Medium cultivation blueberry irrigation method and system based on weighing feedback of Internet of Things

Abstract

The invention relates to the technical field of blueberry irrigation, and particularly discloses a substrate cultivation blueberry irrigation method and system based on Internet of Things weighing feedback, and the method comprises the steps: obtaining a plurality of blueberry real-time weight values according to a preset interval time, and obtaining the daily irrigation amount according to the plurality of blueberry real-time weight values, acquiring daily blueberry canopy leaf image information according to a first preset time, and acquiring a coverage rate of each blueberry according to the daily blueberry canopy leaf image information; obtaining each demand of the blueberries according to the coverage rate of each blueberry, and obtaining supplementary irrigation amount according to each demand of the blueberries and daily irrigation amount; and obtaining the EC value of the discharged liquid and the EC value of the fed liquid of the blueberries according to a second preset time. By monitoring the weight change of the blueberries in real time and dynamically adjusting the irrigation amount, it is ensured that the blueberries obtain water in time when needed, poor growth caused by water shortage is avoided, meanwhile, excessive irrigation is avoided, and the utilization efficiency of water resources is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of blueberry irrigation, in particular to a substrate cultivation blueberry irrigation method and system based on Internet of Things weighing feedback. Background Art

[0002] Blueberries are fruits with high economic value and have relatively high requirements for growth environment and irrigation management. The growth of blueberries is affected by various factors, including soil conditions, climate, light, temperature, and humidity, etc. The root system of blueberries is relatively shallow and sensitive to the demand for water and nutrients. Especially in substrate cultivation, the water holding capacity and drainage performance of the substrate are different from natural soil, and the requirements for irrigation are more stringent.

[0003] Existing blueberry planting farms adopt a fixed irrigation plan without considering the actual water demand of blueberries and environmental changes, resulting in insufficient or excessive irrigation. The fixed irrigation plan and manual judgment are prone to over-irrigation, which not only wastes a large amount of water resources but also causes salt accumulation in the substrate, affecting the root health and growth of blueberries. Summary of the Invention

[0004] The purpose of the present invention is to provide a substrate cultivation blueberry irrigation method and system based on Internet of Things weighing feedback to solve the technical problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] A substrate cultivation blueberry irrigation method based on Internet of Things weighing feedback, applied to Internet of Things edge computing, includes:

[0007] Obtain multiple real-time blueberry weight values at preset intervals, and obtain the daily irrigation amount according to the multiple real-time blueberry weight values;

[0008] Obtain the daily blueberry canopy leaf image information at a first preset time, and obtain the blueberry coverage rate per plant according to the daily blueberry canopy leaf image information;

[0009] Obtain the water demand per blueberry plant according to the blueberry coverage rate per plant, and obtain the supplementary irrigation amount according to the water demand per blueberry plant and the daily irrigation amount;

[0010] Obtain the EC value of the discharged liquid and the EC value of the inlet liquid of the blueberry at a second preset time;

[0011] Judge whether the EC value of the discharged liquid is within the preset return liquid pH value range;

[0012] If it is within, judge that the irrigation at the second preset time is completed;

[0013] If not, it is determined that the irrigation at the second preset time is not completed, and the leaching mode is turned on until the EC value of the discharge liquid is the same as the EC value of the inlet liquid and is within the preset return liquid pH value range.

[0014] Preferably, the step of obtaining multiple real-time blueberry weight values at preset time intervals includes:

[0015] Taking 7:00 am and 3:00 pm every day as the first initial recording time and the second initial recording time respectively;

[0016] Obtaining the first initial weight of the blueberries at the first initial recording time and the second initial weight of the blueberries at the second initial recording;

[0017] Obtaining the preset recording time interval every day;

[0018] Starting from the first initial weight, obtaining multiple first blueberry weight values according to the preset recording time interval;

[0019] Starting from the second initial weight, obtaining multiple second blueberry weight values according to the preset recording time interval;

[0020] Obtaining multiple real-time blueberry weight values of the blueberries every day according to the multiple first blueberry weight values and the multiple second blueberry weight values.

[0021] Preferably, the step of obtaining the daily irrigation amount according to the multiple real-time blueberry weight values includes:

[0022] Obtaining multiple weight reduction amounts according to the multiple real-time blueberry weight values;

[0023] Judging whether each weight reduction amount is greater than a preset value;

[0024] If it is less than, it is determined that the blueberries at this time do not need irrigation;

[0025] If it is greater than, it is determined that the blueberries at this time need irrigation, and the weight reduction amount at this time is used as the real-time irrigation amount;

[0026] Obtaining all the real-time irrigation amounts to obtain the daily irrigation amount.

[0027] Preferably, the step of obtaining the per blueberry coverage rate according to the daily blueberry canopy leaf image information includes:

[0028] Performing normalization processing on the daily blueberry canopy leaf image information to obtain the blueberry canopy leaf image information in a state;

[0029] Converting the blueberry canopy leaf image information into a leaf grayscale image;

[0030] Segment the grayscale image of the leaf based on a preset threshold to obtain a leaf pixel map and a background pixel map;

[0031] Obtain the number of leaf pixels according to the leaf pixel map;

[0032] Obtain the number of background pixels according to the background pixel map;

[0033] Obtain the per blueberry coverage rate according to the number of leaf pixels and the number of background pixels.

