Agricultural support methods

Abstract

To accurately estimate information about agricultural crops.SOLUTION: A computer executes the following process: estimating the growth amount of each leaf and each inflorescence of the crop based on actual measurements or predicted values of a cultivation environment after a specified date, calculating the sum of each growth amount and the ratio of each growth amount to the sum based on each estimated growth amount, and estimating a dry matter distribution amount of each leaf and each inflorescence based on the result of the calculation and the actual measurements or predicted values of the cultivation environment.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an agricultural support method. [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] Furthermore, 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] JP 2002-203002 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, since 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 location and environmental conditions. As a result, when actually cultivating crops, there is a risk that the crops will not grow as expected. 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] The present invention aims to provide an agricultural support method capable of estimating information related to agricultural crops with high accuracy. [Means for solving the problem]

[0007] In one aspect, the agricultural support method is an agricultural support method for estimating information related to agricultural crops, in which a computer executes processes to estimate the growth amount of each leaf and each inflorescence of the crop based on actual measured values ​​or predicted values ​​related to the cultivation environment after a specified date, calculate the sum of each growth amount and the ratio of each growth amount to the sum based on each estimated growth amount, and estimate the dry matter distribution amount of each leaf and each inflorescence based on the result of the calculation and the actual measured values ​​or predicted values ​​related to the cultivation environment. Effect of the Invention

[0008] The agricultural support method of the present invention has an effect of enabling information about agricultural crops to be estimated with high accuracy. [Brief description of the drawings]

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

[0010] An embodiment of the 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 an embodiment. The agricultural system 100 of this embodiment is a system for providing information to farmers (hereinafter referred to as "producers") supporting the selection of cultivars and cultivation management when the producers cultivate fruit vegetables such as tomatoes, strawberries, cucumbers, and peppers. In this embodiment, the case of a producer cultivating strawberries will be described.

[0011] 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 such as a PC (Personal Computer), a tablet terminal, or a smartphone used by a producer. 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 the 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 and the like, and the input unit 195 includes a keyboard, a mouse, a touch panel and 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 strawberry variety selection 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 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 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 acquiring unit 42 as an acquiring unit, a cultivation information acquiring 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 memory unit stored in the memory 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 on 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 (predicted 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 temperature, solar radiation and temperature in a vinyl 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 / solution culture, number of leaves at planting, amount of fertilizer, concentration of culture 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 out parameters corresponding to the variety accepted by the selection acceptance unit 41 from the parameter DB 50, and creates a growth model using the read out parameters and data transmitted from the environmental data acquisition unit 42 and the cultivation information acquisition unit 43. Here, the parameters stored in the parameter DB 50 are, for example, parameters as shown in FIG. 9, and are set for each variety. Then, the simulation unit 44 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 site and cultivation method selected by the producer. As the results of the simulation by the simulation unit 44, the leaf area, the flowering date for each inflorescence, the yield for each inflorescence, the fruit dry matter distribution rate, the amount of photosynthesis, the amount of growth (stem and leaves), the amount of growth (fruit), the amount of nutrient absorption (amount of fertilizer), etc. are obtained. The simulation unit 44 transmits the simulation results to the output unit 45.

[0020] The output unit 45 generates a screen for displaying the simulation results received from the simulation unit 44, and transmits the screen 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 for displaying the simulation results for different cultivation conditions in a comparable state.

[0021] The update unit 46 acquires information on the variety actually cultivated and the 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. 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 inputs the actual cultivation results.

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

[0023] The process of the server 10 is shown in a flowchart in Fig. 4. In the process 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 selects each of the combinations of "Tochiotome Tsukuba", "Tochiotome Morioka", "Koiminori Tsukuba", "Oi C Berry Tsukuba", and "Sachinoka Kurume".

[0024] If the determination in step S10 is positive, 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 spot 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 (for example, planting time, planting density, soil cultivation / nutrient cultivation, number of leaves at planting). When 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 which 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, and obtains a simulation result showing how each variety grows at each cultivation location. The growth model created by the simulation unit 44 and the simulation result will be described in detail later. The simulation unit 44 transmits the simulation result to the output unit 45.

