38 results about "Crop species" patented technology

The invention belongs to the field of computer vision, and discloses a plant disease identification method and system based on a three-branch deep neural network, and the method comprises the steps: firstly extracting global, local and middle-layer multi-scale positioning features through employing Vision Transformer, ResNet50 and YOLO in parallel; secondly, aligning and fusing the three paths of features, carrying out interactive enhancement through Transform block, and then respectively predicting crop types and disease types through a double-end stacking classifier; and finally, by setting a proper loss function combination and a joint training strategy, performing end-to-end optimization on the whole network, so as to improve the recognition capability of difficult-to-judge samples and small-scale lesions. According to the invention, accurate identification of plant diseases in a natural scene can be realized. Experimental results show that the method provided by the invention obtains classification performance equivalent to or even better than that of the most advanced plant disease identification method in the prior art.

The invention provides an intelligent diagnosis and decision-making method and system for crop diseases in intelligent agriculture, and the method comprises the steps: extracting spatial features through employing a convolutional neural network based on standardized remote sensing image data in a unified multi-source data set, generating preliminary positioning data of a scab region, and carrying out the preliminary positioning of the scab region; the scab area preliminary positioning data comprises scab position coordinates and range boundaries; inputting the key time weighted sequence data and the scab area preliminary positioning data into a space-time attention mechanism, and fusing spatial position coordinates and time environment features through attention weight distribution to generate comprehensive disease feature vector data; and based on the preliminary prevention and control prescription data, adopting a drug resistance evaluation model to analyze the drug use frequency, the disease type and the crop variety in the historical drug use data, generating optimized prevention and control prescription data, and adjusting the drug variety or dosage to reduce the drug resistance risk.

A crop species identification system based on satellite telemetry data is disclosed, which includes: a receiver module, receiving plural telemetric vegetation indexes of a target area; a data cleaning module, cleaning anomalous data in the telemetric vegetation indices, to correspondingly generate cleaned index data; a feature extraction module, including at least two different convolution kernels for mapping the cleaned index data into at least two feature scale mapping data which respectively correspond to the convolution kernels, performing a pooling operation of the feature scale mapping data to generate a pooled data, and concatenating the at least two feature scale mapping data and the pooled data into concatenated data; and a classification module, including a fully-connected layer, for extracting features of the concatenated data, to generate a species classification result for the target area.

The invention provides a saline-alkali soil crop multi-water-source irrigation control method and system, and belongs to the technical field of agriculture, and the method comprises the steps: determining an irrigation water salinity target threshold value and a target total irrigation amount according to soil salinity data and crop physiological parameters; determining a water distribution strategy based on the salinity concentration data, wherein the water distribution strategy at least comprises irrigation priorities and collocation of different types of water sources; based on the target irrigation total amount, the irrigation water salinity target threshold value and the water distribution strategy, the target water taking amount of each type of water source is determined; and generating an irrigation control instruction according to the target water intake amount. According to soil salinity, crop types, crop physiological parameters and salinity concentration of multiple water sources, the irrigation water salinity target threshold value and the irrigation water total amount are dynamically and accurately determined; and meanwhile, a priority water distribution strategy is formulated, so that flexible allocation of irrigation among multiple water sources and fine management of the salinity concentration of crop irrigation water can be realized, and soil salinization and crop salinity stress are effectively avoided.

The application provides a crop disease precision identification method and system, and relates to the technical field of crop disease identification. The method comprises the following steps: establishing standard lesion feature image datasets of different crops and different organs; constructing a background feature database of common crop diseases; forming a crop type and organ identification algorithm model and an organ lesion identification algorithm model; determining the crop type and the organ of the crop in an image to be identified based on the crop type and organ identification algorithm model; determining the disease range of the image to be identified based on the organ of the crop and using the organ lesion identification algorithm model corresponding to the organ of the crop, and outputting a lesion disease with similar features; outputting a matched crop disease type based on the background feature database of common crop diseases; and obtaining a common disease type in the determined lesion disease and the determined crop disease type, so as to realize the precision identification of the disease. The application classifies and grades to form a structured disease identification process, and improves the identification precision.

The invention discloses a rice field robot cluster remote cooperative control system based on edge computing, and relates to the field of program control, and the system comprises a master control module which serves as a central control end, issues a control instruction to distributed edge nodes, and receives state feedback; the crop identification module is deployed at an edge node and acquires attribute data of crop types, growth stages and distribution density of each region of the target rice field through an image sensor; the environment acquisition module is used for being deployed at an edge node and acquiring rice field meteorological data and soil environment data in real time; the crop growth environment and the machine state are monitored and responded in real time, when an abnormal environment event is detected, crop identification data can be rapidly integrated to generate an influence event and evaluate an influence coefficient, and a nearby automatic machine is immediately matched and scheduled for intervention, so that the timeliness of operation is ensured, crop loss can be effectively prevented, and the working efficiency is improved. And the efficiency of agricultural production is improved.

