System and methods for assessing plant tissue growth status

Abstract

This invention relates to a system and method for assessing plant tissue growth status. Addressing the problem that insufficient accuracy in acquiring plant growth images leads to technicians being unable to detect abnormal plant growth in a timely manner or making incorrect judgments, the system provided by this invention includes: a detection module for detecting a first light intensity in the plant's environment; and a control module communicatively connected to the detection module. When the detection module detects that the first light intensity of the environment exceeds or falls below a preset light intensity range that can objectively reproduce the plant tissue growth status, the control module adjusts the first light intensity of the environment to the preset light intensity range and acquires a first image of the plant. The control module is configured to: determine the clarity of the first image and adjust the light intensity of the plant's environment, thereby obtaining a second image that can be used for feature data extraction.

Description

Technical Field

[0001] This invention relates to the field of plant monitoring technology, and in particular to a system and method for assessing the growth status of plant tissues. Background Technology

[0002] In agricultural production, crop diseases occur frequently, and their occurrence and spread are extremely rapid. If pests and diseases appear in a region and measures are not taken in time, they will spread over a large area in a short period of time, leading to a significant reduction in crop yield or even complete crop failure. Therefore, monitoring the growth status of plants in agricultural production is an essential process. Current monitoring methods typically rely on manual identification and the acquisition of plant images through remote sensing technology to determine the plant's growth status.

[0003] On the one hand, agricultural crops are usually numerous and cover a wide area. Manually identifying whether plants are affected by pests and diseases is time-consuming and labor-intensive, easily leading to eye fatigue and low efficiency. Furthermore, some small lesions or color changes are easily overlooked. If appropriate measures are not taken to control pests and diseases in the early stages, their rapid spread can lead to large-scale plant infection and huge losses. On the other hand, although remote sensing technology, such as satellites or drones, is simple and quick to use to collect images of plants and determine their growth status, the accuracy of the brightness, color, and clarity of the collected images can vary depending on the weather or the time of day due to factors such as the direction of sunlight and cloud scattering. Therefore, the accuracy of subsequent image analysis cannot be guaranteed.

[0004] On the other hand, the current image acquisition angle is usually from the top of the plant towards the base. This shooting angle is singular, and the spatial positions of the plant, the sun, and the measuring device are fixed. A single shooting angle cannot observe the growth status of each plant, and when the leaves of the plant are bent, tilted, overlapped, or twisted, it will interfere with the image, resulting in inaccurate results during analysis.

[0005] Furthermore, existing plant tissue growth status assessment systems primarily rely on image acquisition of plant features to generate corresponding comparison results. While multi-dimensional or multi-angle information acquisition increases the accuracy of the assessment results, the accuracy of the initial data acquisition is often overlooked, and its impact on the assessment results is not considered. For example, when the assessment system needs to collect leaf size data to determine the plant's growth status, excessive sunlight can cause halos to appear on the edges of some leaves during imaging, resulting in a smaller perceived leaf area than its actual area. Similarly, when the system needs to collect leaf color data to determine if the plant is diseased or infested, the low intensity and colored red and blue light supplied to the plants in the greenhouse can affect the color of the acquired image, causing actual yellow patches to appear brown in the acquired image, leading to inaccurate assessment results.

[0006] Current research on plant growth status assessment systems typically focuses more on assessment methods while neglecting the accuracy of the collected target plant images. In other words, the accuracy of the initial data collection cannot be guaranteed. When the colors of the collected plant growth images become blurry and inaccurate due to factors such as lighting and shooting angle, it will affect the accuracy of the system's assessment of plant growth status. This will prevent technicians from detecting abnormal plant growth in a timely manner or make incorrect judgments, thus hindering timely and effective intervention and ultimately reducing plant yield.

[0007] With rising market demand, traditional breeding methods can no longer meet current needs. To quickly obtain the required crop varieties and yields, it is necessary to minimize or avoid unexpected events during crop cultivation, such as the failure to promptly detect crop diseases, in order to improve breeding efficiency and shorten the breeding cycle. Therefore, this application provides a system and method for assessing plant tissue growth status. This technical solution is applicable to breeding equipment. Accurate monitoring of plant growth processes helps managers to promptly identify adverse factors in plant growth and take corresponding measures, thereby accelerating the breeding process.

[0008] Furthermore, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making this invention, but due to space limitations, not all details and contents were listed in detail. However, this does not mean that the present invention does not possess the features of these prior art. On the contrary, the present invention already possesses all the features of the prior art, and the applicant reserves the right to add relevant prior art to the background art. Summary of the Invention

[0009] Current plant tissue growth status assessment systems primarily rely on image acquisition of plant features to generate corresponding comparison results. While multi-dimensional or multi-angle information acquisition enhances the accuracy of these results, current research often focuses on the assessment methodology, neglecting the precision of the acquired target plant images. The accuracy of the initial data acquisition is not guaranteed, meaning its impact on the assessment results is often overlooked. When the colors in the acquired plant growth images become blurred or inaccurate due to factors such as lighting and shooting angle, the system's accuracy in assessing plant growth status is affected. This can lead to technicians failing to detect abnormal plant growth promptly or making incorrect judgments, hindering timely and effective intervention and ultimately reducing plant yield.

[0010] To address the shortcomings of existing technologies, this invention provides a system for assessing the growth status of plant tissues, comprising:

[0011] The detection module is used to detect the initial light intensity of the plant's environment.

[0012] and a control module that is communicatively connected to the detection module.

[0013] When the detection module detects that the first light intensity of the environment exceeds or falls below a preset light intensity range that can objectively reproduce the plant tissue growth status, the control module adjusts the first light intensity of the environment to within the preset light intensity range and acquires a first image of the plant.

[0014] The control module is configured as follows:

[0015] When the edge width representing the sharpness of the part in the first image that meets the experimental requirements for extracting feature data is greater than a standard threshold, the second illumination intensity of the environment in which the part is located is adjusted, thereby obtaining a second image that can be used for feature data extraction.

