308 results about "Cyanobacteria" patented technology

The invention relates to the technical field of water environment risk monitoring, in particular to a method for evaluating the algal bloom risk of a water body. The method comprises the following steps: collecting historical monitoring data of a to-be-evaluated water body, wherein the historical monitoring data comprises blue-green algae abundance data, water quality data and hydrological data; analyzing the correlation between the cyanobacteria abundance or chlorophyll a concentration and the water quality and hydrological data of the to-be-evaluated water body; hydrological and water quality parameters with the highest correlation with the cyanobacteria abundance or chlorophyll a concentration are screened out; hydrology and water quality parameters of a water body to be evaluated are taken as predictive variables, and cyanobacteria abundance or chlorophyll a concentration is taken as a response variable to construct a Bayesian network model; the weight of each parameter in the Bayesian network model is calculated, and the algal bloom risk probability that the cyanobacteria abundance exceeds a specific threshold value under the given parameter condition is calculated according to the weights. According to the invention, the scene-based probability deduction of the stable period and the dynamic period is realized through the double-branch Bayesian network model, so that the accuracy and timeliness of algal bloom risk assessment are improved.

The invention discloses a plug flow type mechanical pressurization cyanobacteria control ship, which belongs to the field of ecological environment governance, and mainly comprises a ship body, an algae collection head, a buoyancy cabin, a water collection tank, a pressurization treatment cabin and a pressurization assembly, the lever principle and the electric push rod are used for pressurizing, so that compared with a mode of directly pressurizing a water body by using an air compressor, a water pump and the like, the treatment energy consumption is low, and the pressurizing speed is higher; through the combined design of the dustpan-shaped algae collecting head, the algae inlet position, the pressurization treatment bin layering and the like, the entering and the discharging of high-algae-content water are realized by utilizing the ship advancing power and the water impeller, the operation energy consumption is greatly reduced compared with the water pump sampling, and the device can be suitable for blue-green algae prevention and control in water areas such as lakes, reservoirs, water sources, landscape water bodies and the like.

The present invention discloses a method for extracting a stable body from cyanobacteria, comprising the following steps: S1. Cultivating cyanobacteria; S2. Pretreating cyanobacteria; S3. Ultrasonic disruption; S4. Differential centrifugation; S5. Ultrafiltration; S6. Ultracentrifugation; S7. Density gradient centrifugation; S8. Removing peripheral proteins. The extraction method provided by the present invention has high extraction efficiency, stable and controllable process, no toxic by-products, is green and environmentally friendly, and does not require high temperature and high pressure equipment and large instruments and equipment, thereby expanding application scenarios and reducing application costs. The present invention can obtain high polyP n Stable, active granular biomaterials with high polymerization degree, concentration, and purity, as well as high bioactivity, can meet the stringent requirements of applications in the food and daily chemical sectors, as well as clinical medicine and scientific research. They possess significant practical application value and commercial prospects, and will address the technical challenges of preparing stable, active granular biomaterials in China.

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 belongs to the technical field of lake and reservoir water source risk prediction, and provides a lake and reservoir water source algae bloom risk early warning system based on a 16S / 18SrRNA gene expression quantity threshold, and the method comprises the following steps: S1, collecting a sample from a lake and reservoir water source surface layer water body; s2, using 7-gate water bloom algae specific primers for blue-green algae, green algae, diatom, euglena, dinoflagellate, chrysophyta and cryptoalga; s3, based on the qPCR standard curve, calculating the copy number of the 16SrRNA / 18SrRNA gene of the seven water bloom algae; s4, when the gene expression quantity of a certain algal bloom algae continuously reaches 106-7 copy number / mL for 7-12 days, determining that the algal bloom algae is in a window phase; according to the threshold value of the gene expression quantity of the water bloom algae 16SrRNA / 18SrRNA, the window period of water bloom algae cells can be accurately recognized, so that early warning of the algae bloom risk in the lake and reservoir water source is achieved, and early warning of algae bloom outbreak in the lake and reservoir water source is achieved one week or above in advance.

