JP6810967B2 - Agricultural model extension system, agricultural model extension method and agricultural model extension program - Google Patents

Description

The present invention relates to an agricultural model dissemination system or the like capable of disseminating various agricultural models.

In order to adapt to climate change, agricultural testing and research institutes are conducting research on agricultural support technologies such as growth prediction, high temperature damage prediction, and cultivation management technology for each region according to the variety and cultivation method of crops. In order to utilize these agricultural assistance technologies, it is necessary to have a mechanism to perform forecast calculations based on actual weather data and disseminate warning information based on the calculation results to the region.

As a practical study utilizing agricultural support technology, Non-Patent Document 1 supports the determination of the optimum transplantation period that is less susceptible to high temperature damage in order to reduce the high temperature damage of the sake rice variety "Yamada Nishiki" in Hyogo Prefecture. The "Yamada Nishiki Optimal Crop Seasoning Support System" and the "Yamada Nishiki High Temperature Hazard Warning System" that displays the fields where the occurrence of white immature grains is predicted from the weekly weather forecast are disclosed.

In addition, Non-Patent Document 2 discloses a framework for implementing an agricultural model as a web application.

Masaru Ikegami, Masanobu Kato "Development of Cultivation Support System to Reduce High Temperature Damage to Sake Rice" Crop Research Vol.59, pp.63-65 2014 Kei Tanaka "Study on Framework of Distributed Cooperative System in Agricultural Simulation Model" Central Agricultural Research Institute Research Report No.20, pp.1-115 2013

However, the system described in Non-Patent Document 1 is supposed to be used in Hyogo prefecture, and in order to use it in other areas, it is necessary to add meteorological data or modify the program. Similarly, in order to use it with varieties other than Yamada Nishiki, it is necessary to modify the program.

In addition, in the technology described in Non-Patent Document 2, it is necessary to develop a system by utilizing a framework, and agricultural researchers such as agricultural testing and research institutes who do not have knowledge of system development can easily utilize agricultural support technology. Can't.

The present invention has been made in view of the above-mentioned problems, and an object of the present invention is to enable an agricultural researcher to disseminate various agricultural models without modifying an existing system or developing a new system. It is to provide an agricultural model extension system that allows users such as agricultural researchers, agricultural innovation support specialists, extension instructors, and farmers to easily utilize agricultural models.

The first invention for achieving the above object receives an input of agricultural models, including model formula meteorological parameters is included as a variable, and agricultural model input receiving unit that be stored in agriculture model file, the model equation accepting an input of the risk evaluation rules including risk level and risk criteria corresponding to the calculation result, agricultural meteorological data including the risk assessment rule input accepting section you stored in the risk assessment rule file, the data of the meteorological parameters each region mesh The storage unit that stores the data, the model formula calculation unit that substitutes the data of the meteorological element into the model formula and calculates the calculation result of the model formula, and the determination of the risk level according to the risk standard for each of the regional meshes. The model formula of the agricultural model file is provided with a risk level calculation unit for calculating the result and a display control unit for controlling the display of the calculation result of the model formula and the determination result of the risk level for each region mesh. Can be input so as to include the calculation result of the model formula related to the other agricultural model file as a variable, and the risk standard related to the risk evaluation rule file is the model formula related to a plurality of the agricultural model files. It is an agricultural model dissemination system characterized in that it can be input based on the calculation result of . According to the agricultural model dissemination system of the first invention, agricultural researchers can disseminate various agricultural models without modifying existing systems or developing new systems, and agricultural researchers and agricultural innovation support specialists. Users such as staff, extension instructors, and farmers can easily utilize the agricultural model. There are differences in agricultural models between regions such as prefectures, even for the same crop, depending on the variety and cultivation method. It is equipped with an agricultural model input reception area to enable the use of local agricultural models. In addition, a risk evaluation rule input reception unit is provided so that risk evaluation using an agricultural model can be easily performed, including visualization on a map. You can then customize the file to create a region-specific file. In addition, with the progress of file maintenance in this way, it becomes possible to utilize complex files.

The first invention, alert criteria corresponding to the level of risk determination result, and accepts the input of alarm information generation rules comprising the measures information if it exceeds the alert criteria, you stored alarm information generation rule file When it is determined whether or not the judgment result of the risk level exceeds the warning standard for each of the warning information generation rule input reception unit and the field position of the user represented by the area mesh, and the warning standard is exceeded. Further includes a warning information generation unit that generates warning information including the risk level determination result and the countermeasure information, and a warning information notification unit that notifies a user registered in advance of the warning information. The display control unit controls the display of the warning information for each field position, and the warning standard related to the warning information generation rule file is based on the determination result of the risk level related to the plurality of risk evaluation rule files. It may be possible to input as follows. As a result, it is possible to promptly notify local agricultural innovation support specialists, extension instructors, farmers, etc. of warning information when caution is required. It is equipped with a warning information generation rule input reception unit to convey to the user the warning information judged from the risk evaluation results calculated on a daily basis, including predictions. You can then customize the file to create a region-specific file. In addition, with the progress of file maintenance in this way, it becomes possible to utilize complex files.

Further, the agricultural model input receiving unit inputs dummy data of the meteorological element stored in advance into the model formula, and calculates the calculation result of the model formula to confirm whether or not there is an error. You may.

Further, when the variable of the model formula includes the calculation result of the other model formula, the agricultural model input reception unit first calculates the calculation result of the other model formula and calculates the value of the value of the model. It may be confirmed whether or not there is an error by inputting into the formula and calculating the calculation result of the model formula .

Further, the agricultural model input receiving unit may make an error when the model formula and the other model formula are circular references including the calculation results of each other as variables .

