PROGRAM, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING APPARATUS

Abstract

To evaluate an effect of biostimulants to a farm field using an objective barometer.SOLUTION: A program causes an information processing device to execute: obtaining first data including the type of a farm field, the area thereof, and the kind of plant cultivated at the farm field, second data including the type of a material that has an action to enhance the tolerance against non-biological stress, the applied amount thereof, the kind of a fertilizer and the applied amount thereof, and third data including the harvesting day of the plant; inputting the first to third data to a first calculation formula to calculate the carbon accumulating amount of soils, and calculating the carbon accumulating amount of the farm field; and / or inputting the first to third data to a second calculation formula to calculate a greenhouse effect gas discharging amount, and calculating the greenhouse effect gas discharging amount from the farm field.SELECTED DRAWING: Figure 12

Description

[Technical field]

[0001] The present invention relates to a program, an information processing method, and an information processing device. [Background technology]

[0002] Conventionally, a system for evaluating carbon storage agriculture that aims to visualize carbon storage agriculture is known (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2022-153012 Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, there have been attempts to apply biostimulants, which are materials that have the effect of increasing the resistance of plants to abiotic stress, to plants to promote their growth and improve the yield or quality of agricultural crops. By applying biostimulants, it is possible to reduce the amount of fertilizer used.

[0005] Conventional techniques calculate either or both of the carbon storage and greenhouse gas emission reductions in agricultural land resulting from the application of soil improvement materials containing biochar, but do not evaluate the impact of biostimulants on agricultural fields.

[0006] Therefore, an object of the technology disclosed herein is to provide a new mechanism that makes it possible to evaluate the impact of biostimulants on farm fields using objective indices. [Means for solving the problem]

[0007] A program according to one embodiment of the present disclosure causes an information processing device to acquire first data including the type and area of ​​a field and the type of plant cultivated in the field, second data including the type and application amount of a material that has the effect of increasing resistance to abiotic stress and the type and application amount of fertilizer applied, and third data including the harvest date of the plants, inputting the first to third data into a first calculation formula that calculates carbon storage in the soil to calculate the carbon storage amount of the field, and / or inputting the first to third data into a second calculation formula that calculates greenhouse gas emissions to calculate the greenhouse gas emissions of the field. Effect of the Invention

[0008] According to the present disclosure, the impact of a biostimulant on a farm field can be evaluated using an objective index. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an overview of an information processing system according to an embodiment of the present disclosure. [Diagram 2] FIG. 1 is a diagram illustrating an example of a configuration of an information processing system according to an embodiment of the present disclosure. [Diagram 3] FIG. 1 is a diagram illustrating an example of a configuration of an information processing device according to an embodiment of the present disclosure. [Figure 4] FIG. 1 is a diagram illustrating an example of an information processing device according to an embodiment of the present disclosure. [Diagram 5] FIG. 1 is a diagram illustrating an example of parameters (part 1) according to an embodiment of the present disclosure. [Figure 6] FIG. 13 is a diagram illustrating an example of parameters (part 2) according to an embodiment of the present disclosure. [Figure 7] FIG. 13 is a diagram illustrating an example of input parameters according to an embodiment of the present disclosure. [Figure 8] FIG. 13 is a diagram showing a calculation process when input parameters are input according to an embodiment of the present disclosure. [Figure 9] FIG. 1 is a diagram showing an example of a cultivation period and a timing for acquiring data according to an embodiment of the present disclosure. [Figure 10] FIG. 1 is a diagram illustrating a verification example 1 according to an embodiment of the present disclosure. [Figure 11] FIG. 11 is a diagram illustrating a verification example 2 according to an embodiment of the present disclosure. [Figure 12] 11 is a flowchart illustrating an example of an evaluation process of an information processing device according to an embodiment of the present disclosure. [Figure 13] 1 is a flowchart illustrating an example of a process in fertilization design according to an embodiment of the present disclosure. [Figure 14] 11 is a flowchart illustrating an example of a verification process according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Preferred embodiments of the disclosed technology will be described with reference to the accompanying drawings. In each drawing, the same reference numerals denote the same or similar configurations.

[0011] [Embodiment] <System> First, the material applied to the field in the technology of the present disclosure will be described. This material is an agricultural material also called biostimulant (hereinafter, also referred to as "BS"), which is a biostimulant containing various substances and microorganisms that bring about better physiological conditions in plants and soil. This material has the potential to have a positive effect on plants in terms of plant health, stress resistance, yield and quality, post-harvest condition and storage, etc., by utilizing the natural power inherent to plants and their surrounding environment.

[0012] BS are usually made from natural ingredients, extracts from plants and animals, or metabolic products of microbial origin. BS may be these alone or in combination. Also, unlike pesticides, BS contain materials that have the effect of mitigating abiotic stress.

[0013] The effects of BS include, for example, suppression of active oxygen, activation of photosynthesis, promotion of flowering and fruiting, control of transpiration, regulation of osmotic pressure, improvement of the root zone environment, increase in root volume and improvement of root activity, etc., but it does not have all the effects.

[0014] Next, the system of the present disclosure will be described with reference to Figures 1 and 2. Figure 1 is a diagram for explaining an overview of an information processing system 1 according to an embodiment of the present disclosure. In the example shown in Figure 1, ground data A input by a plant producer for a field to which a BS is applied is transmitted from an information processing device 20 used by the producer to an information processing device (server) 10 used by a manager of the information processing system 1. In addition, ground data B acquired from a sensor 40 installed in the field is transmitted to the information processing device (server) 10.

[0015] The ground data A is information related to cultivation, and may include, for example, information related to cultivation (production) in the field, information related to fertilizer and BS, and information related to the harvesting of plants. The ground data B may include information related to the soil and surrounding environment of the field, and information related to the quality of the plants.