The utility model discloses an aeration cyclone offshore algae control system, which belongs to the technical field of offshore prevention and control of blue-green algae, and comprises an air compressor, a water tank, a heat exchanger, a cooling circulation device and a plurality of aeration cyclone mechanisms, each aeration cyclone mechanism comprises an aeration main pipe, a horizontal aeration branch pipe and a plurality of vertical aeration branch pipes, according to the utility model, active offshore algae control is realized in the time period of stronger illumination and higher air temperature, and the'gas stripping 'effect generated by the rising of bubbles is utilized, so that the Reynolds number is increased, the turbulence degree of a water body is increased, and the aeration effect of the water body is improved. Meanwhile, the normal migration rule of the blue-green algae can be destroyed due to the occurrence of the rotational flow, so that the blue-green algae cannot normally perform photosynthesis, and water layers at different temperatures can be sufficiently mixed due to the rotational flow, so that the water temperature of the surface water body is greatly reduced, and the growth of the blue-green algae is effectively controlled.

The invention discloses a blue-green algae type discrimination method based on a three-dimensional fluorescence spectrum. The method comprises the following steps: S0, obtaining a to-be-detected sample; the method comprises the following steps: S1, acquiring original three-dimensional fluorescence spectrum data; s2, preprocessing the original three-dimensional fluorescence spectrum data; rayleigh scattering and Raman scattering in the original three-dimensional fluorescence spectrum are removed, and smooth denoising is carried out on the original three-dimensional fluorescence spectrum; s3, spectral features are extracted based on a parallel factor-peak ratio method, and spectral feature vectors are obtained; and S4, carrying out missing value supplement and data standardization processing on the obtained spectral feature vectors, inputting the processed feature vectors into a trained LightGBM multi-classifier, outputting probabilities by a classification model, and selecting a category with the maximum probability. According to the method, the distribution mechanism of the blue-green algae fluorescent pigment is combined, and the fluorescent component characteristics and the relative content characteristics of the fluorescent components of the blue-green algae are comprehensively considered, so that the three-dimensional fluorescence spectrum information of the blue-green algae sample can be more comprehensively, completely and meticulously represented, and the variety discrimination of different blue-green algae with smaller difference is realized.

The invention relates to the technical field of blue-green algae cleaning, and discloses a blue-green algae cleaning boat and a cleaning method.The blue-green algae cleaning boat comprises a boat body, a bearing frame, a cleaning assembly, a dumping and collecting box and a power supply driving assembly, and the boat is composed of two suspension bodies to improve buoyancy and stability. The bearing frame is located on the inner side of the ship body and provides a bearing area for installing the cleaning assembly and other related components. The cleaning assembly is located above the bearing frame and used for cleaning and conveying algae pollutants. And the dumping and collecting box is arranged at the tail end of the cleaning assembly and is used for receiving and storing the cleaned and conveyed algae pollutants. The power supply driving assembly provides assembly working power and supports work of the cleaning assembly. The small boat firstly runs to a preset position and is accurately positioned by additionally arranging a built-in navigation system. And after the blue-green algae arrives at the target area, the cleaning assembly starts to work, and the blue-green algae is removed from the water surface through a cutting and conveying mechanism and conveyed into a dumping and collecting box. The cleaned algae are directly conveyed into the collecting box through the conveying device, and the pollutant collecting process is completed.

The invention is applicable to the field of blue-green algae detection, and particularly provides a blue-green algae detection method based on multi-task deep learning and adaptive background removal, in the detection method, a MAGAN model is constructed, local features are extracted through a graph convolutional network, global context perception is enhanced by using a self-attention mechanism, and the detection accuracy is improved. And finally, the foreground and background distinguishing is optimized through a background removing module, so that the self-adaptive background removing task is realized. Then, a multi-task deep learning framework is adopted; the targets of the multiple tasks are learned in the same model at the same time, so that the model can share knowledge from the multiple tasks; the blue-green algae detection task and the background removal task share part of features and are cooperatively optimized, background removal is achieved, support is provided for blue-green algae recognition, the blue-green algae recognition provides reference information for background removal, the cooperative effect between the tasks is enhanced, the model can more accurately distinguish blue-green algae from other water substances, and false detection and missing detection are reduced.