The second invention is a computer receives an input of agricultural models, including model formula meteorological parameters is included as a variable, the steps you stored in agriculture model file, the risk levels and risk corresponding to the calculation result of the model formula accepting an input of the risk evaluation rules including a reference, the steps you stored in the risk assessment rule file, and storing agricultural meteorological data including data of the meteorological parameters each region mesh, said data of said meteorological model A step of substituting into the formula to calculate the calculation result of the model formula, a step of calculating the judgment result of the risk level according to the risk standard for each region mesh, and a calculation of the model formula for each region mesh. The step of controlling the display of the result and the determination result of the risk level is executed so that the model formula of the agricultural model file includes the calculation result of the model formula related to the other agricultural model file as a variable. It is possible to input, and the risk standard according to the risk evaluation rule file is an agricultural model dissemination method characterized in that it can be input based on the calculation result of the model formula related to a plurality of the agricultural model files. .. According to the method of disseminating agricultural models of the second invention, agricultural researchers can disseminate various agricultural models without modifying existing systems or developing new systems, and agricultural researchers specialize in agricultural innovation support. Users such as staff, extension instructors, and farmers can easily utilize the agricultural model. You can then customize the file to create a region-specific file. In addition, with the progress of file maintenance in this way, it becomes possible to utilize complex files.

A third invention is a computer receives an input of agricultural models, including model formula meteorological parameters is included as a variable, the steps you stored in agriculture model file, the risk levels and risk corresponding to the calculation result of the model formula accepting an input of the risk evaluation rules including a reference, the steps you stored in the risk assessment rule file, and storing agricultural meteorological data including data of the meteorological parameters each region mesh, said data of said meteorological model A step of substituting into the formula to calculate the calculation result of the model formula, a step of calculating the judgment result of the risk level according to the risk standard for each region mesh, and a calculation of the model formula for each region mesh. The step of controlling the display of the result and the determination result of the risk level is executed so that the model formula of the agricultural model file includes the calculation result of the model formula related to the other agricultural model file as a variable. It is possible to input, and the risk standard related to the risk evaluation rule file is an agricultural model dissemination program for executing so that it can be input based on the calculation result of the model formula related to a plurality of the agricultural model files. is there. By installing the agricultural model dissemination program of the third invention on a general-purpose computer, the agricultural model dissemination system of the first invention can be obtained.

According to the present invention, various agricultural models can be disseminated without modifying an existing system or newly developing a system, and users such as agricultural researchers, agricultural innovation support specialists, extension instructors, and farmers can easily disseminate agricultural models. It is possible to provide an agricultural model dissemination system that can be utilized.

Diagram showing the outline of agricultural model extension system 1 Diagram showing an example of agricultural model file 4 Diagram showing an example of risk evaluation rule file 5 The figure which shows an example of the warning information generation rule file 6. Flowchart showing the processing flow of the input receiving unit 30 Flowchart showing the processing flow of the model formula calculation unit 34 Flowchart showing the processing flow of the risk level calculation unit 35 A flowchart showing the processing flow of the warning information generation unit 36 and the warning information notification unit 37. Flow chart showing the processing flow of the display control unit 38 Diagram showing an input example

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. The agricultural model in the embodiment of the present invention is a simulation model relating to agricultural support techniques such as growth prediction, high temperature damage prediction, and cultivation management technology for each region according to the variety and cultivation method of the crop. The agricultural model may be any model as long as it is represented by a model formula in which meteorological elements are included as variables.

FIG. 1 is a diagram showing an outline of the agricultural model extension system 1. As shown in FIG. 1, the agricultural model extension system 1 is connected to a terminal 2 used by users such as an agricultural researcher, an agricultural innovation support specialist, an extension instructor, and a farmer, and is connected to the terminal 2 via a network 8. It is composed of a server 3 and a server 3. The agricultural model dissemination system 1 is operated to disseminate agricultural support technology in each region (prefecture, etc.). Here, the agricultural researcher studies the agricultural support technology in the area at an agricultural testing and research institute or the like. Agricultural innovation support specialists provide support to extension instructors. The extension instructor gives guidance to the farmers. These organizational forms are common throughout the country.

The terminal 2 and the server 3 include a CPU as a control unit (abbreviation of "Central Processing Unit"), a memory as a main storage unit, an HDD as an auxiliary storage unit (abbreviation of "Hard Disk Drive"), a flash memory, and a display unit. It has a liquid crystal display as an input unit, a keyboard and mouse as an input unit, a touch panel display, a LAN (Local Area Network) as a wired communication unit, a wireless module as a wireless communication unit, and the like.

The HDD or flash memory as an auxiliary storage unit stores an OS (abbreviation of "Operating System"), an application program, data required for processing, and the like. The CPUs of the terminal 2 and the server 3 read the OS and application programs from the auxiliary storage unit, store them in the main storage unit, control other devices while accessing the main storage unit, and execute the processing described later. The terminal 2 is, for example, a desktop PC, a notebook PC, a tablet terminal, a smartphone, or the like. The server 3 may be, for example, a server computer arranged in a data center or the like, or a server computer arranged in a company or the like. Further, the server 3 may be realized in one housing, or may be realized in a plurality of housings. The network 8 is, for example, an in-house LAN, the Internet, or the like.

When the agricultural model dissemination system 1 is constructed as a web application, a web browsing software program is installed in the auxiliary storage unit of the terminal 2, and a web application program is installed in the auxiliary storage unit of the server 3. , The database required for the agricultural model extension system 1 is constructed. When the agricultural model extension system 1 is constructed as a client-server application, an application program that provides the client function of the agricultural model extension system 1 is installed in the auxiliary storage unit of the terminal 2, and the auxiliary storage unit of the server 3 is installed. An application program that provides a server function of the agricultural model extension system 1 is installed in the system, and a database required for the agricultural model extension system 1 is constructed. In this case, the terminal 2 may have some functions of the server 3 described later.

