46 results about "Meat sample" patented technology

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 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.

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.

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 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 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.

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 application provides a yak meat intramuscular fat content prediction method and system based on near-infrared spectroscopy, relates to the technical field of data analysis, and comprises the following steps: acquiring the original near-infrared spectroscopy curve of multiple-source yak meat samples and the corresponding intramuscular fat content standard value. Secondly, deep feature extraction is performed on the spectrum through a wavelet scattering network to obtain multi-level scattering feature representation with stable deformation. Then, the pasture and part metadata of the samples are fused to construct a hypergraph structure representing the complex high-order correlation between the samples. Then, a heat diffusion model is established on the hypergraph, and the known fat content is used as a heat source for collaborative diffusion to obtain stable state information values fused with topological information. Finally, a prediction model is constructed by combining the multi-level features and the stable state information, so that the intramuscular fat content of new samples can be quickly and non-destructively predicted. The application improves the accuracy and efficiency of the fat content prediction of multiple-source heterogeneous yak meat samples.

The invention provides an SNP (Single Nucleotide Polymorphism) molecular marker remarkably related to the content of a chicken flavor substance (E, E)-2, 4-decadienal and a breeding application method. The SNP molecular marker is rs316165567 and contains nucleotide sequences with C / A polymorphism at 2nd, 519th and 798bp positions on a chicken chromosome 14, and when the genotype of the site is AA, the content of (E, E)-2, 4-decadienal of a corresponding chicken sample is high. According to the established molecular assisted breeding technology, the flavor quality character of the high-quality broiler chicken is selected in an early stage by determining the genotype of the SNP site of the chicken to be detected, the content of the chicken breast muscle (E, E)-2, 4-decadienal can be increased, and the molecular assisted breeding technology has great industrial application value and economic and scientific research value.

The invention relates to the technical field of image processing, in particular to a meat product grading system and method based on machine vision, and the system comprises an image collection module which is used for collecting a surface image of a meat product to be detected through an image sensor; the image processing module comprises a preprocessing unit which is used for preprocessing the surface image of the meat product to be detected so as to output the visual features of the meat product; the meat product grading module comprises a feature statistical unit used for performing statistical analysis on the meat product visual features to obtain meat product grading reference standards; the filtering adjusting module is used for determining the filtering color standard deviation in the preprocessing process according to the meat grading error rate; the light reflection identification adjusting module is used for determining a highlight discrimination threshold value of a surface image light reflection area mask according to the texture missing rate of the surface image; and the front-end gain adjusting module is used for determining the analog front-end gain multiple in the surface image acquisition process according to the feature preserving rate of the surface image. According to the method, the meat grading accuracy is improved.

The invention provides a yak meat intramuscular fat content prediction method and system based on a near infrared spectrum, and relates to the technical field of data analysis, and the method comprises the steps: obtaining an original near infrared spectrum curve of a multi-source yak meat sample and a corresponding intramuscular fat content standard value; secondly, deep feature extraction is carried out on the spectrum through a wavelet scattering network, and multi-level scattering feature representation with deformation stability is obtained; thirdly, fusing the pasture metadata and the part metadata of the samples, and constructing a hypergraph structure representing complex high-order correlation among the samples; then, a thermal diffusion model is established on the hypergraph, the known fat content is used as a heat source for collaborative diffusion, and a steady-state information value fused with topological information is obtained; and finally, constructing a prediction model in combination with the multi-level features and the steady-state information, and realizing rapid and lossless prediction of the intramuscular fat content of a new sample. According to the method, the accuracy and efficiency of predicting the fat content of the multi-source heterogeneous yak meat sample are improved.

