132 results about "Meat sample" patented technology

The invention belongs to the technical field of food fermentation, and provides a lactobacillus plantarum CMRC 1L and application thereof. The lactobacillus plantarum CMRC 1L disclosed by the invention is separated from a sour meat sample in Maojia village region in Lijiang City, Yunnan Province, grows well on an MRS culture medium, is high in acid production speed, has the biological characteristics of salt resistance, frostbite resistance, inhibition of growth and reproduction of spoilage microorganisms and the like, has a good fermentation effect on various plant proteins, and is an excellent strain for preparing a leavening agent for production. The invention also provides a leavening agent containing the strain and application of the leavening agent in vegetable protein meat products. Compared with the vegetable protein jerky without the leavening agent, the vegetable protein jerky product prepared by the preparation method provided by the invention has the advantages of stable quality, fresh and sweet fermentation fragrance, no beany flavor and good flavor and taste. The strain CMRC 1L has great potential when being applied to production of vegetable protein meat products.

The invention discloses a pork quality index accurate determination method and system based on multi-modal spectrum fusion. Based on visible near-infrared imaging hyperspectrum, near-infrared imaging hyperspectrum and Raman spectrum data of a longissimus dorsi and waist muscle sample of a pig, accurate determination of key pork quality indexes of the pig is realized through a multi-modal fusion network SF-Net, a set of pork quality index accurate determination system is constructed, the system can automatically collect three modal spectrums of a pork sample, and the accuracy of the pork quality indexes is improved. Spectral features and frequency features of meat samples are analyzed and extracted, and feature fusion is performed by using a multi-modal fusion network, so that accurate measurement of the key meat quality indexes of the pigs is realized. Compared with the prior art, on the basis of realizing lossless and efficient determination of the pig key meat quality indexes, the accuracy of meat quality index determination is further improved. According to the method, the meat quality indexes can be accurately measured, meanwhile, the multiple meat quality indexes can be synchronously measured, and a new method is provided for online real-time intelligent evaluation of the meat quality.

The invention discloses a chilled beef freshness rapid detection model training method and a freshness detection method.The chilled beef freshness rapid detection model training method comprises the steps that a chilled beef sample is obtained, and the freshness index of the chilled beef sample is measured, the freshness indexes comprise the sensory score, the color a *, the pH value, the volatile basic nitrogen TVB-N, the thiobarbituric acid reactant TBARS, the total bacterial count TVC, the carbonyl content, the total sulfydryl content and the solubility of the chilled beef sample; establishing a chilled beef freshness grade evaluation standard according to the freshness index; collecting multi-modal data of the chilled beef sample, wherein the multi-modal data comprises near infrared spectrum data NIR, hyperspectral data HSI and low-field nuclear magnetic resonance LF-NMR relaxation time data; performing feature extraction on the multi-modal data through a feature extraction method to obtain multi-modal feature data; and carrying out preprocessing on the multi-modal characteristic data through a standardization SS and a Savitzky-Golay smooth filtering SG preprocessing method so as to obtain preprocessed data.

The invention relates to the technical field of fish meat source identification, in particular to a method for identifying different sources of fish meat by combining an electronic tongue with HS-SPME-GC / MS. The method comprises the following steps: obtaining a fish meat sample; performing taste detection on the fish meat sample by adopting an electronic tongue to obtain a taste detection result; after the fish meat sample is extracted, volatile odor substance detection is conducted through chromatography and mass spectrometry, volatile odor substances comprise one or more of dimethyl phthalate, nonanal, n-hexyl alcohol, naphthalene, octanol, 1-octylene-3-alcohol and alpha-platylene, and a volatile odor substance detection result is obtained; and identifying the fish meat source in combination with the taste detection result and the volatile odor substance detection result. According to the method, an electronic tongue technology and a headspace solid phase microextraction-gas chromatography-mass spectrometry technology are combined for use, and the taste and the smell are detected at the same time so as to distinguish fish meat from different sources, so that a more reliable quality evaluation system can be established, accurate traceability and grading are supported, and different user requirements are met.

