WO2023037931A1

WO2023037931A1 - Yield prediction system, management assistance system for plant factory, yield prediction method, and yield prediction program

Info

Publication number: WO2023037931A1
Application number: PCT/JP2022/032611
Authority: WO
Inventors: 祐二中嶋; 豊宮本; 義剛進藤; 郷藤田
Original assignee: 三菱重工業株式会社
Priority date: 2021-09-09
Filing date: 2022-08-30
Publication date: 2023-03-16
Also published as: JP2023039465A

Abstract

A yield prediction system for predicting a yield in a plant factory that cultivates plants is provided, comprising: a photosynthesis amount calculation unit configured to use a first correlation between an insolation amount and a photosynthesis rate of the plants to calculate a photosynthesis amount per day of the plants from insolation amount data indicating the insolation amount per time slot of the day; and a yield prediction unit configured to use a second correlation between the photosynthesis amount of the plants and the yield to predict the yield of the plants.

Description

Yield prediction system, plant factory management support system, yield prediction method, and yield prediction program

The present disclosure relates to a yield prediction system, a plant factory management support system, a yield prediction method, and a yield prediction program.
This application claims priority based on Japanese Patent Application No. 2021-146551 filed with the Japan Patent Office on September 9, 2021, the content of which is incorporated herein.

When cultivating plants in a plant factory, etc., we may use a computer to predict the harvest time, yield, etc., for the purpose of making appropriate cultivation plans.

For example, Patent Literature 1 describes predicting plant cultivation conditions (harvest start date, number of removed leaves, etc.) based on a cultivation condition prediction formula constructed based on past cultivation performance data. Here, the actual cultivation data includes environmental measurement value data and growth survey value data. The environmental measurement value data is data measured in the growing environment of plants, and includes, for example, the temperature, humidity, amount of solar radiation, and carbon dioxide concentration in the greenhouse. The growth survey value data is data obtained by observing the growth state of plants, and includes, for example, leaf color, flower color, number of fruiting per flower cluster, average number of fruiting and yield.

JP 2019-30253 A

By the way, in order to improve the profitability of plant factories, it is desirable to predict the yield of plants with good accuracy using a simple procedure.

In view of the circumstances described above, at least one embodiment of the present invention provides a yield prediction system, a plant factory management support system, a yield prediction method, and a yield prediction program capable of predicting the yield of a plant with high accuracy through a simple procedure. intended to

A yield prediction system according to at least one embodiment of the present invention comprises
A yield prediction system for predicting the yield in a plant factory for cultivating plants,
Photosynthesis configured to calculate the amount of photosynthesis per day of the plant from the amount of insolation data indicating the amount of insolation for each time period of the day, using a first correlation between the amount of insolation and the photosynthetic rate of the plant. a quantity calculator;
a yield prediction unit configured to predict the yield of the plant using a second correlation between the amount of photosynthesis and the yield of the plant;
Prepare.

In addition, the plant factory management support system according to at least one embodiment of the present invention includes:
A management support system for a plant factory for cultivating plants,
A determination unit configured to determine whether production adjustment of the plant is necessary based on the predicted yield of the plant predicted by the yield prediction system and weather forecast information or market information regarding the plant. .

In addition, the yield prediction method according to some embodiments of the present invention includes
A yield prediction method for predicting the yield in a plant factory for cultivating plants,
a step of calculating the amount of photosynthesis per day of the plant from the amount of insolation data indicating the amount of insolation for each time period of the day using the first correlation between the amount of insolation and the photosynthetic rate;
predicting the yield of the plant using a second correlation between photosynthesis and yield;
Prepare.

Further, the yield prediction program according to at least one embodiment of the present invention includes
A yield prediction program for predicting the yield in a plant factory for cultivating plants,
to the computer,
A step of calculating the amount of photosynthesis per day of the plant from the amount of insolation data indicating the amount of insolation for each time zone of the day using the first correlation between the amount of insolation and the photosynthetic rate;
A step of predicting the yield of the plant using the second correlation between the amount of photosynthesis and the yield;
is configured to run

According to at least one embodiment of the present invention, there is provided a yield prediction system capable of predicting the yield of a plant with high accuracy through a simple procedure, a plant factory management support system, a yield prediction method, and a yield prediction program.

BRIEF DESCRIPTION OF THE DRAWINGS It is a schematic block diagram of the yield prediction system which concerns on one Embodiment, and the management support system of a plant factory. 2 is a graph showing an example of measurement results of photosynthetic rate against solar radiation for a plant (strawberry) cultivated in a plant factory. 3 is a graph obtained based on the graph of FIG. 2 and is a graph showing the relationship between the reciprocal of light intensity (horizontal axis) and the photosynthetic rate (vertical axis). Fig. 10 is a graph showing an example of measurement results of the amount of fruit growth with respect to the amount of photosynthesis for a plant (strawberry) cultivated in a plant factory. It is a flowchart of the management support method of the plant factory which concerns on one Embodiment. 1 is a schematic diagram of a bunch of strawberries; FIG. It is a table|surface for demonstrating the method of determination of thinning/fruit thinning object.

