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583 results about "Food sample" patented technology
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Campus smart canteen management platform based on AI and IOT
InactiveCN119624483Apromote healthy growthImprove satisfactionDatabase distribution/replicationCommerceIntelligent decision support systemPesticide residue
The invention discloses a campus smart canteen management platform based on AI and IOT. The campus intelligent canteen management platform comprises a global sensing system, an intelligent decision support system, a credible tracing system, a safety and supervision system and a user experience optimization system. The global sensing system is used for collecting multi-modal data and carrying out data fusion and preprocessing on the multi-modal data; the intelligent decision support system is used for performing multifunctional analysis on the fused and preprocessed multi-modal data to obtain a management decision; the credible traceability system is used for recording digital traceability information, storing reserved food samples and detecting pesticide residues in real time; the safety and supervision system is used for providing food reserved sample management, food quality event monitoring and analysis, supervision record management and parent applet functions; and the user experience optimization system is used for providing health inspection, health monitoring and personalized suggestions, identity verification and payment modes. In this way, the overall level of canteen management is improved.
Owner:SHENZHEN BEIZE INTELLIGENT CONTROL TECH CO LTD
Food quality component analysis method and system based on near infrared spectrum technology
The invention relates to the technical field of food component analysis, in particular to a food quality component analysis method and system based on a near infrared spectrum technology, and the method comprises the following steps: obtaining a food sample set, and obtaining original near infrared spectrum data based on the food sample set, combining the original near infrared spectrum data to form an original infrared spectrum matrix; preprocessing the original infrared spectrum matrix to generate a processed spectrum matrix; and extracting the characteristic wavelength of the near infrared spectrum information based on the processed spectrum matrix, constructing a food quality quantitative analysis model according to the characteristic wavelength in combination with a partial least squares regression algorithm, and outputting a component content predicted value according to the food quality quantitative analysis model. And generating a quality component analysis report of the to-be-detected food based on the component content predicted value. The method has the advantages that food quality and ingredients can be quickly, nondestructively and accurately detected, and detection precision and accuracy are improved.
Owner:SHANTOU CITY HAPPYFOOD FOOD CO LTD
Food safety risk analysis method and system based on big data
The invention relates to a food safety risk analysis method and system based on big data. The method comprises the steps of collecting food full-life-cycle key data through Internet of Things equipment and a data platform, and completing data format standardization to form a structured data set; key risk factors are extracted through the structured data set, a risk factor weight matrix is constructed, and a primary risk value of the food sample is calculated; establishing a time sequence prediction model by using the primary risk value and historical time sequence data, calculating a risk change trend, and predicting a future risk fluctuation condition; calculating a food risk grade according to the primary risk value and the risk change trend, and generating a corresponding risk classification label; performing comparative analysis on the risk classification label and an actual supervision result, calculating a model deviation, and optimizing a risk calculation and trend prediction model based on a deviation result; the optimized analysis results are integrated, the risk level and the change trend are displayed through a graphical interface, and intelligent early warning prompts and intervention decision suggestions are provided.
Owner:BEIJING YELLOW ELEPHANT FOOD TECH CO LTD
Food heavy metal pollution detection system based on plasma emission spectrum analysis
The invention provides a food heavy metal pollution detection system based on plasma emission spectrum analysis, and aims to realize rapid and accurate detection of heavy metal elements in a food sample. The system comprises a sample processing module, an excitation module, a spectrum detection module, a signal processing module, a data analysis module and an output module. The sample processing module converts a food sample into an aerosol or steam state. The spectrum detection module is used for extracting spectrum characteristic information of heavy metal elements. And the signal processing module adopts an AI-driven spectrum denoising algorithm to remove background noise and interference signals. And the data analysis module calculates the concentration of each element based on the characteristic peak intensity and generates heavy metal pollution data. And the output module is used for visually displaying the detection result. According to the method, complex sample pretreatment steps are reduced, the detection efficiency and sensitivity are improved, and the method is suitable for food safety detection scenes and particularly has remarkable advantages in field rapid detection application of agricultural products, drinking water and processed food.
