Growth state estimation device, plant management system, growth state estimation method, and program

Abstract

To enable understanding of a plant growth state regardless of the skill level of a worker.SOLUTION: The growth state estimation device may include an acquisition unit that acquires multiple indices related to leaf expansion of a plant. The growth state estimation device may include an estimation unit that estimates the growth state of the plant based on relationship information indicating a relationship between the multiple indices related to leaf expansion of the plant and the growth state of the plant, and the multiple indices acquired by the acquisition unit. The multiple indices may include at least two of leaf hardness, leaf thickness, vein density, stem thickness, leaf color, vein color, leaf shape, leaf size, phyllotaxis, and leaf attachment angle.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present invention relates to a growth state estimating device, a plant management system, a growth state estimating method, and a program. [Background technology]

[0002] Patent document 1 describes a method of generating learning data from image data before and after fruit thinning, inputting unknown image data showing unknown agricultural crops before fruit thinning, and estimating the target of fruit thinning using the learned learning model. [Prior art document] [Patent documents] [Patent Document 1] JP 2022-114418 A Summary of the Invention [Problem to be solved by the invention]

[0003] It is desirable to be able to grasp the growth state of plants regardless of the skill level of the worker. [Means for solving the problem]

[0004] A growth state estimation device according to an aspect of the present invention may include an acquisition unit that acquires a plurality of indices related to leaf expansion of a plant. The growth state estimation device may include an estimation unit that estimates a growth state of the plant based on relationship information indicating a relationship between the plurality of indices related to leaf expansion of the plant and a growth state of the plant and the plurality of indices acquired by the acquisition unit.

[0005] In the growth state estimation device, the estimation unit may estimate the growth state of the plant based on a trained prediction model in which the multiple indicators are used as explanatory variables and the growth state of the plant is used as a target variable.

[0006] In any of the growth condition estimation devices, the multiple indicators may include at least two of leaf hardness, leaf thickness, vein density, stem thickness, leaf color, vein color, leaf shape, leaf size, phyllotaxy, and leaf attachment angle.

[0007] In any of the growth state estimation devices, the acquisition unit may acquire a leaf hardness based on a measurement result using a hardness meter. The acquisition unit may acquire a leaf thickness based on a measurement result using a thickness measuring device. The acquisition unit may acquire a stem thickness based on a measurement result using a thickness measuring device or a result of image analysis of an image of the plant captured by an imaging device. Or, the acquisition unit may acquire at least one of a leaf vein density, a leaf color, a leaf vein color, a leaf shape, a leaf size, a phyllotaxis, and a leaf attachment angle based on a result of image analysis of an image of the plant captured by an imaging device.

[0008] A plant management system according to one embodiment of the present invention may include any of the growth state estimation devices and an environmental control unit that controls environmental control equipment that controls the environment within a plant factory in which the plants are cultivated in accordance with predetermined conditions corresponding to the estimation result of the growth state of the plant by the estimation unit.

[0009] In the plant management system, the predetermined conditions may indicate a relationship between the growth state of the plant and at least one of the water content, electrical conductivity, hydrogen ion exponent, temperature and humidity around the plant, the amount of light irradiated to the plant, and carbon dioxide concentration of the culture medium. The environmental control unit may adjust at least one of the water content, electrical conductivity, hydrogen ion exponent, temperature and humidity around the plant, the amount of light irradiated to the plant, and carbon dioxide concentration of the culture medium by controlling the environmental control equipment according to the predetermined conditions.

[0010] In any of the plant management systems, the multiple indices may include at least two of leaf hardness, leaf thickness, vein density, stem thickness, leaf color, vein color, leaf shape, leaf size, phyllotaxis, and leaf attachment angle. The acquisition unit may acquire leaf hardness based on a measurement result using a hardness meter. The acquisition unit may acquire leaf thickness based on a measurement result using a thickness measuring device. The acquisition unit may acquire stem thickness based on the measurement result using the thickness measuring device or the result of image analysis of an image of the plant captured by an imaging device. Alternatively, the acquisition unit may acquire at least one of vein density, leaf color, vein color, leaf shape, leaf size, phyllotaxis, and leaf attachment angle based on the result of image analysis of an image of the plant captured by an imaging device. The plant management system may further include a mobile body control unit that moves a mobile body having an arm holding at least one of the hardness meter, the thickness measuring device, and the imaging device within the plant factory and causes at least one of the hardness meter, the thickness measuring device, and the imaging device to perform measurements related to the multiple indicators of the plant.

[0011] In any of the plant management systems, the environmental control equipment may include a nutrient solution supplying equipment that supplies a nutrient solution containing a fertilizer component to the plant. The environmental control unit may adjust a fertilizer concentration of the nutrient solution supplied to the plant by the nutrient solution supplying equipment so that the growth state of the plant estimated by the estimation unit becomes a predetermined growth state.

[0012] In any of the plant management systems, the environmental control equipment may include an irrigation equipment that supplies water to a medium in which the plant is grown. The environmental control unit may adjust the amount of water irrigated to the medium by the irrigation equipment so that the growth state of the plant estimated by the estimation unit becomes a predetermined growth state.

