Intelligent citrus planting picking management system and method

Abstract

The invention belongs to the technical field of agricultural planting, and discloses an intelligent citrus planting and picking management system and method.In the citrus growing season, a data acquisition module acquires data in real time and transmits the data to a data analysis processing module, and after analysis, an intelligent decision module generates a fertilization instruction and an irrigation instruction; the execution control module controls the fertilization equipment and the irrigation equipment to perform periodic fertilization and irrigation, and the fertilization and irrigation period is determined according to the soil type, the local meteorological data and the citrus tree growth stage; when the data analysis processing module finds that citrus leaves have disease and pest symptoms through image recognition, the intelligent decision-making module recommends the corresponding prevention and control pesticide amount, the execution control module controls the disease and pest prevention and control equipment to perform pesticide application operation, and the camera continuously shoots fruit images near the picking season. And the data analysis processing module judges the fruit maturity through image analysis, and when the maturity is qualified, the picking robot is controlled to pick.

Description

Technical Field

[0001] The present invention belongs to the technical field of agricultural planting, and in particular relates to an intelligent citrus planting and picking management system and method. Background Art

[0002] Citrus is the world's largest fruit, and China is one of the main producing countries, and the output of citrus is increasing year by year. The southwest region has suitable climatic conditions. It is the only citrus-free area in my country and the core area of ​​the "Citrus Advantage Industrial Belt in the Middle and Lower Reaches of the Yangtze River", and occupies an important position in the development of the country's citrus industry.

[0003] The current citrus planting supervision system is mostly simple. It does not take into account that citrus growth is a continuous process. From growth to harvesting, it will encounter various meteorological and disease problems. It is impossible to independently regulate the fertilization, irrigation and pest control during the citrus growth process based on these problems, resulting in the quality and yield of citrus being affected. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent citrus planting and picking management system and method to solve the problems faced by the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An intelligent citrus planting and picking management system, comprising: a data acquisition module, a data analysis and processing module, an intelligent management module and an execution control module;

[0007] The data acquisition module includes a soil sensor, a meteorological sensor, and a camera. The soil sensor is used to collect soil parameter information in real time; the meteorological sensor is used to collect meteorological data in real time; and the camera is used to photograph the growth status of citrus trees, including pest and disease conditions and fruit maturity image information.

[0008] The data analysis and processing module is used to receive the data transmitted by the data acquisition module, and to determine whether the soil fertility needs to be supplemented and whether the soil water needs to be supplemented by analyzing the soil parameters and meteorological data; and to identify the pest information and the maturity of the fruit in combination with the image captured by the camera;

[0009] The intelligent management module generates corresponding planting and harvesting management decisions based on the results of the data analysis and processing module;

[0010] The execution control module includes irrigation equipment, fertilization equipment, pest control equipment and a picking robot, which is used to execute corresponding decisions based on planting and picking management decisions.

[0011] As a further description of the solution of the present invention, the working process of the data acquisition module includes:

[0012] Soil sensors were evenly distributed in the citrus grove, with a depth of 10-20 cm to accurately collect soil parameter information;

[0013] Install weather sensors in open, well-ventilated locations that represent the overall weather conditions in the citrus orchard to accurately collect weather information;

[0014] Installing a camera above the citrus tree can clearly capture every part of the tree and ensure the integrity of image acquisition.

[0015] As a further description of the solution of the present invention, the specific working process of the data analysis and processing module includes:

[0016] Step S10, obtaining soil fertilization decision based on soil parameters and meteorological data;

[0017] Step S20, obtaining soil irrigation decision based on soil parameter information and meteorological data;

[0018] Step S30, obtaining pest control decisions based on citrus tree leaf image information;

[0019] Step S40, obtaining a picking decision based on the citrus fruit image information.

[0020] As a further description of the solution of the present invention, the specific process of step S10 includes:

[0021] Obtain soil parameter information and compare all soil parameter information with the target threshold set by the system. If any soil parameter information is lower than the target threshold, immediately add the fertilizer corresponding to the parameter information. If no soil parameter information is lower than the target threshold, predict the current soil fertilization cycle.

