WO2020110210A1 - Computer system, predicted profit proposing method, and program - Google Patents

Computer system, predicted profit proposing method, and program Download PDF

Info

Publication number
WO2020110210A1
WO2020110210A1 PCT/JP2018/043665 JP2018043665W WO2020110210A1 WO 2020110210 A1 WO2020110210 A1 WO 2020110210A1 JP 2018043665 W JP2018043665 W JP 2018043665W WO 2020110210 A1 WO2020110210 A1 WO 2020110210A1
Authority
WO
WIPO (PCT)
Prior art keywords
agricultural
sales
profit
cost
livestock products
Prior art date
Application number
PCT/JP2018/043665
Other languages
French (fr)
Japanese (ja)
Inventor
俊二 菅谷
Original Assignee
株式会社オプティム
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 株式会社オプティム filed Critical 株式会社オプティム
Priority to JP2020557443A priority Critical patent/JP7066256B2/en
Priority to PCT/JP2018/043665 priority patent/WO2020110210A1/en
Publication of WO2020110210A1 publication Critical patent/WO2020110210A1/en

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; Forestry; Mining

Definitions

  • the present invention relates to a computer system for proposing agricultural and livestock products, a forecasted profit proposing method, and a program.
  • Patent Document 1 presents agricultural crops that can be cultivated and profits obtained from the agricultural crops in a specific cultivation place, the agricultural products that are expected to have high profits are not limited to specific places, and workers are Was difficult to recognize. In addition, since only agricultural products are targeted, it has been difficult for workers to recognize livestock products that do not consider livestock products and are expected to generate high profits.
  • An object of the present invention is to provide a computer system, a forecast profit proposing method, and a program that allow easy understanding of highly profitable agricultural and livestock products.
  • the present invention provides the following solutions.
  • the present invention is a computer system that proposes highly profitable agricultural and livestock products, Sales forecasting means for forecasting sales of the agricultural and livestock products, Production cost calculation means for calculating the cost of producing the agricultural and livestock products, Sales cost calculating means for calculating the cost of selling the agricultural and livestock products, Profit forecasting means for forecasting the profit of the agricultural and livestock products based on the sales, the cost for the production and the cost for the sale; A profit proposing means for proposing the profit, There is provided a computer system comprising:
  • a computer system that proposes highly profitable agricultural and livestock products predicts the sales of the agricultural and livestock products, calculates the cost of producing the agricultural and livestock products, and sells the agricultural and livestock products.
  • the cost is calculated, the profit of the agricultural and livestock products is predicted based on the sales, the cost of the production, and the cost of the sales, and the profit is proposed.
  • the present invention is a system category, but also in other categories such as methods and programs, the same action/effect according to the category is exhibited.
  • FIG. 1 is a diagram showing an outline of the forecast profit proposal system 1.
  • FIG. 2 is an overall configuration diagram of the forecast profit proposal system 1.
  • FIG. 3 is a flowchart showing a profit forecasting process executed by the computer 10.
  • FIG. 4 is a flowchart showing a profit proposal process executed by the computer 10.
  • FIG. 5 is an example of a diagram schematically showing a predicted profit data table recorded by the computer 10.
  • FIG. 6 is an example of a diagram schematically showing a screen displayed by the computer 10 on the worker terminal.
  • FIG. 7 is an example of a diagram schematically showing a screen displayed on the worker terminal by the computer 10.
  • FIG. 1 is a diagram for explaining an outline of a forecasted income proposal system 1 which is a preferred embodiment of the present invention.
  • the forecast profit proposal system 1 is a computer system that includes a computer 10 and proposes highly profitable agricultural and livestock products.
  • Agricultural and livestock products are agricultural products such as grains, vegetables, fruits, and flowers, and livestock products such as cows, pigs, and chickens. Further, not only these agricultural products and livestock products themselves, but also processed products and the like may be included.
  • the forecast profit proposal system 1 may include a worker terminal owned by a worker in the agriculture and livestock industry, other terminals such as a computer, and devices. Further, the forecasted profit proposal system 1 may be realized by a single computer such as the computer 10, or may be realized by a plurality of computers such as a cloud computer.
  • the computer 10 is connected to a worker terminal or the like via a public line network so as to be able to perform data communication, and executes necessary data transmission/reception.
  • the computer 10 predicts sales of agricultural and livestock products.
  • the computer 10 may be configured to predict sales based on at least one of the sales trend of agricultural and livestock products and the population distribution of consumers.
  • the computer 10 records past sales trends of agricultural products that have been recorded in advance or refer to various databases (changes in sales amount, changes in sales amount, changes in growing area, changes in the number of workers, etc.) and production locations. Predict sales of this agricultural and livestock product based on the population distribution around the area and the sales place.
  • the computer 10 calculates the cost of producing agricultural and livestock products. At this time, the computer 10 considers at least one of the predicted yield of agricultural and livestock products, growing conditions (climate, soil, water, etc.) and environmental information (sunlight, rainfall, temperature, pests, diseases, etc.). Calculate the cost of producing livestock products. The computer 10 calculates, for example, the total of the seedling cost per unit amount, the feed cost, the facility cost, and the labor cost based on the working hours per unit volume as the cost required for the production. The computer 10 adds or subtracts costs required for labor costs and equipment costs based on the predicted yield, for example, to calculate the costs for production.
  • the computer 10 calculates the cost of production by adding or subtracting the cost required for the facility for adjusting the climate (greenhouse required for cultivation of vinyl greenhouses, etc.) to the agricultural and livestock products where the climate is not appropriate. To do. For example, at the time when a pest occurs, the computer 10 calculates by adding the labor required for the pest and the cost required for the medicine. The computer 10 may calculate the cost of production by combining the examples described above.
  • the computer 10 calculates the cost of selling agricultural and livestock products. At this time, the computer 10 calculates the cost of selling in consideration of the cost of transporting and storing the agricultural and livestock products.
  • the computer 10 stores, for example, a transportation cost necessary for physical distribution from the production site to the sales site, a storage cost during storage at the production site, and a storage cost during storage at the sales site by the time of sale.
  • the cost of selling agricultural and livestock products is calculated as the main cost of selling.
  • the computer 10 may take into account other costs such as operating costs and costs for securing a selling place as costs for selling agricultural and livestock products.
  • the computer 10 predicts the profit of the agricultural and livestock products based on the predicted sales, costs for production, and costs for sales.
  • the computer 10 calculates profit by subtracting the cost of production and the cost of sales from the predicted sales, and predicts the calculated result as the profit of the agricultural and livestock products.
  • a calculation method is adopted for simplification of description, but not limited to this calculation method, a predetermined coefficient is used, depreciation cost, etc. are taken into consideration, and a dedicated
  • the income of agricultural and livestock products may be predicted by taking into consideration the deduction of employees.
  • the computer 10 proposes the predicted profit to the worker. At this time, the computer 10 may propose at least one of the predicted sales, the calculated production cost, and the calculated sales cost in addition to the profit.
  • the computer 10 may suggest to a worker a breeding method suitable for this agricultural and livestock product in consideration of at least one of the agricultural and livestock product growing conditions and environmental information. Further, the computer 10 may suggest at least one of a production place and a sales place to the worker.
  • the computer 10 predicts sales of agricultural and livestock products (step S01).
  • the computer 10 predicts the sales of agricultural and livestock products in each region (Hokkaido, Tohoku, Kanto, Chubu, Kinki, Shikoku, Kyushu Okinawa, each prefecture, each municipality, etc.).
  • the computer 10 predicts sales for each agricultural and livestock product in each region, for example.
  • the computer 10 considers at least one of the above-mentioned past sales trend of the agricultural products, the distribution of the population of consumers in each region, around the production place, and/or around the sales place as described above. Predict sales.
  • the computer 10 calculates the cost of producing agricultural and livestock products (step S02).
  • the computer 10 calculates the cost of producing agricultural and livestock products in consideration of at least one of the above-mentioned predicted yield of agricultural and livestock products, growing conditions, and environmental information.
  • the computer 10 calculates the cost of selling agricultural and livestock products (step S03).
  • the computer 10 calculates the cost of selling based on the transportation cost and the storage cost of the agricultural and livestock products as described above.
  • the computer 10 predicts the profit of the agricultural and livestock products based on the predicted sales and the calculated production and sales costs (step S04).
  • the computer 10 calculates the value obtained by subtracting the cost required for production and sales from the above-mentioned sales as the income of the agricultural and livestock products.
  • the computer 10 predicts this calculation result as the income of the agricultural and livestock products.
  • the computer 10 proposes the predicted profit to the worker (step S05).
  • the computer 10 proposes to the worker the predicted profit of this agricultural and livestock product based on the name of the agricultural and livestock product designated by the worker.
  • the computer 10 proposes to the worker the name of the highly profitable agricultural and livestock product in this area and the predicted profit in this agricultural and livestock product based on the area designated by the worker.
  • the computer 10 proposes to the worker the name of the highly profitable agricultural and livestock product in the area around this current position and the predicted profit of this agricultural and livestock product based on the current position of the worker.
  • the computer 10 also proposes the name of the agricultural and livestock product that meets the sales, production cost, and/or selling cost specified by the worker and the predicted profit for this agricultural and livestock product.
  • the computer 10 similarly proposes the predicted profit to the worker.
  • the computer 10 may propose at least one of the predicted sales, the calculated production cost, and the calculated sales cost in addition to the profit.
  • the computer 10 may propose a cultivation method suitable for agricultural and livestock products in consideration of at least one of agricultural and livestock product growth conditions and environmental information in addition to profits. Further, the computer 10 may propose at least one of a production place and a sale place of this agricultural and livestock product.
  • FIG. 2 is a diagram showing a system configuration of the forecast profit proposal system 1 according to the preferred embodiment of the present invention.
  • the forecast profit proposal system 1 is a computer system which includes a computer 10 and proposes highly profitable agricultural and livestock products.
  • forecasted profit proposal system 1 may include other terminals and devices such as the above-mentioned worker terminal and other computers.
  • the predicted profit proposal system 1 may be realized by a single computer such as the computer 10 or a plurality of computers such as a cloud computer.
  • the computer 10 is connected to the above-described worker terminal (not shown) and the like so as to be able to perform data communication via a public line network, etc., and executes necessary data transmission/reception.
  • the computer 10 includes a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), and the like, and a device for enabling communication with other terminals or devices as a communication unit, for example, the IEEE 802. .. 11 compliant Wi-Fi (Wireless-Fidelity) compatible device and the like. Further, the computer 10 includes, as a recording unit, a hard disk, a semiconductor memory, a recording medium, a data storage unit such as a memory card. Further, the computer 10 includes various devices that execute various processes as a processing unit.
  • a CPU Central Processing Unit
  • RAM Random Access Memory
  • ROM Read Only Memory
  • the computer 10 includes, as a recording unit, a hard disk, a semiconductor memory, a recording medium, a data storage unit such as a memory card.
  • the computer 10 includes various devices that execute various processes as a processing unit.
  • control unit reads a predetermined program to realize the proposal request acquisition module 20, the profit proposal module 21, the training method proposal module 22, and the place proposal module 23 in cooperation with the communication unit. Further, in the computer 10, the control unit reads a predetermined program to realize the recording module 30 in cooperation with the recording unit. Further, in the computer 10, the control unit reads a predetermined program, thereby cooperating with the processing unit, the sales prediction module 40, the production cost calculation module 41, the sales cost calculation module 42, the profit prediction module 43, and the proposal content creation. The module 44 is realized.
  • FIG. 3 is a diagram showing a flowchart of the profit prediction process executed by the computer 10. The processing executed by each module described above will be described together with this processing.
  • the sales forecasting module 40 forecasts the sales of agricultural and livestock products (step S10).
  • step S10 the sales forecasting module 40 forecasts sales of agricultural and livestock products in a predetermined range such as each region.
  • the sales prediction module 40 predicts the sales of one agricultural and livestock product in each region, for example. If the agricultural and livestock products are grapes, forecast the sales of the grapes within a given range.
  • the sales forecasting module 40 forecasts sales of various agricultural and livestock products in a predetermined range.
  • the sales forecasting module 40 forecasts sales in consideration of the sales trend of agricultural and livestock products and/or the population distribution of consumers. For example, the sales forecasting module 40 records, as a sales trend, a change in the sales amount of grapes within a predetermined range, a change in the sales amount itself, a change in the sales amount, a change in the growing area, a change in the number of workers, etc. It is acquired by referring to a database previously recorded in 30, a database recorded by another computer, or the like. In addition, the sales forecasting module 40 pre-stores the distribution distribution of consumers in a predetermined range, around the production place of agricultural and livestock products, and/or around the selling place of agricultural and livestock products in the recording module 30 as the population distribution of consumers. It is acquired by referring to the recorded database or the database recorded by another computer. The sales prediction module 40 predicts the sales of agricultural and livestock products based on at least one of the sales trend and the population distribution of consumers.
  • the sales prediction module 40 predicts the sales amount and sales amount of agricultural and livestock products to be sold, based on the changes in the sales amount itself and the changes in the sales amount as the sales trend.
  • the sales prediction module 40 predicts sales of agricultural and livestock products by multiplying the predicted sales amount by the sales amount.
  • the sales forecasting module 40 forecasts the sales of agricultural and livestock products based on the average distribution amount and the ratio and total number of consumers who purchase the agricultural and livestock products around the sales place as the population distribution.
  • the sales prediction module 40 predicts the sales of agricultural and livestock products by multiplying the sales amount by the ratio or total number of consumers who purchase.
  • the sales prediction module 40 may be configured to predict sales of agricultural and livestock products based on sales trends and population distribution. In this case, for example, the sales prediction module 40 predicts the sales of agricultural and livestock products based on the transition of the sales amount itself, the transition of the sales amount, and the population distribution around the sales place. The sales prediction module 40 predicts the sales amount of this agricultural and livestock product based on the change in the sales amount. The sales forecasting module 40 forecasts the sales volume based on the population distribution at the selling place and based on the ratio and total number of consumers who purchase the agricultural and livestock products. The sales prediction module 40 predicts the sales of this agricultural and livestock product by multiplying the predicted sales amount by the predicted sales amount.
  • the above-described calculation method by which the sales prediction module 40 predicts sales is merely an example, and is not limited to the above-described example, and can be changed as appropriate.
  • the production cost calculation module 41 calculates the cost (production cost) required to produce agricultural and livestock products (step S11).
  • the production cost calculation module 41 considers at least one of the predicted yield of agricultural and livestock products, growing conditions (climate, soil, water, etc.), and environmental information (sunshine, rainfall, temperature, pests, diseases, etc.). Calculate the production cost of agricultural and livestock products.
