Tea tree germplasm resource nursery management method and system

Abstract

The invention discloses a tea tree germplasm resource garden management method, which adopts a tea tree germplasm resource garden management system consisting of a data storage module, a data processing module, a system operation module, a system display module and an external port module. Through overall plane data and block distribution data of a tea tree germplasm resource garden, meteorological station and soil moisture content information data, basic information data of tea tree germplasm resources entering the garden, germplasm resource agronomic characteristic original data and data processing, agronomic character mean values of vigorous tea tree germplasm resource states in the fourth, fifth and sixth years are converted into standard values; and comparing agronomic character data of the seventh year with a standard value, carrying out fixed-period tea tree data acquisition, and combining a scientific management mode of resource nursery soil and climate factors to realize effective management of dynamic growth of resources of the resource nursery.

Description

Technical Field

[0001] The invention relates to a method and system for managing germplasm resources in a tea tree germplasm resource garden, so as to solve the problem of dynamic growth management of tea tree resources in the tea tree resource garden. Background Art

[0002] In the field of plant genetics, germplasm resources (including variety resources, genetic resources and gene banks, etc.) have become an indispensable source of genes for species improvement due to their unique ecological adaptability and genetic diversity. With the construction of provincial and national germplasm resource nurseries, the preserved germplasm resources are becoming more and more abundant. For example, the Zhejiang Tea Germplasm Resource Nursery (Lishui), built by the patent application unit Lishui Academy of Agriculture and Forestry Sciences, has collected and preserved 3,500 sources of tea germplasm resources covering my country's 10 major tea-producing provinces (Zhejiang, Jiangxi, Hunan, etc.) and typical tea-producing countries (India, Kenya, Japan, etc.) as of December 2024. According to the plan of the applicant unit, the number of sources will increase year by year, and more than 5,000 will be preserved by 2030.

[0003] Currently, tea germplasm resources are primarily cultivated and preserved in the field. Differences in tea germplasm origins lead to significant variations in tea plant biological characteristics. As climate change changes, tea germplasm adaptability and biological characteristics differ from those of their original source. Efficient, accurate, and modern scientific management of the thousands or even tens of thousands of living tea germplasm resources within a nursery is crucial. Periodically and quickly monitoring the growth status of each germplasm within the nursery is crucial, providing scientific data for management units. Summary of the Invention

[0004] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art and to provide a method for managing a tea germplasm resource garden that can solve the technical problems of the large number of tea germplasm resources preserved in the garden, the differences in biological characteristics and the annual growth variation, and can monitor the dynamic growth of each germplasm in the garden and provide early warning of abnormalities.

[0005] In order to achieve the above-mentioned object, the present invention provides a tea germplasm resource garden management method, comprising a tea germplasm resource garden management system composed of a data storage module, a data processing module, a system operation module, a system display module, and an external port module, characterized in that the management method comprises the following steps:

[0006] (a) collecting the overall layout design data of the tea germplasm resource garden and the distribution data of each block and storing them in the data storage module;

[0007] (b) setting up a micro-meteorological station and a soil moisture monitoring instrument in the tea germplasm resource garden, collecting and storing the tea germplasm resource garden soil nutrient standard determination and three-year meteorological data mean values ​​including monthly maximum temperature, minimum temperature, monthly rainfall, and annual rainfall in a data storage module in the tea germplasm resource garden management system;

[0008] (c) collecting and storing data on basic information of tea germplasm resources entering the nursery, wherein the basic information of tea germplasm resources includes the origin of the tea germplasm, the name of the germplasm, and the digital number of the entry into the nursery;

[0009] (d) Collection of original data on agronomic characteristics of tea germplasm resources in the nursery: The tea germplasm resources were planted and cultivated for 3 years. Starting from the 4th year, data on agronomic characteristics of each tea germplasm were collected for 3 consecutive years. The agronomic characteristic data index of each tea germplasm resource in the nursery for three years was obtained. The mean of the data index was used as the basic standard value. The mean of the annual data index was used as the first-level data package of the unit data, and the monthly data index was used as the second-level data package.