[0022] As a further description of the scheme of the present invention, the specific process of predicting the current soil fertilization cycle includes:

[0023] Construct the mathematical calculation model of the current soil fertilization cycle, the expression is:

[0024] ;

[0025] Where k is the conversion coefficient, is the coefficient of the first growth stage, S is the current soil fertility index, is the environmental coefficient, F is the fertilization efficiency coefficient, Fertilize the soil for the current cycle;

[0026] The soil fertility index S can be obtained by fitting the soil parameter information, and the expression is:

[0027] ;

[0028] Where n is the number of soil parameters collected, is the data of the i-th soil parameter, is the standard data of the i-th soil parameter set by the system, is the weight coefficient corresponding to the i-th soil parameter, where i belongs to n, is the adjustment factor, used to adjust S to the range ;

[0029] The first growth stage coefficient C is assigned according to the current crop growth stage, and the value range of C is , when the citrus is in the spring shoot growth period, C=0.3, when the citrus is in the flowering period, C=0.15, when the citrus is in the young fruit stage, C=0.2, when the citrus is in the fruit expansion period, C=0.25, when the citrus is in the fruit maturity period, C=0.1;

[0030] The environmental coefficient E can be obtained by fitting the environmental parameter information, and the expression is:

[0031] ;

[0032] In the formula, is the average ambient temperature during the citrus growth period, is the average environmental humidity during the citrus growth period, is the average ambient light intensity during the citrus growth period, , and are the weight coefficients corresponding to ambient temperature, ambient humidity and ambient light intensity, is the adjustment coefficient of the exponential function, is the adjustment factor used to Adjust to range ;

[0033] Construct a mathematical model of fertilization efficiency coefficient F, the expression is:

[0034] ;

[0035] In the formula, is the amount of fertilizer for the jth nutrient, For soil nutrients after fertilization, For soil nutrients before fertilization, The amount of fertilizer nutrient, j belongs to m, is the weight coefficient corresponding to the jth nutrient, is the adjustment factor used to Adjust to range ;

[0036] Said , and Based on experimental data.

[0037] As a further description of the solution of the present invention, the specific process of step S20 includes:

[0038] The soil moisture content information is obtained and compared with the target threshold set by the system. If the moisture content information is lower than the target threshold, water is added immediately. If the moisture content information is not lower than the target threshold, the current soil irrigation cycle is predicted.

[0039] As a further description of the solution of the present invention, the specific process of predicting the current soil irrigation cycle includes:

[0040] Construct the mathematical calculation model of the current soil irrigation cycle, the expression is:

[0041] ;

[0042] In the formula, is the conversion coefficient, A is the coefficient of the second growth stage, B is the crop transpiration coefficient, and D is the soil water consumption coefficient;

[0043] The second growth stage coefficient A is assigned according to the current crop growth stage, and the value range of A is , when the citrus is in the spring shoot growth period, A=0.1, when the citrus is in the flowering period, A=0.15, when the citrus is in the young fruit stage, A=0.25, when the citrus is in the fruit expansion period, A=0.4, when the citrus is in the fruit maturity period, A=0.1;

[0044] The crop transpiration coefficient B is obtained by direct measurement, and the expression is:

[0045] ;

[0046] In the formula, is the current stem flow rate, is the current citrus leaf area, is the adjustment factor used to Adjust to range ;

[0047] Construct the mathematical model of soil moisture coefficient D, the expression is:

[0048] ;

[0049] In the formula, is the amount of irrigation water, is the soil moisture after irrigation, is the soil moisture before irrigation, is the adjustment factor used to Adjust to range ;

[0050] Said , and Based on experimental data.

[0051] As a further description of the solution of the present invention, the specific process of step S30 includes:

[0052] Collect citrus leaf image data and input them into a trained pest and disease recognition model. If the output result is that there is no pest and disease, there is no need to carry out pest and disease control. If the output result is that there is pest and disease, calculate the control parameters, and the control parameters include the severity index of pest and disease and the amount of pesticide used.

