157 results about "Growth curve" patented technology

The invention provides a seedling cultivation growth condition monitoring method, which comprises the steps of performing data processing on a time series data set of hydrological conditions, obtaining a dynamic association rule among different hydrological parameters, constructing an association model of the hydrological parameters, and quantitatively describing mutual influence and restriction relationships among water temperature, dissolved oxygen and salinity parameters by the association model; performing data processing on the time sequence data set of seedling growth, establishing a seedling growth process model, determining key parameters of a seedling growth curve by analyzing growth rate change rules of seedlings in different growth stages, and correcting the model according to initial quality and stocking density factors of the seedlings; a seedling growth prediction model is combined with an intelligent optimization algorithm, key control parameters in the breeding process are dynamically adjusted, and according to the seedling growth trend predicted by the model, hydrological conditions and feeding strategies are adaptively optimized, so that intelligent management of the breeding process is realized.

The invention provides a plant management and control method and device based on bubble mud, and relates to the technical field of plant management and control technologies. Based on the plant variety information, matching the type, the proportion and the replacement period of the bubble mud; monitoring the actual growth state of the plant, and calculating deviation data of an actual growth curve and a standard growth curve; if the deviation data exceeds a preset threshold value, generating a bubble mud regulation and control scheme; adjusting or replacing the bubble mud, and guiding a user to carry out environment coordinated regulation and control; and collecting the operated plant state, evaluating the control effect, and dynamically adjusting the subsequent control strategy to make the plant growth state close to the standard growth curve. The plant management and control method and device based on the bubble mud have the advantages that bubble mud configuration is matched with plant requirements, bubble mud selection is more targeted, fertilizer loss and environmental pollution are reduced, bubble mud replacement and adjustment opportunity judgment is more accurate, and plant management and control are more effective.

The invention discloses a cauliflower phenotype analysis and prediction method based on a field high-throughput phenotype system. According to the method, on the basis of RGB images and hyperspectral images of field cauliflower, through a cauliflower segmentation model, cauliflower, flower ball and leaf areas are automatically extracted, phenotype data and chlorophyll content are extracted, data of different growth periods are sorted according to a time sequence, a growth curve is drawn, and a regression model is constructed, so that the growth states of the cauliflower in different stages are predicted. Compared with the prior art, an effective non-contact scheme is provided for cauliflower phenotype analysis, phenotype parameters of cauliflower can be obtained without manual field on-site measurement, and corresponding culture measurement is combined, so that the cauliflower culture efficiency can be effectively improved, the culture cost can be reduced, and double friendliness of human resources and biological safety is realized.

The invention relates to the technical field of power system operation and control, and particularly discloses a time-sharing electric quantity prediction method based on a logarithmic load density growth curve, which comprises the following steps of: firstly, performing causal detection and dynamic time-delay optimization on historical load and multivariate external data through convergence cross mapping and mutual information technologies, and constructing a causal time-delay feature set; and the problems of multi-element coupling and time-delay effect quantization are solved. Secondly, fitting a load trend by using time-frequency decomposition in cooperation with a segmented logistic model, extracting dynamic parameters representing a growth rate and a saturation capacity, and endowing the model with a sensing ability for a load evolution stage; then, causal features, growth parameters and load components are deeply fused through cross-domain modulation and a gating mechanism, the nonlinear modulation effect of an external environment on a load mode is explicitly modeled, and finally, a probability interval is generated in combination with quantile regression and residual error correction. According to the scheme, accurate and probabilistic prediction of the time-sharing electric quantity in a complex scene is realized, and the scientificity of an agent electricity purchase decision is improved.

The invention discloses a digital children growth and development predictive guidance method, particularly relates to the field of children growth and development evaluation, solves the problems of individual growth trajectory matching and specificity recognition, and comprises the following steps: segmenting a normal growth curve into local reference windows and constructing a long-term standard curve; generating a target growth curve in combination with a dynamic time warping method, and capturing the growth characteristic difference between short-term fluctuation and global trend of a target individual; by extracting a relative curvature unbalance factor and a cross-section extension entropy difference value, dynamic deviation of a target growth curve in local and global ranges is quantitatively described; performing time domain division dynamic evaluation by using a short-term mutation deviation index and a long-term gradual deviation index, generating an explanation credibility coefficient of a normal target growth trajectory, dividing individual growth characteristic grades, and determining an explanation capability range of a normal growth curve to the target trajectory, thereby being beneficial to distinguishing the matching degree of a target and a normal growth mode, and improving the target growth accuracy. And the growth specificity is recognized.