[0016] In plant cultivation systems, feature data from images or videos acquired by the acquisition module is typically used to determine the plant's growth status. However, due to the influence of lighting conditions in the plant's environment, the acquired images cannot accurately reflect the plant's actual growth status. For example, excessively dark or bright lighting can lead to underexposed or overexposed images, affecting the accuracy of subsequent feature extraction. For instance, unclear image edges or excessively dark areas can also hinder data extraction. This invention addresses this by using a detection module to measure the ambient light intensity before the first image acquisition, determining if the light intensity is within a preset range. Theoretically, images acquired within this range should be clear and appropriately bright, suitable for data extraction. When the initial light intensity exceeds or falls below the preset range, the control module adjusts the light intensity of the plant's environment to within the preset range before acquiring the first image, reducing the acquisition of useless images. The usability of the acquired first image is assessed: if the edge width is within a standard threshold, the image can be directly used for feature data extraction; if the edge width exceeds the standard threshold, the image cannot be used for feature data extraction. Furthermore, the light intensity of the environment surrounding the parts of the plant used for feature data extraction, which meet the experimental requirements, is adjusted a second time. Compared with existing technologies, this invention ensures the usability of the acquired images in subsequent analysis by adjusting the light intensity of the parts used for feature data extraction. The purpose of this invention is not to require that the entire image be usable for feature data extraction, but only that the local target areas that meet the experimental requirements be usable for feature data extraction. On the other hand, existing technologies ensure the usability of captured images by adjusting the overall ambient light intensity. However, the actual operation method (directly adjusting the brightness of the supplemental lighting in the space where the plant is cultivated) cannot guarantee that the clarity of local areas of the image meets the standard. It is possible that the clarity of one part of the image meets the requirements, while the clarity of another part does not. Therefore, adjusting the second light intensity of the environment surrounding the parts of the plant used for feature data extraction allows for the acquisition of a second image that can be used for feature data extraction, ensuring that the second image used for data extraction can objectively reflect the true growth status of the plant.

[0017] Preferably, the system includes a functional output module with a supplementary lighting unit and a light-shielding unit, wherein,

[0018] The supplemental lighting unit adjusts its height to change the angle and second light intensity of the light projected onto the plant's parts that meet the experimental requirements for extracting feature data.

[0019] The shading unit alters the second light intensity of the environment in which the part of the plant is located by adjusting its tilt and / or height relative to the height of the plant.

[0020] In this invention, adjusting the ambient light intensity is achieved by changing the height and tilt of the supplementary lighting unit and the shading unit, which is significantly different from the existing technology that directly increases or decreases the light intensity of the supplementary lighting unit. Directly increasing or decreasing the light intensity of the supplementary lighting unit only affects the overall brightness of the environment and cannot guarantee that the brightness of every part of the acquired image is within a suitable range. For example, if the acquired image is too dark, increasing the light intensity of the supplementary lighting unit will result in some parts having suitable brightness while others are overexposed after re-acquiring the image, and the acquired image will still not be suitable for feature data extraction. This invention, however, analyzes the causes of images where the edge width exceeds a standard threshold, confirming that it is underexposed or overexposed. It then further adjusts the lighting conditions of the environment surrounding the underexposed or overexposed plant parts in the image to solve the problem of underexposed or overexposed areas in the image used for data extraction.

[0021] Preferably, when the edge width of the target area containing the part of the plant in the first image that meets the experimental requirements for feature data extraction is greater than the standard threshold, the control module controls the height or tilt of the function output module to acquire the second image. When the edge width of the first image exceeds the standard threshold, it indicates that the acquired image cannot be used for feature data extraction. Further, the height or tilt of the function output module is adjusted to adjust the light intensity of the target area containing the part of the plant that meets the experimental requirements for feature data extraction, specifically changing the light conditions of the plant parts corresponding to the target area to avoid local underexposure or overexposure in the target area.

[0022] Preferably, the control module includes a first judgment unit for obtaining the edge width of the target region and a second judgment unit for obtaining the brightness value of the target region. The second judgment unit obtains the brightness value of the target region when the edge width of the target region obtained by the first judgment unit is greater than a standard threshold. When the edge width of the first image is at the standard threshold, it indicates that the first image can be directly used for feature data extraction. When the edge width of the first image exceeds the standard threshold, it indicates that the acquired image cannot be used for feature data extraction, and it is necessary to determine the reason why the edge width exceeds the standard threshold. Therefore, the second judgment unit is activated to obtain the brightness value of the target region. The advantage of this setting is that the second judgment unit is only activated when the edge width exceeds the standard threshold, reducing the operating load on the control module.

[0023] Preferably, based on the fact that the sharpness of the target area in the first image is greater than the standard threshold, the control module obtains the brightness value of the target area to determine whether the target area is overexposed or underexposed. This invention determines whether a target area is overexposed or underexposed by obtaining its brightness value. The brightness value reflects the brightness of the image, offering high accuracy in determining exposure levels.

[0024] Preferably, when the brightness value of the target area exceeds the maximum value of the effective range that reflects the plant's growth status, the control module reduces the brightness value of the target area by lowering the height of the supplementary lighting unit, lowering the height of the shading unit, or reducing the tilt angle of the shading unit, thereby obtaining a second image for feature data extraction. A brightness value exceeding the maximum value of the effective range indicates that the image is too dark. By reducing the brightness value, the brightness of the image is improved. This invention improves the brightness of the image by adjusting the lighting conditions of the plant parts corresponding to the target area. Specifically, lowering the height of the supplementary lighting unit reduces the distance between the light source and the plant parts corresponding to the target area, increasing the light intensity of the environment in which the plant parts are located. Lowering the height of the shading unit reduces the obstruction of the light source, allowing more light to be projected onto the plant parts. Since the environment in which the plant parts are located is under-lit, reducing the tilt angle of the shading unit allows more light to be projected onto the plant parts.

[0025] Preferably, when the brightness value of the target area is lower than the minimum effective range that reflects the plant's growth status, the control module increases the brightness value of the target area by increasing the height of the supplementary lighting unit, increasing the height of the shading unit, or increasing the tilt angle of the shading unit, thereby obtaining a second image for feature data extraction. A brightness value less than the minimum effective range indicates that the image is too bright. By increasing the brightness value, the brightness of the image is reduced. This invention reduces the brightness of the image by adjusting the lighting conditions of the plant parts corresponding to the target area. Specifically, increasing the height of the supplementary lighting unit increases the distance between the light source and the plant parts corresponding to the target area, thereby reducing the light intensity of the environment in which the plant parts are located. Increasing the height of the shading unit increases the blocking of the light source, reducing the light projected onto the plant parts. Since the light in the environment in which the plant parts are located is too strong, increasing the tilt angle of the shading unit reduces the light projected onto the plant parts, thereby reducing the light intensity of the environment.

