807 results about "Soil nutrients" patented technology

The present invention relates to the technical field of land engineering, and relates to a water and soil resource comprehensive improvement method for loess hilly and gully region channels. The method comprises: (1) soil layer general survey: performing soil layer thickness survey and soil nutrition content measurement; (2) soil body reconstruction: on the basis of soil layer general survey data, selecting a soil body construction mode, and performing soil body profile reconstruction, soil body nutrition reconstruction and field parcel arrangement; and (3) constructing a water resource regulation and control system for the loess hilly and gully region channels. According to the present invention, investigation and survey are performed firstly, then treatment is performed, water and soil are treated simultaneously, and steps are coordinated, so that ecological treatment of the loess hilly and gully region channels is finally completed, and comprehensive improvement of water and soil resources is achieved. The present invention ensures mechanical cultivation of the region after the improvement, effectively increases the area of the irrigable land and the area of the non-irrigated land, effectively improves the farmland quality and the grain yield, and effectively reduces the soil erosion amount of the channels.

The invention relates to the technical field of intelligent decision making, in particular to an accurate fertilization intelligent decision making method and system based on multi-source remote sensing, and the method comprises the steps: obtaining a multi-source remote sensing image which comprises an unmanned aerial vehicle image and a stationary satellite image; acquiring soil nutrient data and fertility indexes of the sample field parcels; acquiring meteorological data and soil data; carrying out image preprocessing and feature extraction; constructing a crop identification and classification model; carrying out crop type identification and block division on the multi-source remote sensing image; extracting crop growth features based on the multi-source remote sensing image and the result of the crop identification and classification model; based on the crop growth characteristics and the soil nutrient data, analyzing the relationship between the crop growth stage and the nutrient demand; constructing a nutrient utilization efficiency maximization model; based on a nutrient utilization efficiency maximization model, generating a precise fertilization decision scheme; and outputting a precise fertilization decision scheme, and carrying out precise analysis and intelligent decision making on the growth state and nutrient demand of farmland crops.

The invention belongs to the technical field of microorganisms, and particularly relates to a Prlisteria ataveovii strain and application thereof. The invention provides a Pichia aryabhattai B8, which is preserved in the General Microbiological Culture Collection Center of the China Committee for Culture Collection of Microorganisms, the preservation date is September 10, 2024, and the preservation number is CGMCC No.31932. The Pichia aryabhattai B8 disclosed by the invention has the advantages that the Pichia aryabhattai B8 can be used for preparing the Pichia aryabhattai B8; the prelisteria aryabhattai B8 disclosed by the invention has a relatively strong function of producing indoleacetic acid, and the content of indoleacetic acid in plants can be increased, so that the stress resistance of the plants is improved; dissolution of insoluble phosphorus and potassium in soil can be promoted, soil nutrients are improved, plant growth is promoted, and plant quality is improved; and meanwhile, the P.aryabhattai B8 has a certain antagonistic effect on pathogenic bacteria of the wheat root rot, and can be used for preventing and treating the wheat root rot.

The invention provides an agricultural environment monitoring method and system based on the Internet of Things. According to the method, multi-source data weights are dynamically distributed through a soil sensor array connected with Internet of Things nodes, and a global soil parameter set is generated; deploying a micro-electro-mechanical micro-fluidic chip in the coverage area to carry out soil solution selective permeation, converting the target ion concentration into an electric signal, and synchronously transmitting the electric signal and soil parameters; historical time series data are extracted, coherence is established through time correlation analysis, and undeployed area data are filled in combination with a spatial interpolation algorithm to construct a dynamic prediction model; according to the nutrient space change trend output by the model, crop growth requirements are matched to generate a fertilization amount adjustment instruction, and the fertilization amount adjustment instruction is issued to field fertilization equipment through the Internet of Things to execute dynamic regulation. Space-time precise sensing of soil nutrients and self-adaptive fertilization regulation and control are realized, and the utilization efficiency of agricultural resources and crop growth sustainability are improved.