The application discloses a method for evaluating rice field and dry land crop removal of soil heavy metal flux based on model estimation, relates to the field of agricultural environmental science and technology, and determines the planting mode characteristics and the estimation range of the crop removal of soil heavy metal flux under various planting modes in a target region through a standardized field test, and constructs a standardized crop heavy metal absorption parameter database, wherein the planting modes include single-cropping rice, double-cropping rice, rice-oil rotation, rice-tobacco rotation and leafy dry land crops, and the planting mode characteristics include planting cycles and crop types. Through the construction of the standardized crop heavy metal absorption parameter database, the combination of the planting mode characteristics and the dynamic change data of the heavy metal form of rhizosphere soil, the removal ability of crops to soil heavy metals can be more accurately quantified, meanwhile, the crop heavy metal absorption parameter database integrates the biomass, heavy metal concentration and flux calibration data, eliminates the interference of environmental variation, and forms a reliable heavy metal removal flux estimation range.

The invention relates to the technical field of laser illumination, in particular to a laser diode agricultural illumination system and method based on a combined spectrum, and the system comprises a light source module, an illumination intensity adjustment module, an illumination time control module, a spectrum monitoring module and a feedback adjustment module. According to light quality requirements of leaf vegetables and solanaceous crops in different growth stages, a spectrum combination proportion is determined, a specific wavelength spectrum is supplemented, illumination intensity is dynamically adjusted according to a plant growth state, illumination time is set according to crop types and growth stages, the spectrum is monitored in real time, optimal parameters are compared, and a spectrum combination is adjusted according to deviation. Spectrum, light intensity and illumination time are accurately matched with crop requirements, light energy waste is reduced, it is guaranteed that crops obtain proper illumination conditions in all growth stages, photosynthesis efficiency is promoted to be improved, and efficient and accurate development of agricultural production is promoted.

The disclosure relates to isolated microorganisms—including novel strains of the microorganisms, microbial consortia, and agricultural compositions comprising the same. Furthermore, the disclosure teaches methods of utilizing the described microorganisms, microbial consortia, and agricultural compositions comprising the same, in methods for imparting beneficial properties to target plant species. In particular aspects, the disclosure provides methods of increasing desirable plant traits in agronomically important crop species.

The invention provides a method for biomimetic directional construction of crop growth-promoting synthetic bacteria and application, and belongs to the technical field of microbial screening. According to the method, optimized microbial communities are naturally selected based on wild sibling species, a species composition feature table is determined through high-throughput sequencing data analysis, core bacteria are calculated, and core bacteria composition feature tables of amplicons and metagenomes are obtained respectively; and then a hybrid correction strategy of a machine learning algorithm is adopted to obtain a high-quality core bacterium composition feature table of the wild related species of the crops, and growth-promoting synthetic bacteria are designed according to the core bacterium composition feature table, so that candidate microorganisms are directionally screened from the wild related species of the crops in a targeted manner, and the growth-promoting synthetic bacteria of the cultivated species of the crops are constructed. According to the method disclosed by the invention, interaction between crop species specificity and synthetic bacteria is considered, the method has the advantages of high efficiency, accuracy, orientation and the like, and construction of crop synthetic bacteria composition is converted from artificial random combination to bionic oriented construction.

The utility model relates to agricultural ploughing technology field, and disclose a kind of ploughing equipment for agricultural planting, the ploughing equipment for agricultural planting, including trolley, the top end surface of trolley is fixedly connected with hydraulic cylinder, the output of hydraulic cylinder is fixedly connected with flat plate, the bottom of flat plate is provided with ploughing assembly.This ploughing equipment for agricultural planting is set up ploughing assembly, ploughing roller carries out ploughing to soil, and soil is pushed apart to both sides by soil frame, while ploughing, fertilizer cylinder is matched with rotary drum, just can synchronously scatter fertilizer into ditch, realize ploughing and fertilization integration, substantially reduce the repeated labor of farmer, improve field operation speed, change the volume of containing cylinder, realize the adjustment of fertilizer spreading amount, farmer can flexibly adjust according to crop type, soil fertility, fertilization demand, accurately control the amount of fertilizer, can avoid overfertilization once, also can avoid too little, adapt to different crops and growth stage.