Owner:JIANGSU SUPERVISION & INSPECTION INST FOR PROD QUALITY
Improved food sensory quality evaluation method and system based on fuzzy mathematical method
The invention discloses an improved food sensory quality evaluation method and system based on a fuzzy mathematical method, and relates to the technical field of food inspection and detection. Performing a single-factor test on the improved food sample, and performing a response surface test on the basis of the single-factor test; performing comprehensive sensory evaluation on each sample in the response surface test by adopting a fuzzy mathematical analysis method; and physical and chemical indexes of the improved food under the optimal process are determined. According to the invention, the technology of the improved food is optimized, and the physicochemical indexes of the improved food with the optimized response surface are measured; a single-factor test and a response surface test are carried out in sequence, sensory scores are taken as evaluation standards, and factors influencing the quality of the improved food are determined; the optimal formula of the improved food is finally determined through a verification experiment; a fuzzy mathematics comprehensive sensory evaluation model is established for the improved food, and the obtained sensory evaluation result is used for response surface optimization evaluation.
Owner:ZHAOQING UNIV +1
Food safety traceability detection method and system based on machine learning
InactiveCN119494667Aavoid enteringimprove accuracyCommerceSpecial data processing applicationsFood safetyFeature data
The invention discloses a food safety traceability detection method and system based on machine learning, and relates to the technical field of food safety supervision, the food safety traceability detection method based on machine learning comprises the following steps: obtaining corresponding detection feature data; obtaining a food safety risk detection index; constructing a food safety risk prediction model; performing safety detection on the food sample; and starting a traceability program according to a safety detection result, and taking corresponding measures. According to the method, key factors influencing food safety can be accurately identified by analyzing the detection characteristic data, so that whether a food sample meets food safety standards or not can be accurately judged by continuously testing and comparing key safety parameters while the detection quality is ensured, and the detection accuracy is improved. Therefore, unsafe food is effectively prevented from entering the market, and the health of consumers is protected.
Owner:JIANGSU HOT FOODTECH CO LTD
Food reserved sample quality monitoring method based on machine learning
The invention relates to a food reserved sample quality monitoring method based on machine learning, and the method specifically comprises the following steps: deploying a sensor array in a food reserved sample environment, collecting reserved sample multi-dimensional physicochemical characteristic data in real time, constructing a training set through historical normal and degraded batch data, and marking a state; the method comprises the following steps: constructing a machine learning model for food reserved sample quality monitoring, inputting sample data in a training set into the model, sequentially passing through a dynamic distribution alignment module, a physical constraint confrontation enhancement module and a multi-scale residual space-time network, and performing dynamic attention mechanism enhancement by utilizing physical constraint and environment modulation. And finally, outputting a quality category probability by the multi-modal classifier. Then calculating model loss, and carrying out iterative training on the model to obtain a trained model; and deploying the trained model at a reserved sample monitoring terminal, inputting newly collected monitoring data, and predicting the quality state of the food reserved sample. According to the invention, high-efficiency and real-time quality monitoring on the quality of the reserved food sample can be realized.
Owner:SHANDONG INST FOR FOOD & DRUG CONTROL
Food pollution detection method and system based on multi-wavelength spectrophotometry
The invention provides a food pollution detection method based on multi-wavelength spectrophotometry, and the method comprises the steps: transmitting light in a series of wavelength ranges to a food sample through a tunable multi-wavelength light source system, generating spectral response, collecting the spectral response through a high-resolution spectrometer, and forming a multi-dimensional spectral image, a deep learning algorithm is used for analyzing, identifying and distinguishing subtle spectral differences between natural components and potential pollutants in a food sample, a preliminary identification result is obtained, a self-adaptive wavelength selection mechanism is implemented, wavelength output of a light source is dynamically adjusted, spectral response data is obtained, and the spectral response data is compared with a preset food safety standard database. According to the technical scheme provided by the invention, natural components and potential pollutants in a food sample are efficiently and accurately recognized, and the sensitivity, specificity and accuracy of pollutant detection are remarkably improved.
