5526 results about "Plant growth" patented technology

The invention provides a soybean planting fertilization management system, and relates to the technical field of management systems.Soil physicochemical properties, a meteorological microenvironment, a plant growth state and agricultural machinery operation data are collected in real time through a field sensor network and an unmanned aerial vehicle multispectral imaging technology, and a farmland dynamic portrait is constructed; the intelligent decision-making unit uses a deep learning model and a GLCM texture analysis technology to dynamically identify plant nutrient deficiency pathological characteristics, determines a nutrient deficiency type in combination with an element concentration threshold and triggers early warning; the scheme decision module dynamically optimizes the nitrogen-phosphorus-potassium ratio through a reinforcement learning algorithm, generates a field-level fertilization prescription map by using Kriging interpolation, recommends the optimal fertilization opportunity and dosage, and the precise execution module is linked with a variable fertilizer applicator to realize integrated precise application of water and fertilizer. The user interaction module supports remote monitoring and intervention of farmers through a GIS visual interface and a mobile terminal APP, can dynamically adapt to environmental changes and crop requirements, and significantly improves the nutrient utilization efficiency.

The invention discloses a garden landscape plant health assessment method, and belongs to the technical field of resource assessment. Comprising the following steps: step 1, constructing a time sequence database of environmental factors and plant growth states; step 2, according to different plant species and growth stages thereof, dynamically calculating and generating a health reference value adapted to the current environmental condition; step 3, in the optimal evaluation time window, performing preliminary evaluation on the plant health condition, extracting original health indexes, and performing correction in combination with an environment disturbance compensation factor; step 4, performing double comparative analysis on the corrected health assessment result, eliminating false anomalies caused by environmental fluctuation, and calculating an anomaly confirmation credibility index; step 5, grading the plant health conditions, visually displaying the plant health conditions in a thermodynamic diagram form, and marking the environmental interference degree; and step 6, based on an evaluation result, automatically generating a targeted maintenance suggestion, and designing a corresponding maintenance effect verification scheme.

The invention relates to the technical field of agricultural production data prediction, and discloses a tobacco plant number prediction method based on deep learning, and the method comprises the steps: collecting tobacco field environment data through a soil humidity sensor, a weather sensor, a laser radar point cloud sensor, a multispectral sensor and other multi-source agricultural sensors, carrying out the multi-source feature fusion through a dynamic feature selection network, and generating an environment feature vector. And inputting the model into a multi-modal time sequence prediction model adopting a space-time attention mechanism, and modeling a tobacco plant growth trend. And constructing an adaptive weighted regression model according to a prediction result, and dynamically adjusting the weight by using an improved particle swarm optimization algorithm. And constructing a hierarchical correction model to optimize prediction data. A real-time prediction updating method is provided, and newly-added data can be processed. The multispectral sensor data is subjected to dimension reduction, correlation modeling and interpolation fusion processing. According to the method, multi-source data is fully utilized, the accuracy, real-time performance and stability of tobacco plant number prediction are improved, and powerful support is provided for tobacco planting management.

The invention relates to the technical field of agricultural science and technology, in particular to a leaf disease and pest identification method and system based on image processing, and the method comprises the following steps: setting multispectral and thermal imaging equipment, collecting multispectral images and thermal imaging data of a target frequency band, deleting images with insufficient definition and data with excessive noise, obtaining optimized multispectral images, and obtaining the leaf disease and pest identification result. And marking and classifying the data according to the collected date to form a time sequence image data set. According to the method, the network parameters are dynamically adjusted to reflect the state of each stage of leaf growth, so that the pest and disease damage prediction is not only based on static data, but also reflects the actual change of plant growth, and the real-time application value and accuracy of the prediction model are improved; the introduction of state transition learning enables the transition from health to each stage of pest and disease damage to be predicted more accurately, carries out early diagnosis and timely intervention, improves the recognition precision of the specific position of the pest and disease damage, can carry out local processing, and effectively improves the pertinence and economic efficiency of the processing.

The invention provides bacillus and application thereof, the bacillus is preserved in Guangdong Microbial Culture Collection Center on June 6, 2025, and the preservation number is GDMCC No.66483; one application of the bacillus is to prepare a preparation for promoting growth and / or resisting diseases of plants, and the other application is to use the bacillus for inhibiting microorganisms; the bacillus can effectively and enduringly inhibit the growth of phytopathogen, and can be used as a broad-spectrum antibacterial biological antibacterial agent to enhance the resistance of plants and promote the growth of the plants.

