7723results about How to "Increase production" patented technology

The invention relates to the technical field of data processing, in particular to a decision-making method and system for multi-source information fusion. The method comprises the following steps: obtaining hyperspectral image data, visible light image data and infrared image data collected by an unmanned aerial vehicle, and collecting ground environment monitoring data collected by a ground sensor; the hyperspectral image data, the visible light image data and the infrared image data are subjected to image preprocessing, so that a standardized multispectral data set is obtained, and image preprocessing comprises geometric correction, radiation correction and atmospheric correction; and color and texture feature extraction is carried out on the visible light image in the multispectral data set, and appearance feature and growth density identification of crops is carried out so as to obtain morphological feature data. Through integrated analysis of multi-source data, abnormal growth of crops and potential pest and disease damage risks can be identified more accurately, so that engineers are assisted to make irrigation and fertilization decisions.

The invention belongs to the technical field of image classification neural networks, and discloses a lightweight image classification neural network architecture system based on knowledge distillation. The invention provides a lightweight image classification neural network architecture system based on knowledge distillation. The lightweight image classification neural network architecture system comprises a data set preprocessing module, a teacher model preprocessing module, a subnet model construction module, a personalized training module, a real loss calculation module, a distillation loss calculation module, a total loss calculation module and a student model construction module. The invention provides a lightweight neural network architecture system based on knowledge distillation, and designs a brand new training mode by using the superiority of knowledge distillation for teacher model weight extraction: the knowledge distillation of teacher and student models is combined with a deep compression method; the system for constructing the lightweight network can be used for training various complex image classification neural networks so as to improve the network performance.

The invention discloses a method for realizing high-efficiency low-consumption micro-aerobic hydrolytic acidification of petrochemical wastewater by regulating and controlling the aeration rate in combination with a space-time diagram neural network and reinforced learning, and relates to a method for realizing high-efficiency low-consumption micro-aerobic hydrolytic acidification of petrochemical wastewater by regulating and controlling the aeration rate. The method comprises the following steps of: 1, collecting and cleaning data; 2, constructing a graph data set; 3, training the ST-GNN model; 4, constructing a deep Q reinforcement learning model; 5, the trained ST-GNN model is embedded into an automatic control system of a sewage treatment plant, and the model outputs the optimal aeration rate of the current time step and predicts the micro-aerobic hydrolytic acidification effect through interaction of the current working condition and historical data; and adjusting operation parameters of aeration equipment according to the output of the model, and carrying out hydrolytic acidification treatment. The method is high in regulation and control efficiency and low in operation error, and can be applied to the field of digital and intelligent management of sewage treatment plants.

The invention relates to the technical field of crop production, in particular to a big data-based crop yield prediction and synergistic management system, which comprises a data acquisition module, a data processing module, a multi-scale crop growth prediction module and a plant stomata dynamic adjustment and transpiration monitoring module, the data acquisition module acquires multi-dimensional agricultural data; the data processing module receives and preprocesses the collected multi-dimensional agricultural data; the multi-scale crop growth prediction module predicts growth trends of crops in different time dimensions; and the plant stomata dynamic adjustment and transpiration monitoring module analyzes and predicts the transpiration rate of the crops, and adjusts the irrigation amount in real time in combination with the prediction result of the growth trend of the crops. According to the invention, the sustainability of water resource utilization is improved, the waste of agricultural resources is reduced, and finally the benefits of agricultural production and the sustainability of the environment are improved.

