332 results about "Food sample" patented technology

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.

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.

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.

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.

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.

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.

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.

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.

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.

The invention discloses a bidirectional coupling numerical simulation method for a translation heating process of regular or irregular food in a microwave cavity, and belongs to the technical field of microwave heating. According to the invention, liquid nitrogen is adopted for freezing and homogenizing food samples, so that the accuracy of food electric heating characteristic parameters can be improved; the prediction precision of microwave heating numerical simulation can be improved by adopting a bidirectional coupling translational motion mode. The method for accurate modeling of regular food and platform or round corner approximate modeling of irregular food corners can effectively conform to the finite element and finite time domain difference principle. Aiming at microwave-assisted heating models of various heat sources, the fluid power grid division mode provided by the invention can effectively reduce false cooling phenomena occurring at the initial stage of heating translational motion operation, and is more suitable for the actual microwave-assisted heating treatment process. According to the invention, the time and economic cost of sample testing can be greatly reduced, and accurate prediction of microwave processing temperature changes of regular food and irregular food can be realized.

The invention relates to the technical field of intelligent detection, and discloses an intelligent detection method and system for illegal food addition and a storage medium. The method comprises the following steps: preparing a multi-target SERS substrate for inhibiting interference; a food sample is extracted and injected into the substrate, and a multi-dimensional spectrum is obtained through three-wavelength laser scanning; performing noise reduction and alignment on the spectral data to extract characteristic peak fingerprints to form a unique identification matrix; and training a multi-path parallel attention network, and simultaneously identifying various additives and concentrations through feature fusion. The method solves the problem of insufficient detection sensitivity and specificity caused by the influence of interfering substances such as citrate in food safety detection in the SERS technology, and breaks through the technical bottleneck that a traditional method is difficult to detect various illegal food additives at the same time; the problem of low accuracy and efficiency of a detection result caused by lack of intelligent data processing in the prior art is solved.

The invention discloses a rapid component detection system based on food additives, and relates to the technical field of food safety detection.A food sample is collected, matrix information of the food sample is obtained, an additive fingerprint feature group is extracted based on a reference model, sample response signals are collected through multi-channel detection, and feature matching analysis is carried out; outputting additive existence judgment and a matching degree score; when the matching degree score is lower than a preset threshold value, abnormal response features are extracted, feature vectors of the components to be verified are constructed and compared with the high-risk component template data, and suspected illegal added components are marked; by fusing spectrum, fluorescence and electrochemical multi-dimensional detection channels, the method has the characteristics of broad spectrum, rapidness and high adaptability, can realize intelligent identification and early warning of unknown or illegal additives, and is suitable for mobile detection and risk screening in various food scenes.

1. Name of the designed product: sample scale. 2. Use of the designed product: weighing, food sample, data recording and transmission. 3. Design points of the designed product: in shape. 4. Picture or photo that best shows the design points: perspective view.

To provide an allergic reaction test food which contains nuts as the only allergen, can be provided to infants without the risk of aspiration, and a method for producing the allergic reaction test food.SOLUTION: Provided is an allergic reaction test food product comprising a freeze-dried product of a predetermined shape that contains nuts, starch, and dextrin and does not contain any allergens other than those derived from nuts. The nuts are in a paste form, preferably with a maximum particle size of 900 μm or less, preferably with a nut content of 0.02 to 4.2 g per piece in terms of weight before freeze-drying, and preferably dissolved in water or hot water at the time of use to form a paste.SELECTED DRAWING: None