The hardware configuration of the agricultural model extension system 1 is not limited to the example shown in FIG. For example, when built as a stand-alone application, only one computer is required and it is not necessary to be connected to the network 8. In the following, a case where the agricultural model extension system 1 is constructed as a web application will be described as an example.

The server 3 includes an input receiving unit 30 that receives data input by the user and stores it in a file or the like. The input receiving unit 30 receives the input of the agricultural model including the model formula including the meteorological element as a variable, and stores the agricultural model input receiving unit 31 in the agricultural model file 4, the risk level corresponding to the calculation result of the model formula, and the risk level. The risk evaluation rule input reception unit 32 that accepts the input of the risk evaluation rule including the risk standard and stores it in the risk evaluation rule file 5, the caution standard corresponding to the judgment result of the risk level, and the countermeasure when the caution standard is exceeded. It includes a warning information generation rule input receiving unit 33 that accepts input of a warning information generation rule including information and stores it in the warning information generation rule file 6. The data storage means is not limited to a file, and may be a database.

FIG. 2 is a diagram showing an example of the agricultural model file 4. The data items of the agricultural model file 4 are the agricultural model ID 401 that uniquely identifies the agricultural model as identification information and is automatically assigned by the server 3, and the character string input by the user, and the name of the agricultural model. The agricultural model name 402 shown, the creation date and time 403 automatically set from the system time at the time of file creation, and the user ID that uniquely identifies the user, the creator 404 in which the user ID at the time of file creation is set. And, including. In the example of the input contents shown in FIG. 2, the agricultural model ID 401 is "m1234", the agricultural model name 402 is "daily average saturation", the creation date and time 403 is "2017/07/10 13:00:00", and the creator 404. Is "u2468". Saturation is an index showing how much more water vapor can enter in air at a certain temperature and humidity.

Further, the data items of the agricultural model file 4 are character strings input by the user as explanatory information, and are the outline / technical data 405 showing the outline of the agricultural model and the information of the technical data, and the characters input by the user. It is a column and includes usage / use / restriction 406, which indicates the usage, use, and restriction of the agricultural model. In the example of the input contents shown in Fig. 2, the outline / technical data 405 is "free capacity of water vapor per 1 m ^{3 of} air (g / m ³ )", and the usage / use / restriction 406 is "moisture of plants due to saturation". "Understanding the state".

Further, the data item of the agricultural model file 4 is selected by the user from the meteorological element 407 selected by the user and the agricultural model ID related to the input agricultural model as the variable information included in the model formula of the agricultural model. 408 and the calculation result of other model formulas. A plurality of meteorological elements 407 and calculation results 408 of other model formulas can be selected. In the example of the input contents shown in FIG. 2, the meteorological element 407 is “daily average temperature TMP_mean” and “daily average relative humidity RH”, and the calculation result 408 of another model formula is “none”.

Further, the data items of the agricultural model file 4 are model formula 409 composed of constants, variables and arithmetic formulas, initial value 410 of model formula 409, and data type 411 of the calculation result of the model formula as model formula information. , Regional mesh calculation range 412 and. In the example of the input contents shown in FIG. 2, the model formula 409 is “1323 × exp ((17.269 × TMP_mean) / (237.3 + TMP_mean)) / (273.16 + TMP_mean) × (1-RH / 100)”, and the initial value is 410. Is "none", the data type 411 is "floating point number", and the area mesh calculation range 412 is "all". In the area mesh calculation range 412, in addition to "all", a specific area mesh such as "user field position" can be specified as the calculation range. Here, the variable TMP_mean included in the model formula 409 indicates the "daily mean temperature TMP_mean" of the meteorological element 407, and the variable RH indicates the "daily mean relative humidity RH" of the meteorological element 407.

Further, the data items of the agricultural model file 4 include, as execution condition information, a start date 413 for starting the execution of the calculation process of the agricultural model, an end date 414 for ending the execution of the calculation process of the agricultural model, and the calculation of the agricultural model. Includes execution time 415, which indicates the daily execution start time of the process. In the example of the input contents shown in FIG. 2, the start date 413 is “August 1”, the end date 414 is “September 30”, and the execution time 415 is “8:00 am”.

FIG. 3 is a diagram showing an example of the risk evaluation rule file 5. The data items of the risk evaluation rule file 5 are a risk evaluation rule ID 501 that uniquely identifies the risk evaluation rule as identification information and is automatically assigned by the server 3, and a character string input by the user, and is a risk evaluation. The risk evaluation rule name 502 indicating the name of the rule, the creation date and time 503 automatically set from the system time at the time of file creation, and the creator 504 in which the user ID at the time of file creation is set are included. In the example of the input contents shown in FIG. 3, the risk evaluation rule ID 501 is "r1357", the risk evaluation rule name 502 is "risk evaluation of paddy rice trunk cracking due to saturation", and the creation date and time 503 is "2017/07/10 13:30: 00 ”, the creator 504 is“ u2468 ”.

