An intelligent fertilization control system for mushroom cultivation based on the Internet of Things

Abstract

The invention relates to the technical field of agricultural machinery control, and in particular to an intelligent fertilization control system for mushroom cultivation based on the Internet of Things, comprising: a data acquisition module, used for collecting environmental data and culture medium data during mushroom cultivation, and transmitting the corresponding data to a data processing module; the data processing module, used for processing the environmental data and culture medium data, and determining the current growth state of the mushrooms; the data processing module comprises an environmental analysis unit, a culture medium analysis unit and a mushroom growth analysis unit; the environmental analysis unit, used for evaluating the environmental data of the mushrooms, determining whether the current temperature, humidity and ventilation conditions can meet the growth requirements of the mushrooms, and obtaining an environmental analysis coefficient; the precise, intelligent and adaptive fertilization is achieved, and the economic and ecological benefits of mushroom cultivation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural machinery control, and in particular to an intelligent fertilization control system for mushroom cultivation based on the Internet of Things. Background Art

[0002] At present, the empirical fertilization method is mostly used for mushroom fertilization, that is, the staff conducts artificial fertilization based on the fertilization experience gained from previous artificial fertilization. However, due to the different culture media used, and the nutrients, absorption conditions and natural conditions received at different locations are often different, the empirical fertilization method may cause inaccurate fertilization. In addition, the data collection for mushroom cultivation is mostly manual soil testing formula and the growth data of the previous crop, in order to reasonably adjust the proportion of fertilizer elements.

[0003] For example, Chinese patent publication number CN116520747A discloses a variable fertilization control system and method, in which the system includes: a module for obtaining a position to be fertilized, used to obtain the position to be fertilized of a fertilizer application vehicle in a field; a module for determining a basis for formulating a variable fertilization plan, used to determine a basis for formulating a variable fertilization plan based on the position to be fertilized and a preset fertilizer marking map; a variable fertilization plan formulating module, used to formulate a variable fertilization plan based on the basis for formulating a variable fertilization plan and a preset variable fertilization plan formulating experience library; a variable fertilization control module, used to control the fertilizer application vehicle to perform variable fertilization at the position to be fertilized based on the variable fertilization plan.

[0004] However, the prior art tends to control the fertilization position and the corresponding wind direction when fertilizing, resulting in the inability to timely identify the relevant conditions of the culture medium used for mushroom cultivation when controlling the cultivation of mushrooms, etc., resulting in the inability to timely supplement nutrients during mushroom cultivation and improve the secondary utilization of the mushroom cultivation culture medium. Summary of the invention

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: an intelligent fertilization control system for mushroom cultivation based on the Internet of Things, including: a data acquisition module, used to collect environmental data and culture medium data during mushroom cultivation, and transmit the corresponding data to a data processing module.

[0006] The data processing module is used to process the environmental data and culture medium data to determine the current growth status of the mushrooms.

[0007] The data processing module includes an environment analysis unit, a culture medium analysis unit and a mushroom growth analysis unit.

[0008] The environmental analysis unit is used to evaluate the environmental data of the mushrooms, determine whether the current temperature, humidity, and ventilation conditions meet the growth requirements of the mushrooms, and obtain the environmental analysis coefficient.

[0009] The culture medium analysis unit is used to analyze the culture medium data, determine the delivery path of nutrients during mushroom growth, and the component stability coefficient corresponding to the pH value and conductivity.

[0010] The mushroom growth analysis unit is used to observe the growth rate of mushrooms, determine whether the shape, color and size of mushroom fruiting bodies conform to the normal growth state, and obtain the conformity coefficient of the mushroom growth state.

[0011] The fertilization decision module is used to receive the output results of the data processing module and determine the fertilization plan currently used for the mushrooms according to the growth status of the mushrooms.

[0012] The fertilization evaluation module is used to evaluate the growth status of the mushrooms after fertilization and determine the fertilization effect produced by the fertilization plan.

[0013] The beneficial effects of the present invention are as follows: the present invention collects and processes data in real time through the Internet of Things technology, making fertilization decisions more accurate and reducing the situation of excessive or insufficient fertilization; by setting an intelligent fertilization plan, it can better meet the growth needs of mushrooms and improve the growth rate and quality of mushrooms; by real-time evaluation of fertilization effects and adjustment of fertilization plans, unnecessary waste of resources is avoided and production costs are reduced; the fertilization plan can be automatically adjusted according to different environmental conditions and mushroom growth states, thereby enhancing the adaptability and flexibility of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0015] Figure 1 The system framework diagram of an intelligent fertilization control system for mushroom cultivation based on the Internet of Things.

[0016] Figure 2 The present invention is a system framework diagram of a data processing module of an intelligent fertilization control system for mushroom cultivation based on the Internet of Things.

