CN117223459B - Automatic fertilizer mixing system based on data analysis - Google Patents
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Abstract
The invention belongs to the technical field of automatic fertilizer mixing, and particularly discloses an automatic fertilizer mixing system based on data analysis, which comprises the following components: the actual growth stage of the crops is analyzed by monitoring the current growth health state of the crops, and the basic demand content of various fertilizer components of the crops in the designated monitoring area in the next planting time stage is evaluated, so that the fertilizer allocation error caused by the actual growth state deviation is avoided. The compensation content of various fertilizer components is evaluated by analyzing the change condition of the missing content of various elements in the soil so as to ensure the blending relation of the content of various elements in the soil and the fertilizer components, obtain the weather condition of the future time period, predict the fertilizer nutrient availability factor of the future time period and avoid the influence of weather on the nutrient absorption and utilization efficiency. The multi-dimensional data is combined to comprehensively analyze the required content of the fertilizer, so that the fertilizer is scientifically and reasonably managed, and the accuracy of fertilizer allocation is ensured.
Description
Technical Field
The invention belongs to the technical field of automatic fertilizer mixing and relates to an automatic fertilizer mixing and mixing system based on data analysis.
Background
The fertilizer is one of important input products in agricultural production, the nutrient requirements of crops in different growth stages are different, excessive fertilization not only can cause nutrient waste, but also can cause pollution to soil and environment, and reasonable fertilizer proportion can ensure that crops can obtain proper nutrient supply, help the crops to grow and develop normally, increase the yield and quality, and simultaneously can effectively control the fertilization cost so as to reduce the economic burden of farmers. Therefore, the invention of the automatic fertilizer mixing technology has important significance and value for promoting sustainable agricultural development and improving agricultural production benefits.
The existing fertilizer proportioning mode has some defects, and mainly comprises the following aspects: 1. the common fertilizer proportioning mode is to preset fixed ingredient proportions for fixed throwing, the difference of the nutrition demands of crops in different growth stages is not considered, flexible adjustment cannot be carried out according to the actual growth conditions of the crops, the application of the fertilizer is not accurate enough, the actual needs of the crops cannot be met, and excessive or too little waste of the fertilizer can be caused.
2. The common fertilizer proportioning mode is mainly calculated based on the total amount of the fertilizer, the influence of the content change condition of uncombined soil elements and weather on the nutrient absorption and utilization effect is not combined, and the analysis data is lack of diversification, so that the result of calculating the fertilizer proportioning has larger errors, the plant nutrition imbalance and the low fertilizer utilization rate are caused, and the quality of crops is also reduced.
Disclosure of Invention
In view of this, in order to solve the problems set forth in the background art, an automatic fertilizer mixing system based on data analysis is now proposed.
The aim of the invention can be achieved by the following technical scheme: the invention provides an automatic fertilizer mixing system based on data analysis, which comprises: the growth image acquisition module is used for monitoring the crop growth image in the appointed monitoring area in real time, and carrying out individual positioning interception on the current crop growth image to obtain each plant individual image of the current crop growth image.
And the crop monitoring module is used for identifying the types of the individual images of each plant, wherein the types comprise weeds and plants, and further analyzing the current crop growth health index.
The growth prediction module is used for obtaining the current actual growth stage of the crops and predicting the predicted growth health index of the next planting time stageFurther, the basic demand content of various fertilizer components of crops in the next planting time stage is evaluated.
The soil element monitoring module is used for acquiring the content of various elements in the soil and analyzing the missing content of various elements in the soil.
The fertilizer component proportioning module is used for acquiring weather information of a future time period, evaluating fertilizer nutrient availability coefficients of the future time period, and further determining the demand content of various fertilizer components by combining the analyzed multidimensional data.
The information statistics library is used for storing standard images of crops at various planting time stages, specified growth health indexes, conventional contents of various fertilizer components and standard contents of various soil elements, and storing various abnormal leaf shape images of plants.
Illustratively, the means for analyzing the current crop growth health index is: obtaining the planting time of crops, screening according to the planting time corresponding to the set various planting time stages of the crops to obtain the current planting time stage of the crops, extracting a standard image of the crops in the current planting time stage from an information statistics library, comparing the standard image with the current growth image of the crops to obtain the leaf growth deviation coefficient of the cropsAnd branch growth deviation coefficient->。
Analysis of crop growth health indexWherein->The set coefficient duty ratios corresponding to the blade growth deviation and the branch growth deviation are respectively shown.