Further, the data items of the risk evaluation rule file 5 are character strings input by the user as explanatory information, and are input by the user as an outline / technical material 505 showing an outline of the risk evaluation rule and information of the technical data. Includes usage, usage, and restrictions 506 that indicate the usage, usage, and restrictions of the risk evaluation rule. In the example of the input contents shown in FIG. 3, the outline / technical data 505 “evaluates the risk of paddy rice barrel cracking from the saturation (including the predicted value)”, and the usage / use / restriction 506 “saturation value and danger”. Grasp the day and area that exceed the standard. "

Further, the data item of the risk evaluation rule file 5 includes the agricultural model ID 507 selected by the user from the input agricultural model IDs related to the agricultural model as the evaluation target information. A plurality of agricultural model IDs 507 can be selected. In the example of the input contents shown in FIG. 3, the agricultural model ID 507 is “m1234”.

Further, the data items of the risk evaluation rule file 5 include, as rule information, a risk level 508 indicating the number and labels of the risk levels, and a risk standard 509 indicating the criteria for allocating the risk levels. In the example of the input contents shown in FIG. 3, the risk level 508 is “1: dangerous, 0: none”, and the risk standard 509 is “dangerous when it exceeds 9.0 g / m ³ ”.

Further, the data items of the risk evaluation rule file 5 include, as execution condition information, a start date 510 for starting the execution of the risk evaluation judgment process, an end date 511 for ending the execution of the risk evaluation judgment process, and the risk evaluation. Includes execution time 512, which indicates the daily execution start time of the determination process. In the example of the input contents shown in FIG. 3, the start date 510 is “August 1”, the end date 511 is “September 30”, and the execution time 512 is “after the calculation of m1234”.

Further, the data items of the risk evaluation rule file 5 are, as display control information, a mesh display mode 513 showing a legend and color coding related to mesh display, and a graph display mode showing a graph display title, a range of data axes, and a graph type. 514 and. In the example of the input contents shown in FIG. 3, the mesh display mode 513 is "color-coded in 7 steps (blue to red)", the graph display mode 514 is "vertical axis: saturation value (g / m ³ ), horizontal axis: date". (10 days live, 10 days forecast), Graph type: Line ".

FIG. 4 is a diagram showing an example of the warning information generation rule file 6. The data items of the warning information generation rule file 6 are the warning information generation rule ID 601 that uniquely identifies the warning information generation rule and is automatically assigned by the server 3 as identification information, and a character string input by the user. , The warning information generation rule name 602 indicating the name of the warning information generation rule, the creation date and time 603 that is automatically set from the system time at the time of file creation, and the creator 604 that sets the user ID at the time of file creation. including. In the example of the input contents shown in FIG. 4, the warning information generation rule ID 601 is "a1235", the warning information generation rule name 602 is "warning information for cracking paddy rice due to saturation", and the creation date and time 603 is "2017/07/10 14: 00:00 ", the creator 604 is" u2468 ".

Further, the data items of the warning information generation rule file 6 are character strings input by the user as explanatory information, and the outline / technical material 605 showing the outline of the warning information generation rule and the information of the technical data, and the user. It is an input character string and includes usage / use / restriction 606 indicating usage, use, and restriction of the warning information generation rule. In the example of the input contents shown in FIG. 4, the outline / technical data 605 "generates warning information for paddy rice barrel cracking from the saturation (including the predicted value)", and the usage / use / restriction 606 "saturation value is". When the danger level is exceeded, warning information is transmitted. "

Further, the data item of the warning information generation rule file 6 includes the risk evaluation rule ID 607 selected by the user from the risk evaluation rule IDs related to the input risk evaluation rules as the evaluation target information. A plurality of risk evaluation rule ID 607 can be selected. In the example of the input content shown in FIG. 4, the risk evaluation rule ID 607 is “r1357”.

Further, the data items of the warning information generation rule file 6 include, as rule information, a warning level 608 indicating the number and label of the warning level, a warning standard 609 indicating a standard for allocating to the warning level, and countermeasure information 610 for each warning level. ,including. In the example of the input contents shown in FIG. 4, the alert level 608 is "1: dangerous, 0: none", the alert standard 609 is "danger if" 1: dangerous "is 1 day or more in the predicted period", and countermeasure information. 610 is "early harvest if the foehn dry days continue around maturity".

Further, the data items of the warning information generation rule file 6 include the start date 611 for starting the execution of the warning information generation processing, the end date 612 for ending the execution of the warning information generation processing, and the warning information generation processing as execution condition information. Includes execution time 613, which indicates the daily execution start time of. In the example of the input contents shown in FIG. 4, the start date 611 is "August 1", the end date 612 is "September 30", and the execution time 613 is "after calculation of r1357".

Further, the data item of the warning information generation rule file 6 includes, as notification information, a format 614 used for shaping the warning information and a medium 615 used for notifying the warning information. In the example of the input contents shown in FIG. 4, the form 614 is "alert level: arranged at the top by day, countermeasure information: arranged at the bottom", and the medium 615 is "mail". The medium 615 may be, for example, a "push notification" if the terminal 2 is a smartphone.

FIG. 5 is a flowchart showing a processing flow of the input receiving unit 30. The processing of the input receiving unit 30 is executed in response to a request from the user. As shown in FIG. 5, when the terminal 2 receives a request for input of any of the agricultural model, the risk evaluation rule, and the warning information generation rule, the input reception unit 30 confirms whether or not to refer to the input file ( Step S11). When referring to the input file (Yes in step S11), the input reception unit 30 reads the input file (step S12) and duplicates the input file (step S13). On the other hand, when the input file is not referred to (No in step S11), the input receiving unit 30 newly creates a file (step S14).

Next, the input receiving unit 30 receives the input of data from the terminal 2 (step S15). In the case of inputting an agricultural model, the input receiving unit 30 provides an input interface screen similar to a scientific calculator and a preview display screen of the input model formula. This allows the user to enter a model formula for any agricultural model without having to create a program.