The invention relates to the technical field of microorganisms, in particular to application of a cladosporium spp. Strain and a synthetic flora thereof in plant growth promotion and bacterial wilt prevention and treatment, the cladosporium spp. HX2 is a new strain, has a good symbiotic relationship with tomatoes, has a good prevention effect on tomato bacterial wilt, and has a good application prospect in plant growth promotion and bacterial wilt prevention and treatment. After the bacterial strain is mixed with congeneric strains LJ1, MS2 and LC3 to prepare a cladosporium bacterial agent, the growth-promoting and disease-resisting capabilities of the bacterial agent are enhanced, and experiments show that the synthetic flora has a good growth-promoting function on tomatoes and fresh ginger, the yield of the fresh ginger is remarkably increased, and the growth vigor of tomato plants is improved; meanwhile, the synthetic flora also has a good prevention and treatment effect on bacterial wilt of tomatoes, fresh ginger and tobaccos, and can improve the bacterial wilt resistance of plants, so that the strain HX2 and the synthetic flora prepared from the strain HX2 can be used as an anti-microbial agent or a raw material for preparing a bio-organic fertilizer in the later period.

The invention belongs to the technical field of intelligent agricultural data analysis, and relates to a crop identification and growth process prediction method and system based on multi-modal data. The method comprises the following steps: collecting growth process images and multi-modal environment data of crops in each growth stage; constructing a crop feature data set; constructing a sample data set; training to obtain a crop type identification model; obtaining a crop type identification result; generating a fusion feature vector; performing data enhancement processing; constructing a long-short-term memory network for training to obtain a growth stage prediction model; and predicting the growth stage of the crops. Crop type identification is performed by constructing a deep neural network model, feature fusion is performed on crop growth process image features and multi-modal environment data, crop growth stage prediction is performed by using a long-short-term memory network, fertilization, irrigation and pest control measures are optimized in combination with the multi-modal environment data, and the crop growth stage prediction accuracy is improved. The crop yield and quality are improved.

The invention belongs to the technical field of gene engineering and enzyme engineering, and particularly relates to an ornithine decarboxylase mutant as well as a coding gene, an expression vector, a recombinant strain and application thereof. The ornithine decarboxylase mutant is obtained by mutating wild ornithine decarboxylase ODC10 of which the amino acid sequence is shown as SEQ ID NO.1, the catalytic activity of the obtained mutant is improved, and the biosynthesis efficiency of 1, 4-butanediamine is favorably improved. The recombinant strain for expressing the ornithine decarboxylase mutant constructed by the invention can efficiently synthesize 1, 4-butanediamine, and the molar conversion rate of ornithine is remarkably improved, so that the production benefit is improved, and the production cost is reduced.

The invention relates to a recombinant escherichia coli THRS and a method for synthesizing L-threonine by using the recombinant escherichia coli THRS. The invention belongs to the technical field of bioengineering, and provides a recombinant escherichia coli THRS which overexpresses encoding genes of ppc, aspC, aspA, thrAmutBC, asd, rhtC, rhtA, asdtm and thrAmut, knockout an encoding gene of fnr and knockout an encoding gene of iclR, the recombinant escherichia coli THRS takes glucose as a substrate for fermentation, and the yield and conversion rate of L-threonine are obviously improved; the L-threonine strain has the advantages that the L-threonine strain does not contain exogenous plasmids, all modification sites are integrated onto a genome, higher stability is achieved, antibiotics do not need to be added into a fermentation culture medium of the strain, and the produced L-threonine product is free of antibiotic residues and higher in safety.

The invention discloses immobilized bacteria-algae microspheres, a preparation method thereof and application of the immobilized bacteria-algae microspheres in removal of ammonia nitrogen and total phosphorus in aquaculture water. The preparation method comprises the following steps: adding polyvinyl alcohol and sodium alginate into deionized water, heating and sterilizing while fully dissolving polyvinyl alcohol and sodium alginate to obtain an embedding medium; adding the iron modified biochar powder into a mixed solution of chlorella and photosynthetic bacteria for adsorption to obtain a bacteria-algae-biochar mixture; adding the bacteria-algae-biochar mixture into an embedding medium to form a gel solution; adding the gel solution into a cross-linking agent for cross-linking, and after cross-linking, separating a solid and cleaning to obtain immobilized bacteria-algae microspheres; the preparation method of the iron-modified biochar powder comprises the following steps: adjusting the pH value of a mixed solution containing biochar powder, Fe < 2 + > and Fe < 3 + > to 9.5-10.5, carrying out heat preservation stirring at 75-85 DEG C for 1-5 hours, carrying out solid-liquid separation, taking a solid, washing, and drying to obtain the iron-modified biochar powder.