This utility model relates to the field of meat product testing technology, specifically to a heavy metal detection device for fresh meat. It includes a digestion tank, a lid fixedly installed on the top of the digestion tank, a pulverizing component fixedly installed at the front end of the lid, a liquid addition pipe fixedly connected to the top of the lid and to the left of the pulverizing component, a stirring component installed inside the lid, and a collection box fixedly installed at the bottom of the digestion tank. The stirring component includes a drive housing fixedly installed in the middle of the top of the digestion tank, a stirring shaft rotatably connected to the inside of the lid, and a transmission box installed outside the stirring shaft, with the stirring shaft rotatably connected to the transmission box. This utility model, through its design, improves the mixing effect, resulting in more uniform solid-liquid contact and ensuring the uniformity of meat sample size. The pulverized meat sample can fully contact the digestion liquid, shortening the reaction time and thus improving the digestion efficiency.

The utility model relates to the technical field of beef sample detection, and discloses a yak meat sample detection device which comprises detection equipment, a display screen is arranged on the outer wall of the detection equipment, an adjusting knob is movably connected to the outer wall of the detection equipment, a lifting button is arranged on the outer wall of the detection equipment, and the lifting button is movably connected with the display screen. The top of the detection equipment is movably connected with a sealing cover, an electric telescopic machine is installed in an inner cavity of the detection equipment, a power output shaft of the electric telescopic machine is connected with a detection table, a loader is placed at the top of the detection table, a transparent cover is placed on the outer wall of the loader, and a temperature cavity is formed in the inner cavity of the detection equipment. According to the device for detecting the yak meat sample, the heating pipe on the device is matched with an adjusting knob, a display screen and a camera module for use, so that the device can completely record the change of the sample and the freshness of the meat at different temperatures and time.

The invention belongs to the technical field of heterogeneous chicken breast quality detection, and provides a chicken breast fibrosis degree online detection method and system in order to adapt to industrial production line low-cost and large-batch real-time detection of chicken breast samples. The established graph-spectrum coupling chicken breast fibrosis degree discrimination model accurately classifies lignified chicken breast, Italian meat and normal chicken breast, meets the requirements of low complexity and high robustness, and realizes real-time detection on low-computing-power equipment.

This invention discloses a pH colorimetric membrane for indicating meat freshness, obtained through the following steps: First, konjac glucomannan and polyvinyl alcohol are dissolved separately in distilled water and heated and stirred until dissolved; then, the konjac glucomannan aqueous solution and the polyvinyl alcohol aqueous solution are mixed to obtain a film-forming solution; curcumin and alizarin are added to the film-forming solution, homogenized using a homogenizer, and then ultrasonically treated to remove air bubbles; the solution is poured into a plastic petri dish and dried in an incubator to obtain the pH colorimetric membrane. This invention uses a 3:1 mass ratio of curcumin and alizarin as colorants, resulting in stronger pH sensitivity and more obvious color changes. Furthermore, all raw materials used are derived from natural substances, are safe and non-toxic, and edible. No complex processing of meat samples is required, making the operation simple and low-cost. It has great application potential in meat freshness monitoring and intelligent packaging, and can be applied to the freshness monitoring of various meat products.

The invention relates to the technical field of food detection, is used for solving the problems that existing manual grading is limited by subjective factors, evaluation standards are inconsistent, repeatability is poor and efficiency is low, and particularly discloses a beef pattern grade prediction analysis method based on texture map extraction. The method comprises the following steps: acquiring surface texture spectral information of a beef sample through hyperspectral imaging, introducing a multi-angle scanning and gray-level co-occurrence matrix construction technology, identifying the uniformity and contrast ratio of the texture of a muscle region from multiple angles, constructing texture morphological characteristics with higher discrimination, and determining the texture morphological characteristics of the beef sample. According to the method, automatic identification of pattern grades and grade interval delimitation are realized, and cross verification is completed through a standard nutritional quality index and edible quality index two-dimensional detection result. And the precision and efficiency of beef pattern grade prediction are obviously improved.

