JP7437431B2 - agricultural management system - Google Patents

Description

The present invention relates to an agricultural management system.

BACKGROUND ART Conventionally, IoT (Internet of Things) technology for improving the efficiency of agricultural work has been proposed (for example, see Patent Document 1).

JP2021-096726A

In the agricultural field, there is only a classification based on the concepts of production and consumption, and during production, the properties of soil and crops are measured using sensors according to different characteristics, and environmental conditions have been created that are optimal for each. In the context of ``agriculture (production)'' + ``storage, transportation, and sales (consumption),'' we have only looked at the value of products based on the standards required by end users.

In addition, agriculture is a mass of know-how, and there is a persistent impression that the population in the agricultural industry is aging, the working age is decreasing, and it is hard work without holidays, etc., and it is difficult to break down the walls of volunteer farmers.

Furthermore, uniform cultivation without diversity has progressed in limited agricultural soil, resulting in soil and river pollution due to continuous crop failure, pests, and excessive fertilization. It is a source of greenhouse gas emissions such as oxides and carbon dioxide.

Therefore, it is an object of the present invention to provide an agricultural management system that can manage and control the growth of agricultural crops and share information regarding the crops.

An agricultural management system according to one aspect of the present disclosure (e.g., agricultural management system 1 described below) includes a agricultural product sensor device (e.g., agricultural product sensor device 2, described later) that detects the state of agricultural products, and manages information regarding the agricultural products. An agricultural management device (for example, agricultural management device 3 described below) and a farmer terminal (for example, a farmer terminal described below) that can communicate with the agricultural management device and is operated by a farmer who grows or cultivates the agricultural products. 4), the agricultural product sensor device transmits agricultural product detection data that detects the state of the agricultural products to the agricultural management device, and the agricultural management device transmits the agricultural product detection data transmitted from the agricultural product sensor device. , obtain the determination result of the state of the agricultural products as a label, and perform supervised learning using the combination of the agricultural product detection data and the label as training data to construct a learning model regarding the state of the agricultural products. , receives input of the agricultural product detection data detected by the agricultural product sensor device, determines whether the state of the agricultural product is normal or abnormal from the learning model and the agricultural product detection data, and determines the past state of the agricultural product used as the teacher data. Based on the data, the optimal growth information of the agricultural products is estimated, and the determination result of whether the state of the agricultural products is normal or abnormal, and the optimal growth information of the agricultural products are transmitted to the farmer terminal, and the farmer terminal displays the determination result of whether the condition of the agricultural product is normal or abnormal, and the optimal growth information of the agricultural product.

Further, the agricultural management system is capable of communicating with the agricultural management device and a crop sensor device (for example, a harvest sensor device 5 described later) that detects the state of the crop after the agricultural product is harvested. and further includes a business terminal (for example, a business terminal 6 described below) operated by a business operator that conducts business related to the harvest, and the harvest sensor device detects the state of the harvest. The agricultural management device acquires the crop detection data transmitted from the crop sensor device, and includes an identification number for identifying the type of the agricultural product, and an identification number for identifying the type of the agricultural product. When the state of the agricultural product and the state of the harvested product are stored in association with each other, and the input of the identification number of the agricultural product is received from the vendor terminal, the state of the agricultural product associated with the identification number of the agricultural product is stored. and the state of the harvested product is transmitted to the vendor terminal, and the vendor terminal centrally displays the state of the agricultural product and the state of the harvested product associated with the identification number of the agricultural product.

Moreover, the agricultural products sensor device and the harvested product sensor device include at least a sensor using nanodiamonds.

Further, the agricultural management device can be accessed by people other than farmers through the farmer terminal and the trader terminal.

Further, the agricultural product sensor device includes a soil sensor using a nanodiamond electrode.

Further, the harvested product sensor device is attached to a package for packaging the harvested product, and includes a sensor using a nanodiamond electrode.

According to the present invention, it is possible to provide an agricultural management system that can manage and control the growth of agricultural products and share information regarding the agricultural products.

