345 results about "Rice growth" patented technology

The invention discloses a rice field irrigation drainage strategy dynamic optimization method and system. The method comprises the steps of collecting environmental parameters of a target rice field in a current decision period; determining a to-be-optimized target of the target rice field, and constructing a multi-target optimization model in combination with the environmental parameters; performing dynamic planning solution on the multi-objective optimization model by adopting an intelligent algorithm to obtain a real-time optimized irrigation drainage strategy of the current decision period; implementing a real-time optimized irrigation drainage strategy of the current decision period; monitoring whether the final period of the rice growth period is reached when the current decision-making period is ended or not: otherwise, acquiring actual environment parameters when the decision-making period is ended, correcting the state vector at the moment, updating the initial state vector of the next decision-making period of the target rice field through the transfer function, and repeating the solving and implementation process of the irrigation and drainage strategy optimized in real time; if yes, the circulation is ended, and the optimal irrigation drainage strategy in the whole growth period of the target rice field is obtained.

The invention provides a rice growth model construction method and system based on salt stress, and relates to the technical field of growth model.The rice growth model construction method comprises the steps that firstly, monitoring points are arranged in a planting sample area, and soil conductivity data of different depths are obtained through a multi-depth soil conductivity sensor and a Kriging interpolation method; collecting root system density, a multispectral remote sensing image and a leaf area index, and calculating a canopy salt stress index; measuring the concentration of related ions to obtain a sodium adsorption ratio, and establishing a salt stress coefficient by combining the soil conductivity and the irrigation volume; fusing canopy and soil stress indexes to generate a stress comprehensive index, and introducing a salinity feedback item to represent the crop compensation capability; and finally, constructing a hybrid machine learning model by adopting a convolutional neural network and a long-short-term memory network to realize rice growth dynamic prediction. According to the method, multi-dimensional salinity stress quantification of a soil-crop system is realized, and decision support is provided for salinization treatment in precision agriculture.

The invention provides a rice endophyte for promoting rice growth and reducing cadmium as well as a preparation method and application of the rice endophyte, and relates to the field of environmental microbiology and agricultural microorganisms. The rice endophyte is stenotrophomonas, is named as Stentrophomonas sp.R5, is preserved in the China Center for Type Culture Collection, the address is Wuhan University, Wuhan, China, the postcode is 430072, the preservation number is CCTCC NO: M 20231758, and the preservation date is September 20, 2023. The rice endophyte not only has the capabilities of producing IAA, dissolving phosphorus, producing siderophores and the like for promoting the growth and development of rice, but also has an efficient inhibition effect on absorption and transportation of cadmium in the rice, particularly, the cadmium reduction amplitude of mature rice grains reaches up to 57.69%, and the rice endophyte has little influence on microbial communities in a soil environment, and has a good application prospect. Excessive interference is not caused, and conversion of available nutrients in the soil is promoted.

The invention discloses a rice leaf tip small target detection and counting method based on global information enhancement, and the method comprises the steps: firstly building a field rice leaf tip image data set as a basis, and constructing an improved YOLO-DCL model; the core innovation of the method lies in that a global context information enhancement module, an inverted residual-cascade grouping attention module and a re-parameterization shared convolution detection head are introduced, key feature expression is enhanced and detection efficiency is optimized through effective fusion of global information, the recognition precision and processing speed of the model on a tiny rice leaf tip target are significantly improved, and the method is suitable for large-scale popularization and application. After training parameters are set, an optimization model is trained, then system performance verification and module optimization are carried out on the model, and a version with the optimal rice leaf tip detection performance is screened out. The technical bottlenecks that small target leaf tips are prone to missing detection and false detection and insufficient in real-time performance under the complex farmland background are effectively overcome, and reliable and efficient technical support is provided for rice growth early-stage yield prediction.

