A method for precise fertilization of fruit trees based on a vehicle-mounted hole applying all-in-one machine

Abstract

The present application provides a kind of fruit tree precision fertilization method based on vehicle hole application integrated machine, the method obtains the position information and three-dimensional image of each fruit tree in orchard by positioning navigation module and fruit tree information acquisition module, obtains the stem diameter, crown diameter information of each fruit tree by image processing module, calculates the hole punching position, the number of hole punching and the amount of fertilization of each fruit tree according to the above information, to achieve the purpose of quantitative and accurate fertilization, reduce the environmental pollution problem caused by over-fertilization, improve fertilization efficiency. Navigation system cooperates with hole application integrated machine to realize automatic positioning and hole punching fertilization, effectively reduces manual labor.

Description

Technical Field

[0001] This invention belongs to the field of fruit tree cultivation technology, and in particular relates to a method for precise fertilization of fruit trees based on a vehicle-mounted hole-applying integrated machine. Background Technology

[0002] Fruit trees are perennial plants with high nutrient requirements, long periods of continuous nutrient consumption, and varying nutrient needs at different growth stages, necessitating proper fertilization. Fertilization should be tailored to the tree species, age, and root system characteristics, flexibly selecting the most suitable fertilization method, application site, and depth. To ensure optimal growth, fertilization typically involves digging holes, applying fertilizer, and covering with soil. Currently, most orchard fertilization is done manually, with holes dug and fertilizer poured in or poured in. The amount of fertilizer and the location of the holes are determined based on the grower's experience. Therefore, traditional fertilization methods require a large amount of manual labor and suffer from uneven and inconsistent application. Over-fertilization not only wastes fertilizer but also leads to environmental pollution, negatively impacting both economic and ecological benefits. Summary of the Invention

[0003] This invention addresses the technical problem in existing technologies where fertilizer application and hole placement are determined based on fruit growers' experience. It proposes a precise fertilization method for fruit trees based on a vehicle-mounted hole-applying machine, which formulates a scientific fertilization strategy according to the actual production conditions of each fruit tree.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] A method for precision fertilization of fruit trees based on a vehicle-mounted integrated hole-applying machine, wherein the vehicle-mounted integrated hole-applying machine includes a positioning and navigation module, an image acquisition module, an image data analysis module, a database module, and a hole-applying mechanism. The positioning and navigation module includes a visual navigation module and a Beidou navigation module, used to acquire the location of each fruit tree and plan the driving path; the image acquisition module includes a binocular stereo vision depth camera, used to acquire fruit tree image information; the image data analysis module is used to process the fruit tree images and calculate the trunk diameter and crown diameter information of the fruit trees.

[0006] The precise fertilization method for fruit trees includes the following steps:

[0007] (1) The vehicle-mounted hole-applying integrated machine sequentially acquires the location information and three-dimensional image of each fruit tree in the orchard through the positioning and navigation module and the image acquisition module and transmits them to the database module;

[0008] (2) The image data analysis module processes the fruit tree images, including reading digital images, grayscale processing, image denoising and feature extraction, to obtain the trunk diameter and crown diameter information of each fruit tree and store them in the database.

[0009] The image denoising step is based on the Bounded Mean Oscillation Space (BMO) edge detection optimization algorithm. The BMO algorithm is introduced into the PDE model to construct an image edge gradient detection optimization operator suitable for 3D images. Specifically...

[0010]

[0011] Where ZQ(u,x,r) is the BMO form of the cube region Q(x,r,t); y and z are functions on the cube; and Q(x,r,t) is the position information of the cube region.

[0012] (3) Calculate the number of holes N based on the canopy diameter, where,

[0013] N = [0.75πD],

[0014] D is the diameter of the tree crown, in cm;

[0015] (4) Determine the location of the planting hole based on the canopy diameter. The location of the planting hole is a point r cm away from the tree trunk.