[0017] Figure 3 The present invention is a system flow chart of an intelligent fertilization control system for mushroom cultivation based on the Internet of Things. DETAILED DESCRIPTION

[0018] The embodiments of the present invention are described in detail below. The embodiments described below are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. If no specific techniques or conditions are specified in the embodiments, the techniques or conditions described in the literature in the art or the product specifications are used.

[0019] See also Figure 1 , Figure 2 , Figure 3, an intelligent fertilization control system for mushroom cultivation based on the Internet of Things, including: a data acquisition module, a data processing module, a fertilization decision module and a fertilization evaluation module, the data processing module includes an environment analysis unit, a culture medium analysis unit and a mushroom growth analysis unit; the data acquisition module transmits the real-time collected environment and culture medium data to the data processing module; the data processing module processes the data through its three analysis units, and outputs the processing results to the fertilization decision module; the fertilization decision module formulates a fertilization plan according to the processing results and guides the fertilization operation; the fertilization evaluation module evaluates the effect after fertilization and adjusts the fertilization plan according to the evaluation results.

[0020] The data acquisition module is used to collect environmental data and culture medium data during mushroom cultivation, and transmit the corresponding data to the data processing module.

[0021] The data processing module is used to process the environmental data and culture medium data to determine the current growth status of the mushrooms.

[0022] The data processing module includes an environment analysis unit, a culture medium analysis unit and a mushroom growth analysis unit.

[0023] The environmental analysis unit is used to evaluate the environmental data of the mushrooms, determine whether the current temperature, humidity, and ventilation conditions meet the growth requirements of the mushrooms, and obtain the environmental analysis coefficient.

[0024] The culture medium analysis unit is used to analyze the culture medium data, determine the delivery path of nutrients during mushroom growth, and the component stability coefficient corresponding to the pH value and conductivity.

[0025] The mushroom growth analysis unit is used to observe the growth rate of mushrooms, determine whether the shape, color and size of mushroom fruiting bodies conform to the normal growth state, and obtain the conformity coefficient of the mushroom growth state.

[0026] The fertilization decision module is used to receive the output results of the data processing module and determine the fertilization plan currently used for the mushrooms according to the growth status of the mushrooms.

[0027] The fertilization evaluation module is used to evaluate the growth status of the mushrooms after fertilization and determine the fertilization effect produced by the fertilization plan.

[0028] The collected environmental data include the temperature, humidity and ventilation conditions corresponding to the growth of mushrooms; the collected culture medium data include the pH value, conductivity and nutrients in the culture medium, such as the nutrients brought by wheat bran, rice bran, bean cake powder, gypsum, lime and potassium dihydrogen phosphate placed in the culture medium. The purpose of analyzing the nutrients at this time is to determine the amount of components consumed in the current nutrient base and whether the corresponding components in the current nutrient base need to be supplemented by fertilization.

[0029] pH value: Analyze whether the pH value of the culture medium is within the appropriate range. Changes in pH value will affect the absorption of nutrients by mushrooms.

[0030] Conductivity: The nutrient salt concentration in the culture medium can be monitored by conductivity to understand the salt content of the culture medium.

[0031] Nutrient content: Analyze whether the nutrients in the culture medium are sufficient, such as the content of nitrogen, phosphorus, potassium and other elements.

[0032] Wheat bran: provides carbon and nitrogen sources; Rice bran: rich in protein and other trace elements; Soybean cake powder: provides high-quality protein and amino acids; Gypsum: provides calcium ions, which helps the growth of mycelium; Lime: adjusts the pH value to maintain appropriate pH; Potassium dihydrogen phosphate: provides phosphorus and potassium elements to promote the growth of mycelium.

[0033] In order to determine the changes in relevant culture medium data and environmental data, temperature and humidity are collected using temperature and humidity sensors every 15 minutes, and ventilation conditions are collected every half hour to determine the current temperature and humidity, and whether the concentration of carbon dioxide has decreased, to determine whether the ventilation is operating normally; pH ​​value and conductivity are collected once a day, and nutrients are collected once a week to determine the relevant changes in the current mushroom cultivation.

[0034] The growth status of mushrooms can be monitored by video surveillance to determine their growth after planting and to identify mushrooms with abnormal growth, so that the fertilization of mushrooms can be adjusted in time to reduce the risks in mushroom planting.

[0035] In one embodiment of the present invention, the method for obtaining the environmental analysis coefficient is to first compare the currently identified temperature, humidity, and ventilation conditions with preset data, and determine the correlation coefficients of temperature, humidity, and ventilation conditions in turn; and use the weighted average of the correlation coefficients of temperature, humidity, and ventilation conditions as the output environmental analysis coefficient.

[0036] For the temperature correlation coefficient, the current temperature is compared with the temperature corresponding to different time periods when the mushrooms grow to determine the current temperature correlation coefficient. For example, using the Pearson correlation coefficient, the data of the two temperatures at this time are input to calculate the temperature correlation coefficient.

[0037] The calculation method of the correlation coefficient of humidity is the same as that of temperature. At this time, the current humidity is compared with the humidity corresponding to different time periods when the mushrooms grow to obtain the correlation coefficient of humidity.

