Intelligent herbicide recommendation method based on ecological data analysis

Abstract

The invention relates to an intelligent herbicide recommendation method based on ecological data analysis, and belongs to the technical field of herbicide recommendation. Obtaining the degradation half-life period of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area of the current time period through the herbicide degradation half-life period database and the ecological environment characteristic data in the target area of the current time period, and finally setting a degradation half-life period threshold value. And analyzing the initial herbicide recommendation set according to the degradation half-life period of each herbicide type in the initial herbicide recommendation set under the environment characteristic data in the target area to obtain a final herbicide recommendation set. According to the method, the optimal herbicide is selected according to the degradation half-life period of each herbicide type under the ecological environment characteristic data in the target area in the current time period, so that ecological pollution is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of herbicide use recommendations, and particularly to an intelligent herbicide recommendation method based on ecological data analysis. Background Art

[0002] In agricultural cultivation, weeds compete with crops for nutrients, water, etc., so the presence of weeds will inhibit the growth of crops. China is a large agricultural country with a vast agricultural planting area and a variety of planting varieties. The demand for herbicides by farmers is also increasing day by day. Currently, the national herbicide application area has reached 60 million hm2. However, after a certain dose of herbicide is used, it will remain in the soil. The residual pesticides will have varying degrees of impact on non-target organisms and will also enter the human body through the food chain and food web, resulting in the accumulation of pesticide residues in the human body

[52] . Therefore, evaluating the ecological toxicity of pesticides to non-target organisms is one of the important indicators for evaluating their safe use. Herbicides will not only have toxic effects on non-target organisms but also have harmful effects on humans. When the accumulation in the human body reaches a certain amount, it will cause acute poisoning or carcinogenic, mutagenic effects, etc. It is reported that some herbicides have carcinogenic effects or contain carcinogenic compounds. The US Environmental Protection Agency has listed oxyfluorfen as a potential human carcinogen. Research shows that most diphenyl ether herbicides will irritate the eyes and skin, causing some diseases such as hemolytic anemia. For example, oxyfluorfen may cause hematological diseases by inhibiting human protoporphyrinogen oxidase. Therefore, when applying diphenyl ether herbicides, protective equipment should be worn, and herbicides should be applied reasonably within the scope of medication stipulated by the state to avoid direct contact of herbicides with human skin and causing acute poisoning and endangering human health. And the selection of herbicides is of utmost importance. In the prior art, in the process of using herbicides, only resistance is often considered, and the harm to the ecological environment is not considered, resulting in unreasonable selection of herbicides. Therefore, the selection of herbicides is an important link for the ecological environment. Summary of the Invention

[0003] The present invention overcomes the deficiencies of the prior art and provides an intelligent herbicide recommendation method based on ecological data analysis.

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

[0005] The first aspect of the present invention provides an intelligent herbicide recommendation method based on ecological data analysis, including the following steps:

[0006] Obtain the weed type information in the target area, and obtain an initial herbicide recommendation set according to the weed type information in the target area;

[0007] Collect ecological environment characteristic data in the target area during the current time period, and construct a herbicide degradation half-life database according to the initial herbicide recommendation set;

[0008] Obtain the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area during the current time period through the herbicide degradation half-life database and the ecological environment characteristic data in the target area during the current time period;

[0009] Set a degradation half-life threshold, and analyze the initial herbicide recommendation set according to the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area to obtain the final herbicide recommendation set.

[0010] Further, in this method, obtain the weed type information in the target area, and obtain the initial herbicide recommendation set according to the weed type information in the target area, specifically including:

[0011] Collect weed image data information in the target area, construct a retrieval sample based on the weed image data information in the target area, and perform retrieval analysis based on the retrieval sample to obtain the weed type information in the target area;

[0012] Construct a retrieval label according to the weed type information in the target area, perform a retrieval through big data based on the retrieval label to obtain the weed type information in the target area, and construct an initial herbicide recommendation set;

[0013] Take the weed type information in the target area as a data sample and input it into the initial herbicide recommendation set, and output it from the initial herbicide recommendation set.