The invention relates to a Tarromyces sp. Strain and application thereof, the Tarromyces sp. Strain is named as Tarromyces sp. Strain F19, the preservation number is GDMCC No: 65365, and the preservation date is October 28, 2024. The Tarromyces sp. Strain is named as Tarromyces sp. Strain F19, the preservation number is GDMCC No: 65365, and the preservation date is October 28, 2024. According to the invention, a new strain of cyanobacteria with phytopathogen resisting and plant growth promoting effects is separated from rhizosphere soil of corn and is preserved, and the strain has a remarkable inhibition effect on various phytopathogens such as fusarium oxysporum, phytophthora nicotianae or Kleiella solani, and can be used as a biocontrol bacterium for preventing and treating various plant diseases; in addition, the strain can also be used for plant growth promotion. The strain resources of the biocontrol bacteria are enriched, and the method can be applied to the development of biopesticides.

The invention provides a microalgae fertilizer capable of improving salt and alkali resistance of cucumbers, and the microalgae fertilizer is a composite microalgae bio-fertilizer and comprises scenedesmus obliquus, nitzschia grain and extracellular polymeric substances generated in the culture process of the nitzschia grain. The components of the microalgae compound fertilizer disclosed by the invention are all freshwater algae strains and natural active microalgae cells, so that sodium ions and metal cations cannot be accumulated, the microalgae compound fertilizer does not contain blue-green algae, and cytotoxin which is harmful to the environment cannot be generated; the used algae strains are easier to breed, and the biomass accumulation speed of the algae strains is far higher than that of other algae strains, so that the prepared microalgae biological fertilizer has the advantages of saving time and cost. And the polyunsaturated fatty acid generated by the microalgae fertilizer can enhance the plant resistance through an osmotic regulation system and an antioxidant enzyme ROS system.

The invention discloses a rapid emergency intelligent treatment method and system for lake algal bloom outbreak, and belongs to the technical field of water environment governance, and the treatment method comprises the steps that a plurality of long-strip-shaped standard enclosure pieces are sequentially connected end to end to form an enclosure, and an algal bloom outbreak area is surrounded; geographic position information and water chlorophyll concentration information are obtained through a monitoring device in the enclosure and transmitted to a cloud processing platform, and the cloud processing platform plans a driving route according to the geographic position information and determines the dosage of a flocculating agent and a biological inhibitor according to the chlorophyll concentration; the unmanned ship loads a flocculating agent and a biological inhibitor in sequence according to the respective dosage, and enters the enclosure along the driving route to be thrown after each time of loading. Through combined application of the semi-open enclosure and an intelligent system, the whole treatment process is more efficient and convenient, the labor cost is reduced, and a more scientific, efficient and economical solution is provided for treatment of cyanobacterial bloom.

The invention discloses a preparation method and application of polydeoxyribonucleotide derived from prokaryotes. The preparation method comprises the following steps: 1) enriching blue-green algae biomass; 2) ultrasonically crushing; (3) carrying out RNA elution; 4) DNA and protein separation; (5) dissolving the DNA; (6) separating out DNA; 7) gradient cleaning of DNA; (8) dissolving the DNA; and (9) preparing PDRN. The preparation method of the water-blooming cyanobacteria PDRN is developed by taking the prokaryote cyanobacteria as the raw material, the preparation method is simple and easy to implement, the molecular weight of the PDRN can be efficiently controlled, the purity and yield of DNA are ensured by controlling the RNA elution step and the DNA and protein separation step, the antioxidant capacity of the DNA is verified, and the method is suitable for industrial production. And a new way is provided for resource utilization of the water-blooming cyanobacteria biomass.