[0013] In any of the plant management systems, the environmental control facility may include a light source facility having a light source that irradiates the plant with artificial light. The environmental control unit may adjust an amount of light irradiated to the plant by the light source facility and an irradiation time such that the growth state of the plant estimated by the estimation unit becomes a predetermined growth state.

[0014] A growth state estimation method according to an aspect of the present invention may include a step of acquiring a plurality of indices related to leaf expansion of a plant by an acquisition unit, and a step of estimating a growth state of the plant based on relationship information indicating a relationship between the plurality of indices related to leaf expansion of the plant and a growth state of the plant and the plurality of indices acquired by the acquisition unit.

[0015] A program according to an aspect of the present invention may cause a computer to function as an acquisition unit that acquires a plurality of indices related to leaf expansion of a plant. The program may cause the computer to function as an estimation unit that estimates a growth state of the plant based on relationship information indicating a relationship between the plurality of indices related to leaf expansion of the plant and a growth state of the plant, and the plurality of indices acquired by the acquisition unit.

[0016] The above summary of the invention does not list all of the features of the present invention. Also, subcombinations of these features may also be inventions. [Brief description of the drawings]

[0017] [Figure 1] FIG. 2 is a diagram illustrating an example of functional blocks of the overall configuration of the plant management system. [Diagram 2] FIG. 1 is a diagram showing a mobile robot moving within a plant factory. [Diagram 3] FIG. 13 is a diagram for explaining the leaf attachment angle. [Figure 4] FIG. 2 is a diagram illustrating an example of functional blocks of the plant management device. [Diagram 5] 11 is a flowchart showing an example of a procedure for environmental control according to leaf tension. [Figure 6] FIG. 2 illustrates an example of a hardware configuration. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention according to the claims. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0019] In order to harvest plants such as vegetables, fruits, or flowers in a desired growth state, it is important to grasp the growth state of the plants during the cultivation process. This is because it is necessary to control the environment in which the plants exist depending on the growth state of the plants. Here, an expert may grasp the growth state of the plants by checking the tension of the leaves of the plants. However, it is not easy for an inexperienced worker to grasp the growth state of the plants by checking the tension of the leaves of the plants. Therefore, it is desired to be able to grasp the growth state of the plants based on the tension of the leaves of the plants, regardless of the skill level of the worker.

[0020] Therefore, in this embodiment, a system is provided that can estimate the growth state of a plant based on the tension of the leaves of the plant, regardless of the skill level of an operator.

[0021] FIG. 1 is a diagram showing an example of a functional block of the overall configuration of a plant management system according to this embodiment. The plant management system includes a gutter 20, a light source equipment 40, a nutrient solution supplying equipment 50, a carbon dioxide supplying equipment 60, an air conditioning equipment 70, a ventilation equipment 80, a sensor 90, and a plant management device 100. The light source equipment 40, the nutrient solution supplying equipment 50, the carbon dioxide supplying equipment 60, the air conditioning equipment 70, and the ventilation equipment 80 are examples of environmental control equipment. In this embodiment, the plant factory 10 is an artificial light type plant factory that uses artificial light such as LEDs or incandescent lamps as a light source to cultivate the plants 30. However, the plant factory 10 may be a sunlight type plant factory that uses sunlight as a light source to cultivate the plants 30.

[0022] The multiple gutters 20 cultivate plants 30 such as vegetables, fruits, or flowers. The sowing date may be shifted for each set of one or more gutters 20, so that the plants 30 can be harvested at different harvest times. The multiple gutters 20 may be installed in separate spaces 12 for each set of one or more gutters 20, and the environments in the spaces 12 may be individually controlled by environmental control equipment, so that the plants 30 may be cultivated in different environmental conditions for each space 12. The spaces may be highly insulated and airtight. The plant management device 100 may individually control the environmental conditions for each set of gutters 20. Depending on the type of the plants 30, the plants 30 may be cultivated in a cultivation unit in which multiple cultivation shelves are stacked.

[0023] The light source equipment 40 includes a plurality of light sources 42 that emit artificial light, such as LEDs or incandescent lamps, and emits artificial light from each of the plurality of light sources 42 to the plants 30. The plurality of light sources 42 may be disposed facing the cultivation surface of the gutter 20.

[0024] The nutrient solution supplying equipment 50 has a pump 52 and a pipe 54, and supplies a nutrient solution containing each fertilizer component such as potassium or calcium to the gutter 20 via the pump 52 and the pipe 54. The nutrient solution supplying equipment 50 appropriately adjusts the fertilizer concentration and supplies the nutrient solution with the adjusted fertilizer concentration to the plant 30. The nutrient solution supplying equipment 50 may supply the nutrient solution to the plant 30 by spraying the nutrient solution with the adjusted fertilizer concentration in the form of a mist onto the roots of the plant 30. The nutrient solution supplying equipment 50 may function as an irrigation equipment that supplies water to the medium in which the plant 30 is grown. The amount of irrigation water supplied to the gutter 20 may be adjusted by adjusting the amount of nutrient solution supplied from the nutrient solution supplying equipment 50 to the gutter 20.