The utility model discloses a food detection sample centrifugal separation device, and belongs to the technical field of food detection equipment.The centrifugal separation device comprises a shell and a top cover arranged on the shell, a servo motor is installed at the upper end of the top cover, a centrifugal barrel is arranged in the shell, and a sealing cover is arranged at the upper end of the centrifugal barrel; the centrifugal cylinder and the sealing cover are provided with a quick-mounting mechanism, the quick-mounting mechanism comprises hinge seats symmetrically mounted on the sealing cover, and positioning clamping seats are hinged to the hinge seats; the centrifugal cylinder and the sealing cover can be separated, so that a food sample needing to be detected can be conveniently poured in, the interior of the centrifugal cylinder can be conveniently and completely cleaned after the centrifugal cylinder is taken out from the interior of the shell in the later period, and incomplete cleaning at deep or dead angles is avoided; the positioning seats are arranged at the two ends of the centrifugal barrel, and the positioning clamping seats clamped with the positioning seats are arranged at the two ends of the sealing cover, so that the centrifugal barrel and the sealing cover can be conveniently mounted and dismounted, and a worker can conveniently clean the centrifugal barrel by taking down the sealing cover.

The invention relates to the technical field of food quality inspection, in particular to a multi-dimensional analysis food quality detection system, which comprises a data acquisition module for performing non-destructive physical detection on a target food sample, acquiring a multi-source sensing signal and generating a food original physical characteristic data stream; the feature extraction module is used for constructing a multi-dimensional physical feature vector matrix of food and carrying out dimension standardization and redundant feature elimination processing; the characteristic correlation analysis module is used for performing similarity comparison on the multi-dimensional physical characteristic vector matrix and a preset food component database, outputting a food component estimation result and establishing a mapping model between physical characteristics and chemical indexes; and the quality evaluation module is used for comparing a food component estimation result with a food standard parameter, generating a quality risk grade evaluation report and dynamically adjusting a sensing strategy. According to the invention, the safety, efficiency and broad-spectrum adaptive capacity of food detection are improved, and the method is especially suitable for online rapid screening scenes of complete commodities, raw materials or in-transit food.

The utility model relates to the technical field of sample storage, and discloses food sample storage equipment with a temperature monitoring function, which comprises a storage box, a box door is hinged to the front side of the storage box, a cold air device is fixedly connected to the top of the storage box, a fan shaft is movably connected to the inside of the cold air device, and the fan shaft is fixedly connected to the front side of the storage box. A plurality of fan blades are fixedly connected to the surface of the fan shaft, a plurality of placing tables are arranged in the storage box, a temperature sensor is fixedly connected to the upper portion of the left side in the storage box, and an alarm is fixedly connected to the outer portion of the joint of one end of the temperature sensor and the storage box. According to the food sample storage equipment, the temperature in the storage equipment can be monitored in real time, and when the temperature in the storage equipment exceeds a preset safety range, the alarm can give an alarm immediately, so that abnormal conditions can be found and handled in time, and samples are prevented from going bad or being damaged due to too high temperature.

The invention relates to the technical field of spectral analysis, in particular to a hydroxytyrosol content detection method and system for food quality inspection.The method comprises the steps that spectral data of an olive oil food sample are collected, liquid chromatographic data of the food sample are obtained, a peak point, a chromatographic peak sequence and a chromatographic peak half-and-half sequence are determined, a chromatographic peak shape interference coefficient is obtained, and a hydroxytyrosol content detection result is obtained. Acquiring a peak shape symmetric inclination coefficient based on the chromatographic peak shape interference coefficient and the difference before and after peak points in the chromatographic peak half-and-half sequence, determining a self-adaptive asymmetric penalty coefficient, acquiring chromatographic data of the corrected olive oil food sample, and judging whether the content of hydroxytyrosol in the olive oil food sample reaches the standard or not. The method aims at solving the problems that in a traditional BEADS algorithm, an asymmetric penalty factor cannot be dynamically adjusted according to the liquid chromatogram data of the olive oil food sample, so that the liquid chromatogram data of the olive oil food sample is excessively corrected and is not sufficiently corrected.