The invention discloses a fertilization and topdressing intelligent decision-making system and method based on rice open space sensing data. The method comprises the following steps: acquiring agricultural condition data through a multi-source data acquisition module formed by an unmanned aerial vehicle multispectral camera, a ground sensor network and a meteorological station; generating a standardized data set by adopting a space-time fusion algorithm; the CNN-LSTM hybrid model is used for realizing rice growth prediction, disease, pest and weed identification and maturity evaluation; dynamically generating a base fertilizer / topdressing prescription map, a pesticide application scheme and an agricultural machine path plan in combination with an agricultural rule base; and the intelligent agricultural machine is linked through the Internet of Things interface to execute accurate operation. Millimeter-level sensing of the farmland state, variable control over fertilizer application and pesticide application and autonomous execution of agricultural machine operation are achieved, and compared with a traditional mode, the fertilizer utilization rate is increased by 35% or above, the pesticide application amount is reduced by 40%, and the comprehensive yield is increased by 15-20%.

The invention provides a rice planting area identification method and device based on multi-temporal remote sensing data, equipment and a storage medium. The method comprises the following steps: acquiring the multi-temporal remote sensing data according to a rice phenological period; determining a spectral index sequence of the multi-temporal remote sensing data to construct a spectral index time sequence curve, and generating planting characteristic data in the target area according to a spectral change curve; determining a spectrum time sequence template matched with the rice growth rule according to the planting characteristic data, performing matching analysis on the planting mode of each land block, and marking a land block set of rice planting mode characteristics; performing cross comparison on the plot set and the rice planting reference sample to generate a rice planting mode sample set, and constructing a rice planting area identification model based on the rice planting mode sample set; and analyzing the remote sensing data of the land parcels to be identified in the research area according to the rice planting area identification model, and determining a rice planting area identification result. According to the scheme, the accuracy of rice identification can be effectively improved.

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

The invention relates to the field of artificial intelligence, in particular to a rice growth vigor dynamic monitoring method and system based on modal fusion and deep learning. The method comprises the following steps: for a plurality of target regions in the same administrative division, acquiring multi-dimensional agricultural data related to rice growth vigor in each target region; performing space-time fusion on the multi-dimensional agricultural data of the plurality of target areas to obtain a linkage monitoring map; performing rice growth prediction on each target area in the linkage monitoring map through a DSW Transform model to obtain an independent growth prediction result of each target area; a correlation weight is dynamically calculated through a deep learning model of a cross-modal attention mechanism in combination with geographic data, meteorological data and a linkage monitoring map, and rice growth prediction is performed on a rice block formed by linkage of each target area based on the correlation weight to obtain a comprehensive growth prediction result; and pushing rice growth information in each target area to the user according to the independent growth prediction result and the comprehensive growth prediction result.

The invention provides a rice variable rate fertilization method and device, electronic equipment and a storage medium, and relates to the technical field of agricultural intelligent information process.The method comprises the steps that non-rice plant interferents in a multispectral remote sensing image are removed, and a rice plant canopy mask is generated; based on the rice plant canopy mask, multi-dimensional features of the rice plant canopy are extracted and fused, and a fused growth feature vector is obtained; grading the rice growth vigor according to the fused growth vigor feature vector through a growth vigor grade prediction model to obtain a predicted growth vigor grade; performing standardization processing on the predicted growth vigor level to obtain a standardized growth vigor level; determining a nitrogen fertilizer adjustment factor based on the standardized growth vigor grade; and according to the nitrogen fertilizer adjustment factor, adjusting a standard nitrogen application amount to obtain a recommended nitrogen application amount. According to the invention, accurate recommendation of the nitrogen application amount in the rice planting process can be realized, so that accurate fertilization is realized.