Several embodiments of the present invention will be described below with reference to the accompanying drawings. However, the dimensions, materials, shapes, relative arrangements, etc. of the components described as embodiments or shown in the drawings are not intended to limit the scope of the present invention, and are merely illustrative examples. do not have.

(Configuration of yield prediction system and management support system)
FIG. 1 is a schematic configuration diagram of a yield prediction system and a plant factory management support system according to one embodiment. As shown in FIG. 1, in one embodiment, the yield prediction system 12 may function as part of the plant factory management support system 10 .

The yield prediction system 12 shown in FIG. 1 is a yield prediction system for predicting the yield in a plant factory that cultivates plants (vegetables, fruits, etc.). A plant factory management support system 10 shown in FIG. 1 is a plant factory management support system for cultivating plants (vegetables, fruits, etc.).

In some embodiments, the plant factory to which the yield prediction system 12 and the management support system 10 are applied is a plant factory that uses sunlight to grow plants.

The yield prediction system 12 and the management support system 10 include a computer equipped with a processor (CPU, etc.), main storage (memory device; RAM, etc.), auxiliary storage, interface, and the like. The management support system 10 receives signals from a sensor 42 (described later) or a storage unit 40 (described later) via an interface. The processor is configured to process the signal thus received. Also, the processor is configured to process the program deployed in the main memory. As a result, the functions of the later-described units that constitute the yield prediction system 12 and the management support system 10 are realized.

The yield prediction system 12 and the management support system 10 may be implemented in the same computer or may be implemented in separate computers. may be implemented on separate computers.

The processing contents of the yield prediction system 12 and the management support system 10 are implemented as programs executed by a processor. The program may be stored, for example, in an auxiliary storage device. During program execution, these programs are expanded in the main memory. The processor reads the program from the main memory and executes the instructions contained in the program.

In addition, the storage unit 40 may include a main storage device or an auxiliary storage device of a computer that constitutes the yield prediction system 12 and the management support system 10, or the storage unit 40 is connected to the computer via a network. A remote storage device may also be included.

As shown in FIG. 1, the yield prediction system 12 includes a photosynthesis amount calculation unit 14 and a yield prediction unit 16.

The photosynthesis calculation unit 14 uses the correlation (first correlation) between the amount of solar radiation and the photosynthetic rate of the plant to calculate the amount of photosynthesis of the plant from the solar radiation amount data indicating the amount of solar radiation for each time period of the day. is configured to calculate

The photosynthesis amount calculation unit 14 acquires from the storage unit 40 the above-described first correlation stored in advance in the storage unit 40 and/or the solar radiation amount data indicating the amount of solar radiation for each time zone of the day. may be configured.

The first correlation between the amount of solar radiation and the photosynthetic rate of plants can be obtained in advance by measuring the photosynthetic rate with respect to the amount of solar radiation at a plurality of points. Here, FIG. 2 is a graph showing an example of measurement results of the photosynthetic rate with respect to the amount of solar radiation at a plurality of points for strawberries, which is an example of plants cultivated in a plant factory. As shown in FIG. 2, the photosynthetic rate of plants (vertical axis) tends to increase as the light intensity (indicator of solar radiation; horizontal axis) increases. In the graph of FIG. 2, the true photosynthetic rate PG is the sum of the respiratory rate B (the photosynthetic rate when the light intensity is zero) and the measured photosynthetic rate at each light intensity (apparent photosynthetic rate PA). .

FIG. 3 is a graph obtained based on the graph of FIG. 2, showing the relationship between the reciprocal of light intensity (horizontal axis) and the true photosynthetic rate PG (vertical axis). As a result of diligent studies by the present inventors, as can be seen from the graph in FIG. 3, the reciprocal of the light intensity and the reciprocal of the true photosynthetic rate PG are represented by an approximate straight line L1 (coefficient of determination R ² =0.9943). It was found to have a linear correlation as shown. That is, in the first correlation between the amount of solar radiation and the photosynthetic rate of plants, it was found that the reciprocal of the amount of solar radiation (reciprocal of light intensity) and the reciprocal of photosynthetic rate (true photosynthetic rate) have a linear correlation. rice field.

The first correlation between the amount of insolation and the photosynthetic rate of plants may include an expression of the function representing the approximate straight line L1 described above (the function representing the relationship between the reciprocal of the light intensity and the reciprocal of the true photosynthetic rate PG). .

The amount of solar radiation data that indicates the amount of solar radiation for each time period of the day can be obtained from a pre-created database. As the above-mentioned database, for example, an annual hourly solar radiation amount database (https://www.nedo.go.jp/library/nissharyou.jp) published by NEDO (New Energy and Industrial Technology Development Organization) is used. html) can be used. As the amount of solar radiation data indicating the amount of solar radiation for each time period of the day, the amount of solar radiation for each time period (every hour, etc.) of each day of the yield prediction target period may be acquired from the database described above.