[0034] Preferably, the step of obtaining the daily water requirement of blueberries according to the blueberry canopy leaf coverage rate includes:

[0035] Obtain the water quantity relationship coefficient between growth and water requirement according to the blueberry canopy leaf coverage rate;

[0036] Obtain the per blueberry requirement based on the greenhouse Penman formula and the water quantity relationship coefficient.

[0037] Preferably, the step of obtaining the EC value of the discharge liquid of blueberries according to the second preset time includes:

[0038] Obtain the discharge liquid sample of blueberries based on the second preset time;

[0039] Obtain the discharge liquid EC value according to the discharge liquid sample;

[0040] Obtain the inflow volume of the blueberry spraying device;

[0041] Obtain the inflow EC value according to the inflow volume.

[0042] The present invention also discloses a substrate cultivation blueberry irrigation system based on Internet of Things weighing feedback, which is applied to Internet of Things edge computing and includes:

[0043] The first acquisition module is used to acquire multiple real-time blueberry weight values at preset intervals and obtain the daily irrigation amount according to the multiple real-time blueberry weight values,

[0044] The second acquisition module is used to acquire the daily blueberry canopy leaf image information at the first preset time and obtain the per blueberry coverage rate according to the daily blueberry canopy leaf image information;

[0045] The third acquisition module is used to obtain the per blueberry requirement according to the per blueberry coverage rate and obtain the supplementary irrigation amount according to the per blueberry requirement and the daily irrigation amount;

[0046] The fourth acquisition module is used to acquire the EC value of the discharge liquid and the inflow EC value of blueberries at the second preset time;

[0047] The judgment module is used to judge whether the discharge liquid EC value is within the preset return liquid pH value range;

[0048] If it is in a certain state, it is determined that the irrigation is completed at the second preset time;

[0049] If it is not in the certain state, it is determined that the irrigation at the second preset time is not completed, and the leaching mode is started until the EC value of the discharged liquid is the same as the EC value of the incoming liquid and is within the preset return liquid pH value range.

[0050] Preferably, the second acquisition module includes:

[0051] The first acquisition unit is used to normalize the daily blueberry canopy leaf image information to obtain the blueberry canopy leaf image information in a certain state;

[0052] The second acquisition unit is used to convert the blueberry canopy leaf image information into a leaf grayscale image;

[0053] The third acquisition unit is used to segment the leaf grayscale image based on a preset threshold to obtain a leaf pixel map and a background pixel map;

[0054] The fourth acquisition unit is used to obtain the number of leaf pixels according to the leaf pixel map;

[0055] The fifth acquisition unit is used to obtain the number of background pixels according to the background pixel map;

[0056] The sixth acquisition unit is used to obtain the per blueberry coverage rate according to the number of leaf pixels and the number of background pixels.

[0057] The present invention also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned substrate cultivation blueberry irrigation method based on Internet of Things weighing feedback are implemented.

[0058] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned substrate cultivation blueberry irrigation method based on Internet of Things weighing feedback are implemented.

[0059] The beneficial effects of the present application are as follows: By real-time monitoring the weight change of blueberries, the present invention dynamically adjusts the irrigation amount to ensure that blueberries can obtain water in time when needed, avoiding poor growth caused by water shortage, while avoiding over-irrigation, improving the utilization efficiency of water resources. At the same time, regularly obtaining samples of the discharged liquid of blueberries, measuring the EC values of the discharged liquid and the incoming liquid, and dynamically adjusting the irrigation strategy to ensure that the salt concentration in the substrate is maintained within an appropriate range, avoiding the negative impact of salt accumulation on the growth of blueberries, improving the efficiency and accuracy of blueberry irrigation management, and also solving the problems of inaccuracy, water resource waste, salt accumulation, excessive manual intervention, insufficient data support and poor environmental adaptability existing in traditional irrigation technologies. Brief Description of the Drawings

[0060] Figure 1 It is a schematic flowchart of the method according to an embodiment of the present application.

[0061] Figure 2 It is a schematic structural diagram of the system according to an embodiment of the present application.

[0062] The realization of the purpose, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. Detailed Embodiments

[0063] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0064] As Figure 1 shown, the present application provides a substrate-cultivated blueberry irrigation method based on Internet of Things weighing feedback, which is applied to Internet of Things edge computing and includes:

[0065] S1. Obtain multiple real-time blueberry weight values at preset intervals, and obtain the daily irrigation amount according to the multiple real-time blueberry weight values;

[0066] S2. Obtain the daily blueberry canopy leaf image information at a first preset time, and obtain the per-blueberry coverage rate according to the daily blueberry canopy leaf image information;

[0067] S3. Obtain the per-blueberry requirement according to the per-blueberry coverage rate, and obtain the supplementary irrigation amount according to the per-blueberry requirement and the daily irrigation amount;

[0068] S4. Obtain the EC value of the discharged liquid and the EC value of the incoming liquid of the blueberries at a second preset time;

[0069] S5. Judge whether the EC value of the discharged liquid is within the preset return liquid pH value range;

[0070] If it is within, it is judged that the irrigation at the second preset time is completed;

[0071] If it is not within, it is judged that the irrigation at the second preset time is not completed, and the flushing mode is started until the EC value of the discharged liquid is the same as the EC value of the incoming liquid and is within the preset return liquid pH value range.

