247 results about "Meat sample" patented technology

The invention discloses a method for identifying and predicting the freshness of meat. It includes the following steps: place the meat sample in a closed container, the sample gas is adsorbed to the sensor channel of the electronic nose through a built-in pump, and the gas reacts with the sensor to obtain a response signal; then sensory evaluation, volatility and Determination of basic nitrogen and detection of microbial content; feature selection and extraction of electronic nose response signals; establishment of relationships between electronic nose response signals and meat storage time, sensory scores, volatile basic nitrogen content, and microbial content using neural networks mathematical model. The invention can use the electronic nose to effectively identify and predict the freshness of meat without pretreatment, the analysis result is objective and accurate, the operation is simple, the cost is low, the method is fast and non-destructive, and has great economic value in the fields of meat processing, sales and detection.

The invention discloses a detection system for the total number of bacteria in livestock meat. The detection system comprises a light source apparatus emitting a spot light source to irradiate a livestock meat sample, a hyperspectral imaging apparatus used for acquiring spectral information of the livestock meat sample, an electric adjusting apparatus used for adjusting the position of the livestock meat sample and the position of the hyperspectral imaging apparatus, a controller apparatus used for controlling the motion of a motor of the electric adjusting apparatus, a sensor apparatus used for determining the position of the livestock meat sample and the position of the hyperspectral imaging apparatus and outputting position signals, a computer processor used for receiving the position signals, outputting processed position signals to the controller apparatus, analyzing hyperspectral information of the livestock meat sample and outputting analysis results and a dark box used for placement of the hyperspectral imaging apparatus. According to the invention, automatic real-time detection and real-time outputting of detection results are realized, experiment efficiency and accuracy are improved, obtained results are more reliable, and an operation method of the detection system is simple.

The invention discloses a chilled fresh meat quality non-destructive testing method based on a hyperspectral imaging technology. The method includes the steps of: 1) collecting and preparing a large number of chilled fresh meat samples, and collecting hyperspectral data of the chilled fresh meat samples by means of a hyperspectral imaging system; 2) according to national standard demand, testing physical and chemical reference values of to-be-tested quality indices of the chilled fresh meat samples by means of physical and chemical methods; and 3) with the acquired hyperspectral data and the physical and chemical reference values of the chilled fresh meat samples, establishing a hyperspectral prediction module of the to-be-tested quality indices of the chilled fresh meat by means of data processing methods such as machine learning, chemometrics and the like. When the method is applied to detection of content of TVB-N in beef, abnormal samples of chilled fresh beef are rejected through a MCS method, and then chilled fresh beef sample sets are divided through a CG algorithm; a CARS algorithm is employed to establish a PLSR model by optimally selecting a characteristic wave band of the content of TVB-N in the beef. The model has excellent prediction function.

The invention discloses a method for rapidly measuring the content of sodium chloride in salted meat. The method comprises the following steps: (1) with multiple salted meat products added with sodium chloride of different contents as correction samples, acquiring a near-infrared hyperspectral image of the correction samples so as to obtain a spectral reflectance value of the correction samples; establishing a quantitative relation between the spectral reflectance value of the correction samples under hyperspectral characteristic wavelength and the standard sodium chloride content of the correction samples through a multiplicative correction algorithm, and obtaining a salted meat sodium chloride content correction model; and (2) acquiring a near-infrared hyperspectral image of a to-be-measured salted meat sample so as to obtain a spectral reflectance value of the to-be-measured salted meat sample, and inputting the spectral reflectance value of the to-be-measured salted meat sample under the hyperspectral characteristic wavelength into the salted meat sodium chloride content correction model, so as to obtain the content of the sodium chloride in the to-be-measured salted meat sample. Compared with the prior art, the method has the advantages of zero damage, convenience in operation and rapidness.