Illustratively, the crop leaf growth deviation coefficient is calculated by: and summarizing each plant individual image from each plant individual image, identifying each plant individual leaf, obtaining each plant individual leaf abnormal shape value, and comparing the leaf abnormal shape value with a preset abnormal shape allowable value.
If the abnormal leaf shape value of a plant species individual exceeds the preset abnormal shape allowable value, marking the plant species individual, otherwise, obtaining the leaf color difference value of the plant species individual to obtain the number of the marked plant species individualsAnd leaf color difference value of individual plant species +.>，/>Representing plant species individual number,/->。
Calculating the leaf growth deviation coefficient of cropsWherein->Representing the total number of individuals of the plant->Representing a preset normal difference value of the color of the blade.
Illustratively, the branch growth deviation coefficient is calculated by: the normal branch size value of the plant species individual in the current planting time stage is identified from the standard image of the crop in the current planting time stageAnd obtaining the normal growth concentration of plants in the current planting time stage>。
Obtaining the current growth density of crops based on the interception position of each plant variety individual imageAnd the growth height and branch diameter of each plant species are obtained and respectively marked as +.>。
Calculating the branch growth deviation coefficient of cropsWherein->Representing the corresponding set deviation threshold value of branch size, < ->Setting compensation factors representing the growth deviation coefficients of the branches, < >>Is the circumference ratio.
Illustratively, the predicting the predicted growth health index for the next planting time period comprises the following specific steps: according to the current planting time stage of crops, screening the appointed growth health indexes of the current planting time stage and the next planting time stage from an information statistical library, and comparing the appointed growth health index of the current planting time stage with the current crop growth health index to obtain the current growth health deviation rate of the cropsPredicted growth health index +.>，/>A specified growth health index representing the next planting time period.
Illustratively, the evaluating the basic demand content of various fertilizer components of the crop at the next planting time period includes: the underground part of the appointed monitoring area is detected by utilizing underground organ detection equipment, the root system distribution depth and distribution density of crops are displayed, and the current actual growth stage of the crops is confirmed by combining the current crop growth health index.
Extracting conventional content of various fertilizer components in the next planting time stage corresponding to the current actual growth stage of crops from an information statistics libraryG represents the fertilizer ingredient type number, ++>。
The specified growth health index of the crops in the next planting time stage is added with the set growth deviation index and then is subjected to difference with the expected growth health index in the next planting time stage to obtain a crop growth difference value, and if the crop growth difference value is greater than or equal to 0, the crop growth difference value is calculated byAs a fertilizer ingredient expansion coefficient, < > for>Indicating the setting of the growth bias index.
If the crop growth difference value is less than 0, thenAs a fertilizer component reduction factor, obtaining the basic demand content of various fertilizer components of crops in the next planting time stage>，/>Adjusting coefficient representing the content of fertilizer ingredients, +.>E represents a natural constant.
Illustratively, the analysisThe corresponding analysis steps of the missing content of various elements in the soil are as follows: acquiring standard contents of various soil elements in a specified monitoring area in a current planting time period, detecting the contents of the soil elements in the specified monitoring area in real time, acquiring detected contents of various elements in soil at various time points in a set time period, subtracting the detected contents of corresponding elements in the soil at various time points in the set time period from the standard contents of the various soil elements in the specified monitoring area in the current planting time period, and obtaining differential contents of various elements in the soil at various time points in the set time periodK represents the soil element species number, +.>R represents a time point number, < >>。
Respectively carrying out average value calculation and summation calculation on the difference contents of various elements in the soil at each time point in a set time period to obtain the average value of the difference contents of various elements in the soil in the set time periodSum of difference content->。
Extracting the maximum difference content and the minimum difference content of various elements in the soil in a set time period from the difference content of various elements in the soil in various time points in the set time period, and recording as。
From analytical formulasObtaining the deletion content of various elements in the soil, wherein->Indicating the set allowable value of differential content, +.>The set difference content deviation value is indicated to correspond to the influence weight.
Illustratively, the assessment of fertilizer nutrient availability coefficients for a future time period is by: l1, extracting weather information in a future time period from a local weather forecast platform, and acquiring rainfall of each day in the future time period if rainfall weather exists in the future time periodJ represents the number of days in the future period, < +.>Further calculating the fertilizer nutrient availability factor for the future time period +.>In (1) the->Represents a set integrated rainfall threshold, +.>Indicating that the total rainfall value in the future period of time does not exceed the set integrated rainfall threshold,/>Indicating that the total rainfall exceeds the set integrated rainfall threshold value in the future time period, +.>Respectively indicate->、/>In this case, the deviation correction coefficient is set correspondingly.