[0072] As described in the above steps S1 - S6, blueberries, as fruits with high economic value, have relatively high requirements for the growth environment and irrigation management. The growth of blueberries is affected by various factors, including soil conditions, climate, light, temperature, humidity, etc. Especially in substrate cultivation, due to the water - holding capacity and drainage performance of the substrate being different from natural soil, the requirements for irrigation are even more stringent. Reasonable irrigation management can not only ensure the healthy growth of blueberries, but also improve the yield and fruit quality. Although the existing blueberry irrigation technologies meet the basic needs of blueberry growth to a certain extent, there are still many defects in practical applications. These defects not only affect the growth and yield of blueberries, but also increase the management cost and labor intensity of growers. Many farms adopt a fixed irrigation plan without considering the actual water demand of blueberries and environmental changes. This one - size - fits - all method cannot adapt to the water demand in different growth stages and different environmental conditions, easily leading to insufficient or excessive irrigation. And it relies on manual observation and empirical judgment of irrigation timing and amount, which is prone to subjective errors. The uneven experience levels of growers result in inconsistent irrigation decisions, affecting the growth of blueberries.

[0073] Through high-frequency weight monitoring, the system can obtain the real-time weight value of blueberries in real time and dynamically calculate the daily irrigation volume based on this data. When the weight reduction reaches or exceeds the preset weight value and it is within the irrigation working time, the system will automatically open the irrigation valve, and the irrigation volume is equal to the weight reduction. The total daily irrigation volume is the sum of all irrigation volumes. This method of real-time monitoring and precise irrigation can not only ensure that irrigation is carried out in a timely manner when blueberries need water, avoiding poor growth caused by water shortage, but also avoid water resource waste caused by over-irrigation. Traditional irrigation methods often rely on experience and fixed irrigation times, unable to accurately reflect the actual water requirements of plants, easily leading to under-irrigation or over-irrigation, affecting the growth and yield of blueberries. Through the real-time monitoring of the Internet of Things weighing device and the dynamic adjustment of the irrigation volume, the system effectively solves these problems and improves the utilization efficiency of water resources. Secondly, the system obtains the daily blueberry canopy leaf image information according to the first preset time (such as 7 o'clock every morning) through the camera and image processing technology, and calculates the daily blueberry coverage rate (LC). The specific steps include normalizing the image, converting it into a grayscale image, performing image segmentation based on a preset threshold, calculating the number of leaf pixels and the number of background pixels, and finally obtaining the daily blueberry coverage rate. This method can accurately evaluate the growth status of the blueberry canopy and provide a scientific basis for subsequent water requirement calculations. Traditional manual measurement of leaf coverage rate is prone to errors, affecting the accuracy of irrigation decisions, and it is difficult to achieve continuous data collection and dynamically monitor the growth status of plants. Through image processing technology, the system can automatically obtain the daily leaf coverage rate, reducing the workload of manual measurement and improving the accuracy and continuity of data. Next, the system calculates the growth and water requirement relationship coefficient (KLC) according to the daily blueberry coverage rate (LC), and uses KLC and the improved greenhouse Penman formula to calculate the daily water requirement of blueberries (ET LC). Then, according to the difference between the daily water requirement and the actual irrigation volume, the supplementary irrigation volume is calculated. This accurate water requirement calculation method combines leaf coverage rate and meteorological parameters, can more accurately reflect the daily water requirement of blueberries, and ensure that plants obtain appropriate moisture. Traditional irrigation plans are often static and unable to be dynamically adjusted according to the growth status of plants and environmental changes, easily leading to under-irrigation or over-irrigation, affecting the growth and yield of blueberries. By dynamically adjusting the irrigation strategy, the system can ensure that the growth requirements of blueberries are fully met according to the difference between the actual water requirement and the irrigated volume, improving the efficiency and accuracy of irrigation management. In addition, the system obtains the drainage sample of blueberries according to the second preset time (such as the same time point every three days), and measures the EC value of the drainage with a conductivity meter. At the same time, the system obtains the inflow volume of the blueberry spraying device and calculates the EC value of the inflow. By monitoring the EC values of the drainage and the inflow, the system can timely understand the accumulation of salts in the substrate and prevent damage to plants caused by excessive salts.Traditional irrigation methods are difficult to detect and solve the problem of salt accumulation in the substrate in a timely manner, which affects the growth of blueberries. By regularly and automatically collecting the EC values of the drainage liquid and the influent liquid, the system can reduce the workload of manual operation, improve the accuracy and continuity of data, effectively monitor and control the salt content in the substrate. Finally, the system determines whether the EC value of the drainage liquid is within a preset return liquid pH value range (such as 4.5 to 5.5). If both the EC value and the pH value of the drainage liquid are within the preset range, the system determines that the irrigation at the second preset time is completed. If the EC value of the drainage liquid is higher than the EC value of the influent liquid or the pH value is greater than or equal to 5.5, the system starts the leaching mode until the EC value of the drainage liquid is consistent with the EC value of the influent liquid and the pH value is between 4.5 and 5.5 to stop leaching. This salt control method effectively removes excessive accumulated salt in the substrate by starting the leaching mode and maintains the healthy state of the substrate. Traditional manual operations are prone to misjudgment, which affects the irrigation effect. Through automated management, the system can automatically determine whether to start the leaching mode, reduce the need for manual intervention, and ensure the healthy growth of blueberries in a suitable growth environment.

