69 results about "Milk sample" patented technology

The invention relates to the technical field of food microorganism detection, and discloses a real-time detection method for microbial pollution of normal-temperature pure goat milk. The method comprises the following steps: dividing a target goat milk sample into a plurality of detection units representing independent production batches, collecting microbiological detection data, physicochemical property data and spectral characteristic data of each unit, and integrating to form a multi-source detection data set; and constructing a pollution risk scoring index and a quality stability evaluation index based on the data set, and dynamically generating an initial pollution risk value through an early warning trigger mechanism and model operation. And dynamically correcting the initial pollution risk value according to the time sequence correlation of the adjacent detection units to generate a corrected risk value. And performing sorting processing on the corrected risk values, creating a risk level priority form, and connecting a real-time monitoring platform to perform visual display and alarm output. According to the method, multi-source data fusion analysis is realized, high-risk batches can be identified in time, and an efficient means is provided for quality control of normal-temperature pure goat milk.

The invention discloses an enzyme-linked immuno sorbent assay (ELISA) technology-based detection optimization method for A2 protein content in milk, and relates to the technical field of protein content detection.The method comprises the following steps: collecting a milk matrix interference detection data set, and establishing a milk matrix interference corrector; generating an ELISA dynamic detection module; preparing a milk sample to be detected, and controlling the ELISA dynamic detection module to perform protein optimization detection on the milk sample to be detected to obtain milk absorbance detection data; and establishing an absorbance-concentration standard curve, and determining the detection result of the A2 protein content of the milk. The technical problems that in the prior art, when the A2 protein in milk is detected through ELISA, the detection accuracy and reliability are poor due to the fact that the A2 protein in the milk is easily interfered by components and the adaptability to different types of milk is insufficient are solved, the A2 protein content in the milk can be detected more accurately, the anti-interference capacity is higher, and the detection accuracy and reliability are improved. The technical effect of improving the accuracy and the reliability of the ELISA technology for detecting the A2 protein of the milk is achieved.

The invention discloses an MIP / CoNiFe-PBA / RGO / GCE working electrode as well as a preparation method and application thereof, and belongs to the technical field of food safety detection.The prepared CoNiFe-PBA-based self-reporting type molecularly imprinted electrochemical sensor has the following outstanding performances when detecting BPA: the detection limit is as low as 0.18 nM (S / N = 3), the linear range is 1.0-500.0 nM, and in a milk sample labeling recovery experiment, the detection limit is as low as 0.18 nM (S / N = 3), and the detection limit is as low as 0.18 nM (S / N = 3). The recovery rate is 97.18 to 102.96 percent, and the relative standard deviation is 1t; the current retention rate is 93.81% (n is equal to 3) for 100 nM BPA detection in a continuous 15-day water immersion test (0.1 M PBS, pH 7.4) under the room temperature, and the signal attenuation is 8.6% after 10 times of continuous use, and the current retention rate is 93.81% (n is equal to 3) for 100 nM BPA detection.

The application discloses a kind of based on GC-IMS pure milk flavor sensory digitalization fast evaluation method, belong to food analysis and evaluation technical field.The pure milk sample to be measured is detected by headspace sampling using GC-IMS, and a fingerprint spectrum is obtained.The fingerprint spectrum data or characteristic volatile component data is input into the OPLS-DA model, and the preference degree of pure milk is evaluated according to the clustering result.The construction method of OPLS-DA model is as follows: different pure milk samples are selected, and CATA sensory evaluation method is used for sensory evaluation of pure milk samples.Different pure milk samples are detected by headspace sampling using GC-IMS, and a fingerprint spectrum is obtained.Partial least squares-discriminant analysis method is used for regression modeling using fingerprint spectrum data or characteristic volatile component data to obtain OPLS-DA model.The application uses GC-IMS to digitally and quickly evaluate the flavor of pure milk, which has high sensitivity, does not require sample enrichment and concentration, saves detection time, and avoids tedious pretreatment process.