[0016] As described later, in order to estimate the carbon storage amount and the like of the farm field, the information processing device 10 may acquire satellite data from each satellite 50. In addition, the information processing device 10 may acquire the data by inputting the analysis values ​​obtained by performing soil analysis before or after the production of plants using soil collected from the farm field, or may acquire the data from the information processing device 30, which may be an analysis device.

[0017] The information processing device 10 objectively evaluates the impact on the field when BS is applied using each acquired data. For example, the information processing device 10 calculates the amount of carbon storage and greenhouse gas emissions by acquiring data on the field, plants, fertilizer, etc., performs fertilization design, provisionally calculates the price of carbon credits, and verifies the price of carbon credits from actual values ​​measured by cultivation data and soil analysis.

[0018] Fig. 2 is a diagram showing an example of the configuration of an information processing system 1 according to an embodiment of the present disclosure. As shown in Fig. 2, the information processing system 1 includes an information processing device 10, information processing devices 20A and 20B (hereinafter also referred to as "information processing devices 20") used by plant producers and the like, information processing devices 30A and 30B (hereinafter also referred to as "information processing devices 30") that analyze soil components in the field and input analytical values ​​after the analysis, sensors 40 installed in the field, and satellites 50 that transmit satellite data, and the devices in the information processing system 1 can transmit and receive data to and from each other via a network N.

[0019] For example, the information processing device 10 shown in Fig. 2 is, for example, a personal computer, a server device, etc., and the information processing devices 20 and 30 are, for example, a personal computer, a mobile terminal such as a smartphone, a tablet terminal, etc. Each information processing device may be represented as an n-th information processing device (n = 1, 2, 3, ...) and each may be distinguished from the other. The information processing device 30 may be an analysis device that analyzes soil components.

[0020] <Configuration> Fig. 3 is a diagram showing an example of a configuration of the information processing device 10 according to an embodiment of the present disclosure. Fig. 4 is a diagram showing an example of a configuration of the information processing device 20 according to an embodiment of the present disclosure. The processing of each device will be described below.

[0021] The information processing device 10 includes one or more processors (CPU: Central Processing Unit) 110, one or more network communication interfaces 120, a memory 130, a user interface 150, and one or more communication buses 170 for interconnecting these components.

[0022] The user interface 150 includes a display and an input device (such as a keyboard and / or a mouse, or some other pointing device), but does not necessarily have to be provided in the information processing device 10, and if provided, may be connected as an external device.

[0023] Memory 130 may be, for example, a high-speed random access memory (primary memory), such as DRAM, SRAM, or other random access solid-state memory, or may be a non-volatile memory (secondary memory), such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state memory devices.

[0024] Furthermore, the memory 130 may be a non-transitory computer-readable recording medium that stores a program, etc. Furthermore, the memory 130 may be either a main storage device (memory) or an auxiliary storage device (storage), or may include both.

[0025] As another example, memory 130 may be one or more storage devices located remotely from processor 110. In one embodiment, memory 130 stores programs, modules and data structures, or a subset thereof, that are executed by processor 110.

[0026] The memory 130 stores data used by the information processing system 1. For example, the memory 130 stores information / data such as basic cultivation information on fields and plants (hereinafter also referred to as "first data"), cultivation information on materials (hereinafter also referred to as "second data"), harvest information including plant yields (hereinafter also referred to as "third data"), analysis results of soil components, and satellite data.

[0027] The processor 110 executes a program stored in the memory 130, for example, by executing each instruction included in the program, thereby constituting a control unit 111 that controls the processing of the present disclosure.

[0028] The control unit 111 controls the processing of the acquisition unit 112, the calculation unit 113, the setting unit 114, the verification unit 115, the estimation unit 116, the design unit 117, and the output unit 118 in order to execute the processing of the present disclosure.

[0029] The acquisition unit 112 acquires basic cultivation information (first data) including the type and area of ​​the field and the type of plant cultivated in the field, growth information (second data) including the type and application amount of materials that have the effect of increasing resistance to abiotic stress and the type and application amount of fertilizer applied, and harvest information (third data) including the harvest date of the plant.

[0030] For example, the acquisition unit 112 acquires basic cultivation information input by a producer who produces plants in a field using the information processing device 20 from the information processing device 20. The information processing device 20 may install an application linked to the present system and transmit the basic cultivation information to the information processing device 10 through the application.

[0031] The basic cultivation information may include data such as the type of plant cultivated in the field, the cultivation area, the land use classification (type), the location (location information such as latitude and longitude), the air temperature, the soil temperature, the soil classification, etc. The acquisition unit 112 may estimate the air temperature, the soil temperature, and the soil classification from the location, or may acquire them from another database.

[0032] The acquisition unit 112 may also acquire cultivation information set by input or the like of a producer from the information processing device 20. The cultivation information may include data such as the product name, type, amount used, and application date of a pesticide or fertilizer, and data such as the product name, type, amount used, and application date of a BS.

[0033] The acquisition unit 112 may also acquire harvest information set by input or the like by the producer from the information processing device 20. The harvest information includes data such as the yield, production volume, and harvest date of the plant. The plant includes crops cultivated in agricultural land, flowers, and other perishables.

[0034] The calculation unit 113 calculates the carbon storage amount of the field by inputting the first to third data into a first calculation formula that calculates the carbon storage amount in the soil, and / or calculates the greenhouse gas emission amount of the field by inputting the first to third data into a second calculation formula that calculates the greenhouse gas emission amount.

[0035] For example, the calculation unit 113 may calculate the carbon stock amount and / or the greenhouse gas emission amount by inputting each data into a predetermined calculation formula using the Rothamsted Carbon Model for the carbon content.

