2722 results about "Biomass" patented technology

The invention discloses a regional scale crop nitrogen dynamic regulation and control method and device. The method comprises the following steps of obtaining multi-source data and constructing a space-time database; selecting a crop growth model, and calibrating and verifying the crop growth model based on the space-time database to obtain the crop growth model and generate a localized model parameter set; dividing a target area into space units, inputting soil data, meteorological data and a localized model parameter set of each space unit to a crop growth model, simulating crop growth processes of different nitrogen gradients, extracting optimal biomass and critical nitrogen concentration data point pairs of each space unit, and performing fitting to generate a spatialized pCNDC parameter map layer; inverting an actual biomass and nitrogen concentration spatial distribution map based on remote sensing data, calculating critical nitrogen concentration and nitrogen nutrition index of each spatial unit in combination with a pCNDC parameter map layer, and generating a spatial distribution map; when the nitrogen nutrition index is lower than a preset threshold value, the nitrogen deficiency amount is calculated, and a variable fertilization prescription map is generated.

The invention discloses a method for evaluating enhancement and release seedling resources based on environmental DNA polymerization analysis. The method comprises the following steps: carrying out gridding partition on a target water area, collecting a water sample through a designed sampling scheme, and carrying out DNA extraction and high-throughput sequencing to obtain species sequence information of each sampling point. Sequencing data is subjected to species identification by using a bioinformatics method, released species are identified, a spatial abundance model is established, and a preliminary distribution map is generated. And establishing a DNA degradation kinetic model in combination with water area environmental parameters, and carrying out reverse correction on abundance distribution. And through a resource inversion model coupled with hydrodynamics, analyzing biomass distribution characteristics and migration laws of the release group, and obtaining a resource evaluation result. And finally, a species environment preference model is constructed based on migration path analysis, an optimal release area is matched in a target water area, a scientific scheme including release point locations, opportunities and quantity is generated, and a whole-process technical support and a decision basis are provided for enhancement and release.

The invention discloses a method for estimating plant biomass based on map multi-modal feature extraction and fusion. The method comprises the following steps: acquiring a plant RGB image and a multi-spectral image; inputting the preprocessed RGB image and NIR wave band image into a double-model cooperation segmentation framework to realize image segmentation; binary image features, color features, texture features, reflectivity and the like are calculated, feature splicing is carried out, and high-dimensional features are constructed; carrying out dimension reduction on the high-dimensional features; and training a deep neural network through the effective features and the biomass to realize biomass estimation. According to the method, a zero sample learning-based double-model cooperation segmentation framework is utilized to realize accurate segmentation of a single plant on the premise that a large number of training sets are not needed; multi-modal feature information is extracted based on the segmented single plant image, an improved SHAP model is introduced to reduce the feature space dimension, and the inversion precision and the operation efficiency are improved while the information effectiveness is ensured; through a high-precision deep neural network model, rapid, lossless and accurate biomass acquisition is realized.

The invention relates to the technical field of chemical automation control, and discloses an intelligent closed-loop control system for producing p-dichlorobenzene by a biomass method, which comprises a signal acquisition module, a residence time reconstruction module, a thermal coupling analysis module, a parameter self-adaptive scheduling module and an execution control module. The rheological characteristics of raw materials are monitored by collecting the current of a stirring motor, the liquid level is dynamically increased through a retention time reconstruction module to prolong the retention time of the materials, and a liquid level periodic migration strategy is introduced to prevent scaling of a gas-liquid interface; the thermal coupling analysis module and the parameter self-adaptive scheduling module are used for calculating thermal retardation post factors, temperature control parameters are corrected in real time, the upper limit of cooling output is limited, inner wall supercooling crystallization is prevented, and the problems that the conversion rate is reduced, the heat transfer efficiency is reduced and equipment is hung on the wall due to viscosity fluctuation of biomass raw materials are effectively solved. And the self-adaptive stable control of the reaction process is realized.