Owner:CSSC HAISHEN MEDICAL TECH CO LTD
Food pesticide residue safety detection and analysis method based on machine learning
ActiveCN119580877AImprove detection accuracyImprove detection reliabilityMolecular entity identificationComponent separationPesticide residueBiology
The invention relates to the technical field of food detection, and discloses a food pesticide residue safety detection analysis method based on machine learning, which comprises the steps of food sample collection, extract pretreatment, two-dimensional liquid chromatography-high resolution mass spectrometry combined technology analysis, mass spectrum acquisition, mass spectrum numerical data conversion, data correction and machine learning model establishment. The method comprises the following steps: identifying and classifying pesticide residue components, extracting a pretreatment extract, analyzing a to-be-detected sample, acquiring a mass spectrum, converting the mass spectrum into to-be-detected mass spectrum numerical data, correcting the data, inputting a model, identifying and classifying pesticide residues, quantitatively analyzing, comparing food safety standards, judging conformity and generating a detection report. The invention aims to improve the accuracy, sensitivity and efficiency of pesticide residue detection. Meanwhile, through technical correction and optimization, the problems of environmental interference, data deviation and the like faced by an existing method are effectively solved.
Owner:HEZE INST OF FOOD & DRUG INSPECTION & TESTING
Food sampling inspection decision-making method based on graph attention network and Crack-Topsis
The invention relates to a food sampling inspection decision-making method based on a graph attention network and Crack-Topsis, and belongs to the technical field of food safety. Firstly, data are preprocessed; then, constructing a graph attention network model, inputting the preprocessed data into a GAT model for training, and predicting the number of sampling inspection times of each node by extracting node features and calculating association weights among the nodes; and finally, decision-making is carried out on the sampling inspection sequence of different hazardous substances by adopting a Crimic-Topsis method, the sampling inspection sequence of the hazardous substances is determined according to the closeness degree of the hazardous substances, and the sampling inspection efficiency and effect are improved. Through the method, a more scientific and reasonable food sampling inspection plan can be realized, the food safety is guaranteed, the decision-making efficiency of a supervision department is improved, and the waste of sampling inspection resources is reduced.
Owner:BEIJING TECH & BUSINESS UNIV
D-A type organic fluorescent small molecule, preparation method and application of D-A type organic fluorescent small molecule in detection of nitrofuran antibiotics
ActiveCN119912403AOrganic chemistryFluorescence/phosphorescenceRapid identificationFluorescent quenching
The invention provides a D-A type organic fluorescent small molecule, a preparation method and application of the D-A type organic fluorescent small molecule in detection of nitrofuran antibiotics, and belongs to the technical field of fluorescent sensing. The D-A type organic fluorescent micromolecule is composed of 2-(2-aminophenyl) benzothiazole and an electron-donating group, the excitation spectrum of the D-A type organic fluorescent micromolecule is obviously overlapped with the absorption spectrum of nitrofuran antibiotics, and fluorescence quenching response can be shown through the inner filter effect; the trace nitrofuran antibiotics can be detected in a liquid phase in an ultrafast, high-sensitivity, excellent-selectivity and strong-anti-interference manner. According to the invention, a quantitative evaluation system can be constructed in combination with a smart phone, the RGB value of the image of the liquid-phase fluorescence sensor is output in real time, and rapid, accurate and visual quantitative detection of nitrofuran antibiotics in a real food sample or a water source is realized. In addition, the filter paper fluorescence sensor has the advantages of being portable and easy to prepare, and nitrofuran antibiotics can be rapidly identified on site in an actual scene.