The utility model discloses a frozen meat sampling device, and relates to the technical field of food sampling, the frozen meat sampling device comprises a base, the upper surface of the base is fixedly connected with a support, the horizontal section of the support is fixedly connected with a driving device, and the output end of the driving device is provided with a guide structure. Through cooperative arrangement of structures such as the sampling pipe, the collecting bag, the groove and the jacking column, after the frozen meat penetrates through, the sampling pipe is pushed by the driving device to continue to move downwards, at the moment, the jacking column fixedly mounted on the bottom wall of the groove is reversely inserted into an inner cavity of the sampling pipe from the bottom end of the sampling pipe, and the frozen meat remaining in the sampling pipe is jacked into the collecting bag; a user can perform sampling again through the whole device after replacing the collecting bag, and the problems that after sampling of an existing sampler, a frozen meat sample is reserved in a sampling tube, the frozen meat sample in the sampling tube needs to be inspected and then can be sampled again through the sampling tube, and use is very inconvenient when the user needs to perform sampling and detection for multiple times are solved as much as possible.

The present invention is applicable to the technical field of nondestructive detection of food quality and safety, and provides a nondestructive rapid detection method for the texture of fish meat with different freshness, comprising the following steps: preparing fish meat samples with different freshness, so that the modeled fish meat samples contain primary, secondary and tertiary freshness; using a texture analyzer to test the elasticity, hardness and chewiness indexes of fish meat with different freshness; using near infrared and Raman spectroscopy to collect near infrared spectrum and Raman spectrum information of fish meat respectively; using CARS and SiPLS methods to extract features from the spectral information of fish meat, and then using the OSC method for preprocessing on this basis, performing intermediate data fusion on the processed spectra, and establishing PLSR prediction models for elasticity, hardness and chewiness respectively; finally, using the established prediction model to test the texture characteristics of fish meat with unknown freshness. The detection method of the present invention improves the accuracy of nondestructive detection of fish meat texture, and is of great significance for the rapid evaluation of fish meat quality.

The invention discloses a rapid marinating soup quality parameter acquisition method and a marinating time optimization method in a sauced product cooling process, and belongs to the technical field of sauced product production processes, and the method comprises the following steps: S1, acquiring near infrared spectrum data of a meat sample by adopting a near infrared spectrum technology; performing two-dimensional correlation analysis on the near infrared spectrum data, converting the one-dimensional spectrum data into two-dimensional correlation spectrum data, and improving the resolution of the one-dimensional spectrum data and the separation degree of overlapping peaks to obtain a two-dimensional correlation analysis result; s2, processing the two-dimensional correlation spectrum data by using a moving window technology, observing a time period in which a functional group changes along with external interference, and converting static detection of a substance into dynamic analysis to obtain a moving window technology processing result; and S3, acquiring nuclear magnetic resonance data of the meat sample by adopting a nuclear magnetic resonance technology, and reflecting the motion state of hydrogen protons. According to the invention, the meat moisture migration and fat oxidation degree can be accurately identified.

The invention discloses a preparation method and application of an Au@AgNPs-Van / PDMS thin film SERS detection platform. First, an Au@AgNPs sol is prepared, then an Au@AgNPs-Van solution is synthesized, and finally an Au@AgNPs-Van / PDMS thin film SERS detection platform is constructed: a PDMS film is subjected to a hydrophilic treatment, the hydrophilic treated PDMS film is placed in 3-aminopropyl-trimethoxysilane, shaken and cultured overnight, washed with water and placed in an Au@AgNPs-Van solution, and reacted and taken out to obtain an Au@Ag NPs-Van / PDMS film. The invention realizes the application of the Au@AgNPs-Van / PDMS thin film SERS detection platform to the rapid capture, enrichment and SERS detection of foodborne pathogens in actual beef samples, and realizes the rapid capture, enrichment and detection of foodborne pathogens in a complex solution environment.

The invention provides a beef freshness detection method and detection system, and relates to the technical field of optical identification detection, the detection system comprises a sample detection device and a detection platform, the sample detection device carries a visual identification assembly, a cleaning mechanism, a locking extension assembly and a lifting mechanism, a light source control system, a database, a feature extraction module and a prediction analysis module are further carried in the visual recognition assembly, a model is established in the detection platform, and side plates are welded to the two sides of the sample detection equipment. According to the method, the water content of the surface layers of different samples is highly consistent, the interference of wrinkles on the surface of the to-be-detected beef sample on the final result in the image acquisition process is avoided, the detection accuracy is improved, the pretreatment difficulty of the beef sample in the early stage is reduced, and the whole detection process is highly standardized and unified.