1 is a diagram showing an example of the configuration of an agricultural management system according to the present embodiment. FIG. 1 is a diagram showing an example of the configuration of a crop sensor device. It is a figure showing an example of composition of a crop sensor device. It is a diagram showing an example of the configuration of an agricultural management device. It is a diagram showing an example of the configuration of a farmer terminal. It is a diagram showing an example of the configuration of a business terminal. It is a flowchart which shows the flow of construction processing of a learning model by the agricultural management device concerning this embodiment. It is a flow chart showing the flow of processing by the agricultural management device and the farmer terminal according to the present embodiment. It is a flowchart showing the flow of processing by the agricultural management device and the business terminal according to the present embodiment.

Hereinafter, embodiments of the agricultural management system of the present invention will be described with reference to the drawings.
FIG. 1 is a diagram showing an example of the configuration of an agricultural management system 1 according to the present embodiment. As shown in FIG. 1, the agricultural management system 1 includes a agricultural product sensor device 2, an agricultural management device 3, a farmer terminal 4, a harvest sensor device 5, and a business operator terminal 6.

The agricultural product sensor device 2 is configured to be able to communicate with the agricultural management device 3, and detects the state of agricultural products. The agricultural management device 3 is configured to be able to communicate with the agricultural product sensor device 2, farmer terminal 4, harvest sensor device 5, and business operator terminal 6, and manages information regarding agricultural products.

The agricultural management device 3 stores detection data detected by the agricultural product sensor device 2 and the harvest sensor device 5, as described later. The agricultural management device 3 has a function of performing machine learning on a large number of stored detection data to construct a learning model, a function of estimating optimal growth information of agricultural products from a large number of stored detection data, and the like.

The farmer terminal 4 can communicate with the agricultural management device 3 and is operated by a farmer who grows or cultivates agricultural products. The harvested product sensor device 5 detects the state of the harvested product, which is the state after the agricultural products have been harvested. The business operator terminal 6 is capable of communicating with the agricultural management device 3 and is operated by a business operator that conducts business related to harvested products.

Further, the farmer terminal 4 and the business terminal 6 can be accessed even by people other than farmers, that is, they can be accessed by anyone who is involved in agriculture. As a result, the agricultural management system 1 allows anyone who is interested in the agricultural industry to engage in agriculture as a volunteer farmer even if he or she does not own farmland, thereby making agriculture a more diverse industry.

FIG. 2A is a diagram showing an example of the configuration of the agricultural product sensor device 2. As shown in FIG. The agricultural product sensor device 2 may be, for example, a soil sensor placed in the soil of a field where agricultural products are grown. The agricultural product sensor device 2 includes a nanodiamond sensor 21, a control section 22, and a communication section 23.

The nanodiamond sensor 21 has, for example, an electrode in which nanodiamonds are supported on a cellulose nanofiber carrier, and measures the voltage/current that affects the nitrogen content between the electrodes to determine the nitrogen content in the soil in real time. Quantity can be measured. Thereby, in the nanodiamond sensor 21, by using carbon-derived nanodiamonds and plant-derived cellulose nanofibers, it is possible to produce an electrode using a member that takes soil affinity into consideration. Furthermore, the electrode of the nanodiamond sensor 21 generates current and voltage at specific values due to available nitrogen around the electrode, so by measuring the current and voltage values at any time, the nitrogen content (in-situ , total amount, etc.) can be accurately measured in real time. Note that the agricultural product sensor device 2 may use a sensor section that detects the above-mentioned data using another method instead of the nanodiamond sensor 21.

The control unit 22 is composed of, for example, a microcomputer, and performs predetermined processing and calculations on the current/voltage detected by the nanodiamond sensor 21 (or the detection unit 21), and communicates the detected agricultural product detection data. The information is transmitted to the agricultural management device 3 by the unit 23 .
The communication unit 23 is a communication interface for communicating with external devices via a network.