[0025] The carbon dioxide supplying equipment 60 has a tank 62 and a nozzle 64. The tank 62 stores carbon dioxide. The carbon dioxide supplying equipment 60 supplies the carbon dioxide stored in the tank 62 to each space 12 in the plant factory 10 via the nozzle 64.

[0026] The air conditioning equipment 70 adjusts the temperature and humidity of the air in the plant factory 10, and circulates the temperature- and humidity-adjusted air in each space. The ventilation equipment 80 includes a circulator or an electric fan that supplies wind to the plant factory 10. The sensor 90 includes various sensors that measure the environmental conditions around the plant 30 and the growth condition of the plant 30. The sensor 90 includes various sensors that measure the temperature, humidity, light amount, and carbon dioxide concentration of the stem, leaf, and fruit of the plant 30. The sensor 90 may include an imaging device that images the plant 30.

[0027] The plant management device 100 controls the growth state of the plant 30 by controlling the light source equipment 40, the nutrient solution supplying equipment 50, the carbon dioxide supplying equipment 60, the air conditioning equipment 70, and the air blowing equipment 80. The plant management device 100 communicates with the light source equipment 40, the nutrient solution supplying equipment 50, the carbon dioxide supplying equipment 60, the air conditioning equipment 70, and the air blowing equipment 80 via a wireless network or a wired network. The plant management device 100 is an example of a growth state estimation device.

[0028] The plant management device 100 may be a computer having a central processing unit (CPU) and a memory. The light source equipment 40, the nutrient solution supply equipment 50, the carbon dioxide supply equipment 60, the air conditioning equipment 70, and the ventilation equipment 80 may each be equipped with a computer having a central processing unit (CPU) and a memory.

[0029] The computer may be a personal computer, a tablet computer, a smartphone, a workstation, a server computer, a general-purpose computer, or a computer system in which multiple computers are connected. Such a computer system is also a computer in a broad sense. The computer may be a dedicated computer designed for environmental control of a plant factory, or may be dedicated hardware realized by a dedicated circuit. The computer may be implemented by a virtual computer environment. When a computer is used, the plant management device 100, the light source equipment 40, the nutrient solution supply equipment 50, the carbon dioxide supply equipment 60, the air conditioning equipment 70, and the air blowing equipment 80 are realized by executing a program by the computer.

[0030] 2 shows a mobile robot 200 moving within the plant factory 10. The mobile robot 200 is a vehicle that moves on the ground. The mobile robot 200 may be an aircraft such as an unmanned aerial vehicle that moves in the air, or a ship that moves on water. The mobile robot 200 may move between gutters 20 in which plants 30 are cultivated.

[0031] Mobile robot 200 includes arm 210 and measuring unit 212 provided at the tip of arm 210. Arm 210 may be a multi-joint arm unit rotatably provided on the main body of mobile robot 200. Measuring unit 212 may include a hardness meter, a thickness gauge, and an imaging device. The configuration of mobile robot 200 is an example, and any configuration may be used as long as measuring unit 212 can perform various measurements required to estimate the growth state of plant 30.

[0032] The hardness meter may measure the hardness (hardness) of the leaves of the plant 30. The mobile robot 200 may control the arm 210 so that the hardness meter can measure the hardness of the leaf blade portion other than the veins of the leaf by performing image recognition with an imaging device provided on the arm 210.

[0033] The thickness measuring device may measure the thickness of the leaf. The thickness measuring device may be a digital caliper or a micrometer. The mobile robot 200 may control the arm 210 so that the thickness measuring device can measure the thickness of the leaf blade portion other than the veins of the leaf by performing image recognition using an imaging device provided on the arm 210.

[0034] The thickness measuring device may measure the thickness of the stem of the plant 30. The thickness measuring device may measure the thickness of the main axis or the lateral axis of the plant 30 as the stem thickness. The mobile robot 200 may control the arm 210 so that the thickness measuring device can measure the stem thickness by performing image recognition with an imaging device provided on the arm 210. The plant management device 100 may measure the stem thickness by performing image analysis on the image of the plant 30 captured by the imaging device.

[0035] Furthermore, the plant management device 100 may identify at least one of the vein density, leaf color, vein color, leaf shape, leaf size, phyllotaxy, and leaf attachment angle of the plant 30 by performing image analysis on the image of the plant 30 captured by the imaging device. The leaf attachment angle is the angle α between the branch 32 and the petiole 34, as shown in Fig. 3. The imaging device may be a twin-lens 3D camera or a ToF (Time of Flight) camera.

[0036] Note that the measurement of the plant 30 using the hardness meter or thickness gauge may be performed by an operator, and the operator may input the measurement results into the plant management device 100.

[0037] The measurement unit 212 may further include various sensors that measure the environmental conditions around the plant 30 and the growth conditions of the plant 30. The measurement unit 212 may include various sensors that measure the temperature, humidity, light amount, and carbon dioxide concentration of the stem, leaf, and fruit parts of the plant 30, respectively.

[0038] 4 is a diagram showing an example of functional blocks of the plant management device 100. The plant management device 100 includes an acquisition unit 102, an estimation unit 104, a generation unit 120, an environment control unit 140, a mobile object control unit 150, and a storage unit 130. The storage unit 130 stores programs that operate in the plant management device 100. The programs are executed on a processor included in the plant management device 100 to cause the processor to function as the acquisition unit 102, the estimation unit 104, and the environment control unit 140.

