Agricultural support program, agricultural support method, and agricultural support device

Abstract

To provide an agriculture assisting program, an agriculture assisting method and an agriculture assisting device, which output appropriately information for assisting in breed selection and cultivation management.SOLUTION: Provided is an agriculture system in which a server and a plurality of user terminals are connected to a network such as the Internet, in which the server comprises a selection acceptance unit 41, an environment data acquisition unit 42, a cultivation information acquisition unit 43, a simulation unit 44, an output unit 45, and an update unit 46. The simulation unit 44 reads a parameter that indicates the feature per breed of farm crops from a parameter database 50, and acquires environment data corresponding to a cultivation point selected by a producer from the environment data acquisition unit 42. The simulation unit 44 creates a growth model per breed on the basis of the acquired environment data and the read parameter, and executes a simulation using the created growth model. The output unit 45 outputs simulation results as information for assisting in breed selection and cultivation management.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an agricultural support program, an agricultural support method, and an agricultural support device. [Background technology]

[0002] Conventionally, in catalogs and the like that contain information on agricultural products, the characteristics and properties of each variety are generally expressed using words, images, average values, etc. Therefore, when selecting a variety to cultivate, farmers refer to the characteristics and properties of each variety that are expressed using words, images, average values, etc.

[0003] In recent years, a technology has become known that, when a user specifies a cultivation area, cultivation period, and item, displays a list of varieties of the specified item that can be cultivated in the specified cultivation area and period (see, for example, Patent Document 1, etc.). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-203002 Summary of the Invention [Problem to be solved by the invention]

[0005] However, because the catalog only lists the general characteristics and properties of each variety, it is not possible to accurately determine whether the variety is suitable for the intended cultivation location and environmental conditions. As a result, when actually cultivating crops, there is a risk that the crops will not grow as expected. Furthermore, even if a list of varieties is displayed as in Patent Document 1, it is difficult to determine which variety should actually be cultivated.

[0006] An object of the present invention is to provide an agricultural support program, an agricultural support method, and an agricultural support device that are capable of outputting appropriate information for supporting variety selection or cultivation management. [Means for solving the problem]

[0007] In one embodiment, the agricultural support program provides a user-selected crop variety. and multiple combinations of cultivation locations Accepting information from At each of the above cultivation locations Obtain information about the growing environment of agricultural crops, Acquire information about the cultivation method input by the user, read parameters indicating the characteristics of each of the varieties from a storage unit, The parameters read from the storage unit and the acquired information about the cultivation environment, The acquired information on the cultivation method; A growth model that predicts the daily growth of each organ of a crop based on of Create and Note The growth model calculates the daily growth of each organ of the crop. Cultivation conditions, which are a combination of information on variety, cultivation location, and cultivation method and predicting the results obtained by the prediction. of crops The purpose is to have the computer execute a process that outputs information indicating the daily growth of each organ in a comparable manner, updates the parameters based on information input by a predetermined user that has a certain level of reliability or higher from information indicating the cultivation results of agricultural crops input by users, and stores the updated parameters in the memory unit. [Effects of the Invention]

[0008] The agricultural support program, agricultural support method, and agricultural support device of the present invention have the effect of being able to output appropriate information that supports variety selection or cultivation management. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating a configuration of an agricultural system according to an embodiment. [Figure 2] 2(a) is a diagram showing the hardware configuration of the user terminal of FIG. 1, and FIG. 2(b) is a diagram showing the hardware configuration of the server of FIG. [Figure 3] FIG. 2 is a functional block diagram of a server. [Figure 4] 10 is a flowchart showing a process of the server. [Figure 5] FIG. 1 is a diagram showing an overview of a growth model. [Figure 6]FIG. 10 is a diagram conceptually illustrating changes in crop size in a simulation. [Figure 7] This shows the relationship between growth stage and size of leaves and stems as relative values. [Figure 8] FIG. 10 is a diagram illustrating an example of weather data used in a simulation. [Figure 9] FIG. 10 is a diagram illustrating an example of parameters used in a simulation. [Figure 10] 10(a) and 10(b) are diagrams conceptually showing the leaf growth process and the fruit growth process in this simulation. [Figure 11] FIG. 10 is a diagram (part 1) showing a screen displaying simulation results. [Figure 12] FIG. 2 is a diagram (part 2) showing a screen displaying the simulation results. [Figure 13] 13(a) and 13(b) are diagrams (part 3) showing a screen displaying the simulation results. [Figure 14] FIG. 4 is a diagram (part 4) showing a screen displaying the simulation results. [Figure 15] 10 is a flowchart illustrating an example of processing by an update unit. DETAILED DESCRIPTION OF THE INVENTION

[0010] An embodiment of an agricultural system will be described in detail below with reference to Figs. 1 to 15. Fig. 1 shows a schematic configuration of an agricultural system 100 according to one embodiment. The agricultural system 100 of this embodiment is a system for providing information to farmers and other such producers (hereinafter referred to as "producers") to assist them in selecting cultivars and managing cultivation when they cultivate fruit vegetables such as tomatoes, strawberries, cucumbers, and peppers. In this embodiment, the case of a producer cultivating strawberries will be described.

[0011] As shown in Fig. 1, the agricultural system 100 includes a server 10 as an agricultural support device and a user terminal 70. The user terminal 70 is a terminal used by producers, such as a personal computer (PC), tablet terminal, or smartphone. The server 10 and the user terminal 70 are connected to a network 80 such as the Internet, enabling information to be exchanged between the devices.

[0012] The user terminal 70 transmits information input by the producer to the server 10. FIG. 2(a) shows the hardware configuration of the user terminal 70. As shown in FIG. 2(a), the user terminal 70 includes a CPU (Central Processing Unit) 190, a ROM (Read Only Memory) 192, a RAM (Random Access Memory) 194, a storage unit (here, an SSD (Solid State Drive) or an HDD (Hard Disk Drive)) 196, a network interface 197, a display unit 193, an input unit 195, and a portable storage medium drive 199 capable of reading the portable storage medium 191. These components of the user terminal 70 are connected to a bus 198. The display unit 193 includes a liquid crystal display or the like, and the input unit 195 includes a keyboard, a mouse, a touch panel, or the like.

[0013] The server 10 is a device that acquires information from the user terminal 70, generates information based on the acquired information to assist in the selection of strawberry varieties and cultivation management, and outputs a screen displaying the information to the user terminal 70 used by the producer.

[0014] FIG. 2(b) shows the hardware configuration of the server 10. As shown in FIG. 2(b), the server 10 includes a CPU 90, a ROM 92, a RAM 94, a storage unit (here, an SSD or HDD) 96, a network interface 97, and a portable storage medium drive 99 as a computer. These components of the server 10 are connected to a bus 98. In the server 10, the CPU 90 executes a program (including a cultivation assistance program) stored in the ROM 92 or the HDD 96, or a program (including a cultivation assistance program) read from the portable storage medium 91 by the portable storage medium drive 99, thereby realizing the functions of the components shown in FIG. 4. The functions of the components shown in FIG. 4 may be realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0015] Fig. 3 shows a functional block diagram of the server 10. In the server 10, the CPU 90 executes a program to function as a selection receiving unit 41, an environmental data acquisition unit 42 as an acquisition unit, a cultivation information acquisition unit 43, a simulation unit 44, an output unit 45, and an update unit 46, as shown in Fig. 3. Note that Fig. 3 also shows a parameter DB 50 as a storage unit stored in the storage unit 96 of the server 10.