Next, the input receiving unit 30 performs a test with dummy data (step S16). In the case of an agricultural model, the input receiving unit 30 inputs dummy data of meteorological elements stored in advance into the model formula and calculates the calculation result of the model formula. When the calculation result of another model formula is included in the variable, the input receiving unit 30 calculates the calculation result of the other model formula first, inputs the value into the model formula, and calculates the model formula. Calculate the result. For example, when two model expressions include each other's calculation results as variables, a so-called "circular reference" results in an error. Similarly, in the case of the risk evaluation rule and the warning information generation rule, the input reception unit 30 first calculates the calculation result of the related model formula and the judgment result of the risk level, and uses the values to check if there is an error. Please check.

If there is an error (No in step S17), the input reception unit 30 repeats the process from the data input reception (step S15). On the other hand, if there is no error (Yes in step S17), the input receiving unit 30 saves the file (step S18) and ends the process.

Returning to the description of FIG. The server 3 further includes an agricultural weather data DB (abbreviation of "Database") 71 as a storage unit for storing agricultural weather data including data of weather elements for each regional mesh.

The agricultural meteorological data DB 71 is stored for each regional mesh in which regions are divided into meshes of substantially the same size based on latitude and longitude. The agricultural meteorological data DB 71 stores data periodically acquired from an external server, observation data by a meteorological observation device, and the like. Examples of data periodically acquired from an external server include mesh agricultural meteorological data provided by the National Research and Development Corporation, National Agriculture and Food Research Organization. This mesh agricultural meteorological data includes daily mean temperature, daily maximum temperature, daily minimum temperature, precipitation, sunshine time, total solar radiation, downward long wave radiation, daily average relative humidity, daily average wind speed, snow depth, and snow equivalent. Includes historical, forecast and normal data for meteorological factors such as water volume and water equivalent to daily snowfall. However, the data acquisition source is not particularly limited.

The server 3 further substitutes the data of the meteorological element into the model formula, calculates the calculation result of the model formula, and stores the model formula calculation result DB 72 as a storage unit in the model formula calculation unit 34, and for each region mesh. The calculation result of the model formula is calculated for each of the risk level calculation unit 35, which calculates the risk level determination result according to the risk standard and stores it in the risk level determination result DB73 as a storage unit, and the user's field position represented by the area mesh. It is determined whether or not the warning standard is exceeded, and if it exceeds the warning standard, warning information including the calculation result of the model formula and countermeasure information is generated and stored in the warning level judgment result DB74 as a storage unit. It includes an information generation unit 36 and a warning information notification unit 37 that notifies a user registered in advance of warning information.

The server 3 further includes a user DB 75 as a storage unit for storing user data. The user DB 75 includes user types (agricultural researchers, agricultural innovation support specialists, extension instructors, farmers, etc.), user email addresses, field locations, and jurisdiction areas (in the case of user types other than farmers). Data and data necessary for calculating an agricultural model such as a variety of agricultural products and a cultivation method (value specified by the initial value 410 of the agricultural model file 4) are stored. When the area mesh calculation range 412 of the agricultural model file 4 shown in FIG. 2 is set to the “user field position”, the model formula calculation unit 34 reads the field position (region mesh) and the initial value 410 from the user DB 75. In addition, the warning information notification unit 37 reads user data such as an e-mail address, a field position, and a jurisdiction area from the user DB 75 when notifying the user of the warning information. The warning information notification unit 37 can extract a user who has jurisdiction over a specific field position based on the jurisdiction area of the user DB 75. That is, the farmer and the extension instructor are associated with each other depending on the field position of the user DB75 and the jurisdiction area.

FIG. 6 is a flowchart showing a processing flow of the model formula calculation unit 34. The processing of the model formula calculation unit 34 is executed every day by, for example, batch processing. As shown in FIG. 6, the model formula calculation unit 34 reads the input agricultural model file 4 (step S21) and confirms whether or not the execution condition is satisfied (step S22). If the execution condition is not satisfied (No in step S22), the model formula calculation unit 34 ends the process. When the execution condition is satisfied (Yes in step S22), the model formula calculation unit 34 proceeds to step S23.

Next, the model formula calculation unit 34 acquires data of meteorological elements included as variables of the model formula, initial values, and calculation results of other model formulas (step S23).

Next, the model formula calculation unit 34 substitutes the meteorological element data, the initial values, and the calculation results of other model formulas acquired in step S23 into the model formula for each region mesh, and calculates the calculation result of the model formula. (Step S24). In the example shown in FIG. 2, the model formula calculation unit 34 substitutes the daily mean temperature TMP_mean and the daily mean relative humidity RH acquired from the agricultural meteorological data DB 71 into the model formula 409, and calculates the calculation result.

Next, the model formula calculation unit 34 stores the calculation result of the model formula calculated in step S24 in the model formula calculation result DB 72 for each region mesh (step S25), and for all the region meshes in the region mesh calculation range. It is confirmed whether or not the calculation is completed (step S26). When all the calculations are not completed (No in step S26), the model formula calculation unit 34 repeats the process from step S23. On the other hand, when all the calculations are completed (Yes in step S26), the model formula calculation unit 34 ends the process.

FIG. 7 is a flowchart showing a processing flow of the risk level calculation unit 35. The processing of the risk level calculation unit 35 is executed every day by, for example, batch processing. As shown in FIG. 7, the risk level calculation unit 35 reads the input risk evaluation rule file 5 (step S31) and confirms whether or not the execution condition is satisfied (step S32). If the execution condition is not satisfied (No in step S32), the risk level calculation unit 35 ends the process. When the execution condition is satisfied (Yes in step S32), the risk level calculation unit 35 proceeds to step S33.

