92 results about "Cash crop" patented technology

The invention discloses an intelligent breeding method for commercial crops based on big data analysis, and relates to the technical field of agricultural breeding, the method comprises the following specific steps: seed multi-modal data acquisition and processing: acquiring physical characteristic data of seeds, acquiring physiological indexes and genome information data through biochemical experiments and gene sequencing, and determining the seed multi-modal data according to the physiological indexes and the genome information data; carrying out pretreatment on the raw materials; according to the method, after multi-modal data are integrated and preprocessed, a seed vigor accurate evaluation model is constructed by using deep learning and data fusion technologies, the seed vigor level can be measured more accurately, and meanwhile, the electric signal change of the early growth stage of crops is monitored in real time by using high-precision plant electric signal acquisition equipment, so that the accuracy of the seed vigor evaluation is improved. And a correlation model of the electric signal characteristics and multiple traits of crops is established, and fusion analysis is performed on seed vigor evaluation data and plant electric signal data, so that the breeding efficiency is greatly improved, and powerful support is provided for cultivation of high-quality varieties.

The invention relates to the technical field of intelligent monitoring, and discloses a farmland grain planting condition dynamic monitoring method and system and a storage medium, and the method comprises the steps: obtaining a multi-temporal optical remote sensing image of a target area, and reconstructing the multi-temporal optical remote sensing image to obtain a high-resolution farmland image; performing feature extraction and crop identification on the high-resolution farmland image to obtain a crop type distribution diagram; and performing multi-time comparative analysis on the crop type distribution diagram to obtain cultivated land utilization change data, and generating a cultivated land grain planting condition monitoring report based on the cultivated land utilization change data. Precise distinguishing between grain crops such as rice, wheat and corn and commercial crops is achieved, fine non-grain changes are effectively recognized, and the accuracy of dynamic monitoring of cultivated land and grain planting conditions is improved.

The invention belongs to the technical field of molecular biology breeding, and particularly relates to application of a GhCASPL1F1 gene in cultivation of high-temperature-resistant cotton germplasm, and an amino acid sequence of a protein coded by the GhCASPL1F1 gene is shown as SEQ ID NO.3. The invention also relates to application of the GhCASPL1F1 gene in cultivation of high-temperature-resistant cotton germplasm. The invention provides a novel gene GhCASPL1F1 for negative regulation of high-temperature resistance of cotton, and by negative regulation of expression of the gene, adaptability of plants to high temperature and high-temperature stress tolerance can be improved, male fertility in a high-temperature environment can be maintained and improved, and high-temperature resistance of the plants can be improved. The method has important theoretical value and practical significance for improving the high-temperature resistance of commercial crops and improving the yield and quality of the crops in a high-temperature frequent environment, has good economic benefits, and has wide application prospects in cultivation of new high-temperature-resistant varieties of cotton.

The invention belongs to the technical field of fertilizers, and particularly relates to magnesium-containing controlled-release urea and a preparation method thereof, and the magnesium-containing controlled-release urea is characterized in that magnesium or magnesium-boron, magnesium-zinc and magnesium-boron-zinc medium trace element combinations are added into large-particle urea, and then coating is carried out. According to the controlled-release urea, elements such as magnesium are added into molten urine, then roller granulation and cooling are carried out, and finally coating is carried out. According to the prepared product, urea, magnesium and other elements can be synchronously and slowly released for a long time, nitrogen, magnesium and other nutrients have synergistic benefits, the utilization rate of nitrogen fertilizer, magnesium and other elements can be further increased, robust growth of crops is promoted, the yield is increased, the quality is improved, the stress resistance is enhanced, and labor is saved; and the method is especially suitable for regions with relatively common lack of medium trace elements and high-added-value commercial crops, and has a wide practical application value.

The invention discloses a planting method for overcoming continuous cropping obstacles of silage corn, which solves the problems of soil degradation and diseases and insect pests caused by continuous cropping by integrating soil physical remediation, chemical remediation, biological remediation, microbial community regulation and ecological intercropping technologies. The core technology content comprises the steps that deep ploughing is combined with organic matter and a biochar modifier to repair the soil structure, a compound microbial agent is sprayed to inhibit pathogenic bacteria, leguminous green manure and commercial crop rape are used for improving nitrogen circulation and reducing the autotoxicity effect every two years, and a precise fertilization management technology is matched. After the scheme is implemented, the soil health condition is remarkably improved, the silage corn yield is remarkably increased, and good ecological and economic benefits are achieved.