This invention belongs to the field of biosensor technology and provides a biosensor for detecting Salmonella typhimurium based on DNAzyme-amplified DNA nanowires activating CRISPR / Cas12a, comprising: CRISPR / Cas12a protein, Mg 2+ The nucleotide sequences are as shown in SEQ ID NO:1-8: aptamer Apt, A strand, AB strand, DNAzyme strand, H1 strand, H2 strand, H3 strand, and crRNA. This biosensor exhibits high detection sensitivity, low detection limit, and a detection range of 10⁻¹⁰. 5 With a CFU / mL range, high specificity, low background interference, stable fluorescence signal, simple operation, and mild reaction conditions, it is suitable for rapid on-site detection and applicable to the detection of actual food samples. The spiked recovery rate is 100.3%-103.9%, and it can be widely used in the detection of Salmonella typhimurium in the food industry and public health field.

The invention belongs to the technical field of food nondestructive detection, and particularly relates to a food deterioration nondestructive rapid detection method based on an electronic nose and mode recognition, which comprises the following steps: selecting to-be-detected food, pretreating, and putting into a sealed detection container, so that volatile odor components released by a sample reach a concentration stable state in a sealed space; starting an electronic nose detection system to carry out dynamic adsorption detection on volatile odor components in the sealed space, and obtaining an original odor response signal sequence in real time; preprocessing the original smell response signal sequence to obtain a standardized signal sequence; based on the standardized signal sequence, extracting a time domain feature, a frequency domain feature and a trend feature, and splicing the three features according to a preset sequence to obtain an odor feature vector of the to-be-detected sample; and inputting the extracted odor feature vectors into a pre-trained pattern recognition model, carrying out classification recognition on the feature vectors, and outputting the deterioration degree grade of the to-be-detected food sample, thereby realizing effective elimination of multi-source interference, comprehensive feature extraction and accurate classification recognition.

The present invention relates to a fiber optic fluorescence sensing detection system for food pathogens, comprising a sensing module and a detection module. The sensing module includes a fiber optic fluorescence sensing module (optical components and a fluorescence reaction module) and an environmental sensing module. The optical components include an optical fiber array, a filter, a collimating lens, and an image sensor. The fluorescence reaction module includes an excitation light source and a multi-channel fluorescence reaction tank. The excitation light source irradiates the solution in the centrifuge tube in the multi-channel fluorescence reaction tank to stimulate a fluorescence signal. The fiber optic array transmits the fluorescence signal. The filter selects the fluorescence signal. The collimating lens amplifies and focuses the fluorescence signal. The image sensor is used to image the fluorescence signal. The environmental sensing module includes several sensors that collect environmental data. The detection module obtains a fluorescence intensity image obtained by the image sensor and environmental data collected by the environmental sensing module, and performs pathogen detection on the solution of the food sample. The present invention can effectively detect food pathogens.

The invention discloses a multifunctional food quality safety detection device and an application method thereof, and relates to the technical field of food detection. The device comprises a sampling assembly, the sampling assembly is provided with a flow regulation and control assembly, a particle screening assembly is arranged on the sampling assembly, and a power regulation and control assembly is arranged on the sampling assembly; the sampling assembly is used for automatically sampling food samples; the flow regulation and control assembly is used for regulating and controlling the food discharging amount. Through use of the device, screening of particulate matters in liquid food is realized, convenience is provided for subsequent particulate matter sampling, and through movement of a push plate and a magnetic rod, not only can electric energy be generated, but also particulate matters on one side of a first sieve plate can be washed, and blockage caused by the particulate matters is prevented; and in addition, through cooperative use of the sampling assembly and the power regulation and control assembly, multiple liquid in food can be automatically sampled, the diversity and convenience of sampling are improved, power is accurately distributed, and excessive consumption of energy is reduced.

