Citrus phenological period identification method, device, equipment and medium

Abstract

The invention discloses a citrus phenological period identification method and device, equipment and a medium. The method comprises the following steps: acquiring a to-be-identified image of a citrus in a target area and a current environment parameter of the target area; on the basis of a citrus phenological period identification model, according to the to-be-identified image and the current environmental parameters, determining candidate phenological periods of the citrus; and correcting the candidate phenological period according to the acquisition time of the to-be-identified image, and determining a target phenological period of the citrus. According to the technical scheme, the influence of the citrus image, the environmental parameters and the acquisition time on citrus phenological period identification is considered, so that the identification accuracy of the citrus phenological period is improved.

Description

Technical Field

[0001] The present application relates to the field of information processing technology, and in particular to a method, device, equipment and medium for identifying citrus phenological periods. Background Art

[0002] Phenological period is the growth law characteristic of crops corresponding to periodic climate change. Phenological period is sequential, repetitive and overlapping to a certain extent. By identifying the phenological period of crops, effective irrigation, fertilization and pest control measures can be taken in critical periods, which can effectively promote crop yield and quality. For example, during the spring shoot budding period of citrus, aphids often gather on the new shoots to suck juice, resulting in poor growth of citrus new shoots. Therefore, when it is identified that the current phenological period of citrus is the spring shoot budding period, imidacloprid and other pesticides can be used for prevention and control in a timely manner.

[0003] At present, the identification of phenological periods mostly relies on manual observation and empirical judgment, which has the following problems: 1) The data collection process is cumbersome, labor-intensive, and inefficient; 2) The accuracy and timeliness of recorded data are insufficient, making it difficult to form long-term continuous monitoring; 3) The correlation with environmental data is insufficient, lacks scientific basis, and is highly subjective; 4) It is difficult to achieve full coverage monitoring of large-scale planting sites. Therefore, it is impossible to identify the key growth stages of crops in a timely and accurate manner, which affects the precise arrangement of agricultural activities such as pest control, fertilization and irrigation, and pruning. Summary of the invention

[0004] The present application provides a method, device, equipment and medium for identifying citrus phenological periods, which improves the recognition accuracy of citrus phenological periods by taking into account the influence of citrus images, environmental parameters and collection time on the recognition of citrus phenological periods.

[0005] According to one aspect of the present application, a method for identifying citrus phenological phases is provided, the method comprising:

[0006] Acquire an image of citrus fruits to be identified in a target area and current environmental parameters of the target area;

[0007] Based on the citrus phenological period recognition model, determining the candidate phenological period of the citrus according to the image to be recognized and the current environmental parameters;

[0008] The candidate phenological period is corrected according to the acquisition time of the image to be identified to determine the target phenological period of the citrus.

[0009] According to another aspect of the present application, a citrus phenological phase identification device is provided, the device comprising:

[0010] A data acquisition module, used to acquire an image of citrus fruits to be identified in a target area, and current environmental parameters of the target area;

[0011] A model prediction module, for determining the candidate phenological period of the citrus based on the citrus phenological period recognition model according to the image to be recognized and the current environmental parameters;

[0012] The phenological period correction module is used to correct the candidate phenological period according to the acquisition time of the image to be identified, so as to determine the target phenological period of the citrus.

[0013] According to another aspect of the present application, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the citrus phenological period identification method described in any embodiment of the present application.

[0014] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the citrus phenological period identification method described in any embodiment of the present application when executed.

[0015] The technical solution provided by the present application obtains the image of citrus to be identified in the target area and the current environmental parameters of the target area; based on the citrus phenological period recognition model, the candidate phenological period of citrus is determined according to the image to be identified and the current environmental parameters; the candidate phenological period is corrected according to the acquisition time of the image to be identified to determine the target phenological period of citrus. This technical solution improves the recognition accuracy of citrus phenological period by taking into account the influence of citrus images, environmental parameters and acquisition time on the recognition of citrus phenological period.

[0016] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A flow chart of a method for identifying citrus phenological periods provided in Example 1 of the present application;

[0019] Figure 2A schematic diagram of the structure of a citrus phenological period identification device provided in Example 2 of the present application;

[0020] Figure 3 It is a structural schematic diagram of a device for implementing a method for identifying citrus phenological periods in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "target", "current", "to be identified", "intercepted", "collected", "candidate", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] Embodiment 1

[0024] Figure 1 This is a flowchart of a method for identifying the phenological period of citrus provided in Example 1 of the present application. This embodiment is applicable to the case of identifying the phenological period of citrus. The method can be executed by a citrus phenological period identification device. The citrus phenological period identification device can be implemented in the form of hardware and / or software. The citrus phenological period identification device can be configured in a device with data processing capabilities. Figure 1 As shown, the method includes:

[0025] S110, obtaining an image of citrus fruits to be identified in a target area and current environmental parameters of the target area.