In addition, instead of the nanodiamond sensor 21, the agricultural products sensor device 2 includes a soil sensor that detects data on electrical conductivity, temperature, and moisture content of soil, a sugar content sensor that detects the sugar content of agricultural products, NH ₃ , CH ₄ , It may be a conventional sensor such as a gas sensor that detects _CO2 , _O2 gas, etc. Furthermore, the agricultural product sensor device 2 may include an environmental sensor that detects the temperature, humidity, CO ₂ concentration, solar radiation, wind direction, wind speed, rainfall, water level, volumetric moisture content, etc. of the field where agricultural products are grown. Further, the agricultural product sensor device 2 may acquire information on fertilizer, information on harvest time, and the like.

The agricultural product sensor device 2 includes a plurality of sensors that are a combination of conventional sensors such as soil sensors, sugar content sensors, gas sensors, environmental sensors, etc., and the nanodiamond sensor 21 in order to obtain more diverse and more accurate detection data. It is preferable that the sensor device has the following. The agricultural product sensor device 2 detects, for example, the amount of photosynthesis (temperature, irradiation amount, etc.) based on the pH and temperature of moisture contained in the soil, environmental data obtained by other sensors above ground, and the nitrogen content detected by the nanodiamond sensor 21. By combining this with the amount, the growth and marketability (sugar content) of agricultural crops can be diagnosed from the soil.

FIG. 2B is a diagram showing an example of the configuration of the harvest sensor device 5. As shown in FIG. The harvest sensor device 5 includes a nanodiamond sensor 51, a control section 52, and a communication section 53. Since the crop sensor device 5 has the same configuration as the agricultural crop sensor device 2 described above, description of each configuration will be omitted. Further, in place of the nanodiamond sensor 51, the harvest sensor device 5 may use, for example, a near-infrared sensor as the sensor section 51, or may combine the nanodiamond sensor 51 and a near-infrared sensor.

The harvest sensor device 5 is attached to, for example, a packaging body for packaging the harvest, and detects gas (for example, NH ₃ , CH ₄ , CO ₂ , O ₂ gas) released when the harvest ripens. do. Thereby, the harvest sensor device 5 and the agricultural management device 3 can track and manage the harvest until it reaches the consumer. Moreover, the packaging body for packaging harvested products is made of cellulose nanofibers and the like. Thereby, the long-term storage property of the harvested product packaged with the package can be ensured.

FIG. 3 is a diagram showing an example of the configuration of the agricultural management device 3. As shown in FIG. As shown in FIG. 3, the agricultural management device 3 includes a control section 31, a storage section 32, and a communication section 33.

The control unit 31 is realized, for example, by a hardware processor such as a CPU (Central Processing Unit) executing a program (software). Some or all of these components are LSI (Large Scale Integration), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), GPU (Graphics Processing Unit) and other hardware (circuit part; (including circuitry), or may be realized by cooperation between software and hardware.

The program may be stored in advance in a storage device (a storage device equipped with a non-transitory storage medium) such as an HDD (Hard Disk Drive) or flash memory, or may be stored in a removable storage device such as a DVD or CD-ROM. It is stored in a medium (non-transitory storage medium) and may be installed when the storage medium is attached to a drive device.

However, as will be described later, the control unit 31 requires a large amount of calculations associated with machine learning, so for example, if a personal computer is equipped with a GPU (Graphics Processing Unit), technology called Accordingly, high-speed processing may be made possible by configuring the GPU to be used for arithmetic processing associated with machine learning.

Furthermore, in order to perform faster processing, the agricultural management device 3 constructs a computer cluster using multiple computers equipped with such GPUs, and performs parallel processing by the multiple computers included in this computer cluster. You may also do this.

The storage unit 32 includes, for example, a non-transitory storage medium such as an HDD (Hard Disk Drive), a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), or a ROM (Read Only Memory). Storage device or RAM ( Random Access Memory), etc.