  • the production cost calculation module 41 calculates, for example, the total of the seedling cost per unit amount, the feed cost, the equipment cost, the labor cost based on the working hours per unit amount, and the like as the production cost.
  • the production cost calculation module 41 calculates the final production cost by adding at least one of the predicted yield, the growing condition, and the environmental information to this production cost.
  • the production cost calculation module 41 calculates the final production cost by adding the cost required for adjusting the final shipping amount to the production cost when the predicted profit is higher than usual. Further, the production cost calculation module 41 calculates the final production cost by adding the cost required for the facility (greenhouse, etc.) for adjusting the growing condition to the production cost when the climate is predicted to be unsuitable. .. Further, when the occurrence of pests is predicted, the production cost calculation module 41 calculates the final production cost by adding the costs for the labor force and the medicine required for pest control to the production cost.
  • the production cost calculation module 41 may calculate the cost of producing agricultural and livestock products in consideration of a combination of the above-mentioned predicted yield, growing conditions, and environmental information. For example, in the above-mentioned example, the production cost calculation module 41 calculates the final production cost by adding the cost required for the facility for adjusting the growing condition and the cost required for pest control to the production cost.
  • the production cost calculation module 41 may calculate the final production cost after further considering the costs of other productions. Further, the production cost calculation module 41 may calculate the final production cost by adding other conditions.
  • the sales cost calculation module 42 calculates a cost (sales cost) required to sell agricultural and livestock products (step S12).
  • the selling cost calculation module 42 calculates the final selling cost in consideration of the costs of transporting and storing the agricultural and livestock products.
  • transportation costs include transportation costs required to transport agricultural and livestock products from a production site to a sales site.
  • storage costs include storage costs required for storage of agricultural and livestock products at the production site and storage costs required for storage of agricultural and livestock products at the sales site.
  • the selling cost calculation module 42 calculates the final selling cost by using the costs for transportation and storage as the substantial selling cost.
  • the selling cost calculation module 42 may calculate the final selling cost by further considering other costs such as operating costs and costs for securing a selling place in addition to the above-mentioned ones.
  • the profit prediction module 43 predicts the profit of the agricultural and livestock products based on the predicted sales, the calculated production cost and the sales cost (step S13). In step S13, the profit prediction module 43 calculates the profit by subtracting the calculated production cost and sales cost from the predicted sales. That is, the profit prediction module 43 predicts this calculation result as profit.
  • the profit forecasting module 43 is not limited to the above-described calculation method, and other calculation methods such as a calculation method that uses a predetermined coefficient for the predicted sales, the calculated production cost, and the sales cost, depreciation costs, deductions for full-time employees, etc.
  • the profit may be predicted based on another calculation method such as a calculation method that takes into consideration.
  • the calculation method by which the profit prediction module 43 predicts the profit can be changed as appropriate.
  • the recording module 30 records the name of the agricultural and livestock product, the production location of the agricultural and livestock product, the predicted sales, the calculated production cost, the calculated sales cost, and the predicted profit in association with each other as predicted profit data (step S14).
  • the recording module 30 records the type name, the variety name, the product name, the processed product name, etc. as the names of the agricultural and livestock products, records the above-mentioned predetermined range as the production place, and the sales as described above.
  • the predicted value is recorded, the calculated value is recorded as the production cost, the calculated value is recorded as the sales cost, and the predicted value is recorded as the profit.
  • the recording module 30 further records general forecasting methods and sales places in the applicable predetermined range in addition to the forecast profit data.
  • the recording module 30 may record the above-mentioned forecast profit data other than the above-mentioned example together.
  • the recording module 30 does not necessarily need to record all the above-described examples in the above-described predicted profit data, and can be changed as appropriate.
  • FIG. 5 is a diagram schematically showing an example in which the recording module 30 records the predicted profit data in a table format.
  • the recording module 30 records the management number, the name of agricultural and livestock products, the production location, the breeding method, the sales, the production cost, the sales cost, the revenue, and the sales location in a table format in association with each other as the predicted revenue data.
  • the recording module 30 gives management numbers in order from the one with the highest profitability.
  • the recording module 30 has, for example, a management number 0001 with a farm and livestock product name of chicken, a production place of Miyazaki Prefecture, a breeding method of flat breeding, sales of 80 million yen, and production cost of 40 million yen.
  • the sales cost is 10 million yen
  • the profit is 30 million yen
  • the sales place is Fukuoka prefecture.
  • the recording module 30 newly records the predicted profit data
  • the recorded profit is compared with the predicted profit in the already recorded predicted profit data and the predicted profit in the newly recorded predicted profit data, and the profit is high. Add the newly recorded forecast revenue data to the place where the order position is maintained. At this time, the recording module 30 changes the management number based on the added predicted profit data.
  • forecast revenue data table may have a configuration in which newly recorded forecast revenue data is added to the lowest position without changing the order.
  • FIG. 4 is a diagram showing a flowchart of the profit proposing process executed by the computer 10. The processing executed by each module described above will be described together with this processing.
  • the proposal request acquisition module 20 acquires a proposal request for predicted profit data from a worker (step S20).
  • the proposal request acquisition module 20 acquires a proposal request for profit data from a worker terminal or the like.
  • This proposal request includes a condition for profit data specified by the worker.
  • this condition for example, the predicted profit data of agricultural and livestock products in the surrounding area based on the own position information, the predetermined number of predicted profit data, the predicted profit data of the predetermined agricultural and livestock products, displayed on the worker terminal
  • the forecast profit data based on the area or place designated on the map, and the forecast profit data of agricultural and livestock products satisfying the sales, the production cost and/or the sales cost designated by the worker can be given.
  • the proposal content creation module 44 creates the proposal content of the predicted profit data for this worker based on the acquired request request for the predicted profit data (step S21).
  • step S21 the proposal content creation module 44 creates the proposal content based on the conditions included in the proposal request described above.
  • the proposal content creation module 44 extracts a predetermined number of predicted profit data in the surrounding area based on the position information of the worker from the predicted profit data table in descending order of profit and creates the proposal content. To do.
  • the proposal content creation module 44 extracts a predetermined number of items in descending order of profit regardless of region from the predicted profit data table, and creates the proposal contents.
  • the proposal content creation module 44 extracts a predetermined number of predicted profit data corresponding to the agricultural and livestock products designated by the worker from the predicted profit data table in descending order of profit, and creates the proposal content. Further, the proposal content creation module 44 extracts a predetermined number of predicted profit data in the area or place designated by the worker in the descending order of profit from the predicted profit data table, and creates the proposal contents. In addition, the proposal content creation module 44 extracts a predetermined number of pieces of predicted profit data that match or approximate the sales, production cost, and/or sales cost designated by the worker from the predicted profit data table in descending order of profit. , Create as a proposal content.
  • the proposal content creation module 44 creates, as the content of the proposal, a training method suitable for agricultural and livestock products in consideration of at least one of the training conditions and environmental information with respect to the training method in the forecast profit data.
  • the proposal content creation module 44 uses, for example, greenhouse cultivation for improving profitability by accelerating the shipment time when the cultivation method in the forecast profit data is open field cultivation, when the climate in this area is mild. Create forcing culture as a proposal.
  • the proposal content creation module 44 creates a greenhouse greenhouse cultivation as a rain measure as the proposal content when the growing method in the forecast profit data is open field cultivation and when the amount of rainfall in this area is larger than the average area. To do.
  • the proposal content creation module 44 creates at least one of the production location and the sales location in the forecast profit data as the proposal content.
  • the proposal content creation module 44 creates, in addition to the predicted profit, the predicted sales, the production cost, the sales cost, the training method, the production location and the sales location as the proposal content.
  • suggestion content creation module 44 may create a breeding method suitable for agricultural and livestock products as a suggestion content in consideration of the breeding condition and environmental information for the breeding method. Further, the proposal content creation module 44 may create the production location and the sales location as the proposal content for the sales location.
  • the proposal content creation module 44 is configured to create, as a proposal content, at least one of predicted sales, production cost, sales cost, training method, production location, and sales location in addition to the expected profit as the proposal content. It may be. Further, the proposal content creation module 44 may be configured to create, as the proposal content, at least one of the measured sales, the production cost, and the sales cost as the proposal content in addition to the predicted profit. In addition, the proposal content creation module 44 may be configured to create, as the proposal content, the training method and/or the production place or the sales place as the proposal content in addition to the predicted profit.
  • the proposal content creation module 44 includes, as the proposal content, at least one of the predicted sales, the production cost, and the sales cost in addition to the predicted profit, and further, the training method and/or the production place or the sales place as the proposal content.
  • the configuration may be created.
  • the profit proposal module 21 proposes a profit to the worker (step S22).
  • the profit proposing module 21 sends the created proposal contents to the worker terminal and displays the proposal contents on the worker terminal to propose a profit.
  • the profit proposing module 21 also proposes any one or a combination of predicted sales, production costs, sales costs, training methods, production locations and sales locations included in the created proposal content.
  • the breeding method suitable for agricultural and livestock products may be suggested by the breeding method suggestion module 22.
  • the place of production and the place of sale of the agricultural and livestock products may be suggested by the place suggestion module 23.
  • the raising method suggesting module 22 may propose a raising method and the place suggesting module 23 may suggest a production place and a selling place.
  • FIG. 6 is a diagram schematically showing an example of a screen displayed on the worker terminal by the profit proposing module 21.
  • FIG. 7 is a diagram schematically showing an example of another screen displayed on the worker terminal by the profit proposing module 21.
  • the profit proposal module 21 causes the worker terminal to display the profit proposal screen 100.
  • This profit proposal screen 100 is based on the proposal contents created by the above-described proposal content creation module 44 by extracting a predetermined number of profitable data tables in descending order of profit regardless of region.
  • the profit proposing module 21 displays the management number, the name of the agricultural and livestock products, the predicted profit, the predicted sales, the production cost, the sales cost, the breeding method, the production place, and the sales place as the profit proposal screen 100 on the worker terminal. Display it.
  • the items to be displayed are based on the proposal contents created by the above-mentioned proposal contents creating module 44.
  • the profit proposing module 21 displays each agricultural and livestock product in descending order of profit. In this example, the profit proposing module 21 displays that the profitability is high in the order of chicken, milk, grape,... Based on the order of management numbers.
  • the profit proposal module 21 displays each item described above in each agricultural and livestock product.
  • the profit proposing module 21 may be configured to highlight or highlight the one with the highest profitability, or to display visual changes in the order of high profitability. Further, the display is not limited to the table display as shown in FIG. 6, and other display modes such as a graph may be displayed.
  • each agricultural and livestock product only specific items may be displayed. For example, for chicken, the expected income, breeding method, and production place are displayed, for milk, the expected income, estimated sales, production cost, and sales cost are displayed, and in the grape, only the expected income is displayed.
  • the above-described suggestion content creation module 44 may create the suggestion contents in which only the specific items are displayed as the suggestion contents.
  • the proposal content creation module 44 may create at least the predicted profit of each agricultural and livestock product as the proposal content, and other items can be appropriately changed.
  • the proposal request acquisition module 20 displays the map 200 on the worker terminal.
  • the worker specifies a desired area for this map 200.
  • the area designated by the worker on the map 200 is indicated by the icon 210.
  • the proposal request acquisition module 20 causes the worker terminal to display the enlarged map 220 including the area designated by the worker.
  • the worker further designates the area desired by the worker on the enlarged map 220.
  • the area designated by the worker on the enlarged map 220 is indicated by the icon 230.
  • the proposal request acquisition module 20 acquires the proposal request of the forecast profit data for the area designated by the icon 230.
  • the proposal content creation module 44 Based on the acquired proposal request, the proposal content creation module 44 extracts a predetermined number of predicted profit data corresponding to this region from the predicted profit data table in descending order of profit and creates the proposal contents.
  • the profit proposal module 21 displays the created proposal contents on the worker terminal as a predicted profit display field 240.
  • the profit proposing module 21 displays the predicted profit display field 240 in a format to be superimposed on the enlarged map 220.
  • the profit proposal module 21 displays the name of the agricultural and livestock product, the predicted profit, the predicted sales, the production cost, the sales cost, the breeding method, the production place, and the sales place in the predicted profit display field 240.
  • the items to be displayed are based on the proposal contents created by the above-mentioned proposal contents creating module 44.
  • the harvest proposal module 21 displays the one related to the agricultural and livestock products with the highest predicted profit.
  • the proposal request acquisition module 20 may display a further enlarged map including the area designated by the enlarged map 220. This may be repeated one or more times to display a map with various enlargement ratios.
  • the profit proposal module 21 is not limited to displaying the profit of one agricultural and livestock product. It may be configured to display the profits of a plurality of agricultural and livestock products. In this case, the other agricultural products are displayed in the descending order of profit, or the other agricultural products are displayed by displaying an icon for displaying the other agricultural products. It may be configured to display livestock products. Further, the display mode, the display position, and the like of the predicted profit display field 240 are not limited to this example, and can be changed as appropriate.
  • the above-described means and functions are realized by a computer (including a CPU, an information processing device, and various terminals) reading and executing a predetermined program.
  • the program is provided in the form of being provided from a computer via a network (SaaS: software as a service), for example.
  • the program is provided in a form recorded in a computer-readable recording medium such as a flexible disk, a CD (CD-ROM, etc.), a DVD (DVD-ROM, DVD-RAM, etc.), for example.
  • the computer reads the program from the recording medium, transfers the program to the internal recording device or the external recording device, records the program, and executes the program.
  • the program may be recorded in advance in a recording device (recording medium) such as a magnetic disk, an optical disk, a magneto-optical disk, and provided from the recording device to a computer via a communication line.