The embodiment of the invention provides a soil nutrient spectrum detection and regulation method and system, and belongs to the technical field of soil nutrient spectrum detection and regulation. The method comprises the following steps: collecting soil multispectral original data and environmental data, generating a calibration matrix and a nonlinear correction parameter, executing optical reflectivity conversion, and synchronously fusing a time domain reflectometry dielectric constant and a spectral moisture index to obtain fused moisture content; selecting a nutrient diagnosis characteristic wave band pair to obtain a moisture inhibition type spectral index; and predicting the soil nutrient content by using a pre-trained transfer learning model to obtain a soil nutrient content prediction value, and performing fertilization regulation and control based on the fertilization decision risk coefficient. According to the invention, extreme soil moisture measurement deviation is solved through a soil type adaptive moisture fusion technology; through multi-source risk quantitative decision and PID self-adaptive regulation and control, the fertilization amount can be dynamically optimized, execution safety is guaranteed, and a detection-decision-execution precision agriculture closed loop is formed.

The invention discloses a crop sowing parameter control optimization method applied to multi-target precise fertilization, and relates to the technical field of agricultural crop sowing, and the method comprises the following steps: collecting a soil sample, carrying out spectrum scanning and analysis, combining with known soil nutrient data, building a soil nutrient content prediction model, and calculating a soil nutrient content prediction model; and combining spectral data to predict the nutrient content in the soil. According to the invention, through accurate evaluation of soil nutrient conditions and deep analysis of crop growth demands, fertilization and sowing parameters are optimized, so that crops can obtain required nutrients in the growth process, the optimized sowing depth, row spacing and plant spacing can effectively promote the development of crop roots, the absorption ability of the crops to moisture and nutrients is enhanced, and the quality of the crops is improved. And through real-time monitoring and adjustment of the intelligent fertilization equipment, the fertilization amount can be dynamically adjusted according to actual demands of crops, and the common problem of excessive or insufficient fertilizer in a traditional fertilization method is avoided.

The invention discloses a soil nutrient recycling method and system based on prediction driving, and belongs to the technical field of agricultural soil management.The method specifically comprises the steps that soil nutrient content data are obtained through sampling, and soil nutrient abnormal areas are preliminarily screened in combination with a geographic information system and a remote sensing technology; soil physicochemical properties are measured in the soil nutrient abnormal area, soil nutrient form distribution is measured through X-ray diffraction and near infrared spectroscopic analysis, and nutrient stability and release potential are evaluated; constructing a soil nutrient cyclic dynamic model based on multi-source data, and simulating nutrient evolution; according to simulation results, crop requirements, soil states and environmental factors, an accurate fertilization scheme is formulated; intelligent management and precise fertilization of soil nutrients are realized, and the fertilizer utilization rate and the agricultural production efficiency are improved.

The invention provides a vehicle-mounted soil nutrient detection method and device based on soil spectral data classification, and relates to the technical field of soil detection.The method comprises the steps that soil near infrared spectral data of soil of a current site in a farmland area to be detected is collected through vehicle-mounted equipment; then obtaining first spectrum difference information and second spectrum difference information based on the soil near infrared spectrum data; further determining the similarity degree of the near infrared spectrum data of the soil; dividing the soil near infrared spectrum data into a plurality of different soil near infrared spectrum data subsets through a spectral clustering algorithm, and performing soil nutrient detection through a farmland soil nutrient detection model. According to the vehicle-mounted soil nutrient detection method based on soil spectral data classification, the total nitrogen content and the organic matter content of the soil can be accurately output in real time, and the detection effect of soil nutrient detection is improved.

The invention relates to the technical field of farmland fertilization management, and discloses an intelligent fertilization management method and system based on machine learning. The method comprises the steps that a soil parameter set and an environment parameter set of a target farmland are collected, soil parameters comprise soil humidity, nitrogen phosphorus and potassium content and pH value, and environment parameters comprise illumination intensity, temperature and rainfall; constructing a soil nutrient dynamic change model according to historical data, and predicting a soil nutrient consumption trend in a future preset period; generating an initial fertilization scheme based on the nutrient consumption trend and the crop growth stage characteristics; monitoring the growth state of crops in real time by using a multi-mode sensor, and obtaining a leaf surface color index, a stem height and a fruit development progress to form a growth state data set; and inputting the growth state data set and the initial fertilization scheme into a fertilization decision model, and comparing growth state deviation to adjust the nutrient distribution ratio to generate an optimized fertilization scheme.