[0026] Preferably, the system further includes a data processing module for extracting the feature data, wherein,

[0027] When the second image is acquired, the data processing module extracts feature data from the target region. In this invention, the data processing module only starts working when the acquired image can be used for feature data extraction, rather than starting the data processing module every time an image is acquired, thereby reducing the generation of useless data and minimizing the operating load of the data processing module.

[0028] Preferably, the plant feature data acquired by the data processing module includes one or more of the following: plant height, leaf area, leaf color, stem color, flower morphology, flower color, fruit color, chlorophyll level, and leaf nitrogen level. Since the clarity of the images acquired for feature data extraction can objectively reproduce the true condition of the plant, the feature data can at least include data on plant height, color, and external morphology. Furthermore, analysis of leaf color can further reveal chlorophyll and nitrogen levels.

[0029] This invention also provides a method for assessing the growth status of plant tissues, comprising the following steps:

[0030] The initial light intensity of the plant's environment was measured.

[0031] Adjust the initial light intensity of the environment to a preset light intensity range that can objectively reflect the growth status of plant tissues;

[0032] Acquire the first image of the plant;

[0033] Determine the edge width representing the sharpness of the target region where the part of the first image that meets the experimental requirements for extracting feature data is located.

[0034] When the edge width of the characterization clarity of the target region is greater than the standard range, the light intensity of the environment in which the plant part is located is controlled to obtain a second image that can be used for feature data extraction.

[0035] Extract the characteristic data of the plant.

[0036] The beneficial effects of this invention are:

[0037] 1. In existing greenhouses, infrared, red, orange, yellow, blue, and green spectral combinations are selected to provide suitable light sources for plants according to their growth needs. Different proportions of spectral combinations form specific light color components, and the light color determines the overall color tone of the image. When shooting against a background with a high proportion of blue light, the image will appear dark, which is not conducive to the accuracy of subsequent data extraction. However, this invention can reduce the impact of light color components on the image color tone by setting up a supplementary lighting unit to adjust the ambient light intensity.

[0038] In some cases, plants are provided with light at night to promote growth. However, the light intensity at night is lower than during the day to minimize disruption to the plant's circadian rhythms. Therefore, images acquired at night for analysis may have lower ambient light intensity, affecting the accuracy of feature data extraction. In other cases, different greenhouses employ different lighting strategies, such as alternating, intermittent, and gradual lighting. For example, with intermittent lighting, the light source is turned on for a period and then stopped for another. If images are acquired during the period when lighting is stopped, the images will be too dark to extract accurate data for subsequent analysis. Furthermore, in some greenhouse cultivation, to save energy, managers use lenses to focus light and increase the light intensity in the cultivation area when the weather is sunny and bright. At this time, the light intensity in the cultivation area can reach 90,000 Lux. Images acquired under these conditions will also affect the accuracy of the analysis results.

[0039] The light detection unit, supplementary lighting unit, and shading unit of this invention effectively solve the aforementioned problems. Before acquiring the first image, the light detection unit detects the ambient light intensity to determine if it falls within a preset light intensity range. Theoretically, images acquired against a background within the preset light intensity range are clear and have appropriate brightness, making them suitable for data extraction. When the detected ambient light intensity is below the lower limit of the preset light intensity range, the supplementary lighting unit provides supplementary lighting to bring the light intensity within the preset range. Conversely, when the detected ambient light intensity exceeds the upper limit of the preset light intensity range, the shading unit shades the environment to bring the light intensity within the preset range. When the light intensity of the plant's environment is within the preset light intensity range, the first image is acquired.

[0040] 2. When the ambient light intensity is within the preset range that theoretically allows for the acquisition of images with moderate brightness, the image acquisition module acquires the first image. The control module determines whether the image is actually clear and usable for feature data extraction. When the first judgment unit of the control module determines that the edge width of the image is greater than the standard threshold and therefore cannot be used for feature data extraction, the second judgment unit is activated to analyze the blurred image and determine whether the blurred image is caused by underexposure or overexposure. Based on the cause of the blur, the control module controls the height and angle of the supplementary lighting unit and the tilt and height of the shading unit to adjust the ambient light intensity. If the adjusted ambient light intensity is still too high or too low, the control module continues to control the supplementary lighting unit and the shading unit until the acquired image is clear and natural and can be used for feature data extraction. The advantage of this setting is that it first adjusts the ambient light intensity to a preset range before the first image acquisition, reducing the acquisition of useless images. Furthermore, after the images are acquired, their usability is assessed. Compared to the traditional method of directly using the acquired images for data extraction, this setting can identify images that are unusable for data extraction and adjust environmental factors to ensure that the final acquired images are clear and natural. Based on the accuracy of the acquired images, the reliability of the feature data extracted from these images is guaranteed.

[0041] 3. This invention determines the usability of an image by detecting the sharpness and brightness values ​​of the target area in the acquired image. The reason for this setting is that the standard for image usability varies depending on different experimental needs, such as extracting leaf area, extracting leaf lesions, or extracting fruit color. When the experimental purpose is to extract fruit color, if the sharpness and / or brightness values ​​of the target area where the fruit is located in the acquired image are within a preset range, the sharpness or brightness of other parts of the image will not affect the data extraction. Therefore, it is sufficient to achieve the purpose as long as the sharpness and / or brightness values ​​of the target area are within the preset range. Compared with existing technologies, this invention utilizes the adjustment of the height and / or tilt of the supplementary lighting unit and the shading unit to adjust the light intensity of the environment in which the target area of ​​the plant is located. This targeted adjustment of the light intensity of specific parts of the plant effectively reduces the number of useless image acquisitions. In existing technologies, the brightness of the supplementary lighting unit is usually adjusted as a whole to acquire images. For example, if the acquired image is underexposed, increasing the light intensity of the supplementary lighting unit may result in some areas of the acquired image being at normal brightness while others are overexposed due to the influence of the projection distance or projection angle of the supplementary lighting unit. This leads to low image reliability, increases the number of image acquisitions, and wastes research resources.