[0036] Carbon storage = SOC amount (soil organic carbon amount) = ΣSOC(t) = Σ t Y × (ΔPd + ΔPr) Equation (1) ΔPr=Pr(t-1)-Pr(t) (Pr(t-1)>Pr(t) because the resolution decreases) =Pr(t-1)×(1-e‐ mwck Δ t )...Equation (2) ΔPd=Pd(t-1)-Pd(t) (decomposition decreases, so Pd(t-1)>Pd(t)) =Pd(t-1)×(1-e mwck Δ t )...Equation (3) Carbon GHG (Green House Gas) emissions = ΣCO2(t) = Σ t X×(ΔPd+ΔPr) Equation (4) Nitrogen GHG emissions = ΣN 2 O(t)=Σ t ΔN...Equation (5) ΔN=N(t-1)-N(t) (N(t-1)>N(t) because the resolution decreases) =N(t-1)×(1-e‐ mwck Δ t )...Equation (6) GHG emissions = GHG emissions of carbon + (GHG emissions of nitrogen × GWP) Equation (7) For example, formula (1) is the first calculation formula, and formulas (4) to (7) are the second calculation formulas.

[0037] Each coefficient in equations (1) to (7) Pd / P+Pr / P=1: Set d=Pd / P and r=Pr / P from the land use classification (first data) Pd = d × P, Pr = r × P t: time (third data) P: Organic matter, residue amount (second or third data) Pd: The amount of decomposable plant DPM in P d=Pd / P Pr: The amount of decomposable plant RPM in P r=Pr / P X: Of the decomposition amount, CO 2 Quantity Percentage Y: The ratio of carbon storage to the amount of decomposition M: soil temperature coefficient W: soil moisture coefficient C: Coefficient of soil coverage K: Decomposition rate coefficient N: Nitrogen content of organic matter and chemical fertilizers (second data) GWP:N 2 Global Warming Potential of O Among the above coefficients, those that do not depend on the input value may be set in advance. For example, the calculation unit 113 can obtain N from a database of a public institution (e.g., https: / / soilco2.rad.naro.go.jp / q12) and GWP from a database of a public institution (e.g., https: / / www.env.go.jp / policy / local_keikaku / data / guideline.pdf).

[0038] For example, DPM (easily degradable plant matter) and RPM (hardly degradable plant matter) differ depending on the land use classification. For example, when the classification is crops and pasture grass, DPM is 59% and RPM is 41%, when the classification is wild grass and shrubs, DPM is 40% and RPM is 60%, when the classification is trees, DPM is 20% and RPM is 40%, and when the classification is compost, DPM is 49% and RPM is 49% (HUM 2%).

[0039] For example, the calculation unit 113 sets parameters P of organic matter and residue amount from the applied BS, the cultivated crop, etc., and calculates Pd and Pr from the parameter P. In addition, the calculation unit 113 calculates the desired time from the input of organic matter (e.g., BS, etc.) to the field for time t. For example, if the carbon storage amount and the GHG emission amount of carbon in the last month are known, Δt=this month-last month, and t is in months. In addition, the reason for using the harvest date as the third data is that the estimated value calculated before the harvest is compared with the actual value obtained after the harvest (see, for example, FIG. 10). For example, in the cultivation of a certain plant, the first harvest is sown in March and harvested in June, and the second harvest is sown in July and harvested in November. In this case, when calculating the carbon storage amount in May, the calculation unit 113 calculates Δt=June (harvest date)-May to calculate the estimated value (A) of the carbon storage amount as of June. In addition, the calculation unit 113 may obtain a measurement value (B) after the harvest in June, when a soil sample was collected in June and the carbon storage amount was measured using an apparatus, and compare the estimated value A with the measurement value B.

[0040] By the above processing, the impact of BS on a farm field can be evaluated using objective indices. For example, carbon stocks and GHG emissions can be calculated and used as one of the objective indices that express the impact of BS on a farm field.

[0041] The calculation unit 113 may also calculate the amount of GHG emissions using the type of fertilizer and the amount of fertilizer applied when BS is not applied, subtract the amount of GHG emissions when BS is applied from the amount of GHG emissions when BS is not applied, and calculate this as the amount of GHG emission reduction. This makes it possible to present how much GHG emissions can be reduced depending on whether or not BS is applied.

[0042] Moreover, the calculation unit 113 can calculate the GHG emission amount using the following calculation formula other than the above-mentioned formulas (4) to (7). Carbon GHG emissions = C × Ec Equation (8) Nitrogen GHG emissions = N × En Equation (9) GHG emissions = GHG emissions of carbon + (GHG emissions of nitrogen × GWP) Equation (7) C: Carbon content of organic matter Ec: Organic CO 2 emissions N: Nitrogen content of organic matter and chemical fertilizers En:N from chemical fertilizers 2 O emission factor GWP:N 2 Global Warming Potential of O Ec and En can be obtained from public institution databases (for example, https: / / ghg-santeikohyo.env.go.jp / files / calc / itiran_2020_rev.pdf).

[0043] Furthermore, the setting unit 114 sets the amount of fertilizer included in the second data from the type and amount of application of the material included in the second data based on the correspondence information that corresponds the type and amount of application of the predetermined material to the reduction amount of the predetermined fertilizer. For example, correspondence information that associates the amount of fertilizer application of BS, a fertilizer that can be reduced, and the reduction amount or the amount of fertilizer application after the reduction for each type of BS material based on the results of a previous experiment is stored in the memory 130. The setting unit 114 may refer to the correspondence information based on the type and amount of fertilizer application of BS acquired by the acquisition unit 112 and set the amount of fertilizer application after the reduction. For example, the correspondence information corresponds to the fact that when applying BS for red peppers, the amount of conventional fertilizer can be reduced by a predetermined percentage.