A sampling device for taking a representative milk sample from a milking device. The milking device includes a milking means, a milk jar, a milk hose, a milk tank, a milk line, a milk pump for pumping the milk, a milk meter for determining the quantity of milk milked, and a control unit. The sampling device includes a sample line with an input connection to the milk jar, the milk pump or the milk line, an output to a sample collection receptacle, and a control device controllable by the control unit based on the quantity of milk determined by the milk meter in order to direct, during pumping, a sample quantity of milk through the sample line. The control unit knows how much milk must be pumped and can take precisely enough milk samples distributed over the pumping operation such that an accurate representative sample is obtained.

The invention discloses a GC-IMS-based pure milk flavor sensory digitalization rapid evaluation method, and belongs to the technical field of food analysis and evaluation. The method comprises the following steps: detecting a pure milk sample to be detected by GC-IMS through headspace sampling to obtain a fingerprint spectrum, substituting fingerprint spectrum data or characteristic volatile component data into an OPLS-DA model, and evaluating the preference degree of the pure milk according to a clustering result; the construction method of the OPLS-DA model comprises the following steps: selecting different pure milk samples, and carrying out sensory evaluation on the pure milk samples by adopting a CATA sensory evaluation method; the method comprises the following steps: detecting different pure milk samples through headspace sampling by using GC-IMS to obtain a fingerprint spectrum, and performing regression modeling by using a partial least squares-discriminant analysis method by using fingerprint spectrum data or characteristic volatile component data to construct and obtain an OPLS-DA (Optical Partial Least Squares-Discriminant Analysis) model. According to the invention, GC-IMS is adopted to carry out digital rapid evaluation on the pure milk flavor sense organ, the sensitivity is extremely high, a sample does not need to be enriched and concentrated, the detection time is saved, and a tedious pretreatment process is avoided.

This utility model relates to the field of food testing equipment technology, and discloses a food testing box for walnut milk production with a scraping structure. The box includes a body, a liquid level window fixedly provided on the surface of the body, a liquid level gauge fixedly provided on one side of the liquid level window, a scraper slidably provided inside the body, a silicone ring engaging with the surface of the scraper, a buckle hinged to the top of the body, and a lid engaging with the top of the body. A retainer is fixedly provided on the surface of the lid to engage with the buckle. The box can store walnut milk samples, and the liquid level can be observed through the liquid level window and gauge. The lid can be engaged with the buckle and retainer, allowing the scraper to be positioned inside the box. The silicone ring seals the scraper within the box, facilitating easy transport of the box, preventing sample spillage, and preventing sample contamination. A support assembly provides support for the box.

A milking system (100) is designed to extract milk from an animal (101). The system (100) includes several components for efficient milk sampling and biomarker detection. It is characterized by a feed cassette (140) holding multiple vials (150), at least one of which is prepared for biomarker detection. During milking, a milk sampler (300) transfers some milk into the selected vial (150). The system also has an animal identification device (116) for identifying the animal (101) and an information tagging device (370) for tagging the vials with relevant details. A controller (120) is connected to the identification device (116), the milk sampler (300), and the information tagging device (370). The system identifies the animal, determines whether biomarker detection is required, and, if necessary, signals the milk sampler to transfer milk into the appropriate vial and signals the information tagging device to tag the vial with the animal's identity. The system streamlines the process of collecting and analyzing milk samples.

A system for monitoring and controlling application of milk samples to lateral flow test sticks. The system includes a milk dosing assembly with a needle that moves between an application position contacting a test stick and a retracted position. A moveable structure holds and positions the dosing assembly, while a drive unit controls the movement. A controller determines and maintains proper spacing between the needle tip and test stick by comparing measured distances with predetermined values and making adjustments as needed. The system enables accurate and automated application of milk samples for biomarker testing while preventing sample cross-contamination and ensuring proper sample delivery to the test area.