The invention relates to the technical field of ecological restoration and water and soil conservation, and discloses a wind prevention and sand fixation forest restoration method and system based on a forestry and agriculture compound system. The method comprises the following steps: deploying a distributed wind sand environment sensing node array, constructing a local wind field dynamic evolution model, and identifying a potential wind erosion hot spot region; generating a dynamic forest belt adjustment instruction based on the identification result, and controlling the deployment position and density of the movable shrub barrier unit; forestry and agriculture composite planting regulation and control are synchronously implemented, deep-root-system sand-fixing plants are arranged in a core protection zone, herbaceous plants are mixed and sown in a transition zone, and economic crops are crop-rotated in a peripheral zone; and the self-adaptive reconstruction of the forest belt structure is realized by continuously monitoring the change of the sand grain flux and feeding back the parameters of the optimization model. Through dynamic sensing, prediction and intervention mechanisms, the wind prevention and sand fixation efficiency is remarkably improved, ecological restoration and farmers and herdsmen livelihood are considered, the actually measured wind erosion hot spot area is reduced by 68%, and the ground surface sand transport rate is reduced by 82%.

The invention discloses a mountain land low temperature refined monitoring prediction method and system based on satellite-ground fusion and deep learning, and belongs to the technical field of ecological meteorological monitoring and agricultural disaster prevention and reduction. The invention aims to solve the problems of insufficient mountain low-temperature monitoring space coverage, neglect of local factors, rough prediction resolution and poor terrain adaptability in the prior art. The method comprises the steps of multi-source data acquisition, high-density meteorological station, multi-source satellite and meteorological mode data acquisition, spatial-temporal feature analysis, correlation analysis, key variable screening and weather type association, satellite-ground fusion air temperature reconstruction, generation of refined monitoring data based on a CNN-ANN deep learning framework, and short-term and temporary prediction modeling. And LSTM is combined with a terrain attention mechanism to construct a prediction model, and two-dimensional reliability verification is carried out. According to the method, the mountain low-temperature monitoring precision and the predicted terrain adaptability can be improved, accurate support is provided for low-temperature disaster prevention and reduction of mountain economic crops, and the method has remarkable practical value.

The invention discloses an artificial intelligence-based economic crop planting management method and system. The method comprises the steps of obtaining planting management original data, optimizing the original data, selecting target economic crops, predicting market prices of the economic crops, optimizing economic crop planting strategies and intelligently managing economic crop planting. The invention relates to the technical field of economic crop planting data processing, in particular to an artificial intelligence-based economic crop planting management method and system, which innovatively takes market price prediction as a guide and integrates a method system of target crop intelligent screening and full-cycle planting strategy optimization. The planting income stability of commercial crops is improved, price data signal decomposition processing is introduced, and the quality of commercial crop market price prediction input data is improved; a market price prediction model is innovatively designed, and the accuracy and stability of a model prediction result are improved; and an improved particle swarm optimization algorithm is introduced to realize efficient global optimization of the economic crop planting strategy combination.

The invention discloses an economic crop hyperspectral data prediction method and device based on a causal convolution tensor. The method specifically comprises the following steps: S1, receiving historical hyperspectral data of an economic crop from a server and storing the historical hyperspectral data; s2, constructing an economic crop hyperspectral data tensor according to the historical hyperspectral data of the economic crop; s3, creating an initial causal convolution weight according to historical hyperspectral data of the commercial crops; s4, constructing a target loss function according to the commercial crop hyperspectral data tensor and the initial causal convolution weight, performing iterative training, and extracting a hidden feature matrix and a causal convolution weight matrix; and S5, according to the causal convolution weight matrix and the hidden feature matrix, calculating a hyperspectral data prediction value.