[0044] In addition, the amount of fertilizer reduction related to the above-mentioned correspondence information may be based on the information on soil preparation shown in Fig. 5 described later. For example, even if the same amount of BS is applied, the amount of fertilizer reduction differs between an area where excessive fertilizer has been applied from the beginning and an area where fertilizer reduction measures have been taken to the limit. The information on soil preparation may be included in the first data.

[0045] By using the above process, it is possible to easily determine the amount of fertilizer reduction required when using BS, and it is also possible to more simply calculate carbon storage and GHG emissions.

[0046] The calculation unit 113 may also calculate the price of carbon credits based on the amount of carbon storage or the amount of greenhouse gas emissions. For example, the calculation unit 113 can calculate the amount of GHG emission reduction from the effect of the application of BS on the amount of carbon storage or the amount of fertilizer reduction, and may provisionally calculate the price of carbon credits using this amount of GHG emission reduction. The calculation formula may be, for example, a known formula established by the J-Credit Scheme or a government agency, to calculate the price of carbon credits from the amount of GHG emission reduction.

[0047] Through the above process, it becomes possible to calculate the amount of GHG emissions that can be reduced by applying BS as a carbon credit price, and present the benefits of using BS to producers, etc.

[0048] In addition, the verification unit 115 compares the amount of carbon storage obtained by analyzing the soil components of the field after the plants have been harvested with the calculated amount of carbon storage, and / or compares the amount of greenhouse gas emissions obtained by a sensor 40 installed in the field after the plants have been harvested with the calculated amount of greenhouse gas emissions.

[0049] For example, the verification unit 115 acquires from the information processing device 30 the amount of carbon stock determined by analyzing the soil components of the farm field after the plant is harvested, and compares the analyzed amount of carbon stock with the amount of carbon stock calculated by the calculation unit 113. Furthermore, the verification unit 115 may determine whether or not the difference between the amounts of carbon stock is within a predetermined range as a result of the comparison.

[0050] The verification unit 115 also detects a sensor 40 (e.g., CO 2 The verification unit 115 acquires greenhouse gases detected after the plants are harvested using a greenhouse gas sensor (sensor) and compares the acquired greenhouse gas emissions with the GHG emissions calculated by the calculation unit 113. Furthermore, the verification unit 115 may determine whether or not the respective difference values ​​are within a predetermined range as a result of the comparison of the GHG emissions.

[0051] The verification unit 115 may verify the validity of the producer's data and the suitability of cultivation based on the comparison result of the carbon storage amount and / or the greenhouse gas emission amount, and may decide whether to approve the price of the carbon credit. For example, if the comparison result of the carbon storage amount and / or the GHG emission amount shows that both difference values ​​are within a predetermined range, the verification unit 115 may determine that the producer has properly input or set the data and properly cultivated the plant, and may approve the provisionally calculated price of the carbon credit as being appropriate.

[0052] Through the above processing, the verification unit 115 is able to verify the validity of the producer's data and the suitability of cultivation, and use objective data to decide whether or not to approve the carbon credit price provisionally calculated before harvest.

[0053] The verification unit 115 may also compare target values ​​of soil components of the field based on the second data with actual measured values ​​of soil components of the field after harvesting of the plants. For example, the verification unit 115 may compare target values ​​of soil components calculated from data of a field before cultivation where BS is applied and fertilizer is spread with actual measured values ​​obtained by analyzing soil components after cultivation. The soil components after cultivation are analyzed or input in the information processing device 30, and for example, N (nitrogen), P (phosphorus), K (potassium), bacteria, pH, etc. are obtained.

[0054] The verification unit 115 may determine whether to approve the price of carbon credits based on the comparison result of the soil components. For example, if the difference between the target value and the actual measurement value is within a predetermined range, the verification unit 115 may approve the provisionally calculated price of carbon credits as appropriate.

[0055] Through the above process, it becomes possible to use objective data to determine whether the provisionally calculated carbon credit price is appropriate based on the target values ​​and actual measured values ​​of soil components in the field where crops are cultivated using BS.

[0056] Next, a carbon stock estimation process of the disclosed system will be described. For example, even if the sensor 40 cannot be installed in the field, the carbon stock can be estimated from the similarity of soil components based on satellite data, climate, etc.

[0057] Regarding the estimation of the carbon stock amount, the acquisition unit 112 acquires the position information of a specific farm field. For example, the acquisition unit 112 acquires the position information such as the latitude and longitude of the farm field to be estimated.

[0058] The estimation unit 116 estimates the climate of the specific field from the location information of the specific field. For example, the estimation unit 116 refers to public information from the Japan Meteorological Agency and estimates the monthly precipitation amount of the specific field.

[0059] The estimation unit 116 also acquires satellite data for the specific field from the satellite 50. The satellite data includes, for example, a wavelength range and reflected light. The estimation unit 116 may estimate the soil components of the specific field from the soil components of other fields based on similarity between the wavelength range and reflected light included in the satellite data acquired in the specific field and the wavelength range and reflected light included in the satellite data acquired in other fields in which the sensor 40 is installed. The estimated soil components may include soil chemical properties such as N, P, K, and carbon, soil physical properties such as moisture content, pH, EC (electrical conductivity), air permeability, and hardness, and soil biological properties such as fungus species and fungus content rate.

[0060] The estimation unit 116 may estimate the carbon stock amount of a given field based on the estimated climate and soil components. For example, the estimation unit 116 instructs the calculation unit 113 to calculate the carbon stock amount and the GHG emission amount using parameters based on the estimated climate and soil components. The estimation unit 116 may obtain the carbon stock amount and the GHG emission amount calculated by the calculation unit 113 as the estimated carbon stock amount and the GHG emission amount.

[0061] Through the above process, even in a farm field where the sensor 40 is not installed, it is possible to estimate the amount of carbon stock and GHG emissions by using the soil components of the farm field where the sensor 40 is installed.