The photosynthesis amount calculation unit 14 calculates the photosynthesis amount of plants for each time period of the day (for example, every hour) from the above-described solar radiation amount data and the first correlation obtained from the storage unit 40 and the like. By integrating this for one day (for 24 hours), the amount of photosynthesis of the plant per day can be calculated.

The yield prediction unit 16 is configured to predict the yield of the plant using the second correlation between the amount of photosynthesis of the plant and the yield.

The yield prediction unit 16 may be configured to acquire from the storage unit 40 the second correlation previously stored in the storage unit 40 . Moreover, the yield prediction unit 16 may be configured to receive the amount of photosynthesis of the plant per day calculated by the photosynthesis amount calculation unit 14 .

The second correlation between the amount of photosynthesis and the yield of a plant can be obtained by measuring in advance the amount of plant growth (yield) with respect to the amount of photosynthesis at a plurality of points per unit period (typically per day). can. Here, FIG. 4 is a graph showing an example of measurement results of the amount of fruit growth with respect to the amount of photosynthesis at a plurality of points per day for strawberries, which is an example of plants cultivated in a plant factory. As shown in FIG. 4, as the amount of photosynthesis per day (horizontal axis) increases, the amount of fruit growth per day (that is, yield; vertical axis) tends to increase. It can be seen that the amount of fruit growth has a linear correlation as indicated by the approximate straight line L2.

The second correlation between the amount of photosynthesis and the yield of plants may include an expression of the function representing the above-described approximate straight line L2 (function indicating the relationship between the amount of photosynthesis at multiple points per day and the amount of fruit growth).

The yield prediction unit 16 may be configured to predict the yield of the plant based on the second correlation described above and the amount of photosynthesis of the plant per day calculated by the photosynthesis calculation unit 14. That is, the daily yield of the plant may be calculated (predicted) by applying the daily photosynthesis amount of the plant calculated by the photosynthesis amount calculation unit 14 to the above-described second correlation.

According to the yield prediction system 12 according to the above-described embodiment, the amount of photosynthesis per day is calculated from the amount of insolation data for each time zone of the day, based on the correlation between the amount of insolation and the yield of plants (first correlation). can be calculated. Then, the amount of photosynthesis calculated per day is applied to the correlation between the amount of photosynthesis of the plant and the yield (second correlation) to calculate the yield of the plant per day. can be done. Therefore, according to the yield prediction system 12 according to the above-described embodiment, it is possible to appropriately predict the yield of a plant with high accuracy through a simple procedure.

As shown in FIG. 1, the management support system 10 includes the yield prediction system 12 and the determination unit 18 described above. The management support system 10 may further include a policy determination section 22 and/or a display output section 38 .

The determination unit 18 is configured to determine whether plant production adjustment is necessary based on weather forecast information or market information on plants. For example, the determination unit 18 determines whether or not the target sales amount (sales amount per weight, etc.) is obtained when the plant with the yield predicted by the yield prediction system 12 is harvested. It may be configured to determine the necessity of production adjustment.

The determination unit 18 may be configured to acquire from the storage unit 40 the weather forecast information previously stored in the storage unit 40 or market information related to plants. Alternatively, the determination unit 18 may be configured to acquire the above-described weather forecast information or plant market information stored in a storage medium on a network such as the Internet.

The decision unit 18 decides whether or not production adjustment is necessary based on the predicted yield calculated by the yield prediction system 12 and separately obtained weather forecast information or market information, thereby improving profits in the plant factory. be able to. For example, it is possible to increase the profit in the plant factory by increasing the yield when the shipment amount of outdoor cultivated plants is small.

When the determination unit 18 determines that the production adjustment of the plant is necessary, the policy determination unit 22 adjusts the production at least based on the comparison between the predicted yield calculated by the yield prediction system 12 and the target yield of the plant. configured to determine a policy for

The policy determination unit 22 may be configured to acquire from the storage unit 40 the target yield of the plant stored in advance in the storage unit 40 . Alternatively, the determination unit 18 may acquire the target yield of the plant that is input to the management support system 10 via an input device (keyboard, mouse, etc.; not shown).

When the determination unit 18 determines that plant production adjustment is necessary, the policy determination unit 22 determines a policy for production adjustment based on at least a comparison between the predicted yield of the plant and the target yield. By implementing the policy determined in this way, it is possible to appropriately adjust production and improve the profit in the plant factory.

The policy determination unit 22 is configured to determine a policy for production adjustment based on signals from various sensors 42 (eg, temperature sensor, light sensor, CO2 sensor, camera, etc.) provided in the plant factory. may

As shown in FIG. 1 , the policy determination unit 22 includes a flower removal target determination unit 24, a light shielding rate determination unit 26, a supplementary light amount determination unit 28, a leaf removal amount determination unit 30, a water supply amount determination unit 32, and a fertilizer supply amount determination unit 34. , or the temperature determination unit 36 may be included.

The deflowering target determination unit 24 determines the flower or fruit of the plant to be deflowered or depleted based on the predicted yield of the plant predicted by the yield prediction system 12 and the data on the weight of the fruit of the plant. Configured.