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

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

[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 emergence and elongation, flower emergence and enlargement, nutrient absorption, morphological characteristics (leaf shape, light receiving posture), etc., as shown in Fig. 5, is used. Note that, although a simulation of strawberry is 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 always changing, but in the simulation, it is assumed that the crop size is fixed at midnight, and that it is exposed to temperature and solar radiation in that state from midnight to midnight. If you want to reduce errors due to this assumption, you can do something like shortening the calculation interval of the simulation (the calculation interval in this simulation is one day).

[0033] In this simulation, when performing calculations on the Nth day, the crop size for that day is determined at 0:00 on the Nth day. In other words, in this simulation, the temperature, the state for receiving the amount of solar radiation (relative light receiving rate: value obtained from the leaf area index), and the distribution rate (the ratio of the photosynthetic products generated on that day to each organ, such as leaves, crown, inflorescence, and roots) are fixed from 0:00 to 24:00 on the Nth day. In this simulation, the amount of photosynthesis is calculated at 24:00 on the Nth day based on the temperature, solar radiation, and CO2 concentration on that day (the Nth day), and the crop size changes based on the value calculated by the crop growth calculation. Figure 6 conceptually shows the change in crop size in this simulation. Note that, since the crop size at 0:00 (the crop size on the 0th day) cannot be calculated for the first day of the calculation, the producer or the like sets the value.

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

[0035] In this simulation, crop growth is assumed to be determined primarily by temperature. For example, the growth process of a single leaf is described as follows using accumulated temperatures. The accumulated temperature when growth stops is 1.0, and the accumulated temperature when growth begins is 0, and the growth stage of the leaf 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 value of S(x) between 0:00 and 24:00 on the Nth day (see Figure 7) is defined as the index value of the amount of leaf growth increase per day, [Leaf Increase Index]. Similarly, the relative growth amount of the inflorescence is defined as [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 they are changed 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 in the simulation are the daily average temperature (℃), daily outdoor global solar radiation (MJ / m 2 ), CO2 concentration (ppm), etc. Examples of parameters set by users such as producers are shown in Fig. 9. In this simulation, calculations are performed 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 condition of each organ of the crop (leaves, crown, fruit, roots, inflorescence).

[0041] (2) Simulation method (a) Overview of the simulation This simulation is broadly divided into the processes of "calculating the amount of photosynthesis," "calculating crop growth," "calculating fruit yield," and "amount of nutrient absorption." These calculations are performed on a daily basis. The variables used to calculate the amount of photosynthesis (relative amount of light received, distribution rate) are the values ​​at 0:00 on the calculation day (the day before the calculation day). The relative amount of light received is a variable used to calculate the amount of light received by the crop for photosynthesis from the amount of solar radiation. The distribution rate is the ratio of the source synthesized by the crop on that day to each organ (root, leaf, crown, fruit). The amount of photosynthesis at 24:00 on the calculation day is calculated based on the distribution rate and these values, as well as the temperature and amount of solar radiation on that day. Then, the degree of growth of the crop at 24:00 on the calculation day is calculated based on the amount of photosynthesis. The calculation of the amount of crop growth is divided into (a) calculation of the amount of distribution, (b) calculation of the leaf area, (c) calculation of the number of fruits, (d) calculation of the dry weight of the fruit, and (e) calculation of the distribution rate.

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

[0043] (b) Crop growth process In this simulation, the growth of the crop is determined by the relationship with the previous leaf and the previous inflorescence order (the order of occurrence of leaves and inflorescences. The earlier they occur, the smaller the order), and the accumulated temperature. Figures 10(a) and 10(b) are diagrams conceptually showing the growth process of leaves and inflorescences in this simulation (the numerical values ​​described below are fictitious values ​​assuming 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. Starting from this growth start point, the growth of the leaf ends when the accumulated temperature reaches 450°C. 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 the start of flower bud differentiation of the previous inflorescence. Starting from this flower bud differentiation, the flowering period begins when the accumulated temperature reaches 600°C, and the enlargement of the fruit that constitutes the inflorescence begins. Furthermore, starting from flowering, the growth of the inflorescence stops when the accumulated temperature reaches 600° C. As shown in FIG. 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 is determined by the conditions of this period.