The invention discloses a gerbera jamesonii growth index monitoring method, device and equipment and a medium, and the method comprises the steps: obtaining multispectral image data of a to-be-monitored gerbera jamesonii region in a greenhouse region, carrying out the preprocessing of the multispectral image data, and obtaining a vegetation index image of the to-be-monitored gerbera jamesonii region; performing texture feature extraction on the vegetation index image to obtain fusion features; and inputting the fusion features into a preset growth index monitoring model to obtain growth indexes of the to-be-monitored area of the gerbera jamesonii. The invention belongs to the field of plant growth prediction. The method comprises the following steps: extracting texture features from vegetation index images of a to-be-monitored area of gerbera jamesonii through multi-spectral image data acquired at low altitude in a greenhouse, combining ground measured data of growth indexes of the gerbera jamesonii, and combining multi-spectral image features with an adaptive machine learning technology to obtain fusion features, so as to obtain a to-be-monitored area of the gerbera jamesonii on the basis of fusion among different features; and the growth condition and the health level of the economic crops in the greenhouse can be evaluated more comprehensively.

The invention relates to the technical field of soil improvement and ecological restoration, and discloses a liquorice planting method based on synergistic utilization of coal-based solid waste and desertified land, which comprises the following steps: crushing alkaline coal-based solid waste and acidic coal-based solid waste, mixing according to a mass ratio of 2: 8-4: 6, adding a modified humic acid-based heavy metal passivator and water, and uniformly mixing to obtain a mixture; uniformly mixing and aging to obtain a coal-based solid waste mixture; spreading the mixture on the surface layer of the desertification land, performing rotary tillage and deep tillage to mix the mixture with the sandy soil, and adjusting the pH value to be stable at 7.5-8.5; the treated liquorice seeds are sown, main roots are harvested in autumn of the third year, deep root systems and lateral root bud points are reserved, and overground straw is smashed and returned to the field; soil nutrition indexes are monitored regularly, other commercial crops are planted when the soil nutrition indexes reach a set threshold value, and if not, regeneration planting of the liquorice is maintained. Through synergistic compounding of acid-base solid waste and chelating of the passivating agent, substrate pH self-regulation and heavy metal resistance control are achieved, and the physicochemical property of sandy soil is improved.

The invention discloses a method for repairing alkaline cadmium-polluted farmland in arid and semi-arid regions and application of the method, and belongs to the technical field of soil repairing. According to the method, the alkaline cadmium polluted farmland soil in the arid and semi-arid areas is subjected to deep ploughing treatment, and organic materials are applied to improve the soil fertility and the environment and health quality. On the basis, an intercropping planting system suitable for the arid and semi-arid land area is constructed, low-cadmium-accumulation grain crops and high-cadmium-accumulation plants are reasonably selected according to the ecological conditions and crop characteristics of the area, and an intercropping combination of low-absorption grain crops and enriched economic crop plants is formed. According to the system, organic unification of source reduction of heavy metal pollution in soil, pollution control in the planting process and continuous and safe utilization of the farmland is achieved, the dual goals of pollution remediation and farmland production are taken into account, and pollution reduction and collaborative improvement of economic benefits are achieved; and a feasible technical path is provided for ecological restoration of alkaline heavy metal polluted farmlands in arid and semi-arid regions.

The invention belongs to the technical field of water-soluble fertilizer preparation, and particularly relates to a water-soluble biochar base fertilizer, which is prepared from the following raw materials in parts by mass: 30 to 40 parts of composite modified biochar, 15 to 20 parts of urea, 10 to 20 parts of potassium nitrate, 10 to 15 parts of sodium borate, 2 to 5 parts of copper sulfate, 0.5 to 1 part of zinc sulfate and 0.5 to 1 part of microbial agent. The surface of the biochar contains more oxygen-containing functional groups due to the excellent porous adsorption structure of the biochar, so that soil adsorbs a large number of positive ions, the cell biological permeability is improved, the photosynthesis of plants is enhanced, the nutrient and moisture absorption capacity of plant root systems is enhanced, and the yield and income of food crops and commercial crops are increased by matching with other nutritional ingredients.