[0010] (e) Method for processing raw data of agronomic characteristics of tea germplasm: (1) in step (d), agronomic characteristic data of tea germplasm resources entering the nursery are collected and stored in the data storage module of the tea germplasm resource nursery management system; (2) the data processing module of the tea germplasm resource nursery management system operates the raw data of agronomic characteristics of tea trees in the data storage module through the formula (change in agronomic trait index value of tea germplasm resources) to obtain agronomic trait index values ​​as data directly called by the system operation module of the tea germplasm resource nursery management system;

[0011] (f) connecting the data ports of the micro-meteorological station and the soil moisture monitoring instrument in the tea germplasm resource garden to the external port module of the tea germplasm resource garden management system;

[0012] (g) Through the periodic collection of agronomic characteristics data of each germplasm resource stored in the tea germplasm resource nursery, data processing, analysis and management, the dynamic growth of germplasm resources in the tea germplasm resource nursery can be intuitively reflected through the tea germplasm resource nursery management system interface, thereby realizing efficient and scientific management of the tea germplasm resource nursery.

[0013] In the step (a), the overall planar layout design data of the tea germplasm resource garden and the distribution data of each block are collected, and the specific operations of the step are:

[0014] (1) Resource garden plan: The plan design data of the germplasm resource garden is collected, and the planned and designed germplasm resource garden plan design data is stored in the data storage module of the tea germplasm resource garden management system;

[0015] (2) Tea germplasm block: After each tea germplasm seedling is planted in the germplasm resource garden, poles are inserted at the four corners of each tea germplasm resource, and the location and orientation of the block are initially located and marked using a drone;

[0016] (3) Identification of tea germplasm resources: The location data of each germplasm block collected and saved in step (2) is manually numbered and labeled with names to obtain the accurate coordinate data of each germplasm resource in the germplasm resource garden park.

[0017] The specific operations of the steps of collecting data on agronomic traits of germplasm resources and establishing a database on agronomic traits of germplasm resources are as follows:

[0018] (1) Accurate block data collection for each germplasm entering the nursery: Collect data on each germplasm resource entering the nursery. A red-marked pole is inserted at the four corners of each germplasm. The drone accurately collects the location and area of ​​each germplasm entering the nursery, and the collected data is saved in the data storage module of the tea germplasm resource nursery management system;

[0019] (2) Collection of tea germplasm basic agronomic traits data: After 3 years of tending, young tea germplasm resources are grown to the standard state after being preserved and established in the nursery. Starting from the 4th year, in the middle of each month in clear weather, drones equipped with high-resolution multispectral image acquisition equipment are used to collect tea germplasm resource image data, including the germplasm crown color value, leaf index, and canopy density index.

[0020] (3) Classification and index value of tea germplasm agronomic traits data: The tea germplasm agronomic traits data are classified into the first-level data package with annual data as the first-level data package and the monthly data as the second-level data package;

[0021] The change of agronomic trait index value of tea germplasm resources refers to the following formula: Agronomic trait change (N) = (C*0.5)+(L*0.3)+(D*0.2)

[0022] Among them: Accession crown color value: a numerical indicator that describes and quantifies the color characteristics of the plant canopy, represented by C, with a weight of 50%;

[0023] Leaf cover index (LAI): The degree of leaf cover in the canopy, expressed as L, is defined as the ratio of the total leaf area to the ground surface area, with a weight of 30%;

[0024] Canopy density index: The compactness of the arrangement of leaves and branches inside the canopy, expressed as D, is defined as the canopy void ratio, with a weight of 20%.

[0025] The image data of tea germplasm resources collected in the 4th, 5th and 6th years were used to calculate the annual average value of agronomic traits changes in the 3-year period and the monthly average value of the corresponding months. The annual average value was used as the annual basic standard value of the germplasm, and the monthly average value was used as the monthly basic standard value of the germplasm.