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Marketing (AREA)
  • Marine Sciences & Fisheries (AREA)
  • Mining & Mineral Resources (AREA)
  • Agronomy & Crop Science (AREA)
  • Health & Medical Sciences (AREA)
  • Economics (AREA)
  • General Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Animal Husbandry (AREA)
  • Primary Health Care (AREA)
  • Strategic Management (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

[Problem] To provide a computer system which makes it possible to easily determine highly profitable agricultural/livestock products, a computer system which makes it possible to easily provide a predicted profit proposing method and program, and a predicted profit proposing method and program. [Solution] This computer system for proposing a highly profitable agricultural/livestock product predicts the sales of the agricultural/livestock product, calculates the cost of production of the agricultural/livestock product, calculates the cost of selling the agricultural/livestock product, predicts a profit from the agricultural/livestock product on the basis of the sales, the cost of production, and the cost of selling, and proposes the profit.

Description

コンピュータシステム、予測収益提案方法及びプログラムComputer system, forecasted revenue proposal method and program
　本発明は、農畜産物を提案するコンピュータシステム、予測収益提案方法及びプログラムに関する。 The present invention relates to a computer system for proposing agricultural and livestock products, a forecasted profit proposing method, and a program.
　近年、農畜産業において、就労者の減少及び高齢化が問題になっている。このような問題は、新規の就労者が育成方法の研修、農地の確保、資金繰り、農畜産物の収益化等の課題に対して十分な解決策を有していないことから、就労者の減少の原因となっている。 In recent years, a decrease in the number of workers and an aging population have become a problem in the agriculture and livestock industry. The number of new workers is not enough because new workers do not have sufficient solutions to problems such as training on training methods, securing farmland, financing, and monetization of agricultural and livestock products. Is the cause of.
　このような課題を解決するための方法として、就農希望者に対して、栽培場所に関する情報（栽培可能な農作物の種類、量及び収益額）と、育成する農作物に関連する指示とを就農希望者に対して提示し、就農を支援する構成が開示されている（特許文献１参照）。 As a method for solving such a problem, information on a cultivation place (type, amount and profit amount of cultivable crops) and instructions relating to the crops to be cultivated are provided to the applicants for farming. Has been disclosed to support farming (see Patent Document 1).
特開２０１８－１２４９１９号公報Japanese Patent Laid-Open No. 2018-124919
　しかしながら、特許文献１の構成では、特定の栽培場所において、栽培可能な農作物及びこの農作物から得られる収益を提示するものであるため、特定の場所に限らず、高収益が見込める農作物を、就労者が認識することが困難であった。加えて、農作物のみを対象とするものであるため、畜産物について考慮されておらず、高収益が見込める畜産物を、就労者が認識することが困難であった。 However, since the configuration of Patent Document 1 presents agricultural crops that can be cultivated and profits obtained from the agricultural crops in a specific cultivation place, the agricultural products that are expected to have high profits are not limited to specific places, and workers are Was difficult to recognize. In addition, since only agricultural products are targeted, it has been difficult for workers to recognize livestock products that do not consider livestock products and are expected to generate high profits.
　本発明は、高収益の農畜産物を把握することが容易なコンピュータシステム、予測収益提案方法及びプログラムを提供することを目的とする。 An object of the present invention is to provide a computer system, a forecast profit proposing method, and a program that allow easy understanding of highly profitable agricultural and livestock products.
　本発明では、以下のような解決手段を提供する。 The present invention provides the following solutions.
　本発明は、高収益の農畜産物を提案するコンピュータシステムであって、
　前記農畜産物の売上を予測する売上予測手段と、
　前記農畜産物の生産に掛かるコストを算出する生産コスト算出手段と、
　前記農畜産物の販売に掛かるコストを算出する販売コスト算出手段と、
　前記売上、前記生産に掛かるコスト及び前記販売に掛かるコストに基づいて、前記農畜産物の収益を予測する収益予測手段と、
　前記収益を提案する収益提案手段と、
　を備えることを特徴とするコンピュータシステムを提供する。 The present invention is a computer system that proposes highly profitable agricultural and livestock products,
Sales forecasting means for forecasting sales of the agricultural and livestock products,
Production cost calculation means for calculating the cost of producing the agricultural and livestock products,
Sales cost calculating means for calculating the cost of selling the agricultural and livestock products,
Profit forecasting means for forecasting the profit of the agricultural and livestock products based on the sales, the cost for the production and the cost for the sale;
A profit proposing means for proposing the profit,
There is provided a computer system comprising:
　本発明によれば、高収益の農畜産物を提案するコンピュータシステムは、前記農畜産物の売上を予測し、前記農畜産物の生産に掛かるコストを算出し、前記農畜産物の販売に掛かるコストを算出し、前記売上、前記生産に掛かるコスト及び前記販売に掛かるコストに基づいて、前記農畜産物の収益を予測し、前記収益を提案する。 According to the present invention, a computer system that proposes highly profitable agricultural and livestock products predicts the sales of the agricultural and livestock products, calculates the cost of producing the agricultural and livestock products, and sells the agricultural and livestock products. The cost is calculated, the profit of the agricultural and livestock products is predicted based on the sales, the cost of the production, and the cost of the sales, and the profit is proposed.
　本発明は、システムのカテゴリであるが、方法及びプログラム等の他のカテゴリにおいても、そのカテゴリに応じた同様の作用・効果を発揮する。 The present invention is a system category, but also in other categories such as methods and programs, the same action/effect according to the category is exhibited.
　本発明によれば、高収益の農畜産物を把握することが容易なコンピュータシステム、予測収益提案方法及びプログラムを提供することが可能となる。 According to the present invention, it is possible to provide a computer system, a forecasted income proposing method, and a program that make it possible to easily grasp highly profitable agricultural and livestock products.
図１は、予測収益提案システム１の概要を示す図である。FIG. 1 is a diagram showing an outline of the forecast profit proposal system 1. 図２は、予測収益提案システム１の全体構成図である。FIG. 2 is an overall configuration diagram of the forecast profit proposal system 1. 図３は、コンピュータ１０が実行する収益予測処理を示すフローチャートである。FIG. 3 is a flowchart showing a profit forecasting process executed by the computer 10. 図４は、コンピュータ１０が実行する収益提案処理を示すフローチャートである。FIG. 4 is a flowchart showing a profit proposal process executed by the computer 10. 図５は、コンピュータ１０が記録する予測収益データテーブルを模式的に示した図の一例である。FIG. 5 is an example of a diagram schematically showing a predicted profit data table recorded by the computer 10. 図６は、コンピュータ１０が就労者端末に表示させた画面を模式的に示した図の一例である。FIG. 6 is an example of a diagram schematically showing a screen displayed by the computer 10 on the worker terminal. 図７は、コンピュータ１０が就労者端末に表示させた画面を模式的に示した図の一例である。FIG. 7 is an example of a diagram schematically showing a screen displayed on the worker terminal by the computer 10.
　以下、本発明を実施するための最良の形態について図を参照しながら説明する。なお、これはあくまでも一例であって、本発明の技術的範囲はこれに限られるものではない。 Hereinafter, the best mode for carrying out the present invention will be described with reference to the drawings. Note that this is merely an example, and the technical scope of the present invention is not limited to this.
　［予測収益提案システム１の概要］
　本発明の好適な実施形態の概要について、図１に基づいて説明する。図１は、本発明の好適な実施形態である予測収益提案システム１の概要を説明するための図である。予測収益提案システム１は、コンピュータ１０から構成され、高収益の農畜産物を提案するコンピュータシステムである。 [Outline of Forecast Profit Proposal System 1]
An outline of a preferred embodiment of the present invention will be described with reference to FIG. FIG. 1 is a diagram for explaining an outline of a forecasted income proposal system 1 which is a preferred embodiment of the present invention. The forecast profit proposal system 1 is a computer system that includes a computer 10 and proposes highly profitable agricultural and livestock products.
　農畜産物とは、穀物、野菜、果物、花等の農作物と、牛、豚、鶏等の畜産物とである。また、これらの農作物や畜産物そのものだけでなく、加工品等が含まれてもよい。 Agricultural and livestock products are agricultural products such as grains, vegetables, fruits, and flowers, and livestock products such as cows, pigs, and chickens. Further, not only these agricultural products and livestock products themselves, but also processed products and the like may be included.
　なお、予測収益提案システム１は、農畜産業の就労者が所持する就労者端末、その他のコンピュータ等の他の端末や装置類が含まれていてもよい。また、予測収益提案システム１は、例えば、コンピュータ１０等の一台のコンピュータで実現されてもよいし、クラウドコンピュータのように、複数のコンピュータで実現されてもよい。 Note that the forecast profit proposal system 1 may include a worker terminal owned by a worker in the agriculture and livestock industry, other terminals such as a computer, and devices. Further, the forecasted profit proposal system 1 may be realized by a single computer such as the computer 10, or may be realized by a plurality of computers such as a cloud computer.
　コンピュータ１０は、就労者端末等と、公衆回線網等を介して、データ通信可能に接続されており、必要なデータの送受信を実行する。 The computer 10 is connected to a worker terminal or the like via a public line network so as to be able to perform data communication, and executes necessary data transmission/reception.
　コンピュータ１０は、農畜産物の売上を予測する。このとき、コンピュータ１０は、農畜産物の販売動向、消費者の人口分布の少なくとも一つに基づいて、売上を予測する構成であってもよい。コンピュータ１０は、予め記録した又は各種データベース等を参照した各農作物の過去の販売動向（販売額の増減の推移、販売額の推移、育成面積の推移、就労者数の推移等）や、生産場所周辺や販売場所周辺における人口分布に基づいて、この農畜産物の売上を予測する。 The computer 10 predicts sales of agricultural and livestock products. At this time, the computer 10 may be configured to predict sales based on at least one of the sales trend of agricultural and livestock products and the population distribution of consumers. The computer 10 records past sales trends of agricultural products that have been recorded in advance or refer to various databases (changes in sales amount, changes in sales amount, changes in growing area, changes in the number of workers, etc.) and production locations. Predict sales of this agricultural and livestock product based on the population distribution around the area and the sales place.
　コンピュータ１０は、農畜産物の生産に掛かるコストを算出する。このとき、コンピュータ１０は、農畜産物の予測収量、育成条件（気候、土壌、水等）、環境情報（日照、雨量、気温、害虫、病気等）の少なくとも一つを考慮して、この農畜産物の生産に掛かるコストを算出する。コンピュータ１０は、例えば、単位量当りの種苗費や飼料費、設備費、単位量当りの労働時間に基づいた労働費の総計を、生産に掛かるコストとして算出する。コンピュータ１０は、例えば、予測収量に基づいて、労働費や設備費に必要なコストを加算あるいは減算して、生産に掛かるコストを算出する。また、コンピュータ１０は、気候が適切でない農畜産物に対して、気候を調整する設備（ビニルハウス栽培等で必要な温室等）に必要なコストを加算あるいは減算して、生産に掛かるコストを算出する。コンピュータ１０は、例えば、病害虫が発生する時期では、病害虫に必要な労働力や薬剤に必要なコストを加算して算出する。コンピュータ１０は、上述した例を組み合わせて生産に掛かるコストを算出してもよい。 The computer 10 calculates the cost of producing agricultural and livestock products. At this time, the computer 10 considers at least one of the predicted yield of agricultural and livestock products, growing conditions (climate, soil, water, etc.) and environmental information (sunlight, rainfall, temperature, pests, diseases, etc.). Calculate the cost of producing livestock products. The computer 10 calculates, for example, the total of the seedling cost per unit amount, the feed cost, the facility cost, and the labor cost based on the working hours per unit volume as the cost required for the production. The computer 10 adds or subtracts costs required for labor costs and equipment costs based on the predicted yield, for example, to calculate the costs for production. Further, the computer 10 calculates the cost of production by adding or subtracting the cost required for the facility for adjusting the climate (greenhouse required for cultivation of vinyl greenhouses, etc.) to the agricultural and livestock products where the climate is not appropriate. To do. For example, at the time when a pest occurs, the computer 10 calculates by adding the labor required for the pest and the cost required for the medicine. The computer 10 may calculate the cost of production by combining the examples described above.
　コンピュータ１０は、農畜産物の販売に掛かるコストを算出する。このとき、コンピュータ１０は、農畜産物の運搬及び貯蔵に掛かるコストを考慮して、販売に掛かるコストを算出する。コンピュータ１０は、例えば、生産場所から販売場所の物流に必要な輸送費と、生産場所で貯蔵している間の貯蔵費と、販売場所で販売時までに貯蔵している間の貯蔵費とを、主な販売に掛かるコストとして、農畜産物の販売に掛かるコストを算出する。その他にも、コンピュータ１０は、農畜産物の販売に掛かるコストとして、営業費、販売場所の確保に掛かる費用等の別の費用を加味してもよい。 The computer 10 calculates the cost of selling agricultural and livestock products. At this time, the computer 10 calculates the cost of selling in consideration of the cost of transporting and storing the agricultural and livestock products. The computer 10 stores, for example, a transportation cost necessary for physical distribution from the production site to the sales site, a storage cost during storage at the production site, and a storage cost during storage at the sales site by the time of sale. , The cost of selling agricultural and livestock products is calculated as the main cost of selling. In addition, the computer 10 may take into account other costs such as operating costs and costs for securing a selling place as costs for selling agricultural and livestock products.
　コンピュータ１０は、予測した売上、生産に掛かるコスト及び販売に掛かるコストに基づいて、農畜産物の収益を予測する。コンピュータ１０は、予測した売上から、生産に掛かるコスト及び販売に掛かるコストを減算したものを、収益として算出し、算出した結果を、農畜産物の収益として予測する。本例では、説明の簡略化のために、このような計算方式を採用しているが、この計算方式に限らず、所定の係数を用いることや、減価償却費等を考慮することや、専従者控除を考慮すること等を加味したうえで、農畜産物の収益を予測してもよい。 The computer 10 predicts the profit of the agricultural and livestock products based on the predicted sales, costs for production, and costs for sales. The computer 10 calculates profit by subtracting the cost of production and the cost of sales from the predicted sales, and predicts the calculated result as the profit of the agricultural and livestock products. In this example, such a calculation method is adopted for simplification of description, but not limited to this calculation method, a predetermined coefficient is used, depreciation cost, etc. are taken into consideration, and a dedicated The income of agricultural and livestock products may be predicted by taking into consideration the deduction of employees.
　コンピュータ１０は、予測した収益を就労者に提案する。このとき、コンピュータ１０は、収益に加えて、予測した売上、算出した生産に掛かるコスト、算出した販売に掛かるコストの少なくとも一つを併せて提案してもよい。 The computer 10 proposes the predicted profit to the worker. At this time, the computer 10 may propose at least one of the predicted sales, the calculated production cost, and the calculated sales cost in addition to the profit.
　コンピュータ１０は、就労者に対して、農畜産物の育成条件、環境情報の少なくとも一つを考慮して、この農畜産物に適した育成方法を提案してもよい。また、コンピュータ１０は、就労者に対して、生産場所、販売場所の少なくとも一つを提案してもよい。 The computer 10 may suggest to a worker a breeding method suitable for this agricultural and livestock product in consideration of at least one of the agricultural and livestock product growing conditions and environmental information. Further, the computer 10 may suggest at least one of a production place and a sales place to the worker.
　予測収益提案システム１が実行する処理の概要について説明する。 Explain the outline of the processing executed by the forecast profit proposal system 1.