[0044] (c) Calculation of photosynthesis amount Light use efficiency (LUE) (gDW / MJ) is a value that indicates the amount of dry matter produced by 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 [total solar radiation inside the greenhouse] (MJ / m 2 ) is [Outdoor global solar radiation] (MJ / m 2 ) by the house'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 on the previous day. [Light received amount] N = [Relative amount of light received] (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 =[Amount of light received] N [LUE] N …(4)

[0048] The amount of photosynthesis per plant, [Photosynthesis amount] (gDW / plant), is multiplied by [Plant Density] (plant / m), which is the number of plants per unit area (constant). 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 done 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 In the calculation of the amount of photosynthesis, the amount of photosynthesis produced is calculated and distributed to each organ. The amount of distribution is calculated as a value for the entire crop, and is basically determined from the amount of photosynthesis and the distribution rate, but a correction is made by setting [inflorescence potential growth amount] (gDW / plant) as the maximum amount of source that an inflorescence can receive (maximum amount of distribution). [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 one inflorescence can receive per 1°C of air temperature, and [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 amount 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 of photosynthesis amount and allocation amount is (gDW / plant). [Leaf allocation amount (1)], [Crown allocation amount (1)], [Inflorescence allocation amount (1)], and [Root allocation amount (1)] (gDW / plant) are calculated using the following formulas (7A) to (7D), assuming that the amount of photosynthesis from 0 to 24 hours on the day is allocated to each organ according to the allocation rate on 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 allocation (2)], [Crown allocation (2)], and [Root allocation (2)] (gDW / plant) are corrected as follows so that the inflorescence allocation 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] In addition, [Flower cluster allocation amount (2)] is [Flower cluster allocation amount (1)] N <[Flower cluster potential growth amount] N If so, [Inflorescence distribution amount (2) N =[Inflorescence distribution amount (1)] N …(7C1)' In other cases, [Flower bunch distribution amount (2)] N = [Flower cluster potential growth] N …(7C2)' Let us assume that.

[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 Allocation (1)] N +[Inflorescence distribution amount (1)] N +[Root distribution amount (1)] N )-([Leaf distribution amount (2)] N +[Crown Allocation Amount (2)] N +[Inflorescence distribution amount (2)] N +[Root distribution amount (2)] N ) …(8)

[0055] The excess dry matter is reallocated to areas other than the inflorescence, and the amount of each allocated area is 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 the leaf area, calculate the area of ​​each leaf, and 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 formula (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 formula (10B). Note that 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). Here, NL stands for the number of leaves.

[0061]

number

[0062] Using these values, the leaf dry weight, [Leaf DW] (gDW / plant), is calculated 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 the leaf that newly unfolds after planting), and all others 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] In addition, the crown is assumed to increase by a certain percentage when one leaf is added, and the dry weight [Stem DW] (gDW / plant) is calculated in the same manner 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 taken as the first node) and all others 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 with 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] In addition, the total leaf area of ​​the crop [Leaf Area] is defined as [Total Leaf Area(1)](m 2 / plant), [Total Leaf Area(1)] is calculated using the following equation (16).

[0066]

number

[0067] Furthermore, the 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 2 ) is used to calculate the value from the following equation (17). [LAI] N =[Total Leaf Area] N [Plant Density] …(17)

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

[0070] (c) Calculation of fruit set number The number of fruits is calculated for each inflorescence from the amount of photosynthesis (period dry matter production) during a specific period (flower number determination period) starting the day after the flower bud differentiation of the crop begins, and the relationship between the period dry matter production and the number of fruits. Flower bud differentiation occurs in the order of the inflorescence order, and the next inflorescence order will not differentiate until a certain amount of temperature has accumulated after the differentiation of the next inflorescence order (the previous inflorescence).

