231 results about "Soil carbon" patented technology

The invention relates to the field of agricultural fertilization, in particular to a soil carbon nitrogen ratio fused straw returning fertilization optimization method, which comprises the following steps of: performing standardization processing on farmland static characteristic data to obtain a farmland standardization characteristic vector and a characteristic standardization threshold value; performing coupling analysis on the straw returning amount and the soil carbon-nitrogen ratio in the farmland standardized feature vector set to obtain risk factors; performing path gradient integration on the risk potential energy field function to obtain a symmetric path cost gain factor; performing path cost gain correction on the Euclidean distance to obtain adaptive distance measurement; and fuzzy C-means clustering is performed on the farmland standardized feature vectors through adaptive distance measurement to obtain differentiated fertilization management partitions, so that the problem of inaccurate fertilization decision caused by incapability of identifying key feature nonlinear coupling risks in existing management partitions based on Euclidean distance is solved.

The invention discloses a forest carbon sink function monitoring method based on multi-source data. The method comprises the following steps: collecting data such as vegetation, soil, weather, landform and interference factors; the collected data are preprocessed; the preprocessed data are input into a Biome-BGC model for processing, and ecological system carbon flux parameters are obtained; determining a vegetation carbon sink amount and a soil carbon sink amount based on an ecological system carbon flux parameter, and obtaining a comprehensive carbon sink amount by combining artificial and natural interference carbon emission amounts; determining the forest carbon sink potential through a constructed forest carbon sink potential calculation formula based on the calculated comprehensive carbon sink amount; based on the calculated comprehensive carbon sink amount, time stability, space stability and anti-interference stability are determined, weighted summation is carried out on the time stability, the space stability and the anti-interference stability, and the carbon sink stability is determined; according to the method, the forest carbon sink function is monitored through multi-source data, the monitoring accuracy is improved, and the forest carbon sink potential, the carbon sink stability and the investment value are accurately quantified.

The invention relates to the field of agricultural data analysis, in particular to a japonica rice paddy field soil carbon nitrogen ratio dynamic intelligent assessment method, which comprises the following steps: acquiring and preprocessing japonica rice paddy field environment time sequence data to obtain a standardized environment data set; performing nonlinear congestion analysis on the soil moisture content state to obtain a corrected moisture dimension distance component; obtaining a corrected temperature dimension distance component by evaluating the metabolism permissible degree of the soil moisture on the temperature effect; performing double weighted fusion on the moisture and temperature correction distance components to obtain a soil environment state clustering result; through coupling calculation of a soil environment state clustering result and a first-order dynamic decomposition model, a dynamic intelligent evaluation result of the carbon-nitrogen ratio of the japonica rice paddy field soil is obtained, so that the problem that existing clustering cannot accurately distinguish aerobic and anaerobic environment states in a japonica rice paddy field scene and causes deviation of the evaluation result of the carbon-nitrogen ratio of the soil is solved.

The invention discloses a forest carbon reserve and carbon sink monitoring and evaluating method based on a multi-source remote sensing technology. The method comprises the following steps: multi-source remote sensing data acquisition: respectively acquiring optical remote sensing data and radar remote sensing data; tree species classification and identification: carrying out tree species classification on the forest in the research area to realize tree species scale space distribution information extraction; for different tree species, biomass model parameters obtained through field investigation are combined, a biomass estimation model based on the tree species is established, model input parameters are biomass model parameters, and vegetation biomass is output; calculating the carbon reserve: calculating the vegetation carbon reserve by utilizing the inverted vegetation biomass and combining the carbon content coefficients of different tree species; estimating the soil carbon reserve, and finally obtaining the total carbon reserve of the forest ecosystem: calculating the carbon reserve variation of the forest ecosystem at different time points based on the multi-source remote sensing data of the long-term sequence. According to the invention, large-range, high-precision and continuous forest carbon reserve and carbon sink monitoring and evaluation considering tree species difference is realized.