　コンピュータ１０は、農畜産物の売上を予測する（ステップＳ０１）。コンピュータ１０は、各地域（北海道、東北、関東、中部、近畿、四国、九州沖縄、各都道府県、各市町村等）における農畜産物の売上を予測する。コンピュータ１０は、例えば、各地域における農畜産物毎の売上を予測する。このとき、コンピュータ１０は、上述したような農作物の過去の販売動向、各地域、生産場所周辺及び／又は販売場所周辺における消費者の人口分布の少なくとも一つを考慮して、この農畜産物の売上を予測する。 The computer 10 predicts sales of agricultural and livestock products (step S01). The computer 10 predicts the sales of agricultural and livestock products in each region (Hokkaido, Tohoku, Kanto, Chubu, Kinki, Shikoku, Kyushu Okinawa, each prefecture, each municipality, etc.). The computer 10 predicts sales for each agricultural and livestock product in each region, for example. At this time, the computer 10 considers at least one of the above-mentioned past sales trend of the agricultural products, the distribution of the population of consumers in each region, around the production place, and/or around the sales place as described above. Predict sales.
　コンピュータ１０は、農畜産物の生産に掛かるコストを算出する（ステップＳ０２）。コンピュータ１０は、上述したような農畜産物の予測収量、育成条件、環境情報の少なくとも一つを考慮して、農畜産物の生産に掛かるコストを算出する。 The computer 10 calculates the cost of producing agricultural and livestock products (step S02). The computer 10 calculates the cost of producing agricultural and livestock products in consideration of at least one of the above-mentioned predicted yield of agricultural and livestock products, growing conditions, and environmental information.
　コンピュータ１０は、農畜産物の販売に掛かるコストを算出する（ステップＳ０３）。コンピュータ１０は、上述したような農畜産物の輸送費及び貯蔵費に基づいて、販売に掛かるコストを算出する。 The computer 10 calculates the cost of selling agricultural and livestock products (step S03). The computer 10 calculates the cost of selling based on the transportation cost and the storage cost of the agricultural and livestock products as described above.
　コンピュータ１０は、予測した売上と、算出した生産及び販売に掛かるコストに基づいて、農畜産物の収益を予測する（ステップＳ０４）。コンピュータ１０は、上述したような売上から生産及び販売に掛かるコストを減算したものを、農畜産物の収益として算出する。コンピュータ１０は、この算出結果を、農畜産物の収益として予測することになる。 The computer 10 predicts the profit of the agricultural and livestock products based on the predicted sales and the calculated production and sales costs (step S04). The computer 10 calculates the value obtained by subtracting the cost required for production and sales from the above-mentioned sales as the income of the agricultural and livestock products. The computer 10 predicts this calculation result as the income of the agricultural and livestock products.
　コンピュータ１０は、予測した収益を就労者に提案する（ステップＳ０５）。コンピュータ１０は、就労者が指定した農畜産物の名称に基づいて、この農畜産物における予測した収益を就労者に提案する。また、コンピュータ１０は、就労者が指定した地域に基づいて、この地域における高収益の農畜産物の名称及びこの農畜産物における予測した収益を就労者に提案する。また、コンピュータ１０は、就労者の現在地に基づいて、この現在地周辺における地域における高収益の農畜産物の名称及びこの農畜産物における予測した収益を就労者に提案する。また、コンピュータ１０は、就労者が指定した売上、生産コスト及び／又は販売コストを満たす農畜産物の名称及びこの農畜産物における予測した収益を提案する。また、コンピュータ１０は、これらの例以外の場合においても、同様に、就労者に予測した収益を提案する。このとき、コンピュータ１０は、収益に加えて、予測した売上、算出した生産に掛かるコスト、算出した販売に掛かるコストの少なくとも一つを併せて提案してもよい。 The computer 10 proposes the predicted profit to the worker (step S05). The computer 10 proposes to the worker the predicted profit of this agricultural and livestock product based on the name of the agricultural and livestock product designated by the worker. In addition, the computer 10 proposes to the worker the name of the highly profitable agricultural and livestock product in this area and the predicted profit in this agricultural and livestock product based on the area designated by the worker. In addition, the computer 10 proposes to the worker the name of the highly profitable agricultural and livestock product in the area around this current position and the predicted profit of this agricultural and livestock product based on the current position of the worker. The computer 10 also proposes the name of the agricultural and livestock product that meets the sales, production cost, and/or selling cost specified by the worker and the predicted profit for this agricultural and livestock product. In addition, in the cases other than these examples, the computer 10 similarly proposes the predicted profit to the worker. At this time, the computer 10 may propose at least one of the predicted sales, the calculated production cost, and the calculated sales cost in addition to the profit.
　なお、コンピュータ１０は、収益だけでなく、農畜産物の育成条件、環境情報の少なくとも一つを考慮して、農畜産物に適した育成方法を提案してもよい。また、コンピュータ１０は、この農畜産物の生産場所、販売場所の少なくとも一つを提案してもよい。 Note that the computer 10 may propose a cultivation method suitable for agricultural and livestock products in consideration of at least one of agricultural and livestock product growth conditions and environmental information in addition to profits. Further, the computer 10 may propose at least one of a production place and a sale place of this agricultural and livestock product.
　以上が、予測収益提案システム１の概要である。 The above is the outline of the forecast profit proposal system 1.
　［予測収益提案システム１のシステム構成］
　図２に基づいて、本発明の好適な実施形態である予測収益提案システム１のシステム構成について説明する。図２は、本発明の好適な実施形態である予測収益提案システム１のシステム構成を示す図である。図２において、予測収益提案システム１は、コンピュータ１０から構成され、高収益の農畜産物を提案するコンピュータシステムである。 [System configuration of forecast profit proposal system 1]
Based on FIG. 2, a system configuration of the forecast profit proposing system 1 which is a preferred embodiment of the present invention will be described. FIG. 2 is a diagram showing a system configuration of the forecast profit proposal system 1 according to the preferred embodiment of the present invention. In FIG. 2, the forecast profit proposal system 1 is a computer system which includes a computer 10 and proposes highly profitable agricultural and livestock products.
　なお、予測収益提案システム１は、上述した就労者端末や他のコンピュータ等の他の端末や装置類が含まれていてもよい。また、予測収益提案システム１は、例えば、コンピュータ１０等の１台のコンピュータ又はクラウドコンピュータのように複数のコンピュータで実現されてもよい。 Note that the forecasted profit proposal system 1 may include other terminals and devices such as the above-mentioned worker terminal and other computers. In addition, the predicted profit proposal system 1 may be realized by a single computer such as the computer 10 or a plurality of computers such as a cloud computer.
　コンピュータ１０は、図示していない上述した就労者端末等と、公衆回線網等を介してデータ通信可能に接続されており、必要なデータの送受信を実行する。 The computer 10 is connected to the above-described worker terminal (not shown) and the like so as to be able to perform data communication via a public line network, etc., and executes necessary data transmission/reception.
　コンピュータ１０は、ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）、ＲＡＭ（Ｒａｎｄｏｍ　Ａｃｃｅｓｓ　Ｍｅｍｏｒｙ）、ＲＯＭ（Ｒｅａｄ　Ｏｎｌｙ　Ｍｅｍｏｒｙ）等を備え、通信部として、他の端末や装置等と通信可能にするためのデバイス、例えば、ＩＥＥＥ８０２．１１に準拠したＷｉ―Ｆｉ（Ｗｉｒｅｌｅｓｓ―Ｆｉｄｅｌｉｔｙ）対応デバイス等を備える。また、コンピュータ１０は、記録部として、ハードディスクや半導体メモリ、記録媒体、メモリカード等によるデータのストレージ部を備える。また、コンピュータ１０は、処理部として、各種処理を実行する各種デバイス等を備える。 The computer 10 includes a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), and the like, and a device for enabling communication with other terminals or devices as a communication unit, for example, the IEEE 802. .. 11 compliant Wi-Fi (Wireless-Fidelity) compatible device and the like. Further, the computer 10 includes, as a recording unit, a hard disk, a semiconductor memory, a recording medium, a data storage unit such as a memory card. Further, the computer 10 includes various devices that execute various processes as a processing unit.
　コンピュータ１０において、制御部が所定のプログラムを読み込むことにより、通信部と協働して、提案要求取得モジュール２０、収益提案モジュール２１、育成方法提案モジュール２２、場所提案モジュール２３を実現する。また、コンピュータ１０において、制御部が所定のプログラムを読み込むことにより、記録部と協働して、記録モジュール３０を実現する。また、コンピュータ１０において、制御部が所定のプログラムを読み込むことにより、処理部と協働して、売上予測モジュール４０、生産コスト算出モジュール４１、販売コスト算出モジュール４２、収益予測モジュール４３、提案内容作成モジュール４４を実現する。 In the computer 10, the control unit reads a predetermined program to realize the proposal request acquisition module 20, the profit proposal module 21, the training method proposal module 22, and the place proposal module 23 in cooperation with the communication unit. Further, in the computer 10, the control unit reads a predetermined program to realize the recording module 30 in cooperation with the recording unit. Further, in the computer 10, the control unit reads a predetermined program, thereby cooperating with the processing unit, the sales prediction module 40, the production cost calculation module 41, the sales cost calculation module 42, the profit prediction module 43, and the proposal content creation. The module 44 is realized.
　［収益予測処理］
　図３に基づいて、予測収益提案システム１が実行する収益予測処理について説明する。図３は、コンピュータ１０が実行する収益予測処理のフローチャートを示す図である。上述した各モジュールが実行する処理について、本処理に併せて説明する。 [Revenue forecasting process]
The profit prediction process executed by the predicted profit proposal system 1 will be described with reference to FIG. FIG. 3 is a diagram showing a flowchart of the profit prediction process executed by the computer 10. The processing executed by each module described above will be described together with this processing.
　売上予測モジュール４０は、農畜産物の売上を予測する（ステップＳ１０）。ステップＳ１０において、売上予測モジュール４０は、各地域等の所定の範囲における農畜産物の売上を予測する。売上予測モジュール４０は、例えば、各地域における一の農畜産物における売上を予測する。農畜産物が葡萄である場合、この葡萄の所定の範囲における売上を予測する。売上予測モジュール４０は、様々な農畜産物において、所定の範囲における売上を予測することになる。 The sales forecasting module 40 forecasts the sales of agricultural and livestock products (step S10). In step S10, the sales forecasting module 40 forecasts sales of agricultural and livestock products in a predetermined range such as each region. The sales prediction module 40 predicts the sales of one agricultural and livestock product in each region, for example. If the agricultural and livestock products are grapes, forecast the sales of the grapes within a given range. The sales forecasting module 40 forecasts sales of various agricultural and livestock products in a predetermined range.
　このとき、売上予測モジュール４０は、農畜産物の販売動向及び／又は消費者の人口分布を考慮して売上を予測する。例えば、売上予測モジュール４０は、販売動向として、所定の範囲における葡萄の販売額の増減の推移、販売額そのものの推移、販売量の推移、育成面積の推移、就労者の推移等を、記録モジュール３０に予め記録したデータベースや他のコンピュータ等が記録するデータベース等を参照することにより取得する。また、売上予測モジュール４０は、消費者の人口分布として、所定の範囲、農畜産物の生産場所周辺及び／又は農畜産物の販売場所周辺における消費者の人口分分布を、記録モジュール３０に予め記録したデータベースや他のコンピュータ等が記録するデータベースを参照することにより取得する。売上予測モジュール４０は、この販売動向、消費者の人口分布の少なくとも一つに基づいて、農畜産物の売上を予測する。 At this time, the sales forecasting module 40 forecasts sales in consideration of the sales trend of agricultural and livestock products and/or the population distribution of consumers. For example, the sales forecasting module 40 records, as a sales trend, a change in the sales amount of grapes within a predetermined range, a change in the sales amount itself, a change in the sales amount, a change in the growing area, a change in the number of workers, etc. It is acquired by referring to a database previously recorded in 30, a database recorded by another computer, or the like. In addition, the sales forecasting module 40 pre-stores the distribution distribution of consumers in a predetermined range, around the production place of agricultural and livestock products, and/or around the selling place of agricultural and livestock products in the recording module 30 as the population distribution of consumers. It is acquired by referring to the recorded database or the database recorded by another computer. The sales prediction module 40 predicts the sales of agricultural and livestock products based on at least one of the sales trend and the population distribution of consumers.
　売上予測モジュール４０が売上を予測する一例について説明する。売上予測モジュール４０は、販売動向として、販売額そのものの推移と、販売量の推移とに基づいて、これから販売する農畜産物の販売額及び販売量を予測する。売上予測モジュール４０は、予測した販売額と販売量とを乗算することにより、農畜産物の売上を予測する。また、売上予測モジュール４０は、人口分布として、販売場所周辺におけるこの農畜産物を購入する消費者の割合や総数と、平均的な販売額とに基づいて、農畜産物の売上を予測する。売上予測モジュール４０は、購入する消費者の割合や総数と販売額とを乗算することにより、農畜産物の売上を予測する。 An example of the sales forecast module 40 forecasting sales will be described. The sales prediction module 40 predicts the sales amount and sales amount of agricultural and livestock products to be sold, based on the changes in the sales amount itself and the changes in the sales amount as the sales trend. The sales prediction module 40 predicts sales of agricultural and livestock products by multiplying the predicted sales amount by the sales amount. Further, the sales forecasting module 40 forecasts the sales of agricultural and livestock products based on the average distribution amount and the ratio and total number of consumers who purchase the agricultural and livestock products around the sales place as the population distribution. The sales prediction module 40 predicts the sales of agricultural and livestock products by multiplying the sales amount by the ratio or total number of consumers who purchase.
　なお、売上予測モジュール４０は、販売動向及び人口分布に基づいて、農畜産物の売上を予測する構成であってもよい。この場合、例えば、売上予測モジュール４０は、販売額そのもの推移と、販売量の推移と、販売場所周辺における人口分布とに基づいて、農畜産物の売上を予測する。売上予測モジュール４０は、販売額の推移に基づいて、この農畜産物の販売額を予測する。売上予測モジュール４０は、販売場所における人口分布に基づいて、この農畜産物を購入する消費者の割合や総数に基づいて、販売量を予測する。売上予測モジュール４０は、この予測した販売額に、予測した販売量を乗算することにより、この農畜産物の売上を予測する。 The sales prediction module 40 may be configured to predict sales of agricultural and livestock products based on sales trends and population distribution. In this case, for example, the sales prediction module 40 predicts the sales of agricultural and livestock products based on the transition of the sales amount itself, the transition of the sales amount, and the population distribution around the sales place. The sales prediction module 40 predicts the sales amount of this agricultural and livestock product based on the change in the sales amount. The sales forecasting module 40 forecasts the sales volume based on the population distribution at the selling place and based on the ratio and total number of consumers who purchase the agricultural and livestock products. The sales prediction module 40 predicts the sales of this agricultural and livestock product by multiplying the predicted sales amount by the predicted sales amount.
　また、上述した売上予測モジュール４０が売上を予測する計算方法は、あくまでも例に過ぎず、上述した例に限られるものではなく、適宜変更可能である。 The above-described calculation method by which the sales prediction module 40 predicts sales is merely an example, and is not limited to the above-described example, and can be changed as appropriate.