[0062] Next, the fertilization design of the disclosed system will be explained. In the fertilization design, the soil components before fertilization are acquired, and target values ​​are set for how the acquired soil components change when BS is applied and when it is not applied. Next, fertilization design is performed, such as how much BS should be used, based on the difference between these target values.

[0063] Regarding fertilization design, the acquisition unit 112 acquires evaluation values ​​of soil components of the field. For example, the acquisition unit 112 acquires evaluation values ​​of the soil components from the information processing device 30 or the sensor 40 that analyzed the soil components of the field before fertilization. The evaluation values ​​may include, for example, N, P, K, carbon, and other elements included in the soil chemistry, water content, pH, EC, air permeability, hardness, and the like included in the soil physical properties, and fungus species and fungus content rate included in the soil biological properties.

[0064] Based on the acquired evaluation value, the design unit 117 sets a first target value of the soil component when BS is not applied and a second target value of the soil component when BS is applied after harvesting of the plant cultivated in the field. Next, the design unit 117 performs fertilization design based on the difference between the first target value, the second target value, and each actual measurement value.

[0065] For example, the design unit 117 performs fertilization design as follows. (No BS) Fertilization amount F=Σ X F(x)=T(x)-A(x)...Equation (10) (BS also available) Fertilization amount F=Σ X F BS (x)=T BS (x)-A BS (x)...Equation (11) x: type of element A(x): Actual amount of element x contained in soil T(x): The target amount of element x to be contained in the soil (first target value) F(x): Fertilizer amount of element x A BS (x): Actual amount of element x contained in soil when BS was applied TBS (x): Target amount of element x to be contained in soil when applying BS (second target value) F BS (x): Fertilizer application amount of element x when applying BS

[0066] Here, since applying BS can reduce the amount of fertilizer, F BS <F holds. The design department 117 calculates the differences between the first target value and the second target value and their respective measured values as follows. (Without combined use of BS) Difference between target value and measured value = T(x) t-1 -A(x) t <ΔF(x) ··· Equation (12) (With combined use of BS) Difference between target value and measured value = T BS (x) t-1 -A BS (x) t <ΔF BS (x) ··· Equation (13) T: Time x: Type of element A(x): Measured amount of element x contained in soil T(x): Target amount of element x to be contained in soil ΔF(x): Tolerance A BS (x): Measured amount of element x contained in soil when applying BS T BS (x): Target amount of element x to be contained in soil when applying BS ΔF BS (x): Tolerance when applying BS

[0067] The design department 117 may determine the fertilizer application amount to be used from the set target value so that the difference between the target value set before fertilization and the measured value obtained by analyzing the soil components after fertilization is within the tolerance. Also, the design department 117 can present to the producer how much the fertilizer application amount differs depending on whether BS is used in combination or not. For example, the design department 117 may control to transmit the fertilizer application amounts in each case of whether BS is used in combination or not to the information processing device 20 or 30 used by the producer.

[0068] Through the above processing, the disclosed system makes it possible to carry out fertilization planning based on whether or not BS is used in combination, enabling producers to understand the difference in the amount of fertilizer to be applied based on whether or not BS is used in combination, and facilitating the decision of whether or not to use BS.

[0069] The output unit 118 outputs values ​​calculated, set, designed, etc. by the control unit 111 to an external device. For example, the output unit 118 may transmit the amount of carbon storage and / or the amount of greenhouse gas emissions calculated by the calculation unit 113 to an information processing device 20 used by the producer. The output unit 118 may also transmit the price of carbon credits calculated by the calculation unit 113 to the information processing device 20. The output unit 118 may also transmit the amount of fertilizer application designed by the design unit 117 to the information processing device 20.

[0070] 4 is a diagram illustrating an example of an information processing device 20 according to an embodiment of the present disclosure. The information processing device 20 includes one or more processors (e.g., CPUs) 210, one or more network communication interfaces 220, a memory 230, a user interface 250, and one or more communication buses 270 for interconnecting these components.

[0071] The user interface 250 includes a display and an input device (such as a keyboard and / or a mouse or some other pointing device).

[0072] Memory 230 is, for example, a high-speed random access memory (main storage device) such as DRAM, SRAM, or other random access solid-state storage device. Memory 230 may also be a non-volatile memory (secondary storage device) such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. Memory 230 may also be a non-transitory computer-readable recording medium that stores programs and the like. Memory 230 may also be either a main storage device (memory) or a secondary storage device (storage), or may include both.

[0073] The memory 230 stores data and programs used by the information processing system 1. For example, the memory 230 stores application programs for mobile terminals in the information processing system 1.

[0074] The processor 210 executes a program stored in the memory 230 to configure a control unit 212 that controls processing related to BS evaluation and the like on the client side. For example, the control unit 212 includes a web browser or an application related to BS evaluation and the like.

[0075] The web browser enables browsing of web pages of a platform provided by the information processing device 10. The web browser appropriately displays and transitions between web pages, provides information, and transmits and receives data. For example, the web browser uses a web page to transmit information set or input by a user to the information processing device 10. The transmitted information is, for example, basic cultivation information, growth information, harvest information, and other information.

[0076] The control unit 212 may also enable execution of functions provided by the platform of the disclosed system by executing an installed client application. The control unit 212 has an acquisition unit 213, a display control unit 214, and an output unit 215 to execute the processing of the present disclosure on the client side.

[0077] The acquisition unit 213 acquires data set or input by the user using the user interface 250, such as basic cultivation information, growth information, and harvest information.

[0078] The display control unit 214 controls the display on the screen of, for example, an input screen for basic cultivation information, growth information, harvest information, etc., the amount of carbon storage, GHG emission, and carbon credit price calculated by the information processing device 10, etc.