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

[0072] In this simulation, based on the value of the above [Flower bud differentiation stage accumulated temperature], [Differentiation condition judgment A], which is an index for judging whether the accumulated temperature from the day after flower bud differentiation of the pre-order inflorescence begins, has exceeded a certain value (for example, 600°C), is calculated as follows. Note that the value of 600°C is set at 150°C, which is the accumulated temperature required for one leaf to appear, since in this variety, four leaves usually 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 / strain), 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, becomes 1, it will remain 1 thereafter. That is, [Differentiation Start 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 us assume that.

[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 [Differentiation start index] the day before was 0 and the value on the day was 1. The initial value of [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 initial value is set to a negative value in order 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 Start Index] F,N-1 = 0 and [Differentiation Start Index] F,N If =1, [Flower bud differentiation stage temperature accumulation] F,N =[Accumulated temperature] N …(22A) In other cases, [Flower bud differentiation stage temperature accumulation] F,N =[Accumulated temperature during flower bud differentiation] F,N-1 …(22B) It 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 is an index showing whether or not it is a flower number determination period, 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 Start 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] Meanwhile, 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 = [Photosynthetic amount during the determination period] 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 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](plants / m 2 ) can be used to obtain the following equation (26): [Number of fruits (1)] F,N = [Photosynthetic amount during the determination period] M,N ·[Number of fruits per unit dry matter production during the determined period]·[Plant Density] …(26)

[0080] The number of fruits (pieces / plant) will be 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 us assume that.

[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 is set on the assumption that after flower buds differentiate, they bloom with four leaves, and that an accumulated temperature of 150°C is required per leaf. The flowering stage accumulated temperature is set so that it only becomes effective after the flower bud differentiation stage accumulated temperature has been determined, and its initial value is -1.0. Once the flowering stage accumulated temperature has been set, it is assumed to remain the same value. That is, [Accumulated temperature during flower bud differentiation] 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) It 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 accumulated temperature during the flowering stage 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, [Accumulated temperature during flowering period] 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 us assume that.

[0083] In addition, [Fruits Size Index] (dimensionless) is calculated using the following equation (30). The initial value of 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 of the previous day (midnight of the current day) to midnight of 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 number of fruits per inflorescence is assumed to be 10, the inflorescence is corrected using the following equation (32) to obtain the [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 after [Fruits Growth Index] becomes larger than 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] N-[Fruits Increase Index] F,N / [Total Fruits Increase Index] N …(34B)

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

[0091] Weighting is applied to [Total Fruits Increase Index], [Total Leaf Increase Index], and [Total Stem Increase Index] from experimental data such as during dissection surveys. [Fruit distribution adjustment coefficient], [Leaf distribution adjustment coefficient], and [Crown distribution adjustment coefficient] are set as [α], [β], and [γ]. From these, 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 are not harvested in one day within the inflorescence, but rather harvested gradually. The [Harvest Start Index] (dimensionless), which indicates that harvesting is possible, is set to 1 from the day after the [Fruits Increase Index] first reaches 1.0 or above, and is zero before that. The first day when the [Harvest Start Index] reaches 1 is 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) It becomes.

[0094] Here, the total harvest volume per fruit cluster is [Fruits DW] (gDW / plant) on the start of harvest. Basically, [Fruits DW] does not increase after [Fruits Growth Index] becomes larger than 1, so it is the same from the start of harvest onwards. Each fruit is harvested over a period in which the accumulated temperature reaches 60°C, and [Harvested Fruit Temperature DW] (gDW / plant·°C), which is the dry weight of fruit harvested per 1°C of air temperature, is calculated as follows. The initial value of [Harvested Fruit Temperature DW] is -1.0, and once a valid value is set, it remains the same value. 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:

[0095] The dry weight of harvestable fruits before harvesting on the calculation date is defined as [Fruits unHarvest] (gDW / plant), and [Fruits unHarvest] is calculated as follows. Note that [Fruits unHarvest] is given the [Fruits DW] of the previous day on the start date of harvesting, and thereafter decreases by the amount harvested. 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) It becomes.