[0016] r = D / 2 + 20

[0017] r is the distance between the hole and the tree trunk, and D is the diameter of the tree crown, both in cm;

[0018] (5) Calculate the tree age based on the trunk diameter, and then determine the corresponding fertilizer application amount based on the tree age.

[0019] m = d × a,

[0020] m is the tree age, d is the trunk diameter of the fruit tree, and a is the average growth factor of each type of fruit tree.

[0021] (6) Retrieve the corresponding fertilizer amount from the database according to the fruit tree variety and tree age. If there is no corresponding data in the database, manually enter the value and store it in the database.

[0022] (7) The vehicle-mounted hole-applying machine records the path and the results calculated above based on the positioning and navigation system to make quantitative holes for the fruit trees in the orchard at the corresponding locations, and applies fertilizer evenly into the hole according to the corresponding amount of fertilizer, and then covers it with soil.

[0023] Preferably, the positioning and navigation system includes a visual navigation module and a BeiDou navigation module.

[0024] Preferably, the diameter of the acupuncture hole is 30-40cm and the depth is 35-45cm.

[0025] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0026] This invention provides a precise fertilization method for fruit trees. It uses a positioning and navigation system and a fruit tree information acquisition system to obtain the location information and images of each fruit tree in the orchard. Image processing is then used to determine the trunk diameter and crown diameter of each tree. Based on this information, the scientific location, number of holes, and amount of fertilizer to be applied to each tree are determined, achieving precise quantitative fertilization, reducing environmental pollution caused by excessive fertilization, and improving fertilization efficiency. The navigation system, combined with an integrated hole-drilling machine, enables automatic positioning and hole-drilling fertilization, effectively reducing manual labor. Attached Figure Description

[0027] Figure 1 This is a flowchart of the process for the precision fertilization method for fruit trees of the present invention. Detailed Implementation

[0028] To better understand the present invention, specific details are provided below with reference to embodiments.

[0029] Example:

[0030] A method for precise fertilization of fruit trees based on a vehicle-mounted integrated hole-applying machine, wherein the vehicle-mounted integrated hole-applying machine includes a positioning and navigation module, an image acquisition module, an image data analysis module, a database module, and a hole-applying mechanism. The positioning and navigation module includes a visual navigation module and a Beidou navigation module, used to acquire the location of each fruit tree and plan the driving path; the image acquisition module includes a binocular stereo vision depth camera, used to acquire image information of the fruit trees; the image data analysis module is used to process the fruit tree images and calculate the trunk diameter and crown diameter information of the fruit trees; the database module is used to store the scientific fertilization amount for different varieties and ages of fruit trees, as well as the data information acquired or calculated by the positioning and navigation module, the image acquisition module, and the image data analysis module. The hole-applying mechanism includes a hole-applying module and a fertilization and soil-covering module, wherein the hole-applying module and the fertilization and soil-covering module are existing technologies, and their specific structures are not described in detail. The image data analysis module and the database module can be directly mounted on the vehicle-mounted integrated hole-applying machine, or they can be set up independently and communicate with the vehicle-mounted integrated hole-applying machine.

[0031] like Figure 1 As shown, the precise fertilization method for fruit trees includes the following steps:

[0032] 1. The vehicle-mounted hole-applying machine acquires the location information and images of each fruit tree in the orchard through a positioning and navigation module and an image acquisition module. Specifically, the machine travels within the orchard according to a pre-set path within the positioning and navigation module. During this journey, the image acquisition module activates a binocular stereo vision depth camera to capture panoramic images of each fruit tree and transmits the image information to the database module for storage. Simultaneously, the positioning and navigation module records the specific location of each fruit tree and transmits it to the database module for storage, facilitating subsequent hole-drilling and fertilization operations. To improve the positioning and navigation accuracy of the system, it includes a visual navigation module and a Beidou navigation module; the combination of these two ensures that the vehicle-mounted hole-applying machine travels along the planned path.