　生産コスト算出モジュール４１は、農畜産物の生産に掛かるコスト（生産コスト）を算出する（ステップＳ１１）。ステップＳ１１において、生産コスト算出モジュール４１は、農畜産物の予測収量、育成条件（気候、土壌、水等）、環境情報（日照、雨量、気温、害虫、病気等）の少なくとも一つを考慮して、農畜産物の生産コストを算出する。生産コスト算出モジュール４１は、例えば、単位量当りの種苗費や飼料費、設備費、単位量当りの労働時間に基づいた労働費等の総計を、生産コストとして算出する。このとき、生産コスト算出モジュール４１は、予測収量、育成条件、環境情報の少なくとも一つを、この生産コストに加味し、最終的な生産コストを算出する。 The production cost calculation module 41 calculates the cost (production cost) required to produce agricultural and livestock products (step S11). In step S11, the production cost calculation module 41 considers at least one of the predicted yield of agricultural and livestock products, growing conditions (climate, soil, water, etc.), and environmental information (sunshine, rainfall, temperature, pests, diseases, etc.). Calculate the production cost of agricultural and livestock products. The production cost calculation module 41 calculates, for example, the total of the seedling cost per unit amount, the feed cost, the equipment cost, the labor cost based on the working hours per unit amount, and the like as the production cost. At this time, the production cost calculation module 41 calculates the final production cost by adding at least one of the predicted yield, the growing condition, and the environmental information to this production cost.
　生産コスト算出モジュール４１が生産コストを算出する一例について説明する。生産コスト算出モジュール４１は、予測収益が通常よりも多い場合、最終的な出荷量の調整に掛かる費用を、生産コストに加算して、最終的な生産コストを算出する。また、生産コスト算出モジュール４１は、気候が適切でない状況が予測される場合、育成状況を調整する設備（温室等）に掛かる費用を、生産コストに加味して、最終的な生産コストを算出する。また、生産コスト算出モジュール４１は、病害虫の発生が予測される場合、病害虫駆除に必要な労働力や薬剤に掛かる費用を、生産コストに加味して、最終的な生産コストを算出する。 An example of the production cost calculation module 41 calculating the production cost will be described. The production cost calculation module 41 calculates the final production cost by adding the cost required for adjusting the final shipping amount to the production cost when the predicted profit is higher than usual. Further, the production cost calculation module 41 calculates the final production cost by adding the cost required for the facility (greenhouse, etc.) for adjusting the growing condition to the production cost when the climate is predicted to be unsuitable. .. Further, when the occurrence of pests is predicted, the production cost calculation module 41 calculates the final production cost by adding the costs for the labor force and the medicine required for pest control to the production cost.
　なお、生産コスト算出モジュール４１は、上述した予測収量、育成条件、環境情報の複数を組み合わせたものを考慮して、農畜産物の生産に掛かるコストを算出してもよい。例えば、上述した例において、生産コスト算出モジュール４１は、育成状況を調整する設備に掛かる費用と、病害虫駆除に掛かる費用とを、生産コストに加味して、最終的な生産コストを算出する。 Note that the production cost calculation module 41 may calculate the cost of producing agricultural and livestock products in consideration of a combination of the above-mentioned predicted yield, growing conditions, and environmental information. For example, in the above-mentioned example, the production cost calculation module 41 calculates the final production cost by adding the cost required for the facility for adjusting the growing condition and the cost required for pest control to the production cost.
　また、生産コスト算出モジュール４１は、他の生産に掛かるコストをさらに加味したうえで、最終的な生産コストを算出してもよい。また、生産コスト算出モジュール４１は、他の条件を加味して、最終的な生産コストを算出してもよい。 Further, the production cost calculation module 41 may calculate the final production cost after further considering the costs of other productions. Further, the production cost calculation module 41 may calculate the final production cost by adding other conditions.
　販売コスト算出モジュール４２は、農畜産物の販売に掛かるコスト（販売コスト）を算出する（ステップＳ１２）。ステップＳ１２において、販売コスト算出モジュール４２は、農畜産物の運搬及び貯蔵に掛かるコストを考慮して、最終的な販売コストとして算出する。運搬に掛かるコストとしては、例えば、農畜産物の生産場所から販売場所に運搬するために必要な輸送費が挙げられる。貯蔵に掛かるコストとしては、例えば、農畜産物の生産場所における貯蔵に必要な貯蔵費、農畜産物の販売場所における貯蔵に必要な貯蔵費が挙げられる。販売コスト算出モジュール４２は、運搬及び貯蔵に掛かるコストを、実質的な販売コストとして、最終的な販売コストを算出する。 The sales cost calculation module 42 calculates a cost (sales cost) required to sell agricultural and livestock products (step S12). In step S12, the selling cost calculation module 42 calculates the final selling cost in consideration of the costs of transporting and storing the agricultural and livestock products. Examples of transportation costs include transportation costs required to transport agricultural and livestock products from a production site to a sales site. Examples of the storage costs include storage costs required for storage of agricultural and livestock products at the production site and storage costs required for storage of agricultural and livestock products at the sales site. The selling cost calculation module 42 calculates the final selling cost by using the costs for transportation and storage as the substantial selling cost.
　なお、販売コスト算出モジュール４２は、上述したものに加えて、営業費、販売場所の確保に掛かる費用等の別の費用をさらに考慮したうえで、最終的な販売コストを算出してもよい。 Note that the selling cost calculation module 42 may calculate the final selling cost by further considering other costs such as operating costs and costs for securing a selling place in addition to the above-mentioned ones.
　収益予測モジュール４３は、予測した売上、算出した生産コスト及び販売コストに基づいて、農畜産物の収益を予測する（ステップＳ１３）。ステップＳ１３において、収益予測モジュール４３は、予測した売上から、算出した生産コスト及び販売コストを減算したものを収益として算出する。すなわち、収益予測モジュール４３は、この算出結果を、収益として予測する。 The profit prediction module 43 predicts the profit of the agricultural and livestock products based on the predicted sales, the calculated production cost and the sales cost (step S13). In step S13, the profit prediction module 43 calculates the profit by subtracting the calculated production cost and sales cost from the predicted sales. That is, the profit prediction module 43 predicts this calculation result as profit.
　なお、収益予測モジュール４３は、上述した計算方式に限らず、予測した売上、算出した生産コスト及び販売コストに所定の係数を用いる計算方式、減価償却費や専従者控除等の他の費用や控除を考慮する計算方式等の他の計算方式に基づいて、収益を予測してもよい。収益予測モジュール４３が収益を予測する計算方式は、適宜変更可能である。 Note that the profit forecasting module 43 is not limited to the above-described calculation method, and other calculation methods such as a calculation method that uses a predetermined coefficient for the predicted sales, the calculated production cost, and the sales cost, depreciation costs, deductions for full-time employees, etc. The profit may be predicted based on another calculation method such as a calculation method that takes into consideration. The calculation method by which the profit prediction module 43 predicts the profit can be changed as appropriate.
　記録モジュール３０は、農畜産物の名称、農畜産物の生産場所、予測した売上、算出した生産コスト、算出した販売コスト、予測した収益を対応付けて予測収益データとして記録する（ステップＳ１４）。ステップＳ１４において、記録モジュール３０は、農畜産物の名称として、種類名、品種名、商品名、加工品名等を記録し、生産場所として、上述した所定の範囲を記録し、売上として、上述した予測したものを記録し、生産コストとして、上述した算出したものを記録し、販売コストとして、上述した算出したものを記録し、収益として、上述した予測したものを記録する。 The recording module 30 records the name of the agricultural and livestock product, the production location of the agricultural and livestock product, the predicted sales, the calculated production cost, the calculated sales cost, and the predicted profit in association with each other as predicted profit data (step S14). In step S14, the recording module 30 records the type name, the variety name, the product name, the processed product name, etc. as the names of the agricultural and livestock products, records the above-mentioned predetermined range as the production place, and the sales as described above. The predicted value is recorded, the calculated value is recorded as the production cost, the calculated value is recorded as the sales cost, and the predicted value is recorded as the profit.
　また、記録モジュール３０は、この予測収益データに、さらに、該当する所定の範囲における一般的な育成方法及び販売場所を併せて記録する。 Further, the recording module 30 further records general forecasting methods and sales places in the applicable predetermined range in addition to the forecast profit data.
　なお、記録モジュール３０は、上述した予測収益データに上述した例以外のものを併せて記録してもよい。また、記録モジュール３０は、上述した予測収益データに、必ずしも上述した例を全て記録する必要性はなく、適宜変更可能である。 Note that the recording module 30 may record the above-mentioned forecast profit data other than the above-mentioned example together. In addition, the recording module 30 does not necessarily need to record all the above-described examples in the above-described predicted profit data, and can be changed as appropriate.
　［予測収益データテーブル］
　図５に基づいて、記録モジュール３０が記録する予測収益データについて説明する。図５は、記録モジュール３０が予測収益データを、テーブル形式で記録した一例を模式的に示す図である。図５において、記録モジュール３０は、予測収益データとして、管理番号、農畜産物名、生産場所、育成方法、売上、生産コスト、販売コスト、収益、販売場所を関連付けてテーブル形式で記録する。このとき、記録モジュール３０は、収益性が高いものから順番に管理番号を付与している。記録モジュール３０は、この予測収益テーブルにおいて、例えば、管理番号０００１には、農畜産物名が鶏、生産場所が宮崎県、育成方法が平飼い、売上が８０００万円、生産コストが４０００万円、販売コストが１０００万円、収益が３０００万円、販売場所が福岡県を登録する。他の農畜産物についても同様である。仮に、記録モジュール３０が、新たに予測収益データを記録した際、既に記録している予測収益データにおける予測収益と、今回新たに記録する予測収益データにおける予測収益とを比較して、収益の高いもの順の位置を維持した場所に、新たに記録する予測収益データを追加する。このとき、記録モジュール３０は、管理番号を追加された予測収益データに基づいて、変更する。 [Predicted Revenue Data Table]
The predicted profit data recorded by the recording module 30 will be described with reference to FIG. FIG. 5 is a diagram schematically showing an example in which the recording module 30 records the predicted profit data in a table format. In FIG. 5, the recording module 30 records the management number, the name of agricultural and livestock products, the production location, the breeding method, the sales, the production cost, the sales cost, the revenue, and the sales location in a table format in association with each other as the predicted revenue data. At this time, the recording module 30 gives management numbers in order from the one with the highest profitability. In the predicted profit table, the recording module 30 has, for example, a management number 0001 with a farm and livestock product name of chicken, a production place of Miyazaki Prefecture, a breeding method of flat breeding, sales of 80 million yen, and production cost of 40 million yen. The sales cost is 10 million yen, the profit is 30 million yen, and the sales place is Fukuoka prefecture. The same applies to other agricultural and livestock products. If the recording module 30 newly records the predicted profit data, the recorded profit is compared with the predicted profit in the already recorded predicted profit data and the predicted profit in the newly recorded predicted profit data, and the profit is high. Add the newly recorded forecast revenue data to the place where the order position is maintained. At this time, the recording module 30 changes the management number based on the added predicted profit data.
　なお、予測収益データテーブルは、順番を変更することなく、新たに記録された予測収益データを、最下位の位置に追加する構成であってもよい。 Note that the forecast revenue data table may have a configuration in which newly recorded forecast revenue data is added to the lowest position without changing the order.
　以上が、収益予測処理である。 The above is the profit forecasting process.
　［収益提案処理］
　図４に基づいて、予測収益提案システム１が実行する収益提案処理について説明する。図４は、コンピュータ１０が実行する収益提案処理のフローチャートを示す図である。上述した各モジュールが実行する処理について、本処理に併せて説明する。 [Profit Proposal Processing]
The profit proposing process executed by the predicted profit proposing system 1 will be described with reference to FIG. FIG. 4 is a diagram showing a flowchart of the profit proposing process executed by the computer 10. The processing executed by each module described above will be described together with this processing.
　提案要求取得モジュール２０は、就労者から予測収益データの提案要求を取得する（ステップＳ２０）。ステップＳ２０において、提案要求取得モジュール２０は、就労者端末等から、収益データの提案要求を取得する。この提案要求には、就労者が指定する収益データの条件が含まれる。この条件としては、例えば、自身の位置情報に基づいた自身の周辺地域における農畜産物の予測収益データ、所定個数の予測収益データ、所定の農畜産物の予測収益データ、就労者端末に表示した地図上において指定された地域や場所に基づいた予測収益データ、就労者が指定した売上、生産コスト及び／又は販売コストを満たす農畜産物の予測収益データが挙げられる。 The proposal request acquisition module 20 acquires a proposal request for predicted profit data from a worker (step S20). In step S20, the proposal request acquisition module 20 acquires a proposal request for profit data from a worker terminal or the like. This proposal request includes a condition for profit data specified by the worker. As this condition, for example, the predicted profit data of agricultural and livestock products in the surrounding area based on the own position information, the predetermined number of predicted profit data, the predicted profit data of the predetermined agricultural and livestock products, displayed on the worker terminal For example, the forecast profit data based on the area or place designated on the map, and the forecast profit data of agricultural and livestock products satisfying the sales, the production cost and/or the sales cost designated by the worker can be given.
　提案内容作成モジュール４４は、取得した予測収益データの提案要求に基づいて、この就労者に対する予測収益データの提案内容を作成する（ステップＳ２１）。ステップＳ２１において、提案内容作成モジュール４４は、上述した提案要求に含まれる条件に基づいて、提案内容を作成する。上述した例では、提案内容作成モジュール４４は、この就労者の位置情報に基づいた周辺地域における予測収益データを、予測収益データテーブルから収益の高い順番に、所定の個数抽出し、提案内容として作成する。また、提案内容作成モジュール４４は、予測収益データテーブルから、地域を問わずに、収益の高い順番に、所定の個数抽出し、提案内容として作成する。また、提案内容作成モジュール４４は、予測収益データテーブルから、就労者が指定した農畜産物に該当する予測収益データを、収益の高い順番に、所定の個数抽出し、提案内容として作成する。また、提案内容作成モジュール４４は、この就労者が指定した地域や場所における予測収益データを、予測収益データテーブルから収益の高い順番に、所定の個数抽出し、提案内容として作成する。また、提案内容作成モジュール４４は、予測収益データテーブルから、就労者が指定した売上、生産コスト及び／又は販売コストに一致又は近似する予測収益データを、収益の高い順番に、所定の個数抽出し、提案内容として作成する。 The proposal content creation module 44 creates the proposal content of the predicted profit data for this worker based on the acquired request request for the predicted profit data (step S21). In step S21, the proposal content creation module 44 creates the proposal content based on the conditions included in the proposal request described above. In the example described above, the proposal content creation module 44 extracts a predetermined number of predicted profit data in the surrounding area based on the position information of the worker from the predicted profit data table in descending order of profit and creates the proposal content. To do. In addition, the proposal content creation module 44 extracts a predetermined number of items in descending order of profit regardless of region from the predicted profit data table, and creates the proposal contents. Further, the proposal content creation module 44 extracts a predetermined number of predicted profit data corresponding to the agricultural and livestock products designated by the worker from the predicted profit data table in descending order of profit, and creates the proposal content. Further, the proposal content creation module 44 extracts a predetermined number of predicted profit data in the area or place designated by the worker in the descending order of profit from the predicted profit data table, and creates the proposal contents. In addition, the proposal content creation module 44 extracts a predetermined number of pieces of predicted profit data that match or approximate the sales, production cost, and/or sales cost designated by the worker from the predicted profit data table in descending order of profit. , Create as a proposal content.