The flower removal target determination unit 24 may be configured to acquire from the storage unit 40 data relating to the weight of the fruit of the above-described plant stored in advance in the storage unit 40 .

The shading rate determination unit 26 may be configured to determine the shading rate in the plant factory using the predicted plant yield predicted by the yield prediction system 12 and the weather forecast information. The shading rate determination unit 26 may be configured to determine the shading rate in the plant factory using the measured value of the light intensity in the plant factory in addition to the weather information described above.

The shading rate determination unit 26 may be configured to acquire the weather forecast information previously stored in the storage unit 40 from the storage unit 40 . Alternatively, the shading rate determination unit 26 may be configured to acquire the weather forecast information described above stored in a storage medium on a network such as the Internet. The light shielding rate determining unit 26 may be configured to receive a signal indicating the light intensity in the plant factory from a light sensor (sensor 42) provided in the plant factory.

The supplemental light amount determination unit 28 uses the predicted yield of the plant predicted by the yield prediction system 12, the weather forecast information, and/or the measured value of the light intensity in the plant factory to determine the supplemental light amount in the plant factory. may be configured. The measured value of light intensity may be obtained by an optical sensor (sensor 42) provided in the plant factory.

The leaf removal amount determination unit 30 uses the predicted yield of the plant predicted by the yield prediction system 12, the weather forecast information, and/or the image data of the leaves of the plant in the plant factory to determine the amount of leaf removal for the plant. may be configured. The imaging data of plant leaves may be acquired by a camera (sensor 42) installed in a plant factory.

The water supply amount determination unit 32 includes the predicted yield of plants predicted by the yield prediction system 12, weather forecast information, measured soil moisture in the plant factory, measured soil pH, measured soil electrical conductivity, Alternatively, it may be configured to determine the amount of water to be supplied to the plants using imaging data of the plants and soil in the plant factory. A soil moisture meter (sensor 42), a pH meter (sensor 42) and an electric It may be obtained by a conductivity meter (sensor 42). The imaging data of the plants and soil in the plant factory may be acquired by a camera (sensor 42) installed in the plant factory.

The fertilizer supply amount determination unit 34 uses the predicted yield of the plant predicted by the yield prediction system 12, the weather forecast information, the measured value of the pH of the soil in the plant factory, or the measured value of the electrical conductivity of the soil. may be configured to determine a fertilizer supply to the The measured value of the soil pH and the measured value of the electrical conductivity of the soil are obtained by a pH meter (sensor 42) and an electrical conductivity meter (sensor 42) provided in the plant factory, respectively. may

The temperature determination unit 36 uses the predicted yield of plants predicted by the yield prediction system 12, weather forecast information, or measured values of the temperature in the plant factory (the temperature inside or outside the greenhouse, the temperature of the soil, etc.). , may be configured to determine a temperature setpoint in the plant factory. The temperature in the plant factory may be obtained by a temperature sensor (sensor 42) provided in the plant factory.

The display output unit 38 is configured to output information including the policy determined by the policy determination unit 22 to the display unit 44 (display). The display unit 44 may be a display of a mobile terminal (smartphone, tablet, etc.).

The display output unit 38 displays the measures determined by the measure determination unit 22 on the display unit 44, so that the plant factory workers can easily know the measures. Therefore, it is possible to improve the working efficiency in the plant factory.

(Plant factory management support flow)
Hereinafter, with reference to FIG. 5, the flow of plant yield prediction and the flow of management support of a plant factory using the above-described yield prediction system 12 and management support system 10 will be described. FIG. 5 is a flowchart of a plant factory management support method according to one embodiment. As shown in FIG. 5, the yield prediction method (steps S2 to S4) according to one embodiment is included in the plant factory management support method (steps S2 to S16) according to one embodiment.

First, in step S2, the photosynthesis amount calculation unit 14 reads from the storage unit 40 or the like the above-described first correlation and/or the amount of solar radiation indicating the amount of solar radiation for each time zone of the day. Get data. Then, using the correlation (first correlation) between the amount of solar radiation and the photosynthetic rate of the plant, the amount of photosynthesis of the plant per day is calculated from the amount of solar radiation data indicating the amount of solar radiation for each time zone of the day. The method for calculating the amount of photosynthesis of plants per day has already been described with reference to FIGS. 2 to 4 and the like.

Next, in step S4, the yield prediction unit 16 acquires the second correlation between the amount of photosynthesis of the plant and the yield from the storage unit 40 or the like, and uses the second correlation between the amount of photosynthesis of the plant and the yield. , to predict plant yield. In step S4, the daily yield of the plant can be calculated (predicted) by applying the daily photosynthetic amount of the plant calculated in step S2 to the above-described second correlation.

Next, in step S8, the determination unit 18 acquires weather forecast information or market information about plants from the storage unit 40 or the like, and determines whether plant production adjustment is necessary based on the acquired information. .

For example, in step S8, when the yield of plants predicted by the yield prediction system 12 is harvested, the production You may make it determine the necessity of adjustment. In this case, if it is expected that the target sales amount or more will be obtained, it is determined that production adjustment is unnecessary (No in step S8), and this flow is terminated. On the other hand, if it is expected that the target sales amount or more will not be obtained, it is determined that production adjustment is necessary (Yes in step S8), and the process proceeds to the next step S10.