The communication unit 33 is a communication interface for communicating with external devices such as the agricultural product sensor device 2 via a network.
The input unit 34 is an input interface such as a mouse, a keyboard, etc.
The display unit 35 is a device that displays images. The display unit 35 is, for example, an LCD (Liquid Crystal Display), an organic EL (Electroluminescence), or the like.

Next, the processing of the control unit 31 of the agricultural management device 3 will be explained.
The control unit 31 acquires the agricultural product detection data transmitted from the agricultural product sensor device 2 and stores it in the detected data storage unit 321. Here, the agricultural product detection data is various detection data detected by the agricultural product sensor device 2 described above.

Next, the control unit 31 acquires the determination result of the state of the agricultural products as a label. Specifically, the control unit 31 receives a label input operation by the input unit 34, and thereby acquires the label. Here, a label is a correct output that should correspond to an input in machine learning. The label is, for example, a two-level degree indicating whether or not the condition of the agricultural product is acceptable. For example, the control unit 31 sets information indicating that the condition of the crops is good to "1" as a label, and sets information indicating that the condition of the crops is not good to "0".

Next, the control unit 31 constructs a learning model regarding the state of the agricultural products by performing supervised learning using the combination of the agricultural product detection data and the label as teacher data.

Then, the control unit 31 stores the constructed learning model in the learning model storage unit 322. Note that it is desirable to prepare a large amount of training data for machine learning in order to improve the accuracy of machine learning.

The control unit 31 performs supervised learning using, for example, regression analysis, a neural network, a least squares method, a stepwise method, or the like. Supervised learning may be performed by online learning, batch learning, or mini-batch learning. Online learning is a learning method in which features are extracted from audio data and supervised learning is performed immediately each time a label is input and training data is created.

In addition, batch learning refers to extracting features from data, inputting labels, and creating training data, which is repeated, while multiple sets of training data are collected depending on the repetition, and all collected training data are This is a learning method that performs supervised learning using teacher data. Furthermore, mini-batch learning is a learning method that is intermediate between online learning and batch learning, in which supervised learning is performed every time a certain amount of teacher data is accumulated.

Next, the control unit 31 receives input of agricultural product detection data detected by the agricultural product sensor device 2. Upon receiving input of the agricultural product detection data, the control unit 31 determines whether the state of the agricultural product is normal or abnormal based on the received agricultural product detection data and the learning model stored in the learning model storage unit 322.

Further, the control unit 31 estimates optimal growth information of the crops based on data on the past state of the crops, which is stored in the detected data storage unit 321 and used as teacher data. Here, crop growth information refers to, for example, information regarding the growth of agricultural crops, such as the amount and type of fertilizer, the timing of applying fertilizer, the degree of growth, the moisture content of soil, temperature and electrical conductivity, the timing of harvest, etc. including. Then, the control unit 31 transmits the determination result of whether the state of the crops is normal or abnormal and the optimal growth information of the crops to the farmer terminal 4 through the communication unit 33.

Furthermore, the control unit 31 acquires harvest detection data transmitted from the harvest sensor device 5. Here, the harvest detection data is various detection data detected by the harvest sensor device 5 described above. The control unit 31 stores in the detection data storage unit 321 an identification number for identifying the type of agricultural product, the state of the agricultural product (crop detection data), and the state of the harvest (harvest detection data) in association with each other. Note that the identification number for identifying the type of agricultural product is, for example, an identification number for identifying and specifying the classification, variety, etc. of the agricultural product.

When the control unit 31 receives input of the agricultural product identification number from the business operator terminal 6, the control unit 31 reads out the state of the agricultural products and the state of the harvested product associated with the agricultural product identification number from the detected data storage unit 321, and Send to terminal 6.

FIG. 4A is a diagram showing an example of the configuration of the farmer terminal 4. As shown in FIG. 4A, the farmer terminal 4 includes a control section 41, a storage section 42, a communication section 43, a display section 44, and an operation section 45.