The invention relates to the field of intelligent irrigation, in particular to an intelligent irrigation method and device based on the Internet of Things, and the method comprises the steps: constructing a soil standard model, obtaining soil data in real time, inputting the soil data into the soil standard model, and outputting a region division result through the soil standard model; based on a regional division result, judging whether the soil data meets an irrigation condition or not; when the soil data meets the irrigation condition, acquiring meteorological data, water pressure data and historical irrigation data; according to the meteorological data, the water pressure data and the historical irrigation data, irrigation parameters needed by the corresponding area of the soil are predicted; and determining corresponding irrigation behaviors in combination with the soil data and the irrigation parameters of the corresponding areas. Soil data is monitored in real time, so that the system can dynamically adjust an irrigation plan, invalid irrigation after rainfall is avoided, a targeted irrigation strategy is made according to the soil humidity level and topographic features, slope water and soil loss is prevented, and it is ensured that the flat ground is prevented from being too wet to cause root system oxygen deficit.

The invention relates to the technical field of agriculture, in particular to a corn stress resistance environment monitoring and management method, which comprises the following steps of S1, collecting environment data of a corn planting area in real time; s2, transmitting the environment data to a data center through a wireless network; s3, preprocessing the environment data transmitted to the data center; s4, establishing an adversity stress assessment model based on the preprocessed environmental data; s5, evaluating the stress resistance of the corn under different environmental stresses; s6, predicting the type and strength of adversity stress which will occur in the future and the influence of the adversity stress on the corn, and forming stress response prediction; and S7, generating a corn growth management decision suggestion. According to the invention, through real-time environment monitoring and accurate adversity stress assessment, in combination with growth characteristics and weather prediction of corn, irrigation, fertilization and pest control strategies are dynamically adjusted, so that accurate management of corn growth is realized, stress resistance is improved, resource utilization is optimized, and yield is increased.

The invention discloses an intelligent sensing algorithm and system for crop growth vigor, computer equipment and a medium, and the algorithm comprises the following steps: 1, carrying out the image collection of a farmland, and collecting the spectral data of different wavebands in the farmland; 2, preprocessing the collected images and spectral data, and extracting multi-dimensional feature information of the crops; 3, fusing the extracted multi-dimensional feature information of the crops to obtain comprehensive and accurate crop growth feature information; 4, performing data analysis on the crop growth feature information through deep learning, and constructing an intelligent decision model; through the implementation of the invention, the characteristics and beneficial effects of multi-information fusion, high-precision perception, cost reduction, quality improvement, wide application and the like are realized through the crop growth vigor intelligent perception algorithm, and the method plays an important role in improvement of agricultural production and agricultural product quality.

The invention relates to the technical field of intelligent agriculture, in particular to a mulberry field monitoring method and system based on the Internet of Things. The method comprises the following steps: acquiring environment and soil data of a mulberry field through a sensor network to obtain original sensor data; performing time sequence data integration on the original sensor data to obtain an environment parameter data set; the method comprises the following steps: performing multispectral image acquisition on mulberries in a mulberry field through a multispectral camera, and performing image preprocessing to obtain preprocessed image data; estimating the chlorophyll content according to the preprocessed image data to obtain chlorophyll content data; and performing growth health parameter analysis according to the preprocessed image data and the chlorophyll content data to obtain growth health parameters. By combining the sensor technology, the multispectral imaging technology and the intelligent algorithm, comprehensive, accurate and real-time monitoring of the mulberry field is achieved, and an effective technical means is provided for fine management of the mulberry field.