The invention relates to the technical field of agriculture, and discloses an intelligent fertilization technical measure and method for improving the fertilizer utilization rate, and the intelligent fertilization technical measure comprises a soil sensor module which is used for monitoring various parameters of soil in real time, including but not limited to soil nutrient content, soil humidity, soil acidity and alkalinity, soil temperature and soil texture; the soil sensor module can collect monitored parameter data with high precision and high frequency, and transmit the data to the central control unit through the wireless communication module; the fertilizer storage and conveying module is internally provided with a plurality of independent fertilizer storage bins, and each storage bin can store different types of fertilizers. According to the present invention, the type, the use amount and the application time of the fertilizer can be precisely controlled according to the growth requirements of different crops and the soil state through the precise fertilization mode so as to ensure the efficient absorption of the fertilizer by the crops, such that the fertilizer utilization rate is significantly improved, and compared with the traditional fertilization mode, the fertilizer waste can be reduced, and the agricultural production cost can be reduced.

The invention provides a soil nutrient detection method based on a gamma-ray energy spectrum and an XGboost algorithm, and the method comprises the steps: constructing a training sample for soil nutrient detection, the training sample comprises radioactive element data, and the label of the training sample is soil nutrient data with the same soil point location as the radioactive element data; the training sample is input into an XGboost model, the XGboost model extracts features of the training sample and predicts soil nutrients of the training sample, the soil nutrients serve as nutrient predicted values, a loss function is constructed according to the nutrient predicted values and labels of the training sample, the XGboost model is trained, and a soil nutrient detection model is obtained; acquiring soil radioactive elements of to-be-detected soil through a gamma-ray energy spectrometer, and inputting the soil radioactive elements into the soil nutrient detection model to obtain a nutrient detection result of the to-be-detected soil.

The invention provides a method for increasing the growth rate of a citrus breeding material, and relates to the field of agricultural science. The method for improving the growth rate of the citrus breeding material comprises the following steps: selecting high-quality seedlings, and selecting citrus seedlings with excellent hereditary characteristics as the breeding material; the soil environment is optimized, the soil structure is improved, and the soil organic matter content is increased; nutrition management: formulating a scientific fertilization scheme including the proportion and the application amount of nitrogen, phosphorus, potassium and trace elements; according to the application of the growth regulator, the plant growth regulator is used for promoting cell division and elongation; disease and pest control: combining biological control and chemical control to control the occurrence of diseases and pests, and regularly monitoring the disease and pest conditions; environment regulation and control: temperature, humidity and illumination conditions are controlled, and a suitable growth environment is created. A scientific fertilization scheme is formulated according to the soil nutrient condition and the nutritional requirements of the citrus, and sufficient nutrients are ensured to be obtained in each growth stage, so that the growth rate is remarkably increased.

The invention relates to the crossing field of precision agriculture and artificial intelligence technology, in particular to a soil component detection system based on machine learning and infrared spectroscopy, which is characterized in that a soil spectrum is acquired on site through a portable Fourier infrared spectrometer, and after pretreatment, feature vectors are constructed by fusing climate, soil and crop data; the deep learning decision-making module extracts spectral features by using one-dimensional convolution, fuses multi-dimensional information through an attention mechanism, synchronously outputs a fertilization scheme, crop suitability scores and soil improvement measures by a multi-task learning sub-network, and finally, verifies by combining an agronomic knowledge base so as to obtain a fertilization result. According to the method, a comprehensive decision report containing a quantitative fertilization formula, a crop suitability sequence and a soil improvement scheme is generated, precise agricultural guidance is realized, spectral features are automatically extracted by adopting a one-dimensional convolutional neural network, and a multi-modal data fusion and multi-task learning framework is combined, so that the system achieves relatively high precision in the aspect of soil nutrient prediction.

The invention discloses a method for collecting orchard ecological environment information, and the method comprises the steps: collecting soil parameters, space environment parameters, insect pest parameters and fruit parameters of an orchard in real time through deploying a plurality of collection devices, and carrying out the collection to form an orchard ecological basic data set; a backstepping model is constructed to indirectly calculate key ecological parameters including soil nutrients, fruit quality and insect pest diffusion trend, and an optimization result is corrected through experimental verification and the model; comparing a backstepping result with an orchard target value to analyze a deviation source, and establishing a macroscopic cause chain through data matching and a visual tool; according to the deviation analysis and the cause chain result, determining an executable regulation and control measure matched with the regulation and control direction; and monitoring the effect after the implementation of the regulation and control measures, verifying the regulation and control effect by comparing the data before and after the implementation of the regulation and control measures, and applying feedback data to iterative optimization of the backstepping model. The method is scientific and efficient and can be used for improving orchard production benefits and ecological environment quality.