　加えて、提案内容作成モジュール４４は、予測収益データにおける育成方法に対して、育成条件、環境情報の少なくとも一つを考慮して、農畜産物に適した育成方法を、提案内容として作成する。例えば、提案内容作成モジュール４４は、予測収益データにおける育成方法が露地栽培である場合、この地域における気候が温暖である場合、出荷時期を早めることによる収益性の向上を図るためのハウス栽培等の促成栽培を、提案内容として作成する。また、提案内容作成モジュール４４は、予測収益データにおける育成方法が、露地栽培である場合、この地域における雨量が平均的な地域よりも多い場合、雨対策としてのビニールハウス栽培を、提案内容として作成する。 In addition, the proposal content creation module 44 creates, as the content of the proposal, a training method suitable for agricultural and livestock products in consideration of at least one of the training conditions and environmental information with respect to the training method in the forecast profit data. For example, the proposal content creation module 44 uses, for example, greenhouse cultivation for improving profitability by accelerating the shipment time when the cultivation method in the forecast profit data is open field cultivation, when the climate in this area is mild. Create forcing culture as a proposal. In addition, the proposal content creation module 44 creates a greenhouse greenhouse cultivation as a rain measure as the proposal content when the growing method in the forecast profit data is open field cultivation and when the amount of rainfall in this area is larger than the average area. To do.
　また、提案内容作成モジュール４４は、予測収益データにおける生産場所、販売場所の少なくとも一つを、提案内容として作成する。 Also, the proposal content creation module 44 creates at least one of the production location and the sales location in the forecast profit data as the proposal content.
　その結果、提案内容作成モジュール４４は、予測収益に加えて、予測売上、生産コスト、販売コスト、育成方法、生産場所及び販売場所を提案内容として作成することになる。 As a result, the proposal content creation module 44 creates, in addition to the predicted profit, the predicted sales, the production cost, the sales cost, the training method, the production location and the sales location as the proposal content.
　なお、提案内容作成モジュール４４は、育成方法に対して、育成条件及び環境情報を考慮して、農畜産物に適した育成方法を、提案内容として作成してもよい。また、提案内容作成モジュール４４は、販売場所に対して、生産場所及び販売場所を提案内容として作成してもよい。 Note that the suggestion content creation module 44 may create a breeding method suitable for agricultural and livestock products as a suggestion content in consideration of the breeding condition and environmental information for the breeding method. Further, the proposal content creation module 44 may create the production location and the sales location as the proposal content for the sales location.
　また、提案内容作成モジュール４４は、提案内容として、予測収益に加えて、予測売上、生産コスト、販売コスト、育成方法、生産場所、販売場所のうち、少なくとも一つを提案内容として作成する構成であってもよい。また、提案内容作成モジュール４４は、提案内容として、予測収益に加えて、測売上、生産コスト、販売コストのうち、少なくとも一つを提案内容として作成する構成であってもよい。また、提案内容作成モジュール４４は、提案内容として、予測収益に加えて、育成方法及び／又は生産場所や販売場所を提案内容として作成する構成であってもよい。また、提案内容作成モジュール４４は、提案内容として、予測収益に加えて、予測売上、生産コスト、販売コストのうち、少なくとも一つ、さらに、育成方法及び／又は生産場所や販売場所を提案内容として作成する構成であってもよい。 Further, the proposal content creation module 44 is configured to create, as a proposal content, at least one of predicted sales, production cost, sales cost, training method, production location, and sales location in addition to the expected profit as the proposal content. It may be. Further, the proposal content creation module 44 may be configured to create, as the proposal content, at least one of the measured sales, the production cost, and the sales cost as the proposal content in addition to the predicted profit. In addition, the proposal content creation module 44 may be configured to create, as the proposal content, the training method and/or the production place or the sales place as the proposal content in addition to the predicted profit. Further, the proposal content creation module 44 includes, as the proposal content, at least one of the predicted sales, the production cost, and the sales cost in addition to the predicted profit, and further, the training method and/or the production place or the sales place as the proposal content. The configuration may be created.
　収益提案モジュール２１は、就労者に収益を提案する（ステップＳ２２）。ステップＳ２２において、収益提案モジュール２１は、作成した提案内容を、就労者端末に送信し、この就労者端末に提案内容を表示させることにより、収益を提案する。このとき、収益提案モジュール２１は、作成した提案内容に含まれる予測売上、生産コスト、販売コスト、育成方法、生産場所及び販売場所の何れか又は複数の組み合わせを併せて提案する。 The profit proposal module 21 proposes a profit to the worker (step S22). In step S22, the profit proposing module 21 sends the created proposal contents to the worker terminal and displays the proposal contents on the worker terminal to propose a profit. At this time, the profit proposing module 21 also proposes any one or a combination of predicted sales, production costs, sales costs, training methods, production locations and sales locations included in the created proposal content.
　なお、農畜産物に適した育成方法は、育成方法提案モジュール２２により提案されてもよい。また、農畜産物の生産場所、販売場所は、場所提案モジュール２３により提案されてもよい。この場合、後述する例において、育成方法提案モジュール２２が育成方法を提案し、場所提案モジュール２３が生産場所、販売場所を提案する構成となればよい。 The breeding method suitable for agricultural and livestock products may be suggested by the breeding method suggestion module 22. Further, the place of production and the place of sale of the agricultural and livestock products may be suggested by the place suggestion module 23. In this case, in the example described later, the raising method suggesting module 22 may propose a raising method and the place suggesting module 23 may suggest a production place and a selling place.
　図６及び図７に基づいて、収益提案モジュール２１が提案する収益について説明する。図６は、収益提案モジュール２１が就労者端末に表示させた画面の一例を模式的に示す図である。図７は、収益提案モジュール２１が就労者端末に表示させた別の画面の一例を模式的に示す図である。 The profit proposed by the profit proposal module 21 will be described based on FIGS. 6 and 7. FIG. 6 is a diagram schematically showing an example of a screen displayed on the worker terminal by the profit proposing module 21. FIG. 7 is a diagram schematically showing an example of another screen displayed on the worker terminal by the profit proposing module 21.
　図６において、収益提案モジュール２１は、就労者端末に、収益提案画面１００を表示させる。この収益提案画面１００は、上述した提案内容作成モジュール４４が、予測収益データテーブルから、地域を問わずに、収益の高い順番に、所定の個数抽出し、作成した提案内容に基づくものである。このとき、収益提案モジュール２１は、就労者端末に、収益提案画面１００として、管理番号、農畜産物の名称、予測収益、予測売上、生産コスト、販売コスト、育成方法、生産場所、販売場所を表示させる。この表示させる項目については、上述した提案内容作成モジュール４４が作成する提案内容に基づいたものである。収益提案モジュール２１は、各農畜産物を、収益が高い順番に表示させる。本例では、収益提案モジュール２１は、鶏、牛乳、葡萄、・・・、の順番に収益性が高いことを、管理番号の順番に基づいて表示させている。収益提案モジュール２１は、各農畜産物において、上述した各項目を表示させる。 In FIG. 6, the profit proposal module 21 causes the worker terminal to display the profit proposal screen 100. This profit proposal screen 100 is based on the proposal contents created by the above-described proposal content creation module 44 by extracting a predetermined number of profitable data tables in descending order of profit regardless of region. At this time, the profit proposing module 21 displays the management number, the name of the agricultural and livestock products, the predicted profit, the predicted sales, the production cost, the sales cost, the breeding method, the production place, and the sales place as the profit proposal screen 100 on the worker terminal. Display it. The items to be displayed are based on the proposal contents created by the above-mentioned proposal contents creating module 44. The profit proposing module 21 displays each agricultural and livestock product in descending order of profit. In this example, the profit proposing module 21 displays that the profitability is high in the order of chicken, milk, grape,... Based on the order of management numbers. The profit proposal module 21 displays each item described above in each agricultural and livestock product.
　なお、収益提案モジュール２１は、収益性が最も高いものをハイライトや強調表示させることや、収益性が高い順に、視覚的な変化を表示させる構成であってもよい。また、図６のようなテーブル表示に限らず、グラフ等のその他の表示態様を表示させる構成であってもよい。 Note that the profit proposing module 21 may be configured to highlight or highlight the one with the highest profitability, or to display visual changes in the order of high profitability. Further, the display is not limited to the table display as shown in FIG. 6, and other display modes such as a graph may be displayed.
　また、各農畜産物において、特定の項目のみを表示させる構成であってもよい。例えば、鶏において、予測収益、育成方法、生産場所を表示させ、牛乳において、予測収益、予測売上、生産コスト、販売コストを表示させ、葡萄において、予測収益のみを表示させるといったものである。このような特定の項目のみを表示させる構成である場合、上述した提案内容作成モジュール４４が提案内容として特定の項目のみを表示させる提案内容を作成していればよい。この場合、提案内容作成モジュール４４は、少なくとも、各農畜産物の予測収益を提案内容として作成すればよく、その他の項目に関しては、適宜変更可能である。 Also, in each agricultural and livestock product, only specific items may be displayed. For example, for chicken, the expected income, breeding method, and production place are displayed, for milk, the expected income, estimated sales, production cost, and sales cost are displayed, and in the grape, only the expected income is displayed. In the case of such a configuration in which only specific items are displayed, the above-described suggestion content creation module 44 may create the suggestion contents in which only the specific items are displayed as the suggestion contents. In this case, the proposal content creation module 44 may create at least the predicted profit of each agricultural and livestock product as the proposal content, and other items can be appropriately changed.
　図７において、提案要求取得モジュール２０は、就労者端末に、地図２００を表示させる。就労者は、この地図２００に対して自身が所望する地域を指定する。図７では、就労者が地図２００において指定した地域をアイコン２１０で示している。提案要求取得モジュール２０は、就労者が指定した地域を含んだ拡大地図２２０を、就労者端末に表示させる。就労者は、この拡大地図２２０に対してさらに、自身が所望する地域を指定する。図７では、就労者が拡大地図２２０に指定した地域をアイコン２３０で示している。提案要求取得モジュール２０は、このアイコン２３０で指定された地域に対する予測収益データの提案要求を取得することになる。 In FIG. 7, the proposal request acquisition module 20 displays the map 200 on the worker terminal. The worker specifies a desired area for this map 200. In FIG. 7, the area designated by the worker on the map 200 is indicated by the icon 210. The proposal request acquisition module 20 causes the worker terminal to display the enlarged map 220 including the area designated by the worker. The worker further designates the area desired by the worker on the enlarged map 220. In FIG. 7, the area designated by the worker on the enlarged map 220 is indicated by the icon 230. The proposal request acquisition module 20 acquires the proposal request of the forecast profit data for the area designated by the icon 230.
　提案内容作成モジュール４４は、取得した提案要求に基づいて、この地域に該当する予測収益データを、予測収益データテーブルから収益の高い順番に、所定の個数抽出し、提案内容として作成する。 Based on the acquired proposal request, the proposal content creation module 44 extracts a predetermined number of predicted profit data corresponding to this region from the predicted profit data table in descending order of profit and creates the proposal contents.
　収益提案モジュール２１は、この作成した提案内容を、就労者端末に、予測収益表示欄２４０として、表示させる。収益提案モジュール２１は、拡大地図２２０に重畳させる形式で、この予測収益表示欄２４０を表示させる。このとき、収益提案モジュール２１は、予測収益表示欄２４０内に、農畜産物の名称、予測収益、予測売上、生産コスト、販売コスト、育成方法、生産場所、販売場所を表示させる。この表示させる項目については、上述した提案内容作成モジュール４４が作成する提案内容に基づいたものである。このとき、収穫提案モジュール２１は、最も予測収益が高い農畜産物に関するものを表示させる。 The profit proposal module 21 displays the created proposal contents on the worker terminal as a predicted profit display field 240. The profit proposing module 21 displays the predicted profit display field 240 in a format to be superimposed on the enlarged map 220. At this time, the profit proposal module 21 displays the name of the agricultural and livestock product, the predicted profit, the predicted sales, the production cost, the sales cost, the breeding method, the production place, and the sales place in the predicted profit display field 240. The items to be displayed are based on the proposal contents created by the above-mentioned proposal contents creating module 44. At this time, the harvest proposal module 21 displays the one related to the agricultural and livestock products with the highest predicted profit.
　なお、提案要求取得モジュール２０は、拡大地図２２０で指定された地域を含んださらに拡大した地図を表示させてもよい。これを一又は複数繰り返し、様々な拡大率の地図を表示させる構成であってもよい。 The proposal request acquisition module 20 may display a further enlarged map including the area designated by the enlarged map 220. This may be repeated one or more times to display a map with various enlargement ratios.
　また、収益提案モジュール２１は、一の農畜産物の収益を表示させるものに限らず。複数の農畜産物の収益を表示させる構成であってもよい。この場合、収益の高い順番に他の農畜産物を表示させる構成や、他の農畜産物を表示させるアイコン等を表示させることにより、このアイコンの入力が行われることを契機として、他の農畜産物を表示させる構成等であってもよい。また、予測収益表示欄２４０の表示態様や表示位置等に関しては、本例に限らず、適宜変更可能である。 Also, the profit proposal module 21 is not limited to displaying the profit of one agricultural and livestock product. It may be configured to display the profits of a plurality of agricultural and livestock products. In this case, the other agricultural products are displayed in the descending order of profit, or the other agricultural products are displayed by displaying an icon for displaying the other agricultural products. It may be configured to display livestock products. Further, the display mode, the display position, and the like of the predicted profit display field 240 are not limited to this example, and can be changed as appropriate.
　以上が、収益提案処理である。 The above is the profit proposal processing.
　上述した手段、機能は、コンピュータ（ＣＰＵ、情報処理装置、各種端末を含む）が、所定のプログラムを読み込んで、実行することによって実現される。プログラムは、例えば、コンピュータからネットワーク経由で提供される（ＳａａＳ：ソフトウェア・アズ・ア・サービス）形態で提供される。また、プログラムは、例えば、フレキシブルディスク、ＣＤ（ＣＤ－ＲＯＭなど）、ＤＶＤ（ＤＶＤ－ＲＯＭ、ＤＶＤ－ＲＡＭなど）等のコンピュータ読取可能な記録媒体に記録された形態で提供される。この場合、コンピュータはその記録媒体からプログラムを読み取って内部記録装置又は外部記録装置に転送し記録して実行する。また、そのプログラムを、例えば、磁気ディスク、光ディスク、光磁気ディスク等の記録装置（記録媒体）に予め記録しておき、その記録装置から通信回線を介してコンピュータに提供するようにしてもよい。 The above-described means and functions are realized by a computer (including a CPU, an information processing device, and various terminals) reading and executing a predetermined program. The program is provided in the form of being provided from a computer via a network (SaaS: software as a service), for example. The program is provided in a form recorded in a computer-readable recording medium such as a flexible disk, a CD (CD-ROM, etc.), a DVD (DVD-ROM, DVD-RAM, etc.), for example. In this case, the computer reads the program from the recording medium, transfers the program to the internal recording device or the external recording device, records the program, and executes the program. Alternatively, the program may be recorded in advance in a recording device (recording medium) such as a magnetic disk, an optical disk, a magneto-optical disk, and provided from the recording device to a computer via a communication line.
　以上、本発明の実施形態について説明したが、本発明は上述したこれらの実施形態に限るものではない。また、本発明の実施形態に記載された効果は、本発明から生じる最も好適な効果を列挙したに過ぎず、本発明による効果は、本発明の実施形態に記載されたものに限定されるものではない。 Although the embodiments of the present invention have been described above, the present invention is not limited to these embodiments described above. Further, the effects described in the embodiments of the present invention are merely enumeration of the most suitable effects resulting from the present invention, and the effects according to the present invention are limited to those described in the embodiments of the present invention. is not.
　１　予測収益提案システム、１０　コンピュータ 1 Forecast profit proposal system, 10 computers