The application provides an end-cloud cooperative farmland condition image acquisition system based on 5G communication and machine learning, relates to the technical field of end-cloud cooperation of 5G communication and machine learning, and uses a data acquisition end to acquire multispectral image data of a farmland to be observed, carries out compression preprocessing, reduces data transmission burden, and then sends the compressed image to a data processing module; the module carries out denoising and feature extraction on the image, constructs a feature data vector and transmits the feature data vector to a cloud server; the cloud server analyzes the feature data vector by using a random forest algorithm model, judges crop types and carries out classification, and finally returns the analysis result to a data display module; the data display module uses a Flask framework to generate a dashboard, directly and intuitively displays farmland condition data, including key indexes such as crop types and coverage, and realizes end-cloud cooperation architecture through 5G communication for data transmission, so that efficient and real-time data transmission and processing are realized.

The utility model discloses an agricultural planting three-dimensional planting frame which comprises a planting frame and a planting auxiliary frame, the planting auxiliary frame is arranged below the planting frame, and connecting columns are installed at the four corners of the planting frame. According to the three-dimensional planting rack for agricultural planting, through the design and use of the planting auxiliary frames, the planting frames and the connecting columns, when crops are planted, growers can reasonably adjust and utilize the planting space according to seasons and crop types, so that the high space utilization rate is achieved, and the economic benefits are improved; by means of the planting auxiliary frame, the planting frame and the connecting columns, double-layer combined planting can be achieved, namely, the fences are placed on the edges of the planting auxiliary frame, the planting frame is kept transparent, and therefore the planting auxiliary frame can be filled with deep soil, and the planting requirements of different crops are met.

The invention relates to a crop seed high-frequency pulse processing device and method. The crop seed high-frequency pulse processing device comprises a conveying frame. The electric rollers are rotatably mounted at the two ends of the conveying frame, the variable-frequency and variable-speed motor is mounted on the front side face of the conveying frame, the belt supporting roller is rotatably connected to the inner side of the conveying frame, the conveying belt is arranged on the surfaces of the two electric rollers in a sleeving mode, the sealing cover is arranged at the upper end of the conveying frame, and the two hanging rods are mounted on the sealing cover. The leveling assembly is mounted on the closed hood; the cabin door automatic opening and closing assemblies are mounted at openings in the left end and the right end of the closed hood; a high-intensity alternating electric field, trace ozone sterilization and full-spectrum illumination are organically combined in the closed treatment cabin, the physiological activity of seeds is activated through the synergistic effect of multiple physical fields, the water absorption and stress resistance are enhanced, the germination rate and the seedling emergence consistency are improved, and by matching with an intelligent operation interface, the seed germination efficiency is improved. One-key selection of crop types, automatic calling of processing parameters and remote monitoring of operation states are achieved, and the purpose of efficient, accurate and convenient modernized seed processing is achieved.

The utility model relates to the technical field of temperature and humidity monitoring, in particular to a temperature and humidity monitoring device for a greenhouse, which is characterized in that one side of the upper part and the lower part of a side frame are respectively connected with two fixing plates in a sliding manner, the inner side of the side frame is connected with a supporting plate in a sliding manner, and the bottom of the supporting plate is fixedly connected with the temperature and humidity monitoring device through a bolt; the top of the supporting plate is rotationally connected with a threaded rod through a rotating shaft, the top end of the threaded rod penetrates through the top of the side frame through a threaded groove, mounting plates are fixedly connected to one side of the upper portion and one side of the lower portion of the bearing plate, and sliding blocks are fixedly connected to one side of the upper portion and one side of the lower portion of the side frame. The temperature and humidity monitoring equipment can be flexibly adjusted in the transverse position according to crop types, planting areas and environment changes, the problem that a traditional fixed installation mode cannot adapt to multi-point-position and dynamic monitoring requirements is solved, the application range of the equipment is widened, and the representativeness of monitoring data is improved.

The present disclosure relates to materials and methods useful for improving the efficacy of a plant breeding program such as, for example, the method for producing hybrid seeds in a facultative apomictic crop species, which in turns are useful for, for example, commercial production of highly uniform hybrid progeny. Hybrid seeds produced by such improved breeding methods, and plant grown from such hybrid seeds are also within the scope of the present invention. The disclosure further relates to processes for making a plant-derived product derived from any of the foregoing hybrid plants, and plant-derived products produced by such processes.

The present application relates to agriculturally beneficial microorganisms, microbial compositions and consortia. The present disclosure relates to isolated microorganisms, novel strains including microorganisms, microbial consortia, and agricultural compositions comprising the same. In addition, the present disclosure teaches methods of utilizing the microorganisms, microbial consortia, and agricultural compositions comprising the same in methods of conferring beneficial properties to target plant species. In particular aspects, the disclosure provides methods of enhancing desired plant traits in agronomically important crop species.