The invention discloses a nondestructive detection method of the total number of bacteria in livestock meat, which comprises the following steps: using a high spectral imaging system to obtain a high spectral scattering image of a livestock meat sample to be detected; using the Lorentz function to fit the scattering features to obtain Lorentz parameters, and using the arithmetic product of the parameters as spectral data; using a stepwise regression method for selecting the optimum wavelength combination; and using the Lorentz parameters at the optimum wavelength part to establish a multivariant linear predict model which can be used for judging the total number of bacteria in the livestock meat. The invention has the advantages of high speed and nondestructive effect, light within the visible-near infrared spectral wavelength range (400 to 1100 nm) is used as a light source for irradiating the livestock meat sample, the scattering spectral information on the surface of the livestock meat sample is analyzed, and the method can be used as the nondestructive detection method of the total number of the bacteria in the livestock meat. After necessary modification, the method of the invention can also be used as a novel method to be applied to the nondestructive detection fields of internal components such as moisture content, protein content, fat content and the like in the livestock meat.

The invention relates to a RT-PCR based method for determining specific meats in mixed meat products, especially to a method for determining the component content of pork. The invention provides real time fluorescence PCR porcine specific oligonucleotide primers and probe for determining the component content of pork in mixed meat products as well as vertebrate general oligonucleotide primers and probe. Furthermore, the invention also provides a detection kit containing the above porcine specific primers and probes as well as the vertebrate general primers and probe. The method provided by the invention can be adopted to simply, rapidly and accurately determine the porcine-derived DNA content in raw meat or a cooked sample. Based on the correlation between a porcine specific primer system and a general primer system amplification curve, the method provided by the invention has a high accuracy and an anti-interference capability. In addition, the invention has such a strong portability that the component contents of other species in the mixed meat sample can be determined by replacing the specific primer system.

The invention provides a method for determining multiple kinds of animal origin meat based on the liquid chromatographic-tandem mass spectrometric technology. The method includes the steps of pretreating samples, screening multiple standard meat sample feature polypeptides, and detecting feature polypeptides in meat samples to be detected through the liquid chromatographic-tandem mass spectrometric technology and the like. Components of the multiple kinds of animal origin meat can be identified by adopting the method, the scanning function of liquid chromatography-tandem mass spectrometry is brought into full play in the technology, the selected ion monitoring mode is monitored to collect signals in real time, second-level daughter ion intensity triggering is used, corresponding parent ion second-level fragmentation full-scanning spectrograms are collected to obtain a more exact qualitative information function, interference of a complex matrix is avoided, and the false positive possibility is reduced. In addition, the method is simple in pretreatment and facilitates operation on samples in batches.

The invention provides a raw fresh meat non-destructive inspection device which is characterized by comprising a light source, a light source controller, a filter, a charge coupled device (CCD) industrial camera, a singlechip, a power supply converter, a shading cover and a protecting cover, wherein the protecting cover is positioned above the shading cover; the light source controller, the filter, the CCD industrial camera, a transitional table, the singlechip and a power supply controller are fixed in the protecting cover; the light source is fixed above the shading cover; a lens of the industrial camera is positioned right above the light source; the filter is positioned on the lens of the industrial camera; and a meat sample is positioned in the shading cover. According to the technical scheme, the CCD camera acquires an image of a beef or port sample or a body detection part, so that contactless real-time detection is realized, and grade judgment for main quality of raw fresh meat is realized. Damage to the meat sample is avoided; the detection device is low in cost and precise and stable in detection performance.

The invention relates to a method for quickly measuring the total quantity of livestock meat bacteria. A hyperspectral imaging technology is used for acquiring hyperspectral imaging data of a livestock sample, and the data can reflect the spectral information of internal features of livestock meat and the image information of the appearance features of livestock meat simultaneously. The method comprises the following steps of: performing black and white marking on original data, and extracting a spectral feature variable representing the internal information of livestock and a color and texture feature variable representing the external information of the livestock meat; fusing these feature variables; establishing a nonlinear predication model for the total quantity of livestock meat bacteria in combination with an international method; and predicting the total quantity of bacteria in a livestock meat sample by using the model. According to the method, rapid quantitative detection of the total quantity of livestock meat bacteria is realized on the premise of not damaging the livestock meat sample, and bases are laid for the raising the intelligent detection management level of livestock meat products in China and ensuring the quality safety of the livestock meat products.