The invention discloses a microbial agent and application thereof in preventing and treating rice blast and promoting rice growth, active ingredients of the microbial agent are formed by compounding cold bacillus with the preservation number of CGMCC (China General Microbiological Culture Collection Center) NO: 33492 and bacillus velezensis with the preservation number of CGMCC NO: 33493, and the microbial agent aims at solving the synergistic problem of preventing and treating rice blast and promoting rice growth. According to the complex microbial inoculant, through the synergistic interaction between the two strains, the metabolite of the complex microbial inoculant can completely inhibit the spore germination of magnaporthe oryzae; meanwhile, the fungicide can degrade cellulose, obviously promote the growth of plant height, fresh weight and dry weight of rice, and realize the integration of disease prevention and growth promotion. The invention further discloses a preparation method of the fungicide and an application method of the fungicide for preventing and treating rice blast and promoting growth in a root irrigation mode in the three-leaf stage of rice. The microbial agent disclosed by the invention has dual functions of efficiently preventing diseases and stably promoting growth, and an efficient and safe biological solution is provided for green and sustainable development of agriculture.

The invention discloses a rice growth period distinguishing method and an intelligent irrigation control device. Belongs to the technical field of crossing of intelligent agriculture and irrigation and water conservancy engineering and particularly relates to the technical field of rice growth period judgment and intelligent irrigation. The technical problem that an accurate and effective rice growth period judgment method for guiding intelligent rice irrigation is lacked at present is solved. The method specifically comprises the following steps: calculating a rice growth process index through an improved accumulated temperature model; and constructing a multi-factor coupling growth period judgment method, and judging the current rice growth period through the rice growth process index. The system comprises a sensing unit, a judgment and decision-making unit, an electric execution unit and an input and power supply unit, the judgment and decision-making unit receives the environment data of the rice field and the water layer depth data of the rice field, judges the current growth period of the rice according to a rice growth period judgment method, calculates the current water layer deviation and generates a control instruction to the electric execution unit.

The invention relates to the technical field of agricultural intelligent prediction, and discloses a fertilization decision-making system fusing soil and rice growth vigor information data acquisition and analysis, which is characterized in that a microcontroller controls an irrigation valve to apply an irrigation pulse with a preset duration, and a soil humidity sensor is used to monitor a time interval when moisture falls back from a peak value to a baseline; according to the method, irrigation behaviors are reconstructed into an active diagnostic tool, traditional chemical index detection is replaced by physical process dynamic monitoring, lag adjustment is converted into a pre-prediction mode, meanwhile, acoustic verification and a differential correction mechanism are combined, and the crop transpiration rate is predicted. And an anti-environmental interference accurate decision-making system is constructed on the basis of low-cost hardware.

The invention belongs to the technical field of agriculture, and particularly relates to a method for promoting growth and development of rice based on illumination and nitrogen. One of the purposes of the invention is to provide a method for promoting growth and development of rice based on illumination and nitrogen. The method comprises the following steps: providing cultivation conditions of illumination intensity of 600-800 [mu] mol.m <-2 >. S <-1 > and nitrogen concentration of 5.51-8.11 mM for rice in a tillering stage of the rice. By accurately applying a specific combination of illumination intensity and nitrogen concentration in the tillering stage of rice, efficient loading and long-distance transportation of photosynthetic products (especially cane sugar and the like) in phloem are promoted, and the photosynthetic products are guided to be more effectively and directionally distributed to developed library organs (such as fruits, grains or root systems); therefore, the transfer and circulation efficiency of carbon-nitrogen substances in plants is improved synergistically on the whole, the waste phenomenon of nitrogen redundancy or local lack and ineffective accumulation of photosynthetic products is reduced, and finally, an important physiological regulation basis is provided for remarkably improving the yield and quality of crops.

