JPH11299351A - Supporting apparatus for determining operation, determination and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To support the determination of a period or contents of proper farm working for each field in persons engaged in the farm working. SOLUTION: A meteorological model 43 for a field is capable of predicting meteorological phenomena for each field and a crop growth model 41 is capable of predicting the growth of crops for each field. A soil map 47 is capable of detecting conditions of soil for each field and an operation history control part 44 is capable of storing the history of farm working for each field. A farm working supporting part 48 is capable of calculating a proposal for the farm working from information about the crop growth from the crop growth model 41, information indicating the conditions of soil from the soil map 47 and the farm working stored in the operation history control part 44.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus and method for determining work, and to a recording medium, and more particularly to calculating a work plan from weather in each field, crop condition in each field, and soil condition in each field. The present invention relates to a work determination support device and method, and a recording medium.

[0002]

2. Description of the Related Art In the cultivation of agricultural crops, it is common for farm workers to determine the content and timing of farm work using a cultivation calendar. The cultivation calendar is a generalized representation of the work content for the season or the growth stage of the crop, based on the past growth of the crop and the climate of the cultivation area. The adjustment of the characteristics of the individual fields and the characteristics of the varieties is performed by the agricultural worker adjusting the work time, the amount of the pesticide and the fertilizer, etc. based on the experience.

[0003] For example, fertilization is based on organic matter contained in soil,
The purpose is to replenish components necessary for growing the crop, such as nitrogen, phosphoric acid, and potassium. Naturally, since the soil components differ depending on the field, the appropriate amount of fertilization differs from field to field. Also,
Even with the same crop, different varieties require different soil components. Further, even for crops of the same variety, the growth amount of the crop varies depending on the integrated temperature and the amount of solar radiation during the cultivation period, and the soil components required at this time differ. Even in the same area, the basic properties of the surrounding environment of the field and soil,
The accumulated temperature and the amount of solar radiation in the field change due to water veins and the like.
Therefore, the farm worker grasps these through experience and adjusts the time of farm work, the amount of fertilizer, the amount of pesticide, etc. based on the cultivation calendar.

[0004] In addition, pest control work for diseases and pests
It is usually executed at a predetermined time for the purpose of preventing occurrence. In the event of a serious disease or pest outbreak in a wide area, local agricultural work guidance organizations such as agricultural cooperatives, agricultural improvement extension offices, and agricultural mutual aid cooperatives will take the lead, and the agricultural workers or these organizations will respond. At this time, an optimal treatment is proposed for the corresponding whole land area, and an optimal treatment is not always proposed for each individual field.

[0005]

As described above, the conventional farm work depends on the experience of farm workers, and there is a problem that the execution time and contents of the farm work for each field are not always appropriate. Was.

The present invention has been made in view of such a situation, and has as its object to support the determination of the time and contents of the appropriate agricultural work for each field regardless of the amount of experience of the farm worker. .

[0007]

According to a first aspect of the present invention, there is provided a work determination support apparatus comprising: a field weather prediction unit for predicting weather for each field; a crop growth prediction unit for predicting a growth state of a crop for each field; Soil state detecting means for detecting the state of the soil for each field; work history storing means for storing the history of the work performed in each field for each field; forecasting of weather, prediction of crop growth state, And a work determination means for determining a plan of work to be performed in a predetermined field from the state and the work history.

According to a fourth aspect of the present invention, there is provided a work decision support method, wherein: a field weather prediction step for predicting weather for each field; a crop growth prediction step for predicting a growth state of a crop for each field;
A soil state detecting step of detecting a state of soil in each field; a work history storing step of storing a history of work performed in each field for each field; a weather prediction, a crop growth state prediction, a soil A work determination step of determining a plan of work to be performed in a predetermined field from the state and the work history.

According to a fifth aspect of the present invention, there is provided a recording medium, comprising: a field weather prediction step for predicting weather for each field; a crop growth prediction step for predicting growth status of a crop for each field; and a soil state detection for each field. A soil state detecting step, a work history storing step of storing, for each field, a history of the work performed in each field, a weather prediction, a crop growth state prediction, a soil state, and a predetermined A computer-readable program for executing a process including an operation determining step of determining a plan of an operation to be performed in a field is recorded.

[0010] In the work decision support apparatus according to the first aspect, the work decision support method according to the fourth aspect, and the recording medium according to the fifth aspect, the weather for each field is predicted, and the crop quality of each field is estimated. Predict growth, detect soil condition in each field,
The history of work for each field is stored, and a work plan is calculated from the information.

[0011]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present invention will be described below. In order to clarify the correspondence between each means of the invention described in the claims and the following embodiments, each means is described. When the features of the present invention are described by adding the corresponding embodiment (however, an example) in parentheses after the parentheses, the result is as follows. However, of course, this description does not mean that each means is limited to those described.

That is, the work decision support device according to the first aspect is a field weather prediction means (for example, the field weather model 43 in FIG. 3) for predicting the weather for each field, and predicts the growth state of the crop for each field. Crop growth predicting means (for example, the crop growth model 41 in FIG. 3) and soil condition detecting means (for example, the soil map 47 in FIG. 3) for detecting the state of the soil in each field.
And work history storage means (for example, the work history management unit 4 shown in FIG. 3) for storing a history of work performed in each field.
4) and work determination means (for example, the agricultural work support unit 48 in FIG. 3) for determining a plan of work to be performed in a predetermined field from weather forecast, crop growth state forecast, soil state, and work history. It is characterized by having.

FIG. 1 is a diagram showing the components of agriculture and the configuration of an embodiment of the agricultural work decision support system of the present invention. In the field 1, the crop 2 is planted by the farm worker 3. The farm worker 3 uses the farm equipment 4 necessary or necessary for the farm work (such as a tractor, a combine, or a rice transplanter with an attached attachment. FIG. 1 shows a tractor as an example). Execute. Although not shown in FIG. 1, agricultural materials such as a vinyl house and a nursery box are used in some agricultural operations. Also, fertilizer,
Consumer goods such as pesticides are also used. The farm worker 3 maximizes the yield and quality of the crop 2 planted in the field 1 with respect to the investment in these agricultural equipment, agricultural materials, and consumables, and the amount of work required for agricultural work. Select the time of the agricultural work and the contents of the agricultural work.