The invention relates to a multi-dimensional space long-span bridge track vertical deviation temperature-sensitive component extraction method. The method comprises the steps of integrating long-span bridge track vertical deviation three-dimensional historical data added with an environment temperature label; adopting empirical wavelet transform to construct an MRA component four-dimensional data set containing a temperature label and a wavelength label; after mileage dimension resampling, projecting data to an amplitude-wavelength space, drawing an accumulated amplitude growth curve, judging the type of the amplitude-wavelength curve, and determining a boundary wavelength of bridge deformation and track irregularity; projecting the data to an amplitude-temperature space, and judging an amplitude curve and temperature sensitivity; and in combination with the boundary wavelength and the temperature sensitivity, extracting a temperature sensitive component of track irregularity and a construction deviation component in actual bridge deformation. According to the method, synchronous identification and extraction of the temperature sensitive component in the track vertical deviation and the bridge construction deviation component can be realized, and a quantitative basis is provided for accurate maintenance and repair of a long-span railway bridge.

The invention discloses an intelligent henhouse management system and method based on the Internet of Things, and the method comprises the steps: S1, obtaining the individual parameters of each broiler chicken and the environmental parameters of each column, dividing the columns with similar feeding time into one group, and constructing a digital twinborn model; the method comprises the following steps: constructing a database containing abnormal broiler chicken caused by environment and non-environment correlation through abnormal cases in broiler chicken breeding in combination with a machine learning interpolation method; according to the collected data, constructing a normal growth curve prediction model, and outputting an expected normal growth curve of each broiler chicken in the current environment; monitoring broiler growth conditions in real time, comparing actual growth data with an expected normal growth curve, marking an abnormal column, and positioning abnormal individual broilers; according to the image data of the abnormal individual broiler chicken, the digital twinborn model and the abnormal database are combined, abnormal reasons are analyzed, abnormal types are judged, and a targeted solution is pushed. According to the method, the accuracy of anomaly detection is improved, and full-closed-loop management of dynamic sensing, accurate diagnosis and self-adaptive regulation and control is also realized.

The invention discloses a meat duck growth curve control method based on image recognition. The meat duck growth curve control method is applied to growth monitoring of meat ducks within 49 days after incubation. The method comprises the following steps: firstly, constructing a standard growth database comprising a standard body weight sequence, an image sequence and a feeding parameter sequence; a meat duck growth image is collected, multi-scale features are extracted, and feature vectors including morphological features, textural features and attitude features are constructed; establishing a deep neural network mapping model between the feature vector and the body weight; calculating growth deviation based on the predicted weight and dynamically adjusting feeding parameters; according to the invention, accurate monitoring and scientific management of the growth state of the meat ducks are realized through non-contact measurement and intelligent analysis, and the breeding efficiency and economic benefits are improved.

The invention relates to a mulberry growth monitoring system and method based on image processing, and the method comprises the steps: obtaining the data of each growth stage of a mulberry, constructing a mulberry data sample, marking, and inputting a mulberry growth analysis model for training; acquiring real-time images of the mulberries, transmitting the images to a mulberry growth analysis model, and outputting growth analysis results of the mulberries; the optimal growth curve, the environmental parameters and the fertilization data are matched, the environmental parameters are controlled, and a fertilization control module controls the fertilization time, the fertilization type and the fertilization amount; an image is collected at a specified time point and transmitted to a mulberry growth analysis model for analysis, an actual growth curve of the mulberry is drawn, and environmental parameters, fertilization time and fertilization amount are adjusted according to specified rules; and mulberry leaf picking is carried out based on the acquired corresponding mulberry leaf maturity data at a specified time point. The mulberry growth monitoring and mulberry leaf maturity acquisition are realized, a data basis is provided for environmental parameters and fertilization control, and mulberry leaves with corresponding maturity are picked for silkworm feeding at corresponding ages.