In addition, the target sales amount (sales amount per weight, etc.) can be set based on market information (for example, wholesale prices) at the time of harvest of the plants cultivated in the plant factory. As market information such as wholesale prices, market information predicted from past market information and weather forecast information may be used.

Next, in step S10, the policy determination unit 22 acquires the target yield of the plant from the storage unit 40 or the like, and at least compares the predicted yield calculated in step S4 with the target yield of the plant. Determine strategies for making adjustments. If the predicted yield is equal to or greater than the target yield (Yes in step S10), the process proceeds to step S12 to determine an appropriate policy. If the predicted yield is less than the target yield (No in step S10), proceed to step S14 to determine an appropriate policy.

If the predicted yield is equal to or higher than the target yield (Yes in step S10), production adjustment is performed so that the actual yield approaches the target yield, that is, the yield is decreased from the predicted yield. Production control strategies include adjusting the amount of shade, adjusting the amount of _CO2 , thinning or fruit thinning, leaf thinning, adjusting water supply, adjusting fertilizer supply, and/or adjusting growing temperature. Weather forecast information and the like may also be taken into consideration when determining which measures to implement for production adjustment.

Regarding the adjustment of the light shielding rate, the light shielding rate is adjusted so that the temperature in the plant factory does not exceed the temperature suitable for plant cultivation (for example, about 25 ° C. for strawberries) and the target yield is obtained. set. The shading rate is the ratio of the area where the sunlight is blocked by the shading material to the area of the plant factory where the shading material is not installed. The light shielding rate may be set within a range of 10% or more and 90% or less. When the temperature control in the plant factory is not sufficient only with the light shielding material, the plant factory may be cooled by cooling. Cooling may be used within a range in which the electricity bill due to use of cooling does not exceed the increase in sales price of crops due to use of cooling.

For the adjustment of the amount of _CO2 , the _CO2 concentration _in the plant factory is less than the range suitable for plant cultivation (e.g. about 2000 ppm for strawberries) so as to obtain the target yield of the crop. Set to be the amount. The CO ₂ concentration may be set within a range of 10% or more and 90% or less with respect to the optimum concentration for plant cultivation. Adjustment of the amount of CO ₂ may be performed within a range in which the cost of adjusting the amount of CO ₂ does not exceed the increase in sales price of the crop due to the adjustment of the amount of CO ₂ .

A part of the fruit may be thinned to delay the harvesting period. Of the harvestable fruits, 10% or more and 90% or less of the fruits may be thinned. In the case of strawberries, the fruit grows in about one month after flowering, so the amount of flower/fruit thinning may be determined according to the production target after one month.

By removing leaves, it is possible to shift production (delay production for the desired period). 10% or more and 60% or less of all leaves may be applied. In addition, when 30% or more of the leaves are removed, it may be determined including replacement with a new strain (young seedling).

The amount of water supply required for plant cultivation can be determined based on the amount of fruit production (yield), the number of leaves, and the amount of roots. Therefore, once the target production amount of the plant is determined, the water supply amount can be set according to the target production amount. The opening degree or opening/closing control of the water supply valve may be controlled based on the set value of the water supply amount.

The amount of fertilizer required for plant cultivation can be determined based on the amount of fruit production (yield), the number of leaves, and the amount of roots. Therefore, once the target production amount of the plant is determined, the amount of fertilizer to be supplied can be set according to the target production amount. In the case of liquid fertilizer, the degree of opening or opening/closing of the fertilizer supply valve may be controlled based on the set value of the fertilizer supply amount. In the case of solid fertilizers, the fertilization period may be delayed.

By adjusting the growth temperature of plants, the growth speed of plants can be controlled. For example, by setting the plant growth temperature to a temperature lower than the optimum temperature, the plant growth rate can be slowed down. The growth temperature of plants may be adjusted so long as the cost of adjusting the temperature does not exceed the increase in the sales price of the crop due to the adjustment of the amount of temperature.

If the predicted yield is less than the target yield (No in step S10), adjust production so as to increase yield and/or profitability. Production control strategies include thinning/thinning, adjusting supplemental light, adjusting growing temperature, adjusting fertilizer supply, and/or adjusting water supply. Weather forecast information and the like may also be taken into consideration when determining which measures to implement for production adjustment.

In order to improve profitability by concentrating nutrients in fruits with high selling prices (such as top and second fruits in the case of strawberries), fruit thinning is performed for fruits with low selling prices. It may be done. Of the harvestable fruits, 10% or more and 90% or less of the fruits may be thinned.

If it is predicted that the amount of sunlight will be insufficient due to weather forecast information, etc., light may be supplemented with LED (light emitting diode) lighting. A supplementary light amount may be set so as to obtain a target yield. Alternatively, the amount of supplemental light may be adjusted so that the cost associated with adjusting the amount of supplemental light does not exceed the increase in profit associated with the increase in yield due to the adjustment of the amount of supplemental light.