The invention provides a GC-IMS (Gas Chromatography-Insulated Mass Spectrometry)-based method for quickly identifying the vinasse preparation time and aroma difference of fish blocks, which comprises the following steps of: incubating fish meat samples in different vinasse preparation stages in a headspace sampling bottle to obtain an incubated sample, extracting a gas sample from the incubated sample by using a sampling needle, and analyzing the extracted gas sample by using a gas chromatography-mass spectrometry (GC-IMS); the extracted gas sample enters a headspace gas chromatography-ion mobility spectrometry combined instrument through a sample injection needle to be measured; detecting the to-be-detected fish block sample by using the same instrument condition; comparing and analyzing the to-be-detected fish blocks and the fish blocks in different vinasse processing stages in the database to confirm the vinasse processing stages of the fish blocks; according to the method disclosed by the invention, the GC-IMS technology is applied to carry out collection and trace analysis on complex aroma substances in the fish blocks in different vinasse processing stages, relatively comprehensive fingerprint information is provided for quality control of the fish blocks, and the vinasse processing stages of the fish blocks are determined according to corresponding characteristic indexes and difference components of the fish blocks in different vinasse processing stages; and rapid and accurate quality confirmation of the fish blocks in different grain pickling stages is realized.

The invention relates to the technical field of food detection, in particular to a composite purification filler and a pretreatment method for sulfonamide drug detection. The composite purification filler comprises carbonyl polymer particles, zinc chloride and polylactic acid, the weight ratio of the carbonyl polymer particles to the zinc chloride to the polylactic acid is 1: (0.1-0.5): (0.05-0.25). The composite purification filler provided by the invention is applied to a pretreatment method for detecting the sulfonamide residues in a meat sample, particularly a pretreatment method for detecting the sulfonamide residues in a chicken sample, so that efficient purification of the sample to be detected before detection can be simply and quickly completed.

The invention discloses a color-sensitive sensing array for meat freshness detection, the color-sensitive sensing array contains four color-sensitive materials capable of generating color development reaction with meat volatile organic compounds (VOCs), and the invention also discloses a smell imaging method for detecting meat freshness based on the color-sensitive sensing array. According to the method, the VOCs are subjected to sensitive detection through the color-sensitive sensing array, change information of the VOCs generated in a meat sample decay process is selectively extracted, and a multivariable prediction model is established by combining image processing and partial least squares regression so as to judge the freshness of meat. According to the invention, rapid and nondestructive detection of meat freshness is realized, the accuracy and efficiency of meat freshness detection can be improved, and the method is especially suitable for on-site real-time detection.

The invention relates to the technical field of food safety detection, discloses a method for determining 5 new pesticide residues in animal-derived foods by gas chromatography-tandem mass spectrometry, optimizes a beef sample pretreatment method based on QuEChERS by orthogonal experimental design, adopts a detection method of gas chromatography-tandem mass spectrometry, and combines external standard method quantification to establish a detection method for detecting 5 pesticide residues in animal-derived foods, which provides certain data support for future animal-derived food supervision and import and export risk monitoring. The method comprises the following steps: 1) preparation of standard solution: respectively preparing a standard reserve solution, a mixed standard working solution and a blank matrix mixed standard working solution; 2) sample pretreatment: placing the sample in a centrifuge tube, vortexing and centrifuging with an extraction solvent and an extraction dispersant, obtaining an upper organic phase, further vortexing and centrifuging in a centrifuge tube containing a dSPE mixture to obtain a supernatant, and filtering for standby use; 3) performing GC-MS / MS analysis on the filtered supernatant.

The invention belongs to the technical field of food flavor analysis and quality control, and particularly relates to a dynamic monitoring and quality evaluation method for flavor substances in the processing process of braised meat. According to the method disclosed by the invention, various detection means such as an electronic tongue, HS-SPME-GC-MS and HS-GC-IMS are adopted to detect and identify flavor components in different braising stages of the braised pork, so that the comprehensiveness and accuracy of flavor detection in the braised pork processing process are remarkably improved; besides, by improving the detection key conditions of the HS-GC-IMS, especially by adopting the treatment of balancing for 30 minutes at the temperature of 80 DEG C in the headspace equilibrium stage, the low-boiling-point volatile matters in the meat sample can be fully released, the desorption efficiency of small molecules is improved, the volatilization loss or thermal decomposition cannot be caused, and the detection sensitivity in the early stage is further improved.