Owner:JILIN UNIVERSITY
Food component analysis method and system based on near infrared spectrum
The invention provides a food component analysis method and system based on a near infrared spectrum. The method comprises the following steps: acquiring a near infrared spectrum signal through a food sample, and generating a sample near infrared spectrum signal by adopting an intelligent sampling method; based on the near infrared spectrum signal of the sample, automatically focusing a key area by using an attention mechanism enhanced convolutional neural network, and combining a spectrum characteristic selection technology to screen spectrum characteristics, and generating sample component and content information; based on the sample component and content information, evaluating the human body metabolism influence degree by applying a gradient boosting decision tree algorithm, analyzing a biological mechanism by combining a bioinformatics analysis technology, and generating a sample influence evaluation report; and based on the sample influence evaluation report, adopting natural language processing to generate a food component analysis report. According to the technical scheme provided by the invention, high-precision and automatic food component analysis is realized, the analysis accuracy and efficiency are improved, and an influence mechanism of food components on human metabolism is deeply analyzed.
Owner:CSSC HAISHEN MEDICAL TECH CO LTD
Food safety risk prediction method and device based on heterogeneous graph neural network
The invention discloses a food safety risk prediction method and device based on a heterogeneous graph neural network, and the method comprises the steps: evaluating the food safety risk: firstly, training a classification model to distinguish the qualified state and the unqualified state of a food sample; then, explaining the model by using an SHAP value, and calculating influence weights of various dopants on food qualification; finally, through weight integration, calculating an overall risk value for each sample, and taking the overall risk value as a prediction label; food safety map representation learning: capturing a complex relationship in a food sample, and identifying a potential risk mode: constructing a heterogeneous food safety map, and representing various entities and mutual relationships thereof; processing graph data by using a heterogeneous graph neural network HGNN fusing a meta-path context, and generating an embedded vector of a food sample node; and risk prediction: classifying the food samples by using the prediction labels and the embedded vectors of the food sample nodes, and dynamically evaluating the food safety risk. According to the method, the dopant feature contribution weight can be accurately calculated, and more accurate data support is provided for risk prediction.
Owner:ZHEJIANG UNIV OF TECH
System for the detection of microbial contamination in food processing systems
A system for detecting microbial contamination in food processing environments, comprising: a sensor array with a variety of biosensors for detecting microbial markers that indicate a specific microbial contamination; a microfluidic analysis unit operatively coupled to the sensor array, the microfluidic unit comprising microchannels that direct environmental or food sample fluids through a series of analyzable stages, including sample concentration, enrichment, and pathogen identification; and a central processing unit (CPU) communicatively connected to the sensor array and the microfluidic device, the CPU being configured to receive and process real-time data from the sensor array, apply machine learning techniques to detect microbial contamination, and trigger an automated response based on predetermined contamination severity thresholds, the system being designed to continuously monitor microbial contamination at various stages of food processing, providing operators with real-time feedback and enabling immediate corrective action.
Owner:ABDELSALAM SAMY SELIM +11
GC-IMS-based food freshness detection method, device and equipment
InactiveCN120446355AComponent separationMaterial analysis by electric/magnetic meansData miningIon-mobility spectrometry
The invention relates to the technical field of food detection, in particular to a GC-IMS-based food freshness detection method, device and equipment, and the method comprises the following steps: obtaining headspace sampling gas of a to-be-detected food sample; according to the type of the to-be-detected food sample, automatically matching preset chromatographic conditions and ion mobility spectrometry conditions from a graded food type database; the headspace sampling gas is injected into GC-IMS, analysis is carried out based on matched chromatographic conditions and ion mobility spectrometry conditions, and a volatile organic compound fingerprint spectrum of the sample is obtained; and extracting preset key feature information from the fingerprint spectrum, and inputting the key feature information into a food freshness evaluation model to obtain a freshness evaluation result of the to-be-detected food sample. Therefore, the problems that in the prior art, detection parameter curing lacks adaptability, key feature analysis is not accurate, and model prediction accuracy is insufficient are solved.