The invention discloses a forest carbon reserve prediction method coupling a Logistic growth curve and meteorological data. The method comprises the following steps: 1) constructing a relation of a forest dynamic Logistic growth curve; 2) fitting a theoretical carbon reserve value based on a Logistic growth curve; 3) a growth period monthly meteorological data calculation model; 4) constructing an actual carbon reserve prediction model coupling the meteorological data and the theoretical carbon reserve; and 5) predicting the future forest carbon reserve by using the multi-scene meteorological data. According to the method, the influence of long-time-span monthly-scale meteorological data on forest carbon reserve value prediction is considered, the forest carbon reserve prediction method coupling the Logistic growth curve and the meteorological data is constructed for forest carbon reserve prediction, and a brand new method is provided for accurate carbon reserve prediction.

The invention provides a resource information determination method and device, equipment and a storage medium, relates to the field of human resources, and is used for determining reserve resource information of a main body object of an institution and providing reliable data support for the institution to formulate long-term and accurate resource planning. The specific scheme is as follows; the method comprises the following steps: quantifying historical business processing data of a subject object to obtain an efficiency index, and fitting based on the quantified efficiency index to obtain a first growth rate of efficiency index growth of the subject object; a target senescence factor coefficient is introduced to correct the first growth rate to obtain a second growth rate which reflects the law of efficiency growth slowing of the subject object after the target time window; combining the first growth rate, the second growth rate and the target time window to generate an efficiency growth curve, and representing the change of the efficiency of the main object along with time; and finally, determining resource information of the mechanism in the target time window based on the efficiency growth curve of each main body object.

A method for generating a standard growth curve for chicken flock breeding comprises the following specific steps that a, the same kind of chicken flock is divided into N groups to be bred, and it is guaranteed that all chickens in each group of chicken flock are born on the same day; b, recording the daily average weight of each group of chicken flocks; c, taking the daily average weight of all groups of chicken flocks as a training set, learning in a learning model, averaging, and finally generating a daily age average weight standard growth curve of the same type of chicken flocks by means of a Gompertz fitting model; and d, changing any condition of variety, gender, region, henhouse control mode, climate and breeding mode to form a new type of chicken flocks, and repeating the steps b and c to obtain daily age average weight standard growth curves of different types of chicken flocks. The daily age average weight standard growth curve obtained by the method is more consistent with the actual weight of the chicken flocks, the average weight prediction of the chicken flocks is more scientific and accurate, and meanwhile, the problem of physical health of the chickens caused by a mode of catching the chickens by sampling is avoided.

The invention relates to the technical field of breeding, in particular to a breeding management system based on increasing the DHA content in eggs, and the system comprises a data collection module which is used for periodically collecting a plurality of related parameters of target laying hens and the actual value of the DHA content in the eggs produced by the target laying hens; a database; the model construction module is used for constructing a DHA related model corresponding to each related parameter and fitting a growth curve and a DHA content change curve of the laying hens; the prediction and comparison module is used for predicting the DHA content value of the eggs produced by the target laying hen in each collection period and determining the abnormal value of the DHA content; the model evaluation module is used for evaluating the relationship between each breeding parameter and the DHA content abnormal value and constructing a DHA abnormity related model; and the parameter adjustment module is used for determining a parameter adjustment mode of each related parameter of the target laying hen. According to the method, the scientificity of breeding management for increasing the DHA content in the eggs can be improved.

The invention provides a strength data processing method and system for concrete performance, and relates to the technical field of data processing.The method comprises the steps that hydration heat temperature strain data of a concrete structure of a super high-rise building foundation is obtained to generate a temperature strain data set with spatial distribution characteristics, and the strength data of the concrete performance is obtained by combining material characteristic parameters of the concrete structure; constructing a concrete three-dimensional entity by using the pre-constructed digital twin model so as to simulate a temperature gradient field, a thermal stress field and a time-space evolution rule of strength development of a concrete structure; based on the space-time evolution rule and different maintenance condition parameters, predicting a strength increase curve of the concrete structure under different maintenance conditions; according to the strength increasing curve, the strength standard probability and the risk threshold value of different curing stages are calculated, strength development simulation and risk early warning of the concrete structure are carried out based on the strength standard probability and the risk threshold value, and the intelligent monitoring and early cracking risk early warning capacity of the concrete strength development process is improved.