The invention discloses an incremental PID control-based commercial crop remote sensing data completion method and device. The method specifically comprises the following steps of S1, acquiring commercial crop remote sensing data from a server and storing the commercial crop remote sensing data; s2, constructing an economic crop remote sensing data matrix according to the economic crop remote sensing data; s3, initializing an incremental PID controller according to the constructed commercial crop remote sensing data matrix; s4, constructing a target loss function according to the commercial crop remote sensing data matrix and an incremental PID controller, performing iterative training, and extracting a hidden factor matrix; and S5, according to the extracted implicit factor matrix, calculating a commercial crop remote sensing data complementation value and storing the commercial crop remote sensing data complementation value.

The utility model discloses an all-directional spraying device for a microelement fertilizer for commercial crops, which relates to the technical field of fertilizer spraying and comprises a fertilizer liquid box and a storage battery. Straps are fixed to the two ends of the left side face of the fertilizer liquid box, a liquid inlet pipe is arranged on the top face of the fertilizer liquid box, a liquid pump is placed on the bottom face in the fertilizer liquid box, a liquid outlet of the liquid pump is connected with one end of a liquid conveying pipe, the other end of the liquid conveying pipe is connected with a liquid inlet of an atomization spray head, and an adjusting unit is arranged on the side face of the fertilizer liquid box. An atomizing nozzle is mounted in the adjusting unit, and the storage battery is fixed on the bottom surface of the fertilizer liquid box; according to the omni-directional spraying device for the microelement fertilizer of the commercial crops, three-dimensional omni-directional uniform spraying is achieved through the atomizing nozzles with the adjustable height, and the omni-directional spraying device is suitable for different crop plant types; intelligent liquid level monitoring and material mixing and stirring functions are provided, so that the fertilizer concentration stability is ensured, and liquid interruption is avoided.

The present invention relates to the field of crop picking technology, and specifically to a rail-mounted intelligent picking system, comprising a picking terminal, a picking robotic arm, a main control screen, a vehicle body, an obstacle avoidance module, a double-track track and a fixed platform. The picking terminal is fixedly connected to the picking robotic arm, the picking robotic arm is fixed to the fixed platform by screws, the fixed platform is fixed to the top surface of the vehicle body by screws, the main control screen is fixed to the side of the vehicle body, the obstacle avoidance module is opened on both sides of the vehicle body, and the double-track track is fixed to the ground. The present invention can improve the picking efficiency of high-value economic crops (such as high-value economic crops, blueberries, mushrooms, etc.), save manpower and realize picking in hilly and low-lying planting environments.

This invention provides a remote sensing intelligent monitoring method for non-grain crop conversion in mountainous areas using zero-sample change detection. The method collects high-resolution optical images, farmland vector data, and economic crop data to construct a typical example library containing seven types of farmland non-grain crop conversion changes. It calculates the change feature vectors for each change type, uses the SAM model for semantic segmentation of pre- and post-processing images, and designs a semantic information change detection operator based on spatially regularized diffusion learning clustering and dual-temporal latent spatial matching. This achieves zero-sample-based extraction of non-grain crop conversion patches in mountainous areas. This invention requires only a small number of typical examples to construct the example library, avoiding large-scale labeled training samples. It is low-cost and highly efficient. The spatially regularized diffusion learning clustering post-processing algorithm improves the segmentation accuracy of fragmented farmland in mountainous areas, and the semantic information change detection operator based on dual-temporal latent spatial matching enhances the detection accuracy of non-grain crop conversion. This provides a new solution for refined farmland identification and food security monitoring.

The application provides an economic crop information recognition method and system based on deep learning, comprising: cutting the unmanned aerial vehicle multispectral remote sensing image of a research area according to a prescribed shape to obtain a regular shape image; sample labeling is performed on the regular shape image, and the regular shape image is divided into a training set, a verification set and a test set; the U-Net model is trained according to the training set and the verification set; the trained U-Net model is used as a basic model, an Inception structure and an SE-Block are added, and the network is deepened; the hyperparameters are selected to optimize the parameters of the network-deepened model, an improved deep learning semantic segmentation ISDU-Net model is generated, and the ISDU-Net model is trained based on the training set and the verification set; and the trained ISDU-Net model is used for information recognition of economic crops. The improved deep learning semantic segmentation model is used for extracting unmanned aerial vehicle remote sensing images of economic crops and completing rapid mapping, and is outstanding in small sample category prediction, thereby providing a new idea for accurate recognition of economic crops.