[0026] The image to be identified can be an image of the citrus planting area obtained by an image acquisition device. For example, a high-definition digital camera, a smartphone camera or other equipment can be used for ground photography; a drone with a camera can also be used for aerial photography to photograph the target area at different heights and angles to obtain a large-area overall image of the citrus orchard; or a surveillance camera installed in the citrus planting area can be used for image acquisition.

[0027] Specifically, the appropriate time can be selected for image acquisition based on the growth cycle and phenological characteristics of citrus. For example, during key growth stages such as flowering and fruit expansion, the frequency of image acquisition can be increased to more accurately monitor the growth changes of citrus. In addition, considering the lighting conditions and weather changes in different seasons, images can be collected when the weather conditions are good or the lighting conditions are sufficient to better show the color and morphology of citrus.

[0028] The current environmental parameter may be a parameter that affects the growth and development of citrus. For example, the current environmental parameter may be temperature, light, humidity, etc. Optionally, the current environmental parameter includes at least one of temperature, light, rainfall, humidity, wind speed, and soil conditions.

[0029] Temperature is one of the most important factors affecting the growth and development of citrus. Different phenological periods, such as budding, flowering, and fruit expansion, usually have specific temperature requirements. For example, high temperatures may accelerate developmental processes, such as bringing forward flowering and fruit ripening, while low temperatures may delay these processes. Abnormal temperature changes (such as frost) may lead to the loss of flower buds and young fruits, which in turn affects phenological period identification.

[0030] Light affects photosynthesis and is directly related to plant energy accumulation. Changes in light, such as daylight duration and light intensity, have a significant impact on plant phenology. For example, shortening the light duration may prompt plants to enter a dormant period, excessive light may cause photodamage, and insufficient light may affect flowering and fruit development.

[0031] Water is one of the key factors for plant growth. Changes in rainfall can affect soil moisture content, thereby affecting plant physiological activities and growth cycles. For example, excessive rainfall can lead to soil saturation and cause root hypoxia, while long-term drought can lead to water stress and affect flower bud differentiation and fruit development.

[0032] Air humidity is closely related to plant transpiration and the occurrence of pests and diseases, and has a direct impact on plant growth and development. For example, high humidity is conducive to the growth of diseases, and corresponding measures need to be taken by identifying these risk periods; low humidity may cause plant water to evaporate too quickly, affecting normal growth.

[0033] Wind speed affects the transpiration and heat dissipation of plants and the spread of diseases, and also has a significant impact on the mechanical damage of fruit trees. For example, strong winds can cause damage or fall off of branches, leaves and young fruits, affecting the normal progress of the next stage of the phenological period.

[0034] Soil conditions include soil temperature, humidity, pH value, nutrients and other factors, which directly affect the health of plant roots and nutrient absorption. Appropriate soil conditions provide sufficient nutrients and water to support the normal phenological performance of plants; poor soil conditions such as poor soil conditions or excessive acidity or alkalinity will inhibit plant growth and cause delayed or abnormal phenological periods.

[0035] In this application, sensor nodes can be reasonably arranged in the citrus planting area, and each node is equipped with data acquisition equipment such as temperature and humidity sensors, light sensors, and image acquisition equipment to regularly collect images of citrus to be identified in the target area and the current environmental parameters of the target area.

[0036] Furthermore, the image to be identified and the current environmental parameters collected by the sensor node can be transmitted to the data storage and processing system by wired or wireless means. For example, the data is transmitted to the cloud server via a wireless network so that the cloud server stores and processes the data uploaded by the sensor, and uses the image recognition algorithm to process the image to be identified and the current environmental parameters to identify the phenological state of citrus.

[0037] Optionally, obtaining an image of citrus fruits to be identified in a target area includes: obtaining a captured image of citrus fruits in the target area; and intercepting a crown area in the captured image to obtain an image to be identified.

[0038] Among them, the crown area can be the part above the trunk of the citrus tree. The distinctive characteristics of the citrus tree in different phenological periods can be reflected by the appearance shape, branch and leaf characteristics, and flower and fruit characteristics of the crown area.