The invention relates to the technical field of processing of fresh meat and animal products, in particular to a finite element-based ultrasonic rolling, kneading and pickling beef brine mass transfer modeling method and application, which comprises the following steps: measuring the content change of salt and moisture in a beef sample under different ultrasonic power conditions, and combining with a Fick second law diffusion model, so as to determine the salt content and moisture content of the beef sample; corresponding salt and water mass transfer coefficients are obtained; establishing a three-dimensional physical field model and a beef sample geometric model by utilizing finite element analysis software, and establishing a simulation model of salt and moisture diffusion; establishing a function relationship between different ultrasonic powers and mass transfer coefficients of salt and moisture; and finally, the two models are combined for use, so that the spatial and temporal distribution conditions of the salinity and the moisture under any ultrasonic power condition can be visually presented. The model method has the characteristics of convenience in operation and dynamic visualization, the permeation condition of the pickling liquid in the beef in the pickling process can be observed, and the development of an ultrasonic synergistic tumbling pickling technology is facilitated.

The invention discloses a meat freshness rapid detection device, and belongs to the technical field of food nondestructive detection. The device aims at solving the problems that existing detection equipment is poor in portability and difficult to use on site, the detection range is limited due to single excitation wavelength, and the detection process depends on manual operation and is insufficient in intelligence. According to the technical scheme, the device is characterized by comprising a sample placement area, an annular multi-wavelength excitation light source module, a spectrum acquisition module, a single-chip microcomputer module, a Bluetooth module and a power supply and discharge module which are integrated in a device shell; the external intelligent terminal is provided with detection analysis software, and the software controls the excitation of the LED lamp beads with specific wavelengths through the Bluetooth module, automatically identifies the type of the freshness indication label based on the collected spectral characteristics, and calls a corresponding prediction model to calculate the freshness index. The device is mainly used for carrying out rapid and portable on-site detection on meat samples with freshness indication labels.

This utility model provides a frozen meat sampling device, relating to the field of frozen meat testing. The device includes a support plate with a horizontally mounted support crossbar above it; a rotating screw vertically mounted on the support crossbar, penetrating the crossbar and capable of axial movement; a heating plate threadedly connected to the lower end of the rotating screw, equipped with a resistance wire for defrosting frozen meat; and a sampling blade threadedly connected to the rotating screw, having a cylindrical structure with evenly distributed teeth on its lower end face, capable of moving along the rotating screw towards the support crossbar. This utility model reduces the labor intensity of sampling and facilitates meat sample removal.

The invention discloses a preparation method and application of a molecularly imprinted polymer and aptamer double-recognition gold nanoparticle-laser induced graphene composite material modified electrode, and belongs to the technical field of flexible electrochemical sensors and kanamycin detection. According to the invention, a gold nanoparticle-laser-induced graphene composite material modified electrode is used as a base material, a kanamycin aptamer is fixed through a gold-sulfur bond by using gold nanoparticles on the surface of the base material, and a molecularly imprinted polymer layer is further modified; therefore, an electrochemical sensing electrode with a molecularly imprinted polymer and aptamer dual recognition interface is constructed, and the electrochemical sensing electrode is used as a high-performance sensitive element of a sensor and shows good analysis performance in actual fish meat sample kanamycin detection. The prepared modified electrode can be used for sensitively detecting KANA in a concentration range of 10.0 pmol / L-1. 0mmol / L, the detection limit is as low as 3.3 pmol / L, and the modified electrode is good in selectivity and stability.

The application discloses a method for detecting chicken breast with wood and white line symbiotic muscle defects by hyperspectral imaging, and comprises the following steps: acquiring wood meat samples and white line meat samples with different grade gradients; acquiring hyperspectral images of the samples; extracting image texture features; preprocessing spectral data; selecting characteristic wavelengths for the spectrum; measuring the physicochemical quality of the samples; taking the image texture features and the spectral data under the selected characteristic wavelengths as inputs, and taking quality index values as outputs, to establish a CNN model; collecting hyperspectral images of chicken breast with wood and white line symbiotic muscle defects, inputting the image texture features and the spectral information of each pixel point in the multispectral image under the characteristic wavelength points into the optimized CNN model, obtaining comprehensive quality index values of each pixel point, respectively assigning colors to each pixel point, and forming a classified visual image; and the model detection and the visual image can accurately analyze and represent the symbiotic state of the white line and the wood tissue.