The invention provides a planting agriculture carbon sink metering method and system and computing equipment. The method comprises the following steps: establishing a dynamic farmland ecosystem carbon sink model according to biomass monitoring data, soil carbon content data, meteorological data and crop management measure records of a farmland ecosystem; based on the dynamic farmland ecosystem carbon sink model, analyzing carbon fixation efficiency under different crop types and different farming modes in a farmland ecosystem; and calculating the total carbon sink amount of the farmland ecosystem. According to the technical scheme provided by the invention, the dynamic farmland ecosystem carbon sink model is established, so that the carbon absorption capacity of the farmland ecosystem can be more accurately quantified, and the carbon sink metering precision is improved.

The invention discloses a gobi photovoltaic base ecological restoration carbon sequestration benefit evaluation method and system, and particularly relates to the technical field of ecological environment governance, and the method comprises the following steps: dividing a photovoltaic base region into a photovoltaic panel lower region, a photovoltaic panel inter-row channel region and a photovoltaic field peripheral region, building corresponding ecological simulation models for different regions, and constructing a photovoltaic field simulation model; simulation data are obtained and substituted into the first common calculation model and the second common calculation model respectively, calculation results of all the areas are summarized and substituted into a pre-trained machine learning model, and an output result is an ecological restoration carbon sequestration benefit value used for representing the final score of overall ecological restoration of the photovoltaic base; according to the method, the vegetation restoration and soil carbon storage process can be dynamically simulated, compared with a traditional static monitoring method, the future ecological restoration trend can be predicted, scientific support is provided for long-term ecological management, a targeted ecological optimization scheme can be provided based on regionalized simulation, and the ecological value of renewable energy sources is improved.

The invention discloses a monitoring system for forest ecological carbon sink calculation, and belongs to the field of ecological environment monitoring and carbon sink evaluation. Comprising a foundation optical remote sensing module, a crown biomass calculation module, a soil carbon component identification module, a vertical carbon flux detection module, a regional microclimate analysis module, a time sequence big data coupling module, a carbon source and carbon sink model fusion module and a result correction feedback module. The method comprises the following steps: collecting vegetation three-dimensional structure data through a multi-frequency laser radar, calculating unit-area canopy carbon storage acceleration in combination with seasonal climate interference parameters, and fusing turbulent carbon exchange and soil carbon change data to construct a regional carbon flux coupling model; the system collects cross-rosa chinensis carbon change data to construct a multi-dimensional feature tensor diagram, dynamically updates a weight and a fitting function, realizes carbon sink dynamic estimation and feedback optimization based on a biology-climate-time three-dimensional cooperation mechanism, and improves forest carbon sink monitoring precision and stability. The beneficial effect is that scientificity and accuracy of ecological environment monitoring and carbon sink evaluation are improved.

The invention relates to the technical field of wetland ecosystem soil carbon sequestration capability, in particular to a seasonal waterlogged wetland soil carbon estimation and dynamic monitoring method, which comprises the following steps of: selecting a sampling zone and a quadrat according to an equal-elevation water level gradient and a vegetation type; an optimal remote sensing estimation carbon model is determined through remote sensing image interpretation and screening of characteristic factors such as image waveband reflectivity, vegetation indexes, principal component characteristics and single-waveband textures, and soil organic carbon spatial distribution characteristics are analyzed through remote sensing inversion and GIS interpolation; constructing a Wetland-DNDC wetland carbon dynamic simulation model based on a DNDC model to predict wetland long-term carbon dynamic change and greenhouse gas emission; the invention provides a method for simulating carbon reserves and carbon dynamic monitoring based on field investigation and coupling a 3S technology with a Wetland-DNDC model. Compared with a traditional field observation method, the method has obvious technical and cost advantages, and can realize the technical advantages of spatial analysis and long-time sequence monitoring. The research method is suitable for a wetland ecosystem with seasonal hydrological characteristic changes.