The invention relates to application of dronedarone hydrochloride in preparation of a polymyxin synergist. A checkerboard method-minimum inhibitory concentration test, a growth curve test and a sterilization curve test prove that dronedarone hydrochloride and colistin have a good in-vitro synergistic antibacterial effect; an isothermal titration calorimetry test confirms that dronedarone hydrochloride can play a synergistic antibacterial role by combining cardiolipin and phosphatidyl glycerol. Meanwhile, a mouse ExPEC drug-resistant strain abdominal cavity infection model shows that the dronedarone hydrochloride can remarkably enhance the in-vivo treatment effect of the colistin. Compared with drug research and development of unknown active compounds, the dronedarone hydrochloride as a marketed drug can effectively accelerate the research and development process of new drugs and reduce the risk of drug research and development failure, which is of great significance in prolonging the antibacterial activity of existing antibiotics and solving the problem of bacterial drug resistance.

This invention relates to the field of mechanical property monitoring technology for mine backfill bodies, specifically to a system and method for acquiring and analyzing tensile strength data of mine backfill bodies. The system comprises a data acquisition unit, a physical information coupling unit, a tensile strength inversion unit, and a spatiotemporal evolution mapping unit. This invention acquires the waveguide flight time and energy attenuation coefficient of the backfill body using an embedded guided wave sensor array. It uses the monotonically increasing law of hydration degree as a physical constraint to train the physical information coupling network, outputting a compliant hydration degree time series. Based on a hydration degree-tensile strength mapping relationship library, it inverts and fits to generate a strength growth curve, which is then loaded into a four-dimensional digital twin model to invert the internal tensile strength gradient field. It automatically identifies local abnormal regions where the growth rate is below the safety threshold, improving the physical rationality and accuracy of the inversion results, and realizing visualization of the spatiotemporal evolution of backfill body strength and early safety warning.

This invention relates to the field of ecological environment management technology, specifically disclosing a refined method and system for visualizing regional vegetation carbon sequestration. The method includes: extracting land use types of a target area based on remote sensing data of land use types and biomass; determining forest areas based on land use types and establishing growth curves for the forest areas based on preset fitting curves; calculating the carbon sequestration amount of the forest areas based on the growth curves and determining the carbon sequestration ratio of different forest areas; allocating the total carbon sequestration amount to different sub-regions of the target area based on the carbon sequestration ratios, and visually converting the allocated target areas. This invention first selects a target area, calculates the carbon sequestration amount based on the forest areas within the target area, then redistributes the carbon sequestration to different areas according to land use types, and visualizes the redistribution results, facilitating the management of the area.

The invention discloses an individual height prediction method and device, electronic equipment and a storage medium, and relates to the technical field of height prediction, and the method comprises the steps: S1, obtaining the growth time interval of an individual, determining a genetic prediction height value in each growth time point, drawing a first height curve which is the trend of age-genetic height, and determining the growth time interval of the individual; determining a basic growth coefficient corresponding to the first height curve; s2, the actually measured height value of the individual in each growth time interval is determined, a second height curve is determined, the second height curve is the age-height trend, and a first feedback coefficient corresponding to the second height curve is determined; s3, acquiring a weight-height trend set in the database as a third height curve, and determining a growth disturbance coefficient of the individual at each time point according to the weight-height trend; s4, comparing the obtained first growth curve, the second growth curve and the third growth curve, and determining an actual prediction value of individual growth; and the height prediction accuracy is improved.

This invention provides a method, apparatus, equipment, and medium for constructing an oil and gas field production growth curve model, belonging to the field of oil and gas field production evolution technology. The method collects multiple sets of geological reserves, first and second rate coefficients, and cumulative production data for oil and gas fields. Then, it applies the oil and gas field growth differential equation and obtains a growth model for cumulative production through mathematical solution. After the model is converted to a first-order linear form, iterative calculations are used to find at least two sets of data to ensure a linear relationship between the independent and dependent variables. These data are used to determine the slope and intercept of the linear equation, thereby estimating the final recoverable reserves and model constants of the oil and gas field. Finally, combining the rate coefficients and estimated parameters, a growth curve model for predicting the cumulative production of the oil and gas field is constructed. This invention improves the accuracy of oil production prediction by constructing an accurate oil and gas field production growth curve model.

The present invention relates to the field of bacteriophages, and in particular to bacteriophages and bactericidal compositions and applications. The present invention provides a bacteriophage, and the phage has a preservation number of CGMCC45383. The best infection multiplicity MOI of the bacteriophage provided by the present invention is 0.001, and the one-step growth curve shows that the incubation period of SRB7757 is 4 hours, the lysis period is 32 hours, and the maximum burst volume is about 100 PFU / cell; it is active in the pH range of 2 to 12, and is still active after being treated at 70°C for 60 minutes; it can significantly reduce the inhibition of metal corrosion caused by SRB; and it is insensitive to chloroform.

