Wheat-corn annual light and temperature resource comprehensive management system

Abstract

The invention relates to the technical field of resource management, in particular to a wheat-corn annual light and temperature resource comprehensive management system, which comprises an environment monitoring module for collecting soil humidity and meteorological condition data, combining growth data of wheat and corn, and calculating a growth stage demand index to obtain growth demand data. According to the invention, the real-time optimization of resource allocation is realized by continuously collecting data such as soil humidity and meteorological conditions. For an adjustment strategy, irrigation and illumination plans are dynamically adjusted according to real-time environmental changes, and deviation is rapidly identified and corrected in a feedback mechanism, so that resource application is more accurate. The improvement of performance evaluation makes it possible to measure resource consumption and crop growth efficiency through numerical indexes, thereby providing data-driven decision support for agricultural production, ensuring maximum efficiency and economy of resource utilization, and improving crop yield and quality.

Description

Technical Field

[0001] The invention relates to the technical field of resource management, and in particular to an integrated management system for wheat and corn year-round light and temperature resources. Background Art

[0002] The field of resource management technology involves effectively planning, allocating and utilizing natural or artificial resources to maximize efficiency and output. In agriculture, this typically includes water management, soil fertility management, light management and energy usage optimization. Modern resource management technologies utilize sensor networks, automated systems, data analytics and predictive models to monitor environmental conditions and crop growth requirements in real time.

[0003] However, existing technologies are not good at responding quickly to environmental changes and crop needs, relying on regular data updates and manual decision-making, and lacking flexibility. This delayed response often leads to waste of resources, such as unnecessary irrigation and inappropriate light adjustments, which increase energy consumption. Therefore, improvements are needed. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a wheat-corn annual light and temperature resource integrated management system.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: A wheat-corn annual light and temperature resource integrated management system comprises: The environmental monitoring module collects soil moisture and meteorological condition data, combines the growth data of wheat and corn, calculates the growth stage demand index, and obtains growth demand data; uses the growth demand data to optimize the sensor data collection frequency and accuracy, adjust soil and meteorological monitoring parameters, and generate comprehensive monitoring data; The resource allocation module calculates the utilization efficiency of current water resources and light resources based on the comprehensive monitoring data to form a primary allocation result; dynamically adjusts the irrigation and light plans by comparing the primary allocation result with the real-time environmental data to generate a resource allocation result; A dynamic feedback module continuously monitors the deviation between crop growth and the expected target according to the resource allocation result, calculates the real-time adjustment demand, and obtains the real-time adjustment instruction; applies the real-time adjustment instruction to modify the resource input parameters in real time, and generates the adjusted resource allocation; The performance evaluation module uses the output data of the adjusted resource configuration to evaluate resource consumption and crop growth efficiency, calculate the current performance indicators, and obtain performance indicator results.

[0006] Preferably, the steps for acquiring the growth demand data are: Collect data on the growth stages of wheat and corn, including growth cycle, root development and leaf area, as well as soil moisture, temperature and precipitation to obtain environmental and growth data sets; Based on the environment and growth data set, the growth requirement index of wheat and corn is calculated using the following formula: ; in, Represents soil moisture data, Represents meteorological data, Represents growth stage data, , and are the weight coefficients of soil moisture, meteorological conditions and growth stage data, is the total number of data items, GDI is the growth demand index; Based on the growth demand index, the control strategy for each growth stage is determined, and the growth demand data is formed in combination with meteorological conditions and soil moisture.

[0007] Preferably, the steps of acquiring the comprehensive monitoring data are: According to the growth demand data, the new data collection frequency is calculated using the following formula: ; in, represents the new data collection frequency, Represents the maximum data acquisition frequency, is the growth demand index, and is the adjustment coefficient; Adjustments are made based on the new data collection frequency, sensor settings are implemented, and comprehensive monitoring data is obtained.

[0008] Preferably, the steps of obtaining the primary configuration result are: Extracting water resources and light data from the comprehensive monitoring data, including real-time irrigation water volume, cumulative rainfall, total sunshine hours and average cloud coverage, to obtain a water resources and light data set; Based on the water resources and light data set, the utilization efficiency of water resources and light resources is calculated, and the calculation formula is: and ; in, and Represent the utilization efficiency of water resources and light resources respectively, represents the total amount of water used, represents the evaporation rate, is the water resources regulation coefficient, represents the direct sunlight, represents the average cloud coverage, is the light resource adjustment coefficient; The primary configuration results are formed based on the efficiency of the use of water resources and light resources.

[0009] Preferably, the steps of obtaining the resource configuration result are: Analyze the preliminary allocation results, evaluate the matching degree with the current season, crop growth cycle and soil type, and determine the preliminary resource allocation plan; According to the preliminary resource allocation plan, soil moisture, temperature, wind speed and rainfall probability are monitored, and compared with the preliminary allocation results, the parameters that need to be adjusted are identified, the starting frequency of the water pump and the illumination intensity of the light are planned, and adjustment suggestions are obtained; Based on the adjustment suggestions, the running time of the water pump is changed, the light intensity and duration are adjusted, and the resource allocation result is obtained.