The personal computer 6 constituting the farm work decision support system is connected to a network 7 represented by the Internet. The network 7 includes an external database and the like, and provides appropriate information requested in response to access from the personal computer 6.
The personal computer 6 only needs to be able to perform necessary information processing, such as a workstation, a sequencer,
Alternatively, an information processing device dedicated to agricultural work decision support may be used.

The personal computer 6 accesses the network 7 and obtains information such as weather necessary for supporting the agricultural work and the occurrence of pests in the surrounding fields. Crop 2 in field 1
, A weather sensor 9 for detecting the weather in the field 1, and a soil sensor 10 for detecting the state of the soil in the field 1 are connected to the personal computer 6. The image of the crop 2 in the field 1 captured by the crop sensor 8 is captured by the personal computer 6 and subjected to a predetermined process. The current crop length indicating the current length of the crop 2 and the color of the crop 2 indicate the occurrence of a disease. This is information indicating the situation. The crop sensor 8 is, specifically, a CCD image sensor,
Any sensor can be used as long as it can use a video camera or the like and can obtain a predetermined image resolution or the like.

The weather sensor 9 supplies weather information such as temperature, humidity, water temperature, solar radiation, precipitation, wind speed, and wind direction of the field 1 to the personal computer 6. The weather sensor 9 is composed of a group of a plurality of sensors such as a temperature sensor and a humidity sensor, and may have the same function as the sensor at the observation point of weather observation. Specifically, the temperature sensor may be a resistance thermometer, a thermocouple, and the solar radiation sensor may be a photosensor. The soil sensor 10 supplies the personal computer 6 with information on the state of the soil, such as the soil temperature of the field 1, the water content, the content of organic matter, and the content of nitrogen, phosphoric acid, potassium, and the like. Specifically, the soil sensor 10 includes an infrared spectrophotometer, an emission analyzer,
A nuclear magnetic resonance absorption device or the like can be used.

FIG. 2 is a hardware configuration diagram of the personal computer 6. CPU (central processing u
The nit 21 actually executes various application programs and a basic OS (operating system). R
The OM (read-only memory) 22 is generally a CPU
21 stores basically fixed data among the programs used and the parameters for calculation. RAM (random-a
The ccess memory 23 stores a program used in the execution of the CPU 21 and parameters that change as appropriate in the execution. These are interconnected by a bus 32.

The keyboard 25 is operated by the farm worker 3 when inputting a text or inputting various commands to the CPU 21. Mouse 26 is a CRT (cath
(ode ray tube) It is operated by the farm worker 3 when instructing or selecting a point on the screen of the display 27. The CRT display 27 displays various information as text or images. HDD (hard disk drive) 28
And an FDD (floppy disk drive) 29 drive a hard disk or a floppy disk, respectively, and record or reproduce a program executed by the CPU 21 or information on the hard disk or the floppy disk. The communication board 30 is an ISDN (inte
A device for connecting to a public line including a grated service digital network) or a communication line such as a LAN (local area network), specifically, a modem or various LANs
It is composed of a board and the like. The sensor connection board 31 is a device for taking information from the crop sensor 8, the weather sensor 9, and the soil sensor 10 into the personal computer 6. These keyboard 25 to sensor connection board 31
Are connected to the interface 24, and the interface 24 is connected to the CPU 21 via the bus 32.

FIG. 3 shows a functional block diagram of the agricultural work decision support system realized by the CPU 21 executing the program. The crop growth model 41 predicts the growth of a crop on a field-by-field basis. Taking cabbage as an example, the spread of leaves, the start time of the outer leaf development period, the head start time, the head size, and the like are predicted. The crop growth model 41 also stores, for each field, actual crop growth information from the start of prediction to the current time. The pathological disease model 42 calculates the probability of occurrence of diseases and pests on a field basis. In addition, the prediction of the spread of the disease and pests once occurring is performed, and the predicted damage is calculated. Damage here refers to the percentage of crops that cannot be shipped. Further, the pathological disease model 42 records a past pathological disease occurrence record for each field.

The field weather model 43 predicts the weather on a field-by-field basis and stores past weather results on a field-by-field basis. The work history management unit 44 stores a history of work results of farm work for each field. For example, in the case of control, the execution date and the type and amount of the pesticide used for the control, the method of spraying, and the like are stored. The display unit 45 determines the display format of the information to be provided to the farm worker 3, and causes the CRT display 27 to display the information. Basically, the display unit 45 preferentially displays information with high urgency and information with high importance. The display format may be set by the farm worker 3.

The farm work knowledge database 46 stores information necessary for deciding farm work, and provides the information upon request. It also has a function of reading necessary information from the network 7, a recording medium or the like and updating the contents. Information on crop varieties includes cultivar characteristics data including crop name, cultivar name, germination rate, seeding amount, growth function, flowering / fruiting function, pest resistance, fertilization response, environmental response indicating behavior to temperature, solar radiation, etc. Includes cultivation characteristics, such as gender, cultivation workability indicating the points of caution in cultivation work, harvesting methods, and storage and transport characteristics, such as maturity / aging, density, volume, and shape.
In addition, information on fertilizer includes cost, effects, components, usage, and the like. Information on control consists of costs, benefits, components, methods of use, and the like. Further, the farm work knowledge database 46 includes information on farm work methods and irrigation plans.

The field map 47 stores the classification of each field, the crop history indicating the overall characteristics of the field, and information indicating the physical characteristics of the soil. The farm work support unit 48 calculates a work content plan of the farm work, and can calculate a plurality of work content plans in response to one calculation request. The plan management unit 49 receives the input reflecting the decision of the farm worker 3 and holds the basic cultivation plan. Basically, based on the basic cultivation plan, a farm work plan is calculated in consideration of the condition of the crop 2, weather forecast, and the like. The detection unit 50 manages the crop sensor 8, the weather sensor 9, and the soil sensor 10,
The detection data is fetched, processed, and provided to the crop growth model 41, the field weather model 43, and the like. The communication unit 51 communicates with the network 7, and acquires weather information, information on the status of pests and the like in surrounding fields from an external database, and the like.