The invention relates to the technical field of soil monitoring and data analysis, and discloses a soil carbon and nitrogen content dynamic prediction method based on deep learning. The method comprises the following steps: acquiring soil monitoring data from an environment monitoring platform, performing dimension reduction by using a multi-layer perceptron model to obtain core features, and dividing a dynamic monitoring data set according to the core features; taking the data set as input, and constructing an initial prediction model by using a time convolutional network; and constructing a meteorological factor library and an influence map, replacing an initial model time node, and obtaining a climatic factor node prediction model through cross validation. And performing regression fitting and cross validation verification by using a Gaussian process, and constructing a soil dynamic prediction model. According to the method, through multi-step data processing and model construction, the influence of soil data characteristics and meteorological factors is effectively mined, the dynamic change of the soil carbon and nitrogen content can be accurately predicted, and powerful support is provided for the fields of precision agriculture, environmental protection and the like.

The invention discloses a multi-modal data fused karst forest soil carbon cycle feature extraction method. The method comprises the following steps: acquiring soil physical and chemical protection component carbon data, bioactive component carbon data, isotopic tracing data and the like of different succession stages of a karst forest to establish multi-source heterogeneous data; integrating the obtained multi-source heterogeneous data into a'physical-chemical-biological-isotope 'four-dimensional feature space through feature tensor decomposition; constructing a carbon saturation capacity prediction hybrid optimization model, and outputting lt; the maximum carbon sequestration capacity and component carbon proportion of 53 [mu] m microaggregates; the method comprises the following steps: performing mineralization culture on soil in different succession stages of the karst forest, analyzing a dynamic proportion of exogenous carbon to original soil carbon and an input / output path of soil carbon in combination with a 13C / 15N double-standard-sample time-varying calibration curve, and calculating a carbon stability disturbance threshold. According to the method, collaborative analysis of multi-source data is realized, and the temporal-spatial resolution and the model precision of carbon cycle feature extraction are remarkably improved.

The invention provides a forest ecosystem carbon sink future scene simulation method and system, and belongs to the technical field of administrative management purpose information. Based on a high-precision curved surface simulation HASM method, processing the climate data and the soil data respectively, and extracting pixel values of the position of the forest sample plot in the climate raster data and the soil raster data into forest sample plot data to obtain a forest sample plot environment information data set; designing a plurality of future scenes of the forest ecosystem under different management measures; and simulating the carbon density of each future scene by using a Forest-DNDC model, predicting the carbon density of other areas except a forest sample plot by using a random forest model, and carrying out HASM simulation by taking a prediction result as an initial field and taking a simulation result output by the Forest-DNDC model as a control condition to obtain forest and soil carbon density raster data in the future scenes. According to the method, the simulation precision can be effectively improved, and a scientific basis is provided for formulating county scale forest management and climate alleviation policies in the future.

The invention relates to the technical field of agricultural ecological management, in particular to a farmland carbon and nitrogen cycle regulation and control method based on an ecological model, and the method comprises the following steps: S1, collecting ecological data of soil; s2, on the basis of the ecological data collected in the S1, constructing a carbon-nitrogen cycle regulation and control model by utilizing an ecological model coupled with a carbon-nitrogen cycle relationship; s3, performing carbon-nitrogen balance analysis by using the carbon-nitrogen cycle regulation and control model, and further determining a balance point between carbon-nitrogen input and loss; s4, formulating a carbon nitrogen regulation and control scheme according to a carbon nitrogen balance analysis result in S3; s5, performing specific operation according to the carbon nitrogen regulation and control scheme formulated in the S4; and S6, if the soil carbon and nitrogen content does not reach the set target, dynamically adjusting the carbon and nitrogen regulation and control scheme according to a feedback result. According to the invention, through combination of ecological data acquisition and a carbon nitrogen cycle model, dynamic balance regulation and control of farmland carbon nitrogen cycle are realized, the resource utilization efficiency is improved, the environmental pollution is reduced, and the sustainability of a soil ecological system is enhanced.