The control unit 41 is realized, for example, by a hardware processor such as a CPU executing a program (software). Some or all of these components may be realized by hardware (including circuits) such as LSI, ASIC, FPGA, GPU, etc., or may be realized by collaboration of software and hardware. . The program may be stored in advance in a storage device such as an HDD or flash memory (a storage device equipped with a non-transitory storage medium), or a removable storage medium such as a DVD or CD-ROM (a non-transitory storage medium). The software may be installed by attaching the storage medium to a drive device.

The storage unit 42 is realized by, for example, a storage device including a non-transitory storage medium such as an HDD, a flash memory, an EEPROM, or a ROM, or a RAM.

The communication unit 43 is a communication interface for communicating with external devices such as the agricultural management device 3 via a network.
The display unit 44 is a device that displays images. The display section 44 is, for example, an LCD, an organic EL, or the like.

The operation section 45 includes buttons and the like for operating the display section 44. Further, the display section 44 and the operation section 45 may be a touch panel in which these functions are integrated. In this case, the operation unit 45 may be a GUI switch displayed on the display unit 44. Further, the operation unit 45 may be a mechanical button.

FIG. 4B is a diagram showing an example of the configuration of the business terminal 6. As shown in FIG. 4B, the business terminal 6 includes a control section 61, a storage section 62, a communication section 63, a display section 64, and an operation section 65. Since the business terminal 6 has the same configuration as the above-mentioned farmer terminal 4, a description of each configuration will be omitted.

FIG. 5 is a flowchart showing the flow of learning model construction processing by the agricultural management device 3 according to the present embodiment.

In step S1, the control unit 31 of the agricultural management device 3 acquires the agricultural product detection data transmitted from the agricultural product sensor device 2, and stores it in the detected data storage unit 321.
In step S2, the control unit 31 acquires the determination result of the state of the agricultural products as a label.

In step S3, the control unit 31 sets the combination of the crop detection data obtained in step S1 and the label obtained in step S2 as teacher data.
In step S4, the control unit 31 constructs a learning model regarding the state of the agricultural products by performing supervised learning using the combination of the agricultural product detection data and the label as teacher data.

In step S5, the control unit 31 determines whether to end the supervised learning. Here, the conditions for ending supervised learning can be arbitrarily determined. For example, the control unit 31 may terminate the supervised learning when the error value between the output of the neural network and the label becomes less than or equal to a predetermined value. Further, the control unit 31 may terminate the supervised learning after repeating the supervised learning a predetermined number of times. If the supervised learning is to be completed (YES), the process moves to step S6. On the other hand, if the supervised learning is not completed (NO), the process returns to step S1.

In step S6, the control unit 31 stores the constructed learning model in the learning model storage unit 322.

FIG. 6 is a flowchart showing the flow of processing by the agricultural management device 3 and farmer terminal 4 according to this embodiment.

In step S11, the control unit 31 receives input of agricultural product detection data detected by the agricultural product sensor device 2.
In step S12, upon receiving input of the agricultural product detection data, the control unit 31 determines whether the state of the agricultural product is normal or abnormal based on the received agricultural product detection data and the learning model stored in the learning model storage unit 322.

In step S13, the control unit 31 estimates optimal growth information for the crops based on past crop state data stored in the detected data storage unit 321 and used as training data.

In step S<b>14 , the control unit 31 transmits the determination result of whether the state of the crops is normal or abnormal and the optimal growth information of the crops to the farmer terminal 4 through the communication unit 33 .
In step S15, the farmer terminal 4 displays the determination result of whether the state of the crops is normal or abnormal and the optimal growth information of the crops.

FIG. 7 is a flowchart showing the flow of processing by the agricultural management device 3 and the business terminal 6 according to the present embodiment.

In step S21, the control unit 31 acquires the harvest detection data transmitted from the harvest sensor device 5.

In step S22, the control unit 31 associates the identification number for identifying the type of agricultural products, the state of the crops (crop detection data), and the state of the harvest (harvest detection data) and stores them in the detected data storage unit 321. Remember.