FIG. 4 is a block diagram showing the structure of the crop growth model 41. From the detection unit 50, the current crop length yn,
The crop growth stage st and the crop density d are input. The solar radiation amount s, the temperature tem, and the rainfall amount r are input from the field weather model 43. From the work history management unit 44, the irrigation amount i and the fertilization amount dr are input. From the field map 47, a soil base characteristic b and a soil fertilizer component n are input. The growth amount Y of the entire crop in a predetermined field is represented by the area of the growth amount y of the individual, and is represented by Expression (1). Y (t) = y (t) dS = h ｛dy / dt; b; n (t ₀ ), dr (t); s (t), tem (t); i (t), r (t); d (t)｝ dtdS (1)

H is a composite system function representing the relationship between each factor and the growth amount. Here, assuming that the control of the temperature tem is large, the growth amount y may be approximated by a linear relationship such as Expression (2). y (t) = h1 (t−τ) tem (τ) dr (2)

Alternatively, in the case of paddy rice, the growth amount may be calculated using an ORYZA model or a Horie model. For crops for which the controlling factor of the growth amount y is unknown, the equation (1) is calculated using fuzzy or genetic algorithm or the like.
What is necessary is just to identify the parameters of the complex system function.

FIG. 5 is a block diagram showing the structure of the field weather model 43. The field weather model 43 has past temperature, humidity, water temperature, ground temperature, solar radiation, sunshine duration, precipitation intensity, wind speed / wind direction information for each field, and the detection unit 50 detects the current temperature, humidity, , Water temperature, ground temperature, solar radiation, sunshine duration, precipitation intensity, wind speed and direction. Further, the field weather model 43 captures weather information via the communication unit 51, and further obtains the current crop length yn and the crop density d from the detection unit 50. The field weather model 43 is based on weather information obtained via the communication unit 51, taking into account weather changes from the past to the present and factors such as changes in temperature, humidity, and ground temperature due to the growth stage of the crop, Predict the weather in the field unit (micro weather near crops).

FIG. 6 is a diagram showing the structure of the field map 47. The field map 47 classifies the information about the field 1 into four layers in order to describe the characteristics of the field 1,
Each layer is stored by being divided into a time scale and a space scale. The first hierarchical level has information on the farmland classification expressing the overall characteristics of the field 1. Specifically, this hierarchy includes classification information indicating basic characteristics of paddy fields, uplands (including orchards) and grasslands as fields, and past crop histories governed by weather and a wider production environment. Is stored. Information on the classification of paddy fields, fields, and grasslands is recorded for each field in units of 10 years. The crop history information is recorded for each field in units of one year or four seasons.

The second to fourth layers of the field map 47 indicate soil characteristics of the field. The second hierarchy indicates a subsurface soil classification. FIG. 7 shows triangular coordinates indicating the composition classification of soil.
The position of the subsoil on the triangular coordinates expresses the basic properties of the soil. The properties of the subsoil dominate the basic properties of the soil. The nature of the subsoil cannot be changed artificially, and the information observed once does not need to be changed for more than 50 years.
Information may be stored in units of a. The third layer shows the basic characteristics of the soil on the field surface where 70% of the crop roots are distributed. Specifically, it has information such as permeability distribution, groundwater level distribution, soil depth distribution, and weed species distribution. The basic characteristics of the soil can be changed by replacing the soil, etc. However, in reality, it is difficult to change economically, and there is almost no change in the period of about 5 to 10 years. Should be held.

The fourth level shows short-term fluctuation characteristics of the soil. Specifically, it has information such as the distribution of weed quantity, ground surface undulation, organic matter content, trace element distribution, nitrogen, phosphoric acid, and potassium distribution. Since these fluctuate greatly in several years and can be artificially changed in a short period of time, detailed distribution information on a yearly basis and in m units is required.

The long-term management of soil characteristics and long-term management strategy include the first, second, third, and fourth layers.
The order of hierarchy is important. Conversely, for short-term forecasts such as the yield of crop 2 for a single year, the fourth, third,
It has the degree of influence in the order of the first layer. Therefore, for the decision support of the agricultural work, the access frequency increases in the order of the fourth hierarchy, the third hierarchy, the second hierarchy, and the first hierarchy. Thus, by adopting a data structure reflecting the hierarchical structure shown in FIG. 6, it is possible to change and read out soil information quickly and reliably. More specifically, a soil map having a hierarchical structure is realized on a relational database or an object-oriented database.

FIG. 8 is a block diagram showing the structure of the pathological disease model 42. First, the pathological disease model 42 calculates an occurrence probability of a pathological disease. The pathological disease model 42 retrieves past pathological disease occurrence distribution data contained therein, obtains field weather forecast information from the field weather model 43, and obtains information on the crop growth stage via the detection unit 50. Based on these, the probability P (x; t) of the occurrence of a pathological disease is calculated by the equation (3).
Is calculated. P (x; t) = F (V (x), ST (x; t), EN (x; t)) (3)

Here, P (x; t) is a probability including time and space. V (x) indicates the occurrence distribution of pathological diseases in the past. ST (x; t) indicates a crop growth stage. EN
(X; t) indicates field weather forecast. The function F has an integral form of a variable because it relates to the past history of the pathological disease occurrence distribution V, the crop growth stage ST, and the field weather forecast EN.

Next, the pathological disease model 42 is
The information on the current amount of pathological disease occurrence in the field is obtained through the communication unit 51, and the information on the amount of peripheral pathological disease occurrence is obtained via the communication unit 51. The probability P (x; t) of the pathological disease and the actual pathological disease From the generated amount D, the diffusion of the pathological disease is predicted from the equation (4). dD (x; t) = P (x; t ₀ ) ΔG (k, D, ST, EN) (4)

Here, k indicates a diffusion coefficient. Equation (4) has the form of a diffusion equation, where the subsequent increase in the pathological disease that occurred at a certain time t ₀ is the diffusion coefficient k, the pathological disease occurrence D, the field weather forecast EN, and the crop growth stage ST. Described by the time evolution of

The damage prediction is calculated by multiplying the occurrence amount D of the pathological disease by the damage coefficient α. The damage coefficient α indicates the degree of the influence on the yield of the pathological disease occurrence D. The damage coefficient α is calculated as a function of the elapsed time from the time t ₀ at which the pathological disease occurred and the field weather forecast EN,
The calculation may be performed based on information obtained by the detection unit.