L2、If weather exceeding the set proper illumination intensity exists in the future time period, acquiring the illumination intensity of each day exceeding the set proper illumination intensity in the future time period, and recording as，/>Number of days indicating more than the set appropriate illumination intensity, +.>Further calculating the fertilizer nutrient availability coefficient in the future time period，/>Indicating that the proper illumination intensity is set>Representing the number of days of extraction corresponding to the future time period, +.>And (5) representing the set evaluation factors corresponding to the fertilizer nutrient availability coefficients.
L3, if neither rainfall weather nor weather exceeding the set proper illumination intensity exists in the future time period, recording the fertilizer nutrient availability coefficient of the future time period as the set valueFurther evaluating the fertilizer nutrient availability factor for future time period +.>，/>Wherein->Respectively indicate rainfall weather and exceeding the set suitabilityThe set influence corresponding to the weather suitable for illumination intensity is given by the weight ratio +.>Indicating the presence of raining weather or weather exceeding a set suitable illumination intensity in the future time period, < >>Indicating that neither rainfall weather nor weather exceeding the set suitable illumination intensity is present for the future period of time.
Illustratively, the multidimensional data includes various fertilizer component basal demand levels of crops at a next planting time period, various element deficiency levels in soil, and fertilizer nutrient availability coefficients for a future time period.
Illustratively, the corresponding method for determining the required content of each fertilizer component is as follows: acquiring soil elements corresponding to various fertilizer components, setting fertilizer component compensation contents corresponding to unit deletion contents of various elements in the soil according to a preset principle, converting the deletion contents of various elements in the soil into corresponding fertilizer component compensation contents by using a multiplication formula, and summing to obtain comprehensive compensation contents of various fertilizer components。
From the evaluation formulaThe desired content of each fertilizer component is determined.
Compared with the prior art, the invention has the following beneficial effects: (1) According to the invention, the actual growth stage of the crops is analyzed by monitoring the current growth health state of the crops, so that the basic demand content of various fertilizer components of the crops in the designated monitoring area in the next planting time stage is evaluated, a determination basis is provided for the proportioning content of various follow-up fertilizer components, the fertilizing amount is more accurate, and the situation of fertilizer proportioning error caused by the deviation of the actual growth state is avoided, thereby improving the fertilizing effect.
(2) According to the invention, the compensation content of various fertilizer components is evaluated by analyzing the change condition of the missing content of various elements in the soil so as to ensure the blending relation of the various element contents in the soil and the fertilizer components, and meanwhile, the weather change condition of the future time period is combined to predict the fertilizer nutrient availability factor of the future time period, so that the influence of weather on the nutrient absorption and utilization efficiency is avoided, and the blending benefit of the fertilizer is improved to the greatest extent.
(3) The method combines multidimensional data to comprehensively analyze the fertilizer demand content, is beneficial to scientifically and reasonably carrying out fertilization management, improves the benefit and the sustainability of agricultural production, can avoid the situation of excessive fertilization or insufficient nutrition, ensures the accuracy of fertilizer proportioning, and further improves the yield and the quality of crops.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the system module connection of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides an automatic fertilizer mixing system based on data analysis, which includes: the system comprises a growth image acquisition module, a crop monitoring module, a growth prediction module, a soil element monitoring module, a fertilizer component proportioning module and an information statistics library. The growth image acquisition module is connected with the crop monitoring module, the crop monitoring module is connected with the growth prediction module, the fertilizer component proportioning module is respectively connected with the growth prediction module and the soil element monitoring module, and the information statistics library is respectively connected with the crop monitoring module and the growth prediction module.
The growth image acquisition module is used for monitoring the crop growth image in the appointed monitoring area in real time, and carrying out individual positioning interception on the current crop growth image to obtain each plant individual image of the current crop growth image.
The crop monitoring module is used for identifying the types of individual images of each plant, wherein the types comprise weeds and plants, and further analyzing the current crop growth health index.
In a specific embodiment of the present invention, the method for analyzing the current crop growth health index is as follows: obtaining the planting time of crops, screening according to the planting time corresponding to the set various planting time stages of the crops to obtain the current planting time stage of the crops, extracting a standard image of the crops in the current planting time stage from an information statistics library, comparing the standard image with the current growth image of the crops to obtain the leaf growth deviation coefficient of the cropsAnd branch growth deviation coefficient->。
Analyzing current crop growth health indexWherein->The set coefficient duty ratios corresponding to the blade growth deviation and the branch growth deviation are respectively shown.