[0010] Preferably, the step of acquiring the real-time adjustment instruction is: Based on the resource allocation result, the plant height and chlorophyll content of the crop are collected to obtain real-time crop growth data; Based on the real-time crop growth data, the deviation between the plant height and the set growth target is compared, the difference between the plant height and the expected height and whether the chlorophyll content meets the standard are analyzed, the causes of the deviation are classified, and the growth deviation analysis results are obtained; According to the growth deviation analysis results, the required irrigation and lighting adjustment amounts are determined, and real-time adjustment instructions are obtained.

[0011] Preferably, the steps of obtaining the adjusted resource configuration are: receiving the real-time adjustment instruction, adjusting the starting frequency of the water pump and the illumination intensity of the light according to the real-time adjustment instruction, and obtaining the adjusted resource configuration; Record changes and synchronize updates to the central database to organize configuration records.

[0012] Preferably, the steps of obtaining the performance indicator results are: Based on the adjusted resource allocation, the resource efficiency index representing resource consumption and crop growth efficiency is calculated, and the formula is: ; in, represents the resource efficiency index, Represents the crop growth score, is the amount of water resources used, is the amount of lighting resources used, is the adjustment coefficient of crop demand; The resource efficiency indicators are compared with industry standards and past data, and resource utilization efficiency, growth rate and resource consumption rate are analyzed to generate performance indicator results.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by continuously collecting data such as soil moisture and meteorological conditions, real-time optimization of resource allocation is achieved. For the adjustment strategy, not only the irrigation and lighting plans are dynamically adjusted according to real-time environmental changes, but also deviations are quickly identified and corrected in the feedback mechanism, making resource application more accurate. The improvement of performance evaluation makes it possible to measure resource consumption and crop growth efficiency through numerical indicators, thereby providing data-driven decision support for agricultural production, ensuring the maximum efficiency and economy of resource utilization, and improving crop yield and quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0016] See also Figure 1 The present invention provides a technical solution: a wheat-corn annual light and temperature resource integrated management system comprising: The environmental monitoring module collects soil moisture and meteorological condition data, combines the growth data of wheat and corn, calculates the growth stage demand index, and obtains growth demand data; uses the growth demand data to optimize the sensor data collection frequency and accuracy, adjust soil and meteorological monitoring parameters, and generate comprehensive monitoring data; The resource allocation module calculates the current utilization efficiency of water resources and light resources based on comprehensive monitoring data to form a primary allocation result; it compares the primary allocation result with real-time environmental data to dynamically adjust irrigation and lighting plans to generate resource allocation results; The dynamic feedback module continuously monitors the deviation between crop growth and the expected target based on the resource allocation results, calculates the real-time adjustment requirements, and obtains real-time adjustment instructions; the real-time adjustment instructions are used to modify the resource input parameters in real time to generate the adjusted resource allocation; The performance evaluation module uses the output data of the adjusted resource configuration to evaluate resource consumption and crop growth efficiency, calculate the current performance indicators, and obtain performance indicator results.

[0017] The steps to obtain growth demand data are as follows: Collect data on the growth stages of wheat and corn, including growth cycle, root development and leaf area, as well as soil moisture, temperature and precipitation to obtain environmental and growth data sets; Based on the environment and growth data set, the growth requirement index of wheat and corn is calculated using the following formula: ; in, Represents soil moisture data, Represents meteorological data, Represents growth stage data, , and are the weight coefficients of soil moisture, meteorological conditions and growth stage data, is the total number of data items, GDI is the growth demand index; Based on the growth requirement index, the control strategy for each growth stage is determined, and the growth requirement data is formed in combination with meteorological conditions and soil moisture.

[0018] Specifically, in order to obtain the growth stage data of wheat and corn and collect soil moisture, temperature and precipitation, multiple monitoring points are selected from the designated planting area, and monitoring devices with temperature and humidity measurement functions are used to record the hourly soil moisture values ​​and ambient temperature. Daily precipitation data are obtained from the local meteorological department and compared with the precipitation information collected by the ground rain monitor. Professional equipment with root image analysis capabilities is used to monitor the degree of root development. At the same time, the leaf area size is measured and marked with corresponding timestamps during the different growth stages of crops. The growth cycle parameters are divided into sections according to the agronomic data manual, and the specific process is registered in weekly sequence from the initial budding to the jointing, heading and then to the maturity stage. The monitoring device and related sensors are synchronized at the same time, the above-mentioned recorded data are periodically collected and all monitoring results are uniformly arranged. The upper and lower thresholds of soil moisture are used to adjust the monitoring frequency in accordance with the historical soil dry-wet change patterns. When the monitored soil moisture value exceeds the set upper threshold, a complete repeated monitoring process is performed to ensure the accuracy of the record. The threshold setting method is defined based on the statistical results of the extreme peak values ​​of soil moisture content in the region based on many years of agricultural observation experience, while the upper temperature threshold is based on the local highest temperature statistics in the past ten years. The precipitation judgment standard comes from the comparison of precipitation data in several typical years to obtain the maximum daily precipitation and define the detection threshold accordingly. The root development degree is composed of the number of root images taken on the spot and the root length measurement results. The leaf area is obtained by multiplying the unfolded length and width of the leaf each time, and the area is approximately divided and determined for irregularly shaped areas. Finally, the contents of each monitoring are uniformly numbered and archived to obtain the environment and growth data set.