FIG. 9 is a flowchart showing the operation of the agricultural work determination support system from the selection of a crop to the end of all the agricultural work in crop cultivation. In step S11, the farm worker 3 adds a crop, a variety,
Display market information. In step S12,
The farm worker 3 selects and sets a crop, a variety, and a field 1 to be planted, and causes the farm work determination support system to predict the yield and investment. Here, investment refers to the cost of purchasing seeds, pesticides, fertilizers, and the like, the cost of labor, the cost of purchasing agricultural equipment and agricultural materials, and the like. In step S13, the farm worker 3 determines the crop 1 and the variety and the field 1 to be planted. In step S14, the farm work determination support system creates a basic cultivation schedule from information on the crops, varieties, and fields to be planted determined in step S13.

In step S15, step S14
Based on the basic cultivation schedule created in the above, support for agricultural work determination is started. Here, the farm work determination support system executes necessary initial settings such as a crop growth model. In step S16, the farm work determination support system displays a farm work plan when farm work is required. The agricultural work plan displayed here is not necessarily singular. Step S1
In 7, the farm worker 3 selects and determines the farm work plan shown in step S16, and performs the farm work on the field 1 and the crop 2. In step S18, the farm worker 3 inputs the results of the farm work executed in step S17 to the farm work determination support system. Step S1
In 9, the farm work support system determines whether or not all the farm work has been completed. If it is determined that the entire farm work has not been completed, the process returns to step S16 and the processing is continued. In step S19, when it is determined that all the farm work has been completed, the farm work determination support system ends the operation.

As described above, the agricultural work decision support system includes:
From the start to the end of crop cultivation, the farm worker 3 provides information necessary for decision making. In the display of the basic cultivation schedule and the plan of the farming work, the related information is integrated and corrected and displayed on a field-by-field basis, so that the farm worker 3 can judge an appropriate farming work without any experience of the farming work. . In addition, even an experienced farm worker 3 can prevent oversight of items to be determined and obtain a stable crop yield.

FIG. 10 is a flowchart showing the operation of the functional blocks and the transmission and reception of messages between the functional blocks in step S11 for displaying the information of the crop, variety and market in FIG. First, in step S101, the farm worker 3 requests the plan management unit 49 to display information on crops, varieties, and markets. In step S102, the plan management unit 49 executes a process corresponding to the crop and variety information request. That is, the plan management unit 49 transmits a message including the crop name and the variety name input by the farm worker 3 to the farm work knowledge database 46. Step S16
In step 1, the farm work knowledge beta base 46 searches for crop and variety information based on the crop name and variety name in the received message. Here, the information on crops and varieties includes general information such as disease resistance, size, cropping type, cultivation precautions, etc. Information. The information on the crops and varieties retrieved from the agricultural work knowledge database 46 is transmitted to the plan management unit 49 and the display unit 45. In step S111, the display unit 45 that has received the information on the crop and the variety displays it on the CRT display 27.

Next, in step S103, the plan management section 49 requests information on the market. That is, the plan management unit 49 transmits a message including the crop name, the variety name, and the market name input by the farm worker 3 to the communication unit 51. In step S141, the communication unit 51 performs market information search based on the received crop name, variety name, and market name. The market information here is the market price of the crop,
Price forecasts and demand forecasts. The market information retrieved by the communication unit 51 is transmitted to the plan management unit 49 and the display unit 45. In step S112, the display unit 45 that has received the market information displays the market information on the CRT display 27. Here, the display unit 45 may simultaneously display information on crops and varieties, and information on markets.

As described above, the agricultural work decision support system includes:
The farmer 3 is presented with general information on the crop, its varieties and the market. Thereby, the farm worker 3 can narrow down the crops and varieties to be planted.

FIG. 11 is a flowchart showing the operation of the functional blocks and the transmission and reception of messages between the functional blocks in step S12 for estimating the yield and investment in FIG. First, in step S201, the farm worker 3
Requests the plan management unit 49 for the yield and investment forecast.
In step S202, the plan management unit 49 executes a field soil information request in response to the request. That is, the plan management unit 49 stores the step S
At 201, a message requesting information on the field designated by the farm worker 3 is transmitted. Step S2
At 91, the field map 47 makes a soil detection request for the designated field. That is, the field map 47 transmits a message requesting the detection unit 50 to detect the current state of the soil in the specified field. In step S251, the detecting unit 50 sets the soil sensor 10 in the designated field.
Then, the condition of the soil is detected. The detecting unit 50 transmits the information on the soil in the designated field to the field map 47.
The field map 47 is the same as the field map 4 in step S292.
After correcting the information of 7 with the soil information of the field from the detection unit 50, the soil information of the designated field is searched, and the soil information is transmitted to the plan management unit 49.

In step S203, the plan management unit 4
9 executes a field weather information request. That is, the plan management unit 49 stores the step S201 in the field weather model 43.
Transmits a message requesting information on weather forecast for the field designated by the farm worker 3. In step S281, the field weather model 43 requests medium-to-long term weather information. That is, the field weather model 43
Transmits a message requesting retrieval of weather information to the communication unit 51. In step S241, the communication unit 51
Performs a search for weather information over the medium to long term. Communication unit 51
Transmits the retrieved weather information to the field weather model 43. The field weather model 43 predicts medium- to long-term weather information based on past weather information included in the field weather model 43 and weather information from the communication unit 51, and transmits it to the plan management unit 4
9

In step S204, the plan management unit 4
9 executes a pathological disease prediction request. That is, the plan management unit 49 stores the pathological disease model 42 in step S201.
Transmits a message requesting pathological disease prediction for the field designated by the farm worker 3. This message includes medium- to long-term weather information of the designated field. In step S2101, the pathological disease model 42 calculates a pathological disease prediction based on past pathological disease information of the designated field and medium-to-long term weather information, and transmits the pathological disease prediction to the plan management unit 49.