[0014] Further, in this method, collect the ecological environment characteristic data in the target area during the current time period, specifically including:

[0015] Collect historical ecological environment characteristic data information in the target area, construct an ecological environment characteristic data prediction model based on a deep neural network, and input the historical ecological environment characteristic data information in the target area into the ecological environment characteristic data prediction model for learning;

[0016] Set a learning rate and a training termination condition, perform learning on the ecological environment characteristic data prediction model based on the learning rate, and determine whether the ecological environment characteristic data prediction model reaches the training termination condition;

[0017] When the ecological environment characteristic data prediction model reaches the training termination condition, the training of the ecological environment characteristic data prediction model terminates, the model parameters of the ecological environment characteristic data prediction model are saved, and the ecological environment characteristic data prediction model is output;

[0018] Obtain the ecological environment characteristic data in the target area within a preset time, input the ecological environment characteristic data in the target area within the preset time into the ecological environment characteristic data prediction model for prediction, and obtain the ecological environment characteristic data in the target area in the current time period

[0019] Furthermore, in this method, a herbicide degradation half-life database is constructed according to the initial herbicide recommendation set, specifically including:

[0020] Based on the herbicide type information in the initial herbicide recommendation set as the retrieval keyword, perform data retrieval based on the keyword;

[0021] Through data retrieval, obtain the herbicide degradation half-life data of each herbicide type information in the initial herbicide recommendation set under each ecological environment characteristic data, and construct a database;

[0022] Input the herbicide degradation half-life data of each herbicide type information in the initial herbicide recommendation set under each ecological environment characteristic data into the database for storage.

[0023] Furthermore, in this method, the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area in the current time period is obtained through the herbicide degradation half-life database and the ecological environment characteristic data in the target area in the current time period, specifically including:

[0024] Input the ecological environment characteristic data in the target area in the current time period into the herbicide degradation half-life database for data matching;

[0025] Through data matching, obtain the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area in the current time period;

[0026] And output the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area in the current time period.

[0027] Furthermore, in this method, a degradation half-life threshold is set, and the initial herbicide recommendation set is analyzed according to the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area to obtain the final herbicide recommendation set, specifically:

[0028] Set a degradation half-life threshold, and determine whether the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area is greater than the degradation half-life threshold;

[0029] When the degradation half-life is greater than the degradation half-life threshold, delete the herbicide type corresponding to the degradation half-life greater than the degradation half-life threshold from the initial herbicide recommendation set;

[0030] When the degradation half-life is not greater than the degradation half-life threshold, keep the herbicide type corresponding to the degradation half-life not greater than the degradation half-life threshold unchanged in the initial herbicide recommendation set;

[0031] After all the herbicide types in the initial herbicide recommendation set have been analyzed, update the initial herbicide recommendation set and output it as the final herbicide recommendation set.

[0032] The second aspect of the present invention provides an intelligent herbicide recommendation system based on ecological data analysis, including a memory and a processor. The memory includes a memory and a processor. The memory includes an intelligent herbicide recommendation method program based on ecological data analysis. When the intelligent herbicide recommendation method program based on ecological data analysis is executed by the processor, the steps of any one of the intelligent herbicide recommendation methods based on ecological data analysis are implemented.

[0033] The third aspect of the present invention provides a computer-readable storage medium, which includes an intelligent herbicide recommendation method program based on ecological data analysis. When the intelligent herbicide recommendation method program based on ecological data analysis is executed by a processor, the steps of any one of the intelligent herbicide recommendation methods based on ecological data analysis are implemented.

[0034] The present invention solves the defects in the background technology and has the following beneficial effects:

[0035] The present invention obtains the weed type information in the target area, obtains the initial herbicide recommendation set according to the weed type information in the target area, then collects the ecological environment characteristic data in the target area at the current time period, and constructs a herbicide degradation half-life database according to the initial herbicide recommendation set, so as to obtain the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area at the current time period through the herbicide degradation half-life database and the ecological environment characteristic data in the target area at the current time period. Finally, a degradation half-life threshold is set, and the initial herbicide recommendation set is analyzed according to the degradation half-life of each herbicide type in the target area under the environmental characteristic data, and the final herbicide recommendation set is obtained. The present invention selects the optimal herbicide according to the degradation half-life of each herbicide type under the ecological environment characteristic data in the target area at the current time period, so as to reduce ecological pollution. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0037] Figure 1 Shows the overall flowchart of the intelligent herbicide recommendation method based on ecological data analysis;

[0038] Figure 2 Shows a partial method flowchart of the intelligent herbicide recommendation method based on ecological data analysis;

[0039] Figure 3 Shows the system block diagram of the intelligent herbicide recommendation system based on ecological data analysis. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] In order to more clearly understand the above objects, features and advantages of the present invention, the present invention will be further described in detail below with reference to the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0041] Many specific details are set forth in the following description in order to fully understand the present invention. However, the present invention may be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0042] Such as Figure 1As shown in the figure, the first aspect of the present invention provides an intelligent herbicide recommendation method based on ecological data analysis, including the following steps:

[0043] S102: Obtain the weed type information in the target area, and obtain the initial herbicide recommendation set according to the weed type information in the target area;

[0044] S104: Collect the ecological environment characteristic data in the target area at the current time period, and construct a herbicide degradation half-life database according to the initial herbicide recommendation set;

[0045] S106: Obtain the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area at the current time period through the herbicide degradation half-life database and the ecological environment characteristic data in the target area at the current time period;

[0046] S108: Set a degradation half-life threshold, and analyze the initial herbicide recommendation set according to the degradation half-life of each herbicide type in the target area under the environmental characteristic data to obtain the final herbicide recommendation set.

[0047] It should be noted that the present invention selects the optimal herbicide according to the degradation half-life of each herbicide type under the ecological environment characteristic data in the target area at the current time period, so as to reduce ecological pollution.

[0048] Further, in this method, obtaining the weed type information in the target area and obtaining the initial herbicide recommendation set according to the weed type information in the target area specifically include:

[0049] Collect the weed image data information in the target area, construct a retrieval sample based on the weed image data information in the target area, and conduct retrieval analysis based on the retrieval sample to obtain the weed type information in the target area;

[0050] Exemplarily, it can be analyzed through image similarity comparison, or through machine learning technology, or through network retrieval analysis, etc.

[0051] Construct a retrieval label according to the weed type information in the target area, conduct a retrieval through big data based on the retrieval label to obtain the weed type information in the target area, and construct an initial herbicide recommendation set;

[0052] Take the weed type information in the target area as a data sample and input it into the initial herbicide recommendation set, and output it from the initial herbicide recommendation set.

[0053] Further, in this method, collecting the ecological environment characteristic data in the target area at the current time period specifically includes:

[0054] Collect historical ecological environment characteristic data information in the target area, construct an ecological environment characteristic data prediction model based on a deep neural network, and input the historical ecological environment characteristic data information in the target area into the ecological environment characteristic data prediction model for learning;

[0055] Exemplarily, the deep neural network includes a multi-layer perceptron neural network, a convolutional neural network, a long short-term memory neural network, a recurrent neural network, etc.

[0056] Set the learning rate and training termination conditions, learn the ecological environment characteristic data prediction model based on the learning rate, and determine whether the ecological environment characteristic data prediction model reaches the training termination conditions;

[0057] When the ecological environment characteristic data prediction model reaches the training termination conditions, the training of the ecological environment characteristic data prediction model terminates, save the model parameters of the ecological environment characteristic data prediction model, and output the ecological environment characteristic data prediction model;

[0058] Obtain the ecological environment characteristic data in the target area within a preset time, input the ecological environment characteristic data in the target area within the preset time into the ecological environment characteristic data prediction model for prediction, and obtain the ecological environment characteristic data in the target area during the current time period

[0059] It should be noted that the ecological environment characteristic data information includes data such as the type information of the soil, environmental temperature characteristic information, environmental humidity information, soil humidity information, soil air permeability information, etc. Through this method, the ecological environment characteristic data in the target area during the current time period can be obtained.

[0060] Furthermore, in this method, construct a herbicide degradation half-life database according to the initial herbicide recommendation set, specifically including:

[0061] Based on the herbicide type information in the initial herbicide recommendation set as the retrieval keyword, perform data retrieval based on the keyword;

[0062] Through data retrieval, obtain the herbicide degradation half-life data of each herbicide type information in the initial herbicide recommendation set under each ecological environment characteristic data, and construct a database;

[0063] Input the herbicide degradation half-life data of each herbicide type information in the initial herbicide recommendation set under each ecological environment characteristic data into the database for storage.

[0064] Further, in this method, the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area during the current period is obtained through the herbicide degradation half-life database and the ecological environment characteristic data in the target area during the current period. Specifically, it includes:

[0065] Input the ecological environment characteristic data in the target area during the current period into the herbicide degradation half-life database for data matching;

[0066] Through data matching, obtain the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area during the current period;

[0067] And output the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area during the current period.