The invention discloses an optimization method for spatial distribution of garden plants, which comprises the following steps: generating a high-precision 3D model of a garden terrain by adopting a plant spatial adaptive layout algorithm and utilizing a laser radar or unmanned aerial vehicle technology, generating a weight matrix according to soil types, illumination intensity and drainage characteristics, and applying a dynamic weight Voronoi algorithm in the terrain model to optimize the spatial distribution of the garden plants. The method comprises the following steps: generating a planting range of each plant, establishing a root distribution model by using an underground imaging technology, simulating distribution dynamic of moisture and nutrients among root systems in combination with underground hydrological data, collecting sensor data in real time by using a wireless network, designing a dynamic irrigation scheme, and optimizing the planting density and irrigation range of the plants. Data such as terrain and climate are integrated into a virtual garden, the virtual garden is ensured to be consistent with an actual state through interaction of a sensor and a digital twinborn model, plant growth, ecological benefit changes and disaster risks are predicted by using the digital model, and a user is allowed to modify and optimize the garden layout in real time through a visual interface.

The invention discloses coal gangue-based artificial ecological soil and a preparation method and application thereof, and belongs to the technical field of ecological improvement, the coal gangue-based artificial ecological soil comprises crushed coal gangue and a compound microbial agent, and the compound microbial agent comprises a microbial activating agent and a microbial passivating agent. According to the invention, the coal gangue can be quickly decomposed through the microbial activating agent, useful mineral elements in the coal gangue can be fully activated and analyzed, and the effect of activating a nutrient library in the coal gangue is achieved, so that useful trace elements contained in the coal gangue are effectively released and are easily absorbed by plant growth; meanwhile, harmful heavy metal elements in the coal gangue are passivated through the microbial passivating fungicide, the water-retaining property and the air permeability of the soil are guaranteed by controlling the decomposition particle size proportion of the coal gangue, the soil conditioner can be used for ecological restoration, desert control, agriculture and animal husbandry planting, flower and nursery planting and urban landscaping, the effects of improving the soil and promoting plant growth are achieved, and the soil conditioner is suitable for large-scale popularization and application. The application is wide.

The invention relates to the technical field of deep learning recognition, and discloses a plant growth state deep learning recognition method and system based on a plant lamp. The method comprises the following steps: carrying out multi-modal data acquisition on a plant growth area by adopting a track type multispectral camera array matched with a fixed LED plant light supplement lamp to obtain a plant image data set and an environment parameter data set; performing feature extraction to obtain a plant growth feature vector; carrying out plant growth state identification and light supplement demand prediction based on a multi-task deep learning model of an improved Transform architecture, and obtaining a plant growth stage discrimination result and light supplement demand spatial and temporal distribution data; and an initial light supplement parameter optimization model is constructed based on the plant growth stage discrimination result and the light supplement demand spatial-temporal distribution data, and an LED plant light supplement lamp illumination parameter sequence is obtained through deep Q network iterative optimization, so that efficient optimization and dynamic adjustment of light supplement parameters are realized, and the light supplement control precision is significantly improved.

The invention discloses a compound fertilizer production nutrient optimization method based on industrial data, relates to the technical field of compound fertilizer production, and firstly solves the problem of unbalanced nutrient release; through the steps S1 and S2, a compound fertilizer production process is decomposed, soil and crop growth related data are collected, an image data processing technology is combined, a plant growth rate Gs and a nutrient supply and demand difference Ns are calculated, and through evaluation of a first supply and demand difference threshold Q1 and a second supply and demand difference threshold Q2, a nutrient release rate is adjusted in time, matching of nutrients and a crop growth cycle is ensured, and the quality of the compound fertilizer is improved. Excessive or insufficient nutrients are avoided; secondly, the trace demand Mn is calculated and evaluated through the step S3, the problem of lack of trace elements is solved, trace element supply is adjusted in time, and it is ensured that crops obtain needed support; and finally, calculating a nutrient loss compensation index Li through the step S4, estimating nutrient loss and adjusting fertilization, so that the applicability of the compound fertilizer under complex climate conditions is improved.