The invention discloses a rhizosphere deposited carbon flux real-time monitoring method adopting a sensor array, and relates to the technical field of soil carbon cycle monitoring, and the method comprises the steps: determining a layered sampling depth and a horizontal concentric circle partition range based on the three-dimensional distribution characteristics of a target plant root system, and mapping the layered sampling depth and the horizontal concentric circle partition range to a preset three-dimensional grid coordinate system; gas sensors and environmental parameter sensors are deployed according to root system partitions, and a multi-dimensional sensor array is constructed. Through the three-dimensional grid coordinate system and the root system density gradient model, accurate spatial mapping of rhizosphere carbon flux is realized, high matching of sensor layout and root system biomass distribution is ensured by utilizing division of vertical layering and horizontal concentric circle partition, and the gas sensor and the environmental parameter sensor are cooperatively deployed, so that the reliability of the system is improved. The device can capture instantaneous changes such as root exudate pulse and microbial respiration, generates a continuous and consistent carbon flux data set, and provides a high-resolution dynamic observation basis for researching plant-soil-microbial interaction.

Disclosed is a method and device for predicting soil organic carbon based on spectrum-guided ensemble learning. The method includes: obtaining a soil sample and a real organic carbon content and an original soil spectrum thereof, pre-processing the original soil spectrum to obtain a soil spectrum sample, constructing, based on the soil spectrum sample, a sample set, grouping the sample set into a first training set and a validation set, and using the real organic carbon content as a label; training, based on the first training set and the corresponding labels, a partial least squares regression model, a Cubist model and a random forest model to obtain carbon content predicted value sets of the three models; constructing, based on the carbon content predicted value sets of the three models and soil spectrum principal component data, a second training set, and training a second random forest model with the second training set and corresponding labels to obtain a spectrum-guided ensemble model. The method combines the advantages of different predictive models and can accurately predict the soil carbon content.

The invention relates to the technical field of carbon sink calculation, in particular to a forestry carbon sink calculation model, a forestry carbon credit calculation method and a storage medium. The model comprises an overground biological carbon sink amount estimation module used for calculating overground biological carbon sink data of a target area, an underground soil carbon sink amount estimation module used for calculating soil carbon sink data of the target area, and a litter carbon reserve estimation module used for calculating litter carbon sink data of the target area. The combined loss calculation module is used for calculating carbon loss data; and the final carbon sink total quantity fusion module is used for calculating the carbon sink quantity according to the aboveground biological carbon sink data, the soil carbon sink data, the litter carbon sink data and the carbon loss data. A forestry carbon sink calculation model based on multiple dimensions is established through multiple types of carbon sink estimation modules, and the problem that the requirement for rapid authentication of the global carbon market cannot be met due to high manual dependency is solved; the problems of low calculation precision, high cost and the like caused by insufficient model dynamics, single model calculation dimension and the like are solved.

The invention provides a hydraulic engineering carbon sink value accounting method and system, and relates to the crossing field of hydraulic engineering and environmental science, and the method comprises the steps: collecting the engineering basic data and multi-dimensional ecological data of the hydraulic engineering; constructing a soil carbon sink sub-model, a water body carbon balance sub-model and a vegetation biological quantum model to form a carbon sink dynamic accounting model; and dynamically calculating the total carbon sink amount and converting the total carbon sink amount into an economic value according to the engineering basic data, the multi-dimensional ecological data and the carbon sink dynamic accounting model. The method is used for quantifying the carbon sink contribution of the water conservancy project to ecological systems such as soil, water and vegetation and converting the carbon sink contribution into economic value evaluation, so that the defects in the prior art are overcome, the carbon sink value of the water conservancy project is accurately and comprehensively calculated, and a scientific basis is provided for environmental benefit evaluation and sustainable development of the water conservancy project.

The invention discloses a dynamic monitoring method, system and device for soil carbon loss and a storage medium, and relates to the technical field of environment monitoring, and the method comprises the steps: obtaining soil parameters through a multi-mode sensing array and a runoff monitoring device which are arranged in a target soil area, the soil parameters comprise a soil gaseous parameter, conductivity, a soil solid parameter and a liquid carbon parameter; calculating a carbon loss amount generated by soil respiration according to the soil gas state parameter, and taking the carbon loss amount as a respiration carbon flux; according to the conductivity, the soil solid parameters and a preset soil organic carbon content relation model, calculating the carbon loss amount of soil erosion migration as erosion carbon flux; calculating the carbon loss amount of soil leaching loss according to the liquid carbon parameters, and taking the carbon loss amount as leaching carbon flux; and performing weighted summation on the respiration carbon flux, the erosion carbon flux and the leaching carbon flux to obtain the total carbon loss of the soil in the target area. A more comprehensive carbon income and expenditure evaluation method is provided by establishing a soil total carbon loss calculation framework covering'gas-solid-liquid 'three phases.