The invention provides a blue-green algae image recognition method and system based on hierarchical self-adaption and domain driving, and the method comprises the steps: enhancing an image through employing an improved dark channel algorithm; constructing a blue-green algae biological attribute text database, and performing synonym replacement and sentence pattern recombination; multi-scale visual features are extracted through a hierarchical adaptive Swin Transform model, and key region characterization is enhanced in combination with dynamic spectrum attention; the text is input into a Bio-ALBERT model, and semantic embedding of field optimization is generated through term mask prediction and attribute relation pre-training; constructing a two-layer heterogeneous graph by using a graph attention interaction network GAIN, calculating a cross-modal association weight through a bidirectional graph attention mechanism, and outputting a cross-modal graph feature; multi-scale cross-modal association is modeled through a hierarchical graph attention fusion mechanism, and a comparison alignment loss optimization model is combined; and high-precision blue-green algae identification is realized. According to the method, through multi-scale perception, domain semantic adaptation and graph structure fusion, the accuracy of blue-green algae detection in a complex environment is improved.

This invention provides compositions and methods for providing high product yield of transgenes expressed in cyanobacteria and microalgae.

The invention discloses a phytoplankton space distribution prediction method based on environment DNA and machine learning, and belongs to the technical field of ecological environment evaluation and treatment. Comprising the following steps: determining a sampling site, and collecting a phytoplankton eDNA sample; carrying out DNA extraction and treatment on the collected eDNA sample, and calculating a species abundance matrix; screening a training data set for training a prediction model according to the sampling time and the sampling site of the eDNA sample; inputting the training data set as an independent variable of a training set, inputting the species abundance matrix as a dependent variable of the training set, and training a prediction model; and inputting remote sensing image data into the prediction model to obtain a species spatial distribution diagram. Compared with the prior art, the method has the advantages that efficient and high-species-resolution spatial distribution prediction of algae species such as blue-green algae can be achieved, the phytoplankton prediction model is trained through the machine learning model, automatic operation of spatial prediction of various phytoplanktons is achieved, the arrangement density of sampling points is reduced, and the monitoring efficiency is improved.

The invention discloses a blue-green algae identification and quantification method and device based on unmanned aerial vehicle remote sensing images and deep learning and a medium, and relates to the technical field of information data processing. Combining meteorological data and water quality monitoring data to construct an adaptive dynamic environment algorithm to extract EXIF metadata including camera parameters and attitude angle information, and establishing a geometric projection model to perform coarse orthographic correction on an original aerial image; the method comprises the following steps: extracting a multi-scale cyanobacterial bloom image feature map by stages based on a ResNet architecture and in combination with a feature pyramid network FPN fused with an attention mechanism, and obtaining an instance mask of cyanobacterial bloom through an anchor-free region proposal network, ROI Align and a head network; based on an improved GIS space projection and deep learning algorithm, carrying out high-precision area measurement and calculation on a binary mask image converted from the instance mask; according to the method, the influence of irrelevant interference on blue-green algae identification can be reduced, and the accuracy and comparability of blue-green algae identification and area calculation are improved.

The invention discloses a confocal laser microscope detection method for micro-plastic surface biofilm components and biomass, and belongs to the field of micro-plastic pollution monitoring. The method comprises the following steps: carrying out stratified sampling and polymer component identification on micro-plastic in an environmental water body; the method comprises the following steps: marking algae, blue-green algae, bacteria and extracellular polymeric substances in a biological membrane through specific fluorescent staining, carrying out high-resolution three-dimensional imaging by utilizing a confocal laser microscope, and realizing batch quantitative analysis of each component of the biological membrane by adopting ImageJ software. The technical problems that an existing detection method is insufficient in parameter dimension, evaluation result deviation is caused only based on partial component quantification, and the influence of the overall structure of the biological membrane on the micro-plastic migration behavior cannot be truly reflected are solved. According to the method, the biomass and spatial distribution of each component of the biological membrane can be comprehensively and accurately quantified, the accuracy of analyzing the vertical migration mechanism of the micro-plastic is improved, and multi-dimensional data support is provided for ecological risk assessment.

The invention discloses a desert blue-green algae large-scale culture nutrient solution and application thereof. The desert blue-green algae large-scale culture nutrient solution is prepared from urea, monopotassium phosphate, potassium chloride, sodium bicarbonate and medium trace element fertilizer. Wherein the concentrations of the urea, the monopotassium phosphate, the potassium chloride, the sodium bicarbonate and the medium trace element fertilizer are 500-550 mg / L, 20-30 mg / L, 10-15 mg / L, 10-15 mg / L and 10 mg / L respectively. The invention provides a nutrient solution special for large-scale cultivation of desert blue-green algae, and solves the technical problems of high cost, low yield and low blue-green algae purity of large-scale cultivation of desert blue-green algae in the prior art. The nutrient solution composition provided by the invention can balance each nutrient composition, so that the nutrient composition can be more suitable for the nutritional requirements of the growth of the desert blue-green algae.