The invention provides a biochar composite porous material for heavy metal contaminated soil remediation and a preparation method and application of the biochar composite porous material. The preparation method comprises the steps that biomass raw materials are subjected to high-temperature pyrolysis carbonization and then smashed, ground and sieved, and biochar powder is obtained; dispersing in a phosphoric acid solution to obtain a biochar solution, and filtering, washing and drying after a hydrothermal activation reaction to obtain activated biochar; dispersing in a chitosan solution, carrying out ultrasonic oscillation, filtering, washing and drying to obtain modified charcoal; mixing sodium bentonite, attapulgite and deionized water, uniformly mixing the modified charcoal, the functional slurry and a sodium carboxymethyl cellulose solution to obtain composite slurry, performing compression molding to obtain a green body, and then drying and calcining the green body. The biochar composite porous material prepared by the invention can simultaneously play multiple roles of physical adsorption, chemical chelation, ion exchange and the like in a heavy metal contaminated soil treatment process, so that efficient fixation of various heavy metal ions is realized.

The invention relates to a mixed scale optimization regulation and control method and device for rural energy and a storage medium, and belongs to the technical field of new energy. According to the method, layered optimization is carried out by establishing a monthly time scale optimization scheduling model, a day-ahead time scale optimization scheduling model and an intra-day time scale optimization scheduling model which are connected with one another, and long-term economic planning and medium-short-term operation scheduling are organically combined, so that multi-target collaboration and multi-energy complementation are realized; specifically, through monthly optimization, an optimal purchase and inventory strategy can be formulated according to seasonal price fluctuation of biomass, the fuel cost is remarkably reduced from the source, and the overall economical efficiency of the system is improved; through a day-ahead gas storage plan and intra-day real-time scheduling, the fluctuation and intermittency of wind energy and solar energy power generation can be effectively stabilized by utilizing the stability and controllability of biomass power generation, and the power load demand can be stably met under various working conditions, so that the stability and reliability of power supply are enhanced, and the energy consumption is reduced. And on-site efficient consumption of rural renewable energy sources is promoted.

The application discloses a kind of derived biomass hard carbon material pulverization process, belong to biomass charcoal material processing technical field, first, pulverization process includes the following steps: after drying, the coconut shell derived hard carbon block is carried out primary crushing, while spraying first modifier, obtain the particle size 1~3mm of coarse crushing modified particle;Coarse crushing modified particle is carried out secondary precision crushing under argon atmosphere, while spraying second modifier, obtain the precision crushing modified particle of D 50 Particle size is 15 μm;Precision crushing modified particle is carried out roll grinding spheroidization, while spraying third modifier, obtain the spherical modified particle of D 50 Particle size is 10 μm;Spherical modified particle is carried out flash drying after cooling, then add magnesium stearate to it, after mixing, obtain derived biomass hard carbon material.Then, the application realizes breakthrough in tap density, particle size distribution, first efficiency and other core indexes by the coordination of three-stage gradient modification and progressive pulverization process.

The invention discloses a biomass charcoal processing pelletizer, and relates to the technical field of pelletizers, the biomass charcoal processing pelletizer comprises a driving assembly and a pelletizing chamber, a circular mold is fixedly connected in the pelletizing chamber, the output end of the driving assembly is an output shaft extending into the pelletizing chamber, during pelletizing operation, two compression rollers revolve around the axis of the circular mold along with rotation of the output shaft, and meanwhile, the two compression rollers rotate around the axis of the circular mold along with rotation of the output shaft. Under the action of the rotating assembly, in the process, the pressing roller automatically rolls to bite materials into an extrusion area, further, force applied to the materials by rolling of the pressing roller is perpendicular to the tangential direction of the outer contour of the pressing roller, and the included angle between the pressure direction and the axis direction of a discharging die hole of the circular die is extremely small, so that the working efficiency is high; active rotation of the compression roller replaces passive rotation, passive rotation promoted by friction between the compression roller and the circular mold and materials is avoided, accumulated heat in the granulation chamber is reduced, energy is saved, meanwhile, abrasion of the materials to the compression roller and the circular mold is relieved through active rotation compared with passive rotation, and the equipment maintenance cost is reduced.