[0016] The selection receiving unit 41 receives information on the combination of variety (e.g., Tochiotome, Koiminori, etc.) and cultivation location (e.g., Tsukuba, Morioka, Kurume, etc.) selected by the producer. The producer may select one or more combinations of variety and location. The selection receiving unit 41 transmits the received information to the simulation unit 44.

[0017] The environmental data acquisition unit 42 acquires environmental data for the cultivation location based on the information about the cultivation location accepted by the selection acceptance unit 41. The environmental data acquisition unit 42 acquires data corresponding to the selected cultivation location from past weather data and future weather data (forecast data) managed in the server 10 or in a device other than the server 10. The weather data includes data such as outdoor solar radiation and air temperature, solar radiation and air temperature inside the greenhouse, humidity, CO2 concentration, soil temperature, and soil moisture. The environmental data acquisition unit 42 transmits the acquired data to the simulation unit 44.

[0018] The cultivation information acquisition unit 43 acquires cultivation information (e.g., planting date, cultivation density, soil culture / hydroponics, number of leaves at planting, amount of fertilizer applied, concentration of nutrient solution, etc.) input by the producer. The cultivation information acquisition unit 43 transmits the acquired information to the simulation unit 44.

[0019] The simulation unit 44 reads parameters corresponding to the variety accepted by the selection accepting unit 41 from the parameter DB 50, and creates a growth model using the read parameters and data transmitted from the environmental data acquiring unit 42 and the cultivation information acquiring unit 43. Here, the parameters stored in the parameter DB 50 are, for example, parameters such as those shown in FIG. 9 , which are defined for each variety. The simulation unit 44 then uses the created growth model to perform a simulation of the growth of the crop when the variety selected by the producer is cultivated at the cultivation location and by the cultivation method selected by the producer. The simulation results of the simulation unit 44 include leaf area, flowering date per inflorescence, yield per inflorescence, fruit dry matter distribution rate, photosynthesis rate, growth amount (stem and leaf), growth amount (fruit), and nutrient absorption amount (fertilizer amount). The simulation unit 44 transmits the simulation results to the output unit 45.

[0020] The output unit 45 generates a screen that displays the simulation results received from the simulation unit 44 and transmits them to the user terminal 70 used by the producer. At this time, the output unit 45 compiles the simulation results for each cultivation condition (combination of variety, cultivation location, and cultivation information) and generates a screen that displays the simulation results for different cultivation conditions in a comparable state.

[0021] The update unit 46 acquires information on the varieties actually cultivated and cultivation results (e.g., leaf area, flowering date per inflorescence, yield per inflorescence, etc.) from the producer. Then, the update unit 46 updates the parameters stored in the parameter DB 50 so that the actual cultivation results approach the simulation results. Note that the update unit 46 may determine whether or not to update the parameters using the actual cultivation results based on a reliability predetermined for the producer who input the actual cultivation results.

[0022] (Regarding Server 10 processing) Next, the details of the processing of the server 10 will be described.

[0023] 4 is a flowchart showing the processing of the server 10. In the processing of FIG. 4, first, in step S10, the selection receiving unit 41 waits until the producer selects a combination of variety and cultivation location on the user terminal 70. Here, for example, it is assumed that the producer has selected the combinations of "Tochiotome Tsukuba," "Tochiotome Morioka," "Koiminori Tsukuba," "Oi C Berry Tsukuba," and "Sachinoka Kurume."

[0024] If the determination in step S10 is affirmative, in the next step S12, the selection receiving unit 41 acquires the selected combination of variety and cultivation location, and transmits it to the environmental data acquisition unit 42 and the simulation unit 44.

[0025] Next, in step S14, the environmental data acquisition unit 42 acquires meteorological data (past data and forecast data) for the cultivation location selected by the producer and accepted by the selection acceptance unit 41.

[0026] Next, in step S16, the cultivation information acquisition unit 43 waits until the producer inputs cultivation information (e.g., planting time, planting density, soil cultivation / nutrient cultivation, number of leaves at planting). Once the producer inputs the cultivation information, the process proceeds to step S18, where the cultivation information acquisition unit 43 acquires the input cultivation information and transmits it to the simulation unit 44.

[0027] Next, in step S20, the simulation unit 44 reads out the parameters of each variety selected by the producer that are stored in the parameter DB 50, and creates a growth model corresponding to the combination of the selected variety and cultivation location based on the parameters, the weather data acquired by the environmental data acquisition unit 42, and the cultivation information acquired by the cultivation information acquisition unit 43.

[0028] The simulation unit 44 then executes a simulation using the created growth model to obtain simulation results that indicate how each variety will grow at each cultivation location. The growth model created by the simulation unit 44 and the simulation results will be described in detail later. The simulation unit 44 transmits the simulation results to the output unit 45.

[0029] Next, in step S22, the output unit 45 generates a screen for displaying the simulation results and transmits it to the user terminal 70. The screen for displaying the simulation results is, for example, a screen as shown in FIGS.

[0030] (About the simulation) The simulation performed by the simulation unit 44 will be described in detail below.

[0031] (1) Basic concept of simulation In this embodiment, a growth model capable of explaining important differences between varieties is used. Specifically, a growth model capable of explaining photosynthetic characteristics, distribution of photosynthetic products, leaf development and elongation, flower development and enlargement, nutrient absorption, morphological characteristics (leaf shape, light reception posture), etc., as shown in Fig. 5, is used. Note that although a simulation of strawberry will be described in this embodiment, the model is designed to clarify the meaning of parameters so that it can be applied to other crops.

[0032] (a) Growth patterns In the simulation, weather data (daily average temperature and daily outdoor global solar radiation) is provided to the growth model on a daily basis, and the growth status of each crop organ (roots, leaves, crown, fruit) is calculated. In reality, crops are always in a state of growth, and crop size (size of roots, leaves, crown, number of fruits, etc.) is constantly changing, but in the simulation, it is assumed that the crop size is fixed at midnight, and that it receives temperature and solar radiation in that state from midnight to midnight. To reduce errors due to this assumption, the calculation interval of the simulation (the calculation interval in this simulation is one day) can be shortened, for example.

[0033] In this simulation, when calculating the Nth day, the crop size for that day is determined at 0:00 on the Nth day. This means that the temperature, solar radiation conditions (relative light interception rate: a value calculated from the leaf area index), and distribution rate (the proportion of photosynthetic products generated that day distributed to each organ: leaves, crown, inflorescence, and roots) for the crop are fixed from 0:00 to 24:00 on the Nth day. In this simulation, the amount of photosynthesis is calculated based on the temperature, solar radiation, and CO2 concentration for that day (day N), and the crop size changes based on this value through crop growth calculations. Figure 6 conceptually illustrates the change in crop size in this simulation. Note that for the first day of the calculation, the crop size at 0:00 (day 0 crop size) cannot be calculated, so the grower or other personnel must set this value.