The invention relates to the technical field of agricultural engineering, and discloses a grain machinery operation area accurate extraction method based on visual remote sensing and AI, and the method comprises the following steps: constructing a multi-source spatio-temporal data set of land parcel level alignment; reconstructing a normalized vegetation index time sequence for each plot by adopting an interpolation method and a filtering method, and generating a plot scale crop growth curve; generating a hourly improved vegetation index image through calculation, and extracting texture features in combination with a crop growth curve; constructing a change atlas based on the normalized vegetation index time sequence; inputting the remote sensing image and the crop growth curve into a semantic segmentation model; performing fusion classification on the texture features and the change atlas by using a random forest algorithm; and converting the probability graph and a binary mask result into a vector boundary, and completing precision verification by calculating an intersection-to-union ratio. Accurate data support is provided for agricultural production monitoring, agricultural machinery scheduling and the like.

The invention discloses an idiopathic knee joint deformity correction method based on combination of growth curve prediction and absorbable material time gradient regulation and control, and is applied to the technical field of biomedical materials. Comprising the following steps: acquiring lower limb bone length data of a normal child, and drawing a growth curve; constructing and fitting a lower limb bone length model by using the growth curve data, and constructing a mathematical model for correcting idiopathic knee varus and valgus; constructing a prediction model to calculate the time of implanting the child patient with idiopathic genu varum into the steel plate for fixation during the semi-epiphyseal fixation; the absorbable zinc-magnesium alloy internal fixation nail plate with different in-vivo absorption time gradients is developed; the zinc-magnesium alloy internal fixation nail plate with the corresponding absorption time is selected for correction according to the time required by different child patients to be implanted into the steel plate for fixation. After a child patient receives a semi-epiphyseal block operation to achieve the correction effect, the internal fixation steel plate can be automatically absorbed and broken, the operation of taking out internal fixation again is omitted, the operation risk and pain are reduced, and the treatment cost is reduced.

The invention provides a culture method and preparation of bifidobacterium longum subsp.infantis B8762 based on carbon source regulation and control, and belongs to the technical field of biology. The method comprises the following steps: inoculating an activated strain into a carbon-source-free improved MRS culture medium, adding a specific carbon source, monitoring a growth curve in real time through an on-line living cell sensor, and analyzing and regulating the growth stage and activity of thalli in combination with metabolites. By precisely regulating and controlling a substrate, the cell activity is remarkably improved, the proportion of living cells is increased, the sugar uptake ability and the key metabolic enzyme activity are enhanced, a growth curve is optimized, and the cell yield coefficient and the substrate conversion efficiency are improved. A bacteriostatic preparation, a viable bacterium preparation and a metabolite preparation can be prepared and respectively have specific metabolite concentration, living cell proportion and enzyme activity. The culture method and preparation of the bifidobacterium longum subsp.infantis B8762 based on carbon source regulation and control are simple to operate and easy to industrialize, the production cost can be reduced, the production efficiency can be improved, and the requirements of different application scenes can be met.

This invention belongs to the field of granulation, specifically disclosing an automated water suspension granulation control method based on online particle size monitoring, comprising: Step 1, during the granulation process, using an online particle size analyzer to monitor the particle size in real time and plotting a real-time particle size growth curve over time; Step 2, based on the morphological characteristics such as the slope change points of the real-time particle size growth curve, automatically dividing the granulation process into three characteristic stages; Step 3, for each stage divided in Step 2, establishing a quantitative model between particle size growth and key process parameters; Step 4, based on the model's predictive and feedback control, executing closed-loop control in a new granulation batch. This invention also discloses an automated water suspension granulation control system. This method and system, through real-time feedback and dynamic adjustment, ensure that the granulation process of each batch follows the optimal growth trajectory, significantly reducing product quality differences between batches.