[0039] The acquisition unit 102 acquires a plurality of indices related to the leaf firmness of the plant 30. The indices related to the leaf firmness of the plant 30 may be measurement values ​​related to characteristics of the plant 30 having a relative relationship with the leaf firmness of the plant 30. The plurality of indices may include at least two of the leaf hardness, leaf thickness, vein density, stem thickness, leaf color, vein color, leaf shape, leaf size, phyllotaxy, and leaf attachment angle of the plant 30.

[0040] The acquisition unit 102 may acquire the hardness of the leaf based on the measurement result by the hardness meter. The acquisition unit 102 may acquire the thickness of the leaf based on the measurement result by the thickness measuring device. The acquisition unit 102 may acquire the thickness of the stem based on the measurement result by the thickness measuring device or the result of image analysis of the image of the plant 30 captured by the imaging device. The acquisition unit 102 may acquire at least one of the density of the leaf veins, the color of the leaf veins, the leaf shape, the leaf size, the phyllotaxis, and the leaf attachment angle based on the result of image analysis of the image of the plant 30 captured by the imaging device.

[0041] The acquisition unit 102 may acquire the above-mentioned multiple indexes from the measurement unit 212 mounted on the mobile robot 200. The acquisition unit 102 may perform image analysis on the image of the plant 30 acquired from the measurement unit 212 to identify at least one of the stem thickness, leaf color, vein color, leaf shape, leaf size, phyllotaxy, and leaf attachment angle.

[0042] The mobile object control unit 150 controls the mobile robot 200 moving within the plant factory 10. The mobile object control unit 150 may move the mobile robot 200 to a predetermined measurement point according to a predetermined schedule, and cause the measurement unit 212 to measure a plurality of indexes related to the leaf tension of the plant 30. The mobile object control unit 150 may move the mobile robot 200 within the plant factory 10, and cause at least one of the hardness meter, the thickness measuring device, and the imaging device to perform measurements related to a plurality of indexes of the plant 30.

[0043] The estimation unit 104 estimates the growth state of the plant 30 based on the relationship information indicating the relationship between a plurality of indices related to the leaf expansion of the plant 30 and the growth state of the plant 30, and the plurality of indices acquired by the acquisition unit 102. The growth state of the plant 30 may indicate the individual weight of the plant 30, the quality (size, color, taste, etc.) of the plant 30, or the health state of the plant 30, such as the occurrence state of physiological disorders.

[0044] The estimation unit 104 estimates the growth state of the plant 30 based on multiple indexes related to leaf expansion, thereby making it possible to more accurately identify the growth state of the plant 30. Since the error in estimating the growth state of the plant 30 is reduced, the plant management device 100 can reduce the processing burden associated with estimating the growth state of the plant 30. The estimation unit 104 estimates the growth state of the plant 30 by focusing on at least two indexes related to the leaf expansion of the plant 30, thereby making it possible to significantly reduce the data processing burden required for estimation by the estimation unit 104 compared to the case where the growth state of the plant 30 is estimated based on a large number of diverse indexes related to the plant 30.

[0045] The estimation unit 104 may estimate the growth state of the plant 30 based on a trained prediction model in which a plurality of indices related to the leaf expansion of the plant 30 are used as explanatory variables and the growth state of the plant 30 is used as a response variable.

[0046] The generating unit 120 may perform machine learning according to a supervised learning algorithm using index data indicating multiple indexes related to the leaf expansion of the plant 30 as explanatory variables and growth state data indicating the growth state of the plant 30 as a target variable to generate a trained prediction model that predicts the growth state of the plant 30 from multiple indexes related to the leaf expansion of the plant 30, and may store the trained model in the storage unit 130. The algorithm may be any type of algorithm, such as a neural network, a support vector machine, a multiple regression analysis, or a decision tree.

[0047] The generating unit 120 may generate N-dimensional index distribution data based on N indexes. The generating unit 120 may perform machine learning according to a supervised learning algorithm with the index distribution data as explanatory variables and the growth state data of the plant 30 as objective variables to generate a trained prediction model that predicts the growth state of the plant 30 from each index, and store the trained model in the storage unit 130. The algorithm may be any type of algorithm, such as a neural network, a support vector machine, a multiple regression analysis, or a decision tree.

[0048] The generation unit 120 may include a preprocessing unit 122, a model generation unit 126, and a model update unit 128.

[0049] The preprocessing unit 122 performs preprocessing on the multiple index data and growth state data stored in the storage unit 130, and supplies the preprocessed data to the model generation unit 126. The preprocessing unit 122 may perform preprocessing for learning.

[0050] The model generation unit 126 uses the index data and the growth state data to generate a trained model that predicts the growth state data from the index data, and stores the trained model in the storage unit 130. The model update unit 128 uses the index data and the growth state data to update the trained model.

[0051] The pre-processing unit 122 may associate the index data and the growth state data according to the acquisition time of the measured value or image from the measurement unit 212. As an example, the pre-processing unit 122 may associate the index data and the growth state data for the same acquisition date, or for different acquisition dates or for the same time interval on the same acquisition date, according to the acquisition time of the measured value or image.