The invention discloses an intelligent garden management method and system based on big data, and belongs to the technical field of garden management. Microclimate region division is carried out on a garden through a clustering algorithm, and the region representative weight of each sensor is calculated in combination with a data heterogeneity response factor and a microtopography interference factor; weighted fusion of sensor data is realized, and a more representative environment estimation value is generated; according to the method, prediction and anomaly detection are carried out on a plant growth environment trend based on time sequence analysis, a garden regulation and control instruction is automatically generated, actual plant state feedback is introduced to realize dynamic optimization and adjustment of a weight, and the method effectively improves the accuracy of environment perception and the intelligent level of decision response, and improves the user experience. And resource misuse and plant health risks caused by information distortion are obviously reduced.

The invention relates to serratia marcescens XJ108 and application thereof, and belongs to the technical field of microorganisms. The serratia marcescens XJ108 is preserved in the China General Microbiological Culture Collection Center (CGMCC), the preservation number is CGMCC No.29557, the preservation date is January 10, 2024, and the address of the preservation institution is No.3, Yard 1, Beichen West Road, Chaoyang District, Beijing. The invention also provides application of the serratia marcescens XJ108 in acid environment, alkaline environment, high salinity environment and high chemical fertilizer environment soil tolerance and plant growth promotion. The serratia marcescens XJ108 provided by the invention has certain biological safety; meanwhile, the plant growth promoting function is achieved; and various extreme soil environments can be tolerated.

The invention relates to the field of monitoring and early warning, and discloses a landscaping maintenance monitoring and early warning system which comprises a garden information acquisition module, a garden image processing module, a normal area analysis module, an abnormal area analysis module, a monitoring and early warning analysis module and a monitoring and early warning output module. The garden information acquisition module is used for acquiring environment data and plant growth data of a garden greening area in real time; the garden image processing module obtains an image of a landscaping area through a camera or an unmanned aerial vehicle, and carries out image processing and analysis; the normal area analysis module analyzes and defines the standard of a healthy area according to the collected data and historical data; the abnormal area analysis module compares the normal area with other areas, and analyzes an abnormal area; and the monitoring and early warning analysis module synthesizes data from normal area analysis and abnormal area analysis to perform intelligent early warning analysis. The method has the advantage of providing accurate early warning.

The invention relates to the technical field of plant cultivation, and discloses a dynamic regulation and control method, system and device for a plant growth environment and a storage medium. Inputting the image data into a growth recognition model to obtain a growth stage and a growth state of the plant; according to the growth stage, obtaining a soil temperature and humidity optimal value of the plant growth environment by adopting a response surface method, and inputting the environment data into the temperature and humidity prediction model to obtain a soil temperature and humidity prediction value; and comparing the predicted soil temperature and humidity value with the optimal soil temperature and humidity value, and regulating and controlling the soil temperature and humidity of the plant growth environment according to a comparison result. According to the method, through refined environment management, temperature and humidity, illumination and pest control required by plant growth are dynamically regulated and controlled, global management and accurate regulation and control of the cultivation process are achieved, the intensification and intelligence level of the whole cultivation method is improved, and cost reduction and efficiency improvement of plant cultivation are achieved.

The present disclosure provides a method for assisting users in plant cultivation, including: determining a pruning plan according to a plant species and a pruning goal, and determining whether to display the pruning plan to the user according to the current season and / or the plant growth stage, wherein the pruning plan includes a pruning approach and a pruning position; and in response to determining to display the pruning plan to the user, depicting the pruning approach and the pruning position in combination with the image of the plant to display the pruning plan to the user. The present disclosure also relates to a device for assisting users in plant cultivation and a non-transitory computer-readable storage medium.

The invention discloses an acid mine wasteland ecological restoration plant dynamic optimization configuration method, and relates to the field of ecological restoration, and the method comprises the following steps: 1, collecting soil attribute data in a predetermined range of an acid mine wasteland in a dotted manner, and synchronously obtaining growth attribute data of to-be-selected plants and periodic weather data of a target area; step 2, extracting a deterioration feature set having a deterioration effect on plant growth based on the soil attribute data, and analyzing a bioremediation feature set capable of inhibiting the deterioration feature in the plant attribute data to generate a candidate plant set; 3, constructing a dynamic environment simulation model based on a deep learning algorithm, wherein input dimensions comprise weather data time sequence features, soil deterioration feature vectors and a plant bioremediation feature matrix; the method can accurately predict the restoration effects of plants under different climate and soil conditions, simulate the effects of different intervention measures in real time, output the optimal intervention scheme, and ensure the balance between the resource utilization efficiency and the restoration effects.