[0068] It should be noted that different herbicide types and different ecological environment data have different degradation half-lives. For example, the field degradation half-life of diphenyl ether herbicides is generally between 0.3 and 28.4 days. Its degradation half-life in the soil is 0.3 to 28.4 days, and its degradation half-life on plant-derived media is 1.1 to 13.3 days. The degradation half-life of the same herbicide in the soil is longer than that on the crop. The reason may be that the types and quantities of microorganisms between the two are different, and the plant itself can absorb part of the herbicide. The degradation half-lives of fluoroglycofen-ethyl in the soil and cotton are the shortest, being 0.3 to 1 day and 1.76 to 1.8 days respectively; the degradation half-lives of fomesafen in the soil and soybean are the longest, being 18.08 to 28.4 days and 2.7 - 9.8 days respectively. Its degradation rate in the soil is positively correlated with soil temperature, soil organic matter content, and soil water content, and negatively correlated with soil pH, etc. Another example is that the degradation rate of oxyfluorfen herbicide is faster in an alkaline environment than in an acidic environment, probably because the stability of oxyfluorfen in an alkaline environment is poor, and the photolysis rate of oxyfluorfen slows down with the increase of its concentration. And some herbicides cannot be degraded and will remain in the soil for a long time. Through this method combined with the concept of greenness, the pesticide residue pollution can be further reduced.

[0069] As Figure 2 shown, further, in this method, a degradation half-life threshold is set, and the initial herbicide recommendation set is analyzed according to the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area to obtain the final herbicide recommendation set. Specifically:

[0070] S202: Set the degradation half-life threshold, and determine whether the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area is greater than the degradation half-life threshold;

[0071] S204: When the degradation half-life is greater than the degradation half-life threshold, delete the herbicide type corresponding to the degradation half-life greater than the degradation half-life threshold from the initial herbicide recommendation set;

[0072] S206: When the degradation half-life is not greater than the degradation half-life threshold, keep the herbicide type corresponding to the degradation half-life not greater than the degradation half-life threshold unchanged in the initial herbicide recommendation set;

[0073] S208: After all the herbicide types in the initial herbicide recommendation set have been analyzed, update the initial herbicide recommendation set and output it as the final herbicide recommendation set.

[0074] It should be noted that through this method, an excellent final herbicide recommendation set can be selected, which can achieve the weeding effect while not polluting the ecological environment.

[0075] In addition, this method also includes:

[0076] Obtain the pesticide chemical composition data information applied in the target area within a preset time, and determine whether the herbicide component data in the final herbicide recommendation set reacts chemically with the pesticide chemical composition data information applied in the target area within a preset time;

[0077] When the herbicide component data in the final herbicide recommendation set reacts chemically with the pesticide chemical composition data information applied in the target area within a preset time, delete the herbicide type corresponding to the chemical reaction with the pesticide chemical composition data information applied in the target area within a preset time from the final herbicide recommendation set;

[0078] When the herbicide component data in the final herbicide recommendation set does not react chemically with the pesticide chemical composition data information applied in the target area within a preset time, it continues to be maintained in the final herbicide recommendation set;

[0079] After deletion, count the final herbicide recommendation set and update the final herbicide recommendation set.

[0080] It should be noted that in fact, pesticides may have been applied in the crop area, and through this method, the rationality of herbicide recommendation can be further improved.

[0081] Such as Figure 3As shown in the figure, the second aspect of the present invention provides an intelligent herbicide recommendation system 4 based on ecological data analysis, including a memory 41 and a processor 42. The memory 41 includes a memory and a processor. The memory 41 includes an intelligent herbicide recommendation method program based on ecological data analysis. When the intelligent herbicide recommendation method program based on ecological data analysis is executed by the processor 42, the following steps are implemented:

[0082] Obtain the weed type information in the target area, and obtain an initial herbicide recommendation set according to the weed type information in the target area;

[0083] Collect the ecological environment characteristic data in the target area at the current time period, and construct a herbicide degradation half-life database according to the initial herbicide recommendation set;

[0084] Obtain the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area at the current time period through the herbicide degradation half-life database and the ecological environment characteristic data in the target area at the current time period;

[0085] Set a degradation half-life threshold, and analyze the initial herbicide recommendation set according to the degradation half-life of each herbicide type in the target area under the environmental characteristic data to obtain a final herbicide recommendation set.

[0086] Further, in this system, obtaining the weed type information in the target area and obtaining an initial herbicide recommendation set according to the weed type information in the target area specifically include:

[0087] Collect the weed image data information in the target area, construct a retrieval sample based on the weed image data information in the target area, and perform retrieval analysis based on the retrieval sample to obtain the weed type information in the target area;

[0088] Construct a retrieval label according to the weed type information in the target area, perform a retrieval through big data based on the retrieval label, obtain the weed type information in the target area, and construct an initial herbicide recommendation set;

[0089] Use the weed type information in the target area as a data sample to input into the initial herbicide recommendation set and output from the initial herbicide recommendation set.