[0052] The pre-processing unit 122 may perform missing data interpolation such as time-series measured values. The pre-processing unit 122 may use an interpolation algorithm such as linear interpolation or spline interpolation to interpolate data for periods where no data exists. When the difference between the data and the average value of a plurality of data exceeds a threshold value predetermined by the user, the pre-processing unit 122 may delete the data as an outlier or change the value to the same as the data before and after the data on the time axis. The pre-processing unit 122 may perform rounding processing such as truncating the data to a predetermined digit or less. The pre-processing unit 122 may discretize the index data and growth state data and associate them with the cultivation area in each cultivation period (sowing, raising seedlings, planting, greening).

[0053] The preprocessing unit 122 may perform preprocessing to extract feature quantities of the index data and the growth state data. The preprocessing unit 122 may extract at least one of an integrated value, a differential value, an average value, a variance value, and data obtained by separating a daytime component and a nighttime component as feature quantities for at least one of the index data and the growth state data. The preprocessing unit 122 may calculate an integrated value of data for each predetermined period as feature quantities. As an example, the preprocessing unit 122 may extract an integrated value of the number of occurrences of a fault, temperature, or humidity, etc., every three hours as feature quantities. In this way, by calculating the integrated value, it is possible to know the delayed influence. The preprocessing unit 122 may calculate a differential value of data at a plurality of data acquisition times and extract the differential value as feature quantities. The preprocessing unit 122 may regard data that changes on the time axis as a composite wave of a daytime component and a nighttime component, and separate one of the daytime component and the nighttime component by interpolation (e.g., spline interpolation) or a frequency decomposition method (e.g., Fourier transform, etc.). Then, the preprocessing unit 122 may separate the difference between one of the separated daytime and nighttime components and the sensor data as the other of the daytime and nighttime components.

[0054] The preprocessing unit 122 may divide the preprocessed data into intervals such as the cultivation period or time period (day and night), and create a data set using the preprocessed data for each interval (average value, variance value, etc.) as explanatory variables. The preprocessing unit 122 supplies the preprocessed data set to the model generation unit 126.

[0055] The model generation unit 126 may receive a portion of the growth status data identified from the index data indicating various indexes acquired by the acquisition unit 102 from the pre-processing unit 122 as data for model generation, and generate a trained model using the data for model generation.

[0056] In addition, the model update unit 128 may compare the growth state of the plant 30 corresponding to a set of multiple indicators with the growth state of the plant 30 predicted from the indicator data using the trained model, and update the trained model.

[0057] The environmental control unit 140 may adjust the fertilizer concentration of the nutrient solution supplied to the medium of the gutter 20 by the nutrient solution supplying equipment 50 so that the growth state of the plant 30 estimated by the estimation unit 104 reaches a predetermined growth state that should be met at the time of estimation. If the growth state of the plant 30 estimated by the estimation unit 104 has not reached the predetermined growth state that should be met at the time of estimation, the environmental control unit 140 may adjust the fertilizer concentration of the nutrient solution supplied to the medium of the gutter 20 by the nutrient solution supplying equipment 50 to increase it. If the growth state of the plant 30 estimated by the estimation unit 104 is growing lower than the predetermined growth state that should be met at the time of estimation, the environmental control unit 140 may adjust the fertilizer concentration of the nutrient solution supplied to the medium of the gutter 20 by the nutrient solution supplying equipment 50 to decrease it. If the plant 30 is a tomato or the like whose growth condition changes depending on the amount of irrigation, the environmental control unit 140 may adjust the amount of irrigation water supplied to the culture medium in the gutter 20 by the nutrient solution supply equipment 50 so that the growth condition of the plant 30 estimated by the estimation unit 104 matches a predetermined growth condition that should be met at the time of estimation.

[0058] The environment control unit 140 may adjust the amount of light irradiated to the plant 30 by the light source equipment 40 and the irradiation time so that the growth state of the plant 30 estimated by the estimation unit 104 becomes a predetermined growth state that should be satisfied at the time of estimation. If the growth state of the plant 30 estimated by the estimation unit 104 has not reached the predetermined growth state that should be satisfied at the time of estimation, the environment control unit 140 may increase the amount of light irradiated to the plant 30 by the light source equipment 40. Alternatively, the environment control unit 140 may extend the irradiation time of light to the plant 30 by the light source equipment 40. On the other hand, if the growth state of the plant 30 estimated by the estimation unit 104 is growing worse than the predetermined growth state that should be satisfied at the time of estimation, the environment control unit 140 may reduce the amount of light irradiated to the plant 30 by the light source equipment 40. Alternatively, the environment control unit 140 may shorten the irradiation time of light to the plant 30 by the light source equipment 40.

[0059] The environmental control unit 140 may control an environmental control facility that controls the environment in the plant factory 10 in which the plant 30 is grown, according to predetermined conditions corresponding to the estimation result of the growth state of the plant 30 by the estimation unit 104. The environmental control unit 140 may control at least one of the light source facility 40, the nutrient solution supply facility 50, the carbon dioxide supply facility 60, the air conditioning facility 70, and the ventilation facility 80, according to predetermined conditions corresponding to the estimation result of the growth state of the plant 30 by the estimation unit 104.