The invention discloses a crop disease remote sensing monitoring and early warning system based on time sequence spectral information analysis, and relates to the technical field of agricultural disease and insect pest monitoring. Computer drawing software is utilized to divide a corn planting field in equal proportion, and sensors are deployed to monitor the growth environment change in each grid in real time and generate microenvironment data information; the method comprises the following steps: calculating a microenvironment difference index Xbd according to microenvironment data, identifying a microenvironment difference aggregation area and sending a risk analysis instruction, after receiving the risk analysis instruction, capturing related spectral data information of the microenvironment difference aggregation area by using an unmanned aerial vehicle and a multispectral sensor, and constructing a multispectral fluctuation coefficient Xgp by analyzing related spectral data, and comparing the calculated rust disease risk assessment index Zpg with a preset threshold W in combination with the microenvironment difference index Xbd and the trained risk assessment model, and obtaining corresponding grade early warning according to the rust disease risk degree.

The invention relates to the technical field of crop cultivation, in particular to a water and fertilizer regulation and control method and system for saline-alkali soil grain-feed crops, and the method comprises the following steps: S1, soil preliminary improvement and crop selection: performing preliminary improvement on saline-alkali soil; s2, dynamically predicting, regulating and controlling the soil conductivity: monitoring and dynamically predicting the change trend of the soil conductivity in real time; s3, formulating a water and fertilizer management strategy: formulating the water and fertilizer management strategy; s4, dynamic optimization of saline-alkali soil moisture evaporation: acquiring environmental data in real time, and performing dynamic optimization management on the moisture evaporation process of the saline-alkali soil; s5, crop root health monitoring and feedback regulation and control: identifying salt damage or water and fertilizer absorption obstacles, and adjusting a water and fertilizer management strategy in real time; s6, final-period management and soil ecological restoration, wherein ecological restoration is conducted on the saline-alkali soil. According to the invention, salt damage or water and fertilizer absorption obstacles are identified and solved in time, and healthy growth of crops is further ensured.

The invention discloses a glycosyl transferase mutant for synthesizing rebaudioside M and a synthesis method of rebaudioside M, and belongs to the technical field of gene engineering. The glycosyl transferase mutant for synthesizing the rebaudioside M is a glycosyl transferase UGT76G4 mutant and / or a glycosyl transferase UGT91C1 mutant, and the glycosyl transferase mutant is a glycosyl transferase UGT76G4 mutant. The glycosyl transferase UGT76G4 mutant is obtained by mutation of an amino acid sequence as shown in SEQ ID NO: 1: 85th amino acid is mutated into R from L, and 90th amino acid is mutated into G from I; the glycosyltransferase UGT91C1 mutant is obtained by mutating an amino acid sequence shown in SEQ ID NO: 3 as follows: the 204th amino acid is mutated into A from L, the 208th amino acid is mutated into A from F, and the 380th amino acid is mutated into D from G. The mutant can realize efficient catalytic synthesis of rebaudioside M, and the yield of rebaudioside M synthesized by an enzymic method is improved.

The invention relates to a high-activity recombinant XVII type collagen as well as a rapid preparation method and application thereof, and belongs to the technical field of bioengineering. The amino acid sequence of the high-activity recombinant XVII type collagen is as shown in SEQ ID NO. 1, and the nucleotide sequence of the high-activity recombinant XVII type collagen is as shown in SEQ ID NO. 2. The invention also provides a preparation method and application of the recombinant XVII type collagen. The high-activity recombinant XVII type collagen has good biological activity, has good effects of promoting cell adhesion, cell proliferation and cell migration, and can be compounded with other proteins to form raw materials of tissue engineering products, cosmetics, health care products or medicines. The high-activity recombinant XVII type collagen gene is integrated to different positions of a yeast genome through three different vectors, and the copy number of a target gene is increased, so that the expression quantity of the recombinant XVII type collagen is remarkably increased, and the yield of the high-activity recombinant XVII type collagen is effectively increased.