[0038] The correlation coefficient of the ventilation condition is obtained by calculating the correlation coefficient between the current ventilation times and the preset ventilation times, and the calculation method is also to use the Pearson correlation coefficient.

[0039] At this time, the correlation coefficients of the three are weighted according to the current growth stage of the mushrooms, and the environmental analysis coefficient is obtained after weighted averaging. The weights set at this time will be adjusted according to the different growth stages. The environmental analysis coefficient calculated at this time will represent the correlation coefficient of the data collected in the current growth stage or the current time period.

[0040] For example, the temperature data at this time is T=[20,22,24,21,23,25,26,27,28,29], and the preset temperature data is P=[21,23,25,22,24,26,27,28,29,30]; it can be found that the two sets of data have certain similarities. At this time, the Pearson correlation coefficient is used for calculation to obtain the correlation coefficient of the data, and the influence of temperature is quantified by the product of the correlation coefficient and the weight.

[0041] For example, the Pearson correlation coefficient can be ;in represents the current temperature at the jth time point, represents the preset temperature at the jth time point, Indicates the average value of the current temperature. Indicates the average value of the preset temperature. represents the number of time points, ; Then the temperature correlation coefficient can be obtained.

[0042] The calculation method for the humidity and ventilation conditions at this time is to replace the recognized humidity with the preset humidity, the current ventilation times with the preset ventilation times and the values ​​corresponding to the temperature in the above calculation method. The calculation formula for the humidity and ventilation conditions is not specifically written here.

[0043] Then, for example, the humidity data at this time is H=[60,62,65,63,64,66,68,70,72,75], and the preset humidity data is Q=[61,63,66,64,65,67,69,71,73,76]; the ventilation times V=[3,4,5,4,3,5,6,7,8,9], and the preset ventilation times W=[2,4,5,3,4,5,6,7,8,10]; based on the above data, the corresponding environmental analysis coefficient can be directly calculated. It should be noted that the data selected at this time is a possible situation in normal measurement. There are many types of data actually measured, and the current implementation method needs to be adjusted according to different situations.

[0044] The weights can be set according to the following conditions; Growth stage 1: spore germination; Temperature: 0.3, Humidity: 0.5, Ventilation: 0.2; In this stage, humidity has the greatest impact on spore germination and is therefore given the highest weight.

[0045] Growth stage two: mycelium growth; temperature: 0.4, humidity: 0.3, ventilation: 0.3; During the mycelium growth stage, the influence of temperature becomes more important, while the weights of humidity and ventilation are relatively balanced.

[0046] Growth stage three: fruiting body formation; temperature: 0.3, humidity: 0.3, ventilation: 0.4; During the fruiting body formation stage, ventilation becomes the most critical factor and is therefore given the highest weight.

[0047] The nutrients used generally include carbon source, nitrogen source, phosphorus source, potassium source, calcium source, magnesium source, trace elements and vitamins, etc.; among them: the main source of carbon source: organic matter, such as glucose, sucrose, starch, etc., is the basis for the growth of mycelium and fruiting body.

[0048] The main sources of nitrogen are: protein, amino acids, urea, nitrates, ammonium salts, etc., which are used to synthesize proteins, nucleic acids and other nitrogen-containing compounds and promote the growth of mycelium.

[0049] The main sources of phosphorus: phosphates, such as potassium dihydrogen phosphate and dipotassium hydrogen phosphate, are involved in energy transfer (ATP) and DNA / RNA synthesis and are very important for cell metabolism.

[0050] The main sources of potassium are: potassium salts, such as potassium chloride and potassium sulfate, which regulate the osmotic pressure within cells, maintain the function of cell membranes, and promote the absorption and transport of nutrients.

[0051] The main sources of calcium are: calcium salts, such as calcium carbonate and calcium sulfate, which constitute part of the cell wall and are used to maintain the stability of the cell structure.

[0052] Main sources of magnesium: Magnesium salts, such as magnesium sulfate, are involved in the synthesis of chlorophyll and are activators of many enzymes.

[0053] The main sources of trace elements are: iron, manganese, copper, zinc, molybdenum, boron, etc., which act as cofactors or activators of enzymes and participate in various metabolic processes.

[0054] The main sources of vitamins: B vitamins (such as vitamin B1, B2, B3, B6, B12), vitamin C, etc., which act as coenzymes or cofactors and participate in various metabolic reactions.

[0055] Specifically, the culture medium formula can be: carbon source: glucose, 20g / L; nitrogen source: peptone, 20g / L; phosphorus source: potassium dihydrogen phosphate, 2g / L; potassium source: potassium sulfate, 1g / L; calcium source: calcium carbonate, 2g / L; magnesium source: magnesium sulfate, 0.5g / L; trace elements: ferrous sulfate, 0.1g / L; manganese sulfate, 0.05g / L; vitamins: vitamin B1, 0.01g / L; pH adjustment: adjust pH to 6.0-7.0. The delivery path and related treatment methods can be set according to the changes in these components.