[0074] In one embodiment, the step of obtaining multiple real-time blueberry weight values at preset time intervals includes:

[0075] S101: Respectively take 7:00 am and 3:00 pm every day as the first initial recording time and the second initial recording time;

[0076] S102: Obtain the first initial weight of the blueberries at the first initial recording time, and obtain the second initial weight of the blueberries at the second initial recording;

[0077] S103: Obtain the preset recording time interval every day;

[0078] S104: Starting from the first initial weight, obtain multiple first blueberry weight values according to the preset recording time interval;

[0079] S105: Starting from the second initial weight, obtain multiple second blueberry weight values according to the preset recording time interval;

[0080] S106: Obtain multiple real-time blueberry weight values of the blueberries every day according to the multiple first blueberry weight values and the multiple second blueberry weight values.

[0081] As described in the above steps S101 - S106, through the above steps, the system of the present invention can monitor the weight change of blueberries in real time, dynamically adjust the irrigation amount, and achieve precise and automated management of blueberry irrigation. Specifically, the system takes 7:00 am and 3:00 pm every day as the first initial recording time and the second initial recording time respectively, and obtains the first initial weight and the second initial weight of the blueberries at these time points. Then, the system obtains the preset recording time interval every day (for example, every 30 seconds), starts from the first initial weight, and obtains multiple first blueberry weight values according to the preset recording time interval; starts from the second initial weight, and also obtains multiple second blueberry weight values according to the preset recording time interval. Finally, the system obtains multiple real - time blueberry weight values of the blueberries every day based on the multiple first blueberry weight values and the multiple second blueberry weight values. These steps bring significant beneficial effects and also solve multiple defects in the existing irrigation technology. First, in terms of real - time monitoring, by recording the weight of blueberries once every 30 seconds, the system can monitor the weight change of blueberries in real time and timely detect the water demand of blueberries. The multi - period recording (7:00 am and 3:00 pm) covers different growth periods of blueberries in a day, ensuring the comprehensiveness and accuracy of the data. Second, in terms of precise irrigation, the system dynamically adjusts the irrigation amount according to the real - time weight change, ensuring that blueberries can obtain water in time when needed and avoiding poor growth caused by water shortage. Through precise weight monitoring and irrigation amount calculation, the system can avoid water resource waste caused by over - irrigation and improve the utilization efficiency of water resources. In addition, in terms of automated management, the system automatically records and analyzes the weight change of blueberries, reduces the need for manual intervention, and improves the management efficiency. Through continuous data collection with high - frequency recording, the system can achieve continuous data collection and provide a scientific basis for the growth status of blueberries.

[0082] In one embodiment, the step of obtaining the daily irrigation amount according to the multiple real - time blueberry weight values includes:

[0083] S107. Obtain multiple weight reduction amounts according to the multiple real - time blueberry weight values;

[0084] S108. Determine whether each weight reduction amount is greater than a preset value;

[0085] If it is less, it is determined that the blueberries at this time do not need irrigation;

[0086] If it is greater, it is determined that the blueberries at this time need irrigation, and the weight reduction amount at this time is used as the real - time irrigation amount;

[0087] S109. Obtain all the real - time irrigation amounts to get the daily irrigation amount.

[0088] As described in the above steps S107 - S109, through the above steps, the system of the present invention can monitor the weight change of blueberries in real time, dynamically adjust the irrigation amount, and achieve precise and automated management of blueberry irrigation. Specifically, the system obtains multiple weight reduction amounts based on multiple real - time weight values of blueberries, and determines whether each weight reduction amount is greater than a preset value (for example, 0.4 kg). If it is less than the preset value, it is determined that the blueberries at this time do not need irrigation; if it is greater than the preset value, it is determined that the blueberries at this time need irrigation, and the weight reduction amount at this time is used as the real - time irrigation amount. Finally, the system obtains all real - time irrigation amounts to get the daily irrigation amount. The above steps bring significant beneficial effects and also solve multiple defects in the existing irrigation technology. First, in terms of precise irrigation, by monitoring the weight change of blueberries in real time, the system can timely detect the water demand of blueberries, ensure timely irrigation when needed, and avoid poor growth caused by water shortage. Dynamically adjusting the irrigation amount ensures that each irrigation is necessary, improving the accuracy of irrigation. Second, in terms of avoiding waste, by using the preset value to judge whether irrigation is needed, unnecessary irrigation is avoided, reducing water resource waste and improving the utilization efficiency of water resources.