The invention belongs to the technical field of biochemical engineering and the technical field of bioengineering, and discloses a schizochytrium limacinum engineering strain for producing EPA (eicosapentaenoic acid) by prolonging a desaturation path. Part or all of the extended desaturase genes from thraustochytrium sp. And fusarium sp. And saprolegnia are expressed. According to the invention, extended desaturase genes from various sources are integrated into a schizochytrium limacinum genome, so that a schizochytrium limacinum gene engineering strain efficiently expresses the extended desaturase genes, and a heterologous EPA synthesis path with high synthesis efficiency, short culture period, simple purification method and low cost is provided; a basis is provided for producing grease rich in EPA from schizochytrium limacinum, and the problems of non-sustainability, high cost and the like caused by obtaining EPA from fishes are solved.

The invention discloses a bacillus subtilis microbial agent for promoting decay of corn straws and application of the bacillus subtilis microbial agent, the preservation date of bacillus subtilis K15 is May 21, 2024, the preservation unit is China General Microbiological Culture Collection Center (CGMCC), and the preservation number is CGMCC No.30716. The bacillus subtilis K15 has the advantages that the preservation number is CGMCC No.30716; the bacillus subtilis K15 is screened from soil in North China Plain, tests prove that the strain produces carboxymethyl cellulase, decomposition of corn straw can be effectively promoted, the decomposed straw provides a fertilizer source for wheat growth, growth of wheat plants and root systems is promoted, and the wheat yield is effectively increased. According to the invention, the function of the bacillus subtilis in straw decay promotion under the winter low-temperature condition in North China Plain is excavated, and a new strain resource is provided for a microbial fertilizer.

The invention belongs to the technical field of optimized coding genes, and discloses a recombinant human I-type collagen as well as a preparation method and application thereof, and the amino acid sequence of the recombinant human I-type collagen is shown as SEQ ID No.1. The recombinant I-type collagen provided by the invention is relatively high in expression quantity, has relatively good cell migration promoting, cell proliferation promoting and cell adhesion promoting properties, is high in safety, and can be widely applied to the fields of medicines, medical instruments, biological materials, tissue engineering, cosmetics and the like.

The invention discloses a crop canopy height estimation method based on laser radar and multispectral fusion, and the method comprises the steps: scanning a crop field through the laser radar, and obtaining the field point cloud data; aerial photography is carried out on a crop field through an airborne multispectral camera to obtain field multispectral image data, and after data image splicing, crop region extraction and land parcel segmentation, two point cloud feature parameters with the strongest correlation with crops are extracted from point cloud data to obtain a point cloud feature parameter; the method comprises the following steps of: extracting a vegetation index with the strongest correlation with the crop height from multispectral image data, solving through multiple linear regression, and establishing a height estimation model; according to the invention, the multispectral vegetation index and the laser radar data are combined, so that the crop canopy height monitoring precision is improved, the crop growth monitoring precision and reliability can be improved, the crop growth condition can be comprehensively understood, and an agricultural decision maker can determine the crop canopy height based on the crop canopy structure data. And a more accurate, timely and effective farmland management decision can be made.

According to the coastal saline-alkali land underground water level adjusting system based on real-time monitoring and intelligent regulation and control, the system integrates the soil salinity sensor, the underground water level sensor and the central processing unit, future trend prediction is carried out by monitoring key parameters such as soil salinity and underground water level in real time in combination with a deep learning model, and the real-time monitoring and intelligent regulation and control are achieved. And precise intelligent regulation and control are realized. The system can effectively reduce soil salinization, prevent seawater from flowing backwards, improve the utilization efficiency of water resources and reduce the labor management cost at the same time. The method is characterized in that the application of multi-parameter comprehensive monitoring, a deep learning prediction model and a self-adaptive intelligent regulation and control algorithm provides a new technical solution for coastal saline-alkali land treatment.