In a specific embodiment of the present invention, the calculation method of the leaf growth deviation coefficient of the crop is as follows: and summarizing each plant individual image from each plant individual image, identifying each plant individual leaf, obtaining each plant individual leaf abnormal shape value, and comparing the leaf abnormal shape value with a preset abnormal shape allowable value.
If the abnormal leaf shape value of a plant species individual exceeds the preset abnormal shape allowable value, marking the plant species individual, otherwise, obtaining the leaf color difference value of the plant species individual to obtain the number of the marked plant species individualsAnd leaf color difference value of individual plant species +.>，/>Representing plant species individual number,/->。
Calculating the leaf growth deviation coefficient of cropsWherein->Representing the total number of individuals of the plant->Representing a preset normal difference value of the color of the blade.
The method for obtaining the leaf color difference value of each plant species individual is as follows: processing each plant type individual image by using image processing software, extracting each blade area in each plant type individual image, converting each blade area in each plant type individual image into a characteristic value representing color by using a color space conversion method, comparing the characteristic value with the standard blade image color characteristic value of each plant type individual image to obtain a color characteristic local difference value of each blade area in each plant type individual image, and summing the color characteristic local difference values of each blade area in each plant type individual image to obtain the blade color difference value of each plant type individual.
The blade shape abnormal value of each plant species individual is obtained by the following steps: comparing each leaf area in each plant type individual image with each abnormal leaf shape image of the plant in the information statistical library, and if the leaf area of a certain plant type individual image is successfully matched with a certain abnormal shape image of the plant in the information statistical library, marking the leaf area of the plant type individual image as a leaf shape abnormal value corresponding to the leaf shape of the plant type individual image asThe method comprises the steps of carrying out a first treatment on the surface of the If a certain leaf area of a plant type individual image is not matched with various abnormal shape images of plants in the information statistics library, obtaining a leaf contour corresponding to the leaf area of the plant type individual image, extracting a leaf contour area, comparing the leaf contour area with a normal leaf contour area of the plant at the current time stage to obtain a leaf shape abnormal value corresponding to the leaf area of the plant type individual image>，/>Representing blade profile area>Normal leaf profile area of plants at the current time stage,/->Representing the set correction factor of abnormal shape deviation, and counting to obtain abnormal value of each leaf shape of each plant species individual>，/>Indicates the leaf number>Further calculating the average value to obtain abnormal leaf shape value of each plant species>，/>Is the number of blades.
The above-described abnormal shape includes a curled shape and a broken shape.
The normal leaf contour area of the plant in the current time stage and the standard leaf image color characteristic value of the plant individual are identified from the standard image of the crop in the current planting time stage.
In another specific embodiment of the present invention, the branch growth deviation coefficient is calculated by: the normal branch size value of the plant species individual in the current planting time stage is identified from the standard image of the crop in the current planting time stageAnd obtaining the normal growth concentration of plants in the current planting time stage>。
Obtaining the current growth density of crops based on the interception position of each plant variety individual imageAnd the growth height and branch diameter of each plant species are obtained and respectively marked as +.>。
Calculating the branch growth deviation coefficient of cropsWherein->Representing branchesSetting deviation threshold value corresponding to dry size, +.>Setting compensation factors representing the growth deviation coefficients of the branches, < >>Is the circumference ratio.
The current growth density acquisition formula of the crops is as follows，/>Representing the number of individuals of the plant species->Indicating setting a constant greater than 1. The corresponding acquisition mode of the normal growth density of the plants in the current planting time stage is the same as the current acquisition mode of the growth density of the crops.
The growth prediction module is used for obtaining the current actual growth stage of crops and predicting the predicted growth health index of the next planting time stageFurther, the basic demand content of various fertilizer components of crops in the next planting time stage is evaluated.
In a specific embodiment of the present invention, the predicted growth health index for the next planting time period is predicted by the following steps: according to the current planting time stage of crops, screening the appointed growth health indexes of the current planting time stage and the next planting time stage from an information statistical library, and comparing the appointed growth health index of the current planting time stage with the current crop growth health index to obtain the current growth health deviation rate of the cropsPredicted growth health index +.>，/>A specified growth health index representing the next planting time period.