The application provides a method for detecting the content of sodium hypochlorite in chicken, and belongs to the technical field of quantitative detection. Terahertz spectrum testing is performed on a dried chicken sample to obtain the peak height of a sodium hypochlorite characteristic peak; then, according to a standard curve and the peak height of the sodium hypochlorite characteristic peak, the content of sodium hypochlorite in the chicken is obtained; the frequency of the sodium hypochlorite characteristic peak is 1.10 THz or 1.25 THz; and the standard curve is a fitting curve of the mass content of sodium hypochlorite in the chicken and the peak height of the sodium hypochlorite characteristic peak. Different molecules exhibit different absorption peaks in terahertz absorption spectrum, and the application detects the content of sodium hypochlorite in chicken by using a terahertz spectrum method, and obtains the content of sodium hypochlorite in chicken by using the fitting relationship between the peak height of the sodium hypochlorite absorption peak and the content of sodium hypochlorite. The method provided by the application is simple, and can quickly and accurately obtain the content of sodium hypochlorite in chicken.

The invention relates to the technical field of analysis and detection, in particular to a method for detecting zeranol in a meat sample. The detection method comprises the following steps: pretreating a meat sample by adopting a magnetic dispersive solid-phase extraction method, and then detecting zeranol by adopting an immunochromatography technology, the magnetic dispersion solid-phase extraction method adopts an HLB magnetic nano material. The detection method provided by the invention has good accuracy, sensitivity and specificity, and can meet the requirement of rapid detection of zeranol in meat samples. The method is simple and convenient to operate, does not need professional detection equipment, can be operated by common law enforcement officers or food supervisors through simple training, and has a wide application prospect.

The disclosure relates to methods and systems for determining one or more parameters, attributes, or characteristics in a meat sample using an iteratively trained detection model. In one embodiment, the methods and systems disclosed herein use automated methods to determine muscle fascicle fracturing. Methods and systems disclosed herein comprise processing one or more images of a meat sample captured with a data capture device; and using an iteratively trained detection model to determine an objective classification, including the presence or absence of muscle fascicle fracturing in the images of the meat sample.

The invention provides a method for detecting antibiotic residues in chicken, and belongs to the technical field of food detection. The detection method comprises the following steps: (1) carrying out freezing pretreatment on a chicken sample; (2) the pretreated chicken sample is subjected to liquid phase extraction, a solution system is adopted for liquid phase extraction, and the solution system comprises acidified acetonitrile, an EDTA-2Na solution and phosphate; (3) enriching and purifying the chicken extracting solution, wherein an HLB solid-phase extraction column, a C18 solid-phase extraction column and an MCX solid-phase extraction column which are connected in series are adopted for enriching and purifying; (4) drawing a standard curve of each antibiotic; and (5) detecting the sample to be detected by using the portable Raman spectrometer, and calculating the content of each antibiotic in the sample according to the standard curve. According to the method, freezing pretreatment, solution system extraction and enrichment and purification of three solid-phase extraction columns are adopted for the sample, so that the extraction efficiency of the antibiotics in the chicken sample is remarkably improved, and the detection accuracy of the antibiotics is further improved.

The invention discloses a meat product detection device and a detection method thereof, and belongs to the technical field of food detection.The meat product detection device comprises a detector body, a base is arranged at the bottom of the detector body, a groove is formed in the side face of the top end of the base, a placement plate is slidably inserted into the groove, and a clamping and pressing assembly is arranged on the placement plate; a rotary adjusting assembly is arranged at one end of the containing plate, a driving motor is fixed to the side face of the top end of the base, and an intermittent adjusting assembly is arranged on one side of the containing plate. According to the meat sample glass plate detection device, multiple meat sample glass plates are synchronously clamped and fixed through the clamping and pressing assembly, the stability of the meat sample glass plates in the detection process is ensured, and detection is convenient; therefore, a plurality of meat sample glass plates on the placement plate are driven to sequentially move to the position under an observation lens of the detector body for detection and analysis, so that a plurality of different meat samples can be sequentially detected and analyzed, and the detection and analysis efficiency is further improved.

The invention provides a method for extracting and detecting free amino acids in meat. The method comprises the following steps: cutting a meat sample into blocks, freeze-drying, crushing and sieving to prepare meat powder; weighing meat powder, adding distilled water, uniformly mixing by vortex, performing water-bath constant-temperature oscillation extraction, and centrifuging to obtain a crude extract; adding sulfosalicylic acid precipitated protein into the crude extracting solution, centrifuging again, taking supernate, and adjusting the pH value with diluted hydrochloric acid to obtain an extracting solution; and filtering the extracting solution by a filter membrane, and detecting by a full-automatic amino acid analyzer. The method takes distilled water as an extraction solvent, efficiently extracts the free amino acid through water bath oscillation, is simple and convenient to operate, high in extraction efficiency and good in stability, is suitable for free amino acid detection of various meat samples such as chicken, beef and pork, and is high in practicability.