The invention discloses a non-destructive detection method for freshness of livestock meat. The method comprises the following steps of: S10, acquiring a multispectral image of a livestock meat sample to be detected, and measuring a freshness evaluation index of the livestock meat sample to be detected; S20, extracting a scattering curve of the multispectral image, and calculating a pixel gray average value, a reflection strength ratio and the numerical integration of the scattering curve of the multispectral image; S30, establishing a multiple linear regression prediction model of the freshness evaluation index of the livestock meat sample to be detected; S40, establishing a discrimination model of the freshness of the livestock meat sample to be detected; and S50, acquiring a prediction value of the freshness evaluation index of the livestock meat sample to be detected by utilizing the prediction model, inputting the prediction value into the discrimination model of the freshness of the livestock meat, and acquiring a detection result. According to the disclosed technical scheme, non-destructive detection of the livestock meat is realized, the modeling difficulty and detection cost are reduced, the detection speed is improved, and actual popularization of the technical scheme is promoted.

The invention discloses a method for rapidly and nondestructively detecting the colony count of chilled meat, which comprises the following steps of: S1. obtaining a chilled meat sample; S2. collecting a high-spectrum image of the sample; S3. calculating the reference value of the colony count per unit area of the sample; S4. subjecting the high-spectrum image to space decomposition so as to obtain spatial diffusion information of the sample at different wavelengths, wherein the Lorentz parameters of the component information of the representative sample is extracted by utilizing the spatial diffusion information according to a nonlinear regression method; and S5. obtaining the relationship between the Lorentz parameters and the reference value in a certain wavelength range so as to establish a mathematical model of the Lorentz parameters and the colony count of the sample according to a multivariate linear regression method, and predicting the colony count of the chilled meat sample by utilizing the model. By means of the method disclosed by the invention, rapid and nondestructive detection of the colony count of a meat product can be realized.

The invention discloses a thiamphenicol molecularly imprinted electrochemical sensor and a preparation method and application thereof. A porous graphene-molybdenum disulfide nano flower-shaped compound is prepared through a hydrothermal one-step method, and the compound is dropped on the surface of an L-type glassy carbon electrode; aminated multi-walled carbon nanotubes and porous Pt-Pd nanoparticles are dispersed so that the imprinting surface area of the electrode can be increased and stability of a modification interface can be enhanced, and accordingly a three-dimensional porous imprinting substrate is obtained; thiamphenicol serves as template molecules, 1,2-diaminobenzene serves as functional monomers, and an imprinted membrane is prepared through cyclic voltammetry; ascorbic acid serves as a photoelectric chemical probe, and the electrochemical sensor for detecting thiamphenicol is built. The sensor has good thiamphenicol responsiveness, the linear range of the sensor is 1.0*10<-9>-3.5*<-6> mol L<-1>, and the detection lower limit is 5.0*10<-9> mol L<-1>. The sensor can be used for detecting thiamphenicol in meat samples and feed samples.

The invention discloses a determination method for texture properties of a meat product. The method comprises the following steps: 1) preparing meat samples from a meat product and detecting the meat samples with a texture analyzer; 2) carrying out curve fitting by using MATLAB so as to obtain a stress curve of the samples, calculating a function of curvature of each point on the stress curve, carrying out fitting on the calculated curvature so as to obtain a curvature curve and screening out indexes consisting of X1, X2, X2-X1 and Y2 on the curves; and 3) reflecting hardness, cohesiveness, gumminess and chewiness of the meat product by using the indexes consisting of X1, X2, X2-X1 and Y2, wherein the greater the indexes are, the better the hardness, the cohesiveness, the gumminess and the chewiness are. According to the invention, the effective indexes used for determination of continuous stress are screened out, which is beneficial for improvement and standardization of texture determination of meat products, and the problem of lacking of effective indexes in texture determination of meat products under the condition of continuous stress is overcome.