The present invention discloses a heterogeneous collaborative intelligent pesticide applicator structure for cash crops in hilly areas and a path tracking method thereof. It belongs to the field of agricultural machinery technology. It comprises a pesticide applicator body 1, a lifting frame 2 fixed at the front end of the pesticide applicator, a foldable pesticide applicator rod 4 fixed on the lifting frame, a medicine box bracket 9 fixed at the rear end of the pesticide applicator, and a medicine box 8 fixed on the bracket. The pesticide applicator body adopts a crawler-type double-layer platform design, including a crawler-type mobile chassis 11, a double-layer bracket 12, and a central controller and drive circuit control board 6, a water pump 7, a data acquisition and communication module 3, a drone 5 and a drone wireless charging platform 10 are fixed on the bracket; the data acquisition and communication module includes a laser radar 32, a visual sensor 31, a Beidou satellite antenna 33 and a radio receiver 34. The present invention designs corresponding structures and path tracking methods for pesticide application operations in hilly areas, and ultimately realizes precise pesticide application and path tracking of heterogeneous collaborative intelligent pesticide applicators.

The invention relates to a planting technology for cooling and storing water for a soil body by utilizing solar power generation refrigeration, which comprises an anti-seepage water storage tank 1, an anti-seepage heat insulation water storage tank 2, a refrigeration pipe 3, a refrigeration pipe sleeve 4, a drip irrigation pipe 5, a breathable layer 6, an organic fertilizer treatment plant partition 7, an organic matter treatment freezing partition 8, a ground surface organic heat insulation layer 9, a planting tree 10, an excavation interface 11, a water absorption layer 12, a refrigerator 13 and a photovoltaic panel 14. Commercial crops 15 and a refrigeration header pipe 19.

The invention belongs to the technical field of agricultural machinery, and relates to a clamping jaw structure for a vibration picking device with a cushioning connection function. The clamping jaw structure comprises a clamping jaw body, a vibration mechanism, a cushioning connecting flange, a pneumatic push rod and a connecting rod. The clamping jaw body is composed of a fixed clamping jaw and a movable clamping jaw, and the movable clamping jaw is rotationally connected with the clamping jaw body through a rotating shaft assembly and connected with the pneumatic push rod through a connecting rod. And flexible clamping gaskets are arranged on the clamping surfaces of the clamping jaws. The vibration mechanism comprises a direct current motor and an eccentric wheel which are installed on the clamping jaw body. The cushioning connecting flange is arranged between the clamping jaw body and the mechanical arm, and cushioning filling materials are contained in the cushioning connecting flange. The structure adopts a modular design, is reliable in connection, has good cushioning performance and adaptability, and is suitable for automatic vibration picking operation of various commercial crops.

The present invention belongs to the technical field of planting. Disclosed is a method for maize-flue-cured tobacco crop rotation with double intercropping of pea / barley. In the method for maize-flue-cured tobacco crop rotation with double intercropping of pea / barley of the present invention, a specific planting pattern for the crop rotation is "flue-cured tobacco-intercropped pea-intercropped barley-rotated maize-intercropped pea- rotated barley-flue-cured tobacco". The symbiotic period of the double intercropped crops in this pattern reaches 70d, and a multiple cropping index of cultivated land is increased to "six harvests in two years", leading to a substantial increase in economic benefits. Moreover, this pattern can effectively reduce the occurrence of continuous cropping obstacles in cash crops such as flue-cured tobacco and peas, and thus is a "grain-tobacco-cash crop coordinated development pattern" that enables sustainable and efficient production. The economic benefits are greatly improved. In addition, pea seedlings are applied to attract migrating tobacco aphids, which reduces aphid infestations and prevents the occurrence of climatic spot disease and tobacco brown spot in upper tobacco leaves caused by excessive nutrient absorption in the late growth stage of flue-cured tobacco.