The invention discloses a high-efficiency lespedeza growth-promoting bacillus Q4 (Bacillus atrophaeus) capable of improving the abundance of dominant bacteria and a preparation method of the high-efficiency lespedeza growth-promoting bacillus Q4. Belongs to the technical field of microorganisms. According to the bacillus atrophaeus Q4 provided by the invention, the conversion from total-effect nutrients to effective nutrients is improved, the consumption of lespedeza to soil nutrients is enhanced, and the abundance of dominant strain groups is increased, so that the effect of promoting the growth of lespedeza is achieved. After the bacillus atrophaeus Q4 provided by the invention is applied, the soil enzyme activity is remarkably improved, the conversion of available nutrients in soil is remarkably enhanced, and the nutrient consumption capability of lespedeza is enhanced. By applying the bacillus atrophaeus Q4, growth and development of lespedeza are promoted, the content of soil hydrolytic nitrogen and available phosphorus is remarkably increased, conversion to soil nutrients is improved, and the conductivity and organic carbon are increased to the maximum extent and are remarkably increased by 142.77% and 64.26% respectively. In the genus level, after being treated by the bacillus atrophaeus Q4, the bacillus (Bacillus) is obviously increased from 0.84% to 2.47%, and the average relative abundance of the pseudomonas (Fictibacillus) is obviously increased from 0.59% to 1.16%. By inoculating the Q4 inoculant, the structure of a soil colony is greatly improved, the relative abundance of a dominant flora is influenced, and the obvious increase of the relative abundance of Bacillus and Fictibacillus is possibly an important factor for promoting plant growth.

The invention relates to the field of saline-alkali soil remediation, and particularly discloses a saline-alkali soil improvement and remediation method which comprises the following steps: step 1, soil pretreatment: performing deep scarification operation on saline-alkali soil at the depth of 40-60cm, and applying desulfurized gypsum particles with the particle size of less than or equal to 5mm at the dosage of 3-5t / ha; step 2, paving a biochar-based composite material: mixing biochar, humic acid and nano-hydroxyapatite according to a mass ratio of 4: 1: 0.5 to form composite particles with the particle size of less than or equal to 2mm, and burying the composite particles into soil in a layered manner according to the dosage of 8-12t / ha; through physical and chemical regulation and control of the biochar-based composite material, biological metabolism activation of the composite microbial agent and dynamic optimization of intelligent water and salt management, a cascade remediation system of material salt resistance-microbial soil improvement-plant salt absorption is constructed, all technical modules are mutually coupled, the salt reduction efficiency is remarkably improved, and the comprehensive utilization rate of the biochar-based composite material is increased. Meanwhile, the soil nutrient circulation capacity is enhanced, and the problems that a traditional single technology is limited in action range and long in remediation period are solved.

The invention provides an agricultural product production process intelligent supervision system and method based on big data analysis. The system comprises a data acquisition assembly, a data analysis assembly and a management planning assembly. The method comprises the following steps: deploying various sensors in a field for automatically collecting target data, and uploading the target data to a data analysis component in real time; analyzing the target data by using the collected target data through an agricultural product production data analysis algorithm to obtain the change trend of the soil nutrient content, and predicting when to apply fertilizer and the amount of the fertilizer; meanwhile, pest and disease damage is predicted, and a corresponding prevention and control scheme is provided; suggestions are provided for irrigation according to historical data and current environmental conditions; the analysis result is applied to an agricultural product planting area; the agricultural product planting area plans the planting layout of agricultural products by means of satellite remote sensing and a geographic information system. The agricultural production efficiency and economic benefits are improved, and powerful technical support is provided for agricultural sustainable development.