The utility model belongs to the technical field of food sample unfreezing, and particularly relates to a sample unfreezing device for food detection, which comprises an unfreezing box, an unfreezing groove is arranged in the unfreezing box, limiting grooves are symmetrically arranged on the inner wall of the unfreezing groove, a sliding plate is arranged between the two limiting grooves in a sliding mode, and a plurality of draining holes are arranged on the sliding plate. A rotating rod is rotationally mounted at the top of the sliding plate and located in the unfreezing tank, and a plurality of stirring rods are fixedly mounted on the peripheral side of the rotating rod and located in the unfreezing tank; the supporting rod is fixedly installed on one side of the unfreezing box, and a sliding groove is formed in the position, located on the top of the unfreezing box, of one side of the supporting rod. According to a sample needing to be unfrozen, the temperature of unfreezing water can be accurately controlled, so that the sample unfreezing speed can reach the fastest, meanwhile, the sample cannot be damaged, and the unfreezing efficiency is improved. It is guaranteed that the sample unfreezing efficiency can be improved, meanwhile, workers can conveniently take out unfrozen samples, and meanwhile the hands of the workers cannot be hurt.

The application relates to a method for detecting additives in food by using pressurized capillary electrochromatography, which comprises the following steps: (1) preparation of mixed series standard solution: standard substances of benzoic acid, sorbic acid and sodium saccharin are weighed respectively, mixed standard solution is prepared by dissolving and constant volume, the mixed series standard solution is obtained by diluting in different proportions; (2) sample treatment and preparation of the liquid to be measured: the weighed food sample is diluted, constant volume is performed after ultrasonic treatment, and the sample liquid to be measured is obtained by filtration; (3) determination: the mixed series standard solution and the liquid to be measured are analyzed by using pressurized capillary electrochromatography, the standard curve is drawn according to the chromatographic peak height and the concentration of the mixed series standard solution, the chromatographic peak height of the liquid to be measured is determined, and the concentration of benzoic acid, sorbic acid and sodium saccharin in the liquid to be measured is obtained according to the standard curve. Compared with the prior art, the pressurized capillary electrochromatography is applied to the simultaneous detection of benzoic acid, sorbic acid and sodium saccharin for the first time, sample treatment is simple, the consumption of the mobile phase and the sample is small, and the detection time is short.

The embodiment of the utility model provides a constant-temperature box for food inspection, and relates to the technical field of constant-temperature boxes, the constant-temperature box comprises a constant-temperature box body and a control host, and the control host is fixedly mounted on the top surface of the constant-temperature box body. The temperature between every two adjacent placement shells is detected in real time through temperature measuring equipment, heat of the heating pipes is blown out to the area between the two placement shells through the through holes by starting the heating pipes and the draught fans, air between the placement shells enters the inner cavities of the placement shells through the through holes in the peripheral positions, gas circulation is formed, and the heat dissipation efficiency is improved. The temperature precision of constant temperature is further improved, so that the culture effect on food samples is good; the motor is started, the motor drives the gears to rotate through the rotating shaft, the gears on the two sides can be meshed with the two racks through mutual meshing of the gears, the height of the containing shells can be adjusted in the constant temperature box body, the distance between every two adjacent containing shells meets the use requirement of sample containing, and use is convenient.

This invention discloses a method for screening key neurotoxic substances in food raw materials and their products using a *C. elegans* model combined with metabolomics. Food samples are processed to prepare a stock solution, which is then used to cultivate *C. elegans*. The sample exhibiting the greatest neurotoxicity to the nematodes is identified by analyzing the number of *C. elegans* movements and neuronal fluorescence images. Subsequently, key neurotoxic substances in food are systematically screened using a combination of non-targeted liquid chromatography-tandem mass spectrometry (LC-MS / MS) and a metabolomics platform. This application establishes a novel method for screening neurotoxic substances by combining nematode activity with non-targeted LC-MS / MS determination and a non-targeted metabolic platform, clarifying key neurotoxic substances in food and providing a theoretical basis for food quality control and high-quality development.