The invention relates to the field of intelligent agriculture, in particular to a high-salt-tolerance rice planting management system based on image recognition, which comprises a data acquisition module, an image processing module, a growth condition detection module and an analysis management module, through the computer vision technology, close planting degree guidance and saline-alkaline degree control are intelligently provided for high-salt-tolerance rice planting, the management efficiency is improved, and the rice yield and quality are improved; according to the method, a Transformer coding method based on a window mechanism and global optimization is adopted, the recognition accuracy of the growth state of a rice plant is improved, the accuracy of analysis of the relationship between the growth condition of the rice and the salt and alkali content and the close planting degree of the rice is improved, and accurate guidance is provided for increasing the yield and quality of the rice; according to the method, a UNet network based on Mama block optimization is adopted, the influence of a field background on rice image feature extraction is removed, and the accuracy of rice growth condition-saline and alkaline content-rice close planting degree relation analysis is improved.

The invention provides a rice yield growth season high-precision prediction method based on a total primary productivity remote sensing product. The method comprises the following steps: firstly, calculating rice total primary productivity GPP and a normalized difference red-edge vegetation index NDRE in a rice growth season on a remote sensing cloud platform based on a time sequence Sentinel-2 image; then, respectively carrying out correlation analysis on the yield by utilizing GPP and NDRE of monthly-scale rice; performing harmonic fitting on the time sequence GPP based on a harmonic analysis technology, and determining an optimal time window in a growth season for rice yield prediction at an interval of 10 days; the rice yield is estimated by utilizing transfer learning and GPP and NDRE of the optimal time window, so that the advantages of GPP in yield estimation are clear; and an inter-annual GPP correction method suitable for different ecological points is constructed, so that the yield estimation precision of independent years is improved. According to the method, the yield of the rice in the field can be accurately estimated in seasons in a regional range, and accurate management of the rice can be promoted by farmers and agricultural technology promoters.

The invention relates to a rice character parameter inversion method combining an optical-microwave collaborative model and a variational auto-encoder. The method comprises the following steps: acquiring multiband optical reflectivity, a microwave backscattering coefficient and observation geometric information of a research area; inputting the data into a multi-mode encoder, and encoding the data into probability distribution of a potential space; an optical and microwave physical model is used as a differentiable decoder, potential variables sampled from a potential space are received, and remote sensing data are simulated and generated; a self-supervised learning normal form is adopted, and end-to-end training is carried out on the whole frame by minimizing a composite loss function; a trained encoder is used as a rapid inversion model, vegetation biological physicochemical parameters are extracted from new remote sensing data, rapid inversion of the parameters is achieved, and uncertainty of the parameters is quantified. The rapid and accurate vegetation character parameter inversion method is established by fusing multi-modal data, a physical model and a deep learning technology, important reference is provided for rice growth monitoring and precision agriculture, and the method has popularization prospects.

The invention discloses a rice whole growth period growth dynamic monitoring system based on multi-source sensing fusion, and relates to the field of agricultural intellectualization, and the system comprises an acquisition module which is used for taking a rice root development core area as a target, adaptively arranging a multi-dimensional sensing array and dynamically adjusting the operation frequency of the array, continuously collecting root system microenvironment and morphological characteristic original data; the preprocessing module is used for receiving the original data acquired by the acquisition module, performing space-time alignment and noise filtering on the root system microenvironment and morphological feature sensing data, and synchronously extracting core data dimensions for driving development analysis through a feature enhancement algorithm; by comprehensively evaluating the generated growth potential and yield potential report, the rice growth state is comprehensively reflected, a planter is assisted to intervene abnormal conditions in advance, the growth stress loss is reduced, and a scientific basis is provided for accurate regulation and control, so that the fine management level and yield potential of rice planting are improved.