[0056] Initial stage: During the mycelium growth stage, focus on supplementing carbon and nitrogen sources to promote the rapid growth of mycelium.

[0057] Middle stage: During the mycelium maturity stage, gradually reduce the nitrogen source and increase phosphorus, potassium and other elements to promote the formation of fruiting bodies.

[0058] Late stage: During the fruiting body development stage, appropriate supplementation of trace elements and vitamins should be done to improve yield and quality.

[0059] By adjusting the composition of the current nutrients and detecting the ingredients contained at this time, the corresponding nutrients and the content that needs to be supplemented are identified.

[0060] In one embodiment of the present invention, the implementation method of the nutrient delivery path includes obtaining sampling points when collecting culture medium data, and plotting the identified culture medium into a nutrient change curve according to the values ​​of the corresponding nutrients in the culture medium data based on the positions of the sampling points.

[0061] Traverse all sampling points, determine the value of the corresponding nutrient at each sampling point in turn, and judge the difference between the value of the corresponding nutrient and the preset nutrient, connect the sampling points with the same difference to form a first path, if there are no sampling points with the same difference, connect the sampling points with the smallest difference with the corresponding sampling points to form a second path; judge the sampling points on the first path and the second path in turn; according to the first path and the second path, obtain the delivery path related to the nutrient.

[0062] The first path is used to connect all sampling points with the same nutrient changes to determine whether different nutrients are consumed at different locations during the current mushroom cultivation, and to identify such different situations to adjust the amount and proportion of nutrient solution added to the corresponding culture medium.

[0063] The second path is used to identify the sampling points where the current nutrient composition changes and the normal changes or differences exist, and these special sampling points are analyzed separately to determine the reasons for the different changes in the nutrient composition in the current culture medium.

[0064] At this time, when the sampling points are connected into the first path and the second path, linear interpolation is used to interpolate between the sampling points, so that the currently formed first path and second path are smoother. The moving average method can be used. First, two sampling points on the first path are selected, and a point is inserted between the two sampling points. The value of the inserted point is the average value of the coordinates of the points on both sides. Points are inserted in sequence until the straight line connecting each sampling point becomes a smoother form.

[0065] According to the first path and the second path, the implementation method of obtaining the delivery path related to the nutrient components is as follows: the first paths are combined into a first path map, and the combination form of the first path map is to merge all the first paths to determine how many different nutrient component values ​​exist in the currently implemented mushroom cultivation, and at the same time, it is necessary to determine the characteristics of each first path to select the first path that needs to be processed currently; the curvature corresponding to each sampling point in the first path map is judged, and the sampling point with a curvature greater than a preset curvature value is taken as the target sampling point, the perpendicular median corresponding to the target sampling point is obtained, and the intersection of the perpendicular median corresponding to the target sampling point and the first path map is selected as the first candidate path; according to the obtained first candidate path, the second candidate path related to the second path is obtained.

[0066] At this time, the perpendicular bisector corresponding to the target sampling point is obtained by selecting two target sampling points to connect into a line segment, and selecting the perpendicular bisector of the connected line segment; then the perpendicular bisector is connected with all the intersection points of the first path graph to obtain the first alternative path; after obtaining the first alternative path, the points on the first alternative path are connected one by one, and the perpendicular bisector of the connecting line segment of each point on the first alternative path is obtained, and the perpendicular bisector on the first alternative path is intersected with the second path, and the intersection points on the second path are connected at this time to obtain the second alternative path. If the perpendicular bisector on the first alternative path cannot intersect with the second path, then the points on the second path that are less than the preset distance value from the first alternative path are selected to form the second alternative path; for the calculation of the above curvature, the corresponding angle after each sampling point is connected is determined, that is, the angle formed by three consecutive sampling points is determined. At this time, the angle between the three consecutive sampling points is required to be no greater than the preset angle to prevent the smoothness of the path or avoid excessive turning angles.

[0067] The curvature can be calculated by the following existing method, assuming that the sampling point is , ..., ; Calculate the first-order derivative and second-order derivative of the sampling point at this time to determine the curvature of the corresponding sampling point; establish a coordinate system in the form of east-west, south-north, and north-south geographical locations, with the east-west direction as the horizontal coordinate and the north-south direction as the vertical coordinate to determine the position of each sampling point.

[0068] The first-order derivative corresponding to the abscissa is calculated as follows: ;in, Represents the horizontal coordinate value of the i+1th sampling point, Indicates the horizontal coordinate value of the i-1th sampling point; Indicates the distance between the current sampling point and the adjacent sampling point. This distance is expressed as the average of the distance values ​​between the current sampling point and the two previous and next sampling points. Represents the first-order derivative of the abscissa of the i-th sampling point.