The invention relates to the technical field of food detection, in particular to a food microorganism detection method which comprises the following steps: baking and sterilizing the outer surface of a sample; sampling a plurality of parts of the disinfected to-be-detected meat sample by using sampling equipment, cutting off a part of the top and the bottom of each sample, leaving a middle part, and marking and cryopreserving the samples at different parts; placing each sample into different culture media to be cultured for three days; the total number of bacterial colonies in different culture media is observed and recorded. The multiple material taking frames are arranged below the movable frame, the material distributing assemblies are arranged in the material taking frames, different parts of a sample are sampled firstly, then the tool rest is used for conducting secondary treatment on the taken sample, the top and the bottom are removed, manual material taking is replaced, the material distributing assemblies are disinfected and air-dried after material feeding is completed, and the material taking efficiency is improved. The detection precision is improved, and subsequent continuous detection is also facilitated.

The invention discloses a meat freshness evaluation method based on an SERS (Surface Enhanced Raman Scattering) substrate of an MOFs (Metal-Organic Frameworks) material and machine learning, a seed mediation method is adopted to synthesize a gold nano sea urchin (GNU), p-mercaptobenzoic acid (p-MBA) is modified on the surface of the gold nano sea urchin, and an MIL-101 shell is coated by a layer-by-layer growth method to form a GNU / p-MBA-coated MIL-101 core-shell structure substrate. The embedded p-MBA molecule not only can be used as an internal standard, but also can be subjected to a derivatization reaction with volatile amines (VAs), so that high-sensitivity quantitative detection of the VAs is realized. The SERS spectrum of a meat sample is collected based on the sensing platform, and feature extraction and classification analysis are performed in combination with a machine learning algorithm, so that rapid, accurate and intelligent evaluation of the meat freshness is realized. The method has the advantages of high detection sensitivity, high selectivity, simplicity and convenience in operation, wide application range, nondestructive detection and the like, and is suitable for the fields of meat food quality monitoring and food safety detection.

The invention relates to the technical field of quality detection in the processing process of fresh meat and animal products, in particular to an ultrasonic synergistic tumbling and pickling beef salinity and moisture content imaging detection method. The method comprises the following steps: disclosing a correlation between the salt and moisture content and spectral data of the novel ultrasonic synergistic tumbled and pickled beef, and determining a quantitative prediction model of the salt and moisture in a beef sample; a contrast experiment verifies that the detection performance is good; and a dynamic permeation map of salt and moisture in the pickling process is successfully drawn by using a hyperspectral visualization technology. Experiments show that the method can realize rapid and nondestructive detection and visual characterization of salt and moisture content in the ultrasonic synergistic tumbling and pickling process, provides technical support for quality monitoring and process optimization in the ultrasonic synergistic tumbling and pickling process, and is suitable for online detection and intelligent control of the ultrasonic synergistic tumbling and pickling process.

The application discloses a method for thawing frozen channel catfish fillets by using magnetoelectric coupling, and comprises the following steps: placing the frozen channel catfish fillets into a sealed bag and placing the sealed bag into a magnetoelectric coupling freezing and refrigerating box; inserting a thermocouple temperature probe into the center of the meat sample to monitor the temperature in real time; and stopping the magnetoelectric coupling when the temperature reaches a predetermined temperature, thereby completing the thawing. The method can reduce the damage of the channel catfish during thawing, improve the quality stability of the thawed channel catfish, and has high thawing efficiency.

The invention relates to the technical field of food safety detection, in particular to a method for rapidly detecting daptomycin in meat food. The core of the method comprises the following steps: a chimeric probe composed of a daptomycin aptamer sequence, a DNA enzyme sequence and a flexible joint sequence is utilized, the probe generates conformational change in the presence of daptomycin and activates the cleavage activity of DNA enzyme, and then a quenching-reporter group labeled substrate chain is cleaved to generate a fluorescence signal; the method also optionally comprises the step of purifying and separating the reacted system by using a magnetic microsphere modified with a capture chain so as to reduce background interference. According to the method, high-specificity and high-sensitivity rapid quantitative detection on the daptomycin in the meat sample is realized under the condition that a complex instrument and a tedious process are not needed.