[0026] (4) The data ports of the micro-meteorological station and soil moisture monitoring instrument in the resource garden are connected to the tea germplasm resource garden management system;

[0027] The tea germplasm resource garden is well designed and planned. Soil in the resource garden is collected according to standards to analyze soil nutrient composition and obtain data. The micro-meteorological station in the resource garden collects annual and monthly meteorological elements for the past three years as the standard. The monthly average temperature, maximum and minimum temperature, and rainfall are used as the standard data for soil and meteorology in the resource garden.

[0028] The data ports of the micro-meteorological station and soil moisture monitor in the resource garden are connected to the tea germplasm resource garden management system, and the soil and meteorological information of the resource garden are observed in real time through the micro-meteorological station and soil moisture monitor.

[0029] During the specific operation of the above steps, tea tree germplasm resources are collected and preserved in the resource garden for 3 years. In the 4th year, the germplasm resources enter the vigorous growth stage. Labels are inserted at the four corners of each germplasm resource block, and the top of the label is painted in a clear red color. Two adjacent germplasm resources are separated by a white ribbon. The image data of tea tree germplasm resources (germplasm crown color value; leaf index; canopy density index) are collected by drone equipped with high-resolution multispectral image acquisition equipment. It takes at least three years to establish the original data of germplasm resources. The germplasm resources are planted for 3 years. In the middle of each month in the 4th, 5th and 6th years, the agronomic characteristics and growth status data of each germplasm resource are collected. The agronomic trait change calculation formula (N) = (C*0.5) + (L*0.3) + (D*0.2) is used to calculate the average value of 3 years as the basic standard value of each germplasm resource. At the same time, when new germplasm resources enter the resource garden, data can be added according to the above steps to establish the data information of the germplasm resources.

[0030] The tea germplasm resource garden management method comprises the following steps:

[0031] (1) The data stored in the data storage module of the tea germplasm resource garden management system includes (1) basic information data of tea germplasm resources, including the origin of tea germplasm, germplasm name, germplasm number, trait name, gene information, and trait; (2) original image data of agronomic data of collected germplasm resources; (3) annual basic standard value and monthly basic standard value according to the following step (2); (4) meteorological and soil moisture data in the resource garden;

[0032] (2) Data processing module: The annual and monthly image raw data of tea germplasm agronomic traits collected by UAVs are used to calculate the annual and monthly basic standard values ​​through the data processing module of the tea germplasm resource garden management system;

[0033] (3) collecting annual and monthly image raw data of agronomic traits of tea germplasm in the 4th, 5th, 6th and 7th years, calculating the annual data value and monthly data value through the data processing module of the tea germplasm resource garden management system, and comparing them with the annual basic standard value and monthly basic standard value obtained in step (2), and monitoring and comparing the growth status of each tea germplasm resource;

[0034] (4) Analysis of tea germplasm growth status: set the standard value S, the measured value M, and the difference D. When D is 10%, it is normal; 10%-20% is slightly abnormal; 20%-30% is moderately abnormal; and greater than 30% is severely abnormal;

[0035] Standard value: S; measured value: M, calculate the difference percentage:

[0036] The difference percentage D was calculated by the following formula: D = [(MS) / S] × 100%

[0037] The difference D was classified into the following levels: normal: 10% ≤ D < 10%; mildly abnormal: 10% ≤ D < 20%; moderately abnormal: 20% ≤ D < 30%; severely abnormal: D ≥ 30%;

[0038] The mean agronomic trait value S for germplasm data collected and processed in the fourth, fifth, and sixth years is used as the standard value. Starting in the seventh year, annual and monthly data M are compared to the standard value S, and the germplasm health status is determined by combining data from the micro-meteorological station and soil moisture monitoring instrument within the resource garden. Starting in the seventh year, data is collected monthly using the above steps as the primary data folder and monthly as the secondary data folder. Data is then compared to the basic standard value calculated using the formula D = [(MS) / S] × 100% in the analysis module of the tea germplasm resource garden management system. Dynamic observation and analysis are then conducted on the real-time growth of each germplasm in the tea germplasm resource garden.