[0053] The pest severity index is based on the formula Get, where The area of ​​lesions, is the total leaf area, and the pesticide dosage is obtained based on the formula pesticide dosage = basic dosage * pest and disease severity index.

[0054] As a further description of the solution of the present invention, the specific process of step S40 includes:

[0055] Collect citrus tree image data and input them into the trained fruit maturity recognition model. If the output maturity is above 85%, arrange for picking in the near future.

[0056] A method for intelligent citrus planting and picking management, the method comprising the following steps:

[0057] Step S1, the data acquisition module continuously collects data on soil, weather and citrus tree growth conditions at set time intervals, and transmits the data to the data analysis and processing module in real time.

[0058] Step S2: The data analysis and processing module cleans, organizes and analyzes the collected data;

[0059] Step S3, the intelligent decision-making module formulates specific planting and harvesting decisions based on the results of the data analysis and processing module, and the decision-making content includes fertilization, irrigation, pest control, and harvesting;

[0060] Step S4, the execution control module receives the instruction of the intelligent decision module and controls the corresponding equipment to operate;

[0061] Step S5: After executing the operation, the data acquisition module periodically collects relevant data, the data analysis and processing module periodically analyzes the data, the intelligent decision-making module adjusts the decision according to the latest analysis results, and the execution control module executes the operation again according to the adjusted decision, forming a closed-loop management.

[0062] Beneficial effects of the present invention:

[0063] 1. Improve planting accuracy: Through real-time monitoring and precise analysis of soil, weather and citrus tree growth conditions, precise fertilization, precise irrigation and precise pest and disease control can be achieved, providing the best growth environment for citrus trees and improving citrus yield and quality;

[0064] 2. Reduce costs: The intelligent management system reduces the reliance on manual experience, avoids the waste of resources caused by improper manual operation, reduces the cost of planting and picking, and improves economic benefits;

[0065] 3. The system can collect and analyze large amounts of data in real time, providing comprehensive and accurate information to planting managers, so that managers can understand the overall situation of the citrus orchard in a timely manner and make scientific and reasonable decisions.

[0066] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0068] Figure 1 This is a schematic diagram of the structure of the intelligent citrus planting and picking management system based on the present invention. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] See also Figure 1 As shown, a citrus planting and picking management system based on intelligence is disclosed, including: a data acquisition module, a data analysis and processing module, an intelligent management module and an execution control module;

[0071] The data acquisition module includes a soil sensor, a meteorological sensor, and a camera. The soil sensor is used to collect soil parameter information in real time; the meteorological sensor is used to collect meteorological data in real time; and the camera is used to photograph the growth status of citrus trees, including pest and disease conditions and fruit maturity image information.

[0072] The data analysis and processing module is used to receive the data transmitted by the data acquisition module, and to determine whether the soil fertility needs to be supplemented and whether the soil water needs to be supplemented by analyzing the soil parameters and meteorological data; and to identify the pest information and the maturity of the fruit in combination with the image captured by the camera;

[0073] The intelligent management module generates corresponding planting and harvesting management decisions based on the results of the data analysis and processing module;

[0074] The execution control module includes irrigation equipment, fertilization equipment, pest control equipment and a picking robot, which is used to execute corresponding decisions based on planting and picking management decisions.

[0075] Through the above technical solution, during the citrus growing season, the data acquisition module collects data in real time, and the data is transmitted to the data analysis and processing module. After analysis, the intelligent decision-making module generates fertilization instructions and irrigation instructions, and the execution control module controls the fertilization equipment and irrigation equipment to perform periodic fertilization and irrigation. The fertilization and irrigation cycles are determined according to the soil type, local meteorological data and the growth stage of the citrus tree. When the data analysis and processing module finds that the citrus tree leaves have symptoms of pests and diseases through image recognition, the intelligent decision-making module recommends the corresponding amount of control medicine, and the execution control module controls the pest control equipment to apply medicine. When the picking season is approaching, the camera continuously captures the fruit image, and the data analysis and processing module determines the maturity of the fruit through image analysis. When the maturity is qualified, the picking robot is controlled to pick.