The invention discloses a water-retaining slow-release fertilizer for a dry-to-water field and a preparation method thereof, and belongs to the field of agricultural fertilizers, the water-retaining slow-release fertilizer is composed of a fertilizer core, water-retaining agent powder and rosin ethanol according to a mixing mass ratio of 100: 5: 5; the preparation method comprises the following steps: S1, pouring the fertilizer core into a water chestnut type disc coating machine; s2, spraying rosin ethanol into the disc coating machine to wet the surface of the fertilizer; s3, adding water-retaining agent powder into the disc in batches, and sieving by using a screening net after 10 minutes; s4, continuously coating the sieved water-retaining agent powder until the surface of the fertilizer core is completely coated with the water-retaining agent powder, and drying to obtain the water-retaining slow-release fertilizer. The water-retaining slow-release fertilizer provided by the invention can effectively improve the water-retaining capacity of the soil of the drought-to-water farmland in the red soil area in southern China, and greatly improves the utilization efficiency of water and irrigation water; the method has very important significance in the aspects of saving water, retaining fertilizer, reducing pollution, improving the ecological environment of soil, increasing the yield of agricultural and forestry economic crops, promoting the sustainable development of agricultural economy and the like.

The invention discloses an agricultural commercial crop ecological greenhouse, and relates to the technical field of ecological greenhouses, the agricultural commercial crop ecological greenhouse comprises a bottom plate, the upper part of the bottom plate is fixedly connected with an arch-shaped rod, one side, close to the arch-shaped rod, of the bottom plate is fixedly connected with a guide rod, the guide rod is provided with a greenhouse driving assembly, and the rotation of a gear pushes a roller to slide on the outer side of the guide rod; a greenhouse rolling locking assembly is arranged on the first servo motor, and the greenhouse rolling locking assembly comprises an electric telescopic rod and a pushing plate which are movably connected to the first servo motor, a second servo motor and a worm which are arranged on the upper portion of the pushing plate, and a worm wheel, a rotating roller and second blocking cloth which are movably connected to the outer side of the pushing plate. Second blocking cloth can be locked through stretching and retracting of an electric telescopic rod, a worm can be driven to rotate through starting of a second servo motor, a worm wheel can be driven to rotate through rotation of the worm, a rotating roller can be driven to rotate through rotation of the worm wheel, and the second blocking cloth can be rolled through rotation of the rotating roller.

The invention provides a mountain cultivated land non-grain remote sensing intelligent monitoring method based on zero sample change detection, and the method comprises the steps: collecting a high-resolution optical image, a cultivated land vector and economic crop data, constructing a cultivated land non-grain change detection typical sample library containing seven change types, calculating the change feature vector of each change type, and calculating the change feature vector of each change type; semantic segmentation is carried out on front and later images by using an SAM model, a semantic information change detection operator for spatial regularization diffusion learning clustering post-processing and dual-time-phase potential space matching is designed, and non-grain pattern spot extraction of the mountain cultivated land based on a zero sample strategy is realized. According to the method, only a small number of typical samples are needed to construct the sample library, large-scale training sample marking is avoided, the cost is low, the efficiency is high, the segmentation precision of the broken farmland in the mountainous area is improved through the space regularization diffusion learning clustering post-processing algorithm, the farmland non-grain detection precision is improved through the semantic information change detection operator matched with the double-time-phase potential space, and the method is suitable for popularization and application. And a new solution is provided for fine identification of cultivated land and grain safety monitoring.

The invention discloses an inter-row mechanical and inter-plant laser combined weeding device, which relates to the technical field of agricultural intelligent equipment and specifically comprises a field walking chassis, a mechanical weeding system, a laser weeding system and a weed collecting system. The mechanical weeding system can accurately remove weeds between rows, and by means of a drawing mode and cooperation with negative pressure adsorption of the weed collection system, weed collection is achieved, and weed residue breeding is avoided; according to the laser weeding system, the types and positions of weeds are positioned through visual recognition, laser energy is precisely regulated and controlled in a non-contact scanning mode, weeds of different types and maturity are selectively ablated, and economic crops are prevented from being damaged while inter-plant weed inactivation is achieved; by means of mechanical-laser synergistic weeding operation, the problems that traditional inter-plant mechanical weeding operation is poor in environment adaptability, soil and crops are prone to damage, single laser weeding is large in energy consumption, efficiency is difficult to improve and the like are effectively solved, and cost reduction and efficiency improvement of complex farmland weeding operation are expected to be achieved.