By adjusting the growth temperature of plants, the growth speed of plants can be controlled. For example, when the temperature is excessively high or low, the plant growth rate can be increased by adjusting the plant growth temperature to a temperature close to the optimum temperature. The growth temperature of plants may be adjusted within a range in which the costs related to temperature adjustment (heating costs in winter, etc.) do not exceed the increase in sales price of crops due to temperature adjustment.

The supply amount of fertilizer necessary for plant cultivation can be determined based on the fruit production (yield), the number of leaves, and the amount of roots. You may make it change the kind of fertilizer. In the case of liquid fertilizer, the opening degree control or opening/closing control of the fertilizer supply valve may be performed based on the changed (increased) set value of the fertilizer supply amount. In the case of a solid fertilizer, the fertilization period may be advanced, or the fertilization type may be changed (potassium sulfate is changed to potassium silicate, etc.).

When it is determined in step S12 or S14 to perform flower thinning or fruit thinning, the thinning target determination unit 24 adds the predicted yield of the plant calculated in steps S2 to S4 and the data on the weight of the fruit of the plant. Based on this, the flower or fruit of the plant to be thinned may be determined.

Regarding how to determine the target for thinning/fruit thinning, the case where the plant cultivated in the plant factory is strawberry will be described with reference to FIGS. 6 and 7. FIG. FIG. 6 is a schematic diagram of a bunch 50 of strawberries, and FIG. 7 is a table for explaining how to determine an object to be thinned.

As shown in FIG. 6, a strawberry bunch 50 consists of a plurality of fruits 52-58. A plurality of fruits are composed of one apical fruit 52 which is the first fruit to be produced, two

secondary fruits

54a and 54b formed respectively on the bifurcated stems from the apical fruit 52, and a total of 4 fruits formed on each of the bifurcated stems 51. It includes individual third fruits 56a to 56d, and a total of eight fourth fruits 58a to 58h formed on the bifurcated stem 51, respectively. Although there is actually an upper limit to the number of fruits that can be produced per bunch, if this upper limit is disregarded, theoretically 2 ^(N-1) Nth fruits can be produced.

In the table shown in FIG. 7, the average weight (one example) of the corresponding fruit is described in the column of each (Nth fruit) of a plurality of fruits formed in one cluster 50. In the example shown in FIG. 7, it is 20 g per apical fruit, 10 g per second fruit, 8 g per third fruit, and 5 g per fourth fruit. These weights are obtained as statistical values (average values, etc.) from past harvest results.

In the table of FIG. 7, for two cases in which the predicted yield per month per strawberry was calculated to be 99 g and 72 g, "fruit thinning" is displayed in the column of fruit determined to be thinned/thinned. there is

Targets for thinning flowers/fruits are determined, for example, as follows. That is, first, the weight of the fruit is accumulated in order from the top (from the left side of the table), and the fruit that falls within the range of the predicted yield is not subject to flower removal, and the fruit that does not fall within the predicted yield is determined to be subject to flower removal. do.

In the upper example (an example where the predicted yield is 99 g), 1 top fruit (20 g), 2 second fruits (10 g), 4 third fruits (8 g), and 5 fourth fruits (5 g) The total fruit weight is 97 g. When the weight of the 4th fruit after the 6th fruit is included in this total weight, the predicted yield of 99 g is exceeded. Therefore, the sixth and subsequent fourth fruits and the fifth and subsequent fruits are determined to be subject to thinning.

In the lower example (an example where the predicted yield is 72 g), the sum of the weight of each fruit is 72 g, including 1 apex (20 g), 2 secondary fruits (10 g), and 4 tertiary fruits (8 g). . When the weight of the first and subsequent fourth fruits is included in this total weight, the predicted yield of 72 g is exceeded. Therefore, the fourth and subsequent fruits are determined to be thinned.

In this way, it is possible to determine the flowers or fruits to be thinned based on the predicted yield of the plant and the data on the weight of the fruit. As a result, it is possible to appropriately adjust the production and improve the profit in the plant factory.

When it is determined to shade or supplement light in step S12 or S14, the shade rate determination unit 26 uses the predicted yield of the plant calculated in steps S2 to S4 and the weather forecast information, You may make it determine the shading rate in a plant factory.

For example, in the case of a plant factory where light shielding materials are installed so that the light shielding rate is 5% to 50% in the summer in a normal year, if weather forecast information predicts a lack of sunlight in the summer, the plant factory The yield can be increased by removing part or all of the light shielding material and improving the light shielding rate. On the other hand, if weather forecast information predicts excessive sunshine in the summer, the cooling cost can be reduced by increasing the shading rate in the plant factory (that is, increasing the number of shading materials to be installed). .

In this way, it is possible to determine the shading rate in a plant factory using the predicted yield of plants and weather forecast information. As a result, it is possible to appropriately adjust the production and improve the profit in the plant factory.

The contents described in each of the above embodiments can be understood, for example, as follows.