[0034] (b) Relationship between photosynthate amount and size In this simulation, photosynthetic products are called "sources," and organs that produce sources are called "source organs." Source organs are mainly leaves. On the other hand, organs that store and consume sources are called "sink organs." Sink organs are roots, crowns, leaves, and fruits, but the sink organ with the highest consumption is the fruit.

[0035] In this simulation, crop growth is assumed to be primarily determined by temperature. For example, the growth process of a single leaf is described as follows using accumulated temperature. The accumulated temperature when growth stops is set to 1.0, and the accumulated temperature when growth begins is set to 0, and the leaf growth stage is shown as a relative value of the accumulated temperature. This is defined as the [Leaf Growth Index].

[0036] Here, the relative leaf size corresponding to the [Leaf Growth Index] is defined as the [Leaf Size Index] (Figure 7). The [Leaf Size Index] is set to 1.0 for the size of a fully grown leaf, and 0 for the size before the start of growth.

[0037] In this simulation, the growth of leaves and fruits is approximated by a sigmoid curve. The relationship between [Leaf Growth Index] and [Leaf Size Index] is expressed by equation (1) (Figure 7). x is [Leaf Growth Index] and S(x) is [Leaf Size Index].

[0038]

number

[0039] The difference in the S(x) values ​​between midnight and midnight on the Nth day (see Figure 7) is defined as the [Leaf Increase Index], which is an index value for the amount of leaf growth increase per day. Similarly, the relative growth of the inflorescence is defined as the [Fruits Increase Index]. Note that the values ​​of the sigmoid curve used in this simulation are S(x) = 0.007 at x = 0 and S(x) = 0.993 at x = 1, so we change them to S(x) = 0 below x = 0 and S(x) = 1 above x = 1.

[0040] (c) Overview of the simulation model The simulation is performed based on meteorological data and parameters (constants). The meteorological data used for the simulation are the daily mean temperature (°C), the daily outdoor global solar radiation (MJ / m 2 ), CO2 concentration (ppm), etc. Examples of parameters set by users such as producers are shown in Figure 9. This simulation is calculated on a daily basis, with values ​​calculated for each leaf and each inflorescence, as well as values ​​calculated for the entire crop. Growth is calculated for the state of each organ of the crop (leaf, crown, fruit, roots, inflorescence).

[0041] (2) Simulation method (a) Overview of the simulation This simulation is broadly divided into the following processes: photosynthesis calculation, crop growth calculation, fruit yield calculation, and nutrient absorption calculation. These calculations are performed on a daily basis. The variables used to calculate photosynthesis (relative light interception, distribution rate) are values ​​at midnight on the calculation day (the day before the calculation day). Relative light interception is a variable used to calculate the amount of light interception used by the crop for photosynthesis from the amount of solar radiation. The distribution rate is the proportion of the source synthesized by the crop on that day that is distributed to each organ (roots, leaves, crown, fruit). The amount of photosynthesis at midnight on the calculation day is calculated using the distribution rate and these values, as well as the temperature and solar radiation on that day. The crop growth level at midnight on the calculation day is then calculated based on the amount of photosynthesis. The crop growth calculation is divided into (a) distribution amount calculation, (b) leaf area calculation, (c) fruit number calculation, (d) fruit dry weight calculation, and (e) distribution rate calculation.

[0042] In this specification, the subscript N attached to a variable name indicates the result at 24:00 on the Nth day. Variables calculated for each leaf are given the subscript M (leaf rank), and variables calculated for each inflorescence are given the subscript F (inflorescence rank). Variables and constants used in formulas are indicated by brackets [ ]. In this simulation, the value at 0:00 on the first day of calculation is considered the "initial value."

[0043] (b) Crop growth process In this simulation, crop growth is determined by the relationship between the previous leaf and the order of the previous inflorescence (the order in which leaves and inflorescences emerge; the earlier they emerge, the lower their order), as well as the accumulated temperature. Figures 10(a) and 10(b) conceptually illustrate the leaf and inflorescence growth process in this simulation (the values ​​listed below are fictitious values ​​based on a fictitious variety and are not actual values). As shown in Figure 10(a), the growth of the next leaf begins when the accumulated temperature reaches 150°C, starting from the start of growth of the previous leaf. Leaf growth ends when the accumulated temperature reaches 450°C, starting from the start of flower bud differentiation of the previous inflorescence. On the other hand, as shown in Figure 10(b), the flower bud differentiation of the next inflorescence begins when the accumulated temperature reaches 600°C, starting from this flower bud differentiation. Starting from this flower bud differentiation, the flowering period begins when the accumulated temperature reaches 600°C, and the fruit that makes up the inflorescence begins to enlarge. Furthermore, starting from flowering, the growth of the inflorescence ends when the accumulated temperature reaches 600°C. As shown in Figure 10(b), the period from the start of flower bud differentiation to an accumulated temperature of 150°C is the flower number determination period, and the number of fruits set is determined by the conditions during this period.

[0044] (c) Calculation of photosynthesis amount Light use efficiency (LUE) (gDW / MJ) is a value that indicates the dry matter production of the entire crop per unit of received light. It is given as a function of temperature or CO2 concentration.

[0045] Also, the amount of solar radiation inside the greenhouse [global solar radiation inside the greenhouse] (MJ / m 2 ) is [Outdoor global solar radiation] (MJ / m 2 ) is multiplied by the greenhouse's solar transmittance (constant) (Equation (2)). [Total solar radiation inside the greenhouse] N = [Solar transmittance] · [Outdoor global solar radiation] N …(2)

[0046] In addition, the amount of light received by crops for photosynthesis (MJ / m 2 ) is calculated using the following formula (3). The relative light interception rate is calculated from the leaf area of ​​the previous day. [Light received amount] N = [Relative received light amount] (N-1)· [Total solar radiation inside the greenhouse] N …(3)

[0047] Furthermore, the amount of photosynthesis of the entire crop per unit area, [dry matter production] (gDW / m 2 ) is calculated using the following equation (4). [Dry matter production] N =[Light received amount] N [LUE] N …(4)

[0048] The amount of photosynthesis per plant, [Photosynthesis Amount] (gDW / plant), is calculated by multiplying the number of plants per unit area (constant) by [Plant Density] (plant / m 2 ) and calculate it using the following equation (5). [Photosynthesis amount] N = [dry matter production] N / [Plant Density] …(5)

[0049] In addition, in the leaf area calculation that will be performed later, the specific leaf area, which is the leaf area per dry weight of the leaf, [SLA] (m 2 / gDW) is used. [SLA] N is expressed as a function of temperature.