In a specific embodiment of the present invention, the evaluation of the basic demand content of various fertilizer components of the crop at the next planting time stage includes: the underground part of the appointed monitoring area is detected by utilizing underground organ detection equipment, the distribution depth and density of the root system of the crops are displayed, and the current actual growth stage of the crops is confirmed by combining the current growth health index of the crops.
The underground organ detection equipment comprises a detector and a display, wherein the detector detects each underground root system of crops through electromagnetic waves, the display displays the growth depth and the growth position of each underground crop root system, average value calculation is carried out on the growth depth of each underground crop root system to obtain average value depth of the crop root system, and the average value depth is recorded as root system distribution depth of the crops.
The designated monitoring areas are meshed according to the same interval to obtain grid areas, the root system quantity in each grid area is obtained according to the growth position of each root system of crops, and the average value quantity of the root systems in unit grid is obtained by adopting average value calculationFurther calculate the root system distribution density of the crops>，/>Representing the area of division of the unit mesh region.
The step of confirming the current actual growth stage of the crop is as follows: the root system distribution depth and distribution density of crops are respectively recorded asGrowth health index combined with farming current>Calculating to obtain growth state evaluation coefficient of crops>，/>In the formula->Respectively representing the corresponding set reference values of root system distribution depth and distribution density,/for>Respectively representing the set occupation ratio corresponding to the root system distribution depth and the distribution density, and comparing and matching the growth state evaluation coefficient of the crops with the prestored corresponding evaluation coefficients of each growth stage to obtain the current actual growth stage of the crops.
Extracting conventional content of various fertilizer components in the next planting time stage corresponding to the current actual growth stage of crops from an information statistics libraryG represents the fertilizer ingredient type number, ++>。
The specified growth health index of the crops in the next planting time stage is added with the set growth deviation index and then is subjected to difference with the expected growth health index in the next planting time stage to obtain a crop growth difference value, and if the crop growth difference value is greater than or equal to 0, the crop growth difference value is calculated byAs a fertilizer ingredient expansion coefficient, < > for>Indicating the setting of the growth bias index.
If the crop growth difference value is less than 0, thenAs a fertilizer component reduction factor, obtaining the basic demand content of various fertilizer components of crops in the next planting time stage>，/>Adjusting coefficient representing the content of fertilizer ingredients, +.>E represents a natural constant.
It is added that, during the growth process of crops, there is a proper nutrient intake range, when the growth rate of crops reaches a certain value, enough nutrients are usually absorbed, and continuous fertilization can cause excessive nutrient accumulation, so that the environment is polluted and the quality of crops is affected, so that when the growth rate of crops reaches a certain value, the required content of fertilizer components is required to be reduced and adjusted.
According to the invention, the actual growth stage of the crops is analyzed by monitoring the current growth health state of the crops, so that the basic demand content of various fertilizer components of the crops in the designated monitoring area in the next planting time stage is evaluated, a determination basis is provided for the proportioning content of various follow-up fertilizer components, the fertilizing amount is more accurate, and the situation of fertilizer proportioning error caused by the deviation of the actual growth state is avoided, thereby improving the fertilizing effect.
The soil element monitoring module is used for acquiring the content of various elements in the soil and analyzing the missing content of various elements in the soil.
In a specific embodiment of the invention, the analyzing steps of the corresponding analysis of the missing content of each element in the soil are as follows: acquiring standard contents of various soil elements of a designated monitoring area in the current planting time stage, and detecting the soil element contents of the designated monitoring area in real time to acquire soilThe detection content of each element in the soil at each time point in the set time period is obtained by subtracting the detection content of each corresponding element in the soil at each time point in the set time period from the standard content of each soil element in the current planting time period in the appointed monitoring area, so as to obtain the difference content of each element in the soil at each time point in the set time periodK represents the soil element species number, +.>R represents a time point number, < >>。
Respectively carrying out average value calculation and summation calculation on the difference contents of various elements in the soil at each time point in a set time period to obtain the average value of the difference contents of various elements in the soil in the set time periodSum of difference content->。
Extracting the maximum difference content and the minimum difference content of various elements in the soil in a set time period from the difference content of various elements in the soil in various time points in the set time period, and recording as。
From analytical formulasObtaining the deletion content of various elements in the soil, wherein->Indicating the set allowable value of differential content, +.>Indicating deviceThe determined deviation value of the differential content corresponds to the influence weight, < ->Indicating the presence of a symbol->Representing logical AND notation, ">Representing a logical or symbol.