The invention provides an organic carrier in-root-rhizosphere growth-promoting microbial agent for ecological restoration of degraded grassland as well as a preparation method and application of the microbial agent, and belongs to the technical field of grassland ecological restoration and microbial agents. The organic carrier growth-promoting microbial agent disclosed by the invention is prepared from four kinds of growth-promoting bacteria (PGPE) in roots, four kinds of growth-promoting bacteria (PGPR) in roots and an organic carrier, the PGPE comprises terracotta warrior bacillus K4, bacillus 9-3-1, bacillus deserticola 11-5-4 and halomonas L31, the PGPR comprises serratia rubra 5, serratia rubra 23, cosinia cosinii 11 and enterobacter parabarium 24, and the organic carrier is a carbon-based organic fertilizer, a cattle and sheep manure organic fertilizer or biochar. When the organic carrier growth-promoting microbial agent is applied to the degraded grassland, the biomass and coverage of plant communities can be remarkably improved. The organic carrier growth-promoting microbial agent can be used for ecological restoration of degraded grassland.

The invention relates to the technical field of inversion systems, in particular to a coastal wetland forest ecosystem biomass and carbon sink rapid inversion system. According to the technical scheme, the system comprises a data acquisition and preprocessing module, an inversion module based on machine learning, a spatial heterogeneity adaptive module, a dynamic monitoring and updating module and a result visualization and output module. According to the method, a data basis is provided for accurate inversion through multi-source data fusion, and meanwhile, an inversion model combining the generative adversarial network and the long-short-term memory network realizes combination of a physical model and deep learning, so that the interpretability of the physical model is reserved, and the model performance is improved by utilizing the strong fitting capability of the deep learning; according to the invention, the adaptability of the system in a complex coastal wetland environment is improved through the spatial heterogeneity adaptive module, and the reliability of an inversion result is improved; according to the invention, real-time dynamic monitoring of biomass and carbon sink is realized through the dynamic monitoring and updating module, and rapid response of ecological system change is supported.

Certain exemplary embodiments can provide systems and / or methods for producing dried biomass materials, such as from bales of biomass. Biomass materials can be converted into, e.g., pellets, briquettes, cubes, and / or other products with dried and / or densified states. These dried, densified products can be used for, e.g., bioenergy and / or animal feed applications.

The invention relates to the technical field of soil remediation, in particular to a charcoal-fungus symbiont for a freeze-thaw environment and a preparation method and application of the charcoal-fungus symbiont. The preparation method of the charcoal-fungus symbiont comprises the following steps: crushing a biomass raw material, and carrying out pyrolysis to prepare basic charcoal; placing the basic biochar in an iron oxide solution, and carrying out an iron oxide loading reaction to obtain iron oxide biochar; the preparation method comprises the following steps: dipping iron oxide biochar in a chitosan solution for coating modification, then continuously adding a cross-linking agent for cross-linking solidification, and freeze-drying to obtain chitosan-iron oxide composite modified biochar; and immersing the chitosan-iron oxide composite modified biochar into a bacterial suspension of functional microorganisms, oscillating and adsorbing, and freeze-drying to obtain the carbon-bacteria symbiont. The invention aims to improve the heavy metal pollution phenomenon of soil and the soybean root rot disaster in the freezing and thawing cycle environment at the same time.

The invention relates to the technical field of forestry management, in particular to a forest and grass resource dynamic monitoring system which comprises the steps that a graph attention network is adopted to conduct high-low weight recognition processing on the structure difference value between node pairs, feature vectors are established through the canopy height difference and canopy density difference between adjacent nodes, and the canopy height difference and the canopy density difference between adjacent nodes are obtained; an edge weight scoring system is constructed in the form of segmented statistics and proportion weighting, node edge pairs with high influence relation strength are dynamically screened, ordered aggregation of spatial communication strength is realized, a graph neural network is introduced in a parameter fusion stage to construct a node parameter representation mechanism, and the spatial communication strength is improved. The tree species proportion, the grade of diameter at breast height and the community vertical structure in a regional sample plot are used as input features, unified mapping of node features of each region is completed in multiple rounds of iteration, cross-regional difference analysis is executed on model output in combination with biomass change frequency, parameter items with the difference proportion lower than a set threshold value are replaced with unified expression, and the model output is obtained. And parameter synchronization is realized to realize space nesting and feature integration.