[0089] In one embodiment, the step of obtaining the per - blueberry coverage rate according to the daily blueberry canopy leaf image information includes:

[0090] S201. Normalize the daily blueberry canopy leaf image information to obtain the blueberry canopy leaf image information in a normalized state;

[0091] S202. Convert the blueberry canopy leaf image information into a leaf grayscale image;

[0092] S203. Segment the leaf grayscale image based on a preset threshold to obtain a leaf pixel map and a background pixel map;

[0093] S204. Obtain the number of leaf pixels according to the leaf pixel map;

[0094] S205. Obtain the number of background pixels according to the background pixel map;

[0095] S206. Obtain the per - blueberry coverage rate according to the number of leaf pixels and the number of background pixels.

[0096] As described in the above steps S201 - S206, through the above steps, the present invention can perform standardized processing, grayscale image conversion, threshold segmentation, pixel quantity statistics, and coverage rate calculation on the daily blueberry canopy leaf image information, realizing the accurate calculation and dynamic monitoring of the blueberry canopy coverage rate. Specifically, the system first normalizes the daily blueberry canopy leaf image information to obtain standardized image information, eliminating the influence of factors such as light and angle, ensuring the consistency and comparability of the images. Then, the standardized image information is converted into a grayscale image, simplifying the complexity of image processing, reducing the computational amount, improving the processing speed, and at the same time better highlighting the characteristics of the leaves. Then, based on a preset threshold, the grayscale image is segmented, effectively separating the leaf pixels and background pixels, improving the accuracy of image segmentation. Through the segmented leaf pixel map and background pixel map, the system respectively obtains the leaf pixel quantity and background pixel quantity, providing reliable data support for calculating the blueberry canopy coverage rate. Finally, according to the leaf pixel quantity and background pixel quantity, the system can accurately calculate the daily blueberry canopy coverage rate. Among them, in terms of image standardization, by normalizing the daily blueberry canopy leaf image information, the influence of factors such as light and angle is eliminated, ensuring the consistency and comparability of the images, and improving the accuracy of subsequent processing. In terms of image segmentation, based on a preset threshold, the grayscale image is segmented, which can effectively separate the leaf pixels and background pixels, improving the accuracy of image segmentation. In terms of precise segmentation, through threshold segmentation, the system can accurately extract the leaf area, providing reliable data support for subsequent pixel quantity statistics. In terms of pixel quantity statistics, the system respectively obtains the leaf pixel quantity and background pixel quantity according to the leaf pixel map and background pixel map, providing key data for calculating the blueberry canopy coverage rate. In terms of precise calculation, through the leaf pixel quantity and background pixel quantity, the system can accurately calculate the daily blueberry canopy coverage rate.

[0097] In one embodiment, the step of obtaining the daily water requirement of blueberries according to the blueberry canopy leaf coverage rate includes:

[0098] S301. Obtain the water quantity relationship coefficient between growth and water requirement according to the blueberry canopy leaf coverage rate;

[0099] S302. Obtain the daily water requirement of blueberries based on the greenhouse Penman formula and the water quantity relationship coefficient.

[0100] As described in the above steps S301 - S302, through the above steps, the system of the present invention can calculate the relationship coefficient (KLC) between growth and water requirement according to the leaf coverage rate (LC) of blueberry canopy, and calculate the daily water requirement (ETLC) of blueberry by combining with the improved Penman formula for greenhouse. Specifically, the system first calculates the relationship coefficient (KLC) between growth and water requirement according to the leaf coverage rate (LC) of blueberry canopy. The calculation formula of KLC is: Then, the system uses the improved Penman formula for greenhouse to calculate the reference evapotranspiration (ET0), and the formula is as follows:

[0101] Δl is the rate of change of saturated water vapor pressure with temperature, with the unit of kPa / °C; R n is the net radiation amount, with the unit of MJ / m 2 / day; G is the soil heat flux density, set to 0; γ is the psychrometric constant, with the unit of kPa / °C; T is the average temperature, with the unit of °C; e s is the saturated water vapor pressure, with the unit of kPa; e a is the actual water vapor pressure, with the unit of kPa; u 2 is the wind speed at the preset height, with the unit of m / s. Finally, the daily water requirement (ET LC ) of blueberry is calculated by using KLC and ET0:

[0102] ET LC = KLC × ET0;