[0039] The present invention adopts a data layering model and is based on the layered architecture technology to realize the management of the dynamic growth data of tea tree germplasm preserved in the germplasm resource nursery. At the same time, it combines the soil and climate observation data of the germplasm resource nursery to improve the efficiency of germplasm resource management and ensure the accurate monitoring and management of the growth health status of the preserved germplasm resources.

[0040] The tea germplasm resource garden management method provided by the present invention processes the overall plane data and distribution data of each block of the tea germplasm resource garden, combines weather station and soil moisture information data, basic information data of tea germplasm resources entering the garden, and original data of agronomic characteristics of the germplasm resources, and data. The agronomic trait mean values ​​of the vigorous tea germplasm resources in the 4th, 5th, and 6th years are converted into standard values, and the agronomic trait data in the 7th year are compared with the standard values. Fixed-period tea tree data collection and a scientific management model combining soil and climatic factors of the resource garden are carried out to achieve effective management of the dynamic growth of resources in the resource garden. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The present invention implements the collection of basic data on soil, weather and germplasm in the tea germplasm resource garden;

[0042] Figure 2 The present invention implements the collection of agronomic trait data of tea germplasm resources;

[0043] Figure 3 This is a data structure diagram of the tea germplasm resource garden management system implemented by the present invention;

[0044] Figure 4 It is a schematic diagram of the basic structure of the tea germplasm resource garden management system implemented in the present invention. DETAILED DESCRIPTION

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0046] Example:

[0047] The number of germplasm resources collected and preserved in the tea germplasm resource garden and the project are huge. It is impossible to collect and preserve all tea germplasm resources within one year. They are all collected year by year and planted step by step according to the blocks divided by the resource garden. This embodiment takes the collection and preservation of 500 tea germplasm resources for planting in the first phase and the first district of the resource garden as an example to explain the implementation process of the present invention in detail. This embodiment provides a tea germplasm resource garden management method, including a tea germplasm resource garden management system composed of a data storage module, a data processing module, a system operation module, a system display module, and an external port module. The management method steps are as follows:

[0048] (a) collecting the overall layout design data of the tea germplasm resource garden and the distribution data of each block and storing them in the data storage module;

[0049] (b) setting up a micro-meteorological station and a soil moisture monitoring instrument in the tea germplasm resource garden, collecting and storing the tea germplasm resource garden soil nutrient standard determination and three-year meteorological data mean values ​​including monthly maximum temperature, minimum temperature, monthly rainfall, and annual rainfall in a data storage module in the tea germplasm resource garden management system;

[0050] (c) collecting and storing data on basic information of tea germplasm resources entering the nursery, wherein the basic information of tea germplasm resources includes the origin of the tea germplasm, the name of the germplasm, and the digital number of the entry into the nursery;

[0051] (d) Collection of original data on agronomic characteristics of tea germplasm resources in the nursery: The tea germplasm resources were planted and cultivated for 3 years. Starting from the 4th year, data on agronomic characteristics of each tea germplasm were collected for 3 consecutive years. The agronomic characteristic data index of each tea germplasm resource in the nursery for three years was obtained. The mean of the data index was used as the basic standard value. The mean of the annual data index was used as the first-level data package of the unit data, and the monthly data index was used as the second-level data package.

[0052] (e) Method for processing raw data of agronomic characteristics of tea germplasm: (1) in step (d), agronomic characteristic data of tea germplasm resources entering the nursery are collected and stored in the data storage module of the tea germplasm resource nursery management system; (2) the data processing module of the tea germplasm resource nursery management system operates the raw data of agronomic characteristics of tea trees in the data storage module through the formula (change in agronomic trait index value of tea germplasm resources) to obtain agronomic trait index values ​​as data directly called by the system operation module of the tea germplasm resource nursery management system;

[0053] (f) connecting the data ports of the micro-meteorological station and the soil moisture monitoring instrument in the tea germplasm resource garden to the external port module of the tea germplasm resource garden management system;

[0054] (g) Through the periodic collection of agronomic characteristics data of each germplasm resource stored in the tea germplasm resource nursery, data processing, analysis and management, the dynamic growth of germplasm resources in the tea germplasm resource nursery can be intuitively reflected through the tea germplasm resource nursery management system interface, thereby realizing efficient and scientific management of the tea germplasm resource nursery.