[0076] The working process of the data acquisition module includes:

[0077] Soil sensors were evenly distributed in the citrus grove, with a depth of 10-20 cm to accurately collect soil parameter information;

[0078] Install weather sensors in open, well-ventilated locations that represent the overall weather conditions in the citrus orchard to accurately collect weather information;

[0079] Installing a camera above the citrus tree can clearly capture every part of the tree and ensure the integrity of image acquisition.

[0080] The specific working process of the data analysis and processing module includes:

[0081] Step S10, obtaining soil fertilization decision based on soil parameters and meteorological data;

[0082] Step S20, obtaining soil irrigation decision based on soil parameter information and meteorological data;

[0083] Step S30, obtaining pest control decisions based on citrus tree leaf image information;

[0084] Step S40, obtaining a picking decision based on the citrus fruit image information.

[0085] The specific process of step S10 includes:

[0086] Obtain soil parameter information and compare all soil parameter information with the target threshold set by the system. If any soil parameter information is lower than the target threshold, immediately add the fertilizer corresponding to the parameter information. If no soil parameter information is lower than the target threshold, predict the current soil fertilization cycle.

[0087] The specific process of predicting the current soil fertilization cycle includes:

[0088] Construct the mathematical calculation model of the current soil fertilization cycle, the expression is:

[0089] ;

[0090] Where k is the conversion coefficient, is the coefficient of the first growth stage, S is the current soil fertility index, is the environmental coefficient, F is the fertilization efficiency coefficient, Fertilize the soil for the current cycle;

[0091] The soil fertility index S can be obtained by fitting the soil parameter information, and the expression is:

[0092] ;

[0093] Where n is the number of soil parameters collected, is the data of the i-th soil parameter, is the standard data of the i-th soil parameter set by the system, is the weight coefficient corresponding to the i-th soil parameter, where i belongs to n, is the adjustment factor, used to adjust S to the range ;

[0094] The first growth stage coefficient C is assigned according to the current crop growth stage, and the value range of C is , when the citrus is in the spring shoot growth period, C=0.3, when the citrus is in the flowering period, C=0.15, when the citrus is in the young fruit stage, C=0.2, when the citrus is in the fruit expansion period, C=0.25, when the citrus is in the fruit maturity period, C=0.1;

[0095] The environmental coefficient E can be obtained by fitting the environmental parameter information, and the expression is:

[0096] ;

[0097] In the formula, is the average ambient temperature during the citrus growth period, is the average environmental humidity during the citrus growth period, is the average ambient light intensity during the citrus growth period, , and are the weight coefficients corresponding to ambient temperature, ambient humidity and ambient light intensity, is the adjustment coefficient of the exponential function, is the adjustment factor used to Adjust to range ;

[0098] Construct a mathematical model of fertilization efficiency coefficient F, the expression is:

[0099] ;

[0100] In the formula, is the amount of fertilizer for the jth nutrient, For soil nutrients after fertilization, For soil nutrients before fertilization, The amount of fertilizer nutrient j belongs to m, is the weight coefficient corresponding to the jth nutrient, is the adjustment factor used to Adjust to range ;

[0101] Said , and Based on experimental data.

[0102] Through the above technical solution, this embodiment provides a citrus tree fertilization decision-making scheme, which compares all soil parameter information with the target threshold set by the system. If any soil parameter information is lower than the target threshold, the fertilizer corresponding to the parameter information is immediately supplemented. If it does not appear, a soil fertilization cycle is formulated. First, a mathematical calculation model of the current soil fertilization cycle is constructed. ,in, is the coefficient of the first growth stage, S is the current soil fertility index, is the environmental coefficient, F is the fertilization efficiency coefficient, and then the soil fertility index S is calculated by comparing the data of various soil parameters with the benchmark values. The coefficient C of the first growth stage is assigned based on the current growth stage. The environmental coefficient E is calculated based on the meteorological data of the growth period, and the fertilization efficiency coefficient F is calculated based on the experimental data. Finally, the various coefficients are converted and calculated to obtain the fertilization cycle.