[0050] (3) Crop growth calculation (a) Distribution amount calculation The allocation calculation determines the amount of photosynthesis produced distributed to each organ. The allocation amount is calculated as a value for the entire crop, and is basically determined from the amount of photosynthesis and the allocation rate, but a correction is made by setting [inflorescence potential growth amount] (gDW / plant) as the maximum amount of source that can be received by an inflorescence (maximum amount of allocation). [Inflorescence potential growth amount] can be calculated using the following formula (6). Note that the [inflorescence growth amount coefficient] (gDW / (plant·°C)) in formula (6) is a coefficient that indicates the maximum amount of source that can be received by one inflorescence per 1°C of temperature, and the [Total Fruits Increase Index] is the sum of the relative growth amounts of all inflorescences. [Flower cluster potential growth] N = [Flower cluster growth coefficient]·[Temperature]N ·[Total Fruits Increase Index] N-1 …(6)

[0051] Allocation is calculated in three stages. For this reason, the variables for the first two stages are labeled (1) and (2) to distinguish them from the final results. The unit for photosynthesis and allocation is (gDW / plant). [Leaf allocation (1)], [Crown allocation (1)], [Inflorescence allocation (1)], [Root allocation (1)] (gDW / plant) are calculated using the following formulas (7A) to (7D), assuming that the amount of photosynthesis from 0 to 24:00 on the day is allocated to each organ according to the allocation rate of the previous day (0:00 on the day). [Leaf distribution amount (1)] N =[leaf distribution rate] N-1 ·[Photosynthesis amount] N …(7A) [Crown distribution amount (1)] N =[Crown distribution rate] N-1 ·[Photosynthesis amount] N …(7B) [Flower bunch distribution amount (1)] N =[Flower cluster distribution rate] N-1 ·[Photosynthesis amount] N …(7C) [Root distribution amount (1)] N =[root distribution ratio] N-1 ·[Photosynthesis amount] N …(7D)

[0052] In addition, [Leaf distribution amount (2)], [Crown distribution amount (2)], and [Root distribution amount (2)] (gDW / plant) are corrected as follows so that the inflorescence distribution amount does not exceed the inflorescence potential growth amount. [Leaf distribution amount (2)] N =[leaf distribution amount(1)] N …(7A)' [Crown distribution amount (2)] N =[Crown Distribution Amount(1)] N …(7B)' [Root distribution amount (2)] N =[root distribution amount (1)] N …(7D)'

[0053] Regarding [Flower cluster allocation amount (2)], [Flower cluster allocation amount (1)] N <[Flower cluster potential growth rate] N If so, [Inflorescence distribution amount (2) N =[Inflorescence distribution amount (1)] N …(7C1)' In other cases, [Flower bunch distribution amount (2)] N = [inflorescence potential growth] N …(7C2)' Let's say.

[0054] Here, the amount of photosynthesis that was not distributed to the inflorescence because it exceeded the inflorescence potential growth rate, [excess dry matter] (gDW / plant), is expressed by the following equation (8). [Excess dry matter] N =([Leaf distribution amount(1)] N +[Crown Distribution Amount (1)] N +[Inflorescence distribution amount (1)] N +[Root distribution amount (1)] N )-([Leaf distribution amount (2)] N +[Crown Distribution Amount (2)] N +[Inflorescence distribution amount (2)] N +[Root distribution amount (2)] N ) …(8)

[0055] The excess dry matter is redistributed to areas other than the inflorescence, and the respective distribution amounts are calculated using the following formulas (9A) to (9D). [Leaf distribution amount] N =[leaf distribution amount(2)] N + [leaf surplus distribution rate] · [surplus dry matter] N …(9A) [Crown distribution amount] N =[Crown Distribution Amount(2)] N + [Crown surplus distribution rate] · [Excess dry matter] N …(9B) [Flower bunch distribution amount] N =[Inflorescence distribution amount (2)] N …(9C) [Root distribution amount] N =[root distribution amount(2)] N+ [Root surplus distribution rate] · [Excess dry matter] N …(9D)

[0056] (b) Leaf area calculation To calculate leaf area, calculate the area of ​​each leaf, as well as the dry weight (DW) of the leaf and crown. First, calculate the Leaf Growth Index (dimensionless), which indicates the leaf growth stage as a relative value of the accumulated temperature, using the following equation (10A). Note that M is the leaf rank. [Leaf Growth Index] M,N ={[Accumulated temperature] N -(M-1)·150} / 450 …(10A)

[0057] The leaf size index, [Leaf Size Index] (dimensionless), is calculated using the following equation (10B). The initial value of [Leaf Size Index] is set to zero.

[0058]

number

[0059] In addition, the leaf growth index [Leaf Increase Index] (dimensionless) is calculated from the change in leaf size index from midnight of the previous day (midnight of the current day) to midnight of the current day using the following equation (11). [Leaf Increase Index] M,N =[Leaf Size Index] M,N -[Leaf Size Index] M,N-1 …(11)

[0060] The sum of the [Leaf Increase Index] of all leaves is defined as the [Total Leaf Increase Index], which is calculated using the following formula (12): NL stands for the number of leaves.

[0061]

number

[0062] These values ​​are then used to calculate the leaf dry weight, [Leaf DW] (gDW / plant), as follows: The initial value of [Leaf DW] is set by the producer (e.g., 10.0) only for the first leaf (here, the first leaf is defined as the leaf that newly unfolds after planting), and all other values ​​are set to zero. [Leaf DW] M,N =[Leaf DW] M,N-1 +[Leaf ΔDW] M,N …(13A) In addition, [Leaf ΔDW] M,N is expressed by the following equation (13B). [Leaf ΔDW] M,N =[leaf distribution amount] M,N Leaf Increase Index M,N / [Total Leaf Increase Index] N …(13B)

[0063] Additionally, the crown is assumed to increase by a fixed percentage with each additional leaf, and the dry weight [Stem DW] (gDW / plant) is calculated in the same way as [Leaf DW], as follows: The initial value of [Stem DW] is set by the producer (e.g., 5.0) only for the first node (here, the node newly generated after planting is defined as the first node), and all other nodes are set to zero. [Stem DW] M,N =[Stem DW] M,N-1 +[Stem ΔDW] M,N …(14A) In addition, [Stem ΔDW] M,N is expressed by the following equation (14B). [Stem ΔDW] M,N =[Crown distribution amount] M,N Leaf Increase Index M,N / [Total Leaf Increase Index] N …(14B)

[0064] Leaf Area [Leaf Area](m 2 / plant) is the specific leaf area [SLA] (m 2 / gDW) and calculate it using the following formula (15). Note that [Leaf Area] is set by the producer etc. only for the first leaf, and other leaves are set to 0. [Leaf Area] M,N =[Leaf Area] M,N-1 +[SLA] N ·[Leaf distribution amount] M,N Leaf Increase Index M,N / [Total Leaf Increase Index] N …(15)

[0065] The total leaf area of ​​the crop [Leaf Area] is defined as [Total Leaf Area(1)](m 2 / plant), [Total Leaf Area(1)] can be calculated using the following formula (16).

[0066]

number

[0067] Furthermore, leaf parameters used in calculating the amount of photosynthesis are calculated.

[0068] First, the leaf area index (LAI) (dimensionless), which is the leaf area per unit land area, is calculated by multiplying it by the plant density (plants / m), which is the number of crop plants per land area. 2 ) is used to calculate the value from the following equation (17). [LAI] N =[Total Leaf Area] N [Plant Density]...(17)

[0069] Furthermore, the [relative light reception] (dimensionless), which represents the ratio of the amount of solar radiation received by the crop to the amount of solar radiation per land area, can be calculated using the light absorption coefficient [K] (dimensionless) and the leaf area index of the previous day using the following equation (18). The light absorption coefficient is a coefficient that indicates the ease with which light reaches the interior of the canopy. [Relative light reception amount] N =1-exp(-[K]·[LAI] N ) …(18)

[0070] (c) Calculation of number of fruit set The number of fruits is calculated for each inflorescence from the amount of photosynthesis (period dry matter production) during a specific period (the flower number determination period) starting the day after flower bud differentiation of the crop begins, and the relationship between period dry matter production and the number of fruits. Flower bud differentiation occurs in the order of inflorescence rank, and after the differentiation of the next inflorescence rank (the previous inflorescence rank), a certain amount of temperature must accumulate before the next inflorescence rank will differentiate.