In step S205, the plan management unit 4
9 executes a crop growth prediction request. That is, the plan management unit 49 stores the crop growth model 41 in step S201.
Transmits a message requesting a crop growth prediction for the field designated by the farm worker 3. This message includes the medium- to long-term weather information of the designated field and FIG.
Of the crop and the varieties obtained in step S11. In step S271, the crop growth model 4
1 calculates the crop growth prediction including the harvest amount based on the medium- to long-term weather information of the designated field and the information of the crop and the variety, and transmits it to the plan management unit 49.

In step S206, the plan management unit 4
9 calculates the yield and investment prediction based on the pathological disease prediction, the crop growth prediction, the control and fertilization conditions obtained in step S11 in FIG. 9, and displays the yield and investment prediction on the display unit 45. Send. In step S211, the display unit 4
5 displays the yield and investment forecast on the CRT display 27.

As described above, the agricultural work decision support system comprises:
The farmer 3 is presented with the prediction of the yield of the crop 2 and the investment required for each crop 1 for each field 1. Therefore, the farmer 3
The most effective crop 2 and its varieties for the field 1 can be selected from the yield and investment forecast of the crop 2 together with the market information obtained earlier.

FIG. 12 is a flowchart showing the operation of the functional blocks and the transmission and reception of messages between the functional blocks in step S14 for creating the basic schedule in FIG. 9 and in step S15 for starting agricultural work determination support. First, in step S301, the farm worker 3
Then, a basic schedule creation request is made. In step S302, the plan management unit 49 executes a cultivation schedule information request.
That is, the plan management unit 49 transmits to the farm work knowledge database 46 a message requesting cultivation schedule information on the crops and varieties designated by the farm worker 3 in step S301. In step S361, the agricultural work knowledge database 46 searches for information on the cultivation schedule of the specified crop and variety, and transmits the searched cultivation schedule to the plan management unit 49.

In step S303, the plan management unit 4
9 makes a crop growth prediction request. That is, the plan management unit 49 transmits to the crop growth model 41 a message including the information on the crop and the variety specified by the farm worker 3 in step S301 and the field weather information obtained in step S13. In step S371, the crop growth model 41 calculates a crop growth prediction based on the input information and transmits the crop growth prediction to the plan management unit 49. At this time, the crop growth model 41 is, if necessary, a field weather model 43,
The crop growth may be predicted by obtaining information from the field map 47.

In step S304, the plan management unit 4
9 calculates a basic cultivation schedule and transmits it to the display unit 45. In step S311, the display unit 45 displays the basic cultivation schedule on the CRT display 27. FIG.
FIG. 3 is a diagram showing a display example of a cabbage cultivation schedule. The farm worker 3 checks the basic schedule displayed on the CRT display 27, and proceeds to step S305 when it is determined that cultivation is to be performed based on the displayed basic schedule. If a different schedule is required, the conditions such as the variety and the field are changed, and the process is repeated from step S301.

In step S 305, the farm worker 3 inputs the basic cultivation schedule selection setting to the plan management unit 49 using the keyboard 25 or the mouse 26. Step S3
At 06, the plan management unit 49 executes a crop growth prediction start request, and transmits a crop growth prediction start request message including information on crops, varieties, fields, and the like to the crop growth model 41. Crop growth model 41 that received the message
Starts crop growth prediction. In step S307, the plan management unit 49 executes a field weather forecast start request and transmits a field weather forecast start request message including information on the designated field 1 and the like to the field weather model 43.
The field weather model 43 that has received the message starts field weather prediction of the specified field 1 in step S381.

In step S308, the plan management unit 4
9 executes a field state monitoring start request, and transmits a field state monitoring start request message including information on the designated field 1 and the like to the field map 47. The field map 47 that has received the message starts field state monitoring of the specified field 1 in step S391. In step S309, the plan management unit 49 executes a pathological disease prediction start request, and transmits a pathological disease prediction start request message including information on the designated field or the like to the pathological disease model 42.
The pathological disease model 42 that has received the message starts predicting the pathological disease of the designated field 1 in step S3101.

Thereafter, the plan management section 49 calculates an execution plan of the agricultural work based on the basic cultivation schedule. Further, the crop growth model 41, the field weather model 43, the field map 47, and the pathological disease model 42 continuously execute prediction or monitoring of the designated field. The basic cultivation schedule of the plan management unit 49 is corrected by taking in information of the crop growth model 41, the field weather model 43, and the field map 47 at predetermined intervals.

FIG. 14 is a flowchart showing the operation of the functional blocks and the transmission and reception of messages between the functional blocks when the crop growth model 41 starts predicting the growth of the crop in the designated field in step S372 of FIG. is there. The processing in step S471 is performed in step S471 in FIG.
This is the same processing as the processing of 372. In step S472, the crop growth model 41 executes a crop and variety information request, and transmits an information search message including the crop and variety information to the agricultural work knowledge database 46. In step S461, the farm work knowledge database 46 searches the storage information regarding the crop and the variety specified in the message,
The search result is transmitted to the crop growth model 41. In step S473, the crop growth model 41 sets a constant for the crop growth model.

When the crop growth prediction request event occurs, the crop growth model 41 executes processing corresponding to the event. Next, the operation will be described. The crop growth prediction request may be generated by a request from another function such as the field weather model 43 and the crop growth model 41 itself at predetermined intervals. First, in step S571, the crop growth model 41 requests work history information. At this time, a work history information request message including information for specifying the designated field 1 is transmitted from the crop growth model 41 to the work history management unit 44. In step S531, the work history management unit 44 searches for work history information of the designated field 1, and transmits the work history information to the crop growth model 41.

In step S572, the crop growth model 41 requests field information. At this time, a field information request message including information for specifying the designated field 1 is transmitted to the field map 47. In step S591, the field map 47 searches for information on the soil in the specified field 1, and transmits the information to the crop growth model 41.
In step S573, the crop growth model 41 requests field weather information. At this time, a field weather information request message including information for specifying the designated field is transmitted to the field weather model 43. In step S581, the field weather model 43 retrieves the weather information of the designated field 1 and transmits it to the crop growth model 41.

In step S574, the crop growth model 41 requests detection of the growth of the crop 2. At this time, a crop growth detection request message including information for specifying the designated field 1 is transmitted to the detection unit 50. In step S551, the detection unit 50 detects the growth state of the crop 2 in the designated field 1, and transmits the detection result to the crop growth model 41. In step S575, the crop growth model 41 calculates a crop growth prediction based on the input information.