The invention relates to the technical field of peach tree disease and insect pest control, in particular to a peach tree disease and insect pest control method and system.The method comprises the following steps that through peach orchard field investigation and survey, the number of branches is recorded, branch distribution and diseased leaf positions are detected, spot shapes and insect population cardinal numbers are shot, worm egg distribution and tree age information are summarized, and annual rings are checked; and measuring daily variation, soil nutrients and air temperature, and storing into a field table. According to the method, current state parameters of the peach trees are formed by recording key parameters such as the number and distribution of branches of the peach trees, diseased leaf positions, spot shapes, cardinal number of insects, tree age, moisture content, soil nutrients and air temperature, and a basis for dynamic monitoring of diseases and insect pests is established. On the basis of current situation parameter analysis, branch surface color spots, diseased leaf corrosion degree and fruit damage are compared, insect pest types are divided, parasitic characteristics are counted, abnormal data are further decomposed, and deep optimization of disease and insect pest classification and feature recognition is achieved.

The invention relates to the technical field of organic fertilizers and planting of watermelons and muskmelons, and provides a special fertilizer for milk irrigated watermelons and muskmelons and a double-stubble planting method for sweetness enhancement of milk irrigated watermelons and muskmelons. The special fertilizer for the milk irrigated watermelons and muskmelons comprises black goat manure, sophora alopecuroide, sesame seed meal, bran, organic fresh milk, brown sugar and zymophyte. The black goat manure is pulverized into powder by a pulverizer, the sophora alopecuroide is pulverizedinto 1 cm to 2 cm, and the ratio of the black goat manure, the sophora alopecuroide, the sesame seed meal, the brans, the organic fresh milk, the brown sugar and the zymophyte is 2700-3200: 80: 50: 150: 5: 1. The double-stubble planting method for sweetness enhancement of the milk irrigated watermelons and muskmelons comprises the following steps: selection of a nursery seedling plate and soil, cleaning and germination accelerating of seeds, soil preparation, transplanting, irrigation, topdressing, shaping and forking of watermelon and muskmelon vines and fruit bearing of the watermelons and the muskmelons. The problems that in an existing watermelon and muskmelon planting process, soil nutrients are damaged due to the fact that chemical fertilizers are used for a long time, and the sweetness of melons is reduced are solved.

The invention discloses a dynamic black land soil nutrient prediction system based on satellite remote sensing and multi-source data fusion, and relates to the field of artificial intelligence, and the system comprises a data collection module which obtains multi-source data of black land soil, including satellite remote sensing data, ground sensor data, meteorological data and historical soil nutrient data; the feature extraction module is used for extracting feature information of soil nutrients; the prediction model module is used for constructing a soil nutrient dynamic prediction model and accurately predicting the soil nutrient dynamic state; the feedback optimization module is used for optimizing and updating the prediction model, continuously improving the performance of the model, improving the prediction precision and obtaining an optimized prediction model; the visualization module is used for visually displaying a prediction result, displaying spatial and temporal distribution of soil nutrients in the form of a map and a chart, and providing strategy support of fertilization suggestions and land management; according to the data storage and management module, a database stores different types of data, efficient query, updating and maintenance of the data are achieved, and the safety of the soil nutrient dynamic data is improved.

The invention discloses a precise fertilization method, system and device for a rice transplanter, and relates to the technical field of rice cultivation. Comprising the following steps: dividing a to-be-fertilized field into a plurality of sub-regions, analyzing the concentrations of nitrogen, phosphorus, potassium and organic matters, and taking an average value as the nutrient content of the field; the soil compactness is analyzed, and the nutrient penetration depth index is calculated in combination with environmental parameters such as soil temperature and humidity mean values; acquiring field salinity and alkalinity data, and calculating a soil nutrient effectiveness index in combination with the environmental parameters; correcting the fertilization longitudinal spacing and the fertilization depth according to the nutrient effectiveness index and the penetration depth index to obtain an accurate value; finally, the rice precise fertilization operation is completed through a rice transplanter according to the precise fertilization depth and the longitudinal distance. According to the method, soil nutrients and environmental parameters are dynamically combined, the fertilization precision is optimized, and the fertilizer utilization efficiency is improved.