A system and method for in-situ quantitative assessment of Bovine Mastitis (BM) in collected milk samples using optical imaging is disclosed. A bio-functionalized assay tray contains multiple wells, each having a gel with a specially prepared mixture of hemoglobin (Hb) and metal ions. At least one of the wells is filled with a reference milk sample which is characteristic of milk with no BM disease. Other wells are filled with collected milk samples. After waiting an interaction time, luminol and hydrogen peroxide solutions are added to the wells, causing chemiluminescent (CL) light emission. The intensity of CL light emitted by wells containing haptoglobin (Hp) is inhibited due to Hb-Hp binding. After waiting a CL light stabilization time, the tray is placed in a dark box, and a camera and image processor are used to analyze the CL light intensities. A calibration curve yields the Hp concentration in each well.

The invention discloses a mass spectrometric detection method for bisphenol A in milk through rotary evaporation pretreatment and multi-charge peak analysis. The mass spectrometric detection method comprises the following steps: step 1, carrying out rotary evaporation pretreatment on fresh milk; step 2, carrying out rotary evaporation treatment on the milk sample; 3, omics analysis of lipid, metabolites and protein is completed, and UHPLC-Q-Orbitrap HRMS strategy processing based on vDIA is achieved; and 4, analyzing the group database by adopting a multi-charge overlapping peak extraction algorithm and a graph neural network strategy to realize substance identification. The invention belongs to the technical field of mass spectrometry, and solves the problems that the detection error is large when microgram / L-level trace detection of bisphenol A in milk is carried out in the prior art, and false positive is easy to occur due to a wide mass window in the traditional extraction ion chromatography.

The invention discloses a method for detecting lactoferrin in milk based on a competition method test strip, which comprises the following steps: coupling heparin molecules with bovine serum albumin to obtain a heparin molecule-bovine serum albumin artificial antigen; modifying gold nanoparticles by using an artificial antigen to form a gold label I, and constructing a competition method test strip by matching with a gold label II modified by mouse IgG (Immunoglobulin G); a milk sample is subjected to centrifugal fat removal, pH adjustment and casein precipitation pretreatment and then dropwise added to the test strip, and the LF concentration is calculated through a T line gray value and a working curve. Detection can be completed within about 10-15 min, specificity is high (interference of impure protein is avoided), on-site rapid quantitative / semi-quantitative detection of LF in milk can be achieved, the antiviral activity of LF can be indirectly reflected through the binding strength of heparin and LF, the method is suitable for production quality inspection, dealer sampling inspection and consumer self-inspection, and the detection sensitivity reaches 1 microgram / mL.

The invention belongs to the field of biology, and discloses a PDCoV recombinant RBD protein and an IgA Elisa kit thereof, and the amino acid sequence of the recombinant RBD protein is as shown in SEQ ID NO. 1. The recombinant RBD protein is used for an indirect ELISA kit, can cover IgA response in the early stage of infection, can accurately recognize a PDCoV specific IgA antibody in a breast milk sample, and cannot cause false positive due to infection of other common pathogens in a pig herd; the indirect ELISA kit is good in stability (the intra-batch variation coefficient is 1.848%-6.062%, and the inter-batch variation coefficient is 4.504%-7.790%), the coincidence rate of the indirect ELISA kit and an immunofluorescence experiment reaches 93.26%, the repeatability and the coincidence rate are high, and the indirect ELISA kit has the advantages of simplicity and convenience in operation, short time consumption and large detection flux of an ELISA method, and is suitable for large-scale screening of clinical pig milk samples.

The invention provides a double qPCR (quantitative polymerase chain reaction) detection method capable of simultaneously detecting mycobacterium tuberculosis and mycobacterium paratuberculosis. An Rv3876 gene and an IS900 gene are selected as specific targets, a test result shows that the single qPCR detection sensitivity of mycobacterium tuberculosis and mycobacterium paratuberculosis is 1.35 * 10 < 3 > copies / microliter and 1.29 * 10 < 3 > copies / microliter and is improved by 10 times compared with a conventional PCR, a double qPCR detection method is established on the basis, the sensitivity of the double qPCR detection method is equivalent to that of single qPCR, and the specificity is good; in simulation of clinical milk sample detection, a sample boiling method is screened as an optimal method for extracting DNA of two pathogens, high specificity and sensitivity are achieved, interference of inhibitors in fresh milk can be effectively removed, detection stability is ensured, and the method is expected to be a powerful tool for rapid detection of mycobacterium tuberculosis and mycobacterium paratuberculosis in the fresh milk.