[0071] The [Differentiation Start Index], which indicates the start of differentiation, is determined by the [Differentiation Condition Judgment A] (°C) and [Differentiation Condition Judgment B] described below. Here, the [Flower Bud Differentiation Stage Accumulated Temperature] (°C) is the accumulated temperature on the day when the [Differentiation Start Index] first becomes 1, and before that it is -1.0.

[0072] In this simulation, based on the value of the [Flower Bud Differentiation Period Accumulated Temperature], [Differentiation Condition Judgment A] is calculated as follows, which is an index for determining whether the accumulated temperature from the day after flower bud differentiation of the pre-order inflorescence begins exceeds a certain value (for example, 600°C). Note that the value of 600°C is set at 150°C, the accumulated temperature required for one leaf to appear, since in this variety, four leaves normally appear between inflorescences. F in the formula indicates the inflorescence order. [Differentiation start index] F-1,N If =1, [Differentiation condition judgment A] F,N =[Accumulated temperature] N -([Flower bud differentiation stage accumulated temperature] F-1,N +600) …(19A) In other cases, [Differentiation condition judgment A] F,N =-1.0 …(19B) He demands.

[0073] In addition, [Differentiation Condition Judgment B] (gDW / plant), which is an index for judging whether the amount of photosynthesis is in a state where flower bud differentiation is possible, is calculated using the following formula (20). [Differentiation condition judgment B] N = (N-6 to N-day average value of [photosynthetic amount]) ... (20)

[0074] In addition, once the [Differentiation Start Index], which indicates the start of flower bud differentiation, reaches 1, it will remain at 1 thereafter. That is, [Differentiation Initiation Index] F,N-1 If =1, [Differentiation start index] F,N =1 …(21A) 0.0≦[Differentiation condition judgment A] F,N , and 1.0<[Differentiation Condition Judgment B] N If so, [Differentiation start index] F,N =1 …(21B) In other cases, [Differentiation start index] F,N =0 …(21C) Let's say.

[0075] Furthermore, the [Flower bud differentiation stage accumulated temperature] in the above formula (19A) is the accumulated temperature on the day when the value of the [Differentiation start index] the previous day was 0 and the value of the day was 1. The initial value of the [Flower bud differentiation stage accumulated temperature] is -1.0, and once the [Flower bud differentiation stage accumulated temperature] is set, it remains the same value. The reason for setting the initial value to a negative value is to classify [Flower bud differentiation stage accumulated temperature] after the start of the flower bud differentiation stage as positive values, and those before that as negative values. This classification by positive and negative values ​​is also performed for the flowering stage accumulated temperature. That is, [Differentiation Initiation Index] F,N-1 = 0 and [Differentiation Start Index] F,N If =1, [Flower bud differentiation stage accumulated temperature] F,N =[Accumulated temperature] N …(22A) In other cases, [Flower bud differentiation stage accumulated temperature] F,N =[Accumulated temperature during flower bud differentiation] F,N-1 …(22B) is.

[0076] Furthermore, in this simulation, the period after the start of flower bud differentiation in which the accumulated temperature is in the range of 0 to 150°C is defined as the flower number determination period, and the [flower number determination period Index(1)] (dimensionless), which serves as an index indicating whether or not the flower number determination period is in progress, is calculated as follows: The flower number determination period is defined as the period in which one leaf unfolds, and assuming that the accumulated temperature per leaf is 150°C, the accumulated temperature during the flower number determination period is set to 150°C. That is, [Differentiation Initiation Index] F,N If =0, [Flower number determination period index (1)] F,N =-1.0 …(23A) In other cases, [Flower number determination period index (1)] F,N =([Accumulated Temperature] N -[Flower bud differentiation stage accumulated temperature] F,N ) / 150 …(23B)

[0077] The [flower number determination period index] (dimensionless) is calculated as follows so that it is 1 when the accumulated temperature from the start of flower bud differentiation is in the range of 0 to 150°C. 0.0≦[Flower number determination period index(1)] F,N If ≦1.0, [Flower number determination period index] F,N =1 …(24A) In other cases, [Flower number determination period index] F,N =0 …(24B)

[0078] The integrated value of the amount of photosynthesis during the flower number determination period, [determination period photosynthesis amount] (gDW / plant), is expressed by the following equation (25). [Photosynthetic amount during the decision period] F,N =[Determined period photosynthesis rate] F,N-1+[Flower number determination period index] F,N ·[Photosynthesis amount] F,N …(twenty five)

[0079] The number of fruits (1) (pieces / plant) is calculated by the above formula (25) using the amount of photosynthesis in the critical period and the number of fruits per dry matter production in the critical period (m 2 ·Pieces / gDW·Plant), and [Plant Density] (Plant / m 2 ) can be used to obtain the following equation (26): [Number of fruits (1)] F,N =[Determined period photosynthesis rate] M,N ·[Number of fruits per dry matter production in the decision period]·[Plant Density] …(26)

[0080] The number of fruits (pieces / plant) is corrected to fall within the range of 1.0 to 10.0 as follows: That is, [Number of fruits (1)] F,N If <1.0, [Number of fruit set] F,N =1.0 …(27A) 1.0≦[Number of fruit set (1)] F,N If ≦10.0, [Number of fruit set] F,N= [Number of fruits (1)] F,N …(27B) In other cases, [Number of fruit set] F,N =10.0 …(27C) Let's say.

[0081] The flowering stage is defined as the point when the accumulated temperature from the flower bud differentiation stage reaches 600°C, and the accumulated temperature at that point is defined as the [flowering stage accumulated temperature] (°C). The value of 600°C was set based on the assumption that after flower bud differentiation, four leaves bloom, and that an accumulated temperature of 150°C is required per leaf. The flowering stage accumulated temperature is set to be valid only after the flower bud differentiation stage accumulated temperature has been determined, and its initial value is set to -1.0. Once the flowering stage accumulated temperature has been set, it remains the same value. That is, [Flower bud differentiation stage accumulated temperature] F,N If <0, [Accumulated temperature during flowering period] F,N =-1.0 …(28A) In other cases, [Accumulated temperature during flowering period] F,N =[Accumulated temperature during flower bud differentiation] F,N +600 …(28B) This becomes:

[0082] (d) Inflorescence dry weight calculation The Fruits Growth Index (dimensionless), which is the relative growth stage of the inflorescence, is calculated as follows. If the flowering stage accumulated temperature is invalid (less than 0), the value of the Fruits Growth Index is set to -1.0. The initial value of the Fruits Growth Index is also set to -1.0. That is, [Flowering stage accumulated temperature] F,N If <0, [Fruits Growth Index] F,N =-1.0 …(29A) In other cases, [Fruits Growth Index] F,N =([Accumulated Temperature] N -[Flowering stage accumulated temperature] F,N ) / 600 …(29B) Let's say.