The invention provides double-arm picking equipment for shelf-type planted shiitake mushrooms and an operation method thereof. The double-arm picking equipment comprises a moving platform, the upper portion of the moving platform is connected with a chassis, and a lifting device, a shiitake mushroom storage device and a shiitake mushroom picking device are arranged above the chassis. Through mechanical automatic mushroom stick fixing and mushroom picking, intelligent identification, picking and placing of mushroom sticks on a shelf and identification and picking of mushrooms on the mushroom sticks can be carried out at the same time, planting areas can be traversed automatically, the mushroom picking speed is increased, and labor and time cost is saved. Three-dimensional scanning is carried out through the depth camera vision system, the position and size of the mushroom sticks and the maturity of mushrooms can be accurately recognized, and it is ensured that the quality of picked mushrooms is high. The lifting device adjusts the height of the mechanical arm and cooperates with a visual system, picking and mushroom stick processing are more accurate, damage to mushrooms and mushroom sticks is reduced, mushroom picking automation is achieved, operators do not need to put physical labor heavily, and the workload is relieved.

The invention discloses a thin mutual coal seam fracturing, gasification and carbon sequestration integrated method. The method comprises the steps of geological exploration and coal seam refined evaluation; a middle horizontal well is drilled downwards from the ground; top and bottom horizontal wells are planned and drilled in the uppermost and lower sandstone stratums of the thin mutual coal seam; a plurality of top and bottom fishbone wells are drilled obliquely downwards and upwards in the top and bottom horizontal wells; oxygen-enriched water vapor is injected into the middle horizontal well through a continuous oil pipe, the oxygen-enriched water vapor is squeezed into the reservoir under the action of high pressure, and fracturing operation is conducted; initiating an underground gasification process of the coal seam, and synchronously performing extraction operation of the coal seam gas; supercritical CO2 fracturing operation is conducted on the top horizontal well and the bottom horizontal well; injecting water-based fracturing fluid into the top horizontal well and the bottom horizontal well; gasified materials generated by coal seam combustion gasification and desorbed methane gas are extracted through the middle horizontal well, and supercritical carbon dioxide injected before is sealed for a long time. According to the method, the limitation of a traditional hydraulic fracturing technology can be solved, and the transformation effect of the reservoir can be improved.

The invention discloses a hilly slope irrigation control system based on artificial intelligence, and the system comprises a wind speed and wind direction detection module which is used for obtaining wind speed and wind direction data; the sprinkler head adjusting module is used for adjusting the angle and the spraying distance of a sprinkler head based on the wind speed and wind direction data; the soil humidity detection module is used for being connected with a soil humidity sensor and determining irrigation requirements according to data of the soil humidity sensor; the artificial intelligence control module is used for optimizing the irrigation time and the irrigation amount through an artificial intelligence algorithm; the sprinkling irrigation system control module is used for controlling the sprinkling irrigation system to irrigate according to the optimization result; the hilly slope irrigation control system based on artificial intelligence reduces the phenomenon of non-uniform growth of crops, facilitates healthy and uniform growth of the crops, and ensures that the crops can obtain a proper amount of water supply, so that normal growth and development of the crops are promoted, the yield and quality of the crops are improved, and the agricultural production benefits are further improved.

The invention discloses a drip irrigation wheat water nitrogen intelligent monitoring system based on unmanned aerial vehicle multispectral inversion, and the system employs a multispectral sensor carried by an unmanned aerial vehicle to monitor the moisture and nitrogen content of wheat in real time, and employs a dynamic spectrum selection module to automatically select an optimal spectral band for data collection. Therefore, the most accurate crop state information can be obtained. The spectrum frequency conversion module and the adaptive spectrum amplitude modulation module in the system adjust the frequency and amplitude of spectrum data in real time, and further optimize the data quality and accuracy. Based on the high-quality data, a data analysis and decision support module generates an accurate intelligent irrigation and fertilization strategy, and water and nitrogen supply is automatically adjusted to meet the actual requirements of wheat in different growth stages, so that the growth conditions of crops are optimized, the growth quality and yield of wheat are remarkably improved, and the economic benefit is increased. Agricultural production is promoted to develop towards a more intelligent and precise direction, resource waste is reduced, and economic benefits are improved.