The invention discloses clostridium and application thereof in fermentation production of alcohol, and belongs to the technical field of industrial microorganisms. The clostridium is a carbon monoxide eating clostridium strain GG6, and is preserved in the China General Microbiological Culture Collection Center (CGMCC), the preservation number is CGMCC No.34975, and the preservation time is June 23, 2025. The clostridium is a carbon monoxide eating clostridium strain GG6 which is preserved in the China General Microbiological Culture Collection Center (CGMCC), the preservation number is CGMCC No.34975, and the preservation number is CGMCC No.34975. The carbon monoxide eating clostridium GG6 is obtained by enriching tail gas flue sediments of a coal chemical plant through an abundant culture medium, evolving a screening culture medium and sorting single bacteria, the bacterial strain is fermented by taking synthesis gas (CO / H2 / CO2) as raw material gas to generate acetic acid, ethanol, butyric acid and butanol, the thallus biomass OD600 is more than or equal to 6, the concentration of produced ethanol is more than or equal to 10g / L, the concentration of produced butanol is more than or equal to 2.5 g / L, and the concentration of produced butanol is more than or equal to 2.5 g / L; and commercialized implementation of butanol production through gas fermentation is facilitated.

The invention provides a mining area vegetation reconstruction method based on vegetation classification and division. The method relates to the technical field of ecological environment restoration, and comprises the following steps: S1, acquiring mining area environment data by adopting a mode of combining remote sensing images, unmanned aerial vehicle aerial photography and ground sampling, performing spatial interpolation, normalization and filtering preprocessing on the environment data, and outputting a mining area ecological factor database; s2, on the basis of the ecological factor data, constructing a multi-index evaluation model by combining an analytic hierarchy process with clustering analysis to perform vegetation type division on the mining area, and generating partition templates with different ecological functions; and S3, constructing a plant phenological growth prediction model based on years of phenological observation data and weather forecast information. According to the mining area vegetation reconstruction method based on vegetation classification and division, precise planting and spatial layout are completed, the vegetation survival rate, biomass production and community diversity are remarkably improved, and the strict requirements of mining area ecological reconstruction for diversity and adaptability are met.

The invention provides a porous ceramsite adsorption material prepared from straw biochar and rare earth tailings as well as a preparation method and application of the porous ceramsite adsorption material, and belongs to the technical field of environmental functional adsorption materials. The preparation method of the porous ceramsite adsorption material using the straw biochar and the rare earth tailings comprises the following steps: sequentially performing acid pickling and drying on the straw biochar to obtain acidified biomass charcoal; the rare earth tailings are subjected to ball milling, and tailings fine powder is obtained; mixing the acidified biomass charcoal, the tailing fine powder, the attapulgite and the wood chips to obtain a mixture; adding a binding agent and water into the mixture, and sequentially performing kneading and extrusion molding to obtain a ceramsite precursor; and calcining the ceramsite precursor in a protective atmosphere to obtain the porous ceramsite adsorption material. The technical problems that a traditional adsorption material is low in adsorption capacity, poor in strength and difficult to recycle are solved through ternary compounding of the acidified biomass charcoal, the rare earth tailings and the attapulgite and in combination with wood chip pore-forming, segmented calcination and acid pickling pretreatment.

The invention discloses a carbon transaction-oriented biomass gas coupling coal-fired power generation full-life-cycle carbon emission accounting method. The method comprises the steps of determining accounting boundaries of collection and transportation, storage pretreatment, gas production and coupling power generation of covering raw materials; activity data are collected, space-time mapping of upstream batch data and unit side continuous operation data is established, and data quality grading and uncertainty measurement are carried out; when actually measured synthesis gas components or lower calorific values are missing, a soft measurement model is constructed based on operation data, batch characteristic feedforward coupling is introduced, and an estimated value and uncertainty are output; calculating an intermediate quantity based on a material-energy-carbon conservation mechanism model, performing dynamic correction by adopting a residual correction model containing physical consistency constraint, and adjusting a physical constraint weight according to uncertainty; and an emission list and an MRV data packet are generated in combination with the dynamic emission parameters, and are used for monitoring, reporting, checking and transaction settlement, so that the precision and the traceability are improved, and the physical consistency is ensured.