The invention discloses a soil element spectrum detection analysis method and system based on machine learning, and belongs to the technical field of smart agriculture. Field soil element data, plant growth data and environment data are obtained, and an element mineralization release model, an element loss model, a plant absorption model and a pollution element influence model are constructed; the method comprises the following steps: evaluating element mineralization release amount, plant element absorption amount and influence of harmful elements on plant absorption, constructing a soil element content prediction model, introducing the mineralization release amount, element loss amount, plant absorption amount and pollution element influence into the soil element content prediction model to calculate future soil element content, and constructing a fertilization time prediction model. The future soil element content is introduced into the fertilization time prediction model to evaluate the fertilization time, the fertilization time is predicted by coupling the soil element dynamic evolution and plant growth absorption and combining the nutrient demand characteristics of the plant in different growth states, and the plant planting fertilization efficiency is improved.

The invention discloses an intelligent water and fertilizer integrated irrigation system based on an Internet of Things sensor and a large language model, and relates to the technical field of intelligent agriculture. The system obtains soil, weather and plant growth state data in real time through Internet of Things sensors, including a soil sensor, a weather sensor and a multispectral sensor, deployed in a farmland; the method comprises the following steps: based on a large language model architecture, integrating preset agricultural field knowledge base data, performing field adaptive fine tuning on model parameters by adopting a data migration technology, and constructing an intelligent irrigation control model with a dynamic decision-making function; the control model analyzes sensor data and crop growth requirements, generates a water and fertilizer supply strategy, calls an internet-of-things control interface of the water and fertilizer all-in-one machine, and automatically adjusts irrigation water quantity and proportional supply of nutrient elements such as nitrogen, phosphorus and potassium. According to the invention, Internet of Things perception and large model decision are fused, and different environments are adapted through fine adjustment, so that closed-loop precise control is realized, and the water and fertilizer utilization rate and the crop yield are remarkably improved. Actual measurement shows that the system can improve the water and fertilizer utilization rate by 30% or above, and the crop yield is increased by 15-20%.

The invention relates to the technical field of water environment treatment, in particular to a water environment ecological treatment method and system based on a constructed wetland, and the method comprises the following steps: measuring the dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, water temperature and pH value of a root zone in the constructed wetland, and calculating the pollutant concentration distribution value and plant root system distribution density of each monitoring point; and obtaining a water quality root distribution characterization value. In an artificial wetland environment, the concentration of dissolved oxygen, the concentration of ammonia nitrogen, the concentration of total phosphorus, the water temperature and the pH value of a root zone are measured, the concentration distribution of pollutants is calculated, numerical calculation is carried out in combination with the distribution density of plant root systems, water quality root system distribution characterization is constructed, spatial heterogeneity analysis of wetland water quality is enhanced, and the targeting of pollutant degradation is optimized. Based on water quality root system distribution characterization, plant growth cycle parameters are calculated in combination with water quality parameters, association between water quality dynamic changes and plant growth states is constructed, and the adaptability of wetland ecological regulation and control is improved.

The invention discloses a cultivation method for rapid vernalization of winter wheat to accelerate annual iteration, and belongs to the technical field of plant growth regulation and control. The cultivation method comprises the following steps of disinfection and germination, low-temperature vernalization, transplanting and cultivation, and drying and harvesting. The method has the beneficial effects that compared with other current wheat growth acceleration methods, the technical process and the required environment of each stage are simple, and the (semi) winter wheat breeding efficiency is greatly improved. The temperature or photoperiod does not need to be repeatedly adjusted, and vernalization can be performed by adopting short photoperiod / low illumination intensity, so that energy is saved, and the method is environment-friendly and suitable for large-scale popularization. The cultivation method is green, efficient, low in power consumption, low in requirement for environment equipment and simple and convenient. The method is suitable for being used in large-scale plant factories, and meanwhile, a method for rapid vernalization of winter wheat to accelerate annual accelerated iteration of wheat is provided for scientific research institutions, enterprises and public institutions with limited conditions.