The invention provides a fertilization control method and system, and belongs to the technical field of smart agriculture, and the method comprises the steps: determining a target element-deficient region based on a multispectral remote sensing image of a target region crop, a crop type and a crop growth stage; inputting the multispectral reflectivity data, the soil nutrient data and the crop growth stage of the target nutrient-deficient area into a preset nutrition diagnosis model to obtain a deficient nutrient element type and a deficient degree; inputting the nutrient element type, the lack degree, the soil nutrient data, the crop growth stage, the planned irrigation water amount and the fertilizer mother liquor concentration into a water and fertilizer decision model, and calculating to obtain the target fertilizer liquor concentration and the total fertilizer demand; and controlling the fertilization device to adjust the mother liquor injection proportion and the irrigation flow based on the target fertilizer solution concentration and the total fertilizer demand. The fertilization control method and control system provided by the invention realize accurate regulation and control of water and fertilizer, not only can improve the utilization rate of water and fertilizer, but also can improve the yield and quality of crops.

The invention belongs to the technical field of soil improvement, and discloses a preparation method of a manganese slag-coconut shell charcoal-desulfurized gypsum composite soil improvement agent, the soil improvement agent and application. The preparation method of the soil conditioner comprises the working procedures of manganese residue pretreatment, coconut shell pretreatment, precursor preparation, precursor calcination and conditioner compounding, the pretreated coconut shell and the pretreated manganese residue are mixed and then subjected to ball milling, and a manganese residue-coconut shell precursor is obtained; calcining the prepared manganese residue-coconut shell precursor for 1-4 hours at the temperature of 450-650 DEG C in a protective gas atmosphere to obtain manganese residue-coconut shell biochar; and doping desulfurized gypsum powder into the prepared manganese slag-coconut shell charcoal, and uniformly dispersing to obtain the manganese slag-coconut shell charcoal-desulfurized gypsum composite soil conditioner. The method disclosed by the invention has the advantages of low energy consumption, low cost and capability of treating waste with waste, and the prepared soil conditioner has the advantages of improving soil nutrient balance, reducing nutrient loss and stabilizing pH, and is suitable for modifying the acid soil of the rubber plantation in the tropical region.

The invention discloses a Burkholderia gladioli (Burkholderia gladioli) CT-5 strain and an application of the Burkholderia gladioli CT-5 strain, and relates to the technical field of microorganisms. The strain is preserved in the China Center for Type Culture Collection, the preservation number is CCTCC NO: M20242732, and the preservation date is December 05, 2024. The Burkholderia gladioli (Burkholderia gladioli) CT-5 provided by the invention has a remarkable prevention and treatment effect (Plt, Plt) on idesia root rot caused by Fusarium solani (Fusarium solani), and the Burkholderia gladioli (Burkholderia gladioli) CT-5 has a remarkable prevention and treatment effect on idesia root rot caused by Fusarium solani (Busarium solani). The compound has the advantages that the compound can be used for inhibiting pathogenic bacteria of various plants, and the compound can be used for inhibiting pathogenic bacteria of various plants, such as Schizophyllum commune, Diaporthe erens, Colletotrichum acutatum and the like, and has a remarkable inhibiting effect on other various plant pathogenic bacteria such as the Schizophyllum commune, the Diaporthe erens, the Colletotrichum acutatum and the like. In a pot experiment, the biomass, soil nutrients, SOD, POD and CAT enzyme activities of idesia polycarpa seedlings in a CT-5 treatment group are remarkably improved compared with those of a pathogenic bacteria control group (FP) (Plt; 0.05), which indicates that the strain can promote plant growth and activate the activity of defensive enzyme in the body, so that effective control of idesia root rot is realized, and powerful theoretical basis and technical support are provided for sustainable development of idesia.

The invention provides a remote sensing data analysis-combined fertilizer proportion management method and system, and relates to the technical field of remote sensing data, the method comprises the following steps: using an unmanned aerial vehicle to shoot an original data set of crops in a key growth period of a target field, and preprocessing the original data set to obtain a remote sensing image set; calculating a vegetation index according to the remote sensing image set, and generating a vegetation index map in combination with GIS software; obtaining a soil nutrient content data set and a crop nutrient content data set; performing correlation modeling on the crop nutrient content data set and the vegetation index map by using a random forest regression algorithm, and performing nutrient inversion calculation on the target field by using the model to obtain a nutrient spatial distribution map; generating a fertilizer ratio decision; spatial expression is carried out on the decision result through GIS software, and a digital fertilization prescription map is obtained. The technical problems of low efficiency, large error, incomplete coverage and slow response in the prior art are solved.