[0103] The above steps have brought significant beneficial effects and also solved multiple defects in the prior art. First, in terms of accurately calculating the water requirement, by calculating the relationship coefficient (KLC) between growth and water requirement through the leaf coverage rate (LC) of the blueberry canopy, the change in water requirement of blueberries at different growth stages can be more accurately reflected. KLC changes with the change in the leaf coverage rate of the blueberry canopy, ensuring the dynamics and flexibility of water requirement calculation. Second, in terms of scientific water requirement prediction, the improved Penman formula for greenhouses is used to calculate the reference evapotranspiration (ET0), comprehensively considering various environmental factors such as temperature, humidity, light intensity, and wind speed, improving the scientificity and accuracy of water requirement prediction. By introducing multiple environmental parameters, the system can more comprehensively evaluate the water requirement of blueberries and ensure the rationality of the irrigation strategy. In addition, in terms of personalized management, the leaf coverage rates of different blueberry plants may be different. Through the calculation of KLC and ET0, the system can achieve personalized management of each blueberry plant, improving the overall planting efficiency. Blueberries have different water requirements at different growth stages. By dynamically adjusting KLC, the system can better adapt to the growth needs of blueberries and ensure that the water requirement at each growth stage is met. In terms of data support, the system records the values of KLC and ET0 each time, accumulating a large amount of data, providing rich data support for subsequent data analysis and model optimization. Through long-term data recording, the growth trend and water requirement pattern of blueberries can be analyzed to further optimize the irrigation strategy. It effectively solves multiple defects in the prior art. First, in terms of inaccurate water requirement prediction, traditional water requirement prediction methods often use fixed coefficients, without considering the actual growth status and environmental changes of blueberries, which easily leads to inaccurate water requirement prediction. Depending on a single environmental parameter (such as temperature or humidity), the influence of multiple environmental factors is not comprehensively considered. Through the combination of KLC and the Penman formula for greenhouses, the system can more accurately predict the water requirement of blueberries. Second, in terms of inflexible irrigation strategy, traditional irrigation strategies are often fixed and do not adapt to the change in water requirement of blueberries at different growth stages, easily leading to insufficient or excessive irrigation. Traditional irrigation strategies are difficult to consider the individual differences between different plants, affecting the overall planting efficiency. By dynamically adjusting KLC, the system can achieve personalized management of each blueberry plant, improving the overall planting efficiency.

[0104] In one embodiment, the step of obtaining the EC value of the discharge liquid of blueberries according to the second preset time includes:

[0105] S401. Obtain a discharge liquid sample of blueberries based on the second preset time;

[0106] S402. Obtain the discharge liquid EC value according to the discharge liquid sample;

[0107] S403. Obtain the liquid inflow of the blueberry spraying device;

[0108] S404. Obtain the inlet liquid EC value according to the inlet liquid volume.

[0109] As described in the above steps S401 - S404, through the above steps, the system of the present invention can regularly obtain the drainage liquid samples of blueberries, measure the electrical conductivity (EC value) of the drainage liquid, and obtain the liquid intake volume and the inlet liquid EC value of the blueberry spraying equipment. Specifically, the system obtains the drainage liquid samples of blueberries based on a second preset time (for example, the same time point every three days), and then obtains the drainage EC value according to the drainage liquid samples. Then, the system obtains the liquid intake volume of the blueberry spraying equipment and obtains the inlet liquid EC value according to the liquid intake volume. The above steps bring significant beneficial effects and also solve multiple defects in the prior art. First, in terms of salt monitoring, by obtaining the drainage liquid samples of blueberries at the same time point every three days, the system can regularly monitor the salt accumulation in the substrate, ensuring timely discovery and solution of problems. Measuring the EC value of the drainage liquid using a conductivity meter can accurately reflect the salt concentration in the substrate, providing a scientific basis for subsequent salt management and irrigation decision-making. Second, in terms of data support, by regularly collecting drainage liquid samples and measuring the EC value, the system can achieve continuous data collection, providing rich data support for substrate salt management. Through long-term data recording, the change trend of substrate salt can be analyzed to further optimize irrigation strategies and salt management measures. In addition, in terms of irrigation management, by comparing the EC values of the drainage liquid and the inlet liquid, the system can dynamically adjust the irrigation strategy to ensure that the salt concentration in the substrate is maintained within an appropriate range. Avoiding the problem of salt accumulation caused by over-irrigation improves the scientificity and effectiveness of irrigation management. In terms of automated management, the system automatically obtains drainage liquid samples and measures the EC value, reducing the need for manual intervention and improving management efficiency. Through automated management, the system can achieve all-weather monitoring and management to ensure that the growth needs of blueberries are continuously met. The above steps effectively solve multiple defects in the prior art. First, in terms of insufficient salt monitoring, traditional salt monitoring methods often rely on manual sampling and laboratory analysis, making it difficult to achieve continuous monitoring and affecting the timely discovery and treatment of substrate salt accumulation. Manual sampling and laboratory analysis are prone to errors, affecting the accuracy of salt monitoring. By regularly collecting drainage liquid samples and using a conductivity meter to measure the EC value, the system can provide accurate salt data. Second, in terms of unscientific irrigation management, traditional irrigation plans often adopt fixed irrigation amounts and frequencies without considering the salt accumulation in the substrate, easily leading to over-irrigation or under-irrigation. Traditional irrigation systems lack the ability to dynamically adjust irrigation strategies according to the substrate salt concentration and cannot adapt to complex growth environments. By comparing the EC values of the drainage liquid and the inlet liquid, the system can dynamically adjust the irrigation strategy to ensure that the salt concentration in the substrate is maintained within an appropriate range. In addition, in terms of insufficient data support, traditional irrigation systems lack systematic data recording and analysis means, making it difficult to discover the change trends and laws of substrate salt. Lack of systematic data analysis means makes it difficult to discover the change trends and laws of substrate salt.By regularly collecting drainage samples and measuring the EC value, the system can provide rich data support, providing a basis for subsequent analysis and optimization. Manual intervention is required in many aspects. Traditional salt monitoring and irrigation management methods require frequent manual intervention, increasing labor costs and reducing management efficiency. The operation is complex and requires certain professional knowledge and technical background, with relatively high technical requirements for growers. Through automated management, the system simplifies the operation process and reduces the technical threshold.