[0019] The benefit of the formula is that it obtains a more intuitive growth demand index based on the weighted combination of soil moisture, meteorological data and information at different growth stages, and enhances its adaptability to different crop growth cycles and environmental conditions in the process of integrating diverse parameters; Represents soil moisture data, which is recorded every hour by field monitoring devices and averaged at the end of the day to obtain specific values. It represents meteorological data, including daily average temperature and wind force classification, obtained from the local meteorological service center and corrected with on-site thermometer and anemometer records. It represents the growth stage data, which is quantified by the previously obtained indicators such as the root development degree and leaf area. The quantification method is to assign values ​​to various morphological indicators in different growth cycles and obtain a total score by comprehensive weighting. , and They are the weight coefficients of soil moisture, meteorological conditions and growth stage data, which are set according to the sensitivity analysis of field observation data. Specifically, the optimal ratio is calculated by combining multiple monitoring with regression analysis. is the total number of data items, obtained by periodic record accumulation; Calculation process: When the soil moisture data of the three monitoring days are , , When the humidity percentage is converted into a numerical form , , Meteorological data such as daily average temperature and wind speed are calculated by numerical superposition. , , , growth stage data are obtained by quantifying root and leaf area , , , weight coefficient , , The total number of data items obtained from multiple rounds of monitoring and testing and determined by regression testing , calculated according to the formula: ; ; ; ; ; ; The results show that the growth requirement index obtained by superimposing soil moisture, meteorological data and growth stage information within this range is 4.57. When the index value exceeds five, it means that the crop has a greater demand for external resources, while a value below three indicates a lower demand.

[0020] Based on the growth demand index obtained above, by correlating the index value with the agronomic intervals of different growth periods, the control strategies are determined according to the four stages of early stage, jointing, heading and maturity. The meteorological conditions of the specified area include information such as precipitation period and windy weather period. At the same time, the irrigation adjustment method and appropriate topdressing strategy for each growth stage are set in combination with the actual soil moisture measurement results. The execution process includes determining a critical point according to the monitored growth demand index value range and marking it in the data record of each growth period, matching this index with external meteorological forecast information, comparing the index difference of each stage day by day and recording the mapping of the soil moisture difference each time. When recording, the humidity values ​​of different stages are recorded based on the central control unit. A comparison is made with the historical data for the same period, and meteorological conditions that may affect root nutrient absorption are listed in separate items. Daily inspections are carried out to collect leaf status images through fixed cameras, and the leaf area indicators are marked at a unified time and then summarized and analyzed, so as to determine the specific pump-on time and interval in the irrigation plan before the control strategy is implemented, and make corresponding fine-tuning of the amount of topdressing. After comparing the water surplus and deficit fluctuation range of the region's annual meteorological data, the irrigation amount and the number of fertilizations are recorded one by one. When strong winds or extreme weather are monitored in the meteorological conditions, the index change range is reviewed again during the implementation of the strategy. If the index deviates significantly from the previously recorded historical average, the current control method is directly updated. Finally, all records are summarized and the corresponding growth demand data is obtained.

[0021] The steps for obtaining comprehensive monitoring data are as follows: According to the growth demand data, calculate the new data collection frequency, the calculation formula is: ; in, represents the new data collection frequency, Represents the maximum data acquisition frequency, is the growth demand index, and is the adjustment coefficient; Adjustments are made based on the new data collection frequency, and sensor settings are implemented to obtain comprehensive monitoring data.

[0022] Specifically, the formula is beneficial in that it determines the dynamic data collection frequency through multi-dimensional information such as the maximum data collection frequency, the current crop growth demand index, and the adjustment coefficient, reflecting the characteristics of flexible regulation of resource monitoring under variable hydrological and meteorological conditions; Indicates the maximum data collection frequency, and the specific value is obtained by observing the number of monitoring points and the range of monitoring time. is the growth demand index, and is the adjustment coefficient, By analyzing the environmental fluctuation range and experimental control data, numerical positioning is performed. It is obtained by curve fitting of multiple acquisition frequencies and actual effect differences; Calculation process: First select This value is obtained by analyzing the upper limit of monitoring frequency within 24 hours a day and comprehensively evaluating the performance of the equipment. , It is obtained based on the difference between field test data and different demand indexes. The frequency adjustment curve is generated by regressing the irrigation demand response. , and then calculate ,and , , and then get the fraction , followed by a power operation , and finally get ; The result shows that the current frequency of new data collection is about 1.48 times / hour. When the result continues to rise to more than 2 times / hour, it means that environmental monitoring requires more intensive sensor observations, while a value below 1 indicates that the monitoring interval can be appropriately extended.