[0060] The predetermined conditions may indicate a relationship between the growth state of the plant 30 and at least one of the water content, electrical conductivity, hydrogen ion exponent, temperature around the leaves, humidity, amount of light irradiated to the leaves, and carbon dioxide concentration of the medium. The environment control unit 140 may adjust at least one of the water content, electrical conductivity, hydrogen ion exponent, temperature around the leaves, humidity, amount of light irradiated to the leaves, and carbon dioxide concentration of the medium by controlling the environment control device according to the predetermined conditions. The environment control unit 140 may adjust at least one of the water content, electrical conductivity, hydrogen ion exponent, temperature around the leaves, humidity, amount of light irradiated to the leaves, and carbon dioxide concentration of the medium by controlling at least one of the light source equipment 40, the nutrient solution supply equipment 50, the carbon dioxide supply equipment 60, the air conditioning equipment 70, and the ventilation equipment 80 according to the predetermined conditions.

[0061] For example, measures to suppress each type of physiological disorder of leaves are known empirically. The memory unit 130 may store at least one of the control contents of the light source equipment 40, the nutrient solution supplying equipment 50, the carbon dioxide supplying equipment 60, the air conditioning equipment 70, and the ventilation equipment 80 for each type of physiological disorder. The environment control unit 140 may specify the control contents according to the type of physiological disorder of leaves corresponding to the estimated growth state by referring to the memory unit 130, and control at least one of the light source equipment 40, the nutrient solution supplying equipment 50, the carbon dioxide supplying equipment 60, the air conditioning equipment 70, and the ventilation equipment 80 according to the specified control contents.

[0062] For example, when tip burn due to calcium deficiency is progressing as a physiological disorder of leaves, the environmental control unit 140 may control the nutrient solution supplying equipment 50 so as to increase the calcium content in the nutrient solution. Alternatively, the environmental control unit 140 may control the light source equipment 40 so as to reduce the amount of light from the light source 42. The environmental control unit 140 may control the air conditioning equipment 70 so as to lower the temperature in the plant factory 10. The environmental control unit 140 may control the ventilation equipment 80 so as to increase the amount of air supplied to the plant factory 10 so as to efficiently lower the temperature in the plant factory 10.

[0063] FIG. 5 is a flow chart showing an example of a procedure for controlling the environment according to the expansion of the leaves.

[0064] The acquisition unit 102 acquires a plurality of indices relating to the vigor of the plant 30 from the measurement unit 212 mounted on the mobile robot 200 (S100). The acquisition unit 102 may perform image analysis on the image of the plant 30 acquired from the measurement unit 212 to identify at least one of the stem thickness, leaf color, vein color, leaf shape, leaf size, phyllotaxy, and leaf attachment angle.

[0065] The estimation unit 104 estimates the growth state of the plant 30 based on relationship information indicating the relationship between multiple indices related to the leaf expansion of the plant 30 and the growth state of the plant 30, and the multiple indices acquired by the acquisition unit 102 (S102).

[0066] The environmental control unit 140 determines whether the growth state of the plant 30 satisfies a predetermined growth state at the time of estimation (S104). If it does, the environmental control unit 140 continues to control the environmental control equipment under the current environmental control conditions.

[0067] If the estimated growth state of the plant 30 is not a predetermined growth state assumed at the time of estimation, and the estimated growth state of the plant 30 is behind the predetermined growth state assumed at the time of estimation ("Y" in S106), the environmental control unit 140 controls the nutrient solution supplying equipment 50 and the light source equipment 40 to increase the fertilizer concentration of the nutrient solution supplied to the medium in the gutter 20 and the amount of light irradiated to the plant 30 (S108). If the growth state of the plant 30 changes depending on the amount of irrigation, the environmental control unit 140 may increase the amount of irrigation supplied to the plant 30 instead of adjusting the fertilizer concentration.

[0068] On the other hand, if the estimated growth state of the plant 30 is more advanced than the predetermined growth state assumed at the time of estimation ("N" in S106), the nutrient solution supply equipment 50 and the light source equipment 40 are controlled to reduce the fertilizer concentration of the nutrient solution supplied to the medium in the gutter 20 and the amount of light irradiated to the plant 30 (S110). If the growth state of the plant 30 changes depending on the amount of irrigation, the environment control unit 140 may reduce the amount of irrigation supplied to the plant 30 instead of adjusting the fertilizer concentration.

[0069] As described above, according to the present embodiment, the growth state of the plant 30 can be estimated based on a plurality of indices related to the leaf expansion of the plant 30, regardless of the proficiency of the worker. Since the plant management device 100 can estimate the growth state of the plant 30 based on at least two indices related to the leaf expansion of the plant 30, the data processing load related to the estimation of the growth state of the plant 30 can be significantly reduced compared to the case where the growth state of the plant 30 is estimated based on a large number of various indices of the plant 30. Furthermore, the plant management device 100 can more accurately control the environmental control equipment based on the estimated result of the growth state so that the environment in the plant factory 10 becomes the growth state that the plant 30 should satisfy. By improving the accuracy of the estimation of the growth state of the plant 30, the processing time required for the plant management device 100 to appropriately control the environmental control equipment can be shortened, and the processing load of the plant management device 100 can be reduced.