The invention discloses a method for promoting bacillus soil microorganisms to actively absorb oxygen to degrade long-chain alkanes, which comprises the following steps: preparing a catalyst: uniformly mixing oil-containing soil, a carbon source, citric acid, ferric salt, hydrogen peroxide and distilled water, filtering, concentrating clear liquid to obtain a concentrated crystal substance, centrifugally cleaning the crystal substance, and drying to obtain the catalyst; the method comprises the following steps: mixing a catalyst with oil-containing soil, hydrogen peroxide and distilled water, and oscillating on a shaking table for Fenton pre-oxidation; after pre-oxidation, intermittent oscillation oxygenation is carried out, bioremediation is carried out on the petroleum-contaminated soil at normal temperature, and the three petroleum bacteria in the soil are activated. Through pre-oxidation treatment, consumption of soluble organic carbon by microorganisms in soil is stimulated, the active oxygen uptake process of the microorganisms is accelerated, and the carbon metabolism process is accelerated. Finally, the bacillus-like microorganisms capable of degrading the petroleum are activated, so that the aim of degrading the petroleum hydrocarbon in the soil for a long time is fulfilled.

The invention relates to the technical field of forest wetland carbon sink monitoring and evaluation, and particularly discloses a forest wetland carbon sink intelligent monitoring and evaluation system and method. According to the method, a vegetation carbon sequestration potential evaluation result is obtained by analyzing vegetation structure feature data of forest, water and soil composite ecology of the forest wetland, a water-soil-carbon cooperative evaluation result is obtained by analyzing specific hydrological-soil carbon cycle key elements of the forest wetland, and environmental disturbance response factors are obtained by combining various environmental disturbance factors. Through multi-source data fusion and intelligent modeling, a carbon sink quantitative evaluation value is output, and abnormal feedback is triggered; the problems that in the prior art, adaptability to a forest wetland compound ecological system is insufficient, evaluation refinement is insufficient, and dynamic response is lacked are solved. According to the method, accurate and dynamic monitoring and evaluation of forest wetland carbon sink are realized, carbon sink short plates can be accurately positioned, optimization support is provided, and technical support is provided for protection, restoration and optimization management of forest wetland carbon sink resources.

A soil carbon measurement device (100) can include a subsurface support (110) configured to be inserted at least partially under a soil surface. The subsurface support can include an interior volume (114) and a. gas-permeable barrier separating the interior volume (114) from soil under the soil surface. The device (100) can also include an ultraviolet light source (1.30) positioned to expose the soil under the soil surface to ultraviolet light, and a carbon dioxide sensor (150) configured to measure a concentration of carbon dioxide in the interior volume (114) of the subsurface support (110).

The present disclosure discloses a method of determining efficiency of increasing a soil carbon sink based on green manure returning to fields and a system thereof. The method includes: determining green manure biomass of a target farmland based on an unmanned aerial vehicle lidar technology during a fallow period of the target farmland before green manure is turned over; calculating carbon biomass of the target farmland based on the green manure biomass; calculating microbial soil carbon pump efficiency and mineral carbon pump efficiency after the green manure of the target farmland is turned over; and determining a soil carbon sink effect of turning over green manure on the target farmland according to the carbon biomass, the microbial soil carbon pump efficiency and the mineral carbon pump efficiency. The present disclosure realizes the quantitative calculation of efficiency of increasing the soil carbon sink of green manure.