[0023] Based on the new data collection frequency obtained above, the staff sets the collection time interval in the central control unit and associates it with the startup sequence of specific monitoring points. First, the unique identification and network topology of each sensor are entered in the management interface. Then, a specific polling plan is formulated based on the collection time and power statistics of all nodes. The appropriate communication interface is selected to ensure that the collection process is in a continuous operation state. The wind speed, temperature, soil moisture and other elements in the monitoring content are recorded in the specified order and timestamped each time the polling is performed. The original result data obtained during the collection period is accumulated and sorted daily, and the numerical content that exceeds the predetermined threshold is checked. The corresponding period information in the meteorological sample data for many years is compared to determine whether it is necessary to conduct a polling within the threshold range. The data are updated and expanded. When the monitoring value exceeds the respective preset threshold, an additional collection action is added and the newly added collection record is compared with the previous data. The threshold value is obtained based on the statistical sensitivity of crops to moisture and temperature and is refined and adjusted through the data summary of similar planting conditions in adjacent areas. When the wind speed exceeds the local annual maximum wind speed standard, the wind speed rapid reporting channel is activated and the wind speed measurement process is repeated. The upper limit of the wind speed value comes from the actual observation results of extreme instantaneous wind force in many agricultural disasters in recent years. At this time, all sensor states are retrieved through the connection method and the results of repeated measurements are formed into a side-by-side table with specific time points marked. After completing the periodic monitoring of various elements and data archiving, comprehensive monitoring data is obtained.

[0024] The steps to obtain the primary configuration results are: Extract water resources and light data from comprehensive monitoring data, including real-time irrigation water volume, cumulative rainfall, total sunshine hours and average cloud cover, to obtain water resources and light data sets; Based on the water resources and light data sets, the utilization efficiency of water resources and light resources is calculated using the following formula: and ; in, and Represent the utilization efficiency of water resources and light resources respectively, represents the total amount of water used, represents the evaporation rate, is the water resources regulation coefficient, represents the direct sunlight, represents the average cloud coverage, is the light resource adjustment coefficient; The primary configuration results are formed based on the efficiency of the use of water resources and light resources.

[0025] Specifically, based on the comprehensive monitoring data obtained above, the real-time irrigation water volume, cumulative rainfall, total sunshine hours and average cloud coverage involved are split and screened. First, the irrigation water volume readings output by the equipment at each monitoring point are read on the management end, and these readings are arranged in hourly sequence and accumulated to form the corresponding real-time irrigation water volume values. The hourly rainfall is then read in segments from the automatic rain gauge and combined with the historical monthly rainfall data to verify the accuracy of the cumulative rainfall. Subsequently, the start and end time of the sunshine on that day are recorded from the sunshine monitoring instrument. By continuously tracking the sunshine intensity within each monitoring period, the corresponding total sunshine hours are converted. In order to ensure the integrity of the reading process, the comparison data of the local meteorological department is also called. The information is numerically checked. In addition, the cloud coverage is tracked continuously around the clock in combination with the multi-point cloud map observation device. The average cloud coverage is quantified by counting the pixels of the cloud distribution image observed in each time period and calculating the cumulative cloud occlusion rate. The resolution of the cloud distribution image comes from the unified capture process of multiple surveillance cameras and is aligned according to the local geographic coordinates. All the obtained values ​​are horizontally compared on the management side according to the corresponding time period index to ensure the consistency between the previous and next time periods. Then the four types of data, namely real-time irrigation water volume, cumulative rainfall, total sunshine hours and average cloud coverage, are merged into a collection for subsequent analysis, and finally the water resources and light data set is obtained.

[0026] The benefit of the formula is that it integrates various influencing factors of water resources and light resources through quantitative processing of factors such as evaporation, direct sunlight and cloud coverage, thus providing a clear numerical basis for subsequent primary configuration results; It represents the total amount of water used, which is obtained by counting the actual water use data output by irrigation equipment at different time periods. It represents the evaporation amount, which is determined by the surface water evaporation calculation model through the monitoring data of ambient temperature, wind speed and air pressure obtained above. is the water resource regulation coefficient, which is obtained by combining field experiments and seasonal precipitation characteristics to correct the evaporation difference. Represents direct sunlight, which can be obtained by cross-calculating the total solar radiation and the local sunshine hours. Represents the average cloud coverage, which is calculated through cloud map observations. is the light resource adjustment coefficient, which is obtained by summarizing the relationship between different cloud thicknesses and sunlight intensity; Calculation process: First, use the device statistics to Tons, this value comes from the cumulative results of multiple sets of irrigation pump water output sensors. Millimeters are calculated from surface evaporation. It is determined by the difference distribution of local irrigation evaporation and rainfall recharge data for three consecutive years. Kilojoules / square meter comes from the conversion of total solar radiation and hours. It is calculated by averaging the cloud coverage rate throughout the day. It is obtained through the cloud shading comparison test method; First calculate : ; ; ; Then calculate : ; ; ; The results show that About 29.38 and is about 106.67, when When it exceeds 30, it means that the water resource utilization rate has reached a relatively high level. If it is above 100, it indicates that the lighting resources are also maintaining good performance.