[0069] The calculation method of the first-order derivative corresponding to the ordinate is as follows: ;in, Indicates the ordinate value of the i+1th sampling point, Indicates the ordinate value of the i-1th sampling point; Indicates the distance between the current sampling point and the adjacent sampling point. This distance is expressed as the average of the distance values ​​between the current sampling point and the two previous and next sampling points. Represents the first-order derivative of the ordinate of the i-th sampling point.

[0070] At the same time, the calculation method of the second-order derivative corresponding to the horizontal axis is as follows: ;in, Represents the horizontal coordinate value of the i+1th sampling point, Represents the horizontal coordinate value of the i-1th sampling point, Represents the horizontal coordinate value of the i-th sampling point; Indicates the distance between the current sampling point and the adjacent sampling point. This distance is expressed as the average of the distance values ​​between the current sampling point and the two previous and next sampling points. Represents the second-order derivative of the horizontal coordinate of the i-th sampling point.

[0071] The second-order derivative corresponding to the ordinate is calculated as follows: ;in, Indicates the ordinate value of the i+1th sampling point, Represents the ordinate value of the i-1th sampling point, Represents the ordinate value of the i-th sampling point; Indicates the distance between the current sampling point and the adjacent sampling point. This distance is expressed as the average of the distance values ​​between the current sampling point and the two previous and next sampling points. Represents the second-order derivative of the ordinate of the i-th sampling point.

[0072] At this time, the curvature of each sampling point can be expressed as follows: ;in, Indicates the curvature of the i-th sampling point. At this time, the corresponding i-th point is within the range of the selected sampling point number n, so as to quantify the curvature set for the corresponding sampling point and determine which sampling point is currently identified as the target sampling point.

[0073] The maximum and minimum values ​​of nutrients on the first alternative path and the second alternative path are counted; the maximum and minimum values ​​of nutrients on the first alternative path and the second alternative path are obtained by judging whether the first alternative path and the second alternative path currently pass through the corresponding sampling point, and recording the nutrient value of the sampling point to obtain the maximum and minimum values ​​of the relevant nutrients; the sampling point set at this time usually represents a small area for sampling, so when a path passes through, the value of this area will be assigned to the points of the overlapping part of the path and the small area, so that the corresponding values ​​on the path can be determined; thereby obtaining the maximum and minimum values ​​of nutrients at different points on the path when the nutrients change along the path.

[0074] Delete the points between the maximum and minimum points of the first candidate path and the second candidate path, interpolate the maximum and minimum points according to the preset interpolation interval, and use the interpolated path as the output delivery path.

[0075] The preset interpolation interval set at this time is half of the sampling point setting interval. At the same time, since the first alternative path and the second alternative path are interpolated according to the preset interpolation interval, the two paths are not absolutely related. At this time, it is necessary to interpolate in sequence according to the identified maximum and minimum points and the shortest distance between each point, so as to connect and combine the first alternative path and the second alternative path.

[0076] Suppose that in a mushroom farm, 10 sampling points are set up, and each sampling point measures the content of nitrogen (N), phosphorus (P), potassium (K) and the number of mushrooms.

[0077] After analysis, it was found that the nitrogen content at sampling points 1 to 5 was significantly higher than that at sampling points 6 to 10.

[0078] Phosphorus levels at sampling points 3 and 7 were abnormally low.

[0079] Sampling points 8 and 9 had the highest potassium content and the largest number of mushrooms.

[0080] Although the nitrogen content was high at sampling points 1 and 2, the number of mushrooms was very small.

[0081] Further analysis may reveal that sampling points 1 to 5 may have received more nitrogen fertilizer applications or that the soil in these areas may have naturally higher nitrogen content.

[0082] Sampling points 3 and 7 may have phosphorus absorption barriers, and the soil pH or other factors affecting phosphorus availability need to be checked.

[0083] The high potassium content and mushroom numbers at sampling points 8 and 9 may indicate that the soil fertility and water management in these areas are more suitable for mushroom growth.

[0084] Despite the high nitrogen content, sampling sites 1 and 2 had low mushroom numbers, possibly due to other limiting factors (e.g., insufficient water, insufficient light, or pest and disease problems).

[0085] At this time, it is necessary to adjust the fertilization method of each sampling point and the relevant fertilization path; assuming that the nitrogen content at sampling point 3 is significantly higher than that at other sampling points, and the nitrogen content at sampling point 8 is significantly lower than that at other sampling points, then a delivery path needs to be set at this time to reduce the difference in different nutrients between sampling points 3 and 8, so that the mushrooms at these sampling points can grow evenly, thereby improving the utilization rate of the culture medium and the growth efficiency of the mushrooms.

[0086] In one embodiment of the present invention, when obtaining the component stability coefficient, since the trends of pH value and conductivity at different stages of mushroom growth will present different states, in order to make the currently identified pH value and conductivity within the variation range of normal mushroom growth, it is necessary to verify the relevant data of the identified pH value and conductivity in turn, determine whether they are within the variation range required for normal mushroom growth, and verify whether the corresponding trend conforms to the normal variation; calculate the trend repetition rate between the currently recorded trend and the preset trend as the currently identified component stability coefficient.