[0070] 6 shows an example of a computer 1200 that may embody aspects of the present embodiment in whole or in part. A program installed on the computer 1200 may cause the computer 1200 to perform operations associated with an apparatus according to an embodiment of the present invention or one or more "parts" of the apparatus. Alternatively, the program may cause the computer 1200 to execute the operations or one or more "parts". The program may cause the computer 1200 to execute a process or steps of the process according to an embodiment of the present invention. Such a program may be executed by the CPU 1212 to cause the computer 1200 to execute specific operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

[0071] The computer 1200 according to this embodiment includes a CPU 1212 and a RAM 1214, which are connected to each other by a host controller 1210. The computer 1200 also includes a communication interface 1222 and an input / output unit, which are connected to the host controller 1210 via an input / output controller 1220. The computer 1200 also includes a ROM 1230. The CPU 1212 operates according to programs stored in the ROM 1230 and the RAM 1214, thereby controlling each unit.

[0072] The communication interface 1222 communicates with other electronic devices via a network. The hard disk drive may store programs and data used by the CPU 1212 in the computer 1200. The ROM 1230 stores a boot program executed by the computer 1200 when activated and / or a program that depends on the hardware of the computer 1200. The programs are provided via a computer-readable storage medium such as a CR-ROM, a USB memory, or an IC card, or a network. The programs are installed in the RAM 1214, which is also an example of a computer-readable storage medium, or the ROM 1230, and executed by the CPU 1212. The information processing described in these programs is read by the computer 1200, and brings about cooperation between the programs and the various types of hardware resources. An apparatus or method may be configured by implementing an operation or processing of information according to the use of the computer 1200.

[0073] For example, when communication is performed between the computer 1200 and an external device, the CPU 1212 may execute a communication program loaded in the RAM 1214 and instruct the communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 1212, the communication interface 1222 reads transmission data stored in a transmission buffer area provided in the RAM 1214 or a storage medium such as a USB memory, transmits the read transmission data to a network, or writes reception data received from the network to a reception buffer area or the like provided on the storage medium.

[0074] Furthermore, the CPU 1212 may cause all or a necessary portion of a file or database stored in an external storage medium such as a USB memory to be read into the RAM 1214, and perform various types of processing on the data on the RAM 1214. The CPU 1212 may then write back the processed data to the external storage medium.

[0075] Various types of information, such as various types of programs, data, tables, and databases, may be stored in the storage medium and undergo information processing. The CPU 1212 may perform various types of processing on the data read from the RAM 1214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequence of the program, and writes back the results to the RAM 1214. The CPU 1212 may also search for information in a file, database, etc. in the storage medium. For example, when a plurality of entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored in the storage medium, the CPU 1212 may search for an entry that matches a condition, in which the attribute value of the first attribute is specified, from among the plurality of entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0076] The above-described programs or software modules may be stored in a computer-readable storage medium on the computer 1200 or in the vicinity of the computer 1200. Also, a storage medium such as a hard disk or a RAM provided in a server system connected to a dedicated communication network or the Internet can be used as a computer-readable storage medium, thereby providing the programs to the computer 1200 via the network.

[0077] A computer-readable medium may include any tangible device capable of storing instructions that are executed by a suitable device. As a result, a computer-readable medium having instructions stored thereon comprises an article of manufacture that includes instructions that can be executed to create means for performing the operations specified in the flowchart or block diagram. Examples of computer-readable media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, and the like. More specific examples of computer-readable media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disk read-only memories (CD-ROMs), digital versatile disks (DVDs), Blu-ray (RTM) disks, memory sticks, integrated circuit cards, and the like.

[0078] The computer readable instructions may include either source code or object code written in any combination of one or more programming languages. The source code or object code includes conventional procedural programming languages. The conventional procedural programming languages ​​may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state setting data, or object oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and the “C” programming language or similar programming languages. The computer readable instructions may be provided to a processor or programmable circuitry of a general purpose computer, special purpose computer, or other programmable data processing apparatus locally or over a wide area network (WAN) such as a local area network (LAN), the Internet, etc. The processor or programmable circuitry may execute the computer readable instructions to create means for performing the operations specified in the flowcharts or block diagrams. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0079] Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It is clear to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the description of the claims that such modifications and improvements can also be included in the technical scope of the present invention.