[0042] 4. The technical solution of this invention is applicable to breeding equipment. During the growth stages of crops, continuous monitoring of their growth is necessary. Existing technologies typically utilize image acquisition equipment to obtain crop growth data; however, due to external environmental influences, the acquired images may not always reflect the true growth status of the crop, leading to missed opportunities to take appropriate measures. For example, if no appropriate measures are taken in the early stages of plant disease infection, the crop's growth rate may slow down or even die. Even if fruit is produced, the quality of the fruit will be poor and fail to meet market demands. The technical solution provided by this invention can obtain accurate monitoring results during crop growth and promptly detect adverse conditions, reducing unexpected situations during crop development, improving breeding efficiency, and shortening the breeding cycle.

[0043] In the current agricultural context, with the transformation and upgrading of food systems and strong demand for grain, accelerated breeding is particularly important. By ensuring that crops in breeding equipment operate under optimal conditions at each growth stage, the fastest possible maturity can be achieved. Accelerated breeding has enormous development potential in ensuring national food security. Furthermore, applying the technical solutions provided by this invention to breeding equipment can play a significant role in breeding in non-arable land, deserts, Gobi, and even in special environments such as outer space. Attached Figure Description

[0044] Figure 1 This is a simplified schematic diagram of the module connection relationship of the judgment system according to a preferred embodiment of the present invention;

[0045] Figure 2 This is a schematic diagram of the structure of a judgment system according to a preferred embodiment of the present invention.

[0046] List of reference numerals

[0047] 100: Detection module; 110: Light detection unit; 120: Height detection unit; 200: Control module; 210: First judgment unit; 220: Second judgment unit; 300: Function output module; 310: Supplemental lighting unit; 320: Light blocking unit; 400: Image acquisition module. Detailed Implementation

[0048] The following is in conjunction with the appendix Figures 1-2 Please provide a detailed explanation.

[0049] The preset light intensity range refers to the range of light intensity that objectively reflects the plant tissue growth status when acquiring images. In other words, under the background of the preset light intensity range, the acquired plant images can objectively reproduce the plant's growth status. Objectively reproducing the plant tissue growth status means that the plant tissue growth status reflected in the acquired images is consistent with the actual plant growth status, and will not produce results inconsistent with the actual plant growth status due to the influence of external environment (light intensity, light angle, etc.). Feature data refers to phenotypic data information that reflects the plant's growth status and tissue characteristics. The standard threshold is a reference value for judging whether a target area in the image is blurred or sharp.

[0050] Example 1

[0051] like Figures 1-2 The plant tissue growth status assessment system shown includes: a detection module 100 for detecting the light intensity of the plant's environment; a function output module 300 for adjusting the light intensity of the environment; an image acquisition module 400 for acquiring images of the plant; and a control module 200, which is communicatively connected to the detection module 100, the function output module 300, and the image acquisition module 400, respectively. Preferably, the control module 200 is connected to the detection module 100, the function output module 300, and the image acquisition module 400 via wireless or Bluetooth connection. When the detection module 100 detects that the light intensity of the environment exceeds or falls below a preset light intensity range that can accurately reflect the plant tissue growth status, the control module 200 controls the function output module 300 to adjust the light intensity of the environment to the preset light intensity range and controls the image acquisition module 400 to start working. The control module 200 is configured to: determine the quality level of the image and control the function output module 300 to adjust the light intensity of the environment so that the image acquisition module 400 can acquire a clear image.

[0052] Preferably, before the image acquisition module 400 is started, when the light intensity is lower than the lower limit of the preset light intensity range, the control module 200 generates a first judgment result and outputs a first control signal. Based on the first control signal, the function output module 300 increases the light intensity until the light intensity of the plant's environment is within the preset light intensity range.

[0053] When the light intensity exceeds the upper limit of the preset light intensity range, the control module 200 generates a second judgment result and outputs a second control signal. Based on the second control signal, the function adjustment module reduces the light intensity until the light intensity of the plant's environment is within the preset light intensity range.

[0054] When the light intensity is within the preset light intensity range, the control module 200 generates a third judgment result and outputs a third control signal to control the image acquisition module 400 to start working.

[0055] Preferably, the control module 200 is provided with a first judgment unit 210 for judging fuzziness of the acquired image and a second judgment unit 220 for judging the image quality level, wherein,

[0056] When the image is determined to be blurry, the second determination unit 220 starts working.

[0057] Preferably, the system further includes a data processing module for acquiring characteristic data reflecting the plant's growth status, and the control module 200 is configured to:

[0058] When the image is determined to be of the first quality level, the data processing module is controlled to start working to extract the characteristic data of the plant.

[0059] When the image is determined to be of the second quality level, the function output module 300 is controlled to increase the light intensity until the brightness value of the image reaches the first quality level, and the data processing module starts working.

[0060] When the image is determined to be of the third quality level, the function output module 300 is controlled to reduce the light intensity until the brightness value of the image reaches the first quality level, and the data processing module starts working.

[0061] Preferably, the functional output module 300 includes a supplementary lighting unit 310 for increasing the ambient light intensity and a shading unit 320 for reducing the ambient light intensity, wherein...

[0062] The supplemental lighting unit 310 can adjust its height to change the angle and intensity of light it projects onto the plant;

[0063] The shading unit 320 adjusts its tilt and / or height relative to the height of the plant to keep the light intensity of the plant's environment within a preset light intensity range.

[0064] Preferably, the detection module 100 includes a light detection unit 110 for detecting the light intensity of the environment and a height detection unit 120 for detecting the height, wherein,

[0065] When the supplemental lighting unit 310 is lower than the height of the supplemental lighting plant, the supplemental lighting unit 310 is raised to a first position higher than the supplemental lighting plant to meet the supplemental lighting requirements of the supplemental lighting plant.

[0066] Preferably, the first judgment unit 210 is configured to judge whether the target area is blurry or clear.

[0067] Preferably, the second determination unit 220 determines the quality level of the image by extracting the brightness value of the target area.

[0068] Preferably, the control module 200 can be a processor or a microcontroller.