Claims (9)

  1. 　高収益の農畜産物を提案するコンピュータシステムであって、
    　前記農畜産物の売上を予測する売上予測手段と、
    　前記農畜産物の生産に掛かるコストを算出する生産コスト算出手段と、
    　前記農畜産物の販売に掛かるコストを算出する販売コスト算出手段と、
    　前記売上、前記生産に掛かるコスト及び前記販売に掛かるコストに基づいて、前記農畜産物の収益を予測する収益予測手段と、
    　前記収益を提案する収益提案手段と、
    　を備えることを特徴とするコンピュータシステム。     A computer system that proposes highly profitable agricultural and livestock products,
    Sales forecasting means for forecasting sales of the agricultural and livestock products,
    Production cost calculation means for calculating the cost of producing the agricultural and livestock products,
    Sales cost calculating means for calculating the cost of selling the agricultural and livestock products,
    Profit forecasting means for forecasting the profit of the agricultural and livestock products based on the sales, the cost for the production and the cost for the sale;
    A profit proposing means for proposing the profit,
    A computer system comprising:
  2. 　前記売上予測手段は、前記農畜産物の販売動向、消費者の人口分布の少なくとも一つに基づいて、当該農畜産物の売上を予測する、
    　ことを特徴とする請求項１に記載のコンピュータシステム。     The sales forecasting means forecasts the sales of the agricultural and livestock products based on at least one of the sales trend of the agricultural and livestock products and the population distribution of consumers.
    The computer system according to claim 1, wherein:
  3. 　前記生産コスト算出手段は、前記農畜産物の予測収量、育成条件、環境情報の少なくとも一つを考慮して、前記生産に掛かるコストを算出する、
    　ことを特徴とする請求項１に記載のコンピュータシステム。     The production cost calculation means calculates the cost required for the production in consideration of at least one of the predicted yield of the agricultural and livestock products, the growing condition, and the environmental information.
    The computer system according to claim 1, wherein:
  4. 　前記販売コスト算出手段は、前記農畜産物の運搬及び貯蔵に掛かるコストを考慮して、前記販売に掛かるコストを算出する、
    　ことを特徴とする請求項１に記載のコンピュータシステム。     The selling cost calculating means calculates the cost of selling in consideration of the cost of transporting and storing the agricultural and livestock products,
    The computer system according to claim 1, wherein:
  5. 　前記収益提案手段は、前記売上、前記生産に掛かるコスト、前記販売に掛かるコストの少なくとも一つを提案する、
    　ことを特徴とする請求項１に記載のコンピュータシステム。     The profit suggesting means proposes at least one of the sales, the production cost, and the sales cost,
    The computer system according to claim 1, wherein:
  6. 　前記農畜産物の育成条件、環境情報の少なくとも一つを考慮して、当該農畜産物に適した育成方法を提案する育成方法提案手段と、
    　をさらに備えることを特徴とする請求項１に記載のコンピュータシステム。     Breeding method suggesting means for suggesting a breeding method suitable for the agricultural and livestock products in consideration of at least one of the growing conditions of the agricultural and livestock products and environmental information,
    The computer system according to claim 1, further comprising:
  7. 　前記農畜産物の生産場所、販売場所の少なくとも一つを提案する場所提案手段と、
    　をさらに備えることを特徴とする請求項１に記載のコンピュータシステム。     Location suggestion means for suggesting at least one of the production location and the sale location of the agricultural and livestock products,
    The computer system according to claim 1, further comprising:
  8. 　高収益の農畜産物を提案するコンピュータシステムが実行する予測収益提案方法であって、
    　前記農畜産物の売上を予測するステップと、
    　前記農畜産物の生産に掛かるコストを算出するステップと、
    　前記農畜産物の販売に掛かるコストを算出するステップと、
    　前記売上、前記生産に掛かるコスト及び前記販売に掛かるコストに基づいて、前記農畜産物の収益を予測するステップと、
    　前記収益を提案するステップと、
    　を備えることを特徴とする予測収益提案方法。     A predictive profit proposing method executed by a computer system that proposes highly profitable agricultural and livestock products,
    Forecasting the sales of the agricultural and livestock products,
    Calculating the cost of producing the agricultural and livestock products,
    Calculating the cost of selling the agricultural and livestock products,
    Predicting the profit of the agricultural and livestock products based on the sales, the costs for the production, and the costs for the sales;
    Proposing the revenue,
    A forecasted profit proposing method comprising:
  9. 　高収益の農畜産物を提案するコンピュータシステムに、
    　前記農畜産物の売上を予測するステップ、
    　前記農畜産物の生産に掛かるコストを算出するステップ、
    　前記農畜産物の販売に掛かるコストを算出するステップ、
    　前記売上、前記生産に掛かるコスト及び前記販売に掛かるコストに基づいて、前記農畜産物の収益を予測するステップ、
    　前記収益を提案するステップ、
    　を実行させるためのコンピュータ読み取り可能なプログラム。     For computer systems that propose highly profitable agricultural and livestock products,
    Predicting the sales of the agricultural and livestock products,
    Calculating the cost of producing the agricultural and livestock products,
    Calculating the cost of selling the agricultural and livestock products,
    Predicting the profit of the agricultural and livestock products based on the sales, the costs for the production, and the costs for the sales,
    Proposing the revenue,
    A computer-readable program for executing.
PCT/JP2018/043665 2018-11-28 2018-11-28 Computer system, predicted profit proposing method, and program WO2020110210A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
JP2020557443A JP7066256B2 (en) 2018-11-28 2018-11-28 Computer system, forecasted revenue proposal method and program
PCT/JP2018/043665 WO2020110210A1 (en) 2018-11-28 2018-11-28 Computer system, predicted profit proposing method, and program