Next, the risk level calculation unit 35 acquires the calculation result of the related agricultural model (step S33).

Next, the risk level calculation unit 35 calculates the risk level determination result for each regional mesh according to the risk standard (step S34). In the example shown in FIG. 3, the risk level calculation unit 35 determines that the calculation result of the agricultural model ID “m1234” acquired from the model formula calculation result DB72 exceeds the risk standard “9.0 g / m ³ ”. The risk level is set to "1: Danger", and if it is not exceeded, the risk level is set to "0: None".

Next, the risk level calculation unit 35 stores the risk level determination result calculated in step S34 in the risk level determination result DB 73 for each region mesh (step S35), and for all the region meshes in the region mesh calculation range. It is confirmed whether or not the calculation is completed (step S36). When all the calculations are not completed (No in step S36), the risk level calculation unit 35 repeats the process from step S33. On the other hand, when all the calculations are completed (Yes in step S36), the risk level calculation unit 35 ends the process.

FIG. 8 is a flowchart showing a processing flow of the warning information generation unit 36 and the warning information notification unit 37. The processing of the warning information generation unit 36 and the warning information notification unit 37 is executed every day by, for example, batch processing. As shown in FIG. 8, the warning information generation unit 36 reads the input warning information generation rule file 6 (step S41) and confirms whether or not the execution condition is satisfied (step S42). If the execution condition is not satisfied (No in step S42), the warning information generation unit 36 ends the process. When the execution condition is satisfied (Yes in step S42), the warning information generation unit 36 proceeds to step S43.

Next, the alert information generation unit 36 acquires the determination result of the related risk level (step S43).

Next, the warning information generation unit 36 calculates the judgment result of the warning level for each field position of the user represented by the area mesh according to the warning standard (step S44). In the example shown in FIG. 4, in the warning information generation unit 36, the risk level of the risk evaluation rule ID “r1357” acquired from the risk level determination result DB73 is the prediction period, and “1: danger” is one day or more. In some cases, the alert level is set to "1: Danger", and in the case of "0: None", the alert level is set to "0: None".

Next, the alert information generation unit 36 stores the alert level determination result calculated in step S44 in the alert level determination result DB 74 for each regional mesh (step S45), and for all the regional meshes in the regional mesh calculation range. It is confirmed whether or not the calculation is completed (step S46). When all the calculations are not completed (No in step S46), the warning information generation unit 36 repeats the process from step S43. On the other hand, when all the calculations are completed (Yes in step S46), the process proceeds to step S47.

Next, the warning information notification unit 37 confirms whether or not to notify the warning information (step S47). When not notifying the warning information (No in step S47), the warning information notification unit 37 ends the process. When notifying the warning information, the warning information notification unit 37 proceeds to step S48.

Next, the warning information notification unit 37 shapes the warning information (step S48), notifies by a medium (step S49), and ends the process. In the example shown in FIG. 4, the alert information notification unit 37 uses the text data in which the alert level is arranged at the upper part by day and the countermeasure information is arranged at the lower part as the email body, and emails to the email address of the user registered in advance. To send. If the alert level is "1: Danger" or "0: None" by day and the forecast period has "1: Danger" for 1 day or more, the countermeasure information is "Continued dry days with foehn around maturity." If it is an early harvest. " When notifying the warning information, the warning information notification unit 37 may refer to the jurisdiction area of the user DB 75 and notify the extension instructor or the like of the warning information regarding the field position of the farmer in the area. That is, the warning information notification unit 37 searches the jurisdiction area of the user DB75 based on the field position of the user (= farmer) who notifies the warning information, and another user (= extension instructor, etc.) who has jurisdiction over the target field position. ) Can also be notified of warning information.

Returning to the description of FIG. The server 3 further includes a display control unit 38 that controls the display of the calculation result of the model formula, the determination result of the risk level, and the warning information for each area mesh.

FIG. 9 is a flowchart showing a processing flow of the display control unit 38. The processing of the display control unit 38 is executed at the request of the user. As shown in FIG. 9, the display control unit 38 confirms whether or not to perform mesh display (step S51). When the mesh display is not performed (No in step S51), the display control unit 38 proceeds to step S55. When performing mesh display (Yes in step S51), the display control unit 38 proceeds to step S52.

Next, the display control unit 38 confirms whether or not the display mode of the mesh has been input (step S52). If the input has been completed (Yes in step S52), the display control unit 38 proceeds to step S54. If the input has not been completed (No in step S52), the display control unit 38 accepts the input of the mesh display mode (step S53). Then, the display control unit 38 generates mesh display data according to the input mode of the input mesh or the input mesh (step S54). In the example shown in FIG. 3, the mesh display data is color-coded (blue to red) in seven stages for each regional mesh. For example, if the saturation value is 9.0 g / m ³ or more, it is "red", if the saturation value is 7.5 to 9.0 g / m ³ , it is "orange", ..., The saturation value is 1.5 g / m. If it is less than ^3, it will be "blue".

Next, the display control unit 38 confirms whether or not to display a graph (step S55). When the graph is not displayed (No in step S55), the display control unit 38 proceeds to step S59. When performing graph display (Yes in step S55), the display control unit 38 proceeds to step S56.

Next, the display control unit 38 confirms whether or not the display mode of the graph has been input (step S56). If the input has been completed (Yes in step S56), the display control unit 38 proceeds to step S58. If the input has not been completed (No in step S56), the display control unit 38 accepts the input of the graph display mode (step S57). Then, the display control unit 38 generates graph display data according to the input or the display mode of the input graph (step S58). In the example shown in FIG. 3, the graph display data is a line graph in which the vertical axis is the saturation value (g / m ³ ) and the horizontal axis is the date (actual condition 10 days, forecast 10 days).