[0069] Preferably, the light detection unit 110 is an ambient light detector or an ambient light sensor. For example, the light detection unit 110 can be an NHZD203T illuminance sensor probe or a YG-SR1 wireless ambient light detector.

[0070] Preferably, the height detection unit 120 is a height detection sensor or a laser rangefinder. For example, the height detection unit 120 can be an MSE-D150 type laser rangefinder.

[0071] Preferably, the image acquisition module 400, supplementary lighting unit 310, shading unit 320, light detection unit 110, and height detection unit 120 are mounted on guide rails at suitable positions around the plant. Preferably, the image acquisition module 400 can change its acquisition point on the guide rail to acquire images of the plant from different angles, reducing errors in the initial data acquisition. According to a preferred embodiment, the image acquisition unit can perform image acquisition around the plant.

[0072] Typically, the supplementary lighting unit 310 is installed on the top of the plant to ensure that the light can evenly illuminate all parts of the plant. Therefore, in this embodiment, the light detection unit 110 is positioned at the center of the top of the plant to ensure the reliability of the measurement results. Preferably, the height detection unit 120 is communicatively connected to the control module 200. The height detection unit 120 detects the plant's growth height and sends the generated height data to the control module 200. Based on the plant's height, the control module 200 controls the light detection unit 110 to be positioned at the center directly above the plant, at a distance α from the top of the plant. An appropriate distance is maintained between the supplementary lighting unit 310 and the top of the plant to avoid excessive illumination; typically, the distance is 50-100 cm. Preferably, α can be 10 cm, 15 cm, or 20 cm. If the distance α between the light detection unit 110 and the top of the plant is too large or too small, it will affect the detection results, leading to inaccurate judgments from the control module 200. A suitable α ensures the usability of the detection results from the light detection unit 110. Preferably, the supplementary lighting unit 310 adjusts its height to change the angle and intensity of light it projects onto the plant. Taking tomato growth as an example, when the height detection unit 120 detects that the tomato plant height is 50 cm, the height detection unit 120 sends this data to the control module 200. The control module 200 adjusts the light detection unit 110 to a position 10 cm above the center of the tomato plant. When the light detection unit 110 is in this position, it can evenly receive light intensity from all directions in the tomato's environment. Preferably, the supplementary lighting unit 310 can be a supplementary light, such as an LED supplementary light.

[0073] Preferably, the height detection unit 120 cooperates with the supplementary lighting unit 310 to obtain the height of the supplementary lighting unit 310, thereby controlling the distance between the supplementary lighting unit 310 and the top of the plant. Preferably, the height detection unit 120 cooperates with the shading unit 320 to obtain the height of the shading unit 320, thereby controlling the distance between the shading unit 320 and the light source. Preferably, the height detection unit 120 cooperates with the image acquisition module 400 to control the distance between the image acquisition module 400 and the plant. Preferably, the image acquisition module 400 is positioned directly above the plant. Preferably, the distance between the image acquisition module 400 and the top of the plant is set to β. Preferably, β can be 10 cm, 15 cm, 20 cm, or 25 cm.

[0074] According to a preferred embodiment, the image acquisition module 400 is movable on the guide rail. Preferably, the image acquisition module 400 is in single-plant acquisition mode, that is, it acquires images of each plant individually. Preferably, the image acquisition module 400 is in area acquisition mode, that is, it acquires images of plants planted in each area, and the image includes the plants in one area. The height detection unit 120 provided in this embodiment can detect the height of the plant, the height of the supplementary lighting unit 310, the height of the shading unit 320, and the height of the image acquisition module 400, and control the height of the image acquisition module 400 at a position β away from the top of the plant, that is, after the image acquisition module 400 moves from the top of one plant / area to the top of the next plant / area, the distance β between the image acquisition module 400 and the top of the plant remains consistent.

[0075] When the image acquisition module 400 captures images of a single plant, due to individual differences, the height of different plants varies. For example, in the planting area, some rice plants are 40 cm tall, some are 30 cm tall, and some are 50 cm tall. During image acquisition, it is necessary to ensure that the distance between the image acquisition module 400 and the top of the plant is equal. Therefore, after the height of the plant is detected by the height detection unit 120, the distance β between the image acquisition module 400 and the top of the plant remains consistent. That is, after the first rice plant with a height of 40 cm is captured, the height of the image acquisition module 400 is 50 cm. When the image acquisition module 400 moves to another rice plant with a height of 30 cm, the height of the image acquisition module 400 is adjusted to 40 cm.

[0076] When there is insufficient light in the environment, supplementing the light from the top of the plant is the best position for the image acquisition module 400 to acquire plant images. Due to the influence of the light distance, different plant heights require different light distances. For example, mature rice is 60 cm tall. In order for the supplemental light to illuminate the entire plant, when the light intensity of the supplemental light is 300 Lux, the height of the supplemental light needs to be 70 cm, so that there is a 10 cm difference between it and the top of the 60 cm tall rice plant. This ensures that the supplemental light at that lumen intensity can meet the supplemental lighting requirements.

[0077] Preferably, the light detection unit 110 is communicatively connected to the control module 200. The light detection unit 110 is activated after being adjusted to a suitable position. The light detection unit 110 collects the light intensity of the environment in which the plant is located and generates corresponding light intensity data. The light detection unit 110 sends the light intensity data to the control module 200. The control module 200 compares and analyzes the received light intensity data with a preset light intensity range.

[0078] Taking tomato growth as an example, the following explanation is provided. Preferably, the preset light intensity range is set to 40,000~50,000 Lux. Under this light intensity range, theoretically, the acquired images can objectively reflect the true growth status of the tomato plant, such as leaf size, leaf color, fruit size, and fruit color. When the light detection unit 110 detects that the ambient light intensity is 20,000 Lux, the control module 200 generates a first judgment result indicating that the light intensity is less than the lower limit of the preset light intensity range of 40,000 Lux and generates a first control signal. The first control signal is a related operation to perform supplemental lighting to increase the ambient light intensity. According to a preferred embodiment, the function output module 300 includes a supplemental lighting unit 310 for increasing the ambient light intensity and a shading unit 320 for reducing the ambient light intensity.

[0079] Preferably, the height and angle of the supplementary lighting unit 310 are adjustable to control the ambient light intensity.