Owner:SICHUAN TOURISM UNIV
Device and method for chemical analysis
A processing and detection system for detecting presence of at least one gluten protein in a food sample comprises a food processor including: a reservoir containing a process liquid for processing the food sample; a body that comprises a chamber configured to receive the food sample; and a pressing surface configured to press on the reservoir to cause the process liquid to exit the reservoir and mix with the food sample, thereby generating a processed food liquid; and an exit port configured to conduct the processed food liquid out of the food processor; and a cartridge including: at least one sensor configured to receive the processed food liquid and to generate an electrical signal in response to interaction with the at least one gluten protein in the processed food liquid, and an analyzer in electrical communication with the at least one sensor for detecting the electrical signal and determining the presence of the at least one gluten protein in the food sample based on the detected electrical signal.
Owner:GRAPHENE DX INC
Novel fluorescent probe based on triphenylamine as well as preparation method and application of novel fluorescent probe
ActiveCN119504701Afast responsehigh sensitivityOrganic chemistryFluorescence/phosphorescenceFluoProbesDual imaging
The invention discloses a novel fluorescent probe based on triphenylamine and a preparation method and application thereof, the preparation method comprises the following steps: S1, dissolving 4-methoxyaniline and 1-bromo-4-iodobenzene in a solvent A, and then adding copper iodide, 1, 10-phenanthroline and potassium tert-butoxide for reaction to obtain a compound 1; s2, dissolving the compound 1 obtained in the step S1, (5-formylthiophene-2-yl) boric acid and anhydrous potassium carbonate in a solvent B, and then adding PdCl2 (dppf) for reaction to obtain a compound 2; and S3, dissolving the compound 2 obtained in S2 and malononitrile in a solvent C, and then adding triethylamine for reaction to obtain the TPA-CN probe. The TPA-CN probe is used for monitoring exogenous and endogenous SO2 and viscosity change in living cells. According to the invention, dual imaging of SO2 and viscosity in a biological system and a food sample can be realized.
Owner:GUANGDONG MEDICAL UNIV
Method for detecting dish food quality
ActiveCN119470322Aquick filtersmall sample sizeImage enhancementImage analysisBiotechnologyNutrition
The invention relates to the field of food detection, in particular to a method for detecting dish food quality, which comprises the following steps: acquiring a package three-dimensional image and a food three-dimensional image of a dish food to be detected, and respectively processing the package three-dimensional image and the food three-dimensional image to obtain a corresponding package contour map and a food contour map; analyzing contour lines of the package contour diagram and the food contour diagram, and calculating the curvature difference of each corresponding point; according to the curvature difference threshold value and the abnormal corresponding point threshold value, judging whether the to-be-detected dish food has an abnormal area or not; performing spectrum detection on the to-be-determined abnormal food sample to obtain the nutrient content, and determining whether the to-be-determined abnormal food goes bad according to the nutrient content; and storing the to-be-determined qualified product, and detecting the residual nutrient content of the to-be-determined qualified product when the rated storage time is up. According to the method, potential abnormal samples are rapidly screened out by analyzing the contour lines of the package and the food contour, the number of samples needing spectrum detection is reduced, and the overall detection efficiency is improved.