[0110] As Figure 2 shown, the present invention also provides a substrate-cultivated blueberry irrigation system based on Internet of Things weighing feedback, which is applied to Internet of Things edge computing and includes:

[0111] The first acquisition module 1 is used to acquire multiple real-time blueberry weight values at preset intervals and obtain the daily irrigation amount according to the multiple real-time blueberry weight values.

[0112] The second acquisition module 2 is used to acquire the daily blueberry canopy leaf image information at a first preset time and obtain the per-blueberry coverage rate according to the daily blueberry canopy leaf image information.

[0113] The third acquisition module 3 is used to obtain the per-blueberry demand of blueberries according to the per-blueberry coverage rate and obtain the supplementary irrigation amount according to the per-blueberry demand and the daily irrigation amount.

[0114] The fourth acquisition module 4 is used to acquire the EC value of the drainage liquid and the EC value of the influent liquid of blueberries at a second preset time.

[0115] The judgment module 5 is used to judge whether the EC value of the drainage liquid is within a preset return liquid pH value range.

[0116] If it is within, it is judged that the irrigation at the second preset time is completed.

[0117] If it is not within, it is judged that the irrigation at the second preset time is not completed, and the flushing mode is started until the EC value of the drainage liquid is consistent with the EC value of the influent liquid and within the preset return liquid pH value range.

[0118] The judgment module 6 is used to judge whether the data quality deviation value is greater than a preset value.

[0119] If it is greater, the corresponding initial data source information is entered into the database to complete data collection.

[0120] If it is less, the corresponding initial data source information is recollected in multiple sequences.

[0121] In one embodiment, the second acquisition module 2 includes:

[0122] A first acquisition unit for normalizing the daily blueberry canopy leaf image information to obtain the blueberry canopy leaf image information;

[0123] A second acquisition unit for converting the blueberry canopy leaf image information into a leaf grayscale image;

[0124] A third acquisition unit for segmenting the leaf grayscale image based on a preset threshold to obtain a leaf pixel map and a background pixel map;

[0125] A fourth acquisition unit for obtaining the number of leaf pixels according to the leaf pixel map;

[0126] A fifth acquisition unit for obtaining the number of background pixels according to the background pixel map;

[0127] A sixth acquisition unit for obtaining the per blueberry coverage rate according to the number of leaf pixels and the number of background pixels.

[0128] The present invention also provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of the above-mentioned substrate-cultivated blueberry irrigation method based on Internet of Things weighing feedback are implemented.

[0129] The present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned substrate-cultivated blueberry irrigation method based on Internet of Things weighing feedback are implemented.

[0130] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, value library, or other medium provided in this application and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0131] It should be noted that in this article, the term "including", "comprising", or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, apparatus, article, or method including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such a process, apparatus, article, or method. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, apparatus, article, or method including that element.

[0132] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent results or equivalent process transformations made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, are similarly included in the patent protection scope of the present invention.

Claims

1. A matrix cultivation blueberry irrigation method based on Internet of Things weighing feedback, characterized in that: include: Acquire a plurality of real-time weight values ​​of blueberries at preset time intervals, and acquire a daily irrigation amount based on the plurality of real-time weight values ​​of blueberries; Acquire daily blueberry canopy leaf image information according to a first preset time, and acquire the coverage rate of each blueberry according to the daily blueberry canopy leaf image information; Obtaining a required amount of blueberries according to the blueberry coverage rate, and obtaining a supplementary irrigation amount according to the required amount of blueberries and a daily irrigation amount; Obtaining the EC value of the discharged liquid and the EC value of the inlet liquid of the blueberry according to the second preset time; Determining whether the EC values ​​of the discharged liquid are all within a preset return liquid pH value range; If so, it is determined that the irrigation at the second preset time is completed; If not, it is determined that the irrigation within the second preset time is not completed, and the rinse mode is turned on until the EC value of the discharge liquid is consistent with the EC value of the inlet liquid and is within the preset return liquid pH value range.