The application discloses a method for detecting ochratoxin A in milk based on a double-identification electrochemical sensor, and compared with other OTA detection methods, the sensor has a wider linear range (0-300nM) and a lower LOD (0.09nM) under optimal conditions; the sensor has high repeatability, stability and specificity, and the sensor has good feasibility in detection of different types of milk samples, and a good recovery rate of 95.4%-105.6% is obtained.

A milking system for sampling and analysing milk includes a milking device, a sampling device to extract a milk sample, and an analysis device for the sample. The analysis device includes a cassette with an analysis tape having a carrier layer with separate vertical flow analysis pads, a tape displacer, a sample provision device providing a droplet of the sample to a selected analysis pad, a sensor to sense a response in the analysis pad after provision of the sample, and a control unit. The analysis pads include a reagent pad with a reagent reacting with a predetermined compound in the sample, a priming pad with a priming agent to change a property of the sample that enhances the reaction, and a bonding layer between the reagent pad and the priming pad, and including a first and second adhesive layer, and a support layer therebetween.

The invention provides a multiplex digital PCR (Polymerase Chain Reaction) detection method for identifying and diagnosing Brucella bovis and Brucella mevis, i.e., on the basis of obtaining a set of primer probes capable of identifying Brucella and Brucella bovis and Brucella mevis through screening; the invention establishes a high-sensitivity liquid drop type digital PCR detection method capable of identifying zonal distribution Brucella and Brucella of cattle and sheep species. The method disclosed by the invention can be used for simultaneously carrying out quantitative detection on nucleic acids of the Brucella abortus and the Brucella melitensis, is good in repeatability and specificity, and in addition, the sensitivity is 10 times higher than that of a triple fluorescent quantitative PCR (Polymerase Chain Reaction) method. Clinical sample detection results show that the positive detection rate of the triple digital PCR detection method in environmental swabs, tissue samples, milk samples and abortion substances is higher than that of a triple qPCR method. The triple digital PCR detection method provided by the invention can be used for etiological diagnosis of cattle and sheep brucellosis, and has good sensitivity, specificity and repeatability.

A dispensing unit (110) for providing a milk mixture comprising milk and liquid to a milk analysis device (140). The dispensing unit (110) includes a first section (201) comprising a first fluid port (155), a first groove (121), a second fluid port (156), a second groove (122), a first fluid outlet (141), and a third groove (142). The first groove (121) extends from the first fluid port to a mixing chamber (120), and the second groove extends from the second fluid port to the mixing chamber. The third groove extends from the mixing chamber to the first fluid outlet. A second section (202) may be attached to the first section to form a first conduit by enclosing the first groove, a second conduit by enclosing the second groove, a third conduit by enclosing the third groove, and a closed mixing chamber by enclosing the mixing chamber.

The present invention related to a technique for determining the progesterone-associated physiological state of a lactating cow. The technique comprises determining at least one Milk Solid (MS)-related parameter in at least one milk sample from a lactating cow; and determining the progesterone-associated physiological state according to the Milk Solid (MS)-related parameter. Determining the progesterone-associated physiological state may comprise determining the progesterone level of the cow by correlating the MS-related parameter with calibrated data. The MS related parameter may comprise at least one of size, synthesis, composition of a MS, a pattern of progesterone concentration or direction of progesterone concentration, or at least one dielectric parameter of the MS.

The application discloses a buffalo milk adulteration identification method and system based on protein characteristic ratio and a Logistic discriminant model, and belongs to the technical field of dairy product quality and safety detection. The method is characterized in that the content of six key milk proteins in a milk sample is determined, three specific ratios of αs1-CN / α-LA, β-CN / β-LG and κ-CN / αs2-CN are calculated, a probability P is obtained by substituting the three specific ratios into a Logistic regression model P=1 / [1+exp(-(-1.4420-0.3264+1.8531-2.0471))], and whether the milk is buffalo milk is determined by comparing the probability P with a threshold value 0.67. The method has high identification accuracy and is suitable for rapid screening of dairy product quality.