The present application provides a plant control method and device based on bubble clay, relating to the technical field of plant control technology. The key points of its technical solution are as follows: obtaining plant species information; based on the plant species information, matching the type, ratio, and replacement cycle of the bubble clay; monitoring the actual growth state of the plant and calculating the deviation data between the actual growth curve and the standard growth curve; if the deviation data exceeds the preset threshold, generating a bubble clay regulation plan; performing bubble clay adjustment or replacement operations to guide the user to perform environmental collaborative regulation; collecting the plant state after the operation, evaluating the control effect, and dynamically adjusting the subsequent control strategy to make the plant growth state approach the standard growth curve. The plant control method and device based on bubble clay provided by the present application have the advantages of matching the bubble clay configuration with the plant requirements, having more targeted bubble clay selection, reducing fertilizer loss and environmental pollution, more accurate judgment of the timing of bubble clay replacement and adjustment, and more effective plant control.

The invention provides a production proficiency prediction method and device, a storage medium and a program product, and the method comprises the steps: obtaining a prediction request input by a user and historical production data corresponding to a target product, determining a growth curve for producing the target product according to the historical production data, and determining an initial function for representing the form of the growth curve, and on the basis of the initial function, constructing a to-be-fitted function including the offset, fitting the to-be-fitted function according to the historical production data to obtain a target function, and determining and outputting the production proficiency corresponding to the prediction request according to the target function and the target time. According to the method, the defects of low accuracy and strong dependence on manpower caused by an average proficiency degree and manual deviation correction mode can be avoided, the prediction automation is realized, and the prediction accuracy is improved. And the disadvantage of incomplete coverage of the historical production data caused by adopting an AI prediction model can be avoided, and full coverage of the historical production data is realized, so that the prediction accuracy is improved.

The embodiment of the invention discloses a sample analysis system and a control method thereof, and the sample analysis system comprises a blood culture module, a display module and a control module. The blood culture module comprises an incubation assembly and a detection assembly, the incubation assembly is used for loading at least one sample and incubating the sample, and the detection assembly is used for detecting microorganism growth parameters of the sample in the incubation assembly to obtain corresponding detection data; the control module is used for acquiring target detection data of the target sample, generating a growth curve of the target sample according to the target detection data, and displaying the growth curve of the target sample in the first display area through the display module; the growth curve of the target sample comprises a historical growth curve before the target sample is reloaded and an extended growth curve after the target sample is reloaded, and the historical growth curve and the extended growth curve are displayed in different styles. On the basis, the sample analysis system provided by the embodiment of the invention can improve the interaction experience of the user after the sample is reloaded.

The present invention relates to the use of online biomass capacitance monitoring in cultures as a way to control the growth of cells through the use of a temperature control loop. In certain embodiments, a biomass capacitance probe is used to measure the cell density, and a predetermined growth curve is used to adjust the temperature in the culture.

The invention belongs to the field of oil exploitation, and particularly relates to a development index calculation method for calculating a patching release storage reserve well. Comprising the steps of 1, obtaining well historical dynamic data, and determining a production system; 2, arranging and processing the data into a data table available for calculation; 3, calculating the cumulative oil production by applying logistic and utilizing a growth curve method and a formula # imgabs0 #; and 4, water content prediction is carried out according to a formula fw = e (d.t + g). In order to enable the water flooding well pattern and the polymer flooding well pattern to be reasonably matched better, oil production and water content prediction after deblocking is carried out by adopting a growth curve and exponential function prediction water content joint solution, the prediction precision reaches 95% or above, and technical support can be provided for sealing reserve deblocking and water flooding well pattern comprehensive utilization in the future.

A measurement method and system for nutrient solution components of a hydroponic plant, which method and system relate to the technical field of plant nutrition management and hydroponic cultivation. The measurement method comprises: setting growth node time periods for a plant, performing, multiple times at set time points, nutrient component measurement on a nutrient solution where the plant is located, and recording water consumption amounts; using a neural network to establish a detection model by means of the acquired water consumption amounts and data of a nutrient component growth curve, training the detection model, and storing the optimal model; and measuring nutrient components at different time points in real time, and when the difference between an actual measured value and a predicted value of the optimal model is greater than a set error threshold value, triggering a replenishment and adjustment mechanism to ensure that components of the nutrient solution are always maintained within the optimal range. Thus, the growth speed and quality of plants are improved, the frequency and difficulty of manual intervention are reduced, measurement is accurately performed on the basis of a corresponding plant growth period, and a nutrient solution ratio is adjusted on the basis of a measurement result, so as to meet the growth requirements of the plants.