Next, the display control unit 38 generates display data for warning information (step S59), transmits the display data generated in steps S54, S58 and S59 to the terminal 2 (step S60), and ends the process. An example of the display data generated in S59 is data for displaying a list of warning information for each field position of the user, and this data is transmitted to the terminal 2 (step S60) and displayed on the user's screen.

FIG. 10 is a diagram showing an input example. FIG. 10A shows an input example of the basic form. The risk standard according to the first risk evaluation rule file 5a is based on the calculation result of the model formula according to the first agricultural model file 4a. The warning standard related to the first warning information generation rule file 6a is based on the judgment result of the risk level related to the first risk evaluation rule file 5a. The server 3 calculates the calculation result of the first agricultural model file 4a, performs the risk evaluation according to the first risk evaluation rule file 5a, and visualizes the evaluation result by mesh display or graph display. Further, if necessary, the server 3 generates warning information according to the first warning information generation rule file 6a.

FIG. 10B illustrates an input example of a complex agricultural model. The model formula of the second agricultural model file 4b includes the calculation result of the model formula related to the third agricultural model file 4c as a variable. The risk standard according to the second risk evaluation rule file 5b is based on the calculation result of the model formula according to the second agricultural model file 4b. The warning standard related to the second warning information generation rule file 6b is based on the judgment result of the risk level related to the second risk evaluation rule file 5b. The server 3 calculates the calculation result of the third agricultural model file 4c, calculates the calculation result of the second agricultural model file 4b from the calculation result of the third agricultural model file 4c, and evaluates the risk according to the second risk evaluation rule file 5b. Perform the results and visualize the evaluation results by mesh display or graph display. Further, if necessary, the server 3 generates warning information according to the second warning information generation rule file 6b. As described above, in the agricultural model extension system 1, it is possible to use a complex agricultural model including a plurality of agricultural models.

FIG. 10 (c) shows an input example of the combined risk evaluation. The risk standard according to the third risk evaluation rule file 5c is based on the calculation results of the model formulas related to the fourth agricultural model file 4d and the fifth agricultural model file 4e, that is, the calculation results of a plurality of model formulas. The warning standard related to the third warning information generation rule file 6c is based on the judgment result of the risk level related to the third risk evaluation rule file 5c. The server 3 calculates the calculation results of the 4th agricultural model file 4d and the 5th agricultural model file 4e, performs the risk evaluation result according to the 3rd risk evaluation rule file 5c, and visualizes the evaluation result by mesh display or graph display. Further, if necessary, the server 3 generates warning information according to the third warning information generation rule file 6c. In this way, the agricultural model dissemination system 1 can perform a complex risk evaluation using a plurality of agricultural models.

FIG. 10D shows an input example of complex warning information generation. The risk standard according to the 4th risk evaluation rule file 5d is based on the calculation result of the model formula according to the 6th agricultural model file 4f. The risk standard for the 5th risk evaluation rule file 5e is based on the calculation result of the model formula for the 7th agricultural model file 4g. The warning criteria related to the fourth warning information generation rule file 6d are based on the judgment results of the risk levels related to the fourth risk evaluation rule file 5d and the fifth risk evaluation rule file 5e, that is, the judgment results of a plurality of risk levels. The server 3 calculates the calculation results of the 6th agricultural model file 4f and the 7th agricultural model file 4g, performs the risk evaluation results according to the 4th risk evaluation rule file 5d and the 5th risk evaluation rule file 5e, and meshes the evaluation results. Visualize by display or graph display. Further, if necessary, the server 3 generates warning information according to the fourth warning information generation rule file 6d. In this way, the agricultural model dissemination system 1 can generate complex warning information using a plurality of risk assessments.

In the present invention, the reuse of the agricultural model file 4, the risk evaluation rule file 5, and the warning information generation rule file 6 is considered. However, in areas such as prefectures, there are differences in agricultural models depending on varieties, cultivation methods, etc., differences in risk assessment (risk level and risk criteria) using agricultural models in consideration of local climate conditions such as topography, and risks. There are differences in the warning information (warning standards, countermeasures) to be notified to the user depending on the urgency and importance of the response. Differences in risk assessment and alert information can occur even when the same agricultural model is used. Therefore, when reusing, these files can be customized to create a region-specific file. Further, by advancing the preparation of files in this way, it becomes possible to utilize complex files (see FIGS. 10 (b), (c), and (d)).

As described above, the agricultural model dissemination system 1 according to the embodiment of the present invention includes the above-mentioned agricultural model input reception unit 31, risk evaluation rule input reception unit 32, agricultural weather data DB 71, model formula calculation unit 34, and risk level calculation unit 35. And since the display control unit 38 is provided, various agricultural models can be disseminated without creating a program, and users such as agricultural researchers in various regions can easily utilize the agricultural models. is there. That is, using the agricultural model input by the agricultural researcher in one prefecture, the agricultural researcher in another prefecture inputs the risk evaluation rule using his / her own terminal 2, and the server 3 is based on the actual weather data. Can perform predictive calculation and risk assessment. In particular, since the model formula of the agricultural model can be input, customization for each region and variety can be easily performed. Therefore, the cost for disseminating the agricultural model can be reduced as compared with the conventional method, and the agricultural model can be utilized in a short period of time.

In addition, since the agricultural model dissemination system 1 includes the above-mentioned warning information generation rule input reception unit 33, warning information generation unit 36, and warning information notification unit 37, a local agricultural innovation support specialist can quickly perform when caution is required. , Extension instructors, farmers, etc. can be notified of warning information.