[0033] 2. The image data analysis module retrieves image information from the database module, processes the fruit tree images, obtains the trunk diameter and crown diameter information of each fruit tree, and stores them in the database module.

[0034] 3. Based on the tree canopy diameter information obtained in step 2, determine the number of application holes N. First, calculate the number of application holes n. The number of application holes N is an integer value of n.

[0035] n = π(D / 2) 2 / (D / 3)=0.75πD,

[0036] Therefore, N = [n] = [0.75πD],

[0037] D is the diameter of the tree crown, in cm.

[0038] 4. Determine the location of the planting hole based on the canopy diameter value. The location of the planting hole is a point r centimeters away from the tree trunk.

[0039] r = D / 2 + 20

[0040] r represents the distance between the application hole and the tree trunk, and D represents the diameter of the tree crown, both in cm. The application holes are located on a circle with the tree trunk as the center and r as the radius, and the holes are arranged as evenly as possible, i.e., evenly distributing the circumference. The preferred diameter of the application holes is 30-40 cm, and the depth is 35-45 cm.

[0041] 5. Calculate the tree age based on the trunk diameter value obtained in step 2, and then determine the corresponding fertilizer application amount from the tree age. The formula for calculating tree age m is as follows:

[0042] m = d × a,

[0043] Where d is the trunk diameter of the fruit tree, and a is the average growth factor of each type of fruit tree; the average growth factor value of each type of fruit tree can be retrieved from the database, which is usually the annual ring growth width of each type of fruit tree.

[0044] 6. Retrieve the appropriate fertilization amount for a single fruit tree from the database based on the fruit tree variety and age. If the corresponding data is not available in the database, manually enter the value based on experience and store it in the database module.

[0045] 7. The vehicle-mounted hole-applying machine records the path and calculates the results from the above steps based on the positioning and navigation system. It then makes a quantitative hole at the corresponding location for each fruit tree in the orchard, applies fertilizer evenly into each hole according to the corresponding amount, and covers it with soil to complete the fertilization work.

[0046] 8. The database module establishes a database for each orchard to record the fertilization and growth status of fruit trees, recording the fertilization status and growth data of each fruit tree for comparison and adjustment.

[0047] In step 2, the image data analysis module can use existing image processing methods to process the fruit tree image. In this embodiment, to improve image processing efficiency, an image analysis system software is used for image processing and analysis, including steps such as reading digital images, grayscale conversion, image denoising, and feature extraction. The image denoising step is based on a bounded mean oscillation space (BMO) edge detection optimization algorithm. The BMO algorithm is introduced into the PDE model to construct an image edge gradient detection optimization operator suitable for three-dimensional images. Specifically:

[0048] BMO, or Bounded Mean Vibration Model, probes boundary characteristics by determining a new derivative scheme and uses integral averaging to eliminate the influence of noise. This leads to the Z... Q Compared to methods that directly use the gradient magnitude, gradient operators are less susceptible to noise interference; and compared to gradient operators with Gaussian smoothing kernels, their algorithmic structure is simpler.

[0049] Suppose f(x) is a 1-D function, and we integrate it over the interval [xh, x+h] with x as the midpoint and h as the radius. If f(x) is Lebesgue integrable in the neighborhood of x, then the following phenomenon occurs:

[0050]

[0051] Integrating the right side of the equation into the integral, we obtain the following form:

[0052]

[0053] In the function f(x), points possessing such properties are called Lebesgue points. The BMO algorithm is introduced into the PDE model, and based on the 1-D structure of the Lebesgue points, its 3-D structure is derived. Assume Q(x,r,t) is a cube neighborhood with x as its midpoint and a side length of 2r, |Q(x,r,t)| represents the area of ​​this cube neighborhood, and u(x) is a function on the plane. Thus, the 3-D Lebesgue point structure is:

[0054]