As described above, the crop growth model 41 includes:
The crop condition reflecting the latest forecast of the weather of the designated field and the latest condition of the soil is maintained.

FIG. 15 is a flowchart showing the operation of the functional blocks and the transmission and reception of messages between the functional blocks when the field weather model 43 starts predicting the weather in the designated field in step S381 of FIG. . Step S681 is a step corresponding to step S381 in FIG. In step S682,
The field weather model 43 executes a weather information request, and transmits an information search message including information specifying the designated field 1 to the communication unit 51. The communication unit 51 determines in step S64
In step 1, communication with an external database is performed to search for weather information at the position of the field 1 in the message, and the search result is transmitted to the field weather model 43. In step S683, the field weather model 43 executes a crop and variety information request, and transmits an information search message including the designated crop name and variety name to the agricultural work knowledge database 46. In step S661, the farm work knowledge database 46 searches for storage information related to the crop name and the variety name specified in the message,
The search result is transmitted to the field weather model 43. Step S
At 684, the field weather model 43 sets the constant of the field weather model.

The operation of the field weather model 43 when a field weather prediction request event occurs will be described below.
The field weather prediction request may be generated by a request from another function such as the crop growth model 41 and the field weather model 43 itself at predetermined intervals. First, in step S781, the field weather model 43 searches past information of the weather of the designated field 1 owned by the field weather model 43. Step S782
, The field weather model 43 requests a search for weather information. At this time, a request message of weather information including information for specifying the designated field 1 is sent to the field weather model 4
3 to the communication unit 51. In step S741, the communication unit 51 communicates with an external database,
Search for weather information based on the location of field 1 in the message,
The search result is transmitted to the field weather model 43.

In step S783, the field weather model 43 requests detection of the crop length and density. At this time,
A request message for detection of the crop length and density including the information for specifying the designated field 1 is transmitted to the detection unit 50.
In step S751, the detecting unit 50 detects the current crop length and density of the current crop 2 in the designated field 1, and transmits the detection result to the field weather model 43. Step S784
, The field weather model 43 requests detection of the current field weather. At this time, a request message for field weather detection including information specifying the designated field 1 is transmitted to the detection unit 50. In step S752, the detection unit 50 detects the weather in the designated field 1, and transmits the detection result to the field weather model 43. In step S785, the field weather model 43 calculates a field weather forecast based on the input information.

As described above, the field weather model 43 includes:
The latest weather information and the weather conditions reflecting the crop length and density of the crops in the field 1 are held for each field.

FIG. 16 is a flowchart showing the operation of the functional blocks and the transmission and reception of messages between the functional blocks when the monitoring of the soil condition of the designated field 1 is started in the field map 47 in step S391 of FIG. is there. Step S891 is a step corresponding to step S391 in FIG. In step S892,
The field map 47 includes the designated field 1
Search for past information on weeds. In step S893, the field map 47 executes a request for detecting the state of the field 1, and transmits a state detection message including information for specifying the specified field 1 to the detection unit 50. Step S
In step 851, the detection unit 50 detects the state of the soil in the field 1 with the soil sensor 10 based on the information specifying the field 1 in the message, and transmits the detection result to the field map 47.
In step S894, the field map 47 corrects the field information.

The operation of the field map 47 when a field information request event occurs will be described below. The field information request may be generated from requests from other functions such as the crop growth model 41 and the field map 47 itself at predetermined intervals. First, in step S991, the field map 47
Executes a request to detect the state of the field 1, and transmits a state detection message including information for specifying the specified field 1 to the detection unit 50. In step S951, the detection unit 50 detects the state of the soil in the field 1 with the soil sensor 10 based on the information specifying the field 1 in the message, and transmits the detection result to the field map 47. In step S992, the field map 47 requests information of a work history. At this time, a work history request message including information specifying the designated field 1 is transmitted to the work history management unit 44. In step S931, the work history management unit 44
Searches for a work history such as fertilization in the designated field 1 and transmits the detection result to the field map 47. Step S993
In, the field map 47 corrects the field information.

As described above, the field map 47 holds a state in which the latest work history information and the information obtained by detecting the soil state are reflected for each field 1.

FIG. 17 is a flowchart showing the operation of the functional blocks and the transmission and reception of messages between the functional blocks when the pathological disease model 42 starts predicting the pathological disease in the designated field in step S3101 of FIG. is there. Step S10101 corresponds to step S10 in FIG.
This is a step corresponding to 3101. First, step S1
At 0102, the pathological disease model 42 searches the past information on the occurrence of pathological disease in the designated field that it owns. In step S10103, the pathological disease model 42 executes a crop and variety information request, and transmits an information search message including the designated crop name and variety name to the agricultural work knowledge database 46. The farm work knowledge database 46 searches for information on the crop name and the variety name specified in the message in step S1061, and transmits the search result to the pathological disease model 42. Step S10104
In the pathological disease model 42, a constant of the pathological disease model is set.

The operation of the pathological disease model 42 when a pathological disease prediction request event occurs will be described below.
The pathological disease prediction request may be generated by a request from another function such as the agricultural work support unit 48 and the pathological disease model 42 itself at predetermined intervals. In step S11101,
The pathological disease model 42 requires detection of a pathological disease. At this time, a request message for pathological disease detection including information specifying the designated field 1 is transmitted from the pathological disease model 42 to the detection unit 50. In step S1151, the detection unit 50 detects the occurrence state of the pathological disease from the image captured from the crop sensor 8 based on the information specifying the field 1 of the message, and transmits the path disease to the pathological disease model 42.

In step S11102, the pathological disease model 42 requests information on the occurrence of pathological diseases around the field. At this time, a request message of pathological disease occurrence information around the field including information on the position of the designated field 1 is transmitted to the communication unit 51. In step S1141,
The communication unit 51 accesses an external database, searches for occurrence information of a pathological disease around the designated field 1, and transmits the search result to the pathological disease model 42. Step S1
At 1103, the pathological disease model 42 requires detection of a crop growth stage. At this time, a request message for crop growth stage detection including information specifying the designated field 1 is transmitted from the pathological disease model 42 to the detection unit 50. In step S1152, the detection unit 50 detects the crop growth stage from the image captured from the crop sensor 8 based on the information specifying the field 1 in the message, and transmits the search result to the pathological disease model 42.