2. The method for substrate cultivation of blueberries based on Internet of Things weighing feedback according to claim 1, characterized in that: The step of obtaining a plurality of real-time weight values ​​of blueberries at preset time intervals includes: 7:00 a.m. and 3:00 p.m. every day are respectively used as the first initial recording time and the second initial recording time; obtaining a first initial weight of the blueberries at a first initial recording time, and obtaining a second initial weight of the blueberries at a second initial recording time; Get the preset recording time interval for each day; Taking the first initial weight as a starting point, obtaining a plurality of first blueberry weight values ​​according to the preset recording time interval; Taking the second initial weight as a starting point, obtaining a plurality of second blueberry weight values ​​according to the preset recording time interval; A plurality of real-time daily blueberry weight values ​​are obtained according to the plurality of first blueberry weight values ​​and the plurality of second blueberry weight values.

3. The matrix cultivation blueberry irrigation method based on Internet of Things weighing feedback according to claim 1 is characterized in that: The step of obtaining the daily irrigation amount according to the plurality of real-time weight values ​​of the blueberries comprises: Acquire a plurality of weight reduction amounts according to a plurality of real-time weight values ​​of the blueberries; Determining whether each weight reduction is greater than a preset value; If it is less than that, it is determined that the blueberries do not need irrigation at this time; If it is greater than, it is determined that the blueberries need irrigation at this time, and the weight loss at this time is used as the real-time irrigation amount; All the real-time irrigation amounts are acquired to obtain the daily irrigation amount.

4. The method for irrigation of blueberries cultivated in substrate based on weighing feedback of Internet of Things according to claim 3 is characterized in that: The step of obtaining the coverage rate of each blueberry according to the daily blueberry canopy leaf image information comprises: Normalize the daily blueberry canopy leaf image information to obtain the blueberry canopy leaf image information; Converting the blueberry canopy leaf image information into a leaf grayscale image; The leaf grayscale image is segmented based on a preset threshold to obtain a leaf pixel map and a background pixel map; Acquire the number of leaf pixels according to the leaf pixel map; Acquire the number of background pixels according to the background pixel map; The coverage rate of each blueberry is obtained according to the number of leaf pixels and the number of background pixels.

5. The method for irrigation of blueberries cultivated in substrate based on weighing feedback of Internet of Things according to claim 1, characterized in that: The step of obtaining the daily water requirement of blueberries according to the leaf coverage rate of the blueberry canopy comprises: Obtaining a water relationship coefficient between growth and water requirement according to the blueberry canopy leaf coverage rate; The blueberry requirement is obtained based on the greenhouse Penman formula and water relationship coefficient.

6. The method for irrigation of blueberries cultivated in substrate based on weighing feedback of Internet of Things according to claim 5, characterized in that: The step of obtaining the EC value of the discharged liquid of the blueberry according to the second preset time comprises: obtaining a sample of the discharge liquid of the blueberry based on the second preset time; Obtaining a discharge EC value according to the discharge sample; Get the liquid inflow of the blueberry spraying equipment; The EC value of the influent is obtained according to the influent volume.

7. A matrix cultivation blueberry irrigation system based on IoT weighing feedback, applied to IoT edge computing, characterized in that: include: The first acquisition module is used to acquire a plurality of real-time weight values ​​of blueberries at preset intervals, and acquire a daily irrigation amount according to the plurality of real-time weight values ​​of blueberries. A second acquisition module is used to acquire daily blueberry canopy leaf image information according to a first preset time, and acquire the coverage rate of each blueberry according to the daily blueberry canopy leaf image information; A third acquisition module is used to acquire the required amount of blueberries according to the coverage rate of each blueberry, and acquire the supplementary irrigation amount according to the required amount of blueberries and the daily irrigation amount; A fourth acquisition module, used for acquiring the EC value of the discharged liquid and the EC value of the inlet liquid of the blueberry according to the second preset time; A judgment module, used to judge whether the EC value of the discharge liquid is within a preset return liquid pH value range; If so, it is determined that the irrigation at the second preset time is completed; If not, it is determined that the irrigation within the second preset time is not completed, and the rinse mode is turned on until the EC value of the discharge liquid is consistent with the EC value of the inlet liquid and is within the preset return liquid pH value range.

8. The matrix cultivation blueberry irrigation system based on Internet of Things weighing feedback according to claim 7 is characterized in that: The second acquisition module includes: The first acquisition unit is used to normalize the daily blueberry canopy leaf image information to obtain the blueberry canopy leaf image information; A second acquisition unit is used to convert the blueberry canopy leaf image information into a leaf grayscale image; A third acquisition unit is used to segment the leaf grayscale image based on a preset threshold to obtain a leaf pixel map and a background pixel map; A fourth acquisition unit, configured to acquire the number of leaf pixels according to the leaf pixel map; A fifth acquisition unit, configured to acquire the number of background pixels according to the background pixel map; The sixth acquisition unit is used to acquire the coverage rate of each blueberry according to the number of leaf pixels and the number of background pixels.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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