[0080] The control module 200 sends a first control signal to the function output module 300. Preferably, the control module 200 is communicatively connected to the supplementary lighting unit 310. The control module 200 sends the first control signal to the supplementary lighting unit 310. After receiving the first control signal, the supplementary lighting unit 310 increases its light intensity so that the ambient light intensity is within a preset light intensity range.

[0081] When the control module 200 generates a second judgment result indicating that the light intensity exceeds the upper limit of the preset light intensity range, the control module 200 outputs a second control signal. Based on the second control signal, the function adjustment module reduces the light intensity until the light intensity of the plant's environment is within the preset light intensity range. The height detection unit 120 starts working. After receiving the detection result from the height detection unit 120, the control module 200 controls the shading unit 320 to adjust its height. Preferably, the height of the shading unit 320 is adjusted to a second position higher than the plant. For example, when the light detection unit 110 detects that the light intensity in the environment is 90,000 Lux, the control module 200 generates a second judgment result indicating that the light intensity exceeds the upper limit of the preset light intensity range by 50,000 Lux and generates a second control signal. The second control signal is a related operation to perform shading to reduce the light intensity in the environment. Preferably, the control module 200 is communicatively connected to the shading unit 320. The control module 200 sends the second control signal to the shading unit 320. Preferably, the shading unit 320 includes at least a shading plate and an angle adjustment mechanism.

[0082] Preferably, the shading unit 320 adjusts its tilt and / or height relative to the plant's height to ensure the light intensity of the plant's environment is within a preset light intensity range. After receiving the second control signal, the shading unit 320 first changes the tilt of the shading plate by adjusting the angle adjustment mechanism. For example, if the initial tilt of the shading plate is 20°, and the image acquired under this light intensity condition cannot reflect the true state of plant tissue growth due to excessive light intensity, the shading plate is adjusted from the initial tilt of 20° to 45°, bringing the ambient light intensity within the preset light intensity range of 40,000~50,000 Lux.

[0083] Preferably, when the shading unit 320 is adjusted to its maximum tilt angle and the ambient light intensity still exceeds the upper limit of the preset light intensity range, the shading unit 320 can increase its height to increase the shading range, thereby bringing the ambient light intensity within the preset light intensity range. When the shading plate is adjusted from the initial tilt angle of 20° to 90°, i.e., the plane of the shading plate is parallel to the cross-section of the plant body, and the ambient light intensity still exceeds the preset light intensity range of 40,000~50,000 Lux, the height of the shading plate is increased, causing it to move towards the light source to increase its shading range, thereby controlling the ambient light intensity within the preset light intensity range. For example, when the tilt angle of the shading plate reaches its maximum, the ambient light intensity is 55,000 Lux, still exceeding the upper limit of the preset light intensity range of 50,000 Lux. In this case, increasing the height of the shading plate and moving it 15 cm towards the light source will bring the ambient light intensity within the preset light intensity range.

[0084] As the plant grows, its height increases. Preferably, when the supplemental lighting unit 310 is below the height of the plant, it is raised to a first position above the plant to meet its lighting requirements. For example, when a tomato plant is 30 cm tall, the supplemental lighting unit 310 is positioned 50 cm from the top of the plant. When the plant grows to 60 cm, the unit is 20 cm from the top, increasing the light intensity and potentially scorching the plant. Therefore, it is necessary to raise the unit to a first position above the plant. This first position is where the supplemental lighting unit 310 can provide a suitable light intensity for plant growth.

[0085] Preferably, the height of the light-shielding unit 320 is higher than the height of the image acquisition module 400.

[0086] When the control module 200 generates a third judgment result indicating that the light intensity is within a preset light intensity range, the control module 200 outputs a third control signal to control the image acquisition module 400 to start working. Preferably, the image acquisition module 400 can be a camera or an image sensor.

[0087] Preferably, the image acquisition module 400 has at least one acquisition point on the guide rail. Preferably, the control module 200 determines the image quality level based on the image resolution. Preferably, the image quality level is determined by the image's exposure level. Specifically, in this embodiment, the exposure level refers to the brightness of the acquired image. Preferably, the image quality level is determined by the image's brightness value.

[0088] Preferably, the quality grades include a first quality grade, a second quality grade, and a third quality grade.

[0089] Preferably, the first quality level refers to the target plant being clear in the acquired image, that is, the first quality level is moderate exposure. The image of the first quality level can objectively restore the true growth status and tissue characteristics of the target plant, and can extract accurate feature data of the target plant through the image.

[0090] Preferably, the second quality level refers to the target plant in the acquired image being too dark, that is, the second quality level is underexposed, and it is impossible to extract accurate feature data of the target plant.

[0091] Preferably, the third quality level refers to the target plant in the acquired image being too bright, that is, the third quality level is overexposed, and it is impossible to extract accurate feature data of the target plant.

[0092] The analysis system also includes a data processing module for acquiring characteristic data reflecting the growth status of the plant, and the control module 200 is configured as follows:

[0093] When the image is determined to be of the first quality level, the data processing module is controlled to start working to extract the characteristic data of the plant.

[0094] When the image is determined to be of the second quality level, the illumination intensity of the supplementary lighting unit 310 is controlled until the brightness value of the image reaches the first quality level, and the data processing module starts working.

[0095] When the image is determined to be of the third quality level, the tilt and / or height of the light-blocking unit 320 are controlled to adjust the light intensity until the brightness value of the image reaches the first quality level, and the data processing module starts working.

[0096] Preferably, the control module 200 is communicatively connected to the data processing module. Under conditions where the ambient light intensity is within a preset range, the image acquisition module 400 acquires a first image of the plant and sends it to the control module 200. Preferably, the control module 200 is equipped with a first judgment unit 210. The first judgment unit 210 is used to perform fuzzy judgment on the target area in the acquired image. Since this embodiment requires extracting feature data of the target area of ​​the plant part in the image that meets the experimental requirements, it is only necessary to determine whether the target area in the image is clear. Preferably, the target area is the area used for feature data extraction.