The invention belongs to the technical field of intelligent agricultural planting, and particularly relates to an agricultural planting decision-making method and system based on a large language model.The technological process of the method includes the steps that firstly, historical field data and field data are preprocessed, and then processing such as feature extraction, clustering and sensor data fusion is conducted; and finally, predicting according to the agricultural data set and sending to the user. The concrete structure of the system comprises a data processing module, an intelligent agent module and an agricultural interaction model module. The system can be widely applied to precision agriculture, and helps farmers to implement precise management strategies such as precise fertilization, irrigation and pest control according to specific environment and crop requirements, so that the yield and quality of crops are improved. According to intelligent greenhouse management, environment parameters such as temperature, humidity and illumination are monitored in real time through an environment sensor, and after data are processed, an intelligent agent can provide an optimized management strategy to adjust conditions in the greenhouse, so that an optimal environment is created for growth of plants.

The invention discloses a tea garden soil improvement method based on microbial communities. The tea garden soil improvement method aims at improving soil fertility and tea tree yield by means of precisely screening beneficial microorganisms, optimizing culture conditions and the like. Firstly, soil samples are collected from a tea garden area, gene high-throughput sequencing is carried out, soil microbial community composition information is obtained, and beneficial microorganisms are screened out. Then, the breeding speed and biomass of the beneficial microorganisms are optimized by adjusting a culture medium formula. When the bio-fertilizer is prepared, besides concentrated bacterial liquid, an organic carrier, inorganic nutrient elements and humic acid serving as a stabilizer are also added, and a proper amount of trace elements and a plant growth regulator are added. In spring or autumn, according to the physicochemical property of the soil, the bio-fertilizer is uniformly spread and ploughed into the soil layer. After fertilization, soil physicochemical properties and tea tree growth conditions are regularly detected to evaluate the soil improvement effect and adjust the fertilization strategy according to the soil improvement effect. The method is beneficial for improving the tea garden soil health condition and improving the tea yield and quality.

The invention relates to an engineering bacterium of high-yield ornamental blue as well as a construction method and application of the engineering bacterium, and belongs to the technical field of natural dye synthesis by a biological method. The engineering bacterium capable of highly producing the ornamental blue, disclosed by the invention, expresses icd, bpsA, glnAY405F and gd hA; acnR, yggB, glsK, aceA and ldh are knocked out from the engineering bacteria. According to the application, yggB and aceA genes are knocked out, site-directed mutagenesis (Y405F) is carried out on a glnA gene, a glsK gene is replaced by a glnAY405F gene, an acnR gene is replaced by an icd gene, an ldh gene is replaced by a gdhA gene, and a bpsA gene is integrated, so that the formation of by-products such as lactate and succinic acid in a blue-viewing synthesis process can be blocked; the flow direction of a passage from citric acid to isocitric acid to alpha-ketoglutaric acid to glutamic acid to glutamine is improved, so that the concentration of glutamine in cells is improved, and the yield of the ornamental blue is improved.

The present invention relates to a single-sided double-knife roller automatic quick-change online glass fiber high-speed short-cutting machine, comprising a machine body and a short-cutting mechanism, an automatic switching mechanism, a loading mechanism, an online grinding mechanism, a hoisting frame, a leveling mechanism, a sampling material box, a lighting and ventilation unit, a dust removal unit, a safety locking unit, a wire pulling mechanism and a wire pushing mechanism installed on the machine body. The automatic switching mechanism is rotatably installed on the machine body, the short-cutting mechanism is installed on the automatic switching mechanism, and the bottom of the machine body is installed with a leveling mechanism. The advantages of the present invention are: improving the output of glass fiber short-cut finished products and the stability of product quality, reducing the discharge of waste glass fibers, and reducing the pollution of glass fiber short-cut production to the environment.