The soil element content is obtained by a detection instrument arranged at a set position of a designated monitoring area, and the soil element content refers to the content of various chemical elements in soil and comprises two parts of organic elements and inorganic elements. The organic matter elements mainly comprise nitrogen, phosphorus, sulfur and other elements; the inorganic elements mainly comprise common metal elements and nonmetallic elements such as potassium, silicon, manganese, zinc and the like.
The element content in the soil has important significance for soil fertility, crop growth, environmental protection and the like, and the composition and the proportion of the element content in different types of soil are different, so that in agricultural production, accurate analysis and evaluation of the element content in the soil are necessary. The content of the soil element is continuously changed in the monitoring process, so that the content change stability condition of the soil element needs to be analyzed to ensure the representativeness and the reliability of the monitoring data result.
The fertilizer component proportioning module is used for acquiring weather information of a future time period, evaluating fertilizer nutrient availability coefficients of the future time period, and further determining the demand content of various fertilizer components by combining the analyzed multidimensional data.
In a specific embodiment of the invention, the fertilizer nutrient availability coefficient of the future time period is evaluated by the following method: l1, extracting weather information in a future time period from a local weather forecast platform, and acquiring rainfall of each day in the future time period if rainfall weather exists in the future time periodJ represents the number of days in the future period, < +.>Further calculating the fertilizer nutrient availability factor for the future time period +.>In (1) the->Represents a set integrated rainfall threshold, +.>Indicating that the total rainfall value does not exceed the set integrated rainfall threshold for the future time period,indicating that the total rainfall exceeds the set integrated rainfall threshold value in the future time period, +.>Respectively indicate->、/>In this case, the deviation correction coefficient is set correspondingly.
L2, if weather exceeding the set proper illumination intensity exists in the future time period, acquiring the illumination intensity of each day exceeding the set proper illumination intensity in the future time period, and recording as，/>Number of days indicating more than the set appropriate illumination intensity, +.>Further calculating the fertilizer nutrient availability coefficient in the future time period，/>Indicating that the proper illumination intensity is set>Representing the number of days of extraction corresponding to the future time period, +.>And (5) representing the set evaluation factors corresponding to the fertilizer nutrient availability coefficients.
L3, if neither rainfall weather nor weather exceeding the set proper illumination intensity exists in the future time period, recording the fertilizer nutrient availability coefficient of the future time period as the set valueFurther evaluating the fertilizer nutrient availability factor for future time period +.>，/>Wherein->Respectively representing the set influence duty ratio weight of rainfall weather and weather exceeding the set proper illumination intensity, < ->Indicating the presence of raining weather or weather exceeding a set suitable illumination intensity in the future time period, < >>Indicating that neither rainfall weather nor weather exceeding the set suitable illumination intensity is present for the future period of time.
Under normal conditions, rainfall directly influences the soil humidity and the absorption capacity of root systems, and under the condition that the soil humidity is proper, nutrients and moisture can be better absorbed and utilized by plants, so that the utilization rate of the fertilizer is improved. However, if rainfall is excessive, nutrient leaching and soil loss can be caused, and the effectiveness of the fertilizer is reduced.
The higher the temperature is, the more microorganisms in the soil are, the faster the organic matters are decomposed, and the higher the absorption and utilization efficiency of plants is, so that the illumination intensity can positively influence the growth speed and the nutrient absorption efficiency of the plants.
According to the invention, the compensation content of various fertilizer components is evaluated by analyzing the change condition of the missing content of various elements in the soil so as to ensure the blending relation of the various element contents in the soil and the fertilizer components, and meanwhile, the weather change condition of the future time period is combined to predict the fertilizer nutrient availability factor of the future time period, so that the influence of weather on the nutrient absorption and utilization efficiency is avoided, and the blending benefit of the fertilizer is improved to the greatest extent.
In a specific embodiment of the invention, the multidimensional data comprises the basic demand content of various fertilizer components of crops at the next planting time stage, the missing content of various elements in soil and the fertilizer nutrient availability coefficient of the future time period.
In a specific embodiment of the present invention, the corresponding method for determining the required content of each fertilizer component is as follows: acquiring soil elements corresponding to various fertilizer components, setting fertilizer component compensation contents corresponding to unit deletion contents of various elements in the soil according to a preset principle, converting the deletion contents of various elements in the soil into corresponding fertilizer component compensation contents by using a multiplication formula, and summing to obtain comprehensive compensation contents of various fertilizer components。
From the evaluation formulaThe desired content of each fertilizer component is determined.