[0090] Further, in this system, collecting the ecological environment characteristic data in the target area at the current time period specifically includes:

[0091] Collect historical ecological environment characteristic data information in the target area, construct an ecological environment characteristic data prediction model based on a deep neural network, and input the historical ecological environment characteristic data information in the target area into the ecological environment characteristic data prediction model for learning;

[0092] Set the learning rate and training termination conditions, learn the ecological environment characteristic data prediction model based on the learning rate, and determine whether the ecological environment characteristic data prediction model reaches the training termination conditions;

[0093] When the ecological environment characteristic data prediction model reaches the training termination conditions, the training of the ecological environment characteristic data prediction model terminates, save the model parameters of the ecological environment characteristic data prediction model, and output the ecological environment characteristic data prediction model;

[0094] Obtain the ecological environment characteristic data in the target area within a preset time, input the ecological environment characteristic data in the target area within the preset time into the ecological environment characteristic data prediction model for prediction, and obtain the ecological environment characteristic data in the target area during the current time period

[0095] Further, in this system, construct a herbicide degradation half-life database according to the initial herbicide recommendation set, specifically including:

[0096] Based on the herbicide type information in the initial herbicide recommendation set as the retrieval keyword, perform data retrieval based on the keyword;

[0097] Through data retrieval, obtain the herbicide degradation half-life data of each herbicide type information in the initial herbicide recommendation set under each ecological environment characteristic data, and construct a database;

[0098] Input the herbicide degradation half-life data of each herbicide type information in the initial herbicide recommendation set under each ecological environment characteristic data into the database for storage.

[0099] Further, in this system, obtain the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area during the current time period through the herbicide degradation half-life database and the ecological environment characteristic data in the target area during the current time period, specifically including:

[0100] Input the ecological environment characteristic data in the target area during the current time period into the herbicide degradation half-life database for data matching;

[0101] Through data matching, obtain the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area during the current time period;

[0102] Output the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area during the current time period.

[0103] Furthermore, in this system, a degradation half-life threshold is set, and the initial herbicide recommendation set is analyzed based on the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area to obtain the final herbicide recommendation set. Specifically:

[0104] Set the degradation half-life threshold, and determine whether the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area is greater than the degradation half-life threshold;

[0105] When the degradation half-life is greater than the degradation half-life threshold, delete the herbicide type corresponding to the degradation half-life greater than the degradation half-life threshold from the initial herbicide recommendation set;

[0106] When the degradation half-life is not greater than the degradation half-life threshold, keep the herbicide type corresponding to the degradation half-life not greater than the degradation half-life threshold unchanged in the initial herbicide recommendation set;

[0107] After all the herbicide types in the initial herbicide recommendation set have been analyzed, update the initial herbicide recommendation set and output it as the final herbicide recommendation set.

[0108] The third aspect of the present invention provides a computer-readable storage medium, which includes a program for the intelligent herbicide recommendation method based on ecological data analysis. When the program for the intelligent herbicide recommendation method based on ecological data analysis is executed by a processor, the steps of any one of the intelligent herbicide recommendation methods based on ecological data analysis are implemented.

[0109] In several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed with each other can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical, or other forms.

[0110] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0111] In addition, in each embodiment of the present invention, the various functional units may all be integrated in one processing unit, or each unit may be separately a unit on its own, or two or more units may be integrated in one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of a combination of hardware and software functional units.

[0112] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including the above method embodiments; and the foregoing storage medium includes: removable storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks and other various media that can store program code.

[0113] Alternatively, if the above-mentioned integrated units of the present invention are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of the various embodiments of the present invention. And the foregoing storage medium includes: removable storage devices, ROM, RAM, magnetic disks, or optical disks and other various media that can store program code.

[0114] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An intelligent herbicide recommendation method based on ecological data analysis, characterized in that: The following steps are involved: Acquire weed type information in a target area, and acquire an initial herbicide recommendation set according to the weed type information in the target area; Collecting ecological environment characteristic data in the target area in the current time period, and constructing a herbicide degradation half-life database based on the initial herbicide recommendation set; Obtaining the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area in the current time period through the herbicide degradation half-life database and the ecological environment characteristic data in the target area in the current time period; A degradation half-life threshold is set, and the initial herbicide recommendation set is analyzed according to the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area to obtain a final herbicide recommendation set.