[0039] Therefore, the present application improves the efficiency of image candidate processing by intercepting the crown area of ​​the citrus tree in the captured image and removing image data of less importance.

[0040] To determine the crown area, the color, shape, texture and other features of the citrus crown can be used to automatically identify the crown area through image processing algorithms. For example, a color segmentation algorithm can be used to distinguish the green crown from the background, or an edge detection algorithm can be used to determine the outline of the crown. In addition, a pre-trained deep learning model, such as a convolutional neural network, can be used to analyze the collected images to automatically identify the citrus crown area.

[0041] Furthermore, based on the results obtained by the crown area recognition method, the boundary coordinates of the crown in the collected image are determined; using image processing software or programming tools, the collected image is intercepted according to the determined boundary coordinates to obtain an image to be identified that only contains the citrus crown area.

[0042] Optionally, the tree crown area in the acquired image is intercepted to obtain the image to be identified, including: intercepting the tree crown area in the acquired image to obtain a intercepted image; and preprocessing the intercepted image to obtain the image to be identified.

[0043] The preprocessing may include grayscale transformation, edge detection, image enhancement, size adjustment, color standardization, noise removal, etc. The present application embodiment does not limit this, and it can be determined according to actual needs.

[0044] The beneficial effect of the above technical solution is that by determining to intercept and pre-process the crown area in the collected image, an image to be identified that is more suitable for phenological period identification can be obtained, providing a better data basis for subsequent analysis and judgment.

[0045] S120. Based on a citrus phenological period recognition model, determine the candidate phenological period of the citrus according to the image to be recognized and the current environmental parameters.

[0046] The citrus phenological period recognition model can be constructed by using machine learning or deep learning algorithms. For example, a convolutional neural network can be used to extract and classify features of an image, or a recurrent neural network can be used to process time series data.

[0047] Specifically, the recognition image and current environmental parameters can be input into the citrus phenological period recognition model. The model performs analysis and reasoning based on the input image and environmental parameters, and outputs the candidate phenological periods of citrus.

[0048] Optionally, based on the citrus phenological period recognition model, the candidate phenological period of the citrus is determined according to the image to be recognized and the current environmental parameters, including: based on the feature extraction module in the citrus phenological period recognition model, performing feature extraction on the image to be recognized to obtain a feature image, and performing feature extraction on the current environmental parameters to obtain numerical features; based on the classification module in the citrus phenological period recognition model, classifying the feature image and the numerical features to determine the candidate phenological period of the citrus.

[0049] The characteristic image may be an image including color features, texture features and shape features. Specifically, the characteristic image may be obtained by using a color histogram, a gray level co-occurrence matrix and edge detection.

[0050] Feature extraction is performed on the current environmental parameters to obtain numerical features, such as temperature, temperature change trend, humidity value, humidity change range, light intensity level, light duration, soil moisture change rate, etc.

[0051] In the present application, the feature image and the numerical feature can be fused to obtain the fused feature, and the classification module in the citrus phenological period recognition model classifies the fused feature to determine the candidate phenological period of citrus.

[0052] S130, correcting the candidate phenological period according to the acquisition time of the image to be identified, and determining the target phenological period of the citrus.

[0053] The acquisition time may be a timestamp recorded when the image to be identified is acquired.

[0054] The phenological period of citrus can generally be divided into flower bud differentiation period, flower opening period, fruit setting period, fruit expansion period and fruit maturity period. Among them, the flower bud differentiation period can be divided into spring budding period and autumn budding period. The image data and environmental parameters collected by the two are basically similar. If they are only identified by the citrus phenological period recognition model, there will be certain errors.

[0055] Therefore, the present application modifies the candidate phenological period by the acquisition time of the image to be identified to improve the recognition accuracy of the citrus phenological period. For example, the recognition result of the citrus phenological period recognition model is the new bud period. If the acquisition time is March-April, it can be considered as spring new buds, and if the acquisition time is August-September, it can be considered as autumn new buds.

[0056] Optionally, the candidate phenological period is corrected according to the acquisition time of the image to be identified to determine the target phenological period of the citrus, including: according to the acquisition time of the image to be identified, determining at least one preset phenological period corresponding to the acquisition time; and correcting the candidate phenological period according to the preset phenological period to determine the target phenological period of the citrus.