The invention discloses a preparation method of a controlled-release fertilizer for mechanical transplanting rice seedling raising subsoil and application of the controlled-release fertilizer to replace field fertilization, and belongs to the technical field of rice cultivation. A coating of the controlled-release fertilizer is prepared from the following components in parts by weight: 20 to 60 parts of low-density polyethylene resin, 10 to 20 parts of ethylene-vinyl acetate copolymer, 5 to 30 parts of synthetic resin biodegradation inducer, 3 to 15 parts of starch, 10 to 70 parts of talcum powder and 0.2 to 2 parts of nonionic surfactant. The controlled-release fertilizer comprises urea and a compound fertilizer which are respectively coated by the coating film. According to the controlled-release fertilizer for the machine-transplanted rice seedling raising subsoil, a coating material is optimized, the release inhibition period of the controlled-release fertilizer is 20-30 days, normal growth of rice seedlings is ensured, and the rice growth requirements are accurately met. When the method is used for rice planting, a seedling raising subsoil fertilizer carrying method is adopted, integration of rice transplanting and fertilization is achieved, and on the basis of ensuring high and stable yield of rice, the fertilizer application cost and the risk of nitrogen and phosphorus pollution emission in the rice field are reduced.

According to the application of the nano silicon dioxide in relieving rice temperature rise stress, the nano silicon dioxide has a relieving effect on rice growth damage caused by high environment temperature. According to the method, the nano silicon dioxide is used for relieving the temperature rise stress of rice, a new method is provided for crops to cope with the temperature rise stress, the yield loss caused by the temperature rise stress can be remarkably reversed by spraying the nano silicon dioxide on the leaf surfaces in the tillering stage and the jointing stage, and experiments prove that the yield is improved by 34% compared with that of an untreated high-temperature group.

The utility model discloses a rice hydroponic device which comprises a hydroponic box, a fixing frame is arranged in the hydroponic box, a plurality of fixing rings are evenly arranged on the fixing frame, hydroponic barrels are connected in the fixing rings in an embedded mode, a fixing pipe is installed in the middle of the fixing frame, and a screw hole is formed in the middle of the surface of the fixing pipe. The surface of the fixing plate is provided with four limiting holes which are annularly distributed by taking a screw hole as the center, and a screw rod and a limiting column are vertically arranged at the inner bottom of the hydroponic box. The motor is started to drive the screw rod to rotate, and after the screw rod rotates, the fixing pipe moves vertically under the limiting influence of a rotating thread and the limiting column; after the fixed frame is driven to move upwards, the rice root system in the hydroponic cylinder or extending to the lower end of the hydroponic cylinder can be exposed, so that the growth condition of the rice can be conveniently observed; the filter box is arranged outside the water culture box, liquid in the water culture box can be pumped out and filtered through the filter box, the filtered liquid is conveyed into the water culture box, culture liquid can flow, and the problems of precipitation and the like are avoided.

The present invention relates to a prediction method for the occurrence of Chilo suppressalis in rice, including: constructing a data set based on the date of rice growth and development period, the number information of Chilo suppressalis, and meteorological environment data, and dividing it into a training set and a test set; based on the random forest model, using grid search and cross-validation to determine the input parameters and parameter thresholds of the model, and determining the best numerical combination of the model input parameters; respectively predicting the cumulative number of Chilo suppressalis in the training set and the test set; using evaluation indicators to evaluate the training set and the test set respectively to obtain the goodness of fit of the model and the correlation degree between the predicted value and the actual value; using the test set to analyze the trend of the cumulative number of Chilo suppressalis. The beneficial effects of the present invention are: the prediction method for the occurrence of Chilo suppressalis in rice provided by the present invention can overcome problems such as traditional pest prediction relying on experience, low efficiency, and high uncertainty, and realize the prediction of the cumulative number of Chilo suppressalis in the time series of rice.

The invention belongs to the technical field of microbial fermentation and biological agriculture, and discloses a soil remediation fungicide as well as a preparation method and application thereof. The preparation method comprises the following steps: activating bacillus megatherium Z101, inoculating the activated bacillus megatherium Z101 into fermentation liquor containing rice straw powder, carrying out fermentation culture, and carrying out vacuum spray drying on fermentation mixed liquor after fermentation is completed, so as to obtain soil remediation bacterium powder; or further mixing the soil remediation bacterium powder with auxiliary materials and water, and granulating to obtain the soil remediation bacterium granules. The application method comprises the following steps: in a rice planting stage, applying the soil remediation fungicide and an inorganic fertilizer together to remedy rice field soil and promote rice growth. The soil remediation fungicide prepared by fermentation culture of the bacillus megatherium Z101 has remarkable advantages in the aspects of rice yield increase, soil pH value increase and physicochemical property improvement, and a new application way is provided for the bacillus megatherium Z101.