The application discloses an A2 protein content detection optimization method in milk based on an ELISA technology, relates to the technical field of protein content detection, and comprises the following steps: collecting milk matrix interference detection data sets, establishing a milk matrix interference corrector, generating an ELISA dynamic detection module, preparing a milk sample to be detected, controlling the ELISA dynamic detection module to perform protein optimization detection on the milk sample to be detected, obtaining milk absorbance detection data, establishing an absorbance-concentration standard curve, and determining a milk A2 protein content detection result. The application solves the technical problem that, in the prior art, when the ELISA detects the A2 protein in milk, the detection is prone to component interference, and the adaptability to different types of milk is insufficient, resulting in poor detection accuracy and reliability. The application achieves more accurate detection of the A2 protein content in milk and stronger anti-interference capability, and improves the technical effect of the accuracy and reliability of the ELISA technology in detecting the A2 protein in milk.

The application belongs to the field of biology, discloses PDCoV recombinant RBD protein and IgA ELISA kit thereof, and the amino acid sequence of the recombinant RBD protein is shown as SEQ ID NO.1.The recombinant RBD protein is used for indirect ELISA kit, can cover early IgA response of infection, can accurately recognize PDCoV specific IgA antibody in breast milk sample, and will not cause false positive due to infection of other common pathogens in a pig herd; the indirect ELISA kit of the application is stable (the batch variation coefficient is 1.848%~6.062%, and the batch variation coefficient is 4.504%~7.790%), and the coincidence rate with an immunofluorescence experiment reaches 93.26%, the repeatability and the coincidence rate are high, the method has the advantages of simple operation, short time consumption and large detection flux, and is suitable for large-scale screening of clinical pig milk samples.

The application provides a photoelectrochemical sensor, a preparation method and application. The photoelectrochemical sensor is obtained by electropolymerizing a molecularly imprinted polymer on a BiVO4 / CuO-FTO electrode on the basis of the BiVO4 / CuO-FTO electrode, pyrrole as a functional monomer and terramycin as a template molecule. A three-electrode system is constructed by using the photoelectrochemical sensor, terramycin and a buffer solution are mixed to form a standard mixed solution containing different terramycin concentrations, and a photocurrent test is performed to obtain standard photocurrent signals of different terramycin concentrations. A standard curve is obtained by plotting terramycin concentrations as abscissa and the standard photocurrent signals as ordinate. A milk sample containing terramycin is subjected to the above photocurrent test operation to obtain a photocurrent signal, and the terramycin content in the sample solution is obtained by substituting the photocurrent signal into the standard curve. The application has the advantages of small size, simple operation, simple preparation, low cost, good specific selectivity and great application prospect.

The utility model provides a milk freshness detection device. The milk freshness detection device comprises a milk storage tank, a water pump, a quartz container, a light source and a near-infrared spectrometer, the milk storage tank is used for containing milk to be detected; milk in the milk storage tank is conveyed to the quartz container through the water pump and flows back to the milk storage tank; the light source and the near-infrared spectrometer are respectively arranged on two sides of the quartz container; near infrared rays emitted by the light source penetrate through the milk sample in the quartz container and then are received by the near-infrared spectrometer, and spectral data are collected, so that the freshness of the milk sample can be monitored and analyzed in real time on a production line, the quality of milk in the production process is ensured, and the production efficiency is improved. Delay and errors caused by traditional off-line sampling detection are avoided, the detection efficiency can be greatly improved, and waste of milk in the detection process can be effectively avoided.

The present invention belongs to the field of hyperspectral imaging technology and discloses a method for predicting milk fat content based on deep learning combined with hyperspectral imaging technology. The method comprises: using a hyperspectral imaging system to collect hyperspectral image data of milk covering the entire shelf life and determine the fat content; eliminating interference from light and environmental factors on the milk spectral data through a preprocessing method; using JLSP to select characteristic wavelengths and predict fat content of the milk spectral data, and comparing with traditional prediction models PLSR and SVR and traditional wavelength selection methods SPA and CARS. The present invention explores the feasibility of using deep learning methods to predict fat content on milk hyperspectral datasets. A hyperspectral image dataset of milk covering the entire shelf life and the corresponding fat content index are constructed, which solves the problem of incomplete datasets caused by different nutritional components of milk samples during different storage periods.