[0096] After the start of the harvest period, if there are fruits available for harvest, the harvested fruit dry matter weight [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] In addition, if the total [Fruits HARVEST] of all inflorescences is [Fruits Harvested Dry Weight] (gDW / plant), [Fruits Harvested 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 the [Fruit harvested live weight] by the [Number of plants in the field] (plants), the yield for the entire field, [Fruit harvested live weight in the field] (kg), can be calculated using the following equation (43). [Field harvested live weight of fruit] 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 executes a growth simulation for each combination of variety, cultivation location, and cultivation information selected by the producer using the growth model. Then, the simulation result (values ​​obtained by the simulation) for each combination is transmitted to the output unit 45. Note that the simulation unit 44 can also perform simulations for fruit vegetables other than strawberries, such as tomatoes, strawberries, cucumbers, and peppers, by using parameters according to the item and variety.

[0102] (5) Nutrient absorption calculation The amount of nutrient absorbed is calculated by multiplying the increase in dry matter 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, [Leaf ΔDW] M,N is the increase in dry matter in the leaves, [Leaf N%] M,N is the nutrient content of the leaf. The other equations (44B) to (44D) are similar.

[0104] Here, 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 formula: 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] In addition, the amount of nutrients absorbed by leaves, crowns, inflorescences, and roots is expressed by the following formula.

[0106]

number

[0107] Furthermore, the nutrient uptake 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 "nutrient absorption amount" estimated from the increase in dry matter weight per plant. This can be multiplied by the planting density to obtain the "nutrient absorption amount per area." Furthermore, the "nutrient absorption amount" can be divided by the [fertilizer use efficiency] to obtain the "fertilizer application amount."

[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 for displaying the simulation results. For example, the output unit 45 generates a screen for displaying information as shown in FIG. 11 as the simulation results. In this case, the screen in FIG. 11 is displayed on the display unit 193 of the user terminal 70, so that the producer can confirm which variety, which cultivation location, how the variety will grow, and how much yield can be obtained. In addition, the simulation results when multiple items are cultivated under different cultivation conditions are displayed side by side, so that the producer can compare what kind of cultivation results can be obtained when the variety and cultivation conditions are changed.

[0110] In addition, the output unit 45 can generate a screen as shown in FIG. 12, which shows the shipping amount by inflorescence when the variety selected by the producer is cultivated at the selected cultivation site, and output it to the user terminal 70. The producer can check the transition of the harvest amount in the terminal inflorescence, the second inflorescence, the third inflorescence, etc. by referring to the screen of FIG. 12. In FIG. 12, the harvest amount of each inflorescence is displayed in a separate graph, but each graph may be displayed together in one graph. In this case, the bar graph showing the harvest amount of each inflorescence may be displayed in a different color, etc., for easy understanding. Furthermore, the output unit 45 may display the transition of the total yield in a graph, for example, as shown in FIG. 13(a), or may display the transition of the LAI in a graph, as shown in FIG. 13(b). In addition, other growth information (for example, leaf area, flowering date by inflorescence, amount of photosynthesis, growth amount (crown, leaf, fruit, fruit load), amount of nutrient absorption (amount of fertilizer), etc.) may be displayed numerically or graphically.

[0111] In addition, the output unit 45 may display the results of a simulation 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, for example, FIG. 14.

[0112] As described above, the output unit 45 may display the simulation results for each combination of variety, cultivation location, and cultivation information in a comparative manner as shown in FIG. 11, or may display the simulation results when a certain variety is cultivated at a certain cultivation location as shown in FIG. 12 to FIG. 13(b). Also, as shown in FIG. 14, the simulation results when different varieties are cultivated at the same cultivation location may be displayed in a comparative manner. Furthermore, the simulation results when a certain variety is cultivated at different cultivation locations may be displayed in a comparative manner. In any case, it is possible to appropriately express the characteristics of the variety compared to a conventional catalog in which the characteristics of the variety are expressed by words, images, average values, etc. Therefore, producers can appropriately select the variety and cultivation location by checking the simulation results. In addition, since it is possible to grasp how the agricultural crops will grow in the future, it is possible to appropriately perform cultivation management (securing workers, procuring materials, etc.).