[0079] The output unit 215 outputs each piece of information acquired by the acquisition unit 213 to the information processing device 10 via the network communication interface 220.

[0080] 4, the information processing device 30 may further include an analysis unit that analyzes soil components in the field. An acquisition unit of the information processing device 30 acquires data on the soil components, an analysis unit analyzes the soil components, and an output unit transmits the analysis results to the information processing device 10.

[0081] <Data example> FIG. 5 is a diagram showing an example of parameters (part 1) according to an embodiment of the present disclosure. The parameters shown in FIG. 5 are classified into the categories of "initial settings," "basic cultivation information," and "soil preparation." For example, the parameter "initial settings" is the global warming potential CO 2 , N 2 O, includes the fertilizer emission coefficient, and includes a coefficient for soil temperature, a coefficient for soil moisture content, and a coefficient for soil coverage rate estimated from the sensor 40 and the position information of the field.

[0082] Parameters of "basic cultivation information" include plant type, cultivation area, location (location information), air temperature, soil temperature, soil moisture content, soil classification, etc. "Soil preparation" is classified into "soil chemistry", "soil physical properties", "soil biology", and "satellite imagery". Parameters of "soil chemistry" include N, P, K, carbon content, and other trace elements. Parameters of "soil physical properties" include moisture content, pH, EC (electrical conductivity), air permeability, and hardness. Parameters of "soil biology" include fungus species and fungus content. Parameters of "satellite imagery" include wavelength range and reflected light. Information on "soil preparation" may also be included in the basic cultivation information.

[0083] Fig. 6 is a diagram showing an example of parameters (part 2) according to an embodiment of the present disclosure. The parameters shown in Fig. 6 are classified into "cultivation", "harvest", and "post-harvest". "Cultivation" is further classified into "pesticides", "fertilizers", and "biostimulants".

[0084] All parameters for "pesticides," "fertilizers," and "biostimulants" include product name, type, amount used, application date, and number of applications (which can be calculated from the application date).

[0085] The parameters of "harvest" include yield and harvest date as yield, and also include quality. The parameters of "quality" include sugar content, moisture content, amino acids, vitamins, sorting rank, etc., and the "satellite image" of "post-harvest" includes wavelength range and reflected light.

[0086] <Calculation example> Next, an example will be described in which the calculation unit 113 calculates the carbon stock amount and the GHG emission amount using the above-mentioned formulas (1) to (4). Fig. 7 is a diagram showing an example of input parameters according to an embodiment of the present disclosure. For example, the following coefficients are set in the calculation unit 113 as initial settings. CO 2 Global warming potential: 1 N 2 Global Warming Potential of 0: 298 N in fertilizer for rice 2 O emission factor: 0.0049 (tN 2 O / tN) Furthermore, the calculation unit 113 sets the coefficients of the soil temperature, the soil moisture content, and the soil coverage rate to 1.

[0087] The calculation unit 113 calculates the carbon storage amount and the GHG emission amount by inputting the basic cultivation information, growth information, and harvest information (see FIG. 7) acquired by the acquisition unit 112 into formulas (1) to (4). FIG. 8 is a diagram showing a calculation process when input parameters according to an embodiment of the present disclosure are input.

[0088] The calculation unit 113 inputs the amount of fertilizer applied by BS as the parameter P, sets parameters d (59%) and r (41%) from the crops of the land use classification, and calculates Pd (45.5974 kg) and Pr (31.68633 kg) using formulas (2) and (3). The calculation unit 113 also calculates P-(Pd+Pr)=6.716269 kg as the decomposition product after one month. In reality, the parameters (M, W, C) are tuned in the calculation of the decomposition process, but for simplicity, all coefficients are set to 1 assuming that the decomposition has reached the final stage.

[0089] Next, since the carbon content of vegetables is said to be 20-40%, if we assume that the carbon content of paprika used in BS is 40%, the carbon content C of the decomposition product when decomposition is completed is 84kg x 0.4 = 33.6kg. When converted to tons (t), this becomes 0.0336t. 0.0336t corresponds to ΔPd + ΔPr in formula (1).

[0090] The calculation unit 113 calculates the amount of CO 2 Determine the ratio of X to the total carbon in the soil (X / Y = 3.51). .child Here, carbon, which is the source of decomposition, is decomposed and becomes CO2 and carbon storage in the soil, so Y=1-X, and therefore 1=1 / YX / Y. Substituting X / Y=3.51 gives 1=1 / Y-3.51, and Y=1 / (1+3.51). The calculation unit 113 multiplies 0.0336, which corresponds to ΔPd+ΔPr, by Y(=1 / (1+3.51) using formula (1) to calculate the amount of carbon storage. CO 2 The calculation unit 113 calculates the emission amount as (3.51 / (3.51+1))×0.0336=0.026149889 t / ha (formula (1)). In addition, the calculation unit 113 calculates the carbon storage amount as (1 / (3.51+1))×0.0336=0.007450111 t / ha (formula (4)).

[0091] Next, N is the amount of fertilizer used (20 kg), and N 2 The amount of O discharged is N(20kg) x N 2The O emission coefficient is (0.0049) × 44 / 28 = 0.154 kg / 100 (cultivation area) a (Equation (9)). 2 The weight of nitrogen contained in O (14 × 2 = 28) is N 2 The calculation unit 113 converts the weight of N 2 To convert the amount of O emitted into CO2, use 0.154 x N 2 The global warming potential of O is calculated as (298) / 1000 (in tons) = 0.045892 t / ha.

[0092] Finally, the calculation unit 113 calculates the GHG emissions as CO 2 Emissions +N 2 Calculate O emission = 0.072041889 t / ha.