[0055] In the step (a), the overall planar layout design data of the tea germplasm resource garden and the distribution data of each block are collected, and the specific operations of the step are:

[0056] (1) Resource garden plan: The plan design data of the germplasm resource garden is collected, and the planned and designed germplasm resource garden plan design data is stored in the data storage module of the tea germplasm resource garden management system;

[0057] (2) Tea germplasm block: After each tea germplasm seedling is planted in the germplasm resource garden, poles are inserted at the four corners of each tea germplasm resource, and the location and orientation of the block are initially located and marked using a drone;

[0058] (3) Identification of tea germplasm resources: The location data of each germplasm block collected and saved in step (2) is manually numbered and labeled with names to obtain the accurate coordinate data of each germplasm resource in the germplasm resource garden park.

[0059] The specific operations of the steps of collecting data on agronomic traits of germplasm resources and establishing a database on agronomic traits of germplasm resources are as follows:

[0060] (1) Accurate block data collection for each germplasm entering the nursery: Collect data on each germplasm resource entering the nursery. A red-marked pole is inserted at the four corners of each germplasm. The drone accurately collects the location and area of ​​each germplasm entering the nursery, and the collected data is saved in the data storage module of the tea germplasm resource nursery management system;

[0061] (2) Collection of tea germplasm basic agronomic traits data: After 3 years of tending, young tea germplasm resources are grown to the standard state after being preserved and established in the nursery. Starting from the 4th year, in the middle of each month in clear weather, drones equipped with high-resolution multispectral image acquisition equipment are used to collect tea germplasm resource image data, including the germplasm crown color value, leaf index, and canopy density index.

[0062] (3) Classification and index value of tea germplasm agronomic traits data: The tea germplasm agronomic traits data are classified into the first-level data package with annual data as the unit and the monthly data as the second-level data package;

[0063] The change of agronomic trait index value of tea germplasm resources refers to the following formula: Agronomic trait change (N) = (C*0.5)+(L*0.3)+(D*0.2)

[0064] Among them: Accession crown color value: a numerical indicator that describes and quantifies the color characteristics of the plant canopy, represented by C, with a weight of 50%;

[0065] Leaf cover index (LAI): The degree of leaf cover in the canopy, expressed as L, is defined as the ratio of the total leaf area to the ground surface area, with a weight of 30%;

[0066] Canopy density index: The compactness of the arrangement of leaves and branches inside the canopy, expressed as D, is defined as the canopy void ratio, with a weight of 20%.

[0067] The image data of tea germplasm resources collected in the 4th, 5th and 6th years were used to calculate the annual average value of agronomic traits changes in the 3-year period and the monthly average value of the corresponding months. The annual average value was used as the annual basic standard value of the germplasm, and the monthly average value was used as the monthly basic standard value of the germplasm.

[0068] (4) The data ports of the micro-meteorological station and soil moisture monitoring instrument in the resource garden are connected to the tea germplasm resource garden management system;

[0069] The tea germplasm resource garden is well designed and planned. Soil in the resource garden is collected according to standards to analyze soil nutrient composition and obtain data. The micro-meteorological station in the resource garden collects annual and monthly meteorological elements for the past three years as the standard. The monthly average temperature, maximum and minimum temperature, and rainfall are used as the standard data for soil and meteorology in the resource garden.

[0070] The data ports of the micro-meteorological station and soil moisture monitor in the resource garden are connected to the tea germplasm resource garden management system, and the soil and meteorological information of the resource garden are observed in real time through the micro-meteorological station and soil moisture monitor.