[0097] Preferably, the method by which the first judgment unit 210 judges the sharpness of a target region in an acquired image includes the following steps: extracting features of the edge regions of the target region in the image; detecting the edge region features of the target region and grouping them horizontally and vertically; dividing the edge segments into segments of specific lengths; calculating the edge width and obtaining the average edge width; and judging whether the target region in the image is blurry or sharp according to a set standard threshold. When the edge width is greater than the standard threshold, the target region is blurry; when the edge width is equal to the standard threshold, the target region is sharp. When the target region in the image is sharp, the image can be used for feature data extraction. Preferably, sharpness is characterized by edge width.

[0098] Preferably, the control module 200 is provided with a second judgment unit 220 to collect the brightness value of the target area and then judge the quality level of the image.

[0099] When the target area of ​​an image is determined to be blurry, the second judgment unit 220 analyzes the image quality level by collecting the brightness value of the target area of ​​the image, and then finds out the reason for the image blurriness.

[0100] Preferably, the second determination unit 220 generates a brightness value by extracting pixel information of the target region of the image. Specifically, the target region refers to the region in the image from which feature data is to be extracted. In this embodiment, the target region refers to the region in the image where the target plant is located.

[0101] Preferably, the judgment unit compares the generated brightness value with the effective range of brightness values ​​to obtain a brightness value judgment result. For example, 256 gray levels are used as the judgment standard, and the brightness value range is 0~255. Preferably, the effective range of brightness values ​​is set to 30~230. Preferably, images within the effective range of 30~230 are judged as the first quality level, and images of the first quality level can trigger the data processing module to start working to extract feature data of the target plant. Preferably, images within the brightness range of 230~255 are judged as the second quality level. Images of the second quality level are too dark and cannot be used to extract accurate feature data. When an image is judged as the second quality level, the data processing module does not start working, and the control module 200 controls the supplementary lighting unit 310 to increase the light intensity so that the acquired image reaches the first quality level. Preferably, the control module 200 reduces the brightness value of the target area by lowering the height of the supplementary lighting unit 310, lowering the height of the shading unit 320, or reducing the tilt of the shading unit 320. Once the image reaches the first quality level, the data processing module begins processing and extracts the feature data of the target plant in the image. It should be noted that classifying image quality levels based on brightness values ​​is merely one example provided in this embodiment, and the brightness value range listed above is only an example; the range can be changed according to actual needs.

[0102] Preferably, images with a brightness range of 0-30 are classified as third quality level. Images of third quality level are too bright to be used for extracting accurate feature data. When an image is classified as third quality level, the data processing module does not operate, and the control module 200 controls the tilt and / or height of the shading unit 320 to bring the acquired image to first quality level. Preferably, the control module 200 increases the height of the supplementary lighting unit 310, increases the height of the shading unit 320, or increases the tilt of the shading unit 320 to increase the brightness value of the target area. Once the image reaches first quality level, the data processing module starts operating and extracts feature data of the target plant from the image. The methods for adjusting the tilt and height of the shading unit 320 have been described above and will not be repeated here. It should be understood that adjusting the tilt of the shading plate can change the intensity of light illuminating or reflecting onto the target plant, and its tilt can be adjusted as needed; moving the shading plate toward the light source can increase the shading range, and conversely, moving the shading plate away from the light source can reduce the shading range. In this embodiment, the data processing module only starts working when the acquired image is of the first quality level. The advantage of this setting is that it ensures the accuracy of the acquired images in the early stage, that is, the acquired images can objectively restore the growth status and tissue characteristics of the target plant, thereby ensuring the reliability of the feature data extracted by the data processing module in the later stage. Therefore, the plant's growth status can be judged through reliable feature data, avoiding huge losses caused by failure to take timely measures after misjudgment.

[0103] According to a preferred embodiment, the plant characteristic data acquired by the data processing module includes one or more of the following: plant height, leaf area, leaf color, stem color, flower morphology, flower color, fruit color, chlorophyll level, and leaf nitrogen level. Preferably, the image acquisition module 400 can be a multispectral camera, a multispectral camera, an RGB-D camera, etc. Preferably, the data processing module can obtain different spectral bands from the images acquired by the multispectral camera, and then extract the plant's chlorophyll information. Preferably, the data processing module determines the chlorophyll content and nitrogen content information based on the leaf color in the image. Traditional plant nutrient testing is usually conducted in a laboratory using various chemical reagents and instruments, which is time-consuming and cannot yield results quickly. However, the method provided in this embodiment can detect the plant's nutritional status in real time and obtain corresponding results. Preferably, the data processing module analyzes the acquired images using AI and image processing technologies. In terms of appearance feature analysis, yellowing leaves indicate nutrient deficiency in the plant; dark green leaves indicate sufficient nutrition. Therefore, this embodiment can analyze plant nutrients through color. For example, after the data processing module extracts the color of plant leaves from an image, it converts the extracted leaf color to obtain a specific numerical value. This value is then calculated with standard indicators to obtain the chlorophyll content and nitrogen content. Specifically, features are extracted from the leaves in the image, including boundary features, color features, and texture features. The algorithm in the data processing module calculates the actual leaf features with standard indicators to obtain a leaf feature vector, and then calculates the SPAD value (chlorophyll content or nitrogen content).

[0104] For example, a method for obtaining the leaf area of ​​a plant includes the following steps: After the image acquisition module 400 acquires a first image, it sends it to the control module 200. When the edge width of the target area where the leaf is located in the first image acquired by the first judgment unit 210 is greater than a standard threshold, the second judgment unit 220 starts working to acquire the brightness value of the target area where the leaf is located. When the brightness value of the target area exceeds 230, the control module 200 reduces the height of the supplementary lighting unit 310 relative to the plant part corresponding to the target area where the leaf is located in the first image. For example, it reduces the distance from the plant leaf from 50 cm to 30 cm, increasing the light intensity at that part, so that the brightness value of the target area in the second image acquired by the image acquisition module 400 is within an effective range, thereby ensuring that the second image can be used for feature data extraction. Preferably, increasing the light intensity of a specific part of the plant also includes reducing the height of the shade plate. The closer the shade plate is to the light source, the less light is projected onto the plant. Preferably, increasing the light intensity of a specific part of the plant also includes increasing the tilt of the shade plate relative to the plane of the plant's cross-section. The smaller the tilt angle of the light-blocking plate, the more light is projected onto the plant. For example, if the tilt angle of the light-blocking plate relative to the plant leaves is large, the brightness value of the area where the leaves are located in the first image will be too high. In this case, the tilt angle of the light-blocking plate relative to the plane of the plant's cross-section should be increased, for example, from the original 20° to 50°. Preferably, when the brightness value of the target area is less than 30, the opposite measure can be used to adjust the brightness value to an effective range.

