726results about "Testing food" patented technology

The invention relates to the technical field of nourishment detection, and discloses a system and a method for detecting enzymolysis reaction components of brewing nourishment. The method comprises the following steps: collecting dynamic data such as an enzyme activity value, a substrate concentration value and a product generation rate value in an enzymolysis reaction process in real time through a multi-source sensor; performing multi-modal feature fusion processing on the dynamic data to generate an enzymolysis reaction feature vector; classifying enzymolysis reaction state categories based on the feature vectors, and dynamically adjusting detection parameter thresholds according to different state categories; and according to the deviation value between the real-time reaction state and the parameter threshold value, correcting an enzymolysis reaction process control instruction by adopting a nonlinear optimization algorithm. According to the method, the dynamic state of the enzymolysis reaction can be captured in real time, accurate detection of enzymolysis reaction components and reasonable regulation and control of the reaction process are achieved through multi-dimensional data fusion and dynamic adjustment, and the method is suitable for efficient detection of the enzymolysis reaction of the brewing nourishment.

A computing platform is configured to (1) extract first, second, third, fourth, and fifth source datasets from a first database containing data about a set of product-level ingredients, a second database containing data about food products, a third database containing data about manufacturing plants, a fourth database containing data about ingredient source locations, and a fifth database containing data about ingredient transportation modes, respectively, (2) merge the first, second, third, fourth, and fifth source datasets into a first merged dataset, (3) update the first merged dataset by inserting a column representing distance measurements between source locations and plant locations for product-level ingredients, (4) extract a sixth source dataset from a sixth database containing environmental-impact values for ingredients, (5) merge the updated first merged dataset and the sixth source dataset into a second merged dataset, and (6) determine a group of environmental-impact indicators for each product-level ingredient in the set.

A spectrometer for detecting a trace element in an agricultural product and use thereof is provided. The spectrometer includes: a light source device configured to generate light required by spectroscopic detection; a convergence device configured to converge the light generated by the light source device; a chopping device configured to modulate a frequency of light converged by a convergence device; a filter device configured to shield light of a wavelength other than a preset wavelength; a detection device configured to receive light passing through a to-be-detected agricultural product and the filter device, and convert an optical signal into an electrical signal; and a processing device configured to generate spectroscopic analysis data according to the electrical signal outputted by the detection device and output a substance content analysis result according to the spectroscopic analysis data, where the preset wavelength of the filter device ranges from 400 nm to 5,000 nm.

The invention discloses a cold-chain pork quality dynamic evaluation method and system based on multi-source data fusion, and relates to the technical field of data processing and intelligent evaluation, and the method comprises the following steps: collecting multi-source signal information of a whole cold-chain transportation process, sorting according to a unified time sequence, continuously arranging all signals on a time axis, and carrying out data processing on all the signals; a complete dynamic record is formed; and extracting each time interval and signal amplitude change track from the formed dynamic record, analyzing a signal section with repeated wave crests in a short time, and generating a preliminary data manuscript for reflection interference judgment. According to the invention, through time sequence arrangement and dynamic association of multi-source signals, a wave crest track analysis mechanism is constructed, real-time identification and correction of reflection interference are realized, and continuity and accuracy of a gas concentration curve are ensured; and by generating a reflection source position list and adjusting numerical value distribution of repeated fragments, false fluctuation is eliminated, and the stability and reliability of cold-chain pork quality evaluation are improved.

One or more implementations of the present disclosure relate to a wireless, multi-sensor food thermometer that includes a temperature probe having a linear array of temperature sensors that are operative to measure: temperature profiles within a food product during a cooking process, a temperature at a core of the food product, a temperature at the surface of the food product, and a temperature of the ambient cooking environment in which the food is being cooked. The temperature probe includes a wireless interface that transmits temperature information to one or more external devices for use thereby. Rather than transmitting raw temperature data, the temperature probe may transmit coefficients that correspond to a function that describes the temperature profile within the food or parameters necessary to solve a governing heat equation, which reduces data transmission requirements and reduces power consumption. The food thermometer may include a charger case that houses the temperature probe and charges a power source of the temperature probe using a replaceable battery.