The invention discloses an intelligent agricultural planting management method and system, and belongs to the technical field of intelligent agriculture, and the method comprises the steps of data layer construction, water and fertilizer prediction layer construction, planting optimization layer construction and agricultural planting management. The space-time adaptive water and fertilizer prediction layer construction method combining the crop physiological load and the crop growth stage is adopted, the water demand and nitrogen, phosphorus and potassium nutrient demands of crops in the future stage are accurately predicted, the crop growth state and environment changes are dynamically responded, the water and fertilizer demand difference in different growth stages is considered, and the water and fertilizer prediction efficiency is improved. The accuracy and applicability of prediction are improved through time-space fusion, and accurate fertilization can be realized; a planting optimization layer construction method combining digital twinborn and multi-objective optimization is adopted, a water and fertilizer management strategy is subjected to refined and dynamic optimization under the condition of considering a crop growth stage, a soil nutrient condition and a future weather condition, and an optimal management strategy capable of improving the yield, saving water and fertilizer resources and reducing the nitrogen leaching risk is generated.

The invention discloses a self-adaptive fertilizer compensation double-helix fertilizer distributor control system, and relates to the technical field of fertilizer distributors. The data monitoring management center is in communication connection with an information acquisition module, a data processing and analysis module, a fertilizer compensation module, a control decision module, an execution mechanism module and a monitoring and feedback module, all the modules are in electric signal connection, and the information acquisition module is used for collecting farmland environment data and crop growth data and sending the farmland environment data and the crop growth data to the data processing and analysis module. And the collected farmland environment data and crop growth data are transmitted to a data monitoring management center in real time. By monitoring the soil nutrient content and the crop growth state in real time and combining the calculation result of the fertilizer compensation module, the fertilizer application amount, the fertilizer application speed and the fertilizer application time are accurately adjusted, nutrient waste is avoided, and it is ensured that crops obtain needed nutrients in different growth stages.

The invention discloses transplanting equipment for traditional Chinese medicine planting, which comprises an intelligent crawler and two fixing plates, the two fixing plates are oppositely arranged on the left side of the intelligent crawler, the intelligent crawler and the two fixing plates are jointly provided with a transplanting assembly, and the transplanting assembly comprises a plurality of exhaust pipes. And a gas diversion groove is formed in the bottom in the fixed plate. When the improved traditional Chinese medicine transplanting equipment is used, seedling lifting operation of traditional Chinese medicine plants can be automatically completed through control of a control host in the intelligent crawler, then pit digging operation of a planting field is completed through angle adjustment of a fixing plate and movement of a stirring plate, and backfilling and compaction operation of pit soil is completed through inversion of the fixing plate; the operation of injecting the soil nutrient solution near the roots of the traditional Chinese medicine plants is completed, finally the transplanting of the traditional Chinese medicine plants is completed, the automation degree of the device is high, and the working intensity of operators can be greatly reduced.

The invention provides a soil nutrient content prediction method and system, and relates to the technical field of soil nutrient circulation.The soil nutrient content prediction method comprises the steps that to-be-detected soil sample data are obtained, the to-be-detected soil sample data are input into a soil nutrient content prediction model, and prediction parameters of target nutrients in a to-be-detected soil sample are obtained; wherein the soil nutrient content prediction model is a model obtained after training of a joint random forest algorithm and a depth distribution function. And based on the prediction parameter of the target nutrient, obtaining a prediction result of the target nutrient in the to-be-detected soil sample data so as to evaluate change characteristics of the target nutrient in the current to-be-detected soil sample data. On the basis, the problems that in the prior art, in the aspect of deep soil nutrient prediction, the data quality is low, and the sample size is limited can be solved, the effectiveness and accuracy of deep soil nutrient prediction are improved, and the blank in the prior art is filled up.

A soil moisture and fertility sensor system is presented that includes a plurality of probes and a monitoring system. The plurality of probes are configured to make nutrient, moisture, and / or other measurements of the soil at a plurality of depths. The monitoring system is communicatively connected to the plurality of probes and configured to receive data related to the measurements of the soil from the plurality of probes. In one or more arrangements, the monitoring system is configured to track soil status based on the data to facilitate review of and management of soil nutrient and / or moisture levels.