(1) A yield prediction system according to at least one embodiment of the present invention,
A yield prediction system for predicting the yield in a plant factory for cultivating plants,
Photosynthesis configured to calculate the amount of photosynthesis per day of the plant from the amount of insolation data indicating the amount of insolation for each time period of the day, using a first correlation between the amount of insolation and the photosynthetic rate of the plant. a quantity calculator;
a yield prediction unit configured to predict the yield of the plant using a second correlation between the amount of photosynthesis and the yield of the plant;
Prepare.

As a result of intensive studies by the present inventors, it was found that there is a predetermined correlation between the amount of solar radiation and the photosynthetic rate of plants. According to the above configuration (1), it is possible to calculate the amount of photosynthesis per day from the solar radiation data for each time zone of the day based on the correlation between the solar radiation and the yield of the plant (first correlation). can. Then, the amount of photosynthesis calculated per day is applied to the correlation between the amount of photosynthesis of the plant and the yield (second correlation) to calculate the yield of the plant per day. can be done. Therefore, according to the above configuration (1), it is possible to appropriately predict the yield of a plant with good accuracy through a simple procedure.

(2) In some embodiments, in the configuration of (1) above,
In the first correlation, the reciprocal of the amount of solar radiation and the reciprocal of the photosynthetic rate have a linear correlation.

As a result of intensive studies by the present inventors, it was found that the reciprocal of the amount of solar radiation and the reciprocal of the photosynthetic rate of plants have a linear correlation. According to the configuration (2) above, in the first correlation, the reciprocal of the amount of solar radiation and the reciprocal of the photosynthetic rate have a linear correlation, so the plant yield can be appropriately predicted with a simple procedure and with good accuracy. can do.

(3) A plant factory management support system according to at least one embodiment of the present invention,
A management support system for a plant factory for cultivating plants,
Based on the predicted yield of the plant predicted by the yield prediction system according to (1) or (2) above, and weather forecast information or market information regarding the plant, the need for production adjustment of the plant is determined. A determination unit configured as follows.

According to the configuration of (3) above, by determining the necessity of production adjustment based on the predicted yield obtained by the configuration of (1) above and weather forecast information or market information separately acquired, the plant factory It is possible to improve profits in

(4) In some embodiments, in the configuration of (3) above,
The management support system includes:
When the determining unit determines that the production adjustment of the plant is necessary, a policy for adjusting the production is determined based on at least a comparison between the predicted yield and the target yield of the plant. A policy determination unit is provided.

According to the above configuration (4), when it is determined that plant production adjustment is necessary, at least a policy for production adjustment is determined based on a comparison between the predicted yield of the plant and the target yield. By implementing the policy determined in this way, it is possible to appropriately adjust production and improve the profit in the plant factory.

(5) In some embodiments, in the configuration of (4) above,
The management support system includes:
A display output unit configured to output information including the policy determined by the policy determination unit to a display unit.

According to the above configuration (5), the measures determined by the measure determination unit are displayed on the display unit, so that the plant factory workers can easily know the measures. Therefore, it is possible to improve the working efficiency in the plant factory.

(6) A plant factory management support system according to at least one embodiment of the present invention,
A management support system for a plant factory for cultivating plants,
Based on the predicted yield of the plant predicted by the yield prediction system according to (1) or (2) above, and the data on the weight of the fruit of the plant, the flower of the plant to be thinned or fruit thinned A deflowering target determination unit configured to determine a fruit is provided.

According to the above configuration (6), the flowers or fruits to be thinned or thinned are determined based on the predicted yield of the plant and the data on the weight of the fruit, so that the production is adjusted appropriately. It is possible to improve the profit in the plant factory.

(7) A plant factory management support system according to at least one embodiment of the present invention,
A management support system for a plant factory for cultivating plants,
A shading rate determination configured to determine a shading rate in the plant factory using the predicted yield of the plant predicted by the yield prediction system according to (1) or (2) above and weather forecast information. have a department.

According to the above configuration (7), the predicted yield of the plant and the weather forecast information are used to determine the shading rate in the plant factory. Profitability can be improved.

(8) A yield prediction method according to some embodiments of the present invention comprises:
A yield prediction method for predicting the yield in a plant factory for cultivating plants,
a step of calculating the amount of photosynthesis per day of the plant from the amount of insolation data indicating the amount of insolation for each time period of the day using the first correlation between the amount of insolation and the photosynthetic rate;
predicting the yield of the plant using a second correlation between photosynthesis and yield;
Prepare.

According to the method (8) above, it is possible to calculate the amount of photosynthesis per day from the amount of insolation data for each hour of the day based on the correlation between the amount of insolation and the yield of the plant (first correlation). can. Then, the amount of photosynthesis calculated per day is applied to the correlation between the amount of photosynthesis of the plant and the yield (second correlation) to calculate the yield of the plant per day. can be done. Therefore, according to the above method (8), it is possible to appropriately predict the yield of a plant with good accuracy using a simple procedure.