[0027] According to the water resource utilization efficiency and light resource utilization efficiency obtained in the previous step, these two values ​​are managed in sections and cross-indexed with different resource utilization levels in the agricultural experiment records. First, read the resource utilization level range listed in the agricultural experiment records, and write the corresponding utilization efficiency value in the control item. Then check the statistical results of the difference between evaporation and direct light intensity, and compare the change curves of water and light conditions in the same period of previous years. If the utilization efficiency deviates significantly from the established range, recheck whether there is a measurement deviation in the total water consumption or sunshine intensity data obtained in the previous stage, and then retrieve the time point of abnormal fluctuation from the recorded cloud coverage sequence and list the impact of this time point on the water pump start and stop plan and crop light demand parameters. After checking these abnormal values, confirm the level of the final utilization efficiency range, organize it into a configuration reference index and classify it into the primary configuration result.

[0028] The steps to obtain resource configuration results are: Analyze the primary allocation results, evaluate the matching degree with the current season, crop growth cycle and soil type, and determine the preliminary resource allocation plan; According to the preliminary resource allocation plan, soil moisture, temperature, wind speed and rainfall probability are monitored, and the primary configuration results are compared to identify the parameters that need to be adjusted, plan the start-up frequency of the water pump and the intensity of the light, and obtain adjustment suggestions; Based on the adjustment suggestions, change the running time of the water pump, adjust the light intensity and duration, and get the resource allocation results.

[0029] Specifically, after obtaining the primary configuration results, by consulting the information including the current season information, crop growth cycle data and soil type parameters, the field environment and planting conditions recorded therein are subdivided and compared. First, the key temperature reference value is extracted from the monthly average temperature and the day and night temperature difference range of the current season, and the temperature reference value is associated with the crop growth cycle process summarized above. Then, the nutrient transmission capacity and water retention capacity corresponding to the soil type are queried in the internal database, and these retrieved reference values ​​are compared item by item with the water supply ratio and light utilization efficiency in the primary configuration results. Then, when calling the soil particle structure analysis data, the soil porosity and drainage rate records are combined to confirm whether there is a large risk of soil leakage or water accumulation, and the corresponding soil type is queried in the historical experiments. The best irrigation interval and the best light interval recorded are divided into several ranges for detailed comparison to determine the specific water-fertilizer matching required for the crop growth cycle. Then, the difference items of irrigation demand are listed one by one according to the coupling of temperature reference value and soil type, and the conventional interval and ultra-high temperature interval are distinguished. If the temperature data of a certain period is monitored to be greater than the tolerable upper limit, the period is marked as requiring additional verification of water source scheduling and checking for abnormal wind speed. The light utilization efficiency obtained previously is compared to confirm whether the period is in a period of strong sunlight or excessive cloud cover. During the process, the difference items obtained by the verification are stored one by one in a temporary list, and cross-checked with the growth cycle nutrient requirement items in the planting manual. After analyzing all the items, a preliminary resource allocation plan covering irrigation, fertilization and light management recommendations is compiled.

[0030] On the basis of the preliminary resource allocation plan obtained above, the recent hourly averages recorded by the soil moisture monitoring equipment are first organized into an array, and the array is compared with the daily maximum and minimum temperatures output by the temperature sensor. The wind speed index is then called from the wind speed measurement component, and these wind speed values ​​are accumulated daily to see if they are higher than the annual extreme levels in the region. Then, combined with the rainfall probability data released by the local meteorological station, they are searched one by one with the irrigation water supply periods listed in the preliminary resource allocation plan. If a large water supply has been set during a period with a high probability of rainfall, this situation will be marked in the record for subsequent review of the impact on soil moisture. Then, the preliminary plan is compared with the previous plan. The water and light utilization information in the configuration results is used to extract the interval division of irrigation amount and light intensity, and the monitoring results of soil moisture and temperature are mapped to these intervals. The starting frequency of the water pump is corrected according to the evaporation change that may be caused by wind speed, and the impact of rainfall probability on irrigation amount is compared to identify the opening and closing time of the water pump that needs fine-tuning. Then, a list of light requirements is made according to the cloud distribution and sunshine conditions in each time period. The list of requirements is checked with the current data to see if there is any excessive lighting. If it is found that the light intensity exceeds the threshold, the adjustment amount is re-planned, and these correction opinions are verified with the data of various sensors to obtain the final adjustment suggestions.

[0031] After referring to the adjustment suggestions obtained above, first read the expected operation time period and unit water output of the current water pump in the water pump control terminal, compare this information with the recommended operation time in the adjustment suggestion, and if there is a situation that obviously exceeds the upper limit of the local water resource allocation, shorten the period, and record the modified start-stop table in the system in hourly order. Then, update the light intensity level range set in the suggestion at the light control end, increase the light intensity moderately in the period of relatively weak sunshine, and reduce the power output of the artificial lighting module for the period of relatively strong sunshine. Then summarize and compare the total illumination time to see whether the modified illumination time matches the crop growth cycle parameters. If the crop growth cycle has not yet reached the heading stage but the illumination period has exceeded the preset range, fine-tune it by allocating the exceeded illumination period to the subsequent insufficient sunshine period. By rearranging the period by period and synchronizing the soil moisture conditions, a set of feasible configuration lists are completed, and then all update results are generated and recorded in the management interface according to the established timing rules, and finally the resource allocation results are obtained.