In step S23, the control unit 31 receives input of identification numbers of agricultural products from the business terminal 6.
In step S<b>24 , the control unit 31 reads the status of the crops and the status of the harvested products associated with the received identification number of the crops from the detected data storage unit 321 , and transmits them to the business terminal 6 through the communication unit 33 .

In step S25, the business operator terminal 6 centrally displays the state of the agricultural products and the state of the harvested products associated with the identification number of the agricultural products. Specifically, the business terminal 6 displays the status of agricultural products and the status of the harvested products all at once on one screen of the display unit 64. This makes it easier for business operators to grasp the condition of agricultural products and harvested products.

As explained above, the agricultural management system 1 according to the present embodiment is capable of communicating with the agricultural product sensor device 2 that detects the state of agricultural products, the agricultural management device 3 that manages information regarding agricultural products, and the agricultural management device 3. , and a farmer terminal 4 operated by a farmer who grows or cultivates crops. 3 acquires the crop detection data transmitted from the crop sensor device 2, acquires the determination result of the condition of the crop as a label, and performs supervised learning using the combination of the crop detection data and the label as teacher data. , built a learning model for the state of crops, accepted input of crop detection data detected by the crop sensor device 2, determined whether the condition of the crops was normal or abnormal from the learning model and the crop detection data, and used it as training data. Based on data on past crop conditions, the optimal growth information of the crops is estimated, and the results of determining whether the crop conditions are normal or abnormal and the optimal growth information of the crops are sent to the farmer's terminal. 4 displays the determination result of whether the condition of the crops is normal or abnormal and the optimal growth information of the crops.

With such a configuration, the agricultural management system 1 can manage the state of agricultural products using the agricultural product sensor device 2, and can share information regarding the agricultural products with farmers using the farmer terminal 4. As a result, the agricultural management system 1 can, for example, grow crops with fertilizers that are minimized as much as possible, and suppress the generation of greenhouse gases due to fertilization that cannot be absorbed by plants or is impossible. Furthermore, agricultural management system 1 can, for example, break away from dependence on seed manufacturers by cultivating crops that suit the soil (existing species), maintain natural diversity through soil diagnosis and environmental management, and prevent problems such as continuous cropping problems. can contribute to the suppression of

The agricultural management system 1 is also capable of communicating with the agricultural management device 3 and a crop sensor device 5 that detects the state of the harvested product, which is the state after the agricultural products are harvested, and conducts business related to the harvested product. The crop sensor device 5 transmits crop detection data indicating the state of the harvest to the agricultural management device 3, and the agricultural management device 3 The crop detection data transmitted from the sensor device 5 is acquired, the identification number for identifying the type of crop, the condition of the crop, and the condition of the crop are stored in association with each other, and the crop is identified from the operator terminal 6. When the input of the number is accepted, the status of the crops and the status of the harvested products associated with the identification number of the crops are transmitted to the business terminal 6, and the business terminal 6 transmits the status of the crops associated with the identification number of the crops to the business terminal 6. Centrally display the condition and the condition of the harvest.

With such a configuration, the agricultural management system 1 can track and manage the condition of crops from the growing stage to the storage, transportation, and sales stages until they reach consumers, thereby ensuring the safety of the crops. can do.

Moreover, the agricultural products sensor device 2 and the harvest sensor device 5 are equipped with at least a sensor using nanodiamonds. Thereby, the agricultural management system 1 can acquire desired detection data with high accuracy.

Further, the agricultural product sensor device 2 includes a soil sensor using a nanodiamond electrode. Thereby, the agricultural management system 1 can more accurately measure nitrogen compounds in soil in real time by using nanodiamond electrodes that have high soil affinity. Furthermore, the agricultural management system 1 can prevent excessive fertilization when applying nitrogen fertilizer as base fertilizer or top dressing, and can supply glycoproteins (amino acids, etc.) that are optimal for the growth of agricultural crops, based on the measured values of the soil sensor. Become.