[0083] Also, the [Fruits Size Index] (dimensionless) is calculated using the following equation (30). The initial value of the Fruits Size Index is set to zero.

[0084]

number

[0085] In addition, the relative growth increase of the inflorescence is calculated from the magnitude of the relative change in the inflorescence from midnight the previous day (midnight on the current day) to midnight on the current day, and the [Fruits Increase Index(1)] (dimensionless) is calculated using the following equation (31). [Fruits Increase Index(1)] F,N =[Fruits Size Index] F,N -[Fruits Size Index] F,N-1 …(31)

[0086] However, since the inflorescence is based on the assumption that the number of fruits is 10, it is corrected as shown in the following equation (32) and is given as [Fruits Increase Index] (dimensionless). [Fruits Increase Index] F,N =([Fruits Increase Index(1)] F,N ·[Number of fruit set] F,N ) / 10 …(32)

[0087] The sum of the [Fruits Increase Index] of all inflorescences is defined as the [Total Fruits Increase Index] (dimensionless) (see the following formula (33)). Note that NF means the number of inflorescences.

[0088]

number

[0089] In this simulation, these values ​​are used to calculate the inflorescence dry weight, [Fruits DW] (gDW / plant). Basically, [Fruits DW] does not increase once [Fruits Growth Index] exceeds 1. The initial value of [Fruits DW] is set to zero. [Fruits DW] F,N =[Fruits DW] F,N-1 +[Fruits ΔDW] F,N …(34A) In addition, [Fruits ΔDW] F,N is expressed by the following equation (34B). [Fruits ΔDW] F,N =[Inflorescence distribution amount] NFruits Increase Index F,N / [Total Fruits Increase Index] N …(34B)

[0090] (e) Distribution rate calculation The [allocation ratio] (dimensionless) of a crop is calculated as a value for the whole crop based on the amount of crop growth. The allocation ratio is calculated from the [inflorescence sink strength] (dimensionless), which is the ease with which the inflorescence receives the source, and the [total sink strength], which is the sum of the sink strengths of all organs.

[0091] The [Total Fruits Increase Index], [Total Leaf Increase Index], and [Total Stem Increase Index] are weighted based on experimental data from dissection surveys, etc. The [Fruit Distribution Adjustment Coefficient], [Leaf Distribution Adjustment Coefficient], and [Crown Distribution Adjustment Coefficient] are designated as [α], [β], and [γ]. From these, the inflorescence sink strength, leaf sink strength, crown sink strength, and total sink strength are calculated using the following formula. [Flower cluster sink strength] N =[Total Fruits Increase Index] N ·[α] …(35A) [Leaf sink strength] N =[Total Leaf Increase Index] N ·[β] …(35B) [Crown sink strength] N =[Total Stem Increase Index] N ·[γ] …(35C) [Sink Strength Total] N = [Flower cluster sink strength] N +[Leaf Sink Strength] N +[Crown Sink Strength] N +[Root sink strength]...(35D)

[0092] [Inflorescence distribution rate], [Root distribution rate], [Leaf distribution rate], and [Crown distribution rate] (dimensionless) are calculated using the following equations (36A) to (36D). [Flower cluster distribution rate] N = [Flower cluster sink strength] N / [total sink strength] N …(36A) [Root distribution ratio] N =0.05 …(36B) [Leaf distribution rate] N = [leaf sink strength] N / [total sink strength] N …(36C) [Crown distribution rate] N =[Crown Sink Strength] N / [total sink strength] N …(36D)

[0093] (4) Fruit yield calculation In this simulation, it is assumed that the target crops will not be harvested in one day within the inflorescence, but will be harvested gradually. The [Harvest Start Index] (dimensionless), which indicates that harvesting is possible, will be set to 1 from the day after the [Fruits Increase Index] first reaches 1.0 or above, and will be set to zero before that. The first day the [Harvest Start Index] reaches 1 will be considered the harvest start date. The [Harvest Start Index] is expressed as follows, and its initial value is zero. That is, [Harvest Start Index] F,N-1 If =1, [Harvest Start Index] F,N =1 …(37A) [Fruits Source Index] F,N-1 If ≧1.0, [Harvest Start Index] F,N =1 …(37B) In other cases, [Harvest Start Index] F,N =0 …(37C) This becomes:

[0094] Here, the total harvest volume per fruit inflorescence is [Fruits DW] (gDW / plant) on the start of harvest. Basically, [Fruits DW] does not increase once the [Fruits Growth Index] exceeds 1, so it remains the same from the start of harvest. Each fruit is harvested over a period of time until the accumulated temperature reaches 60°C. The dry weight of fruit harvested per 1°C of air temperature, [Harvested Fruit Temperature DW] (gDW / plant·°C), is calculated as follows. The initial value for [Harvested Fruit Temperature DW] is -1.0, and once a valid value is set, it remains the same. That is, [Harvested Fruit Temperature DW] F,N-1 If ≧0.0, [Harvested Fruit Temperature DW] F,N = [Harvested fruit temperature DW] F,N-1 …(38A) [Harvest Start Index] F,N =1 and [number of fruits] F,N-1 If >0.0, [Harvested Fruit Temperature DW] F,N =[Fruits DW] F,N-1 / ([Number of fruit set] F,N-1 60) …(38B) In other cases, [Harvested Fruit Temperature DW] F,N =-1.0 …(38C) Calculate as follows.

[0095] The dry weight of harvestable fruit before harvesting on the calculation date is defined as [Fruits unHarvest] (gDW / plant), and [Fruits unHarvest] is calculated as follows: On the start date of harvesting, [Fruits unHarvest] is given as the [Fruits DW] of the previous day, and thereafter the amount harvested decreases. The initial value of [Fruits unHarvest] is -1.0, and the values ​​before and after the harvest period are also -1.0. That is, [Fruits unHarvest] F,N-1 If ≧0.0, [Fruits unHarvest] F,N =[Fruits unHarvest] F,N-1 -[Fruits HARVEST] F,N-1 …(39A) [Harvest Start Index] F,N-1 =0 and [Harvest Start Index] F,N If =1, [Fruits unHarvest] F,N =[Fruits DW] F,N-1 …(39B) In other cases, [Fruits unHarvest] F,N =-1.0 …(39C) This becomes:

[0096] After the start of the harvest period, if there are fruits available for harvest, the dry weight of the harvested fruits [Fruits HARVEST] (gDW / plant) is calculated as follows. That is, [Harvest Start Index] F,N =1 and [Fruits unHarvest] F,N If >0.0, [Fruits Harvest] F,N =min([Harvested Fruit Temperature DW] F ·[temperature] N ,[Fruits unHarvest] F,N ) …(40A) In other cases, [Fruits Harvest] F,N =0.0 …(40B)

[0097] Furthermore, if the total [Fruits HARVEST] of all inflorescences is [fruit harvest dry weight] (gDW / plant), [fruit harvest dry weight] can be expressed by the following equation (41).