[0071] During the specific operation of the above steps, tea tree germplasm resources are collected and preserved in the resource garden for 3 years. In the 4th year, the germplasm resources enter the vigorous growth stage. Labels are inserted at the four corners of each germplasm resource block, and the top of the label is painted in a clear red color. Two adjacent germplasm resources are separated by a white ribbon. The image data of tea tree germplasm resources (germplasm crown color value; leaf index; canopy density index) are collected by drone equipped with high-resolution multispectral image acquisition equipment. It takes at least three years to establish the original data of germplasm resources. The germplasm resources are planted for 3 years. In the middle of each month in the 4th, 5th and 6th years, the agronomic characteristics and growth status data of each germplasm resource are collected. The agronomic trait change calculation formula (N) = (C*0.5) + (L*0.3) + (D*0.2) is used to calculate the average value of 3 years as the basic standard value of each germplasm resource. At the same time, when new germplasm resources enter the resource garden, data can be added according to the above steps to establish the data information of the germplasm resources.

[0072] The tea germplasm resource garden management method comprises the following steps:

[0073] (1) The data stored in the data storage module of the tea germplasm resource garden management system includes (1) basic information data of tea germplasm resources, including the origin of tea germplasm, germplasm name, germplasm number, trait name, gene information, and trait; (2) original image data of agronomic data of collected germplasm resources; (3) annual basic standard value and monthly basic standard value according to the following step (2); (4) meteorological and soil moisture data in the resource garden;

[0074] (2) Data processing module: The annual and monthly image raw data of tea germplasm agronomic traits collected by UAVs are used to calculate the annual and monthly basic standard values ​​through the data processing module of the tea germplasm resource garden management system;

[0075] (3) collecting annual and monthly image raw data of agronomic traits of tea germplasm in the 4th, 5th, 6th and 7th years, calculating the annual data value and monthly data value through the data processing module of the tea germplasm resource garden management system, and comparing them with the annual basic standard value and monthly basic standard value obtained in step (2), and monitoring and comparing the growth status of each tea germplasm resource;

[0076] (4) Analysis of tea germplasm growth status: set standard value S, measured value M, and difference D. When D is 10%, it is normal; 10%-20% is slightly abnormal; 20%-30% is moderately abnormal; and greater than 30% is severely abnormal; standard value: S; measured value: M, calculate the difference percentage:

[0077] The difference percentage D was calculated by the following formula: D = [(MS) / S] × 100%

[0078] The difference D was classified into the following levels: normal: 10% ≤ D < 10%; mildly abnormal: 10% ≤ D < 20%; moderately abnormal: 20% ≤ D < 30%; severely abnormal: D ≥ 30%;

[0079] The mean agronomic trait value S for germplasm data collected and processed in the fourth, fifth, and sixth years is used as the standard value. Starting in the seventh year, annual and monthly data M are compared to the standard value S, and the germplasm health status is determined by combining data from the micro-meteorological station and soil moisture monitoring instrument within the resource garden. Starting in the seventh year, data is collected monthly using the above steps as the primary data folder and monthly as the secondary data folder. Data is then compared to the basic standard value calculated using the formula D = [(MS) / S] × 100% in the analysis module of the tea germplasm resource garden management system. Dynamic observation and analysis are then conducted on the real-time growth of each germplasm in the tea germplasm resource garden.

[0080] The abnormal germplasm resources displayed by the system are manually analyzed and processed on site, and the abnormal germplasm conditions are analyzed in combination with the data from the soil detector and meteorological station in the resource garden. The real-time growth conditions of each germplasm in the tea germplasm resource garden are dynamically observed and analyzed.

[0081] The tea germplasm resource garden management method provided in this embodiment can not only periodically monitor the growth status of the germplasm preserved in the resource garden, but also provide efficient early warning reminders for abnormal germplasm, effectively manage germplasm resources, and promptly prevent the loss of germplasm resources due to natural factors, pests and diseases, and management factors.

[0082] The tea germplasm resource garden management method provided in this embodiment can design a separate data module for the germplasm resource data in the initial stage, which can specifically include the Chinese and English names of the germplasm resource, the germplasm resource number, the longitude and latitude of the origin, the basic trait type, the basic resistance, etc.; the basic data of the germplasm resource can also include: the crop type of the germplasm resource, the germplasm resource name, the germplasm resource number, the suitable planting range, the longitude and latitude, the trait name, the gene information, the trait grouping, the trait template, the reminder type, etc.