[0103] The specific process of step S20 includes:

[0104] The soil moisture content information is obtained and compared with the target threshold set by the system. If the moisture content information is lower than the target threshold, water is added immediately. If the moisture content information is not lower than the target threshold, the current soil irrigation cycle is predicted.

[0105] The specific process of predicting the current soil irrigation cycle includes:

[0106] Construct the mathematical calculation model of the current soil irrigation cycle, the expression is:

[0107] ;

[0108] In the formula, is the conversion coefficient, A is the coefficient of the second growth stage, B is the crop transpiration coefficient, and D is the soil water consumption coefficient;

[0109] The second growth stage coefficient A is assigned according to the current crop growth stage, and the value range of A is , when the citrus is in the spring shoot growth period, A=0.1, when the citrus is in the flowering period, A=0.15, when the citrus is in the young fruit stage, A=0.25, when the citrus is in the fruit expansion period, A=0.4, when the citrus is in the fruit maturity period, A=0.1;

[0110] The crop transpiration coefficient B is obtained by direct measurement, and the expression is:

[0111] ;

[0112] In the formula, is the current stem flow rate, is the current citrus leaf area, is the adjustment factor used to Adjust to range ;

[0113] Construct the mathematical model of soil moisture coefficient D, the expression is:

[0114] ;

[0115] In the formula, is the amount of irrigation water, is the soil moisture after irrigation, is the soil moisture before irrigation, is the adjustment factor used to Adjust to range ;

[0116] Said , and Based on experimental data.

[0117] Through the above technical scheme, this embodiment provides an irrigation decision-making scheme, which obtains soil moisture content information, compares the soil moisture content information with the target threshold set by the system, and if the moisture content information is lower than the target threshold, water is replenished immediately. If it does not appear, a soil irrigation cycle is formulated, and a mathematical calculation model of the current soil irrigation cycle is constructed, wherein A is the second growth stage coefficient, B is the crop transpiration coefficient, and D is the soil moisture consumption coefficient. Then, the second growth stage coefficient A is assigned based on the current growth stage, the transpiration coefficient B is obtained by self-measurement, and the soil moisture consumption coefficient D is calculated based on experimental data. Finally, each coefficient is converted and calculated to obtain the irrigation cycle.

[0118] The specific process of step S30 includes:

[0119] Collect citrus leaf image data and input them into a trained pest and disease recognition model. If the output result is that there is no pest and disease, there is no need to carry out pest and disease control. If the output result is that there is pest and disease, calculate the control parameters, and the control parameters include the severity index of pest and disease and the amount of pesticide used.

[0120] The pest severity index is based on the formula Get, where The area of ​​lesions, is the total leaf area, and the pesticide dosage is obtained based on the formula pesticide dosage = basic dosage * pest and disease severity index.

[0121] The specific process of step S40 includes:

[0122] Collect citrus tree image data and input them into the trained fruit maturity recognition model. If the output maturity is above 85%, arrange for picking in the near future.

[0123] Through the above technical solution, this embodiment provides a pest control decision-making solution and a picking decision-making solution. The image data of citrus leaves are collected and input into the trained pest recognition model. If the output result is no pests, no pest control is required. If the output result is that there are pests, the leaf spot area and leaf area are obtained. Based on the formula Calculate the severity index of pests and diseases, and then obtain the pesticide dosage through the formula pesticide dosage = basic dosage * pest and disease severity index.

[0124] Collect citrus tree image data and input them into the trained fruit maturity recognition model. If the output maturity is above 85%, arrange for picking in the near future.

[0125] A method for intelligent citrus planting and picking management, the method comprising the following steps:

[0126] Step S1, the data acquisition module continuously collects data on soil, weather and citrus tree growth conditions at set time intervals, and transmits the data to the data analysis and processing module in real time.