The information statistical library is used for storing standard images of crops in various planting time stages, specified growth health indexes, conventional contents of various fertilizer components and standard contents of various soil elements, storing various abnormal leaf shape images of plants and storing corresponding evaluation coefficients of various growth stages.
The method combines multidimensional data to comprehensively analyze the fertilizer demand content, is beneficial to scientifically and reasonably carrying out fertilization management, improves the benefit and the sustainability of agricultural production, can avoid the situation of excessive fertilization or insufficient nutrition, ensures the accuracy of fertilizer proportioning, and further improves the yield and the quality of crops.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.
Claims (6)
1. An automatic fertilizer mixing system based on data analysis, which is characterized by comprising:
the growth image acquisition module is used for monitoring the crop growth image in the appointed monitoring area in real time, and carrying out individual positioning interception on the current crop growth image to obtain each plant individual image of the current crop growth image;
the crop monitoring module is used for identifying the types of individual images of each plant, wherein the types comprise weeds and crop plants, and further analyzing the current crop growth health index;
the growth prediction module is used for obtaining the current growth health deviation rate of crops and predicting the expected growth health index of the next planting time stageFurther evaluating the basic demand content of various fertilizer components of crops in the next planting time stage;
the soil element monitoring module is used for acquiring the content of various elements in the soil and analyzing the missing content of various elements in the soil;
the fertilizer component proportioning module is used for acquiring weather information of a future time period, evaluating fertilizer nutrient availability coefficients of the future time period, and further determining proportioning contents of various fertilizer components by combining the analyzed multidimensional data;
the information statistics library is used for storing standard images of crops at various planting time stages, specified growth health indexes, conventional contents of various fertilizer components and standard contents of various soil elements, and storing various abnormal leaf shape images of plants;
the method for analyzing the current crop growth health index is as follows:
obtaining the planting time of crops, screening according to the planting time corresponding to the set various planting time stages of the crops to obtain the current planting time stage of the crops, extracting a standard image of the crops in the current planting time stage from an information statistics library, comparing the standard image with the current growth image of the crops to obtain the leaf growth deviation coefficient of the cropsAnd branch growth deviation coefficient->；
Analyzing current crop growth health indexWherein->Respectively representing the set coefficient duty ratio corresponding to the blade growth deviation and the branch growth deviation;
the predicted growth health index for predicting the next planting time stage comprises the following specific steps:
according to the current planting time stage of crops, screening the appointed growth health index of the current planting time stage and the appointed growth health index of the next planting time stage from an information statistical library, and combining the appointed growth health index of the current planting time stage with the current farmingComparing the physical growth health indexes to obtain the current growth health deviation rate of cropsPredicted growth health index +.>，/>A specified growth health index representing a next planting time period;
the specific content for evaluating the basic demand content of various fertilizer components of crops in the next planting time stage comprises the following steps:
detecting the underground part of the appointed monitoring area by utilizing underground organ detection equipment, displaying the root system distribution depth and distribution density of crops, and determining the current actual growth stage of the crops by combining the current crop growth health index;
extracting conventional content of various fertilizer components in the next planting time stage corresponding to the current actual growth stage of crops from an information statistics libraryG represents the fertilizer ingredient type number, ++>The method comprises the steps of carrying out a first treatment on the surface of the Basic demand content of various fertilizer components of crops in the next planting time period>，/>An adjustment factor representing the content of the fertilizer component;
fertilizer nutrient availability factor for the future time periodRelated to the amount of rainfall per day in the future time period, the number of days exceeding the set proper illumination intensity, and the number of days exceeding the set proper illumination intensity;
the corresponding method for determining the proportioning content of various fertilizer components comprises the following steps: converting the missing content of various elements in the soil into corresponding compensation content of fertilizer components, and summing to obtain comprehensive compensation content of various fertilizer components；
From the evaluation formulaThe proportion content of various fertilizer components is determined.
2. The automatic fertilizer mixing system based on data analysis of claim 1, wherein: the calculation mode of the blade growth deviation coefficient of the crops is as follows:
summarizing each plant individual image from each plant individual image, identifying each plant individual leaf, obtaining each plant individual leaf abnormal shape value, and comparing the leaf abnormal shape value with a preset abnormal shape allowable value;
if the abnormal leaf shape value of a plant species individual exceeds the preset abnormal shape allowable value, marking the plant species individual, otherwise, obtaining the leaf color difference value of the plant species individual to obtain the number of the marked plant species individualsAnd leaf color difference value of individual plant species +.>，/>Representing plant species individual number,/->；
Calculating the leaf growth deviation coefficient of cropsWherein->Representing the total number of individuals of the plant->Representing a preset normal difference value of the color of the blade.