[0093] <Specific examples of verification> Next, the timing of verification by the verification unit 115 will be described using a specific example. Fig. 9 is a diagram showing an example of the timing of cultivation and data acquisition according to an embodiment of the present disclosure. In the example shown in Fig. 9, two cycles each including application of BS and fertilizer, sowing of plant seeds, cultivation, and harvesting are described, but the cycle is not limited to these two cycles.

[0094] The sensor 40 is a sensor installed in a farm field, and acquires data before and after fertilization. The sensor 40 acquires, for example, soil components, such as each parameter of “soil preparation” shown in FIG.

[0095] The producer inputs basic cultivation information using the information processing device 20, and the information processing device 20 transmits the input or initially set basic cultivation information to the information processing device 10.

[0096] Moreover, since the satellite data from the satellite 50 is used as an alternative data to the sensor 40, it is preferable to acquire the satellite data at the same time as the sensor 40 acquires the data. Moreover, since the state of cultivation and harvesting can be acquired from the satellite images, the satellite data may be acquired at the same time as the cultivation and harvesting.

[0097] Fig. 10 is a diagram illustrating a verification example 1 according to an embodiment of the present disclosure. The example shown in Fig. 10 is an example of verifying the difference between the estimated value of the carbon storage amount at the time of fertilization and the actual value of the carbon storage amount after harvesting of the plant. For example, in the first fertilization design, the calculation unit 113 calculates the estimated value of the carbon storage amount using the basic cultivation information etc. input by the producer and formula (1).

[0098] Next, after the first harvest of the plant, the verification unit 115 verifies whether there is any discrepancy between the actual measurement value of the carbon stock amount specified using the soil components measured by the sensor 40 and the calculated estimated value of the carbon stock amount. For example, if there is a large difference between the actual measurement value and the estimated value, the verification unit 115 may adjust a threshold value for determining whether there is any discrepancy.

[0099] Fig. 11 is a diagram for explaining a verification example 2 according to an embodiment of the present disclosure. The example shown in Fig. 11 is an example of verifying the difference between the target value of the soil component at the time of fertilization design and the actual measured value of the soil component after fertilization. For example, this verification is performed for each cultivation cycle.

[0100] When the BS is used in combination with a fertilizer, the calculation unit 113 estimates the target values ​​of each parameter of the soil components included in "soil preparation" shown in Fig. 5 based on the past soil components, the type and application amount of the BS, and the type and application amount of the fertilizer. Next, after the actual application or fertilization, the verification unit 115 verifies whether there is any discrepancy between the actual measured values ​​of the soil components measured by the sensor 40 and the calculated estimated values ​​of the soil components. For example, if there is a large difference between the actual measured values ​​and the estimated values, the verification unit 115 may adjust a threshold value for determining whether there is any discrepancy.

[0101] <Processing Procedure> Next, a description will be given of each process of the information processing system 1. Fig. 12 is a flowchart showing an example of evaluation processing of the information processing device 10 according to an embodiment of the present disclosure.

[0102] In step S102, the acquisition unit 112 of the information processing device 10 acquires the setting values ​​of the parameters included in the initial setting shown in FIG.

[0103] In step S104, the acquisition unit 112 of the information processing device 10 acquires basic cultivation information, growth information, and the like.

[0104] In step S106, the calculation unit 113 of the information processing device 10 calculates the amount of carbon storage and / or the amount of GHG emission using each parameter acquired by the acquisition unit 112. The calculation unit 113 may also provisionally calculate the price of carbon credits using the amount of GHG emission.

[0105] In step S108, the design unit 117 of the information processing device 10 performs fertilization design based on the BS to be applied and the fertilizer to be applied.

[0106] In step S110, the verification unit 115 of the information processing device 10 performs a verification process on the estimated price of carbon credits calculated by the calculation unit 113. For example, the verification unit 115 performs the verification process by comparing an actual measurement value of the carbon storage amount, etc. obtained by analyzing soil components after harvesting a plant with an estimated value of the carbon storage amount calculated by the calculation unit 113, and by comparing an actual measurement value of the GHG emission amount based on the measurement value of a sensor, etc. with the estimated value of the GHG emission amount calculated by the calculation unit 113.

[0107] In step S112, the verification unit 115 of the information processing device 10 may approve the calculated carbon credit price if the difference value (error) of the comparison result is equal to or less than a threshold value (e.g., 0.2%). The threshold value may be determined based on an actual measurement value of the change over time in the carbon storage amount of domestic non-andosol. In addition, the threshold value may be set on the condition that the acquired cultivation data is for one cycle or one year or more.

[0108] 13 is a flowchart showing an example of a process in the fertilization design according to an embodiment of the present disclosure. In step S202, the acquisition unit 112 of the information processing device 10 acquires soil components before fertilization obtained by analyzing the actual soil.

[0109] In step S204, the design unit 117 evaluates the obtained pre-fertilization soil components and obtains values ​​such as P, N, and K.

[0110] In step S206, the design unit 117 sets target values ​​of the soil components after fertilization when BS is not used in combination.

[0111] In step S208, the design unit 117 sets target values ​​of soil components after fertilization when BS is used in combination.

[0112] In step S210, the design unit 117 calculates the difference between the target value of the soil component when BS is not used and the actual measured value of the soil component before fertilization, and the difference between the target value of the soil component when BS is used and the actual measured value of the soil component before fertilization. This allows producers to understand how much fertilizer can be reduced by using BS in combination, since fertilizer can be reduced by using BS in combination.

[0113] In step S212, the design unit 117 performs fertilization design to fill the difference from the target value by using the difference value of the soil component. For example, the design unit 117 determines the application amount of BS and the application amount of fertilizer, and performs fertilization design.

[0114] Fig. 14 is a flowchart showing an example of a verification process according to an embodiment of the present disclosure. The process shown in Fig. 14 is a specific example of the process of step S110 shown in Fig. 12. Note that steps S302A to S306A and steps S302B to S306B shown below can be processed in parallel.