The present invention is related to the fields of bioplastics. In particular, a strain of photosynthetic cyanobacteria (i.e. blue-green algae) having a high growth rate was engineered to overexpress limonene synthase. These engineered cyanobacteria improve auto-sedimentation for biomass harvest and provide for plastic bioremediation capture. Further, machine-learning methods are provided for improving some of the aspects of cultivating cyanobacteria including, but not limited to, assessing real-time light availability and predicting real-time algae growth rates to increase a cyanobacteria biomass.

A living paint comprises a living photosynthetic microorganism, binder, growth medium, and water. The microorganism may comprise algae, cyanobacteria, or lichens. The binder may be composed of primary

The invention relates to the technical field of water pollution and water body odor substance detection, in particular to a primer group, a kit and a method for detecting cyanobacteria generating 2-methylisoborneol in a water body based on a recombinase-mediated isothermal nucleic acid amplification (RAA) technology. The primer group is designed based on a mic gene conserved region of the 2-methylisoborneol-producing cyanobacteria, and comprises a forward primer, a reverse primer and a specific probe; the 5'end of the reverse primer is modified with a fluorescent marker, the 5 'end of the probe is modified with biotin, the 3' end of the probe is modified with a phosphorylation group, and nuclease cleavage sites are contained in the probe. The primer group disclosed by the invention can effectively amplify the mic gene of the 2-methylisoborneol, has relatively high specificity and sensitivity, has no cross reaction with cyanobacteria which does not generate the 2-methylisoborneol, and can be combined with lateral flow immunochromatography to be used for on-site rapid detection of the 2-methylisoborneol; the method is of great significance in early warning of excessive content of 2-methylisoborneol in the water body.

A recombinant strain of F. diplosiphon was made by transforming wild type F. diplosiphon with a pGEM-7Zf (+) plasmid containing the photolyase gene (phrA) via electroporation. The recombinant strain was designated B481-ViAnSa and overexpressed the phrA gene to result in enhanced UV tolerance compared to wild type F. diplosiphon.

The present disclosure generally relates to liquid compositions that can be used to treat a water body, for example a dam, river or waste water. In particular, the present disclosure relates to compositions that can be used to control cyanobacteria in a water body. The liquid compositions comprise worm castings, a sugar source and optional other additives / excipients. The present disclosure also relates to methods of treating a water body using the liquid compositions. The present disclosure also relates to processes for preparing the liquid compositions, and also to uses and kits comprising the liquid compositions.

To provide methods for culturing cyanobacteria.SOLUTION: A method for cultivating cyanobacteria includes: providing the cyanobacteria; subjecting the cyanobacteria to physical mutagenesis, so as to obtain primary mutant cyanobacteria; subjecting the primary mutant cyanobacteria to chemical mutagenesis, so as to obtain secondary mutant cyanobacteria; and subjecting the secondary mutant cyanobacteria to a temperature resistance test and an environment resistance test, so as to obtain target cyanobacteria, where the lethal rate of the physical mutagenesis ranges between 50% and 80%, and the lethal rate of the chemical mutagenesis ranges between 40% and 55%.SELECTED DRAWING: Figure 1

Disclosed are floating antialgal-agent-loaded sodium alginate hydrogel spheres, a preparation method therefor and use thereof. The preparation method includes preparing a solution A and a solution B; dropwise adding the solution A to the solution B to obtain hydrogel spheres; and filtering and washing to obtain the floating antialgal-agent-loaded sodium alginate hydrogel spheres. The hydrogel spheres may float on the water surface and release copper ions in a low dose for a long time, and continuously inhibit the cyanobacteria on the water surface, with little impact on the water body, which may greatly reduce the risk of water pollution caused by copper ion overdosing. Meanwhile, the hydrogel spheres may effectively reduce the application times of the antialgal agent, reduce the labor cost caused by the long-term application of antialgal agent, float on the water surface for easy recovery, and do not cause secondary pollution to the water body.