The invention discloses a meat freshness rapid detection and prediction method based on laser-induced graphene. The method comprises the following steps: firstly, preparing a laser-induced graphene impedance sensor with a porous structure on a polyimide film through laser processing; then acquiring impedance spectrum data of a meat sample in a wide frequency range by using the sensor, extracting a phase angle and an impedance amplitude as characteristic data, and constructing a training set by combining a volatile basic nitrogen measured value; a neural network model is further constructed and trained, and accurate detection from impedance features to TVB-N values is achieved; meanwhile, a dynamic prediction model with environmental specificity is established, prediction of the TVB-N change trend and freshness grade judgment in the future are supported, the laser-induced graphene impedance sensor is combined with the electrochemical impedance spectroscopy technology, and detection and prediction of the TVB-N value of the meat sample can be completed within a few minutes.

The invention discloses a portable meat doping identification chip and a detection method, and the method comprises the following steps: placing a meat sample slice on a sample bearing layer of the chip, starting the chip to collect a terahertz time-domain spectral signal, and calculating optical parameters of a meat sample in a frequency band of 0.2-2.0 THz; performing principal component analysis on the high-dimensional data of the optical parameters in the whole frequency band to obtain feature vectors; and inputting the feature vector into a pre-trained artificial intelligence model, respectively performing qualitative identification of meat species and quantitative prediction of the doping content, and outputting an analysis report containing a species identification result and a doping ratio.

The disclosure relates to a system and method for identifying one or more features in a meat sample. In one embodiment, the system and method disclosed herein uses automated methods to identify a backfinned pork loin and a non-backfinned pork loin. The system and method disclosed herein comprises imaging a meat sample with an imaging device to obtain one or more images; and using an iteratively trained feature detection model to detect and identify one or more features, including the presence or absence of the features in the images of the meat sample.

The invention relates to a marbling accurate scoring model based on a pork marbling standard scoring board image and a rapid construction method thereof. Acquiring a pork marbling standard scoring board and an actual meat sample image by adopting a scanner with a closed space; pork marbling is accurately extracted by adopting an automatic segmentation algorithm combining a local threshold value and an overall threshold value, and a marbling scoring model is constructed by taking a marbling area proportion extracted by a standard plate image as a characteristic parameter; and evaluating the predictive ability of the model by using the collected actual meat sample. According to the marbling scoring model, the R2 can reach 0.96, and the RMSE is smaller than 0.14; the RP between the marbling score value of the actual meat sample predicted by the model and the artificial perception marbling score value reaches 0.96, and the RMSE is 0.15; the proportion of the samples with the absolute error between the marbling score value predicted by the model and the true value smaller than one score can reach 94.73%.

This invention provides a colorimetric detection method and related apparatus for meat freshness based on a dynamic reference library. The method includes: acquiring a test strip image and meat type information of the meat sample to be tested; determining the region of interest (ROI) of the test strip image, extracting features from the ROI to obtain a feature vector, wherein the feature vector is a feature vector composed of RGB feature values; calculating a predicted concentration value and a confidence index based on the feature vector and a user-defined dynamic reference library using a K-nearest neighbor regression algorithm, wherein the dynamic reference library is constructed based on the mapping relationship between concentration gradient values ​​and RGB feature values ​​of a standard color chart image set and freshness threshold ranges for different meats; and comparing the predicted concentration value with the corresponding freshness threshold range for the meat to determine the freshness level information of the corresponding meat sample. Based on this, this invention can achieve high-precision detection of the freshness of different meats.