The invention relates to the technical field of carbon sink trend extraction, in particular to an extraction method performed by a carbon sink nonlinear trend extraction system based on ensemble empirical mode decomposition, which comprises the following steps: S1, acquiring forest carbon sink time sequence data to form a forest carbon sink time sequence data set, the forest carbon sink time sequence data are vegetation coverage rate VCR, soil coverage rate SCR, vegetation carbon content Cveg, soil carbon content Coil and total carbon storage capacity Ctotal at different seasons and times. According to the method, the overall carbon sink capacity of the forest can be evaluated more accurately by monitoring the carbon storage capacity in the vegetation and the soil, and how the carbon sink is influenced by climatic factors can be better understood by monitoring the changes according to the fact that the carbon storage capacity of the vegetation and the soil possibly fluctuates along with seasonal changes, so that the carbon sink capacity of the forest can be evaluated more accurately. Meanwhile, in the process of monitoring the change of the carbon storage capacity in different seasons, a long-term change trend chart of the forest carbon sink is extracted according to the rule of the influence of the non-linear change of the carbon storage capacity of the vegetation and the soil on the forest carbon sink capacity.

The invention relates to the technical field of carbon sink metering and monitoring, and discloses a forest soil carbon sink metering and monitoring device which comprises a vehicle body and a mounting plate, a turntable is rotatably connected in the mounting plate, a sampling cylinder is fixedly mounted on the inner wall of the turntable, and a mounting frame is fixedly mounted at the top of the mounting plate. According to the forest soil carbon sink metering and monitoring device and method, the excavation sampling assembly is arranged, and after the excavation sampling assembly is used, under starting of a servo motor and meshing transmission of an inner gear ring and a transmission gear, a plurality of excavation shovels can rotate to the lower surface of a sampling cylinder together; according to the soil sampling device, a plurality of digging shovels are arranged in the sampling barrel, and are matched with starting of a servo motor and meshing transmission of a driving gear and an outer gear ring to rotate around the axis of the sampling barrel together, so that soil in the sampling barrel is separated from soil in a sampling area, and cylindrical sampling soil in the sampling barrel can be completely taken out under lifting of the plurality of digging shovels; and the accuracy of forest soil carbon sink metering and monitoring data is ensured.

The invention discloses an acid contaminated soil carbon emission reduction method based on a coupled ecological system, which comprises the following steps: adding rice straw biochar into acid contaminated soil, planting plants which are perennial ryegrass, and after the plants are cultivated to a mature period, strengthening the photosynthesis capability of the plants and the carbon sequestration capability of the soil at the same time, so as to improve the carbon sequestration capability of the acid contaminated soil. The negative increase of the CO2 emission cumulant and the remediation of the acidic polluted soil are realized. According to the method, the emission cumulant of CO2 in the acid polluted soil is greatly reduced, the total absorption amount of CO2 reaches up to 193.41 g / m < 2 >-304.41 g / m < 2 >, and the method has the advantages that raw materials are low in cost and easy to obtain, operation is easy, the operation cost is low, secondary pollution is avoided, and the method is suitable for large-scale use and has wide application prospects in the field of carbon emission reduction of the acid polluted soil (such as heavy metal pollution).

A carbon fixation material for adsorbing heavy metals in soil and a preparation method thereof are provided. The carbon fixation material includes modified biochar, calcium silicate, aluminum sulfate, hydroxymethyl cellulose and urea. The modified biochar is prepared by preparing biochar from agricultural and forestry waste, and modifying the biochar with ferric chloride and a mercapto silane coupling agent. The carbon fixation material has excellent carbon fixation capacity, the biochar is prepared by processing agricultural and forestry waste, the material source is green and environmentally friendly, can reduce environmental pollution. After modified by ferric chloride and mercapto silane coupling agent, the biochar has excellent adsorption amount and adsorption capacity for heavy metal ions and has strong retention capacity after adsorption, the modified biochar can be widely used in soil carbon fixation and heavy metal pollution treatment.

The invention discloses a machine learning and multi-source variable-based high-precision prediction method for soil organic carbon in an arid region, and solves the problems of high spatial heterogeneity of soil organic carbon in the arid region and high traditional detection cost. The method comprises the following steps: collecting a soil sample by adopting layered random sampling, and integrating seven types of environmental variables such as climate, vegetation, terrain and remote sensing to construct a feature set; a Boruta algorithm is adopted for screening, an optimized feature set is obtained, and redundant data are eliminated; the method comprises the following steps: dividing a training set and a test set through Kolmogorov-Smirnov test; the method comprises the following steps of: generating 100 base models by using parameter optimized random forest and extreme gradient lifting double-model collaborative prediction and combining a Bootstrap integration strategy; inputting the target area optimization feature set to obtain an organic carbon prediction result; according to the method, the monitoring cost is effectively reduced, spatial-temporal dynamic inversion of soil organic carbon based on historical environment variables is supported, and a reliable technical scheme is provided for dynamic monitoring and ecological management of soil carbon.