Described embodiments relate to methods of determining quality assessment measures of carcases. The method comprises determining video data comprising a sequence of frames, wherein at least some of the frames depict a part of a carcase to be quality assessed. For a first frame of the sequence of frames, the method comprises a) determining a frame suitability score for assessing a first trait; b) responsive to the frame suitability score being greater than a threshold frame suitability score for the first trait, determining the frame as a suitable frame for assessing the first trait; c) determining, by a segmentation model, a region of interest in the frame for assessing the first trait; d) determining, by a first trait prediction model, a prediction score for the first trait based on the determined region of interest; and e) determining an assessment confidence rating for the first trait. The method further comprises responsive to determining that the assessment confidence rating for the first trait has not exceeded the assessment confidence threshold for the first trait, performing steps a) to e) for a subsequent frame in the sequence; and responsive to determining that the assessment confidence rating for the first trait has exceeded the assessment confidence threshold for the first trait, determining a quality assessment measure of the first trait based on the prediction score for the first trait of the determined suitable frames.

The invention relates to the technical field of chewing testing, in particular to a transmission matching type alternating bionic chewing device and a simulation testing method thereof.The transmission matching type alternating bionic chewing device comprises a supporting frame, a processing tank and a fixing plate, the processing tank and the fixing plate are arranged on the supporting frame, and a feeding port is formed in the processing tank; the pushing assemblies are symmetrically arranged on the fixing plate, and pushing plates are connected to the pushing assemblies; the elastic supporting mechanism is arranged on the push plate, a supporting rod is connected to the elastic supporting mechanism, a chewing mechanism is arranged on the supporting rod, and a first meshing plate and a second meshing plate which are matched with each other are connected to the chewing mechanism; the translation assembly is arranged on the chewing mechanism, a deflection mechanism is further arranged on the chewing mechanism, and the translation assembly can control the first meshing plate and the second meshing plate to execute reciprocating deflection action through the deflection mechanism when the chewing mechanism moves, so that the uniformity of material chewing is guaranteed.

The invention provides a method for determining a current homogeneity parameter of a fodder mixture for farm animals while mixing the fodder mixture in a mixing container of a fodder mixing apparatus, wherein the fodder mixture comprises at least two different fodder components, comprising recording, in sequence, optical spectra of the fodder mixture with a spectral sensor while mixing, wherein the method further comprises the steps of: a) receiving, by an electronic control unit, at least three optical spectra recorded by the spectral sensor, b) calculating, by the electronic control unit, a correlation between the at least three optical spectra, and c) determining, by the electronic control unit, the current homogeneity parameter based on the correlation between the at least three optical spectra.

The invention relates to the technical field of food evaluation, and particularly discloses a multi-element evaluation method and system for potato sirloin prefabricated dishes, and the method comprises the steps: obtaining a target sample; collecting the near infrared spectrum, the total bacterial count, the shearing force and the response value of the electronic nose sensor of the target sample; preprocessing the near infrared spectrum to obtain a near infrared optimized spectrum; carrying out dimension reduction processing on the near-infrared optimized spectrum to obtain a near-infrared light model dimension reduction spectrum; taking the near-infrared light model dimensionality reduction spectrum as input, taking a corresponding target evaluation index as output, combining a target training algorithm corresponding to the target evaluation index, and utilizing the training set to train to obtain a multivariate evaluation model; and receiving a near-infrared light target dimension reduction spectrum, calling the multivariate evaluation model, and synchronously outputting an evaluation result corresponding to each target evaluation index by using the mapping relationship. According to the scheme, training of a multivariate evaluation model is realized by means of a near infrared spectrum technology, multi-dimensional index evaluation can be performed on the sirloin prefabricated dish, and the evaluation accuracy and efficiency are improved.

A method for detecting the extent of microplastic accumulation in bivalve organisms in extreme deep-sea environments is provided. This method is performed through sampling of biological communities to represent the community structure of that biological bed layer, then morphological characterization statistics are conducted to classify the age stage data of individual bivalves, multivariate factor analysis is used to obtain the individual bivalves with the greatest degree of contribution in each classified age stage, subsequently tissue-specific microplastic extraction is performed, the morphology of seafloor microplastics is restored and streamlined identification of full-size microplastics is considered, carbon-14 dating is used to trace the duration of microplastic adsorption by each individual bivalve, dynamic accumulation curves for seafloor bivalves are constructed by connecting each bivalve's survival duration, and finally this is scaled up to the entire bivalve bed to derive the microplastic accumulation rate and historical accumulation of the entire extreme ecosystem.