[0057] Specifically, the corresponding relationship between the collection time and different phenological periods can be established according to the growth law and historical data of citrus, and the corresponding relationship can be stored in the form of tables, charts or databases. For example, through long-term observation and recording, it can be determined that citrus is usually in a specific phenological period within a specific time period.

[0058] After the acquisition time of the image to be identified is obtained, at least one preset phenological period corresponding to the acquisition time can be determined based on the established correspondence between time and phenological period. Since the acquisition time may not completely correspond to a specific phenological period, there may be a situation where multiple phenological periods correspond to a time period. For example, a certain acquisition time may be in the transition stage between the flowering period and the fruiting period, in which case it will correspond to these two preset phenological periods.

[0059] Furthermore, the candidate phenological period determined by the citrus phenological period recognition model is compared with the preset phenological period determined according to the collection time. If the candidate phenological period is different from the preset phenological period, the candidate phenological period can be corrected according to the preset phenological period. Specifically, the phenological period correction can be based on judgment based on experience and knowledge, or it can be corrected through further data analysis and model adjustment.

[0060] The beneficial effect of the above technical solution is that the preset phenological period is determined according to the acquisition time of the image to be identified, and the candidate phenological period is corrected accordingly, making full use of time information and the growth law of citrus, improving the accuracy and reliability of citrus phenological period judgment, and providing a more scientific basis for the management and decision-making of citrus planting.

[0061] Based on the above embodiment, optionally, after correcting the candidate phenological period according to the acquisition time of the image to be identified and determining the target phenological period of the citrus, the method also includes: determining the agricultural operation strategy corresponding to the target phenological period and generating prompt information.

[0062] Specifically, the real-time and historical phenological monitoring data can be displayed through a visual data analysis platform, and agricultural operation strategies can be formulated based on the identification results, such as reasonably arranging irrigation and pesticide application time to improve production efficiency.

[0063] In addition, data can be automatically collected to form a database, and the growth patterns of citrus can be tracked and analyzed over the long term, providing a scientific basis for subsequent planting decisions.

[0064] The beneficial effect of the above technical solution is that by determining the agricultural operation strategy corresponding to the target phenological period and generating prompt information, it can help growers manage orchards scientifically and improve the yield and quality of citrus.

[0065] The embodiment of the present invention provides a method for identifying citrus phenological periods, which obtains an image of citrus to be identified in a target area and the current environmental parameters of the target area; determines the candidate phenological period of citrus based on the image to be identified and the current environmental parameters based on a citrus phenological period identification model; and corrects the candidate phenological period according to the acquisition time of the image to be identified to determine the target phenological period of citrus. This technical solution improves the recognition accuracy of citrus phenological period by taking into account the influence of citrus images, environmental parameters and acquisition time on the recognition of citrus phenological period.

[0066] Embodiment 2

[0067] Figure 2 This is a schematic diagram of the structure of a citrus phenological period identification device provided in Example 2 of the present application. Figure 2 As shown, the device comprises:

[0068] The data acquisition module 210 is used to acquire the image of citrus to be identified in the target area and the current environmental parameters of the target area;

[0069] A model prediction module 220 is used to determine the candidate phenological period of the citrus based on the citrus phenological period recognition model according to the image to be recognized and the current environmental parameters;

[0070] The phenological period correction module 230 is used to correct the candidate phenological period according to the acquisition time of the image to be identified, so as to determine the target phenological period of the citrus.

[0071] The beneficial effect of the above technical solution is that the recognition accuracy of citrus phenological period is improved by taking into account the influence of citrus images, environmental parameters and collection time on the recognition of citrus phenological period.

[0072] Furthermore, the phenological period correction module 230 includes:

[0073] A preset phenological period determination unit, configured to determine, according to the acquisition time of the image to be identified, at least one preset phenological period corresponding to the acquisition time;

[0074] The target phenological period determination unit is used to modify the candidate phenological period according to the preset phenological period to determine the target phenological period of the citrus.

[0075] Furthermore, the current environmental parameter includes at least one of temperature, light, rainfall, humidity, wind speed and soil conditions.

[0076] Furthermore, the data acquisition module 210 includes:

[0077] An image acquisition unit is used to acquire an image of citrus fruits in a target area;

[0078] The to-be-recognized image determination unit is used to intercept the tree crown area in the collected image to obtain the to-be-recognized image.

[0079] Furthermore, the unit for determining the image to be identified includes:

[0080] An image capture subunit, used to capture the tree crown area in the collected image to obtain a captured image;

[0081] The image preprocessing subunit is used to preprocess the captured image to obtain an image to be recognized.