The invention relates to the technical field of intelligent monitoring, and particularly discloses an image-based plant growth cycle monitoring system and method, which is characterized in that plant leaf image sets at different growth stages are acquired in advance, and an image processing technology based on deep learning is introduced; image feature extraction and prototype feature extraction aggregation analysis are carried out on the plant leaf image set of each growth stage to capture plant leaf prototype image features of each growth stage, and then leaf feature matching analysis is carried out on a plant image to be identified by taking the plant leaf prototype image features of each growth stage as a reference to obtain a plant leaf feature matching result; therefore, the current growth stage of the plant can be quickly judged, and targeted fertilization management can be conveniently carried out on the plant. By means of the mode, intelligent monitoring of the plant growth cycle can be achieved, effective guidance is provided for fertilization management of plants, and then scientificity and accuracy of fertilization management are improved.

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 discloses landscaping cultivation equipment, and belongs to the technical field of greening cultivation, the landscaping cultivation equipment comprises a base, the upper side of the base is provided with a water leakage plate, the upper end of the water leakage plate is slidably provided with a plurality of side plates, one end of each side plate is fixedly provided with a first sliding block for sliding, and one side of each side plate is provided with a first sliding groove; the side plates provided with the first sliding blocks are slidably connected with the first sliding grooves in the adjacent side plates, planting cavities used for planting plants are formed among the side plates, grooves are formed in the lower ends of the side plates, adjusting assemblies are installed in the grooves and used for adjusting the positions of the water leakage plates, and a plurality of limiting assemblies are further installed at the upper end of the base. The side plates can automatically move outwards when plants grow, so that the space of the planting cavity is enlarged, the planting pot does not need to be replaced, the situation that the plants cannot adapt to the planting pot due to pot replacement is reduced, the step of pot replacement in the planting process is also reduced, and the planting efficiency is improved. The planting is simpler and more convenient.

The invention relates to the field of microorganisms, in particular to a mortierella alpina strain MA with a plant growth promoting function and application of the mortierella alpina strain MA. The strain has remarkable nitrogen fixation, siderophore production, auxin (IAA) production and cellulase activity, can inhibit various soil-borne pathogenic bacteria such as phytophthora capsici and fusarium, and remarkably improves the disease resistance and growth performance of crops such as pepper. The strain has various functions and broad-spectrum action, is suitable for replacing part of chemical fertilizers and pesticides in intensive agriculture, and realizes green and efficient planting of crops.

The invention discloses two phosphate solubilizing bacteria and application of microbial agents thereof, and belongs to the technical field of microorganisms. The preservation number of the bacillus cereus Sau.XJ-4 is CCTCC (China Center For Type Culture Collection) NO: M 20242890; the preservation number of the arthrobacter sp. Sau.XJ-5 is CCTCC (China Center for Type Culture Collection) NO: M 20242891. The bacillus cereus Sau.XJ-4 and the bacillus cereus Sau.XJ-5 have the characteristics of saline-alkali resistance, aluminum resistance and the like, insoluble inorganic mineral substances such as tricalcium phosphate can be effectively decomposed, insoluble nutrient elements such as nitrogen, potassium and phosphorus in soil are promoted to be converted into soluble nutrients, the content of available nutrients in the soil is increased, and the yield and the quality are improved; the fertilizer can also relieve aluminum stress of plants and promote growth and development of the plants, and has important significance for fully exerting soil ecological fertility and keeping balance of an agricultural ecological environment.

The invention discloses a plant seed seedling raising light environment optimization system and method based on an LED light source, and belongs to the technical field of seed seedling raising. The invention discloses a plant seed seedling culture light environment optimization system and method based on an LED light source. The system comprises a light environment monitoring unit, a light environment optimization unit and a cooperative regulation and control unit. The problem of limitation in the prior art is solved, the light environment monitoring unit monitors light environment parameters of seedling raising in real time, data support is provided for follow-up light environment optimization, the light environment optimization unit conducts analysis according to light environment data provided by the light environment monitoring unit, and the light environment monitoring unit monitors the light environment parameters of seedling raising in real time. The light environment parameters of plant seed seedling raising are dynamically adjusted, it is ensured that plants obtain the optimal growth condition, the cooperative regulation and control unit analyzes the interaction relation between the light intensity, the light quality, the illumination duration and the temperature and humidity by combining light environment data, and therefore cooperative regulation and control over the light environment and the environment parameters are achieved. And more ideal environmental conditions are created for plant growth.

