4846 results about "Growth plant" 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 present invention provides a construction method suitable for vegetation restoration of a bare rock slope, characterized by comprising the following steps: S1, preparation of a treatment area: before actual construction, preparing an area to be treated using a combination of mechanical and manual means; S2: providing a plant vine climbing net; S3: anchor rod construction: implementing on a rock slope surface with an inclination greater than 75°, wherein the slope surface should be drilled from top to bottom, the depth of the drilling is determined according to properties of the rock, a self-spinning resin anchor rod is fixed in a drilled hole on the slope surface with cement slurry, leaving a small part for hanging a galvanized gabion multidimensional mesh cage; S4: building a plant growth chamber, a gabion retaining wall and a construction system apparatus; S5: filling a matrix; S6: vegetation arrangement: selected dominant plant species must be drought-tolerant, barren-tolerant and fast-growing, and have strong sprouting ability and coverage capacity. The present invention integrates slope protection, intelligent water collection, water storage and drip irrigation apparatuses, matrix improvement, and vegetation arrangement, thereby ensuring the effectiveness of the restoration.

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 discloses an ecological garden intelligent management method and system, and belongs to the technical field of landscaping management, and the method specifically comprises the steps: monitoring environmental parameters in real time through multiple sensors, and uploading the environmental parameters to a cloud server; at the cloud end, a dynamic data analysis model is constructed by utilizing historical irrigation data, a plant growth model and real-time monitoring parameters, the water demand of plants is predicted, and an irrigation decision is made; an irrigation threshold value is set according to the decision, and an irrigation program is automatically started and executed through remote control equipment; after irrigation, detailed information is recorded and fed back to the data analysis model, the irrigation effect is evaluated by adopting a data analysis method, and an irrigation decision is finely adjusted accordingly; intelligent and precise irrigation management is realized, and the utilization efficiency of water resources and the growth quality of plants are improved.

The invention relates to paenibacillus polymyxa FangSG106 as well as application, a product and a method thereof, and belongs to the technical field of microorganisms. The invention provides paenibacillus polymyxa FangSG106, the preservation number of the paenibacillus polymyxa FangSG106 is CGMCC (China General Microbiological Culture Collection Center) No.31655. The invention also provides application of the paenibacillus polymyxa FangSG106 with the preservation number of CGMCC No.31655 in the aspects of non-treatment-destination bacteriostasis, plant disease prevention and treatment and plant growth promotion, and based on the paenibacillus polymyxa FangSG106, the application of the paenibacillus polymyxa FangSG106 in the aspects of non-treatment-destination bacteriostasis, plant disease prevention and treatment and plant growth promotion is The invention provides a plant growth promoter, a biopesticide, a method for preventing and treating plant diseases, a method for promoting plant growth and a bacteriostasis method. The paenibacillus polymyxa FangSG106 disclosed by the invention has broad-spectrum antibacterial activity, and can be used for effectively preventing and treating plant diseases and promoting plant growth.

To provide novel plant environmental stress alleviator and plant growth promoter having an excellent effect of reducing environmental stress such as high temperatures.SOLUTION: Provided is a plant environmental stress alleviator or a plant growth promoter, which contains a plant extract containing acetylcholine or an acetylcholinesterase inhibitor and calcium ions. Also provided is a method for alleviating plant environmental stress or a method for promoting plant growth by applying the plant environmental stress alleviator or the plant growth promoter to a plant.SELECTED DRAWING: None

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 provides a vegetation greening layout optimization method, and relates to the technical field of environmental engineering and garden design, and the method comprises the steps: carrying out the homologous retrieval through taking a target region plant growth influence factor as a constraint, and obtaining a plant type and a planting density; calculating a high-frequency planting density threshold value of the plant type; inputting the plant types into a type-attribute comparison table for matching to obtain time zone attributes, determining a plant combination and performing adaptive screening; carrying out vegetation layout design based on the adaptive plant combination and the high-frequency planting density threshold to generate an initial layout scheme; constructing a simulated growth environment to perform growth prediction and simulated viewing on the layout scheme; and performing evaluation and feasibility evaluation on the simulated landscape according to the landscape evaluation function, and determining an optimal layout scheme, thereby solving the technical problems that the vegetation configuration cannot be accurately performed and the vegetation growth effect and the landscape aesthetic property cannot be effectively predicted and evaluated due to lack of systematic analysis on the plant growth. The technical effect of improving the accuracy and predictability of the plant layout is achieved.

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 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 relates to the technical field of microorganisms, and discloses burkholderia gladioli as well as a bacterial agent and application of the burkholderia gladioli. The Burkholderia gladioli (Burkholderia gladioli) CCTCC (China Center For Type Culture Collection) NO: M20242288 provided by the invention has good capacities of fixing nitrogen, dissolving phosphorus, dissolving zinc, producing siderophores and oxidizing sulfur, and can be used for regulating the nutrient structure of soil and converting substances which are difficult to utilize by plants in the soil, so that the growth of the plants is promoted, and the stress resistance of the plants is improved; the strain also can be used for antagonizing Fusarium solani, Fusarium equiseti, Fusarium verticillium, Fusarium verticillium and Rosellinia necatrix, can be used for antagonizing Fusarium solani, Fusarium equiseti, Fusarium verticillium and Rosellinia necatrix, and can also be used for antagonizing Fusarium solani, Fusarium equiseti, Fusarium verticillium, Rosellinia necatrix, Fusarium moniliforme and Rosellinia necatrix, Fusarium moniliforme and Rosellinia necatrix. Besides, the burkholderia gladioli provided by the invention is a strain separated from rape farmland soil, and compared with a strain screened by extreme environment and laboratory mutagenesis, the burkholderia gladioli has better adaptability when being applied to a planting environment, and can be stably colonized in plant rhizosphere and soil, so that the burkholderia gladioli stably plays a growth promoting role for a long time, is safe and environment-friendly, and has a wide application prospect. Wide application prospects are realized.