3. The automatic fertilizer mixing system based on data analysis according to claim 2, wherein: the branch growth deviation coefficient calculation mode is as follows:
the normal branch size value of the plant species individual in the current planting time stage is identified from the standard image of the crop in the current planting time stageAnd obtaining the normal growth concentration of plants in the current planting time stage>；
Obtaining the current growth density of crops based on the interception position of each plant variety individual imageAnd the growth height and branch diameter of each plant species are obtained and respectively marked as +.>；
Calculating the branch growth deviation coefficient of cropsWherein->Representing the corresponding set deviation threshold value of branch size, < ->Setting compensation factors representing the growth deviation coefficients of the branches, < >>Is the circumference ratio.
4. The automatic fertilizer mixing system based on data analysis of claim 1, wherein: the calculation mode of the adjustment coefficient of the fertilizer component content is as follows:
the specified growth health index of the crops in the next planting time stage is added with the set growth deviation index and then is subjected to difference with the expected growth health index in the next planting time stage to obtain a crop growth difference value, and if the crop growth difference value is greater than or equal to 0, the crop growth difference value is calculated byAs a fertilizer ingredient expansion coefficient, < > for>Indicating a set growth deviation index;
if the crop growth difference value is less than 0, thenAs a factor of the reduction of the fertilizer composition,e represents a natural constant.
5. The automatic fertilizer mixing system based on data analysis of claim 4, wherein: the analyzing steps of the corresponding analyzing of the missing content of various elements in the soil are as follows:
acquiring standard contents of various soil elements in a specified monitoring area in a current planting time period, detecting the contents of the soil elements in the specified monitoring area in real time, acquiring detected contents of various elements in soil at various time points in a set time period, subtracting the detected contents of corresponding elements in the soil at various time points in the set time period from the standard contents of the various soil elements in the specified monitoring area in the current planting time period, and obtaining differential contents of various elements in the soil at various time points in the set time periodK represents the soil element species number, +.>R represents a time point number, < >>；
Respectively carrying out average value calculation and summation calculation on the difference contents of various elements in the soil at each time point in a set time period to obtain the average value of the difference contents of various elements in the soil in the set time periodSum of difference content->；
Extracting the maximum difference content and the minimum difference content of various elements in the soil in a set time period from the difference content of various elements in the soil in various time points in the set time period, and recording as；
From analytical formulasObtaining the deletion content of various elements in the soil, wherein->Indicating the set allowable value of differential content, +.>The set difference content deviation value is indicated to correspond to the influence weight.
6. The automatic fertilizer mixing system based on data analysis of claim 5, wherein: the fertilizer nutrient availability coefficient of the future time period is evaluated by the following steps:
l1, extracting weather information in a future time period from a local weather forecast platform, and acquiring rainfall of each day in the future time period if rainfall weather exists in the future time periodJ represents the number of days in the future period, < +.>Further calculating the fertilizer nutrient availability factor for the future time period +.>In (1) the->Represents a set integrated rainfall threshold, +.>Indicating that the total rainfall value does not exceed the set integrated rainfall threshold for the future time period,indicating that the total rainfall exceeds the set integrated rainfall threshold value in the future time period, +.>Respectively indicate->、/>Setting deviation correction coefficients corresponding to the conditions;
l2, if weather exceeding the set proper illumination intensity exists in the future time period, acquiring the illumination intensity of each day exceeding the set proper illumination intensity in the future time period, and recording as，/>A number indicating the number of days exceeding the set appropriate illumination intensity,further calculating the fertilizer nutrient availability coefficient in the future time period，/>Indicating that the proper illumination intensity is set>Representing the number of days of extraction corresponding to the future time period, +.>The set evaluation factors corresponding to the fertilizer nutrient availability coefficients are represented;
l3, if neither rainfall weather nor weather exceeding the set proper illumination intensity exists in the future time period, recording the fertilizer nutrient availability coefficient of the future time period as the set valueFurther evaluating the fertilizer nutrient availability factor for future time period +.>，/>Wherein->Respectively representing the set influence duty ratio weight of rainfall weather and weather exceeding the set proper illumination intensity, < ->Indicating the presence of raining weather or weather exceeding a set suitable illumination intensity in the future time period, < >>Indicating that neither rainfall weather nor weather exceeding the set suitable illumination intensity is present for the future period of time.
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