2. The method for intelligently recommending herbicides based on ecological data analysis according to claim 1, characterized in that: Acquiring weed type information in a target area, and acquiring an initial herbicide recommendation set according to the weed type information in the target area, specifically comprising: Collecting weed image data information in a target area, constructing a retrieval sample based on the weed image data information in the target area, performing retrieval analysis based on the retrieval sample, and acquiring weed type information in the target area; Constructing a search tag according to the weed type information in the target area, performing a search through big data based on the search tag to obtain the weed type information in the target area, and constructing an initial herbicide recommendation set; The weed type information in the target area is input into the initial herbicide recommendation set as a data sample, and the initial herbicide recommendation set is output.

3. The method for intelligently recommending herbicides based on ecological data analysis according to claim 1, characterized in that: Collect ecological environment characteristic data in the target area in the current time period, including: Collect historical ecological environment characteristic data information in the target area, and build an ecological environment characteristic data prediction model based on a deep neural network, and input the historical ecological environment characteristic data information in the target area into the ecological environment characteristic data prediction model for learning; Setting a learning rate and a training termination condition, learning the ecological environment characteristic data prediction model based on the learning rate, and determining whether the ecological environment characteristic data prediction model reaches the training termination condition; When the ecological environment characteristic data prediction model reaches the training termination condition, the training of the ecological environment characteristic data prediction model is terminated, the model parameters of the ecological environment characteristic data prediction model are saved, and the ecological environment characteristic data prediction model is output; The ecological environment characteristic data in the target area within a preset time is obtained, and the ecological environment characteristic data in the target area within the preset time is input into the ecological environment characteristic data prediction model for prediction, so as to obtain the ecological environment characteristic data in the target area in the current time period.

4. The method for intelligently recommending herbicides based on ecological data analysis according to claim 1, characterized in that: Constructing a herbicide degradation half-life database according to the initial herbicide recommendation set specifically includes: Based on the herbicide type information in the initial herbicide recommendation set as a search keyword, searching through data based on the keyword; Through data retrieval, the herbicide degradation half-life data of each herbicide type information under each ecological environment characteristic data in the initial herbicide recommendation set is obtained, and a database is constructed; The herbicide degradation half-life data of each herbicide type information under each ecological environment characteristic data in the initial herbicide recommendation set is input into the database for storage.

5. The method for intelligently recommending herbicides based on ecological data analysis according to claim 1, characterized in that: Obtaining the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area in the current time period through the herbicide degradation half-life database and the ecological environment characteristic data in the target area in the current time period, specifically comprising: Inputting the ecological environment characteristic data in the target area in the current time period into the herbicide degradation half-life database for data matching; By data matching, the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area in the current time period is obtained; And the degradation half-life of each herbicide type in the initial herbicide recommendation set under the ecological environment characteristic data in the target area in the current time period is output.

6. The method for intelligently recommending herbicides based on ecological data analysis according to claim 1, characterized in that: A degradation half-life threshold is set, and the initial herbicide recommendation set is analyzed according to the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area to obtain a final herbicide recommendation set, specifically: Setting a degradation half-life threshold, and determining whether the degradation half-life of each herbicide type in the initial herbicide recommendation set under the environmental characteristic data in the target area is greater than the degradation half-life threshold; When the degradation half-life is greater than the degradation half-life threshold, the herbicide type corresponding to the degradation half-life greater than the degradation half-life threshold is deleted from the initial herbicide recommendation set; When the degradation half-life is not greater than the degradation half-life threshold, the herbicide type corresponding to the degradation half-life being not greater than the degradation half-life threshold is maintained unchanged in the initial herbicide recommendation set; After all the herbicide types in the initial herbicide recommendation set are analyzed, the initial herbicide recommendation set is updated and output as a final herbicide recommendation set.

7. The herbicide intelligent recommendation system based on ecological data analysis is characterized by: It includes a memory and a processor, the memory includes a memory and a processor, the memory includes a herbicide intelligent recommendation method program based on ecological data analysis, and when the herbicide intelligent recommendation method program based on ecological data analysis is executed by the processor, the steps of the herbicide intelligent recommendation method based on ecological data analysis as described in any one of claims 1-6 are implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a program for an intelligent herbicide recommendation method based on ecological data analysis. When the program for an intelligent herbicide recommendation method based on ecological data analysis is executed by a processor, the steps of the intelligent herbicide recommendation method based on ecological data analysis as described in any one of claims 1 to 6 are implemented.

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