The present disclosure relates to edited (genetically modified) microorganisms comprising consortia of microorganisms, and to agricultural compositions comprising said microorganisms, intended to increase the tolerance of plants to nematode pests and / or to directly reduce nematode populations in soil or root systems. In addition, the present disclosure teaches methods of utilizing the described microorganisms, microbial consortia, and agricultural compositions comprising the same in methods of conferring beneficial properties to target plant species. In particular aspects, the present disclosure provides methods for improving desired plant traits and reducing undesired pests that affect crop performance in agronomically important crop species.

The invention provides a crop whole-growth-period drought monitoring and early warning method based on an adaptive water shortage index. The method comprises the following specific steps: establishing a regression relationship between a crop coefficient and a leaf area index; calculating the daily potential evapotranspiration; establishing an effective rainfall experience calculation formula, and calculating day-by-day effective rainfall according to the rainfall observed by the meteorological station; constructing adaptive day-by-day-scale crop water shortage indexes considering different crop types and drought-enduring characteristics in different growth stages; setting a crop drought grade division standard based on the adaptive water shortage index, carrying out crop drought identification and grade research and judgment, and achieving the monitoring and early warning of the whole process of crop drought occurrence, development and ending. According to the method, multi-source data such as remote sensing data, meteorological data and crop characteristic data are fused, the problem of water shortage sensitivity difference of different crop types and different growth stages is considered, the adaptive day-by-day scale crop water shortage index is constructed, and the whole drought process of the crop growth stage can be monitored.

The application provides a saline-alkali soil crop multi-water source irrigation control method and system, and belongs to the field of agricultural technology, and comprises the following steps: determining an irrigation water salt content target threshold value and a target total irrigation amount according to soil salt content data and crop physiological parameters; determining a water distribution strategy based on the salt content concentration data, wherein the water distribution strategy at least comprises irrigation priorities of different types of water sources and collocations; determining a target water intake amount of each type of water source based on the target total irrigation amount, the irrigation water salt content target threshold value and the water distribution strategy; and generating an irrigation control instruction according to the target water intake amount. According to the soil salt content, the crop type, the crop physiological parameters and the salt content concentration of the multi-water source, the irrigation water salt content target threshold value and the total irrigation amount are dynamically and accurately determined; meanwhile, a priority water distribution strategy is formulated, so that flexible allocation of irrigation among the multi-water sources and fine management of the salt content concentration of the crop irrigation water can be realized, and soil salinization and crop salt stress can be effectively avoided.

The application relates to the technical field of rainwater recycling, in particular to a rainwater intelligent recycling system and method for facility agriculture. The system comprises a shed body covering a planting area, a rain guiding and adjusting device installed at the top of the shed body and used for guiding and adjusting the flow direction of rainwater, a rainwater driving device used for driving the rain guiding and adjusting device to act, a rainwater collecting device, a sensing unit used for detecting environmental parameters in and outside the shed in real time, and a processor. The processor is provided with the information about the types of planted crops and the requirements of different growth stages of the crops, is used for calculating the utilization requirement parameters of rainwater according to the information about the types of crops and the growth stages and the environmental parameters detected by the sensing unit, and controls the rainwater driving device based on the parameters to adjust the working state of the rain guiding and adjusting device, so that the rainwater is collected in the shed body area as required. The reasonable distribution of the collection of rainwater and the soil flushing of crops in the shed is solved.

The invention belongs to the technical field of agricultural irrigation, and relates to an intelligent irrigation scheme recommendation method based on terrain soil crop collaborative analysis. A coupling rule knowledge base integrating terrains, gradients, soil types and crop types is constructed, a rule engine is used for matching multivariate parameters input by a user, so that the most suitable irrigation mode is intelligently recommended, a crop water demand model, soil water retention characteristics and gradient correction factors are integrated, and the irrigation efficiency is improved. Quantitative reference flow capable of being directly used for engineering design is obtained through calculation, and key design parameters and key points are output in an associated mode. According to the method, automatic and quantitative output from environment and agronomic parameters to irrigation system model selection, hydraulic calculation and design guidance is realized, the problems of high experience dependence and insufficient multi-factor collaborative consideration in the prior art are effectively overcome, and the method has the characteristics of scientific recommendation result, high adaptability and offline deployment support, and is suitable for popularization and application. The method is suitable for irrigation system planning and design of various agricultural scenes such as high-standard farmlands, orchards, hills and mountains and the like.

