensity"), and blue light intensity (hereinafter referred to as "B light intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit that acquires a two-dimensional scatter diagram with the R light intensity or G light intensity and the B light intensity of each pixel as two axes; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system includes:

18. an image acquisition unit that acquires an image of a plant leaf; a light information acquisition unit that acquires the hue (hereinafter referred to as "H intensity"), saturation (hereinafter referred to as "S intensity"), and lightness (hereinafter referred to as "V intensity") of each pixel from the image acquired by the image acquisition unit; a scatter diagram acquisition unit for acquiring a two-dimensional scatter diagram with the H intensity or V intensity and the S intensity of each pixel as two axes; a yellowing information acquisition unit that acquires yellowing information of a plant based on the two-dimensional scatter diagram; The yellowing information acquisition system includes:

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