The present disclosure relates generally to methods and test kits for identifying SNPs associated with desirable meat eating quality traits in ovine animals. In particular, the present disclosure relates to a SNP-based diagnostic test and method for identifying ovine animals with desirable fat melting point (FMP), intramuscular fat (IMF) and omega-3 long chain polyunsaturated fatty acids (n-3 LC PUFAs) which are characteristic of Australian White sheep or Lamb (e.g., Tattykeel Australian White Lamb), and the use of those tests and methods in animal breeding programs.

The invention relates to the technical field of food quality detection, and discloses a meat product comprehensive scoring method based on principal component analysis, and the method comprises the steps: firstly obtaining physicochemical index (such as protein and fat content) and sensory attribute (such as color saturation and elasticity index) data of multiple batches of samples, and carrying out the structural arrangement of the two types of data according to batches and index dimensions; respectively carrying out Z-score standardization, range normalization and other processing, and extracting a physicochemical index feature vector and a sensory attribute feature vector; constructing a dynamic weight strategy through a variance contribution rate and a feature root ratio, and performing weighted fusion on the two types of feature vectors to obtain a fused feature vector; and finally, inputting the data into a scoring model, and after centesimal system conversion and distribution calibration, dividing quality grades in combination with an industry standard threshold to generate a comprehensive scoring result containing alphanumeric identifiers. The method realizes multi-dimensional data fusion and dynamic empowerment, improves the scoring accuracy, and is suitable for meat product quality evaluation.

The invention discloses a rapid component detection system based on food additives, and relates to the technical field of food safety detection.A food sample is collected, matrix information of the food sample is obtained, an additive fingerprint feature group is extracted based on a reference model, sample response signals are collected through multi-channel detection, and feature matching analysis is carried out; outputting additive existence judgment and a matching degree score; when the matching degree score is lower than a preset threshold value, abnormal response features are extracted, feature vectors of the components to be verified are constructed and compared with the high-risk component template data, and suspected illegal added components are marked; by fusing spectrum, fluorescence and electrochemical multi-dimensional detection channels, the method has the characteristics of broad spectrum, rapidness and high adaptability, can realize intelligent identification and early warning of unknown or illegal additives, and is suitable for mobile detection and risk screening in various food scenes.

The invention belongs to the technical field of agricultural product nondestructive testing and automatic equipment, and discloses a wearable fruit multi-point quality detection method and device based on a manipulator, the wearable fruit multi-point quality detection method and device based on the manipulator are worn on an automatic fruit picking mechanical arm, and the integrated operation of picking, detecting and sorting of fruits can be achieved; and detection and grading of quality indexes of the internal maturity of the fruits are accurately completed. When the mechanical arm picks the fruits, the quality detection module synchronously collects data, the control module receives the data and outputs a quality result through model operation, then a sorting program drives the mechanical arm to transfer the fruits to the storage boxes of the corresponding grades, and picking-detection-sorting integrated operation is achieved. According to the invention, multi-modal quality data can be synchronously obtained, detection of multiple varieties of fruits is flexibly adapted, the detection precision and efficiency are improved, and the limitation of a traditional detection technology is solved.

The quality inspection method for inspecting a horticultural product comprises the following steps: -providing optical reconstruction means including multispectral illuminating means (2) and multispectral sensor means (3); -gathering loose units (6) of said horticultural product in a container (5); -illuminating with the multispectral illuminating means (2) the mass of product present in the container (5) by emitting a sequence of light radiations with different bandwidths; -capturing multispectral (3) images (10', 10") of the product mass present in the container (5) illuminated in this way; - identifying multispectral images (11, 11', 11") of individual units (6) of product by processing the multispectral images (10, 10', 10") of the product mass present in the container (5); - classifying individual (6) bulk units with quality indices associated with the spectrum of their multispectral images (11, 11', 11") thus identified; where the process of identifying the multispectral images (11, 11', 11") of the individual units (6) of product bulk is carried out by means of an artificial neural network trained to segment the images (10, 10', 10") of the product bulk in the container (5).