[0087] The component stability coefficient is obtained by obtaining the change curves of pH value and conductivity, determining the trend repetition rate of the change curves of pH value and conductivity and a preset trend, and outputting the trend repetition rate as the component stability coefficient.

[0088] The setting method of the trend repetition rate is to judge whether the trend of the current pH value and conductivity is the same as the preset trend, that is, whether the increase or decrease value of the pH value and conductivity is within the normal range in the growth stage of the corresponding mushroom. If it is within the normal range and the trend shown is the same as the preset trend, it is judged as a trend repetition, otherwise it is not a trend repetition. After the sampling point collects multiple data, it is judged in turn whether the data collected at each time conforms to the preset trend, and the number of data that conform to the preset trend is compared with the total number of samples to obtain the corresponding trend repetition rate.

[0089] At the same time, the trend mentioned above is determined by judging whether the corresponding values ​​at adjacent time points show an upward or downward trend. Because in greenhouse or other automated forms of breeding, the corresponding pH value and conductivity of mushrooms will show relatively stable changes during growth. At this time, the value range and trend can be judged to determine whether the current mushroom growth is stable.

[0090] At this time, obtaining the component stability coefficient is achieved by judging whether the change curve of the current pH value and conductivity is the same as the preset curve.

[0091] For example, the pH value curve, the initial stage: in the early stage of mushroom inoculation and cultivation, due to the adaptation process of the strain to the environment and the start of metabolic activities, the pH value may have a short period of fluctuation. The pH value change at this stage may not be obvious, but sometimes it varies depending on the strain and culture medium.

[0092] Logarithmic growth phase: As mushrooms enter the logarithmic growth phase, metabolic activity gradually becomes vigorous, hyphae grow rapidly and consume nutrients in the culture medium. During this process, mushrooms release metabolites such as organic acids, causing the pH value of the culture medium to gradually decrease. This downward trend is usually more obvious during the logarithmic growth phase and the speed is faster.

[0093] Stable period and senescence period: When mushrooms enter the stable period, their growth rate begins to slow down and their metabolic activity also weakens relatively. At this time, the downward trend of pH value may gradually slow down or even stabilize. In the senescence period, due to the decline of the physiological function of mushrooms and the further weakening of metabolic activity, the pH value may remain basically unchanged or change very slightly.

[0094] Conductivity change curve, initial stage: Similar to pH value, conductivity may also have a short fluctuation period in the early stage of mushroom inoculation and cultivation. The conductivity change at this stage is affected by multiple factors such as strains, culture medium and environmental conditions.

[0095] Logarithmic growth phase: During the logarithmic growth phase, with the rapid growth of hyphae and the increase of metabolic activity, the ion concentration and electrolyte content in the culture medium may change. This is usually manifested as an increase in conductivity, because the hyphae release or absorb ions during growth, thus changing the conductive properties of the culture medium.

[0096] Stable period and senescence period: When mushrooms enter the stable period, the growth rate and metabolic activity gradually slow down, which may cause the rising trend of conductivity to slow down or stabilize. In the senescence period, due to the decline of mushroom physiological functions and weakening of metabolic activities, the conductivity may remain basically unchanged or slightly decrease.

[0097] It should be noted that the above is only a general trend of change. In the actual planting process, the specific change curves of pH and conductivity will present a complex change pattern due to the combined influence of multiple factors such as strain characteristics, culture medium composition, environmental conditions and management measures. Therefore, growers need to pay close attention to the changes in these parameters and make flexible adjustments and management according to actual conditions.

[0098] In one embodiment of the present invention, the calculation method for the compliance coefficient of the growth status is to obtain the mushroom image data of the current mushroom, compare the mushroom image data with the preset standard growth image, determine the score value of the current mushroom's shape, size, and color, and at the same time calculate the daily growth of the mushroom according to the data collection period, and compare the daily growth with the ideal growth, and set the score value of the current daily growth; the score values ​​of shape, size, color and daily growth are weighted and averaged to obtain the compliance coefficient of the mushroom growth status.

[0099] Mushroom image data: Use a high-definition camera or a professional camera to take photos of mushrooms regularly (e.g., daily) to obtain image data of the mushroom growth process; ensure that the images are clear and the colors are true to life for subsequent accurate identification and analysis.

[0100] Standard growth image data: Before mushroom cultivation or in the early stages of cultivation, take and save images of mushrooms that meet standard growth conditions; these images will serve as a benchmark for subsequent comparisons to assess whether mushroom growth is in line with expectations.

[0101] Daily growth data: The daily growth of mushrooms can be calculated by regularly measuring the dimensions of the mushrooms (such as length, width, height, etc.) and combining the measurement time intervals. This data can be obtained by manual measurement or using automated measurement equipment.