Owner:BEIJING SIECAN TECH CO LTD
Pyrenyl beta-cyclodextrin magnetic graphene oxide gel, preparation method thereof and application of pyrenyl beta-cyclodextrin magnetic graphene oxide gel in food safety detection
PendingCN119346074AIon-exchange process apparatusOther chemical processesAdsorption equilibriumFood safety
The invention belongs to the field of chemical materials, particularly relates to pyrenyl beta-cyclodextrin magnetic graphene oxide gel, a preparation method of the pyrenyl beta-cyclodextrin magnetic graphene oxide gel and application of the pyrenyl beta-cyclodextrin magnetic graphene oxide gel in food safety detection, and discloses the pyrenyl beta-cyclodextrin magnetic graphene oxide gel. The gel is obtained by covalent bond connection and supramolecular interaction-host-guest assembly of magnetic graphene oxide, beta-cyclodextrin molecules and pyrene derivatives. The gel belongs to a lamellar stacked three-dimensional structure, and compared with traditional gel, the gel has the advantages that the overall pore diameter is increased, the separation flux is improved, the separation efficiency is improved, adsorption equilibrium can be quickly achieved within 0.5 min, and specific separation and adsorption of mycotoxin in a complex food sample are facilitated.
Owner:CHINESE ACAD OF INSPECTION & QUARANTINE +1
High-sensitivity moisture fluorescence probe as well as preparation method and application thereof
The invention discloses a moisture fluorescence probe based on a D-pi-A structure as well as a preparation method and application of the moisture fluorescence probe. The preparation method specifically comprises the following steps: dissolving WP in a solvent, reacting with BF3. Et2O under the protection of nitrogen, filtering, washing and drying to obtain a red target product WP-BF3. According to the present invention, the change of the microenvironment moisture content can be responded, the significant fluorescence signal response can be generated at the 487 nm position, the quantitative analysis detection of the moisture content in the organic solvent and the food sample can be achieved, the response is rapid, the sensitivity is good, and the accuracy is high.
Owner:NANJING UNIV OF FINANCE & ECONOMICS
Model construction method and finished dish nutrient analysis method and device
ActiveCN119446423Aimprove accuracyImprove efficiencyNutrition controlNeural learning methodsQuality dataEngineering
The embodiment of the invention provides a model construction method and a finished dish nutrient analysis method and device, and belongs to the technical field of artificial intelligence. The method comprises the steps that food sample data of a dish sample is acquired, the food sample data comprises first food feature data and second food feature data, the first food feature data comprises raw material component data and cooking mode data, and the second food feature data comprises raw material quality data and raw material edible quality data; the first food feature data are encoded and then spliced, first fusion feature data are obtained, and the first fusion feature data are used for indicating the influence degree between the raw material component data and the cooking mode data; and based on the first fusion feature data, the second food feature data and the second fusion feature data of the dish sample, training a preset neural network factorization machine to construct a food nutrient prediction model. The accuracy of nutrient analysis of finished dishes can be improved.
Owner:Guangdong Provincial Center for Disease Control and Prevention (Guangdong Academy of Preventive Medicine Sciences)
Food detection sample storage box
Owner:兰陵县检验检测中心
A sample pretreatment device for food safety detection
The application relates to the field of food detection, and discloses a sample pretreatment device for food safety detection, which comprises a shell, a crushing mechanism, a centrifugal mechanism, a material distribution mechanism, a solid-phase extraction mechanism and a nitrogen blowing mechanism are arranged in the shell; juice is obtained after the food sample is crushed, and the juice is subjected to centrifugal treatment in the centrifugal mechanism; the supernatant after centrifugation is temporarily stored and distributed in the material distribution mechanism; the multiple samples after distribution are subjected to solid-phase extraction in the solid-phase extraction mechanism; and the nitrogen blowing mechanism cooperates with the solid-phase extraction mechanism to complete nitrogen blowing work. Through structural innovation and function integration, the crushing, centrifugal, material distribution, extraction and nitrogen blowing concentration five function modules are integrated in the same equipment, the equipment floor area is reduced, the operation process is optimized, the manual intervention frequency is reduced, and the efficiency and reliability of the food safety detection sample pretreatment are remarkably improved.