The invention relates to a crop classification method and system based on coded aperture snapshot calculation spectral imaging, and the method comprises the following steps: S1, capturing an agricultural scene through an optical encoder and an imaging element based on compressed sensing, and obtaining an output result of the optical encoder; s2, constructing a data set of an output result of the optical encoder and a real label of the crop variety, designing a deep learning decoder, constructing a deep learning framework, respectively carrying out training, testing and verification, and finally obtaining a weight file of the model through gradient descent; and S3, collecting compressed data through an optical encoder, and obtaining a crop classification result of an agricultural scene and a hyperspectral image of the corresponding scene in real time through network reasoning by using the obtained weight file. According to the crop classification method and system, an integrated method of optical hardware coding and decoding based on the deep learning network is used for crop classification, the classification speed is greatly improved, and the data storage cost is reduced.

The invention provides a smart agricultural knowledge base system and method based on an AI large model, and relates to the technical field of smart agricultural knowledge bases. The method comprises the steps of collecting agricultural historical big data, and performing data clustering processing for different crop types to form crop clustering data; performing parameter similarity analysis aiming at operation content on different crop clustering data to form a crop operation similarity model; and obtaining real-time parameters of the target crop, performing similarity analysis according to the crop operation similarity model, and determining corresponding crop operation content. According to the method, agricultural big data is reasonably analyzed and processed, and a more intelligent data matching result is provided to meet operation requirements of different planting and breeding conditions.

The invention relates to the technical field of agricultural land planning, in particular to a land utilization efficiency analysis method and system, and the method comprises the following steps: obtaining planting time sequence data: obtaining historical planting time sequence data of a target land parcel, the data at least comprising the variety of crops planted each time, the corresponding sowing date and the corresponding harvesting date; neutral period calculation: calculating the length of a field neutral period between two adjacent planting in the historical planting time sequence according to the sowing date and the harvesting date; analysis: comparing each field neutral period length obtained by calculation with a preset reasonable neutral period threshold range for a specific combination of preceding and succeeding crops; based on the comparison results, a land utilization efficiency diagnostic report is generated that at least explicitly lists specific crop rotation locations diagnosed as unreasonable. The system comprises a processor and a memory in communication connection with the processor. According to the invention, the compactness and rationality of time utilization can be diagnosed.

The present application belongs to agricultural machinery, and mainly relates to a split and combined movable cutter stubble cleaning and soil avoiding and root breaking ridge-shaped repairing device, which comprises a stubble cleaning device, a root cleaning device and a soil covering device. The stubble cleaning device identifies the type of crops in real time through an observation camera, provides the crop type information to a controller, and controls the movable cutter shaft and the sliding block to move each movable cutter piece to form a new combined movable and fixed cutter. The combined movable and fixed cutter can adapt to the crushing of stubble bodies of different crops, improve the adaptability of the stubble cutter and the stubble crushing quality. The root cleaning device moves the root cleaning wheel up and down through a cylindrical cam structure to avoid the soil between the stubble and the root, avoids large-area soil turning, effectively preserves the soil, and imitates the design of a wolf tooth stick. The arrangement of the root cleaning wheel tips is innovated to make it more consistent with the distribution of the corn root system, and high-quality root crushing is realized. The soil covering device drives the soil covering plate to open and close through a gear mechanism to realize efficient ridge-shaped repair of the area after root cleaning.

The present application relates to the field of agricultural technology, and discloses a drought-resistant and disaster-reducing interplanting method for winter rye with drought climate adaptability, which comprises the following steps: interplanting area selection treatment in a drought and semi-drought area is carried out, target interplanting area data is generated, previous crop type selection treatment is carried out based on the target interplanting area data, previous crop type data is generated, candidate crops are quantitatively evaluated by establishing a previous crop adaptability index formula, and screening standards are set based on climate and soil information of the target interplanting area, so that the scientificity of previous crop selection is ensured, and interplanting sowing is arranged based on actual harvest completion time of the previous crop and suitable sowing period of the winter rye, which can reduce the problem of compressed suitable sowing period of the winter rye due to late harvest of the previous crop, ensure the winter rye to form strong seedlings before winter, lay a foundation for safe overwintering and all-year interplanting, and improve the stability and reliability of the interplanting mode.

The present application relates to agriculturally beneficial microorganisms, microbial compositions and consortia. The present disclosure relates to isolated microorganisms, novel strains including microorganisms, microbial consortia, and agricultural compositions comprising the same. In addition, the present disclosure teaches methods of utilizing the microorganisms, microbial consortia, and agricultural compositions comprising the same in methods of conferring beneficial properties to target plant species. In particular aspects, the disclosure provides methods of enhancing desired plant traits in agronomically important crop species.