[0102] Ideal growth data: Set the ideal growth of mushrooms at a specific growth stage based on factors such as mushroom species, growth environment, and nutritional conditions.

[0103] Image recognition and comparison: Use image recognition algorithms to identify the shape, color, and size of the collected mushroom images. Compare the recognition results with the standard growth images, and set the corresponding score value (1, 0.5, or 0) based on the comparison results.

[0104] Daily growth score: Compare the calculated daily growth of mushrooms with the ideal growth, and set the daily growth score based on the comparison result. The same scoring system of 1, 0.5 or 0 is used.

[0105] Compliance coefficient calculation: The weighted average of the scores of shape, color, size and daily growth is used to obtain the compliance coefficient of the mushroom growth status. The closer the coefficient is to 1, the more the mushroom growth status is in line with expectations; otherwise, it means that there is a deviation in the growth status.

[0106] In one embodiment of the present invention, the processing method for determining the fertilization scheme currently adopted by the mushrooms is as follows: the method for selecting the fertilization scheme is to weighted average the obtained environmental analysis coefficient, component stability coefficient and compliance coefficient to obtain a comprehensive coefficient, and use the comprehensive coefficient as a search condition to retrieve the corresponding fertilizer amount from a preset scheme library, and use the delivery path as a search condition to retrieve the shortest moving path corresponding to the delivery path from the preset scheme library as the fertilization path; and use the obtained fertilization path and fertilization amount as the fertilization scheme currently adopted by the mushrooms.

[0107] When retrieving the amount of fertilizer, the comprehensive coefficient is compared with the coefficient value set in the preset solution library, the coefficient value with the largest Pearson coefficient after calculation is selected, and the amount of fertilizer corresponding to the coefficient value is selected as the implemented amount of fertilizer.

[0108] When retrieving the fertilization path, the delivery path is compared with the fertilization path set in the preset scheme library, and the fertilization path closest to the delivery path is selected. Each point in the selected fertilization path is readjusted according to the shortest path method, and the adjusted fertilization path is output as the currently used fertilization path.

[0109] In one embodiment of the present invention, after selecting a fertilization scheme, the fertilization evaluation module also needs to verify the effectiveness of the fertilization scheme. At this time, it is necessary to set sampling points according to the set fertilization path, and re-test the mushrooms after fertilization to determine whether the growth status of the mushrooms meets expectations. If it meets expectations, it means that the currently used fertilization scheme is effective. If it is not effective, the fertilization path with the highest path overlap rate of the average value of the fertilizer amount in the last fertilization scheme and the fertilization path is selected to adjust the fertilization scheme until the fertilization effect after the current fertilization is positive.

[0110] The fertilization path with the highest path overlap rate set at this time is selected by selecting the fertilization path with the most common sampling points in the previous fertilization path as the fertilization path implemented this time.

[0111] By selecting the fertilization path with the most common sampling points as the fertilization path for this implementation, it can be ensured that the adjustment of the fertilization plan is based on feedback from actual effects.

[0112] Specifically, if the last fertilization plan failed to achieve the expected results, the system will analyze the reasons and try to improve the results by adjusting the fertilization amount and fertilization path. Selecting the fertilization path with the highest path overlap rate means making adjustments while keeping the last fertilization path as much as possible, which helps to locate the problem more accurately and improve the effectiveness of the adjustment.

[0113] At the same time, by continuously monitoring the growth status of mushrooms and adjusting the fertilization plan according to the actual effect, the scientificity and pertinence of the fertilization plan can be ensured. This dynamic adjustment method helps to quickly find the fertilization plan that is most suitable for mushroom growth and improve production efficiency and yield.

[0114] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention and they are still covered by the protection scope of the present invention.