[0113] (Regarding the processing of the update unit 46) When an actual measurement value (actual cultivation result) such as a change in yield or a change in LAI is input by the producer, the update unit 46 compares the actual measurement value with the corresponding simulation result, and adjusts and updates various parameters so that the simulation result approaches the actual measurement value. In this way, the parameters are appropriately updated based on the actual measurement value, so that appropriate simulation results can be obtained in the next and subsequent simulations.

[0114] If the parameters are updated based on the 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 the 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 according to a flowchart as shown in FIG.

[0115] In the process of FIG. 15, first, in step S30, the update unit 46 waits until the producer inputs the actual cultivation result (actual measurement value) via the user terminal 70. Then, when the actual cultivation result is input, the process proceeds to step S32, where the update unit 46 judges whether the input is from a predetermined producer (a producer with high reliability). If the judgment in this step S32 is negative, the entire process of FIG. 15 ends as it is, but if the judgment is positive, the process proceeds to step S34. When the process proceeds to step S34, the update unit 46 updates the parameters so that the simulation result approaches the actual cultivation result, stores the 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 certain producer, the updated parameters may be managed as parameters dedicated 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 up 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 prediction regarding the growth of each variety from the growth model for each variety.

[0119] As described above in detail, according to this embodiment, the simulation unit 44 reads out parameters indicating the characteristics of each variety of the agricultural crop from the parameter DB 50, and obtains environmental data corresponding to the cultivation site 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 executes a simulation using the created growth model. Then, the output unit 45 outputs the simulation result as information supporting variety selection and cultivation management. In this way, in this embodiment, the result of a simulation on the growth of the agricultural crop using a growth model created for each variety and each cultivation site is displayed as information supporting variety selection and cultivation management, so that the characteristics of the variety can be properly expressed compared to a conventional catalog in which the characteristics of the variety are expressed by words, images, average values, etc. Therefore, the producer can properly select the variety and the cultivation site, and can grasp how the variety will grow in the future, so that the producer can properly perform cultivation management.

[0120] In the present embodiment, the update unit 46 updates the parameters based on the actual cultivation results (yield, etc.) input by the producer, and updates 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] 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 each combination of multiple varieties, cultivation locations, and cultivation information, and determine which variety should be cultivated and how.

[0123] In the above embodiment, the server 10 includes the update unit 46, but the present invention is not limited to this. That is, the server 10 does not have to include 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 that case, a program is provided that describes the processing contents of the functions that the processing device should have. The above processing functions are realized on the computer by executing the program on the computer. The program that describes the processing contents can be recorded on a computer-readable storage medium (excluding carrier waves).

[0126] When a program is distributed, it is sold in the form of a portable storage medium on which the program is recorded, such as a DVD (Digital Versatile Disc), a CD-ROM (Compact Disc Read Only Memory), etc. The program can also be stored in a 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. 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 received program 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 embodiment and can be modified in various ways without departing from the scope 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 Agriculture System

Claims

1. An agricultural support method for estimating information about a crop, comprising: Estimating the growth amount of each leaf and each inflorescence of the crop based on actual measurements or predicted values ​​regarding the cultivation environment after a predetermined date; Based on the estimated growth amounts, a sum of the growth amounts and a ratio of each growth amount to the sum are calculated, and a dry matter distribution amount of each leaf and each inflorescence is estimated based on the result of the calculation and an actual measurement value or a predicted value regarding the cultivation environment. An agricultural support method, characterized in that processing is executed by a computer.

2. Acquire information on the variety of the crop; The parameters indicating the characteristics of the variety are read from a storage unit; creating a growth model according to the variety based on the parameters read from the storage unit and actual measured values ​​or predicted values ​​regarding the cultivation environment, and predicting the growth of the agricultural crop using the created growth model according to the variety and the dry matter distribution amount of each of the leaves and each of the inflorescences.

2. The agricultural support method according to claim 1, wherein the processing is executed by a computer.

3. In the process of predicting growth, Calculating the weight of each leaf based on the dry matter distribution amount of each leaf, and calculating the leaf area of ​​each leaf based on the calculated weight of each leaf; predicting the growth of the crop by inputting the calculated leaf area of ​​each leaf into a growth model corresponding to the variety; 3. The agricultural support method according to claim 2, wherein the processing is executed by the computer.

Images