[0083] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for managing a tea germplasm resource garden, comprising a tea germplasm resource garden management system consisting of a data storage module, a data processing module, a system operation module, a system display module, and an external port module, characterized in that The management method steps are: (a) Collect the overall layout design data of the tea germplasm resource garden and the distribution data of each block and store them in the data storage module storage; (b) A micro-meteorological station and soil moisture monitoring instrument were set up in the tea germplasm resource garden to measure the soil nutrient standard of the tea germplasm resource garden and collect the three-year average meteorological data including the monthly maximum temperature, minimum temperature, monthly rainfall and annual rainfall, and store them in the tea germplasm resource garden. In the data storage module of the tree germplasm resource garden management system; (c) Collection and storage of basic information data of tea germplasm resources entering the nursery, including the basic information of tea germplasm resources including the source of tea germplasm Land, germplasm name, and nursery number; (d) Collection of original data on agronomic characteristics of tea germplasm resources in the nursery: The tea germplasm resources were planted and cultivated for 3 years. Starting from the 4th year, data on agronomic characteristics of each tea germplasm were collected for 3 consecutive years. The agronomic characteristic data index of each tea germplasm resource in the nursery for three years was obtained. The mean of the data index was used as the basic standard value. The mean of the annual data index was used as the first-level data package of the unit data, and the monthly data index was used as the second-level data package. (e) Method for processing raw data of agronomic characteristics of tea germplasm: (1) in step (d), agronomic characteristic data of tea germplasm resources collected in the nursery are stored in a data storage module of a tea germplasm resource nursery management system; (2) The data processing module of the tea germplasm resource garden management system processes the original data of the tea tree agronomic characteristics in the data storage module through the formula (change in the agronomic trait index value of the tea tree germplasm resource) to obtain the agronomic trait index value as the data directly called by the system operation module of the tea tree germplasm resource garden management system; (f) connecting the data ports of the micro-meteorological station and the soil moisture monitoring instrument in the tea germplasm resource garden to the external port module of the tea germplasm resource garden management system; (g) Through the periodic collection of agronomic characteristics data of each germplasm resource stored in the tea germplasm resource nursery, data processing, analysis and management, the dynamic growth of germplasm resources in the tea germplasm resource nursery can be intuitively reflected through the tea germplasm resource nursery management system interface, thereby realizing efficient and scientific management of the tea germplasm resource nursery.

2. A tea tree germplasm resource garden management method according to claim 1, characterized in that In the step (a), the overall planar layout design data of the tea germplasm resource garden and the distribution data of each block are collected, and the specific operations of the step are: (1) Resource garden plan: The plan design data of the germplasm resource garden is collected, and the planned and designed germplasm resource garden plan design data is stored in the data storage module of the tea germplasm resource garden management system; (2) Tea germplasm block: After each tea germplasm seedling is planted in the germplasm resource garden, poles are inserted at the four corners of each tea germplasm resource, and the location and orientation of the block are initially located and marked using a drone; (3) Identification of tea germplasm resources: The location data of each germplasm block collected and saved in step (2) is manually numbered and labeled with names to obtain the accurate coordinate data of each germplasm resource in the germplasm resource garden park.