Although preferred embodiments of the agricultural model dissemination system and the like according to the present invention have been described above with reference to the accompanying drawings, the present invention is not limited to such examples. It is clear that a person skilled in the art can come up with various modified examples or modified examples within the scope of the technical idea disclosed in the present application, and these also naturally belong to the technical scope of the present invention. Understood.

1 ………… Agricultural model dissemination system 2 ………… Terminal 3 ………… Server 4 ………… Agricultural model file 5 ………… Risk evaluation rule file 6 ………… Warning information generation rule file 8 ………… Network 31 …… … Agricultural model input reception unit 32 ………… Risk evaluation rule input reception unit 33 ………… Warning information generation rule input reception department 34 ………… Model formula calculation department 35 ………… Risk level calculation department 36 ………… Warning information generation Department 37 ……… Warning information notification unit 38 ……… Display control unit 71 ……… Agricultural weather data DB
72 ……… Model formula calculation result DB
73 ……… Risk level judgment result DB
74 ……… Alert level judgment result DB
407 ………… Meteorological element 408 ………… Calculation results of other model formulas 409 ………… Model formula 508 ………… Risk level 509 ………… Risk standard 608 ………… Warning level 609 ………… Warning standard 610 …… … Countermeasure information

Claims (7)

Receiving an input agricultural models, including model formula meteorological parameters is included as a variable, and agricultural model input receiving unit that be stored in agriculture model file,
Accepting an input of the risk evaluation rules including risk level and risk criteria corresponding to the calculation result of the model formula, and risk assessment rule input accepting section you stored in the risk assessment rule file,
A storage unit that stores agricultural meteorological data including data of the meteorological elements for each regional mesh,
A model formula calculation unit that substitutes the data of the meteorological element into the model formula and calculates the calculation result of the model formula,
For each of the regional meshes, a risk level calculation unit that calculates the determination result of the risk level according to the risk standard, and a risk level calculation unit.
A display control unit that controls the display of the calculation result of the model formula and the determination result of the risk level for each region mesh.
Equipped with a,
The model formula of the agricultural model file can be input so as to include the calculation result of the model formula related to the other agricultural model file as a variable.
An agricultural model dissemination system characterized in that the risk criteria according to the risk evaluation rule file can be input so as to be based on the calculation results of the model formulas related to the plurality of agricultural model files . Alert criteria corresponding to the level of risk determination result, and the reception input of alarm information generation rules comprising the measures information when it exceeds the alert criteria, you stored alarm information generation rule file warning information generation rule input accepting Department and
For each user's field position represented by the area mesh, it is determined whether or not the risk level determination result exceeds the caution standard, and if it exceeds the caution standard, the risk level determination result is determined. And the warning information generation unit that generates warning information including the countermeasure information,
A warning information notification unit that notifies pre-registered users of the warning information,
With more
The display control unit controls the display of the warning information for each field position .
The warning standard according to the warning information generation rule file can be input so as to be based on the determination results of the risk level related to the plurality of risk evaluation rule files. Agricultural model dissemination system. The agricultural model input receiving unit inputs dummy data of the meteorological element stored in advance into the model formula and calculates the calculation result of the model formula to confirm whether or not there is an error. The agricultural model dissemination system according to claim 1 or 2, wherein the agricultural model is disseminated. When the variable of the model formula includes the calculation result of another model formula, the agricultural model input receiving unit calculates the calculation result of the other model formula first, and uses the value as the model formula. The agricultural model dissemination system according to claim 3 , wherein it is confirmed whether or not there is an error by inputting and calculating the calculation result of the model formula . The agriculture according to claim 4 , wherein the agricultural model input receiving unit causes an error when the model formula and the other model formula are circular references including each other's calculation results as variables. Model dissemination system. The computer
Receiving an input agricultural models, including model formula meteorological parameters is included as a variable, the steps you stored in agriculture model file,
Accepting an input of the risk evaluation rules including risk level and risk criteria corresponding to the calculation result of the model equation, the steps you stored in the risk assessment rule file,
A step to store agricultural meteorological data including the data of the meteorological elements for each regional mesh, and
A step of substituting the data of the meteorological element into the model formula and calculating the calculation result of the model formula, and
For each of the regional meshes, a step of calculating the judgment result of the risk level according to the risk standard, and
A step of controlling the display of the calculation result of the model formula and the determination result of the risk level for each region mesh, and
The execution,
The model formula of the agricultural model file can be input so as to include the calculation result of the model formula related to the other agricultural model file as a variable.
A method for disseminating an agricultural model, characterized in that the risk criteria according to the risk evaluation rule file can be input so as to be based on the calculation results of the model formulas related to the plurality of agricultural model files . On the computer,
Receiving an input agricultural models, including model formula meteorological parameters is included as a variable, the steps you stored in agriculture model file,
Accepting an input of the risk evaluation rules including risk level and risk criteria corresponding to the calculation result of the model equation, the steps you stored in the risk assessment rule file,
A step to store agricultural meteorological data including the data of the meteorological elements for each regional mesh, and
A step of substituting the data of the meteorological element into the model formula and calculating the calculation result of the model formula, and
For each of the regional meshes, a step of calculating the judgment result of the risk level according to the risk standard, and
A step of controlling the display of the calculation result of the model formula and the determination result of the risk level for each region mesh, and
To execute ,
The model formula of the agricultural model file can be input so as to include the calculation result of the model formula related to the other agricultural model file as a variable.
The risk criteria related to the risk evaluation rule file can be input so as to be based on the calculation results of the model formulas related to the plurality of agricultural model files.
Agricultural model dissemination program to execute .

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