The invention discloses a shallow lake submerged plant planting matrix and an efficient planting method. The method comprises the steps of submerged plant planting matrix preparation, seedling preparation, culture and maintenance and seed throwing. The planting substrate comprises the following components in percentage by weight: 54-74% of common soil; 12 to 33% of sediment; 11-12% of river sand; 1% of kaolin; after the raw materials are uniformly mixed, a small amount of water is added for multiple times, so that the sticky planting substrate is formed. Propagules such as submerged plant seedlings, buds and seeds are wrapped with the planting substrate. The submerged plants and the planting substrate form a stable whole body which is not easy to separate; after the plant seedlings are maintained and cultivated for 5 days, the submerged plant seedlings are thrown and planted in the lake water area. A small amount of degradable environment-friendly substrate raw materials are added, so that the strength and toughness of the planting substrate can be improved, the substrate can be kept in water until the submerged plants are stable in rooting and germination, necessary nutrient elements can be provided for growth of the submerged plants, and rapid and stable growth of the submerged plants is promoted.

The invention relates to the technical field of soilless culture nutrient solution dynamic optimization, and particularly discloses a soilless culture nutrient solution dynamic optimization method which comprises the steps of multi-source fusion monitoring data set generation, main nutrient element demand prediction, nutrient solution adjustment instruction set generation and nutrient solution adjustment effect evaluation. According to the invention, environment, plant physiology and nutrient solution state data are synchronously acquired, a short-term demand prediction model is utilized to predict nutritional demands, and an adjustment instruction set containing the supplement amount and supplement rate of the current nutrient solution is generated in combination with a plant growth stage, a current nutrient solution state and an environment factor; the adjustment effect of the nutrient solution adjustment instruction set is obtained by comprehensively evaluating the improvement degree of the plant physiological status and the stability of the nutrient solution after adjustment is finished; dynamic matching of nutrient solution supply and plant requirements is achieved, the nutrient utilization efficiency is improved, the adaptability of the system to environment changes is enhanced, and remarkable economic benefits and social benefits are achieved.

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 belongs to the technical field of agricultural microorganisms, and particularly relates to pseudomonas fluorescens as well as a microbial agent and application thereof. The invention discloses a pseudomonas fluorescens TJ194, which is preserved in the China General Microbiological Culture Collection Center (CGMCC), and the preservation number is CGMCC No.33697. The pseudomonas fluorescens TJ194 has the advantages that the pseudomonas fluorescens TJ194 can be used for preparing the pseudomonas fluorescens TJ194, and the pseudomonas fluorescens TJ194 can be used for preparing the pseudomonas fluorescens TJ194; tests prove that the strain has the activity of inhibiting the growth of fusarium pseudograminearum; by applying a fungicide containing the strain, the disease index of the wheat stem rot is remarkably reduced, and meanwhile, the fresh weight of the overground part and the underground part of wheat is increased, so that the pseudomonas fluorescens TJ194 and the fungicide thereof can be applied to prevention and treatment of the plant stem rot and promotion of plant growth.

The invention discloses a method for improving pasture productivity by optimizing a mixed sowing proportion and a sowing mode, which comprises the following steps of: performing rotary tillage on soil and applying humus before freezing in winter, turning over the soil and applying a base fertilizer after reviving in spring, then selecting leguminous plants and gramineous plants according to a weight ratio of 3: 7, respectively and uniformly mixing seeds of two functional groups, the method comprises the following steps: ditching, ridging and sowing gramineous plant seeds in line, sowing leguminous plant seeds in holes between two rows of gramineous plants 20-30 days after the gramineous plant seeds emerge, carrying out topdressing and pest and weed damage management after sowing, mowing the overground part of the grassland at the last stage of plant growth, and controlling the stubble height of the leguminous plants and the gramineous plants. By accurately optimizing the mixed sowing proportion and sowing strategy of leguminous and gramineous pasture and combining the complementarity of plant functional groups in ecological niche (time and space), an innovative pasture mixed sowing method is provided, and theoretical support and technical guarantee are provided for efficient and sustainable development of animal husbandry production.