Owner:SICHUAN FOOD INSPECTION INST +1
Food colony detection and analysis method and system based on artificial intelligence
The invention discloses a food colony detection and analysis method and system based on artificial intelligence, and the method comprises the steps: carrying out gradient elution-layered filtration pretreatment on a to-be-detected food sample to generate an impurity-removed colony sample; synchronously performing bacterial colony microscopic image acquisition and near infrared spectrum data acquisition on the impurity-removed bacterial colony sample to generate initial multi-modal data; performing space-time calibration processing on the initial multi-modal data to generate multi-modal data after space-time calibration; performing multi-dimensional bacterial colony feature extraction and screening processing on the multi-modal data after space-time calibration to generate a strong correlation feature subset; performing AI double-branch attention fusion analysis processing on the strong correlation feature subset to generate a bacterial colony classification result and a bacterial colony concentration estimated value; and performing multi-reference-system correction processing on the bacterial colony classification result and the bacterial colony concentration estimation value to generate a corrected detection result. According to the invention, the timeliness and reliability of the detection result are improved.
Owner:YINUO (TIANJIN) TESTING SERVICE CO LTD
Food sensory evaluation method based on attention mechanism
The invention relates to a food sensory evaluation method and device based on an attention mechanism, equipment and a medium. The method comprises the following steps: acquiring sensory information such as vision, smell, taste and touch of a food sample through multi-modal data acquisition equipment, and performing standardization processing to obtain a sensory feature matrix; generating a sensory feature vector set by using a pre-established multi-modal feature extraction model; modeling each sensory dimension relationship by means of an attention layer in a deep learning network, and calculating to obtain an attention weight of each sensory feature; and performing weighted combination on the sensory feature vector set based on the weight to generate a comprehensive sensory feature basic representation. According to the method, the association among the multi-modal sensory characteristics is effectively modeled through an attention mechanism, and a scientific and efficient solution is provided for food sensory evaluation.
Owner:ZHEJIANG PHARMA COLLEGE
Rapid detection box for food safety sampling
ActiveCN222330353Uquick take outensure safetyContainer handlesExternal fittingsFood labelingFood safety
The utility model relates to the field of food safety, and discloses a food safety sampling rapid detection box which comprises a detection box body, a rotary drum seat is arranged in an inner cavity of the detection box body, a plurality of containing grooves are formed in the top of the rotary drum seat, limiting mechanisms are arranged in inner cavities of the containing grooves, a rotary shaft is fixedly connected to the center of an inner cavity of the rotary drum seat, and the rotary shaft is fixedly connected with the rotary drum seat. According to the food safety sampling rapid detection box, a detection sample test tube is placed in the containing groove and limited by the limiting mechanism, a food label is placed in the label groove, the transparent sealing cover is covered, the test tube is pressed from the top to seal the top, and the transparent sealing cover does not need to be opened when the test tube is taken for detection; the sealing plug is taken down, the rotating block drives the rotating shaft and the rotating drum seat to rotate, so that the required sample test tube is rotated to the bottom of the groove hole, the test tube is ejected by the ejection mechanism, the required sample test tube is conveniently and quickly taken out for detection, and the problem that the required sample test tube is difficult to take out in the conventional food detection box is solved.
Owner:WUXI QIMING TECHNOLOGY CO LTD
Method for detecting metal mercury in food
InactiveCN119375198APreparing sample for investigationFluorescence/phosphorescenceIron sulfateMercuric ion
The invention discloses a method for detecting metal mercury in food, and relates to the technical field of food detection. Comprising the following steps: extracting a mercury-containing solution from a to-be-detected food sample, preparing a ferrous sulfate / graphene oxide nano composite material, enriching mercury ions in the mercury-containing solution by using the nano composite material, and quantitatively analyzing the mercury ions on the nano composite material by adopting atomic fluorescence spectrometry. According to the method, the collected food sample is subjected to digestion pretreatment, the mercury-containing solution is prepared, metal mercury in the food can be fully and effectively extracted, the ferrous sulfate / graphene oxide nanocomposite is prepared, mercury ions on the nanocomposite are quantitatively analyzed through atomic fluorescence spectrometry, metal mercury detection is achieved, and the detection accuracy is high. The mercury ions in the mercury-containing solution can be fully adsorbed and enriched in the whole detection process, pollution source introduction and mercury loss are avoided, the accuracy of the detection result is ensured, the detection process is simple and clear and easy to operate, and the detection period is shortened to a certain extent.