[0127] Step S2: The data analysis and processing module cleans, organizes and analyzes the collected data;

[0128] Step S3, the intelligent decision-making module formulates specific planting and harvesting decisions based on the results of the data analysis and processing module, and the decision-making content includes fertilization, irrigation, pest control, and harvesting;

[0129] Step S4, the execution control module receives the instruction of the intelligent decision module and controls the corresponding equipment to operate;

[0130] Step S5: After executing the operation, the data acquisition module periodically collects relevant data, the data analysis and processing module periodically analyzes the data, the intelligent decision-making module adjusts the decision according to the latest analysis results, and the execution control module executes the operation again according to the adjusted decision, forming a closed-loop management.

[0131] It should be noted that the thresholds, threshold intervals, and coefficients set in this application are all empirical values, and all data in this application have been processed, and all calculations are dimensionless calculations, so there is no need to elaborate on them.

[0132] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An intelligent citrus planting and picking management system, characterized in that: include: Data acquisition module, data analysis and processing module, intelligent management module and execution control module; The data acquisition module includes a soil sensor, a meteorological sensor, and a camera. The soil sensor is used to collect soil parameter information in real time; the meteorological sensor is used to collect meteorological data in real time; and the camera is used to photograph the growth status of citrus trees, including pest and disease conditions and fruit maturity image information. The data analysis and processing module is used to receive the data transmitted by the data acquisition module, and to determine whether the soil fertility needs to be supplemented and whether the soil water needs to be supplemented by analyzing the soil parameters and meteorological data; and to identify the pest information and the maturity of the fruit in combination with the image captured by the camera; The intelligent management module generates corresponding planting and harvesting management decisions based on the results of the data analysis and processing module; The execution control module includes irrigation equipment, fertilization equipment, pest control equipment and a picking robot, which is used to execute corresponding decisions based on planting and picking management decisions.

2. According to claim 1, the intelligent citrus planting and picking management system is characterized in that: The working process of the data acquisition module includes: Soil sensors were evenly distributed in the citrus grove, with a depth of 10-20 cm to accurately collect soil parameter information; Install weather sensors in open, well-ventilated locations that represent the overall weather conditions in the citrus orchard to accurately collect weather information; Installing a camera above the citrus tree can clearly capture every part of the tree and ensure the integrity of image acquisition.

3. The intelligent citrus planting and picking management system according to claim 2 is characterized in that: The specific working process of the data analysis and processing module includes: Step S10, obtaining soil fertilization decision based on soil parameters and meteorological data; Step S20, obtaining soil irrigation decision based on soil parameter information and meteorological data; Step S30, obtaining pest control decisions based on citrus tree leaf image information; Step S40, obtaining a picking decision based on the citrus fruit image information.

4. The intelligent citrus planting and picking management system according to claim 3 is characterized in that: The specific process of step S10 includes: Obtain soil parameter information and compare all soil parameter information with the target threshold set by the system. If any soil parameter information is lower than the target threshold, immediately add the fertilizer corresponding to the parameter information. If no soil parameter information is lower than the target threshold, predict the current soil fertilization cycle.

5. The intelligent citrus planting and picking management system according to claim 4 is characterized in that: The specific process of predicting the current soil fertilization cycle includes: Construct the mathematical calculation model of the current soil fertilization cycle, the expression is: ； Where k is the conversion coefficient, is the coefficient of the first growth stage, S is the current soil fertility index, is the environmental coefficient, F is the fertilization efficiency coefficient, Fertilize the soil for the current cycle; The soil fertility index S can be obtained by fitting the soil parameter information, and the expression is: ； Where n is the number of soil parameters collected, is the data of the i-th soil parameter, is the standard data of the i-th soil parameter set by the system, is the weight coefficient corresponding to the i-th soil parameter, where i belongs to n, is the adjustment factor, used to adjust S to the range ; The first growth stage coefficient C is assigned according to the current crop growth stage, and the value range of C is , when the citrus is in the spring shoot growth period, C=0.3, when the citrus is in the flowering period, C=0.15, when the citrus is in the young fruit stage, C=0.2, when the citrus is in the fruit expansion period, C=0.25, when the citrus is in the fruit maturity period, C=0.1; The environmental coefficient E can be obtained by fitting the environmental parameter information, and the expression is: ； In the formula, is the average ambient temperature during the citrus growth period, is the average environmental humidity during the citrus growth period, is the average ambient light intensity during the citrus growth period, , and are the weight coefficients corresponding to ambient temperature, ambient humidity and ambient light intensity, is the adjustment coefficient of the exponential function, is the adjustment factor used to Adjust to range ; Construct a mathematical model of fertilization efficiency coefficient F, the expression is: ； In the formula, is the amount of fertilizer for the jth nutrient, For soil nutrients after fertilization, For soil nutrients before fertilization, The amount of fertilizer nutrient, j belongs to m, is the weight coefficient corresponding to the jth nutrient, is the adjustment factor used to Adjust to range ; Said , and Based on experimental data.