The utility model belongs to the field of food refrigeration devices and discloses a food sample refrigeration storage device which comprises a refrigeration cabinet, a mounting column is fixed on the side wall of the refrigeration cabinet, and a mounting frame is rotatably mounted on the mounting column. The lifting assembly is mounted in the mounting frame; the placing plate is mounted on the lifting assembly; and the driving assembly comprises a first linear pair and a driving plate, the first linear pair is fixed to the containing plate, and the driving plate is installed at the movable end of the first linear pair and slidably abuts against the containing plate. After the placing plate is lifted to a specified height through the lifting assembly, the first linear pair can drive the driving plate to move, abut against and push a sample box placed on the placing plate into the refrigerated cabinet, and the mode drives the sample box to enter, so that the sample box is more gentle to move, manual pushing is not needed, and the use is more convenient; and the side edge is shielded and blocked through the first linear pair, so that the situation that the sample falls off from the side edge in the pushing process is limited, and the reliability of the sample entering the refrigerated cabinet is ensured.

The application discloses a lysozyme content detection method in food, and belongs to the technical field of biological medicine detection. The method comprises the following steps: constructing a lysozyme detection standard curve; reacting a food sample to be detected with a fluorescent probe in a buffer system, measuring the fluorescence intensity of the reaction system, and calculating the lysozyme content in the food sample to be detected based on the standard curve. The application adopts a fluorescence spectrum method to research and compare the performance of polypeptide CALNNK (FITC) and lysozyme under different buffer systems, pH, temperature and reaction time conditions, and then uses the method to detect the lysozyme content in food. The 20 nmol / L polypeptide CALNNK (FITC) , BR buffer solution with pH=10.0, 4 min of time and 35 DEG C of temperature are the optimal reaction conditions, the lysozyme content in food can be quickly and accurately detected, and the method has far-reaching significance for the healthy development of the food industry.

The invention discloses a QuEChERS-high performance liquid chromatography determination method for diarrheogenic illegal additives in food, and the method comprises the following steps: step 1, taking 2.0 g of a food sample, adding 10 mL of an extraction solvent, carrying out vortex oscillation-ultrasonic treatment, then adding anhydrous magnesium sulfate and sodium chloride, carrying out vortex mixing, carrying out centrifugal treatment, and extracting a supernatant; 2, taking 5mL of the supernate, adding the supernate into a purification tube containing purification salt, carrying out vortex oscillation-centrifugal treatment, taking the supernate, and enabling the supernate to pass through a 0.45 mu m polytetrafluoroethylene microfiltration membrane, so as to obtain a solution to be detected; and 3, injecting the solution to be detected into a high performance liquid chromatograph, carrying out gradient elution by adopting a C18 chromatographic column and taking acetonitrile-water as a mobile phase at a flow rate of 1.0 mL / min, a column temperature of 30 DEG C, a detection wavelength of 210 nm and a sample size of 10 [mu] L, and quantitatively analyzing a target compound through an external standard method. The invention aims to obtain a method for detecting illegal additives in food, which is low in cost and high in detection efficiency.

The invention provides an MOF-on-MOF composite material, an aptamer probe as well as a preparation method and application of the aptamer probe. The MOF-on-MOF composite material comprises an HKUST-1 material, the surface of the HKUST-1 material is coated with a Cu-BDC nanosheet; the synthesized HKUST-1 (at) Cu-BDC / Apt aptamer probe can specifically recognize AFB1, the aptamer probe can directly capture the AFB1 and adsorb the AFB1 to active sites on the surface of a material to reduce the nano-enzyme activity of the AFB1, so that quantitative colorimetric detection of the AFB1 is realized, and the aptamer probe has low detection limit, wide detection range, good selectivity and anti-interference performance on the AFB1 and can be used for detecting the AFB1. The AFB1 in a food sample can be rapidly, sensitively and selectively detected. In addition, the composite material has an adsorption effect and high catalytic activity on fungaltoxin, and AFB1 can be efficiently removed through the adsorption effect and the catalytic action.