[0032] The steps for obtaining real-time adjustment instructions are as follows: Based on the resource allocation results, the plant height and chlorophyll content of crops are collected to obtain real-time crop growth data; Based on real-time crop growth data, compare the deviation from the set growth target, analyze the difference between plant height and expected height and whether the chlorophyll content meets the standard, classify the causes of deviation, and obtain the growth deviation analysis results; Based on the growth deviation analysis results, the required irrigation and lighting adjustments are determined and real-time adjustment instructions are obtained.

[0033] Specifically, based on the resource allocation results, combined with the crop planting distribution information in the designated area, the sampling schedule of multiple monitoring points is compared with the previously configured irrigation and lighting schemes. In the plant height detection link, a measuring rod or a ruler with a scale is used to measure and record the height of the plant stems one by one. In view of possible measurement deviations, multiple measurements are repeated in the same period and the average value is used as the final record. A small collection device that can clamp leaf samples is deployed in the field and the location of the crop is marked simultaneously. Then, a chlorophyll detector with spectral analysis function is used to perform colorimetric processing on the collected leaves, extract the reflection characteristic values ​​of specific bands, and use the correspondence between chlorophyll content and reflected light intensity to quantitatively measure the pigment concentration of each leaf. During the detection process, the sampling multiple can be appropriately increased for field sections prone to leaf diseases and insect pests. If the chlorophyll concentration is found to exceed the historical extreme value, check whether the monitoring device has a fault and compare it with the surrounding normal sections. In the process, all measured heights and chlorophyll values ​​are sorted into the same data set and horizontally corresponded with the crop growth cycle records. After sorting, real-time crop growth data is obtained.

[0034] After obtaining real-time crop growth data, the plant height and chlorophyll content of each crop are compared with the set growth target values. The actual measurement results of the plant height are first reviewed one by one according to the field number, and the expected height range provided in the agricultural standard is called for difference judgment. If the actual height is lower than the range, it is regarded as a certain degree of growth lag. Then, it is checked against the previously recorded chlorophyll content threshold interval to see if it is higher than the minimum standard. The minimum standard here comes from the clustering division method of multiple leaf photosynthesis efficiency measurement results. If the local crop chlorophyll value is detected to be lower than the threshold, the cause analysis program is entered to check the overlap between soil moisture and fertilization period and check whether extreme temperature or light shortage occurs during the period. By summarizing the substandard plants into the difference list, the causes of deviation are classified and labeled, such as water loss, nutrient deficiency or light time deviation, and targeted supporting information is listed, such as the corresponding field number, abnormal wind speed record, and high temperature period length. After completing the classification and identification of all deviation causes and associating them with other data, the growth deviation analysis results are obtained.

[0035] Referring to the various reasons listed in the growth deviation analysis results, the previously configured irrigation and lighting data are retrieved item by item. In areas with insufficient water, the water pump start and stop schedule is detected, and the amount of water supply for each increase is selected according to the correspondence between the schedule and the high temperature period. If the increase is above the water resource allocation limit in the region, it is allocated to the adjacent period for supplementation. For sections with insufficient or excessive light, adjustments are made according to the power setting range of the artificial supplementary lighting equipment. In the list of illumination intensity in the deviation analysis results, it is checked item by item whether there are time periods whose intensity or duration has far exceeded the aforementioned threshold, which is obtained by comparing the photosynthesis saturation of the leaves with the actual light intensity. Subsequently, the operating gear of the lighting equipment is updated in the system and the lighting schedule is rearranged to ensure that the supplementary lighting power is appropriately lowered during the high temperature period and the lighting time is extended as appropriate during the low temperature period. After confirming that all modifications are consistent with the crop growth cycle, the updated operating instructions are formed into a unified command set to ultimately obtain real-time adjustment instructions.

[0036] The steps to obtain the adjusted resource configuration are: Receive real-time adjustment instructions, adjust the starting frequency of the water pump and the illumination intensity of the light according to the real-time adjustment instructions, and obtain the adjusted resource configuration; Record changes and synchronize them to the central database to organize configuration records.

[0037] Specifically, after receiving the real-time adjustment instruction, first read the starting frequency control parameters of the water pump from the executable instruction and list the upper and lower limits of the frequency for each time period in turn, compare these time periods with the soil moisture and meteorological change information summarized in the previous step, and check the specific value of the frequency adjustment with the mechanical load range of the water pump itself. If it is found that the set upper limit is exceeded, the frequency of the time period is lowered with reference to the field observation data. The upper limit is mainly formed according to the statistical results of the highest irrigation peak value and the water output capacity of the equipment in the region over the years. At the same time, if the frequency is lower than a certain reference interval, it is marked that the water supply may be insufficient in the time period. By comparing the soil dryness and humidity in different time periods with the growth status of the plants, it is determined whether to further fine-tune the frequency, and then adjust the frequency under the light. The control end reads the light intensity adjustment command, combines the previously recorded light strategy and crop growth cycle information, and checks the time periods that require adjustment with the actual total sunshine to see if these time periods overlap with high temperature or strong wind weather. If overlap occurs, find a suitable output range from the power coefficient of the lighting device, and limit the power value to a value that will not damage the crops. This value is obtained by testing the crop leaf temperature and light exposure data for multiple times. Then, check whether the light duration needs to be extended in the low temperature section, and adjust multiple lamps in conjunction on the same interface to avoid local overbrightness or darkness. During the process, the results of each device adjustment are recorded in the adjustment process record and confirmed to be normal for the change data in each time period, and finally the adjusted resource configuration is obtained.