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/JP2018/043665 WO2020110210A1 (en) 2018-11-28 2018-11-28 Computer system, predicted profit proposing method, and program

Publications (1)

Publication Number Publication Date
WO2020110210A1 true WO2020110210A1 (en) 2020-06-04

Family

ID=70854129

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2018/043665 WO2020110210A1 (en) 2018-11-28 2018-11-28 Computer system, predicted profit proposing method, and program

Country Status (2)

Country Link
JP (1) JP7066256B2 (en)
WO (1) WO2020110210A1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20220018828A (en) * 2020-08-07 2022-02-15 (주)협신식품 System and method for management of processing livestock products and computer program for the same

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH11353364A (en) * 1998-06-08 1999-12-24 Hitachi Ltd Method for determining shipping destination and shipping quantity of articles
JP2003030278A (en) * 2001-07-19 2003-01-31 National Agricultural Research Organization System for supporting farm management through internet
WO2013128557A1 (en) * 2012-02-27 2013-09-06 富士通株式会社 Cost calculation method, cost calculation program, and cost calculation device

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108121536A (en) * 2018-02-11 2018-06-05 山东省农业信息中心 A kind of agricultural decision making method and device

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH11353364A (en) * 1998-06-08 1999-12-24 Hitachi Ltd Method for determining shipping destination and shipping quantity of articles
JP2003030278A (en) * 2001-07-19 2003-01-31 National Agricultural Research Organization System for supporting farm management through internet
WO2013128557A1 (en) * 2012-02-27 2013-09-06 富士通株式会社 Cost calculation method, cost calculation program, and cost calculation device

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20220018828A (en) * 2020-08-07 2022-02-15 (주)협신식품 System and method for management of processing livestock products and computer program for the same
KR102547735B1 (en) 2020-08-07 2023-06-26 (주)협신식품 System and method for management of processing livestock products and computer program for the same

Also Published As

Publication number Publication date
JP7066256B2 (en) 2022-05-13
JPWO2020110210A1 (en) 2021-09-02

Similar Documents

Publication Publication Date Title
Dalhaus et al. The effects of extreme weather on apple quality
Jaffee et al. Strategic use of private standards to enhance international competitiveness: Vegetable exports from Kenya and elsewhere
Brulard et al. An integrated sizing and planning problem in designing diverse vegetable farming systems
KR20170096953A (en) System and method for managing generated product information
US20170039657A1 (en) Harvest amount distributing method, harvest amount input method, recording medium, and system
Das Nair et al. Making agricultural value chains more inclusive through technology and innovation
Gogo et al. Loss of African indigenous leafy vegetables along the supply chain
Monson et al. The decision to direct market: An analysis of small fruit and specialty-product markets in Virginia
KR101347514B1 (en) The prediction system for the output of agricultural products and the method of using it
WO2018158821A1 (en) Harvest information suggestion system, method and program
WO2020110210A1 (en) Computer system, predicted profit proposing method, and program
KR102222004B1 (en) Prediction system for traffic of fruits and predicting method using the same
Havardi-Burger et al. Driving forces and characteristics of the value chain of flowering potted plants for the German market
García-Salazar et al. Analysis of strategic industry planning and organizational opportunities for Mexican cantaloupe producers
JP6937188B2 (en) Equipment, systems, methods and programs to support the production and distribution of horticultural products
Wijesinghe et al. Factors Influencing Vegetable Farmers' Decisions
Herrington et al. Influence of plant traits on production costs and profitability of strawberry in southeast Queensland
Mojaverian et al. Citrus marketing channel strategy and its determinants in Mazandaran province of Iran: An application of nested logit model
Wilson et al. Time integration: Agribusiness structure for competitive advantage
Chadha et al. Digitalization of Agriculture in India: Pathway to Prosperity
WO2021038813A1 (en) Computer system, food sales mediation method, and program
JP7144585B1 (en) Information processing device, information processing method and program
Bechar et al. Effective productivity management of mixed flower farms
Khadka Study of value chain of apple in Mustang and Jumla district of Nepal
Khanna Applications of big data analytics: A boon for the food industry

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18941762

Country of ref document: EP

Kind code of ref document: A1

DPE1 Request for preliminary examination filed after expiration of 19th month from priority date (pct application filed from 20040101)
ENP Entry into the national phase

Ref document number: 2020557443

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 18941762

Country of ref document: EP

Kind code of ref document: A1