The invention discloses an ELISA (enzyme-linked immune sorbent assay) analytical method for directly detecting furaltadone metabolite AMOZ (3-amino-5-morpholinomethyl-2-oxazolidinone) content in food, which is characterized in that three different AMOZ hapten derivatives are synthesized and crosslinked with carrier protein to synthesize three immunogens and envelope antigens so as to prepare a monoclonal antibody by the hybridoma monoclonal antibody preparation technique. The AMOZ in a sample can be directly detected without derivatization steps by the setup ELISA, and the prepared monoclonal antibody is not in cross reaction with other nitrofurans and metabolite thereof and eight antibiotics, so that the specificity of the antibody is high. AMOZ of different amounts is added into four meat samples including fish, shrimp, chicken and pork liver, the ELISA is used for direct determination, the standard recovery rate ranges from 72.6% to 102.7%, the relative standard deviation is 6.1-17.7%, seven standard samples are detected by HPLC (high performance liquid chromatography) and ELISA simultaneously, determination results are compared, the regression curve is Y=0.9742X-7.6001, and the linearly dependent coefficient is 0.9889, so that the HPLC and the ELISA have high relativity.

The invention relates to the technical field of food safety inspection, and particularly relates to a system and a method for detecting and removing deteriorated meat online. According to the system, a meat sample to be detected is conveyed by a conveying belt, a spectrum acquisition unit is connected to a spectrometer, and a lifting device drives the spectrum acquisition unit to lift and move; a control box is in communication connection with a first sensor, a second sensor and a third sensor respectively, and the first sensor and the second sensor are arranged at an interval along the moving direction of the conveying belt and used for detecting position information of the meat sample to be detected; the third sensor is positioned above the first sensor and used for detecting the height of the meat sample to be detected; meanwhile, a removing device is correspondingly arranged on one side of the conveying belt and used for removing deteriorated meat from the meat sample to be detected. The system can be used for achieving spectrum detection and removal of deteriorated meat on a meat production line, so as to effectively improve the streamline automatic level.

The invention discloses a hyperspectral detection method of color and texture changes in preserved meat salting process, and relates to the technical field of quality detection during animal products processing. The method comprises the following steps: scanning to obtain three-dimensional data block information of preserved meat in different salting processing stages through a hyperspectral imaging system; calculating an average spectrum of a Region of Interest (ROI) of a preserved meat sample, and screening a characteristic wavelength; establishing a partial least squares regression model of color and texture of the salted preserved meat based on a characteristic reflection spectrum and image texture characteristics of the sample; and drawing a color and texture distribution map of the preserved meat in different processing stages in the salting process by forecasting color values L *,a *and b * corresponding to each pixel point and texture indexes (hardness and a viscoelasticity value) in the spectral image. Therefore, intelligent monitoring of the quality in the salted preserved meat processing is realized, and the quality safety of meat products can be precisely controlled.

The present invention discloses a transferable calculation meat quality near infrared detection method and device, which are capable of non-destructively and rapidly detecting meat quality. The device comprises a micro-spectrometer, a mobile terminal and a server; the mobile terminal is connected with the micro-spectrometer and the server, and is used for collecting spectral data of a meat sample, and determining the establishing position of a quality prediction model, the quality prediction model can be established according to the determined establishing position of the quality prediction model on the basis of meat sample spectral data stored in advance in the mobile terminal and corresponding quality data, the meat sample spectral data, which is collected by the mobile terminal, is used as input of the quality prediction model, the output of the quality prediction model is determined as the quality data corresponding to the collected meat sample spectral data, and the establishing position includes the mobile terminal or the server.

The invention provides a method for rapidly identifying adulterated meat. The method comprises the following steps: 1, respectively preparing a pure meat sample, an adulterated meat sample and an unknown meat sample to be measured; 2, respectively acquiring the near infrared diffuse reflection spectra of the pure meat sample and the adulterated meat sample, continuously each of the above samples multiple times, and respectively taking the average value of obtained data as an original spectrum; 3, carrying out modeling wave band optimization selection on the original spectrum, and carrying out spectrum pretreatment on selected modeling wave bands; 4, extracting spectrum characteristic information by adopting a main component analysis process; 5, establishing an adulterated meat identifying model by adopting a discriminant analysis process; and 6, calculating the mahalanobis distance of each of the pure meat sample and the adulterated meat sample to determine the type of each of the pure meat sample and the adulterated meat sample; and 7, utilizing the adulterated meat identifying model to identify and analyze the sample to be measured, and calculating the mahalanobis distance of the sample to be measured in order to determine the type of the sample to be measured. The method can realize the rapid, accurate and stable qualitative classification discrimination of unknown meat.