[0105] When the brightness value of the target area on the leaf surface is within the valid range, the data processing module extracts the leaf area. Preferably, the leaf area extraction method includes the grid area measurement method, the MATLAB method, etc. Here, the grid area measurement method is used as an example. The leaf image is projected onto a 9 mm × 9 mm reference grid, and the number of empty spaces occupied by the leaf in the reference grid is obtained. For example, the area of ​​the reference grid is 81 mm. 2 The blade occupies 49 spaces, which is 49 mm. 2 .

[0106] This embodiment also provides a method for assessing the growth status of plant tissues, including the following steps:

[0107] The light intensity of the plant's environment is detected; the light intensity of the environment is adjusted to a preset light intensity range that can objectively reflect the plant tissue growth status; a first image of the plant is acquired; the edge width of the target area of ​​the part of the first image that meets the experimental requirements for feature data extraction is determined; when the edge width of the target area is greater than the standard range, the light intensity of the environment of the plant's part is controlled to obtain a second image that can be used for feature data extraction; and the feature data of the plant is extracted.

[0108] It should be noted that the specific embodiments described above are exemplary. Those skilled in the art can devise various solutions inspired by the disclosure of this invention, and these solutions all fall within the scope of this invention and its protection. Those skilled in the art should understand that this specification and its accompanying drawings are illustrative and do not constitute a limitation on the claims. The scope of protection of this invention is defined by the claims and their equivalents. This specification contains multiple inventive concepts; terms such as "preferredly," "according to a preferred embodiment," or "optionally" indicate that the corresponding paragraph discloses an independent concept. The applicant reserves the right to file divisional applications based on each inventive concept. Throughout the text, features introduced by "preferredly" are merely optional and should not be construed as mandatory. Therefore, the applicant reserves the right to abandon or delete relevant preferred features at any time.

Claims

1. A system for assessing plant tissue growth status, including: The detection module (100) is used to detect the first light intensity of the environment in which the plant is located; and a control module (200) communicatively connected to the detection module (100), characterized in that, When the detection module (100) detects that the first light intensity of the environment exceeds or falls below a preset light intensity range that can objectively reproduce the growth status of plant tissue, the control module (200) adjusts the first light intensity of the environment to the preset light intensity range and acquires a first image of the plant, wherein, The control module (200) is configured to: When the edge width representing the sharpness of the part in the first image that meets the experimental requirements for extracting feature data is greater than a standard threshold, the second illumination intensity of the environment in which the part is located is adjusted, thereby obtaining a second image that can be used for feature data extraction. The control module (200) includes a first judgment unit (210) for obtaining the edge width of the target area and a second judgment unit (220) for obtaining the brightness value of the target area. When the edge width of the target area obtained by the first judgment unit (210) is greater than the standard threshold, the second judgment unit (220) obtains the brightness value of the target area. The method of the first judgment unit (210) to judge the sharpness of the target area in the acquired image includes the following steps: extracting the features of the edge area of ​​the target area in the image; detecting the edge area features of the target area and grouping them in the horizontal and vertical directions; dividing the edge segments into segments of a specific length; calculating the edge width and obtaining the average width of the edge; judging whether the target area in the image is blurry or clear according to the set standard threshold; when the edge width is greater than the standard threshold, the target area is blurry; when the edge width is the standard threshold, the target area is clear; when the target area in the image is clear, the image is used for feature data extraction.

2. The system of claim 1, wherein, The system includes a functional output module (300) with a supplementary lighting unit (310) and a light-shielding unit (320), wherein, The supplemental lighting unit (310) adjusts its height to change the angle and second light intensity of the light projected onto the environment of the part of the plant that meets the experimental requirements for extracting feature data. The shading unit (320) alters the second light intensity of the environment in which the part of the plant is located by adjusting its tilt and / or height relative to the height of the plant.

3. The system of claim 2, wherein, When the edge width of the target area where the part of the plant in the first image that meets the experimental requirements for extracting feature data is located is greater than the standard threshold, the control module (200) controls the height or tilt of the function output module (300) to obtain the second image.

4. The system of claim 1, wherein, Based on the fact that the edge width of the target region in the first image is greater than the standard threshold, the control module (200) obtains the brightness value of the target region to obtain the result that the target region is overexposed or underexposed.

5. The system of claim 3, wherein, When the brightness value of the target area exceeds the maximum value of the effective range that can reflect the plant growth status, the control module (200) reduces the brightness value of the target area by lowering the height of the supplementary light unit (310), lowering the height of the shading unit (320), or reducing the tilt of the shading unit (320), thereby obtaining a second image for feature data extraction.

6. The system of claim 3, wherein, When the brightness value of the target area is lower than the minimum value of the effective range that can reflect the plant growth status, the control module (200) increases the brightness value of the target area by increasing the height of the supplementary light unit (310), increasing the height of the shading unit (320), or increasing the tilt of the shading unit (320), thereby obtaining a second image for feature data extraction.

7. The system of claim 3, wherein, The system further includes a data processing module for extracting the feature data, wherein, When the second image is obtained, the data processing module extracts feature data from the target region.

8. The system of claim 7, wherein, The plant feature data acquired by the data processing module includes one or more of the following: plant height, leaf area, leaf color, stem color, flower shape, flower color, fruit color, chlorophyll level, and leaf nitrogen level.

9. A method of using the plant growth condition assessment system according to any one of claims 1 to 8, characterized by, Includes the following steps: The initial light intensity of the plant's environment was measured. Adjust the initial light intensity of the environment to a preset light intensity range that can objectively reflect the growth status of plant tissues; Acquire the first image of the plant; Determine the edge width representing the sharpness of the target region where the part of the first image that meets the experimental requirements for extracting feature data is located. When the edge width of the characterization clarity of the target region is greater than the standard range, the light intensity of the environment in which the plant part is located is controlled to obtain a second image that can be used for feature data extraction. Extract the characteristic data of the plant.

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