[0098]

number

[0099] By multiplying this [fruit harvest dry weight] by the [fruit fresh weight] (g / gDW), the [fruit harvest fresh weight] (g / plant) can be calculated as shown in the following equation (42). [Fruit harvested live weight] N = [fruit harvest dry weight] N ·[Fruit fresh weight] …(42)

[0100] Then, by multiplying [Fruit harvested live weight] by [Number of plants in the field] (plants), the yield of the entire field, [Fruit harvested live weight in the field] (kg), can be calculated as shown in the following equation (43). [Field-harvested fruit live weight] N = 0.001·[fruit harvested live weight] N ·[Number of plants in the field] …(43)

[0101] The simulation unit 44 creates a growth model as described above using environmental data and parameters, and uses the growth model to perform a growth simulation for each combination of variety, cultivation location, and cultivation information selected by the producer. The simulation results for each combination (values ​​obtained by the simulation) are then sent to the output unit 45. Note that the simulation unit 44 can also perform simulations for fruit and vegetables other than strawberries, such as tomatoes, strawberries, cucumbers, and peppers, by using parameters according to the item and variety.

[0102] (5) Calculation of nutrient absorption The amount of nutrient absorbed is calculated by multiplying the dry matter increase in leaves, crowns, fruits, and roots by the nutrient content. Here, N (nitrogen) is used as an example, but similar calculations can be used for other elements. [Leaf ΔN] M,N =[Leaf ΔDW] M,N ×[Leaf N%] M,N …(44A) [Stem ΔN] M,N =[Stem ΔDW] M,N ×[Stem N%] M,N …(44B) [Fruits ΔN] F,N=[Fruits DW] F,N ×[Fruits N%] F,N …(44C) [Root ΔN] M,N =[Root DW] M,N ×[Root N%] M,N …(44D)

[0103] In addition, [Leaf ΔN] in the above equation (44A) M,N is the amount of nutrients absorbed by the leaves, and [Leaf ΔDW] M,N is the increase in leaf dry matter, [Leaf N%] M,N is the nutrient content of the leaf. The same applies to the other equations (44B) to (44D).

[0104] Here, the nutrient content ([Leaf N%] M,N etc.) can be expressed as a function of the growth index of the organ, for example, by the following equation: where β and γ are constants. [Leaf N%] M,N =β L ×ln([Leaf Growth Index] M,N )+γ L …(45A) [Stem N%] M,N =β S ×ln([Stem Growth Index] M,N )+γ S …(45B) [Fruits N%] F,N =β F ×ln([Fruits Growth Index] F,N )+γ F …(45C) [Root N%] M,N =γ R …(45D)

[0105] The amount of nutrients absorbed by leaves, crowns, inflorescences, and roots is expressed by the following formula:

[0106]

number

[0107] Furthermore, the amount of nutrients absorbed per plant [Total ΔN] N is expressed by the following equation (47). [Total ΔN] N =[Total Leaf ΔN] N +[Total Stem ΔN] N +[Total Fruits ΔN] N +[Total Root ΔN] N …(47)

[0108] In addition, [Total ΔN] N is the "amount of nutrient absorption" estimated from the increase in dry matter weight per plant. This can be multiplied by the planting density to obtain the "amount of nutrient absorption per area." Furthermore, the "amount of nutrient absorption" can be divided by the [fertilizer use efficiency] to obtain the "amount of fertilizer application."

[0109] (Regarding the processing of the output unit 45) When the output unit 45 receives the simulation results transmitted from the simulation unit 44, it generates a screen displaying the simulation results. For example, the output unit 45 generates a screen displaying information such as that shown in FIG. 11 as the simulation results. In this case, the screen shown in FIG. 11 is displayed on the display unit 193 of the user terminal 70, allowing the producer to confirm how the variety will grow and what yield will be obtained when cultivated in which cultivation location and how. In addition, the simulation results for cultivating multiple items under different cultivation conditions are displayed side by side, allowing the producer to compare what cultivation results will be obtained when the variety and cultivation conditions are changed.

[0110] The output unit 45 can also generate a screen such as that shown in FIG. 12 , which shows the shipping volume by inflorescence when a variety selected by the producer is cultivated at a selected cultivation site, and output the screen to the user terminal 70. By referring to the screen shown in FIG. 12 , the producer can check the trends in the yield for the terminal inflorescence, the second inflorescence, the third inflorescence, etc. While FIG. 12 shows the yield for each inflorescence in separate graphs, these graphs may be displayed together in a single graph. In this case, the bar graphs showing the yield for each inflorescence may be displayed in different colors for easy understanding. Furthermore, the output unit 45 may graphically display the trends in total yield, as shown in FIG. 13( a), or the trends in LAI, as shown in FIG. 13( b). Other growth-related information (e.g., leaf area, flowering date by inflorescence, amount of photosynthesis, growth (crown, leaf, fruit, fruit load), nutrient absorption (fertilizer amount), etc.) may also be displayed numerically or graphically.

[0111] In addition, the output unit 45 may display the simulation results of the changes in dry weight of the leaves, crown, and each inflorescence when varieties A, B, and C are cultivated at a certain cultivation location, as shown in Figure 14, for example.

[0112] As described above, the output unit 45 may display simulation results for each combination of variety, cultivation location, and cultivation information in a comparable manner, as shown in FIG. 11 , or may display simulation results for cultivating a certain variety at a certain cultivation location, as shown in FIGS. 12 to 13(b). Furthermore, as shown in FIG. 14 , simulation results for cultivating different varieties at the same cultivation location may be displayed in a comparable manner. Furthermore, simulation results for cultivating a certain variety at different cultivation locations may be displayed in a comparable manner. In either case, it is possible to appropriately express the characteristics of a variety compared to conventional catalogs that express the characteristics of a variety using words, images, average values, etc. Therefore, producers can appropriately select varieties and cultivation locations by checking the simulation results. Furthermore, by being able to understand how agricultural crops will grow in the future, they can appropriately manage cultivation (securing workers, procuring materials, etc.).

[0113] (Regarding the processing of the update unit 46) When the producer inputs actual measurement values ​​(actual cultivation results) such as changes in yield or LAI, the update unit 46 compares the actual measurement values ​​with the corresponding simulation results, and adjusts and updates various parameters so that the simulation results approach the actual measurement values. In this way, the parameters are appropriately updated based on the actual measurement values, making it possible to obtain appropriate simulation results in the next and subsequent simulations.

[0114] Note that if the parameters are updated based on information input from all producers, there is a risk that the parameters may not be updated appropriately. For this reason, the update unit 46 may update the parameters based on input information only when information is input from a predetermined producer (a producer with high reliability). In this case, the update unit 46 executes processing in accordance with the flowchart shown in FIG. 15.

[0115] In the process of FIG. 15, first, in step S30, the update unit 46 waits until the producer inputs actual cultivation results (actual measurements) via the user terminal 70. Then, when the actual cultivation results are input, the process proceeds to step S32, where the update unit 46 determines whether the input is from a predetermined producer (a producer with high reliability). If the determination in step S32 is negative, the entire process of FIG. 15 ends, but if the determination is positive, the process proceeds to step S34. If the process proceeds to step S34, the update unit 46 updates the parameters so that the simulation results approach the actual cultivation results, stores the updated parameters in the parameter DB 50, and ends the entire process of FIG. 15.