[0038] After updating the parameters of the water pump starting frequency and light intensity, all changes are summarized item by item in the change registration module of the management end and the corresponding execution order is marked. The differences between the new and old parameters are listed by comparing the irrigation configuration and lighting configuration recorded in the previous stage, such as the specific values ​​of increased water flow or reduced fill light power, and then the connection information of the central database is loaded in the same management end. The revised configuration data is stamped with the current timestamp and classified and allocated according to the area number. When the value exceeds the safety range of the equipment or is lower than the established minimum level, it is also marked. The minimum level is mainly obtained by combining local planting experiments with equipment maintenance documents. After confirming that all values ​​are within the established range, the database update process is executed. Once the operation is completed, the change entries are formed in the central database. Then these entries are briefly screened to verify the differences between the new and old records and eliminate conflicting information. Then, the configuration pages of each area in the database are refreshed, and the previously obtained crop growth data and environmental monitoring data are associated to complete the sorting of configuration records and obtain the final synchronized configuration records.

[0039] The steps to obtain the performance indicator results are: Based on the adjusted resource allocation, the resource efficiency index representing resource consumption and crop growth efficiency is calculated as follows: ; in, represents the resource efficiency index, Represents the crop growth score, is the amount of water resources used, is the amount of lighting resources used, is the adjustment coefficient of crop demand; Compare resource efficiency indicators with industry standards and past data, analyze resource utilization efficiency, growth rate and resource consumption rate, and generate performance indicator results.

[0040] Specifically, the formula is useful in that it forms a quantifiable resource efficiency index based on the crop growth score, water and light resource usage, and crop demand adjustment coefficients obtained in the adjusted resource allocation stage; Indicates the crop growth score, which is recorded after comprehensive quantification of factors such as plant height, chlorophyll content, and growth stage adaptability obtained above. Specifically, different growth indicators are assigned values ​​and weighted and summarized to form a total score. is the amount of water used, accumulated from enabled irrigation logs and pump output monitor readings, The amount of light resource usage is calculated and accumulated by combining the power of the plant supplementary light and the actual light duration read by the sunlight monitor. It is the adjustment coefficient of crop demand, which is obtained through the comparison method of field experiments and multiple rounds of measurement of the crop's own sensitivity to water, fertilizer and light; Calculation process: First, assign specific values ​​to each parameter, and the crop growth score obtained above This value is formed by comprehensive evaluation of multiple indicators obtained from monitoring plant morphology and nutritional status. Tons is calculated by accumulating the irrigation water output in each period, and the amount of light resources used The equivalent unit is obtained by combining the artificial light power with the actual sunshine duration, and the crop demand adjustment coefficient After analyzing the response of crops to water and light through multiple experiments, the formula is first Prescription: ; Then Take the natural logarithm: ; Add the two together: ; right Perform a 1.2 power operation: ; Calculate the fraction: ; Then multiply by : ; Finally, we can get: ; The results show that the resource efficiency index is approximately 0.0016588. When the value is greater than 0.002, it means that the water and light resources are more closely matched with crop needs. If the value is too low, it means that there is still a need for optimization in water, fertilizer or light.

[0041] After completing the calculation of the resource efficiency index, first compare the index with the corresponding value range listed in the industry standard archive, and search for the corresponding past time period records in the agricultural experimental literature, extract various water and light values ​​from the recorded planting season, irrigation intensity and light supply cycle, and list them together with the currently calculated resource efficiency index in the statistical table. By comparing the values ​​of different indicators, it is judged whether there is any abnormality in resource utilization, and then call the existing reference curve from aspects such as growth rate and resource consumption rate, and compare the growth amplitude of plants in the current cycle with the average value of previous years in the corresponding stage. If it is found that it obviously exceeds the predetermined standard or lags behind significantly, this phenomenon will be marked in the statistical table, and check whether there is any deviation between the water pump start and stop plan and the lighting arrangement obtained previously. By checking the degree of deviation and the tolerance range of crops, it is determined whether it is necessary to review the actual data readings and the consistency with the industry standards in the subsequent irrigation or supplementary lighting links. Finally, a data list that summarizes the performance indicators is formed in the management interface and the performance indicator results are obtained.

