102 results about "Meat sample" patented technology

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 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 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 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 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 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 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.

The application discloses a microbial nano-enzyme probe, a method for detecting salbutamol and application, and comprises a salbutamol monoclonal antibody and a signal carrier, wherein the signal carrier is a yeast cell loaded with iridium oxide nanoparticles. The application firstly constructs a probe by using a yeast cell loaded with iridium oxide nanoparticles in the detection of an immunochromatographic test strip, uses [3, 3', 5, 5' tetramethylbenzidine (TMB) and hydrogen peroxide (H2O2)] as a substrate to trigger a color developing reaction, can realize high-sensitivity target detection, and the detection limit is as low as 0.012 ng / mL, which is 55 times higher than the sensitivity of a traditional gold-labeled test strip. In addition, the application has a good application prospect, can provide a universal platform for sensitive, accurate and rapid detection of food-borne stimulants, and can be successfully applied to the detection of salbutamol in pig liver and beef samples.

The invention discloses a preparation method of a beef frozen wet powder matrix standard substance, and solves the technical problems of poor authenticity, low fidelity, poor uniformity and high energy consumption when a beef ractopamine residual matrix standard substance is prepared in the prior art. Obtaining a ractopamine positive beef sample; performing acid discharge treatment on the beef sample; pretreating the beef subjected to acid discharge, and cutting the beef into diced meat with the particle size of 5-10mm; preparing a frozen wet powder matrix standard substance by adopting a multi-stage freezing and crushing and pulse screening process; and uniformly mixing the final product at a low temperature, sub-packaging, and storing in an environment of-40 DEG C or-80 DEG C in a sealing manner. The traditional freeze-dried powder process is abandoned, the frozen wet powder is used as a carrier form, and the original physicochemical characteristics of fresh tissues are perfectly reserved by the form.

The application provides a SNP molecular marker and a breeding application method which are significantly related to the content of chicken meat flavor substance (E, E)-2,4-decadienal. The SNP molecular marker is rs316165567, contains a nucleotide sequence with a polymorphism of C / A at 2,519,798 bp of chicken chromosome 14, and when the genotype of the site is AA, the content of (E, E)-2,4-decadienal of the chicken meat sample is higher. The established molecular assisted breeding technology can early select the high-quality chicken flavor quality traits by determining the genotype of the SNP site of the measured chicken, can improve the content of (E, E)-2,4-decadienal of the chicken breast, and has great industrial application value and economic and scientific research value.

The application belongs to the technical field of detecting meat components based on nucleic acid technology, and particularly relates to a primer pair, a kit and a detection method for detecting horse meat components in food. The sequences of the primer pair are shown in SEQ ID NO. 1 and SEQ ID NO. 2. The application further discloses a kit for detecting horse meat components in food and a method for detecting horse meat components. The detection method comprises a pair of primers labeled with 6-FAM fluorescent groups and biotin, can realize high-sensitivity target detection, and can detect as low as 0.1% horse meat in adulterated meat samples. Compared with recombinant enzyme polymerase isothermal amplification real-time fluorescence detection, there is no need to design and screen RPA fluorescent probes. In addition, the application has good application prospect and can be successfully used for detecting horse meat components in donkey meat products, beef products, mutton products and venison products.

The utility model belongs to the technical field of meat product quality detection, and particularly relates to a sample hanging bag for juice loss determination based on meat product quality detection, which comprises a fixing plate, a bag body fixedly connected to the bottom of the fixing plate, a limiting rod fixedly connected to the bottom of the fixing plate and located in the bag body, and a hook slidably connected to the outside of the limiting rod. The two sides of the interior of the fixing plate are rotationally connected with rotating shafts. The utility model provides a sample hanging bag for juice loss determination based on meat product quality detection, and solves the problems that in the prior art, during juice loss determination of a meat sample, the meat sample is mostly manually hung on a hook and then hung in a packaging bag in a suspended manner, so that the manual operation is relatively troublesome, the labor intensity is low, and the like. And the problems that the meat sample is easy to shake due to manual operation, the bag body is easy to be collided by an external object after being hung, the meat sample is in contact with the bag body, the outflow of juice is hindered, or the juice on the bag body is absorbed by the meat sample to flow back, and the accuracy of final determination is influenced are solved.

The present invention discloses a method for detecting the freshness of beef and a computer-readable storage medium. It includes the following steps: introducing clean air into the detection chamber for cleaning; after the detection chamber is cleaned, inhaling the volatile gas generated by the beef sample to be detected into the detection chamber, and the gas sensor array in the detection chamber detects the volatile gas and sends the detection data to a computer; the computer performs partial differential structure processing on the detection data to obtain corresponding partial differential structure signals; the computer inputs the partial differential structure signals into a nonlinear stochastic resonance model to obtain corresponding signal-to-noise ratio eigenvalue; the computer determines the freshness of the beef according to the signal-to-noise ratio eigenvalue. The present invention can perform partial differential structure processing on the detection data, so that the input signal input into the nonlinear stochastic resonance model matches the nonlinear stochastic resonance model, avoiding the situation of non-resonance, thereby improving the detection stability and detection accuracy.