The present invention belongs to the technical field of microorganisms, and specifically relates to Chaetomium F8 and the use thereof. The Chaetomium F8 is deposited in the China General Microbiological Culture Collection Center with the deposit number of CGMCC No.40973. The provided Chaetomium F8 can be used to effectively promote the growth of wheat, maize and rice. In addition, the provided Chaetomium F8 has the functions of promoting straw degradation and phosphorus solubilization, remarkably promotes soil agglomeration under the field condition, can provide strain resources for agricultural straw degradation, and provides reference for further development and utilization of Chaetomium.

The invention relates to the field of fertilizers, in particular to a stable fertilizer for nitrogen fixation and emission reduction of a rice field and a preparation method of the stable fertilizer. The fertilizer core comprises the following components: 28-32 parts of ammonium sulfate, 4-6 parts of monoammonium phosphate, 8-12 parts of potassium sulfate, 0.15-0.50 part of a composite nitrification inhibitor, 1-3.5 parts of zinc sulfate monohydrate and 1-2 parts of borax; wherein the composite nitrification inhibitor is obtained by mixing 3, 4-dimethyl-pyrazole phosphate and a phenylboronic acid-phosphoryl compound in a mass ratio of (2-7): 1. The fertilizer product has a scientific and reasonable formula, the long-acting nutrient content and the trace element substance composition are reasonable, the controlled release function is achieved, nutrients needed by rice growth can be met, the fertilizer utilization rate is increased, and the yield and the quality are improved.

The invention discloses a rice growth image real-time acquisition method. The method comprises the following steps: real-time data acquisition; processing data; carrying out data visualization and analysis; according to the invention, through collection and fusion of multi-dimensional data, in combination with image analysis and a machine learning algorithm, key characteristics of rice growth are extracted; field environment data and rice plant height information are collected in real time, time sequence characteristics of environment parameters and plant height parameters are extracted based on a long-short-term memory network model, a long-term dependency relationship is captured, and accurate prediction of the rice plant height is achieved. A prediction result can be visually analyzed through a thermodynamic diagram and the like, and the growth condition of the rice is visually displayed; through a large number of trained long-short-term memory network models, precise prediction of the rice plant height can be realized, and during subsequent implementation of acquisition of rice growth images, dependence on manual observation or regular shooting is not needed, so that real-time predictability of rice growth is improved.

The invention relates to a rice blast forecasting method coupled with multi-source data, and solves the problem of insufficient forecasting precision caused by single data source in the existing method. The method comprises the following steps: constructing a historical long-time-sequence meteorological product database; constructing a historical disease promoting index according to the historical long-time-sequence meteorological product database; a disease promoting index in the next three days is constructed based on weather forecast data; constructing a rice growth monitoring model based on MODIS data, and determining the rice growth level; the method comprises the following steps of: constructing an improved rice blast disease promoting index model, performing normalization processing on a disease promoting index, converting a disease promoting index layer after grid normalization into a vector point location layer by utilizing a GIS layer conversion method, and performing interpolation processing on the vector point location layer by utilizing a Kriging interpolation method; cutting the interpolation processing result according to the rice distribution data of the target area; and outputting an improved rice blast disease promoting index grade thematic map. According to the invention, multi-source data can be coupled to carry out accurate and periodic forecasting on the rice blast.