The invention relates to the technical field of water circulation treatment, and particularly discloses aquaculture cyanobacteria water circulation treatment equipment which comprises a supporting base, the top of the supporting base is fixedly connected with a purification box, one side of the purification box communicates with a water inlet of an electromagnetic valve, and a water outlet of the electromagnetic valve communicates with a water drainage pipe. Two sides of the purification box are communicated with dosing nozzles, the bottom of the purification box penetrates through and is rotatably connected with a stirring aeration device, one side of the purification box is fixedly connected with an induced draft fan, an air outlet of the induced draft fan is communicated with a first connecting pipe, and the inner wall of the sandy soil settling box is slidably connected with a filtering device. The device is provided with the filtering device, so that the sandy soil filtering rate and the filtering efficiency can be improved in a back-and-forth oscillating and shaking mode, and the device is provided with the stirring and aerating device, so that the contact area between a medicament and sewage can be increased, and the water purifying efficiency is improved.

The present application relates to the technical field of eutrophication water treatment, and discloses a preparation method and application of active substances of algicidal actinomycetes, which comprises the following steps: (1) inoculating actinomycetes into a shaking flask containing a culture medium, wherein the culture medium comprises carbohydrates, salts, glutamic acid and cyanobacteria, and then placing the shaking flask in a culture box for oscillation culture to obtain a first-stage seed liquid; (2) inoculating the first-stage seed liquid into a first-stage seed tank according to a volume fraction of 10-20% to obtain a second-stage seed liquid; (3) inoculating the second-stage seed liquid into a fermentation tank according to a volume fraction of 10-20% to obtain an actinomycete fermentation liquid; and (4) centrifuging the actinomycete fermentation liquid to obtain a supernatant and mixing the supernatant with a stabilizer. Glutamic acid can promote the actinomycetes to secrete more active substances during the fermentation process, and cyanobacteria can enable the actinomycetes to maintain the ability to remove algae during the fermentation process to secrete corresponding active substances. The stabilizer can inhibit the growth of miscellaneous bacteria to maintain the stability of algae removal.

The present invention discloses a biological fertilizer preparation device and a usage method based on the resource utilization of cyanobacteria sludge, including a device bottom plate, a pretreatment tank, a preparation box body and a biological fertilizer integrated preparation mechanism. One side of the top of the device bottom plate is provided with a pretreatment tank, the side of the pretreatment tank is provided with a preparation box body, and a biological fertilizer integrated preparation mechanism is arranged inside the pretreatment tank and the preparation box body, and the cyanobacteria sludge is automatically prepared. The preparation box body is composed of a fermentation chamber at the top and a crushing chamber at the bottom. In the present invention, the pretreatment, fermentation and crushing operations of the cyanobacteria sludge can be carried out independently and synchronously, maximizing the efficiency of preparing biological fertilizers from cyanobacteria sludge.

The invention discloses a bottom mud resuspension dimming method for water source algae control, and relates to the technical field of blue-green algae prevention and control, the method comprises the following steps: establishing an experiment system comprising a plurality of groups of independent water body simulation devices, each group of device being provided with a bivariate combination of bottom mud concentration and resuspension frequency; constructing a parameterized extinction model related to the sediment concentration and the sedimentation time based on the real-time illumination data of the vertical layered optical monitoring network; the turbidity of the water body is monitored in real time, when the turbidity exceeds a critical value, a dynamic compensation coefficient is generated, and a theoretical daily light receiving quantity threshold value is increased according to a direct proportion relation; traversing all double-variable combinations, and screening variable combinations which simultaneously meet the condition that the actual daily light receiving quantity is not greater than the theoretical threshold value subjected to turbidity correction and the product of the total bottom mud adding quantity and the mechanical energy consumption is minimized. According to the scheme, the parameter adaptability under the complex hydrological condition is remarkably improved, the theoretical optimal cost boundary is approached, and the algae control interruption risk is reduced.