Claims

1. An intelligent fertilization control system for mushroom cultivation based on the Internet of Things. It is characterized in that include: The data acquisition module is used to collect the environmental data and culture medium data during mushroom cultivation, and transmit the corresponding data to the data processing module; The data processing module is used to process the environmental data and culture medium data to determine the current growth status of the mushrooms; The data processing module includes an environment analysis unit, a culture medium analysis unit and a mushroom growth analysis unit; The environmental analysis unit is used to evaluate the environmental data of the mushrooms, determine whether the current temperature, humidity, and ventilation conditions meet the growth requirements of the mushrooms, and obtain the environmental analysis coefficient; The culture medium analysis unit is used to analyze the culture medium data, determine the delivery path of the nutrients during the growth of the mushrooms, and the component stability coefficient corresponding to the pH value and conductivity; The mushroom growth analysis unit is used to observe the growth rate of mushrooms, determine whether the shape, color and size of mushroom fruiting bodies conform to the normal growth state, and obtain the conformity coefficient of mushroom growth state; The fertilization decision module is used to receive the output results of the data processing module and determine the fertilization plan used for the current mushrooms according to the growth status of the mushrooms; The fertilization evaluation module is used to evaluate the growth status of the mushrooms after fertilization and determine the fertilization effect of the fertilization scheme; The implementation method of the delivery path of the nutrient components includes obtaining the sampling points when the culture medium data is collected, and drawing the identified culture medium into a nutrient component change curve according to the values ​​of the corresponding nutrient components in the culture medium data according to the positions set by the sampling points; Traverse all sampling points, determine the value of the corresponding nutrient component at each sampling point in turn, and judge the difference between the value of the corresponding nutrient component and the preset nutrient component, connect the sampling points with the same difference to form a first path, if there is no sampling point with the same difference, then connect the sampling point with the smallest difference with the corresponding sampling point to form a second path; Determine the sampling points on the first path and the second path in sequence; According to the first path and the second path, a delivery path related to the nutrient components is obtained; According to the first path and the second path, the implementation method of obtaining the delivery path related to the nutrient components is as follows: the first paths are combined into a first path graph, and the combination form of the first path graph is to merge all the first paths to determine how many different nutrient component values ​​exist in the currently implemented mushroom cultivation, and at the same time, the characteristics of each first path need to be determined to select the first path that needs to be processed currently; Determine the curvature corresponding to each sampling point in the first path map, take the sampling point whose curvature is greater than the preset curvature value as the target sampling point, obtain the perpendicular bisector corresponding to the target sampling point, and select the intersection of the perpendicular bisector corresponding to the target sampling point and the first path map as the first candidate path; obtain a second candidate path related to the second path according to the obtained first candidate path; Count the maximum and minimum values ​​of nutrients on the first alternative path and the second alternative path; Delete the points between the maximum and minimum points of the first candidate path and the second candidate path, interpolate the maximum and minimum points according to the preset interpolation interval, and use the interpolated path as the output delivery path; The second candidate path is obtained by connecting the points on the first candidate path one by one, obtaining the perpendicular bisector of the connecting line segment of each point on the first candidate path, intersecting the perpendicular bisector on the first candidate path with the second path, and connecting the intersection points on the second path at this time to obtain the second candidate path; According to the growth status of mushrooms, the processing method for determining the fertilization scheme currently used by mushrooms is as follows: weighted average the environmental analysis coefficient, component stability coefficient and compliance coefficient obtained to obtain a comprehensive coefficient, and the comprehensive coefficient is used as a search condition to retrieve the corresponding fertilization amount from the preset scheme library, and the delivery path is used as a search condition to retrieve the shortest moving path corresponding to the delivery path from the preset scheme library as the fertilization path; the fertilization path and fertilization amount obtained are used as the fertilization scheme currently used by mushrooms; When searching for the fertilizer amount, the comprehensive coefficient is compared with the coefficient value set in the preset solution library, the coefficient value with the largest Pearson coefficient value after calculation is selected, and the fertilizer amount corresponding to the coefficient value is selected as the implemented fertilizer amount; When retrieving the fertilization path, the delivery path is compared with the fertilization path set in the preset scheme library, and the fertilization path closest to the delivery path is selected. Each point in the selected fertilization path is readjusted according to the shortest path method, and the adjusted fertilization path is output as the currently used fertilization path.

2. According to claim 1, a mushroom cultivation intelligent fertilization control system based on the Internet of Things, It is characterized in that The method for obtaining the environmental analysis coefficient is to first compare the currently identified temperature, humidity, and ventilation conditions with the preset data, and determine the correlation coefficients of temperature, humidity, and ventilation conditions in turn; and use the weighted average of the correlation coefficients of temperature, humidity, and ventilation conditions as the output environmental analysis coefficient.

3. According to the IoT-based intelligent fertilization control system for mushroom cultivation according to claim 1, It is characterized in that The component stability coefficient is obtained by obtaining the change curves of pH value and conductivity, determining the trend repetition rate of the change curves of pH value and conductivity and a preset trend, and outputting the trend repetition rate as the component stability coefficient.

4. According to the IoT-based intelligent fertilization control system for mushroom cultivation according to claim 1, It is characterized in that The calculation method for the compliance coefficient of the growth status is to obtain the mushroom image data of the current mushroom, compare the mushroom image data with the preset standard growth image, determine the score value of the current mushroom's shape, size, and color, and at the same time calculate the daily growth of the mushroom according to the data collection period, and compare the daily growth with the ideal growth, and set the score value of the current daily growth; the score values ​​of shape, size, color and daily growth are weighted and averaged to obtain the compliance coefficient of the mushroom growth status.

5. According to the IoT-based intelligent fertilization control system for mushroom cultivation according to claim 1, It is characterized in that After selecting the fertilization plan, the fertilization evaluation module determines whether the growth status of the mushrooms meets expectations. If it meets expectations, it means that the current fertilization plan is effective. If it is not effective, the fertilization path with the highest path overlap rate of the average fertilizer amount and the fertilization path in the last fertilization plan is selected to adjust the fertilization plan until the fertilization effect after the current fertilization is positive.

Images