In step S11104, the pathological disease model 42 requests field weather prediction. At this time, a field weather forecast request message including information for specifying the designated field 1 is transmitted to the field weather model 43.
In step S1181, the field weather model 43
The weather of the designated field 1 is predicted, and the prediction result is transmitted to the pathological disease model 42. In step S11105, the pathological disease model 42 calculates a pathological disease prediction from the input information.

As described above, the pathological disease model 42 holds a state in which the latest field weather forecast and the growth stage of the crop are reflected for each field 1.

FIG. 18 is a flowchart showing the operation of the functional blocks and the transmission and reception of messages between the functional blocks when calculating the plan for raising seedlings, which is a kind of agricultural work, in step S16 of displaying the agricultural work plan in FIG. It is. First, in step S1201, the plan management unit 49 executes a seedling raising request based on the basic cultivation schedule. At this time, a message of a seedling request containing information such as the crop name,
It is sent from the plan management section 49 to the agricultural work support section 48. In step S1221, the farm work support unit 48 executes a request for information on the seedling raising method. At this time, a request message for seedling raising method information including information such as a crop name and a variety name is transmitted from the farm work support unit 48 to the farm work knowledge database 46. In step S1261, the farm work knowledge database 4 receives the request message for the seedling raising method information.
6 searches for the seedling raising method information based on the crop name and the variety name, and transmits the search result to the agricultural work support unit 48.

In step S1222, the farm work support unit 48 requests the variety information of the crop 2. At this time, a request message for variety information including the crop name and the variety name is transmitted from the agricultural work support unit 48 to the agricultural work knowledge database 46. In step S1262, the farm work knowledge database 46 that has received the type information request message
Searches for the variety information based on the crop name and the variety name, and transmits the search result to the agricultural work support unit 48. In step S1223, the agricultural work support unit 48 requests the growth prediction of the crop 2. At this time, a request message for growth prediction of the crop 2 is transmitted from the agricultural work support unit 48 to the crop growth model 41. In step S1271, the crop growth model 41, which has received the request message for the growth prediction of the crop 2,
The crop growth prediction information is calculated and transmitted to the agricultural work support unit 48.

In step S 1224, the farm work support unit 48 calculates a seedling raising method plan based on the input information, and transmits it to the display unit 45. In step S1211, the display unit 45 displays the seedling raising method plan on the CRT display 27. Specific methods of working,
Execution time is included. The farm worker 3 selects and executes a seedling raising method from the seedling raising method proposals displayed on the CRT display 27, and inputs the results of the seedling raising to the work history management unit 44 in step S1231.

As described above, the agricultural work decision support system includes:
Based on the basic cultivation schedule, an appropriate seedling raising method is presented to the farm worker 3.

FIG. 19 is a flowchart showing the operation of the function blocks and the transmission and reception of messages between the function blocks when calculating the plan of the planting work, which is a kind of farm work, in step S16 for displaying the farm work plan in FIG. It is. First, in step S1301, the plan management unit 49 executes a planting request based on the basic cultivation schedule. Note that the basic cultivation schedule may be modified from changes in seedling raising conditions and weather forecasts, etc., always reflect the latest information, and may be different from the time of seedling raising. At this time, a message of a request for planting including information such as a crop name and a variety name is sent from the plan management unit 49.
It is sent to the agricultural work support unit 48. In response to this request, in step S1321, the agricultural work support unit 48 executes an information request of the seedling achievement. At this time, an information request message of the seedling raising result is transmitted from the farm work support unit 48 to the work history management unit 44. In step S1331, the work history management unit 44 that has received the seedling achievement information request message searches for the seedling achievement information, and transmits the search result to the agricultural work support unit 48. Hereinafter, each step of step S1322 to step S1332 is the same as the case of the seedling raising of step S1221 to step S1231 in FIG.

As described above, the agricultural work decision support system includes:
Based on the basic cultivation schedule, an appropriate planting method is presented to the farm worker 3.

FIG. 20 shows the operation of the functional blocks and the transmission and reception of messages between the functional blocks when calculating the plan of the herbicide spraying operation, which is a kind of agricultural work, in step S16 of displaying the agricultural work plan in FIG. FIG. First, in step S1401, the plan management unit 49
Executes a herbicide application request based on the basic cultivation schedule. At this time, a message of a herbicide application request including information on crops, varieties, etc. is sent from the plan management section 49 to the agricultural work support section 48.
Sent to In response to this request, step S1421
In, the agricultural work support unit 48 requests the herbicide spraying result information. At this time, a herbicide spraying result information request message including information specifying the field 1 to which the herbicide spraying was requested is transmitted to the work history management unit 44. In step S1431, the work history management unit 44 searches the herbicide spraying result information of the field 1 requested to spray herbicide, and transmits the search result to the agricultural work support unit 48.

In step S1422, the agricultural work support unit 48 requests weed information. For this reason, a weed information request message including information specifying the field 1 for which the application of the herbicide has been requested is transmitted to the field map 47. Step S
In 1491, the field map 47 searches for weed information in the field 1 for which the application of the herbicide has been requested, and transmits the search result to the agricultural work support unit 48. In step S1423, the agricultural work support unit 48 requests field weather information information. For this reason, a request message of field weather information including information specifying the field 1 for which the application of the herbicide has been requested is transmitted from the agricultural work support unit 48 to the field weather model 43. In step S1481, the field weather model 43 that has received the field weather information request message searches the field weather information of the field 1 for which the application of the herbicide has been requested, and transmits the search result to the agricultural work support unit 48.

In step S1424, the farm work support unit 48 requests information on crops and varieties. For this reason, a crop and variety information request message including a crop name and a variety name is sent from the farm work support unit 48 to the farm work knowledge database 4.
6 is sent. In step S1461, the farm work knowledge database 46 that has received the crop and variety information request message searches for crop and variety information based on the crop name and variety name, and transmits the search result to the farm work support unit 48. In step S1425, the agricultural work support unit 48
Requests herbicide information. For this reason, a request message for herbicide information including the names of crops, varieties, and the like is transmitted from the agricultural work support unit 48 to the agricultural work knowledge database 46. In step S1462, the agricultural work knowledge database 46 that has received the request message for herbicide information searches for herbicide information based on the crop name, variety name, and the like, and transmits the search result to the agricultural work support unit 48.