3. A tea tree germplasm resource garden management method according to claim 1, characterized in that The specific operations of the steps of collecting data on agronomic traits of germplasm resources and establishing a database on agronomic traits of germplasm resources are as follows: (1) Accurate block data collection for each germplasm entering the nursery: Collect data on each germplasm resource entering the nursery. A red-marked pole is inserted at the four corners of each germplasm. The drone accurately collects the location and area of ​​each germplasm entering the nursery, and the collected data is saved in the data storage module of the tea germplasm resource nursery management system; (2) Collection of tea germplasm basic agronomic traits data: After 3 years of tending, young tea germplasm resources are grown to the standard state after being preserved and established in the nursery. Starting from the 4th year, in the middle of each month in clear weather, drones equipped with high-resolution multispectral image acquisition equipment are used to collect tea germplasm resource image data, including the crown color value and leaf index. canopy density index; (3) Classification and index value of tea germplasm agronomic traits data: The tea germplasm agronomic traits data are classified into the first-level data package with annual data as the first-level data package and the monthly data as the second-level data package; The changes in the agronomic trait index values ​​of tea germplasm resources refer to the following formula: Agronomic trait change (N) = (C*0.5)+(L*0.3)+(D*0.2) Wherein: Germplasm crown color value: a numerical indicator that describes and quantifies the color characteristics of the plant canopy, represented by C, with a weight of 50%; Leaf cover index (LAI): The degree of leaf cover in the canopy, expressed as L, is defined as the ratio of the total leaf area to the ground surface area, with a weight of 30%; Canopy density index: The degree of compactness of the arrangement of leaves and branches within the canopy, represented by D, is defined as the canopy void ratio, with a weight of 20%. For the tea germplasm image data collected in the 4th, 5th, and 6th years, the annual mean of agronomic trait changes over a 3-year period and the monthly mean of the corresponding months were calculated, with the annual mean value calculated as the annual standard value for the germplasm, and the monthly mean value as the monthly standard value for the germplasm. (4) The data ports of the micro-meteorological station and soil moisture monitoring instrument in the resource garden are connected to the tea germplasm resource garden management system; The tea germplasm resource garden is well designed and planned. Soil in the resource garden is collected according to standards to analyze soil nutrient composition and obtain data. The micro-meteorological station in the resource garden collects annual and monthly meteorological elements for the past three years as the standard. The monthly average temperature, maximum and minimum temperature, and rainfall are used as the standard data for soil and meteorology in the resource garden. The data ports of the micro-meteorological station and soil moisture monitor in the resource garden are connected to the tea germplasm resource garden management system, and the soil and meteorological information of the resource garden are observed in real time through the micro-meteorological station and soil moisture monitor.

4. A tea germplasm resource garden management method according to claim 1, characterized in that The tea germplasm resource garden management method comprises the following steps: (1) The data stored in the data storage module of the tea germplasm resource garden management system includes (1) basic information data of tea germplasm resources, including the origin of tea germplasm, germplasm name, germplasm number, trait name, gene information, and trait; (2) original image data of agronomic data of collected germplasm resources; (3) annual basic standard value and monthly basic standard value according to the following step (2); (4) meteorological and soil moisture data in the resource garden; (2) Data processing module: The annual and monthly image raw data of tea germplasm agronomic traits collected by UAVs are used to calculate the annual and monthly basic standard values ​​through the data processing module of the tea germplasm resource garden management system; (3) collecting annual and monthly image raw data of agronomic traits of tea germplasm in the 4th, 5th, 6th and 7th years, calculating the annual data value and monthly data value through the data processing module of the tea germplasm resource garden management system, and comparing them with the annual basic standard value and monthly basic standard value obtained in step (2), and monitoring and comparing the growth status of each tea germplasm resource; (4) Analysis of tea germplasm growth status: set the standard value S, the measured value M, and the difference D. When D is 10%, it is normal; 10%-20% is slightly abnormal; 20%-30% is moderately abnormal; and greater than 30% is severely abnormal; Standard value: S; Measured value: M, calculate the percentage difference: The difference percentage D was calculated by the following formula: D = [(MS) / S] × 100% The difference D was classified into the following levels: normal: 10% ≤ D < 10%; mildly abnormal: 10% ≤ D < 20%; moderately abnormal: 20% ≤ D < 30%; severely abnormal: D ≥ 30%; Among them: the average agronomic trait of the germplasm data collected and processed in the 4th, 5th and 6th years is the standard value S. Starting from the 7th year, the annual and monthly collected data M are compared with the standard value S, and the health status of the germplasm is judged in combination with the data from the micro-meteorological station and soil moisture monitoring instrument in the resource garden.

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