The invention relates to the technical field of biology, in particular to application of a biological product expressed by an EsPTI15 gene to regulation and control of tiller number. The nucleotide sequence of the EsPTI15 gene is shown as SEQ ID NO: 1, it is found for the first time that the tiller number of EsPTI15 gene overexpressed siberian wildrye is remarkably increased compared with wild siberian wildrye, and the result proves that overexpression of the EsPTI15 gene can positively regulate and control the plant tiller development process. The discovery not only enriches the molecular mechanism theory of plant tillering regulation, but also verifies that the EsPTI15 gene has the application potential of increasing the tillering number of the plant, and provides key theoretical support and gene resources for subsequent technical research and development of introducing the EsPTI15 gene through gene operation, increasing the tillering number of forage grass and further realizing biomass improvement.

According to the rural air conditioning device, coal or biomass straw is adopted as fuel, the energy storage technology is combined, flue gas waste heat generated by a kitchen range device is efficiently recycled and stored, the stored energy is used for dragging an absorption type refrigerating device to be used for refrigerating and heating air, and an adopted regenerator can flexibly adjust the operation mode and is used for peak clipping and valley filling; the energy-saving kitchen range is used for refrigerating, heating or drying clothes, the power consumption is low, the comprehensive heat utilization efficiency of the kitchen range is greatly improved, the market application space is obvious, and the expected economic, social and environment-friendly benefits are remarkable.

The invention discloses a green tide biomass acquisition method based on multi-source satellite remote sensing and application, and relates to the technical field of satellite remote sensing green tide monitoring, and the method comprises the steps: respectively constructing biomass inversion models of different satellites based on spectrum curves of different biomass densities measured on site and a satellite spectral response function; processing the satellite remote sensing image, calculating an NDVI vegetation index, extracting green tide information and obtaining a green tide distribution range; the green tide biomass density of each pixel in each star source green tide patch is calculated, and the biomass and the gravity center in the green tide patch are counted; and fusing the multi-source satellite green tide patch biomass to obtain the green tide biomass. Drifting prediction is carried out based on green tide biomass, a to-be-salvaged green tide plaque information table is established, and green tide salvage areas are determined in sequence according to the overall single-day salvage capacity of ships. According to the invention, remote sensing technology achievements are directly endowed to first-line disaster disposal actions, synchronization of monitoring capability and treatment efficiency is realized, and substantial improvement is realized.

The invention belongs to the technical field of building materials, and particularly relates to a preparation method of a biomass reinforced cement-based thermal insulation wall material and the wall material. The preparation method comprises the following steps: (1) crushing wood fibers, putting the crushed wood fibers into a NaOH solution, washing with water and drying; (2) carrying out dry mixing on cement, the modified wood fiber, nano SiO2 particles and calcium stearate; (3) diluting hydrogen peroxide with warm water, adding into the mixture, and stirring; (4) injecting the foaming slurry into a mold, and vibrating; and (5) steam curing. Through a collaborative technology of fiber surface modification, nano-particle regulation and control and hydrophobic layer construction, the comprehensive performance breakthrough of the fireproofing grade of A1 grade, the heat conductivity coefficient of 0.048-0.055 W / (m.K) and the compressive strength of 1.2-1.8 MPa is realized. The energy consumption is reduced by 70% through the low-temperature steam curing process, the proportion of agricultural waste is larger than or equal to 30%, the carbon emission intensity is smaller than or equal to 150 kgCO2 / m < 3 >, and the requirement for green buildings is met.