(9) A yield prediction program according to at least one embodiment of the present invention,
A yield prediction program for predicting the yield in a plant factory for cultivating plants,
to the computer,
A step of calculating the amount of photosynthesis per day of the plant from the amount of insolation data indicating the amount of insolation for each time zone of the day using the first correlation between the amount of insolation and the photosynthetic rate;
A step of predicting the yield of the plant using the second correlation between the amount of photosynthesis and the yield;
is configured to run

According to the program (9) above, the amount of photosynthesis per day can be calculated from the amount of insolation data for each hour of the day based on the correlation between the amount of insolation and the yield of plants (first correlation). can. Then, the amount of photosynthesis calculated per day is applied to the correlation between the amount of photosynthesis of the plant and the yield (second correlation) to calculate the yield of the plant per day. can be done. Therefore, according to the program of (9) above, it is possible to appropriately predict the yield of a plant with good accuracy through a simple procedure.

Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and includes modifications of the above-described embodiments and modes in which these modes are combined as appropriate.

As used herein, expressions such as "in a certain direction", "along a certain direction", "parallel", "perpendicular", "center", "concentric" or "coaxial", etc. express relative or absolute arrangements. represents not only such arrangement strictly, but also the state of being relatively displaced with a tolerance or an angle or distance to the extent that the same function can be obtained.
For example, expressions such as "identical", "equal", and "homogeneous", which express that things are in the same state, not only express the state of being strictly equal, but also have tolerances or differences to the extent that the same function can be obtained. It shall also represent the existing state.
Further, in this specification, expressions representing shapes such as a quadrilateral shape and a cylindrical shape not only represent shapes such as a quadrilateral shape and a cylindrical shape in a geometrically strict sense, but also within the range in which the same effect can be obtained. , a shape including an uneven portion, a chamfered portion, and the like.
Moreover, in this specification, the expressions “comprising”, “including”, or “having” one component are not exclusive expressions excluding the presence of other components.

10 Management support system 12 Yield prediction system 14 Photosynthesis amount calculation unit 16 Yield prediction unit 18 Judgment unit 22 Policy determination unit 24 Flower removal target determination unit 26 Shading rate determination unit 28 Supplementary light amount determination unit 30 Leaf removal amount determination unit 32 Water supply amount determination unit 34 fertilizer supply amount determination unit 36 temperature determination unit 38 display output unit 40 storage unit 42 sensor 44 display unit 50 bunch 51 stem 52 top fruit 54, 54a to 54b second fruit 56, 56a to 56d third fruit 58, 58a to 58h Fourth fruit B Respiration rate PA Photosynthetic rate PG Photosynthetic rate

Claims

A yield prediction system for predicting the yield in a plant factory for cultivating plants,
Photosynthesis configured to calculate the amount of photosynthesis per day of the plant from the amount of insolation data indicating the amount of insolation for each time period of the day, using a first correlation between the amount of insolation and the photosynthetic rate of the plant. a quantity calculator;
a yield prediction unit configured to predict the yield of the plant using a second correlation between the amount of photosynthesis and the yield of the plant;
Yield prediction system with
The yield prediction system according to claim 1, wherein in the first correlation, the reciprocal of the solar radiation amount and the reciprocal of the photosynthetic rate have a linear correlation.
A management support system for a plant factory for cultivating plants,
It is configured to determine whether or not production adjustment of the plant is necessary based on the predicted yield of the plant predicted by the yield prediction system according to claim 1 or 2 and weather forecast information or market information regarding the plant. A management support system for a plant factory comprising a determined determination unit.
When the determining unit determines that the production adjustment of the plant is necessary, a policy for adjusting the production is determined based on at least a comparison between the predicted yield and the target yield of the plant. The plant factory management support system according to claim 3, comprising a policy decision unit.
5. The plant factory management support system according to claim 4, comprising a display output unit configured to output information including the policy determined by the policy decision unit to a display unit.
A management support system for a plant factory for cultivating plants,
Determine the flower or fruit of the plant to be thinned or thinned based on the predicted yield of the plant predicted by the yield prediction system according to claim 1 or 2 and the data on the weight of the fruit of the plant. 1. A management support system for a plant factory comprising a deflowering target determination unit configured to:
A management support system for a plant factory for cultivating plants,
A shading rate determination unit configured to determine a shading rate in the plant factory using the predicted yield of the plant predicted by the yield prediction system according to claim 1 or 2 and weather forecast information. Management support system for plant factories.
A yield prediction method for predicting the yield in a plant factory for cultivating plants,
a step of calculating the amount of photosynthesis per day of the plant from the amount of insolation data indicating the amount of insolation for each time period of the day, using a first correlation between the amount of insolation and the photosynthetic rate of the plant;
predicting the yield of the plant using a second correlation between the amount of photosynthesis of the plant and the yield;
A yield prediction method comprising:
A yield prediction program for predicting the yield in a plant factory for cultivating plants,
to the computer,
A step of calculating the amount of photosynthesis per day of the plant from the amount of insolation data indicating the amount of insolation for each time period of the day using the first correlation between the amount of insolation and the photosynthetic rate of the plant;
a step of predicting the yield of the plant using a second correlation between the amount of photosynthesis and the yield of the plant;
Yield prediction program for executing