The invention provides a method for detecting fish parvalbumin through liquid chromatography tandem mass spectrometry. The method comprises the following steps: step 1: choosing a characteristic peptide fragment; step 2: making a standard curve: taking the concentration value of a quantitative peptide fragment standard product as the x-coordinate and a quantitative daughter ion peak area as the y-coordinate to draw the standard curve, and obtaining an equation; step 3: processing and implementing enzymolysis on a to-be-detected fish meat sample to obtain a liquid supernatant, implementing HPLC-MRM-MS/MS detection on the liquid supernatant, obtaining the daughter ion peak area of the quantitative peptide fragment in the fish meat sample, resolving the concentration of the quantitative peptide fragment in the sample, and further obtaining the concentration of the parvalbumin in the sample. The invention aims at establishing a liquid chromatography tandem mass spectrometry method, and themethod has the advantages of accuracy, precision, sensitivity and the like.

The present invention discloses a method for rapidly identifying meat with different animal sources. The method is characterized by comprising: (1) placing a meat sample at a room temperature, and adopting a near-infrared spectrometer diffuse reflection manner to sample a spectrum of the meat sample after the temperature is balanced; (2) selecting spectrum data of the optimal modeling wave band, and carrying out a pre-treatment on the selected spectrum data; (3) adopting a main component analysis method to extract the spectrum feature information; (4) adopting a discrimination analysis method to establish a qualitative recognition model; and (5) calculating the mahalanobis distance of the meat sample, and judging the classification of the meat sample according to the mahalanobis distance value. According to the present invention, the disadvantages of complex operation, long detection time, high chemical reagent consumption and high cost of the existing identification method are overcome; and the method has advantages of rapidness, no loss, accuracy, stability, simple identification process, and no requirement of professionals, and is easy to promote and apply in the food industry and the food law enforcement and supervision department.

The invention discloses a device and a method for detecting freshness of beef. The method comprises the following steps: firstly, selecting three types of carrier gases for detecting volatile gas generated by freshly-killed beef; secondly, according to the fitting precision of the detection model of each carrier gas, judging the concentration of the volatile gas, wherein when the R value of only one of the three carrier gases is less than 0.9, the concentration of the volatile gas is the most suitable and the detection accuracy can be ensured; thirdly, selecting a beef freshness pre-detection model; fourthly, detecting beef W to be detected by a sensor array; fifthly, obtaining the signal-to-noise ratio maximum SNRW of the beef W; sixthly, computing a storage day value t of the beef W by a computer according to the beef freshness pre-detection model; and finally, judging whether the freshness of a beef sample is unqualified or qualified by a computer. The device and the method have the characteristics of accurate, objective and rapid detection and capability of providing reliable data support for preparing food using beef with qualified freshness.

The invention discloses a THz spectral analysis-based rapid nondestructive testing model for a K value of fresh meat. The model comprises the modeling steps of (1) construction of a multi-layer back-propagation neural network BP-ANN, namely sampling a THz spectrum of a fresh meat sample by adopting THz attenuated total reflection ATR detection mode and treating sample spectrum data and regarding the BP-ANN as a nonlinear function, wherein an input value and a predicted value of the BP-ANN are an independent variable and a dependent variable of the nonlinear function separately and the BP-ANN expresses the function mapping relationship from the independent variable to the dependent variable; and (2) training which comprises network initialization, hidden layer output calculation, output layer output calculation, error calculation, weight updating, threshold updating, and judging whether algorithm iteration is completed or not according to the iteration times and the final iteration error. A relationship model between the THz spectrum data and the freshness K value of the fresh meat is constructed through exploring the THz spectrum characteristic of the freshness of the fresh meat.