[0080] It should be noted that the order of execution of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and may be realized in any order unless the output of a previous process is used in a later process. Even if the operational flow in the claims, specifications, and drawings is explained using "first," "next," etc. for convenience, it does not mean that it is essential to perform the process in this order. [Explanation of symbols]

[0081] 10 Plant factory 12 Space 20 Gutter 30 plants 32 Branches 34 Petiole 40 Light source equipment 42 Light source 50 Nutrient solution supply equipment 52 Pump 54 Pipe 60 Carbon dioxide supply equipment 62 Tank 64 Nozzles 70 Air conditioning equipment 80 Ventilation equipment 90 Sensors 100 Plant management equipment 102 Acquisition Department 104 Estimation part 120 Generation part 122 Pretreatment section 126 Model Generation Unit 128 Model Update Section 130 Storage section 140 Environmental Control Section 150 Mobile control unit 200 Mobile Robot 210 Arm 212 Measurement Unit 1200 Computer 1210 Host Controller 1212 CPU 1214 RAM 1220 Input / Output Controller 1222 Communication Interface 1230 ROM

Claims

1. An acquisition unit that acquires a plurality of indices related to the leaf expansion of a plant; an estimation unit that estimates a growth state of the plant based on relationship information indicating a relationship between a plurality of indexes related to leaf expansion of the plant and a growth state of the plant and the plurality of indexes acquired by the acquisition unit; A growth state estimation device comprising:

2. The growth state estimation device according to claim 1 , wherein the estimation unit estimates the growth state of the plant based on a trained prediction model in which the plurality of indexes are used as explanatory variables and the growth state of the plant is used as a response variable.

3. 2. The growth state estimation device according to claim 1, wherein the plurality of indices include at least two of leaf hardness, leaf thickness, vein density, stem thickness, leaf color, vein color, leaf shape, leaf size, phyllotaxy, and leaf attachment angle.

4. The acquisition unit is The hardness of the leaves is obtained based on the measurement results using a hardness meter. Obtain the leaf thickness based on the measurement results using the thickness measuring device; Obtaining the thickness of the stem based on the measurement result by a thickness measuring device or the result of image analysis of the image of the plant captured by an imaging device, or The growth state estimation device according to claim 3, further comprising: an imaging device that acquires at least one of the following: vein density, leaf color, vein color, leaf shape, leaf size, phyllotaxy, and leaf attachment angle based on the results of image analysis of the image of the plant captured by an imaging device.

5. A growth state estimating device according to any one of claims 1 to 4, an environmental control unit that controls an environmental control facility that controls an environment in a plant factory where the plants are grown, according to a predetermined condition corresponding to a result of the estimation of the growth state of the plants by the estimation unit; A plant management system comprising:

6. the predetermined condition indicates a relationship between the growth state of the plant and at least one of the water content, the electrical conductivity, the hydrogen ion exponent, the temperature around the plant, the humidity, the amount of light irradiated to the plant, and the carbon dioxide concentration of the medium; 6. The plant management system according to claim 5, wherein the environmental control unit adjusts at least one of the water content, electrical conductivity, hydrogen ion exponent, temperature around the plant, humidity, the amount of light irradiated to the plant, and carbon dioxide concentration of the culture medium by controlling the environmental control equipment according to the predetermined conditions.

7. The plurality of indices include at least two of a leaf hardness, a leaf thickness, a vein density, a stem thickness, a leaf color, a vein color, a leaf shape, a leaf size, a phyllotaxis, and a leaf attachment angle; The acquisition unit is The hardness of the leaves is obtained based on the measurement results using a hardness meter. Obtain the leaf thickness based on the measurement results using the thickness measuring device; Obtaining the thickness of the stem based on the measurement result by a thickness measuring device or the result of image analysis of the image of the plant captured by an imaging device, or acquiring at least one of a density of veins, a leaf color, a color of veins, a leaf shape, a leaf size, a phyllotaxis, and a leaf attachment angle based on a result of an image analysis of the image of the plant; The plant management system comprises:

6. The plant management system according to claim 5, further comprising a mobile body control unit that moves a mobile body including an arm that holds at least one of the hardness meter, the thickness measuring device, and the imaging device within the plant factory and causes at least one of the hardness meter, the thickness measuring device, and the imaging device to perform measurements related to the multiple indicators of the plant.

8. the environmental control facility includes a nutrient solution supply facility for supplying a nutrient solution containing a fertilizer component to the plant; 6. The plant management system according to claim 5, wherein the environmental control unit adjusts a fertilizer concentration of the nutrient solution supplied to the plant by the nutrient solution supply equipment so that the growth state of the plant estimated by the estimation unit becomes a predetermined growth state.

9. The environmental control system includes a watering system that supplies water to a medium in which the plant is grown; The plant management system according to claim 5 , wherein the environmental control unit adjusts the amount of water irrigated to the culture medium by the irrigation equipment so that the growth state of the plant estimated by the estimation unit becomes a predetermined growth state.

10. The environmental control facility includes a light source facility having a light source that irradiates the plant with artificial light, 6. The plant management system according to claim 5, wherein the environmental control unit adjusts the amount of light and the irradiation time irradiated to the plant by the light source equipment so that the growth state of the plant estimated by the estimation unit becomes a predetermined growth state.

11. An acquisition unit acquires a plurality of indices related to leaf expansion of a plant; an estimation unit estimating a growth state of the plant based on relationship information indicating a relationship between a plurality of indexes related to leaf expansion of the plant and a growth state of the plant and the plurality of indexes acquired by the acquisition unit; A growth state estimation method comprising the steps of:

12. An acquisition unit that acquires a plurality of indices related to the leaf expansion of a plant; an estimation unit that estimates a growth state of the plant based on relationship information indicating a relationship between a plurality of indexes related to leaf expansion of the plant and a growth state of the plant and the plurality of indexes acquired by the acquisition unit; A program that allows a computer to function.

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