[0082] Furthermore, the model prediction module 220 includes:

[0083] A feature extraction unit, for extracting features from the image to be identified to obtain a feature image based on a feature extraction module in a citrus phenological period recognition model, and for extracting features from the current environmental parameters to obtain numerical features;

[0084] The phenological period prediction unit is used to classify the feature image and the numerical feature based on the classification module in the citrus phenological period recognition model to determine the candidate phenological period of the citrus.

[0085] Furthermore, the device also includes:

[0086] The information prompt module is used to correct the candidate phenological period according to the acquisition time of the image to be identified, determine the target phenological period of the citrus, determine the agricultural operation strategy corresponding to the target phenological period, and generate prompt information.

[0087] A citrus phenological period identification device provided in an embodiment of the present application can execute a citrus phenological period identification method provided in any embodiment of the present application, and has functional modules and beneficial effects corresponding to the execution method.

[0088] Embodiment 3

[0089] Figure 3 A schematic diagram of a device 10 that can be used to implement an embodiment of the present application is shown. The device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0090] like Figure 3 As shown, the device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the device 10 can also be stored. The processor 11, ROM 12 and RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0091] A number of components in the device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0092] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the citrus phenological period recognition method.

[0093] In some embodiments, the citrus phenological phase identification method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the citrus phenological phase identification method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the citrus phenological phase identification method in any other appropriate manner (e.g., by means of firmware).

[0094] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0095] The computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer programs are executed by the processor, the functions / operations specified in the flow charts and / or block diagrams are implemented. The computer programs may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0096] In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device or equipment. A computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A more specific example of a machine readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0097] To provide interaction with a user, the systems and techniques described herein can be implemented on a device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0098] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0099] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0100] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution of this application can be achieved, and this document is not limited here.

[0101] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for identifying citrus phenological phases, characterized in that: The method comprises: Acquire an image of citrus fruits to be identified in a target area and current environmental parameters of the target area; Based on the citrus phenological period recognition model, determining the candidate phenological period of the citrus according to the image to be recognized and the current environmental parameters; The candidate phenological period is corrected according to the acquisition time of the image to be identified to determine the target phenological period of the citrus.

2. The method according to claim 1, characterized in that The candidate phenological period is corrected according to the acquisition time of the image to be identified to determine the target phenological period of the citrus, including: Determining, according to the acquisition time of the image to be identified, at least one preset phenological period corresponding to the acquisition time; The candidate phenological period is modified according to the preset phenological period to determine the target phenological period of the citrus.

3. The method according to claim 1, characterized in that The current environmental parameter includes at least one of temperature, light, rainfall, humidity, wind speed and soil conditions.

4. The method according to claim 1, characterized in that Obtain an image of citrus to be identified in a target area, including: Acquire a collection image of citrus in a target area; The tree crown area in the collected image is intercepted to obtain an image to be identified.

5. The method according to claim 4, characterized in that The tree crown area in the collected image is intercepted to obtain an image to be identified, including: intercepting a tree crown region in the collected image to obtain an intercepted image; The captured image is preprocessed to obtain an image to be recognized.

6. The method according to claim 1, characterized in that Based on the citrus phenological period recognition model, determining the candidate phenological period of the citrus according to the image to be recognized and the current environmental parameters, including: Based on the feature extraction module in the citrus phenological period recognition model, feature extraction is performed on the image to be recognized to obtain a feature image, and feature extraction is performed on the current environmental parameters to obtain numerical features; Based on the classification module in the citrus phenological period recognition model, the feature image and the numerical feature are classified to determine the candidate phenological period of the citrus.

7. The method according to claim 1, characterized in that After the candidate phenological period is corrected according to the acquisition time of the image to be identified and the target phenological period of the citrus is determined, the method further includes: Determine the farming operation strategy corresponding to the target phenological period and generate prompt information.

8. A citrus phenological phase identification device, characterized in that: The device comprises: A data acquisition module, used to acquire an image of citrus fruits to be identified in a target area, and current environmental parameters of the target area; A model prediction module, for determining the candidate phenological period of the citrus based on the citrus phenological period recognition model according to the image to be recognized and the current environmental parameters; The phenological period correction module is used to correct the candidate phenological period according to the acquisition time of the image to be identified, so as to determine the target phenological period of the citrus.

9. An electronic device, characterized in that: The device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the citrus phenological stage identification method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the citrus phenological period identification method according to any one of claims 1 to 7 when executed.

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