This invention belongs to the field of post-harvest quality testing technology for agricultural products, specifically relating to a method for predicting the degree of chilling injury in bitter gourd. The method uses *Bitter Gourd 'Du Ruan'* as the research object, employing segmented pre-cooling treatment to measure indicators such as chilling injury index, respiration rate, weight loss rate, firmness, chlorophyll content, malondialdehyde content, and antioxidant enzyme activity during storage. This determines suitable pre-cooling conditions, explores the impact of different pre-cooling settings on its physiological quality and chilling injury development during storage, and constructs a bitter gourd chilling injury prediction model based on key indicators. The method for predicting the degree of chilling injury in bitter gourd provided by this invention offers a theoretical basis and technical support for optimizing post-harvest cold chain processes for bitter gourd, mitigating low-temperature damage, and extending shelf life.

The utility model discloses a nutrient substance detection device for prefabricated meal, which comprises a rod body, the bottom of the rod body is fixedly provided with a transparent plastic graduated tube, the bottom of the transparent plastic graduated tube is fixedly provided with a suction tube, and the outer side of the bottom of the suction tube is sleeved with a rubber sleeve; a clamping mechanism is arranged at the top of the rod body, and a moving assembly is arranged between the rod body and the transparent plastic graduated tube; wherein the clamping mechanism comprises a protective cover arranged at the top of the rod body, a supporting column is fixedly mounted in the upper part of the rod body, a fixing box is fixedly mounted at the bottom of the supporting column, and a screw rod is rotationally connected between the fixing box and the supporting column, so that the effect of quickly sampling solid food can be realized; furthermore, the flexibility of the device during use can be greatly improved, and the effect of sampling the nutrient substances during processing of various prefabricated vegetables is met, so that the detection efficiency of the nutrient substances of the prefabricated vegetables is further improved.

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.

This utility model discloses a pesticide accelerated dissolution device for detecting pesticide residues in fruits and vegetables, relating to the field of pesticide detection technology. The device includes a dissolution tank for holding the dissolution solution. Through the arrangement of a rotating cover, a pressure plate, and an eccentric roller, during dissolution, a first drive motor rotates the rotating cover, causing the storage cylinder to move with the cover. A second drive motor rotates the eccentric roller, causing the storage cylinder to intermittently vibrate up and down during rotation. During this vibration, the pressure plate extends into the storage cylinder relative to the cylinder, squeezing the fruits and vegetables. This multi-motion coordinated dissolution effect allows the pesticides in the fruits and vegetables to quickly fuse with the solvent, improving dissolution efficiency and data accuracy.

This invention provides a food fraud detection device using terahertz spectroscopy that achieves a compact and stable structural configuration. [Solution] The food fraud detection device 100 using terahertz spectroscopy according to the present invention comprises a base housing 20 and an upright housing 21 attached to the base housing 20. A display unit 1 is provided in the upright housing 21, and a user input unit 2 is provided in the base housing 20. The main body of the device 100 is equipped with a wireless connection antenna 7, a voice generation unit 8, a voice input port 81, first to fourth connection ports 31, 32, 33, 34, an external sensor connection port 4, a server connection port 5, and a port 6 for opening the device. An optical sensor 10, an ultrasonic sensor 11, and a chemical sensor 12 are arranged on the base housing 20 together with corresponding control switches 13, 14, 15.

The invention belongs to the technical field of agricultural product drying, and particularly relates to a jujube slice drying process key quality index prediction method based on multi-source easy-to-measure index fusion. The invention aims to design a key quality index prediction method suitable for a drying process, and provides the key quality index prediction method for the drying process of the jujube slices by establishing a prediction model for important nutritional indexes of the jujube slices in order to solve the problem that the important nutritional indexes of the jujube slices are difficult to monitor in the drying process in the prior art. According to the method, the important nutritional indexes of the jujube slices in the drying process can be quantitatively monitored in real time, the content of different quality indexes of the jujube slices can be rapidly and accurately detected, quantitative data support is provided for optimizing the drying process, the controllability of the drying process and the consistency of product quality are enhanced, and the method has high market application and popularization value.