The invention relates to a yak meat production place tracing method based on multiple elements and stable isotopes. The method comprises the steps of (1), collecting a yak meat sample and carrying outpreprocessing to obtain a defatted yak meat sample; (2), detecting a stable carbon isotope abundance ratio, a stable hydrogen isotope abundance ratio, and a mineral element Ti content in the defattedyak meat sample; (3), carrying out computing to obtain a stable carbon isotope ratio delta<13>C%o and a stable hydrogen isotope ratio delta<2>H%o according to the stable carbon isotope abundance ratio and the stable hydrogen isotope abundance ratio; and (4), substituting the stable carbon isotope ratio delta<13>C%o, the stable hydrogen isotope ratio delta<2>H%o and the mineral element Ti contentinto a judgment model, and judging a production place of the yak meat sample according to a computing result. The method is simple and convenient and is high in operability. Influence of external environment factors on yak meat production place tracing accuracy is effectively reduced. The yak meat production place tracing accuracy can be improved. The method is characterized by speediness, economyand practicality.

The invention provides a method for extracting and analyzing beta-agonists clenbuterol by adopting a DPX (dispersive pipette extraction) tip type dispersive solid-phase microextraction column and relates to the DPX tip type dispersive solid-phase microextraction column (DPX tips <TM>). The method can be matched with various manual and automatic pipetting systems, meat sample treatment and extraction can be completed rapidly and efficiently, and defects that traditional sample treatment is time-consuming and labor-consuming, instrument loss is increased and the like can be perfectly overcome. The simple and fast solid-phase extraction method is combined with HPLC-MS (high performance liquid chromatography-mass spectrometer) analysis, so that purification of 96-384 samples can be finished simultaneously within 10 min, and rapid, qualitative and quantitative high-flux determination for multiple kinds of beta-agonists clenbuterol in animal derived food can be realized.

The invention relates to a method for evaluating the fresh water fish meat quality. The method is characterized by comprising the following steps that 1, the whiteness, the tenderness, the water binding capacity, the trimethylamine content, the freshness and the thiobarbituric acid value of a to-be-tested fresh water fish meat sample are tested separately; 2, the determined values are processed byusing a standard deviation standardization method, and the standardized values are obtained, wherein the standardized whiteness value is denoted as Zx1, the standardized tenderness value is denoted as Zx2, the standardized water binding capacity value is denoted as Zx3, the standardized trimethylamine content value is denoted as Zx4, the standardized freshness value is denoted as Zx5, and the standardized thiobarbituric acid value is denoted as Zx6; 3, the values in the step 2 are substituted into the formula y=-0.095*Zx1+0.168*Zx2+0.34*Zx3+0.342*Zx4+0.313*Zx5+0.328*Zx6, wherein y is the quality evaluation result of fresh water fish meat; 4, the quality of the fresh fish meat is judged through the obtained y, wherein when y is larger than or equal to 1, the quality of the fresh fish meatis extremely poor; when y is larger than -1 and smaller than 1, the quality of the fish meat is general, and when y is smaller than or equal to -1, the quality of the fish meat is extremely good. Themethod is quick and accurate.

The invention discloses a meat adulteration identification method and apparatus applied to origin traceability. The method comprises the following steps: S1: respectively preparing a plurality of different meat sample sets, wherein each sample set comprises a plurality of detection samples; S2: respectively collecting an original spectrum of each detection sample in S1; S3: calculating a mahalanobis distance of each detection sample and a mahalanobis distance threshold value of each meat, obtaining a singular point sample according to the mahalanobis distance of each detection sample and the mahalanobis distance threshold value of the corresponding meat, removing the singular point sample from the sample set of each meat, and obtaining corresponding residual sample sets; S4: preprocessing the original spectrum of all detection samples in the plurality of residual sample sets; and S5: randomly classifying all detection samples in the plurality of residual sample sets into a correction set and a detection set, and establishing an identification model for the detection set by virtue of a modeling method. By adopting the method and apparatus, the adulteration identification of different meats can be realized.