Owner:AGRI PRODS PROCESSING RES INST CHINESE ACAD OF TROPICAL AGRI SCI
Veterinary drug residue intelligent detection system and method based on multi-dimensional spectral characteristics
InactiveCN121476088APreparing sample for investigationColor/spectral properties measurementsAnimal scienceBand spectrum
The invention provides an intelligent veterinary drug residue detection system and method based on multi-dimensional spectral characteristics, and relates to the technical field of veterinary drug residue detection, spectral response data of a to-be-detected sample solution in a visible light band and a near-infrared band is collected, and the residue discrimination degree of veterinary drug residues under any wavelength when the concentration dependence change exists is determined; abnormal wave band combinations with quantitative response to veterinary drug residues are screened out from the visible light wave band and the near-infrared wave band respectively, the residual peak deviation of the veterinary drug residues in the region of interest of the spectrum is determined according to the abnormal wave band combinations, and trace residue marks in the multiple spectrum intensity distribution modes are determined; and performing in-situ nondestructive screening on veterinary drug residues in the to-be-detected animal-derived food sample according to the residue discrimination and the trace residue mark. According to the method, on the premise that the dual-band spectrum collaborative response is enhanced, the veterinary drug residue characteristics can be directionally distinguished and detected, so that the veterinary drug residue screening accuracy is improved.
Owner:WUWEI VOCATIONAL COLLEGE
A streptavidin binding peptide functionalized phage and its preparation method and application in detecting escherichia coli in food
The application provides a preparation method of a functionalized phage probe and application of the functionalized phage probe in detection of escherichia coli. The functionalized phage is a recombinant phage (M13KO7@SaBP) in which streptavidin binding peptide (SaBP) is fused and expressed at the N terminal of the main capsid protein P8 protein of M13K07 phage. In the application, the gene encoding SaBP (MDVEAWLGAR) is inserted into the N terminal of the P8 protein gene of M13K07 phage by site-directed mutagenesis to prepare M13K07@SaBP. The stable signal amplification is realized by using the abundant P8 protein (about 2700) of M13 phage and the super strong binding force of biotin-streptavidin, the interference of food sample matrix is reduced by combining the magnetic separation technology, and a detection method of escherichia coli with high sensitivity and small sample matrix interference is constructed.
Owner:CENTRAL SOUTH UNIVERSITY OF FORESTRY AND TECHNOLOGY
Electrochemical sensing platform for detecting lead ions and malathion as well as preparation method and detection method of electrochemical sensing platform
PendingCN120891054AMicrobiological testing/measurementMaterial analysis by electric/magnetic meansAptamerMalathion
The invention belongs to the field of detection, and particularly relates to an electrochemical sensing platform for detecting lead ions and malathion as well as a preparation method and a detection method of the electrochemical sensing platform. The preparation method of the electrochemical sensing platform comprises the steps of designing a three-chain DNA compound, preparing a gold nanoparticle electrode, preparing the electrochemical sensing platform and the like. The electrochemical sensing platform realizes dual detection of lead ions (in a signal enhancement mode) and malathion (in a signal weakening mode) through specific recognition of DNAzyme and an aptamer on the basis of a three-chain DNA compound and a gold nanoparticle electrode. The method has the advantages of no label, high sensitivity (the detection limits respectively reach 5.42 pM and 0.34 pM), strong anti-interference capability and good stability, and is suitable for rapid detection of trace pollutants in environment and food samples.
Owner:SICHUAN NORMAL UNIV