656 results about "Soil nutrients" patented technology

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 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 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 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 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 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 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 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.

The invention discloses a soil fertilizer nutrition customization regulation and control method and system. The system comprises a data acquisition module, an environment compensation module, a soil nutrient dynamic prediction module, a target demand management module, a multi-target optimization module, a safety evaluation module, a monitoring self-adaptive learning module and the like, soil nutrition and safety indexes and external environment factors are acquired, data are corrected by using a compensation function, nutrient changes are predicted, a target range is set according to different growth stages of crops, and a monitoring self-adaptive learning module is established. A multi-objective optimization model is established based on organic fertilizer contribution and missing nutrients, an optimal formula is generated by comprehensively considering crop requirements, cost and environmental risks, and the model is dynamically updated through continuous monitoring and feedback closed loop after fertilization. According to the method, the fertilizer utilization rate and the fertilization precision can be remarkably improved, the soil acidification and heavy metal risks are reduced, and the balance of yield, quality and ecological safety is achieved.

The invention discloses a regulation and control method and system for rice production, relates to the technical field of agricultural production and intelligent control, is used for solving the problems of low production efficiency, uneven crop growth and unstable quality, and calculates a light-temperature matching coefficient through real-time monitoring of a root activity index and a leaf surface transpiration amount in combination with illumination intensity and canopy temperature difference. The nutrient absorption capacity of the rice is evaluated by detecting the rhizosphere conductivity change and the soil nutrient content, when the rice growth state is poor and the resource regulation capacity is high, an enhanced regulation and control mechanism is automatically entered, and regulation and control increasing levels are set according to the current rice canopy carbon dioxide exchange rate and the current air flow disturbance index; the resource supply coefficient is calculated and the regulation rate is determined through regulation and control level increase, so that the resource supply is optimized, and the agricultural production efficiency and the resource utilization rate are improved.

The invention discloses a bacillus AH83 capable of resisting saline and alkaline and promoting growth and application thereof, and belongs to the technical field of microbiology and biology, the bacillus AH83 is preserved in the China Center for Type Culture Collection with the preservation number of CCTCC No: M 20241495, and the bacillus AH83 is preserved in the China Center for Type Culture Collection with the preservation number of CCTCC No: M 20241495. The AH83 provided by the invention is a new species of bacillus, can inhibit the growth of pathogenic bacteria of cotton fusarium wilt, and has the growth promoting functions of dissolving potassium, generating indoleacetic acid, cellulase, protease, siderophore and the like; meanwhile, the AH83 can survive in a highly saline-alkaline environment, can promote agronomic characters such as plant height, biomass, leaf area and root development in a corn seedling stage when applied in saline-alkaline soil, can also increase soil nutrients and enzyme activity content, and has a promoting effect on lavender seed germination. The strain is of great significance in improving crop yield and stress resistance and developing novel agricultural microbial agents.

The invention discloses a method for estimating total nitrogen of soil of different plough layers based on a field in-situ spectrum, and relates to the technical field of crop growth monitoring. Collecting soil samples of different plough layers in a field, and obtaining in-situ spectral data of soil; performing indoor analysis on the collected soil sample, and determining the total nitrogen content, the soil texture type and the porosity; classifying the soil samples according to the soil texture types, and respectively establishing correlation models between the total nitrogen contents of the soil with different textures and the in-situ spectral data; introducing a northern eagle optimization algorithm to improve a random forest and a generalized regression neural network to improve the prediction capability of the correlation model on the total nitrogen content of the deep soil; and constructing a comprehensive monitoring model by combining a surface spectrum inversion result and a soil vertical variation equation, so as to realize indirect high-precision estimation of the total nitrogen content of the soil in different plough layers. And a theoretical basis is provided for future soil total nitrogen deep monitoring model research, and a technical support and a theoretical decision are provided for rapid acquisition of deep soil nutrients in precision agriculture.

The invention relates to a smart orchard water and fertilizer intelligent management method and system, and the method comprises the steps: obtaining orchard environment monitoring data with a collection timestamp; performing space-time alignment on the precipitation and the soil humidity to obtain precipitation monitoring data and soil humidity monitoring data; acquiring target soil humidity of crops and determining irrigation volume, and distributing irrigation time according to parameters of irrigation equipment; and determining the fertilization amount according to the target yield, the target unit yield nutrient absorption amount and the soil available nutrients. The problems of resource waste and soil degradation caused by extensive traditional water and fertilizer management can be solved.

The invention relates to the field of agricultural data analysis, in particular to a straw returning effect analysis method combining soil nutrients and crop yield, and the method comprises the steps: collecting a multi-source feature data matrix for risk assessment; performing conjoint analysis on the crop yield data and the soil attribute data to obtain a static nitrogen deficiency risk amplification factor; performing difference analysis on the vegetation index data, the yield data and the cluster centroid to obtain a dynamic growth response asymmetric regulatory factor; carrying out fusion evaluation on the static nitrogen deficiency risk amplification factor and the dynamic growth response asymmetric regulation factor to obtain risk perception asymmetric distance measurement based on yield data; the clustering process of risk perception asymmetric distance measurement based on yield data is subjected to zoning optimization, and an optimal management zoning result for formulating a variable fertilization strategy is obtained, so that the nitrogen deficiency risk of crops in the seedling stage is reduced, and the nutrient utilization efficiency and the yield stability are improved.