6. The intelligent citrus planting and picking management system according to claim 4 is characterized in that: The specific process of step S20 includes: The soil moisture content information is obtained and compared with the target threshold set by the system. If the moisture content information is lower than the target threshold, water is added immediately. If the moisture content information is not lower than the target threshold, the current soil irrigation cycle is predicted.

7. The intelligent citrus planting and picking management system according to claim 4 is characterized in that: The specific process of predicting the current soil irrigation cycle includes: Construct the mathematical calculation model of the current soil irrigation cycle, the expression is: ； In the formula, is the conversion coefficient, A is the coefficient of the second growth stage, B is the crop transpiration coefficient, and D is the soil water consumption coefficient; The second growth stage coefficient A is assigned according to the current crop growth stage, and the value range of A is , when the citrus is in the spring shoot growth period, A=0.1, when the citrus is in the flowering period, A=0.15, when the citrus is in the young fruit stage, A=0.25, when the citrus is in the fruit expansion period, A=0.4, when the citrus is in the fruit maturity period, A=0.1; The crop transpiration coefficient B is obtained by direct measurement, and the expression is: ; In the formula, is the current stem flow rate, is the current citrus leaf area, is the adjustment factor used to Adjust to range ; Construct the mathematical model of soil moisture coefficient D, the expression is: ; In the formula, is the amount of irrigation water, is the soil moisture after irrigation, is the soil moisture before irrigation, is the adjustment factor used to Adjust to range ; Said , and Based on experimental data.

8. The intelligent citrus planting and picking management system according to claim 4 is characterized in that: The specific process of step S30 includes: Collect citrus leaf image data and input them into a trained pest and disease recognition model. If the output result is that there is no pest and disease, there is no need to carry out pest and disease control. If the output result is that there is pest and disease, calculate the control parameters, and the control parameters include the severity index of pest and disease and the amount of pesticide used. The pest severity index is based on the formula Get, where The area of ​​lesions, is the total leaf area, and the pesticide dosage is obtained based on the formula pesticide dosage = basic dosage * pest and disease severity index.

9. The intelligent citrus planting and picking management system according to claim 4 is characterized in that: The specific process of step S40 includes: Collect citrus tree image data and input them into the trained fruit maturity recognition model. If the output maturity is above 85%, arrange for picking in the near future.

10. A method for intelligent citrus planting and picking management, the method being applicable to the intelligent citrus planting and picking management system according to any one of claims 1 to 9, characterized in that: The method comprises the following steps: Step S1, the data acquisition module continuously collects data on soil, weather and citrus tree growth conditions at set time intervals, and transmits the data to the data analysis and processing module in real time; Step S2: The data analysis and processing module cleans, organizes and analyzes the collected data; Step S3, the intelligent decision-making module formulates specific planting and harvesting decisions based on the results of the data analysis and processing module, and the decision-making content includes fertilization, irrigation, pest control, and harvesting; Step S4, the execution control module receives the instruction of the intelligent decision module and controls the corresponding equipment to operate; Step S5: After executing the operation, the data acquisition module periodically collects relevant data, the data analysis and processing module periodically analyzes the data, the intelligent decision-making module adjusts the decision according to the latest analysis results, and the execution control module executes the operation again according to the adjusted decision, forming a closed-loop management.

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