The invention discloses a diversified rice planting method in a compound environment based on big data analysis, and particularly relates to the technical field of agricultural information processing. The method comprises the following steps: collecting multi-dimensional monitoring data in a rice planting area, carrying out nonlinear correlation analysis, and extracting interaction characteristics among environment variables; carrying out multi-scale reconstruction analysis in combination with spatial scale difference, and identifying a main influence area of an environment variable; mapping analysis is carried out based on historical rice growth state data and environment variable interaction characteristics, and the comprehensive influence on rice growth is evaluated; analyzing the action time sequence of different environment variables in the rice growth cycle, and extracting the influence weight change rule of the environment variables in each growth stage; according to the method, environmental variable interaction characteristics and influence weight rules are fused, the growth potentials of different rice varieties are evaluated, the planting varieties and planting density of rice are optimized, and precise planting under the multi-variety collaborative adaptation and compound ecological condition of rice is achieved.

The method comprises the following steps: monitoring seedling condition and growth vigor information in a rice growth process, and constructing a seedling condition index spatial distribution diagram; according to the seedling condition index spatial distribution map and a preset rice suitable growth index dynamic curve, generating a topdressing application amount operation prescription map; determining a navigation path diagram of the rice agricultural unmanned aerial vehicle; and fusing the topdressing application amount operation prescription map with the navigation path map, and carrying out topdressing operation through a rice agricultural unmanned aerial vehicle based on a fusion result. Tedious steps such as hyperspectral unmixing and dimensionality reduction modeling are not needed, and the decision-making efficiency is improved. The fertilizer demand is accurately matched, and excessive fertilization is avoided; a navigation path is fused with a prescription map, variable spraying with finer granularity is achieved, rasterization is not needed to restrain a minimum operation unit, and spraying uniformity is improved.

The invention discloses a chloroplast RNA edited gene OsPPR7 for temperature-sensitive regulation and control of rice and application of the gene OsPPR7, and belongs to the technical field of gene engineering. The CDS sequence of the OsPPR7 gene is as shown in SEQ ID NO. 1. The OsPPR7 is an RNA (Ribonucleic Acid) editing factor which has a bidirectional regulation and control function and is sensitive to temperature. Editing of multiple sites on the rpoB gene is negatively regulated and controlled, and meanwhile RNA editing of multiple genes such as ndhB and ndhD which are crucial to the chloroplast function is positively regulated and controlled under high-temperature stress. Under the stress of high temperature of 35 DEG C, the loss of functions can lead to obvious reduction of RNA editing efficiency of a plurality of ndh genes, and serious yellowing of seedlings is caused. The key function of the rice OsPPR7 gene in regulation and control of rice growth and development and high-temperature response is clarified for the first time, the importance of the OsPPR7 gene in maintenance of chloroplast functions under high-temperature stress is clarified, and a new gene resource and a technical path are provided for cultivation of new varieties of high-temperature-resistant rice.

The invention relates to a planting method for covering rice with a biodegradable film in a cold region. Comprising the following steps: (1) dry seedling raising: sowing 20-30g of seeds in each square meter of seedbed by adopting drill sowing or broadcast sowing; (2) preparing a compartment surface, turning over the soil, and loosening the soil; (3) applying a base fertilizer at one time, and applying 7-8 kg / mu of a nitrogen fertilizer, 2-4 kg / mu of a phosphate fertilizer, 3-5 kg / mu of a potassium fertilizer and 1.0-1.5 kg / mu of a zinc fertilizer to the compartment surface; (4) covering a film on the compartment surface, and covering a biodegradable film to be tightly attached to the soil 2-3 days after the fertilizer is applied; (5) transplanting plantlets: transplanting the plantlets when 3-4 true leaves grow on each seedling; (6) water management: after rice transplanting, water is kept in furrows, and no water exists on film surfaces; drying the field in the vigorous tillering stage; (7) timely harvesting. The growth conditions of heat tension, short rice growth period and limited yield potential in the northeast cold region in China are solved, temperature increasing, water retention and fertilizer saving can be achieved, and the comprehensive benefits of rice planting in the northeast cold region are improved.