Claims

1. A wheat-corn annual light and temperature resource integrated management system, characterized in that: The system comprises: The environmental monitoring module collects soil moisture and meteorological condition data, combines the growth data of wheat and corn, calculates the growth stage demand index, and obtains growth demand data; uses the growth demand data to optimize the sensor data collection frequency and accuracy, adjust soil and meteorological monitoring parameters, and generate comprehensive monitoring data; The resource allocation module calculates the utilization efficiency of current water resources and light resources based on the comprehensive monitoring data to form a primary allocation result; dynamically adjusts the irrigation and light plans by comparing the primary allocation result with the real-time environmental data to generate a resource allocation result; A dynamic feedback module continuously monitors the deviation between crop growth and the expected target according to the resource allocation result, calculates the real-time adjustment demand, and obtains the real-time adjustment instruction; applies the real-time adjustment instruction to modify the resource input parameters in real time, and generates the adjusted resource allocation; The performance evaluation module uses the output data of the adjusted resource configuration to evaluate resource consumption and crop growth efficiency, calculate the current performance indicators, and obtain performance indicator results.

2. The wheat-corn annual light and temperature resource integrated management system according to claim 1, characterized in that: The steps for obtaining the growth demand data are as follows: Collect data on the growth stages of wheat and corn, including growth cycle, root development and leaf area, as well as soil moisture, temperature and precipitation to obtain environmental and growth data sets; Based on the environment and growth data set, the growth requirement index of wheat and corn is calculated using the following formula: ; in, Represents soil moisture data, Represents meteorological data, Represents growth stage data, , and are the weight coefficients of soil moisture, meteorological conditions and growth stage data, is the total number of data items, GDI is the growth demand index; Based on the growth demand index, the control strategy for each growth stage is determined, and the growth demand data is formed in combination with meteorological conditions and soil moisture.

3. The wheat-corn annual light and temperature resource integrated management system according to claim 1, characterized in that: The steps for obtaining the comprehensive monitoring data are as follows: According to the growth demand data, the new data collection frequency is calculated using the following formula: ; in, represents the new data collection frequency, Represents the maximum data acquisition frequency, is the growth demand index, and is the adjustment coefficient; Adjustments are made based on the new data collection frequency, sensor settings are implemented, and comprehensive monitoring data is obtained.

4. The wheat-corn annual light and temperature resource integrated management system according to claim 1, characterized in that: The steps for obtaining the primary configuration result are: Extracting water resources and light data from the comprehensive monitoring data, including real-time irrigation water volume, cumulative rainfall, total sunshine hours and average cloud coverage, to obtain a water resources and light data set; Based on the water resources and light data set, the utilization efficiency of water resources and light resources is calculated, and the calculation formula is: and ; in, and Represent the utilization efficiency of water resources and light resources respectively, represents the total amount of water used, represents the evaporation rate, is the water resources regulation coefficient, represents the direct sunlight, represents the average cloud coverage, is the light resource adjustment coefficient; The primary configuration results are formed based on the efficiency of the use of water resources and light resources.

5. The wheat-corn annual light and temperature resource integrated management system according to claim 1, characterized in that: The steps for obtaining the resource configuration result are: Analyze the preliminary allocation results, evaluate the matching degree with the current season, crop growth cycle and soil type, and determine the preliminary resource allocation plan; According to the preliminary resource allocation plan, soil moisture, temperature, wind speed and rainfall probability are monitored, and compared with the preliminary allocation results, the parameters that need to be adjusted are identified, the starting frequency of the water pump and the illumination intensity of the light are planned, and adjustment suggestions are obtained; Based on the adjustment suggestions, the running time of the water pump is changed, the light intensity and duration are adjusted, and the resource allocation result is obtained.

6. The wheat-corn annual light and temperature resource integrated management system according to claim 1, characterized in that: The steps of obtaining the real-time adjustment instruction are as follows: Based on the resource allocation result, the plant height and chlorophyll content of the crop are collected to obtain real-time crop growth data; Based on the real-time crop growth data, the deviation between the plant height and the set growth target is compared, the difference between the plant height and the expected height and whether the chlorophyll content meets the standard are analyzed, the causes of the deviation are classified, and the growth deviation analysis results are obtained; According to the growth deviation analysis results, the required irrigation and lighting adjustment amounts are determined, and real-time adjustment instructions are obtained.

7. The wheat-corn annual light and temperature resource integrated management system according to claim 1, characterized in that: The steps for obtaining the adjusted resource configuration are: receiving the real-time adjustment instruction, adjusting the starting frequency of the water pump and the illumination intensity of the light according to the real-time adjustment instruction, and obtaining the adjusted resource configuration; Record changes and synchronize them to the central database to organize configuration records.

8. The wheat-corn annual light and temperature resource integrated management system according to claim 1, characterized in that: The steps for obtaining the performance indicator results are as follows: Based on the adjusted resource allocation, the resource efficiency index representing resource consumption and crop growth efficiency is calculated, and the formula is: ; in, represents the resource efficiency index, Represents the crop growth score, is the amount of water resources used, is the amount of lighting resources used, is the adjustment coefficient of crop demand; The resource efficiency indicators are compared with industry standards and past data, and resource utilization efficiency, growth rate and resource consumption rate are analyzed to generate performance indicator results.

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