The invention belongs to the technical field of soil organic matter improvers, and discloses a soil organic matter improver based on a compound microbial agent and a preparation method thereof, and the soil organic matter improver comprises the following components: a compound enzyme, a modified chitosan microsphere complex, a modified polyelectrolyte, an inhibitor L-methionine sulfoximine, a substrate, an auxiliary factor and the compound microbial agent. A compound enzyme system is used as a core, soil ammonium ions are circularly and efficiently assimilated through glutamine synthetase / glutamate synthetase, and the soil ammonium ions are converted into organic nitrogen; and energy guarantee is provided by virtue of polyphosphate kinase. The modified chitosan microsphere complex is used for protecting and slowly releasing enzyme and a substrate, and controlled release of the inhibitor L-methionine sulfoximine is realized through the modified polyelectrolyte, so that carbon-nitrogen balance of soil is regulated and controlled. The system has a synergistic effect with a compound microbial agent, the problem of soil organic matter reduction caused by excessive nitrogen application is effectively solved, meanwhile, the crop root biomass is remarkably increased, and the soil organic matter content is increased.

The invention discloses a straw particle plowing and applying technology for rapidly increasing organic carbon in tobacco field soil, which adopts straw particle fertilizer as a returning raw material and returns to the field in a manner of deeply plowing into soil. According to the technical scheme, a certain amount of straw particles are returned to the field in cooperation with deep ploughing and returning to the field, the content of organic carbon components in soil of soil layers of 0-20 cm and 20-40 cm can be increased at the same time, and the method is an effective measure for promoting soil carbon sequestration.

The invention discloses a method for detecting soil active organic carbon based on fluorescence spectrometry, and belongs to the technical field of soil detection. The method comprises the following steps: sequentially drying, sieving and grinding fresh soil to obtain a soil sample, and sequentially performing active organic carbon extraction, purification, decoloration and pH regulation on the soil sample to obtain a soil liquid to be detected. The method comprises the following steps: adding fluorescein into a soil liquid to be detected to form a soil internal standard detection liquid, obtaining a soil fluorescence spectrum through three-dimensional fluorescence spectrum scanning, carrying out background deduction and correction coefficient correction, and calculating the active organic carbon concentration of the soil by using tryptophan, tyrosine and SMP fluorescence concentration standard curves. According to the method, an internal standard method is combined with a fluorescence spectrum technology, and through multi-step sample pretreatment and spectrum correction, the detection accuracy and the anti-interference capability are improved, the active organic carbon concentration of the soil can be rapidly and accurately determined, and an effective means is provided for soil carbon cycle research and quality evaluation.

The invention relates to the technical field of carbon reserve estimation, and discloses a mangrove forest biomass carbon reserve estimation method based on a different-speed growth inversion model, and the method comprises the following steps: 1, setting a quadrat region; 2, collecting aerial images, kandelia candel morphological data, kandelia candel destructive data and soil profile organic carbon density data; step 3, establishing an allotropical growth inversion model; processing the kandelia candel destructive sampling parameters to obtain a kandelia candel carbon conversion coefficient; performing image processing and visual interpretation on the aerial image of the research area to obtain the crown breadth coverage total area and the mud flat coverage area of the kandelia candel in the research area; 4, the overall kandelia candel carbon reserve is obtained by combining the kandelia candel morphological data, the total crown breadth coverage area of the kandelia candel, the different-speed growth inversion model and the kandelia candel carbon conversion coefficient; and combining the organic carbon density data of the soil profile and the mud flat coverage area to obtain the overall soil carbon reserve. Meanwhile, the invention further provides a mangrove forest biomass carbon reserve estimation system based on the different-speed growth inversion model.