1. The name of the design product: all-terrain vehicle pesticide spraying robot (F052001). 2. The use of the design product: the robot belongs to the field of intelligent agriculture, and the core application scene focuses on the field of agricultural production. It can implement intelligent pesticide spraying and irrigation operations for various plants such as crops, fruit trees, and economic crops. 3. The design points of the design product: the combination of shape, pattern, and color. 4. The picture or photo that best indicates the design points: perspective view. 5. The design for which protection is sought includes color.

The invention provides a plant cold-proof, stress-resistant and anti-freezing method for enhancing plant respiratory conduction efficiency, and relates to the technical field of plant cultivation and stress-resistant protection. According to the method, a composite anti-freezing agent containing auxin, a conduction accelerant, a stress-resistant inducer, an osmotic regulator and a nutritional supplement is prepared and sprayed to the whole plant 24-48 hours before low-temperature freezing injury occurs, the respiration and nutrient conduction efficiency of the plant are enhanced, dry matter is quickly accumulated to reduce the freezing point of cells, and a stress-resistant defense system is started. The core innovation lies in multi-component synergistic adaptation, precise spraying opportunity control and broad-spectrum crop adaptability, and the problems that a traditional method is limited in anti-freezing effect and prone to causing physiological unbalance of plants are solved. Practice verification shows that the method can improve the cold resistance of the plants by 2-5 DEG C and reduce the freezing damage loss rate by more than 60%, is suitable for various plants such as field crops, garden crops and commercial crops, is simple and convenient to operate and controllable in cost, and provides effective technical support for plant cultivation in an extremely low-temperature environment.

The invention discloses a one-time fertilization method for rice, and particularly relates to the technical field of one-time fertilization methods for rice, which comprises the following steps: S1, plowing a rice field; s2, frequent shallow water irrigation; s3, an early growth stage after seedling throwing; s4, a fertilization process; s5, rice growth middle and later periods. According to the one-time fertilization method for the rice, soil can be improved, activated carbon can be supplemented for the soil, soil hardening is broken, acidification is inhibited, and degeneration is prevented. Organic and inorganic pollution residues in the soil can be effectively removed, and particularly, an obvious degradation effect on heavy metal cadmium pollution is achieved. If the compound fertilizer is continuously used for 2 years, the quantity of soil actinomycetes can be increased by 28 times, the quantity of nitrogen-fixing bacteria can be increased by 34 times, a good soil environment is created for rice growth, root development and nutrient absorption are facilitated, the yield of food crops can be increased by 15-20%, the yield of commercial crops can be increased by 30-50%, and the product quality is improved by 1-3 grades. After the fertilizer is applied to the late rice field, the yield is obviously higher than that of a contrast field, the rice cadmium content is greatly reduced, and the quality is improved while the yield is increased.

The invention discloses an unmanned aerial vehicle pesticide spraying distribution method and system for commercial crops in multiple operation areas, and the method comprises the steps: carrying out the modeling of a distribution problem of limited pesticide spraying operation time of a UAV among different commercial crops as a game model, taking the UAV as a leader of the game model, and taking each commercial crop as a follower; for the leader, an objective function of the game model is a utility function for selling limited pesticide spraying operation time resources; for the followers, the objective function of the game model is the earnings obtained by purchasing the pesticide spraying operation time; the utility function of the limited pesticide spraying operation time resource is sold to the maximum degree to obtain the optimal unit resource pricing, and the earnings obtained by purchasing the pesticide spraying operation time to the maximum degree to obtain the optimal operation time distribution resource. The distribution problem of the limited pesticide spraying operation time of the UAV among different commercial crops is modeled as a game model to optimize the distribution of the flight operation time of the UAV on different commercial crops.