The invention discloses a lake cyanobacterial bloom intelligent early warning method based on unmanned aerial vehicle remote sensing and image recognition, and the method comprises the steps: fusing an unmanned aerial vehicle multispectral image and a convolutional neural network, extracting the spectral features of cyanobacteria, and calculating the concentration distribution; image registration and a dynamic model are combined to track water bloom boundary change and drift trajectory, satellite remote sensing is used to verify precision and invert biomass density, early warning levels are divided according to the precision and the biomass density, decision information is generated, and intelligent monitoring and accurate early warning of cyanobacterial bloom are realized. The comprehensive technical effects of water bloom dynamic monitoring, accurate early warning and efficient management are achieved, and a scientific basis is provided for water environment treatment.

The invention discloses a high-valued utilization method of waste biomass, which comprises the following steps: firstly, applying current to the waste biomass containing carbon element to generate Joule heat, and generating a high-temperature environment in an extremely short time, so as to realize rapid carbonization of the biomass; then conductive carbon black or other auxiliaries do not need to be additionally added, current is applied again to generate Joule heat, a higher-temperature environment is generated within an extremely short time, and graphitization transformation of the biochar is achieved. Compared with traditional pyrolysis, hydrothermal, roasting or chemical vapor deposition methods, the flash Joule thermal method has the advantages of being easy and convenient to operate, short in consumed time, low in energy consumption, high in efficiency, high in safety, environmentally friendly and the like, and is suitable for high-value utilization of various biomass resources and green preparation of graphene materials.

The invention discloses a semi-solid-state complex no-tillage dry direct seeding method for crop seeds. The no-tillage dry direct seeding method comprises the following steps: S1, keeping a water layer of 1cm-5cm in a ditch, and paving straws obtained by harvesting preceding crops on a ditch surface; S2, applying a base fertilizer on the ditch surface paved with the straws and cleaning the ditch; S3, seeding the crop seeds on the ditch surface, and mixing the crop seeds with semi-solid-state biomass materials, a compound fertilizer and a biopesticide before seeding before seeding seeds, wherein the mixing mass ratio is that the crop seeds to the semi-solid-state biomass materials to the biopesticide is (1-10) to (70-800) to (1-3), and the moisture content of the semi-solid-state biomass materials is 40%-80%; and S4, after seeding the seeds, keeping the ditch surface at a dry state for 3-7 days. According to the semi-solid-state complex no-tillage dry direct seeding method, tillage and combustion of winter crop straws are not carried out, a whole land of field immersing water is not used for irrigation and the water immerses after the seeding, and the biological benefits are obvious; the working energy consumption is reduced, stubbles are not killed by pesticides, haze is reduced and the irrigation water is reduced.

The invention discloses a biomass gas calorific value dynamic prediction and gas distribution optimization method and system, and relates to the technical field of biomass gas, and the method comprises the steps of data preprocessing and dynamic feature extraction, calorific value dynamic prediction, optimization target setting, gas distribution optimization calculation and output and implementation control. According to the method, the change trend of the calorific value is accurately pre-judged, uncertainty is evaluated and predicted with assistance of a confidence interval, a solid and reliable data basis is provided for optimization decision, the problem of low combustion efficiency caused by fluctuation of gas source components is effectively avoided, multi-target comprehensive optimization is realized, dynamic constraint conditions are set, and an optimal optimization target set is generated; the optimal gas distribution proportion is solved, and closed-loop control is formed through real-time feedback; according to the method, the spanning of biomass gas distribution from passive response to active predictive optimization is realized, and multiple remarkable beneficial effects are brought: firstly, the stability and controllability of a gas heat value are greatly improved;

The invention discloses an organic biomass aerobic fermentation oxygen supply control method based on multi-sensor fusion and state observation, and the method comprises the steps: arranging a temperature sensor, a humidity sensor, a pressure sensor, a flow sensor and a weighing device in a fermentation device, and collecting inlet and outlet air parameters and material temperature and mass in real time; the method comprises the following steps: dynamically calculating the moisture evaporation amount based on humid air science and mass conservation, estimating the fermentation heat release amount in combination with a heat balance model, fusing multi-source data through a Kalman filter, dynamically correcting the mass of organic matters and the state quantity of the heat release amount, and realizing accurate estimation of oxygen consumption without an oxygen probe; according to the method, through a residual driving weight adjustment mechanism, measured value correction is enhanced in the fermentation temperature rising period to avoid insufficient oxygen supply, model trust is enhanced in the stationary period to inhibit excessive aeration, closed-loop aeration control is achieved, the scheme gives consideration to energy efficiency, stability and suitability, and oxygen supply accuracy and fermentation efficiency are remarkably improved.