[0116] When the update unit 46 updates the parameters using information input by a producer, the updated parameters may be managed as parameters exclusive to that producer. This allows each producer to customize the parameters according to the actual cultivation results. It is also possible for one producer to call and use the parameters of another producer.

[0117] The producer may directly modify the parameters. When the producer modifies the parameters, the update unit 46 may update the parameter DB 50 in accordance with the modification content.

[0118] As can be seen from the above description, the simulation unit 44 of this embodiment functions as a readout unit that reads out parameters indicating the characteristics of each variety of agricultural crop from the storage unit (parameter DB 50). The simulation unit 44 of this embodiment also functions as a prediction unit that creates a growth model for each variety based on the readout parameters and information on the cultivation environment (environmental data) and executes predictions regarding the growth of each variety from the growth model for each variety.

[0119] As described above in detail, in this embodiment, the simulation unit 44 reads parameters indicating the characteristics of each crop variety from the parameter database 50 and obtains environmental data corresponding to the cultivation location selected by the producer from the environmental data acquisition unit 42. The simulation unit 44 also creates a growth model for each variety based on the acquired environmental data and the read parameters, and performs a simulation using the created growth model. The output unit 45 then outputs the simulation results as information supporting variety selection and cultivation management. In this manner, in this embodiment, the results of a simulation of crop growth using a growth model created for each variety and cultivation location are displayed as information supporting variety selection and cultivation management. This allows for more accurate representation of the characteristics of a variety than conventional catalogs that express the characteristics of a variety using words, images, average values, or the like. This allows producers to appropriately select varieties and cultivation locations, and also understand how the crops will grow in the future, thereby enabling them to appropriately manage cultivation.

[0120] Furthermore, in this embodiment, the update unit 46 updates the parameters based on the actual cultivation results (yield, etc.) input by the producer, thereby updating the parameter DB 50. This makes it possible to update the parameters to appropriate values ​​based on the cultivation record. In this case, the update unit 46 updates the parameters so that the simulation results approach the cultivation record, thereby improving the accuracy of the simulation.

[0121] Furthermore, in this embodiment, if the producer is a predetermined producer (a producer with a predetermined level of reliability or higher) (S32: Yes), the update unit 46 updates the parameters based on the cultivation record entered by the producer (S34). This increases the likelihood that the parameters will be updated appropriately.

[0122] In this embodiment, the output unit 45 performs a simulation for each combination of variety, cultivation location, and cultivation information selected by the producer, and outputs the simulation results in a comparable manner. This allows the producer to compare the simulation results for multiple combinations of variety, cultivation location, and cultivation information, and determine which variety should be cultivated and how.

[0123] In the above embodiment, the server 10 is provided with the update unit 46, but the present invention is not limited to this. That is, the server 10 does not have to be provided with the update unit 46.

[0124] In the above embodiment, the case where the server 10 has the functions of the agricultural support device of the present invention has been described, but this is not limiting, and the user terminal 70 may have the functions of the agricultural support device. In other words, the above processing may be realized by the standalone user terminal 70 operating independently.

[0125] The above processing functions can be realized by a computer. In this case, a program is provided that describes the processing contents of the functions that the processing device should have. By executing the program on a computer, the above processing functions are realized on the computer. The program that describes the processing contents can be recorded on a computer-readable storage medium (excluding carrier waves).

[0126] When distributing a program, it is sold in the form of a portable storage medium on which the program is recorded, such as a DVD (Digital Versatile Disc) or a CD-ROM (Compact Disc Read Only Memory).The program can also be stored in the storage device of a server computer and transferred from the server computer to other computers via a network.

[0127] A computer that executes a program stores, for example, a program recorded on a portable storage medium or a program transferred from a server computer in its own storage device. The computer then reads the program from its own storage device and executes processing in accordance with the program. Note that the computer can also read the program directly from a portable storage medium and execute processing in accordance with that program. The computer can also execute processing in accordance with the program received each time a program is transferred from the server computer.

[0128] The above-described embodiment is a preferred example of the present invention, but the present invention is not limited to this and can be modified in various ways without departing from the spirit of the present invention. [Explanation of symbols]

[0129] 10 Server (Agricultural support equipment) 42 Environmental data acquisition unit (acquisition unit) 44 Simulation section (read section, prediction section) 45 Output section 50 Parameter DB (storage section) 100 Farming Systems

Claims

1. Accepting information on multiple combinations of crop varieties and cultivation locations selected by the user; Acquire information about the cultivation environment of the crops at each of the cultivation locations; Obtain information about the cultivation method entered by the user, parameters indicating the characteristics of each of the varieties are read from a storage unit, a growth model is created that predicts the daily growth of each organ of the agricultural crop based on the parameters read from the storage unit, the acquired information on the cultivation environment, and the acquired information on the cultivation method, and the daily growth of each organ of the agricultural crop is predicted from the growth model for each cultivation condition that is a combination of information on the variety, cultivation location, and cultivation method; outputting information indicating the daily growth of each organ of the crop obtained by the prediction in a comparable manner; updating the parameters based on information input by a predetermined user having a predetermined reliability or higher among information indicating the cultivation results of the agricultural crops input by the user, and storing the updated parameters in the storage unit; An agricultural support program that allows computers to perform processing.

2. 2. The agricultural support program according to claim 1, wherein the parameters are updated so that the results of the prediction approach the predetermined information input by the user.

3. Accepting information on multiple combinations of crop varieties and cultivation locations selected by the user; Acquire information about the cultivation environment of the crops at each of the cultivation locations; Obtain information about the cultivation method entered by the user, parameters indicating the characteristics of each of the varieties are read from a storage unit, a growth model is created that predicts the daily growth of each organ of the agricultural crop based on the parameters read from the storage unit, the acquired information on the cultivation environment, and the acquired information on the cultivation method, and the daily growth of each organ of the agricultural crop is predicted from the growth model for each cultivation condition that is a combination of information on the variety, cultivation location, and cultivation method; outputting information indicating the daily growth of each organ of the crop obtained by the prediction in a comparable manner; updating the parameters based on information input by a predetermined user having a predetermined reliability or higher among information indicating the cultivation results of the agricultural crops input by the user, and storing the updated parameters in the storage unit; An agricultural support method characterized in that processing is executed by a computer.

4. a selection receiving unit that receives information on a plurality of combinations of a plurality of varieties of agricultural crops and cultivation locations selected by a user; an environmental information acquisition unit that acquires information about the cultivation environment of the agricultural crops at each of the cultivation locations; a cultivation information acquisition unit that acquires information about the cultivation method input by the user; a prediction unit that reads out parameters indicating characteristics of each of the varieties from a storage unit, creates a growth model that predicts daily growth of each organ of the agricultural crop based on the parameters read out from the storage unit, the acquired information on the cultivation environment, and the acquired information on the cultivation method, and predicts daily growth of each organ of the agricultural crop from the growth model for each cultivation condition that is a combination of information on the variety, cultivation location, and cultivation method; an output unit that outputs information indicating the daily growth of each organ of the crop obtained by the prediction in a comparable manner; an updating unit that updates the parameters based on information input by a predetermined user having a predetermined reliability or higher among information indicating the cultivation results of the agricultural crops input by the user, and stores the updated parameters in the storage unit; An agricultural support device comprising:

Images