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 the technical field of ecological data processing, in particular to a plant growth evaluation method based on ecological data analysis, and the method comprises the steps: collecting data; determining a temporary grid; soil type identification; identifying an abnormal grid; adjusting a grid; and evaluating the plant growth degree. According to the method, the accuracy of plant growth monitoring is improved through dynamic monitoring and intelligent adjustment, bad growth conditions and abnormal plants can be recognized in time, then targeted intervention measures are provided, the vulnerability of an ecological system is reduced, and meanwhile, the high efficiency and accuracy of data acquisition are ensured through dynamic adjustment of grid spacing and optimization of a monitoring strategy. The method also provides a scientific basis for soil quality and plant health, is helpful for realizing ecological balance, promoting reasonable utilization of resources, improving the stability of an ecological system, and effectively solves the problems of insufficient evaluation comprehensiveness and reduced data acquisition timeliness caused by dependence on a fixed trigger strategy and single data source.

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 belongs to the technical field of microorganisms, and particularly relates to paenibacillus mucilaginosus FangSG101 and application thereof. The preservation number of the paenibacillus mucilaginosus FangSG101 is CCTCC NO: M 20232558, and the paenibacillus mucilaginosus FangSG101 can convert insoluble mineral potassium and mineral phosphorus in soil into quick-acting potassium which can be directly absorbed and utilized by plants, has the capability of generating pathogenic bacterium cell wall hydrolase, has a remarkable promotion effect on seed germination and plant growth of tomatoes and cucumbers, and can be applied to actual agricultural production. Through optimization of a culture medium formula and adjustment of a fermentation process, a bacterial powder product with high viable count and high spore rate is obtained.

The invention belongs to the field of irrigation systems, and provides an intelligent water-saving irrigation system based on the Internet of Things, which comprises a control terminal, and the control terminal comprises a control module, a communication module, a data analysis module and a power supply module; the data acquisition module comprises a meteorological sensor, a soil humidity sensor and a plant growth state monitor which are electrically connected with the communication module; the irrigation execution module comprises an adjustable electric valve and a variable frequency water pump which are controlled in a partition mode, and irrigation operation is conducted according to the instruction sent by the control module; by arranging the control terminal, the data acquisition module and the irrigation execution module, the soil humidity and the plant water demand condition can be accurately sensed, the system can avoid unnecessary irrigation, water resource waste is effectively reduced, full automation and intelligentization of the irrigation process are achieved, manual intervention is reduced, and the working efficiency is improved.

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 discloses a salt and alkali tolerant phosphate-solubilizing growth-promoting bacterium and application thereof, and belongs to the technical field of biology, the salt and alkali tolerant phosphate-solubilizing growth-promoting bacterium is named as Enterobacter hormaechei P03 and preserved in the China Center for Type Culture Collection (CCTCC), and the preservation number is CCTCC No: M 20242250. The enterobacter hormaechei P03 provided by the invention has good salt resistance, acid and alkali resistance, growth promotion and phosphate solubilizing effects, grows well under high salinity, acidic conditions and alkaline conditions, has better phosphate solubilizing capacity, and can generate indoleacetic acid in the growth process to promote plant growth.

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 a microbial compound fertilizer for improving soil pollution, which is prepared by mixing a matrix fertilizer, alginic acid, cellulase, modified bentonite, biochar, a microbial agent, nano zero-valent iron and monopotassium phosphate according to a mass ratio of (30-40): (6-10): (5-8): (20-25): (15-20): (3-5): (4-6): (4-8), the microbial agent comprises pseudomonas, bacillus and silicate bacteria; heavy metal ions in soil can be effectively neutralized through the nanoscale zero-valent iron and the phosphate, pollutants in the soil can be effectively degraded through the microbial flora, meanwhile, nutrients needed by plant growth are provided, the modified bentonite is added, the soil structure can be changed, meanwhile, phosphorus and potassium fertilizers are provided for the soil, and the soil quality is improved. By adding alginic acid and cellulase, the activity of microorganisms is effectively enhanced, the fertility conversion efficiency of the microorganisms is improved, and soil improvement and remediation are achieved.

The invention provides a corridor closed harvesting automatic identification method and system, and relates to the technical field of harvesting, and the method comprises the steps: obtaining environmental parameters in a corridor closed region, calculating the growth condition of plants in a corridor, and obtaining the growth data of the plants; meanwhile, an image of a plant in the corridor is obtained in real time and segmented, a plant area image is obtained, the maturity of the plant is recognized, and plant maturity data is obtained; according to the plant growth data and the plant maturity data, whether the plants in the corridor meet the harvesting condition or not is judged, if the plants meet the harvesting condition, a harvesting execution mechanism is controlled to conduct harvesting operation on the plants in the corridor, harvesting amount data is obtained, and the commodity rate and the inventory are calculated based on the harvesting amount data; environmental parameters in the plant growth model are adjusted, according to the adjusted environmental parameters, the step of calculating the commodity rate and the inventory is repeatedly executed until the commodity rate reaches a preset commodity rate threshold value and the inventory is lower than a preset inventory threshold value, and corridor closed harvesting automatic identification is completed.

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 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.

Vertical hydroponic plant systems and methods are provided herein. The systems may include vertical hanging wall systems, vertical mounted wall systems, seed soaking and / or watering systems, and linear production systems for larger plants. Various methodologies may be employed to provide optimal lighting and nutrients for plant growth.

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.