The invention relates to the technical field of environmental science, and discloses a water and soil conservation carbon sink measuring and calculating method and system based on artificial intelligence, and the method comprises the steps: obtaining soil parameters, climate parameters, terrain parameters and environmental parameters, carrying out the adaptive uncertainty quantification processing, and constructing a standardized data set; on the basis of the standardized data set, combined with a biomass-carbon sink dynamic constraint model, forest and grass carbon sink data are generated; engineering carbon sink data are generated through the microtopography-carbon sink dynamic correction model; further generating cultivation carbon sink data through a carbon turnover-cultivation interaction stability feedback model; performing nonlinear collaborative causal reasoning on the forest and grass carbon sink data, the engineering carbon sink data and the cultivation carbon sink data, and fusing to generate total carbon sink data; and finally, performing error correction prediction on the total carbon sink data, and outputting a carbon sink prediction result. According to the method, accurate quantification of water and soil conservation carbon sequestration with multi-measure cooperation and multi-path interweaving is realized, and the measurement and calculation precision and reliability are effectively improved.

The invention discloses a nano biomass-based flexible electrode as well as a preparation method and application thereof, and belongs to the technical field of biosensors. According to the invention, biomass is used for preparing the flexible electrode, and the biomass has the advantages of being natural, renewable, biodegradable, high in yield, low in cost and the like; the sensor prepared by taking the biomass-based flexible electrode as the substrate cannot cause environmental pollution, and the biomass has good biocompatibility, so that skin discomfort cannot be caused when the sensor prepared by taking the biomass-based flexible electrode as the substrate is worn. The sensor prepared by taking the nano biomass-based flexible electrode as a substrate has high air permeability and high sensitivity, and can promote rapid evaporation of sweat, so that the problem that the continuous monitoring precision is reduced due to sweat accumulation is solved.

The invention provides a crop yield estimation method and device, electronic equipment and a storage medium, and relates to the technical field of agricultural information technology, remote sensing monitoring and artificial intelligence crossing, and the method comprises the steps: carrying out VOD space-time fusion processing based on multi-source microwave remote sensing data through a VOD space-time fusion model, and obtaining VOD fusion data; simulating crop growth based on the environment data and the crop planting data through a target crop growth model to obtain crop physiological process data; constructing multi-source feature data based on the VOD fusion data, the crop physiological process data and the environmental data; and through a double-flow space-time deep learning model, carrying out space-time feature extraction and fusion on the multi-source feature data to obtain a biomass estimated value, and further calculating a crop yield estimated value. According to the method, the crop yield is estimated based on fusion of the multi-source microwave remote sensing data, the crop growth model and the deep learning model, the restriction of a single technical normal form is broken through, and the accuracy of an estimation result can be improved.

The invention discloses an algae species with both efficient denitrification and high free ammonia tolerance and application thereof. The invention provides an inflatedfruit senna herb which is preserved in China General Microbiological Culture Collection Center (CGMCC) on December 11, 2024, and the preservation number of the inflatedfruit senna herb is CGMCC No.46280. The inflatedfruit senna herb has the advantages that the inflatedfruit senna herb is preserved in the China General Microbiological Culture Collection Center (CGMCC); the inflatedfruit senna provided by the invention has efficient assimilation removal capability on NO3 <->-N, NO2 <->-N and NH4 < + >-N, and has relatively strong tolerance on high-concentration free ammonia (FA). A bacterial-algae symbiotic system is constructed by the inflator and activated sludge, and is coupled with a dynamic membrane process, so that the denitrification efficiency of the nitrogen-containing wastewater can be remarkably improved, the addition of exogenous organic matters, the aeration energy consumption and the N2O emission are reduced, meanwhile, high-value microalgae biomass is obtained, and efficient, stable and resourceful treatment of the nitrogen-containing wastewater is realized.