The present invention relates miRNA biomarkers from a bulk milk sample, e.g. exosome-derived microRNA, as indicators of welfare in bovines. In particular, the present invention relates to the identification of heat stress in bovines allowing to propose management actions to improve productive animal welfare at the herd level.

The utility model discloses a milk sample detection turnover basket. The milk sample detection turnover basket comprises a frame body and a butt joint block, by adopting the positioning rods, the positioning holes, the shielding cloth, the butt joint blocks and the butt joint grooves, when the frame body is used, a worker can select a proper number of *-shaped partitions according to different sizes of sample bottles needing to be loaded; the *-shaped partition is butted with the positioning hole in the bottom through the positioning hole in the top, so that the assembling operation of the structure can be realized, the height of the partition is flexibly adjusted, and the isolation protection effect on the sample bottle is ensured; the top of the frame body can be shielded by pulling out the shielding plate and inserting the shielding plate into an inserting hole in the fixing plate through an inserting rod at the bottom of the shielding plate, and then the multiple sets of frame bodies can be rapidly stacked through the butt-joint blocks and the butt-joint grooves. And the falling phenomenon of the frame body caused by shaking can be effectively avoided, and the device has the advantages of being high in practicability, wide in application range and good in protection effect.

The invention provides a rapid pre-discrimination method for outputting sensory values according to flavor characteristics of cow milk. The rapid pre-discrimination method comprises the following steps: performing program optimization on a raw milk sample by adopting HS-SPME-GC-MS to determine volatile matters; heating the raw milk and then carrying out sensory evaluation; measuring by an electronic nose to obtain a sensor response value; establishing a sensory value prediction model based on volatile flavor factor data or fusion of volatile flavor factors and sensor signal data, and evaluating a model effect; and introducing a new sample, and pre-judging the flavor attribute according to the two established models. According to the method, a multi-data fusion method is creatively adopted, that is, the accuracy is higher by combining the temperament data and the electronic nose data and establishing the model with the sensory values, the model accuracy can be improved by increasing the sample number in a gradient mode, and the sensory values are more comprehensively and accurately output. The reason for establishing the model for the two types of data is that the sensory value information can be predicted more accurately according to which data source, and the subjective error and time cost of sensory evaluation personnel are effectively reduced.

The invention provides a dual RPA-LFD detection method for simultaneously detecting mycobacterium tuberculosis and mycobacterium paratuberculosis, Rv3876 and IS900 specific gene markers can be simultaneously identified, the designed primer and probe do not interfere with each other, the detection limits of mycobacterium tuberculosis and mycobacterium paratuberculosis standard substances are 2.1 * 10 < 1 > copies / mu L and 1.68 * 10 < 2 > copies / mu L respectively, and the detection limit of the Rv3876 and IS900 specific gene markers can be compared with that of a conventional RPA-LFD detection method for simultaneously detecting mycobacterium tuberculosis and mycobacterium paratuberculosis standard substances. Compared with conventional PCR, the detection method has the advantages that the detection result is 100 times and 10 times higher, and the specificity is good. The detection sensitivity of the two strains in the simulated polluted milk sample is as follows: MTB is 2.87 * 10 < 4 > CFU / mL, MAP is 6.36 * 10 < 4 > CFU / mL, and an EDTA-TritonX-100 method is screened as an optimal sample pretreatment method for the simulated polluted milk sample, so that the method can be used as a rapid detection method for the two strains in the fresh milk.

Described herein are personalized skin care compositions including a cultured composition including a milk sample and a skin sample. and optionally an additive. Also described herein are kits and methods for making personalized skin care compositions. Also described herein are methods of treating or preventing skin conditions using personalized skin care compositions.