[0055] Introducing an integral average into the integrand yields the 3-D BMO scheme:

[0056]

[0057] Regarding the relationship between the BMO scheme and gradients, by replacing the cube neighborhood Q(x,r,t) with a sphere B(x,r,t), the following equation can be proved:

[0058]

[0059] The above formula applies to the BMO form of the 3-D cube region Q(x,r,t), which is Z. Q Gradient operator:

[0060]

[0061] Z Q The gradient operator combats noise interference through quadratic averaging, while detecting more subtle boundary features with less computation and fewer steps. Therefore, BMO filtering achieves both effective denoising and good preservation of image details.

[0062] The precision fertilization method for fruit trees described in this embodiment acquires the location information and images of each fruit tree in the orchard through a positioning and navigation module and a fruit tree information acquisition module. The image processing module then obtains the trunk diameter and crown diameter information for each tree. Based on this information, the scientific location, number of holes, and amount of fertilizer to be applied for each tree are determined, achieving quantitative and precise fertilization, reducing environmental pollution caused by excessive fertilization, and improving fertilization efficiency. The navigation system, combined with the integrated hole-drilling machine, enables automatic positioning and hole-drilling fertilization, effectively reducing manual labor.

[0063] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for precision fertilization of fruit trees based on a vehicle-mounted integrated hole-applied fertilizer, characterized in that, The vehicle-mounted integrated hole-planting machine includes a positioning and navigation module, an image acquisition module, an image data analysis module, a database module, and a hole-planting mechanism. The positioning and navigation module includes a visual navigation module and a Beidou navigation module, used to acquire the location of each fruit tree and plan the driving path. The image acquisition module includes a binocular stereo vision depth camera, used to acquire fruit tree image information. The image data analysis module is used to process the fruit tree images and calculate the trunk diameter and crown diameter information of the fruit trees. The precise fertilization method for fruit trees includes the following steps: (1) The vehicle-mounted hole-applying integrated machine sequentially acquires the location information and three-dimensional image of each fruit tree in the orchard through the positioning and navigation module and the image acquisition module and transmits them to the database module; (2) The image data analysis module processes the fruit tree images, including reading digital images, grayscale processing, image denoising and feature extraction, to obtain the trunk diameter and crown diameter information of each fruit tree and store them in the database. The image denoising step is based on the Bounded Mean Oscillation Space (BMO) edge detection optimization algorithm. The BMO algorithm is introduced into the PDE model to construct an image edge gradient detection optimization operator suitable for 3D images. Specifically... Z Q (u,x,r) is the BMO form of the cube region Q(x,r,t); y,z is a function on the cube; Q(x,r,t) is the position information of the cube region; (3) Calculate the number of holes N based on the canopy diameter, where, N = [0.75πD], D is the diameter of the tree crown, in cm; (4) Determine the location of the planting hole based on the canopy diameter. The location of the planting hole is a point r cm away from the tree trunk. r＝D / 2+20， r is the distance between the hole and the tree trunk, and D is the diameter of the tree crown, both in cm; (5) Calculate the tree age based on the trunk diameter, and then determine the corresponding fertilizer application amount based on the tree age. m = d × a, m is the tree age, d is the trunk diameter of the fruit tree, and a is the average growth factor of each type of fruit tree. (6) Retrieve the corresponding fertilizer amount from the database according to the fruit tree variety and tree age. If there is no corresponding data in the database, manually enter the value and store it in the database. (7) The vehicle-mounted hole-applying machine records the path and the results calculated above based on the positioning and navigation system to make quantitative holes for the fruit trees in the orchard at the corresponding locations, and applies fertilizer evenly into the hole according to the corresponding amount of fertilizer, and then covers it with soil.

2. The method for precision fertilization of fruit trees based on a vehicle-mounted integrated hole fertilizer as described in claim 1, characterized in that: The diameter of the acupuncture hole is 30-40cm, and the depth is 35-45cm.

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