In step S1426, the agricultural work support unit 48 requests herbicide application method information. For this reason,
The herbicide spraying method information request message including the crop name, the variety name, and the herbicide name is transmitted from the agricultural work support unit 48 to the agricultural work knowledge database 46. In step S1463, the agricultural work knowledge database 46 that has received the herbicide application method information request message searches the herbicide application method information based on the crop name, the variety name, and the herbicide name, and sends the search result to the agricultural work support unit 48. Send.

In step S1427, the agricultural work support unit 48 calculates a herbicide application method from the input information, and transmits it to the display unit 45. In step S1411, the display unit 45 displays the herbicide application method on the CRT display 27. The proposed method of spraying the herbicide includes a specific working method, execution time, and the like. Farm worker 3
Selects and executes a predetermined herbicide application method from the herbicide application method displayed on the CRT display 27, and inputs the herbicide application results to the work history management unit 44 in step S1432.

As described above, the agricultural work decision support system includes:
Based on the basic cultivation schedule, an appropriate herbicide spraying method is presented to the farm worker 3.

FIG. 21 shows the operation of the functional blocks and the transmission and reception of messages between the functional blocks when calculating the plan of the herbicide spraying work, which is a kind of agricultural work, in step S16 of displaying the agricultural work plan of FIG. It is another flowchart which shows. In the case of this flowchart, first, step S1
In 591, the field map 47 executes a herbicide spraying request when it is determined that the weed state obtained by detecting the field state is equal to or greater than a preset threshold. At this time, a message of the herbicide application request is sent from the field map 47 to the agricultural work support unit 48. Steps S1521 to S1532 are performed in step S142 of FIG.
The processing is the same as the processing from step 1 to step S1432,
The description is omitted.

As described above, the agricultural work decision support system includes:
A suitable herbicide spraying method is presented to the farm worker 3 based on the state of the weeds.

As described above, the agricultural work decision support system also displays a method plan for operations other than seedling raising, herbicide application, such as pest control, fertilization, and harvesting.

[0086] In this specification, the system is
It is assumed that the device as a whole is constituted by a plurality of devices.

Note that as a recording medium for providing a user with a computer program for performing the above-described processing,
In addition to recording media such as magnetic disks, CD-ROMs, and solid-state memories, communication media such as networks and satellites can be used.

[0088]

As described above, according to the work decision support apparatus according to the first aspect, the work decision support method according to the fourth aspect, and the recording medium according to the fifth aspect, an appropriate work plan is created. Since it is presented to the farm worker, it is possible to obtain the crop easily and reliably.

[Brief description of the drawings]

FIG. 1 is a diagram showing an embodiment of a farm work decision support system of the present invention.

FIG. 2 is a hardware configuration diagram of a personal computer.

FIG. 3 is a functional block diagram of a personal computer.

FIG. 4 is a block diagram showing a configuration of a crop growth model.

FIG. 5 is a block diagram illustrating a configuration of a field weather model.

FIG. 6 is a diagram showing a configuration of a field map.

FIG. 7 is a diagram showing triangular coordinates indicating the composition classification of soil.

FIG. 8 is a block diagram illustrating a configuration of a pathological disease model.

FIG. 9 is a flowchart illustrating an operation of the farm work determination support system.

FIG. 10 is a flowchart showing an operation of a step of displaying information on crops, varieties, and markets in FIG. 9;

FIG. 11 is a flowchart showing the operation of a step of estimating a yield and investment in FIG. 9;

12 is a flowchart showing the operation of a step of creating a basic schedule in FIG.

FIG. 13 is a diagram showing an example of a cabbage cultivation schedule.

FIG. 14 is a flowchart showing the operation of the crop growth model.

FIG. 15 is a flowchart illustrating the operation of a field weather model.

FIG. 16 is a flowchart illustrating an operation of a field map.

FIG. 17 is a flowchart illustrating an operation of a pathological disease model.

FIG. 18 is a flowchart illustrating an operation of calculating a plan for seedling raising work.

FIG. 19 is a flowchart illustrating an operation of calculating a plan of the planting work.

FIG. 20 is a flowchart showing an operation when calculating a plan of a herbicide spraying operation.

FIG. 21 is a flowchart illustrating another operation when calculating a proposal for a herbicide spraying operation.

[Explanation of symbols]

 41 Crop growth model 42 Pathological disease model 43 Field weather model 44 Work history management unit 47 Field map 48 Agricultural work support unit

Claims (5)

[Claims] 1. A work decision support device for supporting a work decision, comprising: a field weather forecasting means for forecasting weather for each field; a crop growth forecasting means for forecasting a growth state of a crop for each field; Soil state detecting means for detecting the state of the soil, for each of the fields, work history storage means for storing a history of the work performed in each field, the weather forecast, the crop growth state prediction, the soil And a work determination means for determining a plan of work to be performed in a predetermined field from the work history and the work history. 2. The work decision support device according to claim 1, further comprising a pathological disease predicting means for predicting the occurrence and spread of the pathology and disease of the crop for each field. 3. The soil condition detecting means according to claim 1, wherein:
3. Classification as a hierarchical farmland and management on a temporal and spatial scale.
3. The work decision support device according to claim 1. 4. A work decision support method for supporting a work decision, comprising: a field weather forecasting step for forecasting weather for each field; a crop growth forecasting step for forecasting a growth state of a crop for each field; A soil state detecting step of detecting a state of the soil, for each of the fields, a work history storing step of storing a history of work performed in each field, the prediction of the weather, the prediction of the crop growth state, A work determination step of determining a plan of work to be performed in a predetermined field from the state of the soil and the work history. 5. A work decision support device for supporting a work decision, comprising: a field weather forecasting step for forecasting weather for each field; a crop growth forecasting step for forecasting the growth state of a crop for each field; A soil state detecting step of detecting a state of the soil, a work history storing step of storing a history of work performed in each field for each of the fields, the weather forecast, the crop growth state forecast, the soil And a computer readable program for executing a process including a work determination step of determining a work plan to be performed in a predetermined field from the work history.