Further, the harvested product sensor device 5 is attached to a package for packaging the harvested product, and includes a sensor using a nanodiamond electrode. Thereby, the agricultural management system 1 can track and manage the state of harvested products during storage, transportation, and sales stages.

Furthermore, the agricultural management device 3 can be accessed by people other than farmers through the farmer terminal 4 and the business terminal 6. As a result, the agricultural management system 1 allows anyone who is interested in the agricultural industry to engage in agriculture as a volunteer farmer even if he or she does not own farmland, thereby making agriculture a more diverse industry.

Although one embodiment of the present invention has been described above, the present invention is not limited to this. The detailed structure may be changed as appropriate within the spirit of the present invention.

1 Agricultural management system 2 Crop sensor device 3 Agricultural management device 4 Farmer terminal 5 Harvest sensor device 6 Business terminal 21 Nanodiamond sensor 22 Control section 23 Communication section 31 Control section 32 Storage section 33 Communication section 34 Input section 35 Display section 321 Detected data storage unit 322 Learning model storage unit

Claims (5)

A crop sensor device that detects the condition of crops;
an agricultural management device that manages information regarding the agricultural products;
An agricultural management system comprising: a farmer terminal capable of communicating with the agricultural management device and operated by a farmer who grows or cultivates the agricultural products,
The agricultural product sensor device includes:
transmitting crop detection data that detects the state of the crops to the agricultural management device;
The agricultural management device includes:
obtaining the agricultural product detection data transmitted from the agricultural product sensor device;
Obtaining the determination result of the state of the agricultural products as a label,
constructing a learning model for the state of the agricultural products by performing supervised learning using the combination of the agricultural product detection data and the label as training data;
Accepting input of the agricultural product detection data detected by the agricultural product sensor device,
Determining whether the state of the agricultural products is normal or abnormal from the learning model and the agricultural product detection data,
Estimating optimal growth information for the agricultural products based on past state data of the agricultural products used as the teacher data,
transmitting a determination result of whether the state of the agricultural products is normal or abnormal and optimal growth information of the agricultural products to the farmer terminal;
The farmer terminal is
displaying a determination result of whether the state of the agricultural products is normal or abnormal, and optimal growth information of the agricultural products ;
The agricultural product sensor device includes a soil sensor using a nanodiamond electrode,
The soil sensor has a nanodiamond electrode in which nanodiamonds are supported on a cellulose nanofiber carrier, and measures the voltage or current that affects the nitrogen content between the nanodiamond electrodes to detect soil concentration in real time. Measuring nitrogen content,
Agricultural management system. The agricultural management system includes a crop sensor device that detects the condition of the crop after the crop is harvested;
a business terminal that can communicate with the agricultural management device and is operated by a business that conducts business related to the harvest;
further comprising;
The crop sensor device includes:
transmitting crop detection data indicating the condition of the crop to the agricultural management device;
The agricultural management device includes:
obtaining the crop detection data transmitted from the crop sensor device;
storing an identification number for identifying the type of the agricultural product, the state of the agricultural product, and the state of the harvested product in association with each other;
Upon receiving the input of the identification number of the agricultural product from the vendor terminal, transmitting the state of the agricultural product and the state of the harvested product that are associated with the identification number of the agricultural product to the vendor terminal;
The previous vendor terminal is
centrally displaying the state of the agricultural products and the state of the harvested products that are associated with the identification number of the agricultural products;
The agricultural management system according to claim 1. The agricultural management system according to claim 2, wherein the agricultural product sensor device and the harvest sensor device include at least a sensor using nanodiamonds. 3. The agricultural management system according to claim 2, wherein the agricultural management device is accessible by people other than farmers through the farmer terminal and the trader terminal. The agricultural management system according to claim 2 or 3, wherein the harvest sensor device is attached to a package for packaging the harvest, and includes a sensor using a nanodiamond electrode.

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