The application provides a kind of meat sample drip loss continuous determination device and method, it is related to meat sample determination technical field, including refrigerated cabinet is equipped with multiple refrigeration cavities, refrigeration cavity is sealingly connected with closed door, the rear end of closed door is connected with bearing frame, bearing frame is slidingly connected in refrigeration cavity;Two weight monitoring mechanisms are arranged in the upper portion of bearing frame, the front end of closed door is connected with shell, digital display controller is arranged in shell;Weight monitoring mechanism is connected with meat sample positioning mechanism;Suction mechanism is arranged below bearing frame.The water film formed in suction mechanism is contacted with the surface of breast muscle sample or leg muscle sample, to avoid friction and extrusion on breast muscle sample or leg muscle sample, digital display controller cooperates with weight monitoring mechanism and suction mechanism, continuously and synchronously obtains the drip loss data of breast muscle sample, leg muscle sample multiple time points, realizes in the same closed space, continuously determines breast muscle sample and leg muscle sample.

This invention discloses a method for detecting the freshness of giant salamander meat based on color constancy and integrated intelligent vision, belonging to the fields of food safety and computer vision technology. The method includes: acquiring RAW images of the meat sample and an indicator film and resolving them into linear radiosity tensors; constructing a color correction model using a latent diffusion local redraw network and a conditional control network; synthesizing a structure-constrained virtual reference color card in a masked region; extracting ambient light source features and performing adaptive white balance compensation to output a standard color image; inputting this image into a deep network optimized by ArcFace to extract a high-dimensional feature vector; and finally inputting this vector into an XGBoost model to fit a nonlinear decision boundary and outputting a freshness rating. This invention effectively reduces color shift interference from complex light sources, improves the recognition accuracy of samples in the critical period of color change, and provides a highly robust solution for non-destructive monitoring of giant salamander meat freshness in actual market environments.

The invention provides a correlation analysis method for flavor deterioration of chicken with different quality grades, and relates to the technical field of food science and meat quality analys.The correlation analysis method comprises the steps that chicken samples with different quality grades are grouped to obtain first samples for volatile flavor substance and sensory analysis; and a second sample for non-volatile metabolite analysis; carrying out detection and qualitative and quantitative analysis on the volatile organic compounds in the first sample by adopting a gas chromatography-ion mobility spectrometry technology; carrying out non-targeted detection and qualitative and quantitative analysis on the non-volatile metabolites in the second sample by adopting a liquid chromatography-tandem mass spectrometry technology; carrying out sensory evaluation on the color, texture, appearance and smell of the chicken samples with different quality grades; by combining a multivariate statistical analysis method, volatile organic compounds, non-volatile metabolites and sensory evaluation data are comprehensively analyzed, and flavor characteristics, metabolite changes and correlation of chicken with different lignification degrees are analyzed.

The present application relates to the technical field of meat detection, and particularly relates to a data-driven meat quality rapid detection method and system, which collects the physical and chemical data such as spectrum, image, pH value, temperature and humidity, volatile gas and the like of a meat sample through a multi-modal sensor, constructs a meat quality characteristic map, analyzes the map by using a machine learning algorithm, identifies key influencing factors and extracts quality characteristic data such as spectrum, texture and chemistry, analyzes the influence law of different factors on quality based on the characteristic data, obtains meat quality influence data, determines the judgment parameters of each quality grade in combination with the influence data, constructs and trains a deep learning detection model, inputs the real-time data of the meat to be detected into the model, realizes rapid identification and evaluation of quality, makes grade judgment according to the evaluation result, and automatically executes classification processing, improves detection accuracy and stability, and realizes non-destructive, intelligent and efficient meat quality detection.

The invention provides a Jinhua pork quality detection device and method, and relates to the technical field of meat quality detection, the Jinhua pork quality detection device comprises a box body, and a refrigeration chamber, a normal temperature chamber, a pH chamber, a water-holding chamber and a recovery chamber are arranged in the box body; the conveyor is in transmission connection with a plurality of clamping seats; the docking mechanism is arranged in the normal-temperature chamber and is in transmission connection with a plurality of meat sample plates I; the transfer mechanism is arranged in the refrigeration chamber and is in transmission connection with a plurality of meat sample plates II; the pH value detection mechanism is arranged in the pH chamber; the water-holding capacity detection mechanism is arranged in the water-holding capacity chamber; the dismounting mechanism is arranged in the recovery chamber; and the controller is arranged on the box body. According to the Jinhua pork quality detection device, automatic control is carried out through the controller, a detector only needs to prepare a cubic meat sample, then sets the detection time and the unfreezing time based on the slaughter time, and can obtain the detection results under the normal temperature condition and the refrigeration condition after the detection period is ended, so that automatic detection on the Jinhua pork quality is realized.