The invention discloses a fertilization recommendation method combined with a rice seedling raising fertilizer carrying technology in the technical field of agricultural production. The fertilization recommendation method comprises the following steps: S1, acquiring geology and seedling raising states; s2, presetting rice growth requirements; s3, calculating to obtain an additional nutrient amount; s4, dividing the growth cycle of the rice; s5, recommending the fertilization amount according to stages; according to the method, nutrient supply of seedling raising fertilizer is brought into a whole-growth-period fertilization plan, and accurate matching is achieved; on the premise that the yield is not affected, the fertilizing amount in the early and whole growth periods of rice is remarkably reduced, and the fertilizer utilization rate is increased; through dynamic matching of the early-stage fertilizer loading and supplying amount and the middle and later-stage fertilizer needing amount, resource waste caused by excessive fertilization is avoided, and the fertilizer cost is reduced; the nutrient proportion is scientifically distributed according to the nutrient absorption efficiency of each stage, and the fertilizer utilization rate is increased; the final yield can be improved; soil fertility indexes and historical data are combined, the profit and loss trend of soil nutrients is recognized, and cyclic utilization of the soil nutrients is achieved through dynamic matching of the sustained and controlled release fertilizer and the organic fertilizer.

The invention relates to the technical field of agricultural machinery, in particular to a crop layered fertilization intelligent precision plowing and sowing machine which comprises a rack, a walking driving part is arranged on the rack, a sowing machine is arranged on one side of the rack, a bearing frame is fixedly connected to the side, away from the sowing machine, of the rack, and a plurality of rotary tillage assemblies are transversely arranged on the bearing frame at equal intervals; a plurality of fertilization assemblies capable of vertically sliding are arranged at the bottom of the side, close to the rack, of the bearing frame, transmission assemblies are arranged between the soil retaining assemblies and the fertilization assemblies, and the transmission assemblies are used for reducing the impact force of the soil particles raised by the rotary tillage assemblies to the soil retaining assemblies and reducing the impact force of the soil particles raised by the rotary tillage assemblies to the fertilization assemblies. Transmission is converted into driving force for the height of the fertilizing assembly. The soil texture is fed back through the impact force of soil particles raised by rotary tillage and soil disturbance, so that the layered fertilization depth is adjusted in a linkage manner, and the defects of poor adaptability between the fixed layered fertilization depth and different soil properties and soil nutrient loss in traditional tillage and sowing are overcome.

The invention discloses a method for preparing a fertilizer special for spring corn crops under straw returning, and belongs to the technical field of corn planting. According to the method, soil nutrient testing and the yield increasing effect of fertilization on crops are combined, and the nutrient supply level of soil is truly reflected; the habitual fertilization of farmers is optimized under the condition of comprehensively considering the nutrients brought in by the straws of previous crops, the nutrient release rate and the nutrient effectiveness of the straws, the relatively high carbon-nitrogen ratio under straw returning, and the apparent balance of phosphorus and potassium in the soil of a producing area. Compared with traditional farmer habitual fertilization, the optimized recommended fertilization formula provided by the invention not only contains previous crop straw nutrients, but also provides a special fertilizer formula for a main growth stage. The formula of the special crop fertilizer for the spring corn planting system under straw returning not only can improve the yield of crops, but also can improve the utilization efficiency of nutrients.

The invention relates to the technical field of information management, in particular to a smart agriculture precision big data information management system, which comprises a growth index extraction module, a stage data clustering module, a nutrient fluctuation identification module, an agricultural material strategy generation module and a scheduling information scheduling module. According to the method, the acceleration criterion is constructed based on the continuous period leaf area index change sequence, transition node identification is completed in combination with the photosynthetically active radiation utilization rate and the nitrogen absorption rate change trend, accurate positioning of crop growth stage change time points is achieved, the stability of stage classification in a space region is enhanced, and the accuracy of crop growth stage classification is improved. The agricultural material putting grade is judged and the fertilization frequency and dosage are blended by analyzing a root zone soil nutrient concentration difference value and a rate fluctuation frequency detection mode in combination with moisture content and root activity conditions, and operation period adjustment is guided in a task schedule in cooperation with a meteorological element fluctuation rate. The precision of farmland crop stage identification and the timeliness of nutrient fluctuation response are integrally improved.

The invention relates to the technical field of saline-alkali soil improvement and microorganisms, in particular to bacillus pumilus S3-9 and application thereof. The bacillus pumilus S3-9 is preserved in the China General Microbiological Culture Collection Center on December 19, 2024, and the preservation number of the bacillus pumilus S3-9 is CGMCC (China General Microbiological Culture Collection Center) No. 33120. The bacillus pumilus S3-9 provided by the invention has the effects of reducing salinity in saline-alkali soil, increasing nutrients of the saline-alkali soil and improving the diversity and stability of rhizosphere microbial communities of the saline-alkali soil, and can be applied to improving soil fertility, promoting nutrient circulation, improving soil quality, relieving soil salinization and the like. The strain can also be used for increasing the yield of sweet sorghum in saline-alkali land, has a remarkable growth promoting effect on plant height, overground part fresh weight and underground part fresh weight, can effectively improve the K < + > / Na < + > ratio, chlorophyll content, superoxide dismutase activity and catalase activity, and is beneficial to enhancing the adaptive capacity of plants to salt stress.