[0115] In step S302A, the verification unit 115 of the information processing device 10 acquires the carbon storage amount specified from the soil components obtained by analyzing the actual soil after harvest. The verification unit 115 may also acquire the GHG emission amount measured by a gas sensor installed in the farm field.

[0116] In step S304A, the verification unit 115 compares the actual measured value of the carbon storage amount after harvest with the estimated value of the carbon storage amount calculated before fertilization. The verification unit 115 may also compare the actual measured value of the GHG emission amount after fertilization with the estimated value of the carbon storage amount calculated before fertilization.

[0117] In step S306A, the verification unit 115 determines whether the comparison result (difference value) of the carbon stock amount and / or the GHG emission amount is within a threshold value.

[0118] In step S302B, the verification unit 115 of the information processing device 10 acquires soil components obtained by analyzing the actual soil after fertilization.

[0119] In step S304B, the verification unit 115 compares the actual measured values ​​of the soil components after fertilization with the target values ​​of the soil components set before fertilization.

[0120] In step S306A, the verification unit 115 determines whether the comparison result (difference value) between the target value and the actual measured value of the soil component is within a threshold value.

[0121] Although one embodiment of the present disclosure has been described above in detail, the present disclosure is not limited to the above embodiment, and various modifications and changes are possible within the scope of the claims. For example, in the present disclosure, with respect to the processes executed by each of the information processing devices 10 and 20, some of the processes may be transferred to another information processing device, a plurality of information processing devices may be appropriately integrated, or all the processes may be executed by one device. In addition, each of the information processing devices 10 and 20 may be managed by one organization, or may be managed by different organizations. [Explanation of symbols]

[0122] 1...information processing system, 10, 20, 30...information processing device, 110...processor, 111...control unit, 112...acquisition unit, 113...calculation unit, 114...setting unit, 115...verification unit, 116...estimation unit, 117...design unit, 118...output unit, 130...memory, 210...processor, 230...memory, 212...control unit, 213...acquisition unit, 214...display control unit, 215...output unit

Claims

1. In the information processing device, acquiring first data including a type and area of ​​a farm field and a type of a plant cultivated in the farm field, second data including a type and application amount of a material having an effect of enhancing resistance to abiotic stress, a type of fertilizer applied and a fertilizer application amount of the fertilizer that is reduced by the use of the material, and third data including a harvest date of the plant; calculating a carbon stock in the field by inputting the first to third data into a first calculation formula for calculating a carbon stock in soil, and / or calculating an amount of greenhouse gas emissions in the field by inputting the first to third data into a second calculation formula for calculating an amount of greenhouse gas emissions; A program that executes the following.

2. The program described in claim 1, further causing the information processing device to set the amount of fertilizer to be applied included in the second data from the type and amount of application of the material included in the second data, based on correspondence information that matches the type and amount of application of a material having the effect of increasing resistance to abiotic stress with the amount of fertilizer reduction of a specified fertilizer.

3. The program according to claim 1 , further causing the information processing device to calculate a price of carbon credits based on the amount of carbon stock or the amount of greenhouse gas emissions.

4. comparing a carbon stock amount obtained by analyzing soil components in the field after harvesting the plant with the calculated carbon stock amount, and / or comparing a greenhouse gas emission amount obtained by a sensor installed in the field after harvesting the plant with the calculated greenhouse gas emission amount; determining whether to approve a price for the carbon credits based on the comparison of the carbon stocks and / or the greenhouse gas emissions; The program according to claim 3 , further causing the information processing device to execute the following:

5. comparing target values ​​of the soil components of the field based on the second data with actual measured values ​​of the soil components of the field after harvesting the plants; determining whether to approve the price of the carbon credits based on the comparison of the soil components; The program according to claim 3 or 4, further causing the information processing device to execute the following:

6. Acquiring location information of a specified field; Estimating a climate of the specified field from the location information; estimating soil components of the specified field from soil components of the other field based on similarity between satellite data for the specified field and sensor data acquired from a sensor installed in the other field; estimating carbon storage capacity for the given field based on the estimated climate and soil composition; The program according to claim 1 , further causing the information processing device to execute the following:

7. Obtaining an evaluation value of soil components of the field; setting a first target value of the soil component in a case where the material is not applied and a second target value of the soil component in a case where the material is applied, after harvest of the plant cultivated in the field, based on the evaluation value; The program according to claim 1 , further causing the information processing device to perform fertilization design based on a difference between the first target value or the second target value and an actual measured value of a soil component before fertilization.

8. An information processing device, acquiring first data including a type and area of ​​a farm field and a type of a plant cultivated in the farm field, second data including a type and application amount of a material having an effect of enhancing resistance to abiotic stress, a type of fertilizer applied and a fertilizer application amount of the fertilizer that is reduced by the use of the material, and third data including a harvest date of the plant; calculating a carbon stock in the field by inputting the first to third data into a first calculation formula for calculating a carbon stock in soil, and / or calculating an amount of greenhouse gas emissions in the field by inputting the first to third data into a second calculation formula for calculating an amount of greenhouse gas emissions; An information processing method comprising:

9. an acquisition unit that acquires first data including a type and area of ​​a farm field and a type of a plant cultivated in the farm field, second data including a type and application amount of a material having an effect of increasing resistance to abiotic stress, a type of fertilizer applied, and a fertilizer application amount of the fertilizer that is reduced by the use of the material, and third data including a harvest date of the plant; a calculation unit that calculates a carbon stock in the field by inputting the first to third data into a first calculation formula that calculates a carbon stock in soil, and / or calculates a greenhouse gas emission amount in the field by inputting the first to third data into a second calculation formula that calculates a greenhouse gas emission amount; An information processing device comprising:

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