The invention discloses a meat quality detection method and a meat quality detection system based on flexible biological impedance imaging. The meat quality detection method comprises the following steps: acquiring impedance original values, PH, chromatic aberration and tenderness of a to-be-detected meat sample measured according to a preset measurement principle at a plurality of time points; correcting the impedance original value of the to-be-detected meat sample by using the correction coefficient; reconstructing the corrected impedance original value to obtain a reconstructed impedance value; obtaining the time point of meat deterioration according to the PH, color difference and tenderness at different time points; obtaining the average impedance value of all the reconstructed impedance values of the meat sample to be measured at the deterioration time point and the initial time point, calculating the impedance change rate of the meat sample to be measured at the deterioration time point and the initial measurement time point by using the reconstructed average impedance value, and comparing the impedance change rate with the pre-calculated impedance change rate of the frozen meat sample, if the impedance change rate of the to-be-detected meat sample is greater than the freezing impedance change rate, the to-be-detected meat sample is an unfrozen fish, otherwise, the to-be-detected meat sample is an iced fish. The method is simple in step, easy to detect and accurate in detection result.

The invention relates to a rapid detection method for food-borne pathogenic bacteria based on the action of meat-derived symbiotic microorganisms, belongs to the technical field of rapid detection and spectral analysis of fresh meat quality, and aims to solve the problems of tedious detection operation and high dependency on biochemical reagents caused by interference of a complex substrate and symbiotic microorganisms of fresh meat in the prior art. The method comprises the following steps: firstly, carrying out elution separation-homogeneous centrifugation-coating culture pretreatment on a fresh meat sample to eliminate the interference of a fresh meat matrix, and then preferably selecting a high-discrimination characteristic wave band from high-dimensional spectral data by applying a combined characteristic screening algorithm; and finally, detecting the food-borne pathogenic bacteria of the fresh meat by utilizing a qualitative and quantitative model established on the basis of a culture sample under the interference of the meat-borne symbiotic microorganisms in the earlier stage. The detection accuracy and sensitivity of the food-borne pathogenic bacteria in the fresh meat can be improved, meanwhile, the method has the advantages of being rapid, easy and convenient to operate and economical in cost, and technical support can be provided for detection of the food-borne pathogenic bacteria in the fresh meat.

The present disclosure relates to a kind of deep learning-based multi-source spectral fusion chicken quality detection method and sorting equipment, wherein the method comprises: obtaining the near-infrared hyperspectral image and visible-near-infrared hyperspectral image of the chicken to be detected;The near-infrared hyperspectral image and visible-near-infrared hyperspectral image are input into the chicken quality detection model, and the volatile base nitrogen content and total number of colonies of the chicken to be detected are obtained;According to the volatile base nitrogen content and total number of colonies, the quality of the chicken to be detected is determined.The purpose of the present disclosure is to provide a kind of deep learning-based multi-source spectral fusion chicken quality detection method and sorting equipment, which can realize the detection of chicken quality without damaging the integrity of the chicken to be detected.In addition, the detection process does not require human intervention, which not only improves the detection efficiency of chicken quality, but also can be applied to fully automated unmanned actual detection, which is conducive to the detection of large-scale chicken samples.

This utility model discloses a bacterial detection device for meat food safety, relating to the field of food testing technology. It includes a detection machine with a rotating motor installed at its detection port. The output end of the rotating motor is connected to a sealing shell that is in sealing contact with the detection machine. Detection trays are slidably connected to both sides of the sealing shell. This utility model involves placing a meat sample onto the detection tray inside the protective shell, then feeding the meat sample into the sealing shell. The sealing shell rotates, feeding the meat sample into the detection machine, thus completing the meat sample detection. The partition and sealing shell ensure that the device is in a closed state during meat sample detection, preventing external interference. After detection, a reset limiting plate feeds a new set of meat samples into the sealing shell. The sealing shell rotates, feeding the new set of meat samples into the detection machine for a new round of detection. The detected meat sample is then rotated out, thus completing the automatic detection of the meat sample.

The utility model discloses a sample treatment device for food detection, and relates to the technical field of food detection. According to the technical key points, the device comprises a sample treatment table, a horizontally-placed mounting frame is arranged on the upper side of the sample treatment table, a grating cutter is embedded in the mounting frame, and blades in the grating cutter are arranged in a criss-cross mode; a vertical guide rod is arranged on each of opposite sides of the sample treatment table, a sliding block is arranged on each guide rod in a sleeving manner, and opposite sides of the two sliding blocks are fixedly connected with the mounting frame; and the lower ends of the two guide rods are fixedly connected with the sample treatment table through extension rods. When the equipment is used, an experimenter presses down the mounting frame with two hands, a meat sample can be quickly cut into a plurality of small blocks by utilizing the grating cutter in the mounting frame, and compared with the prior art, the processing efficiency of the meat sample is greatly improved, and the risk that the hands of the experimenter are injured in the cutting process can be reduced.