The application relates to the technical field of immunodetection, in particular to a non-crystalline MOF-mediated cascade antibody directional probe and a preparation method and application thereof. The application specifically comprises the following steps: (1) mixing a second antibody solution with a coomassie brilliant blue solution to obtain a second antibody staining solution; (2) mixing a Zn(OAc)2.2H2O solution, an HmIM solution and the second antibody staining solution to obtain aR-ZIF-Ab2 nanocomposite material; and (3) mixing the aR-ZIF-Ab2 nanocomposite material with a first antibody and incubating to obtain aR-ZIF-Ab2-mAb1 cascade antibody directional probe. The CAbD strategy based on aMOF can be used as a promising antibody directional and probe construction means in immunochromatographic analysis, and provides a reference innovation direction for the design and development of an immunobiosensor.

The application discloses a kind of halogen products processing whole process data acquisition method and system, it is related to halogen products processing whole process data acquisition field, for solving in halogen products processing industry, optical sensor lens pollution causes the deviation of halogen soup concentration measurement difficult to find and correct, and then caused process adjustment error and product quality problem, comprising: obtaining the first concentration measurement value of halogen soup, with multiple process parameters related to the concentration change of halogen soup;Based on multiple process parameters, the second concentration calculation value of halogen soup is calculated;Compare first concentration measurement value and second concentration calculation value, identify the deviation between them, and cross validation is carried out in combination with multiple process parameters, to diagnose the progressive measurement deviation caused by optical sensor lens pollution;According to the diagnosis result, the amount of concentrated halogen material that needs to be added is output.

This utility model relates to the technical field of pesticide residue detection in agricultural products, and in particular to a pesticide residue detection device for agricultural products. The device's height can be adjusted according to actual conditions to facilitate use by personnel of different heights, providing convenience for personnel detecting pesticide residues in agricultural products. It includes a housing, inside which is a PLC controller. The top of the housing has a display screen and buttons electrically connected to the PLC controller. A stirrer is detachably connected to the housing. Four sets of guide rods are symmetrically fixed at the bottom of the platform, and each of the four sets of guide rods has a sliding support leg. A positioning frame is fixedly connected to the top of the platform. Rubber clips are symmetrically fixed to the inner walls of the left and right sides of the positioning frame. The housing is secured to the positioning frame by engaging with the rubber clips. The bottom of the housing contacts the top of the platform. Two sets of support plates are fixedly connected to the bottom of the platform, and a transmission worm gear is rotatably mounted on the two sets of support plates for adjusting the height of the platform.

The utility model relates to a food metal detector. Comprising two first conveying belts arranged at intervals and a second conveying belt located between the two first conveying belts, and the conveying direction between the second conveying belts is opposite to the conveying direction of the first conveying belts; the metal detector body is located above the first conveying belt and the second conveying belt. Guide plates for guiding food to the second conveying belts are arranged at one ends of the two first conveying belts; baffles are arranged between the two first conveying belts and the second conveying belt. When food is conveyed, the food is firstly conveyed through the first conveying belt and passes through the metal detector body for the first time, when the food reaches the guide plate through the first conveying belt, the food collides with the guide plate, the food enters the first conveying belt under the action of the guide plate, and in the whole process, the angle of the food changes immediately; and then the food is re-inspected on the second conveying belt through the metal inspection machine body, so that the detection error caused by the angle of the food is effectively avoided, and the detection effect of the metal inspection machine is further improved.

The application discloses a kind of real-time detection method and system of food pollutant based on intelligent sensor, comprising: through the multimodal sensor array of deployment in food processing production line key station, sensor response signal is collected;Baseline response under the condition of no pollution is predicted by establishing dynamic baseline prediction model;Signal separation network based on variational decoupling autoencoder is constructed, residual signal is mapped to low-dimensional latent space by sharing encoder and is divided into baseline error subspace and pollutant signal subspace, respectively by two independent decoders reconstructing baseline prediction error signal and pollutant candidate signal;Multi-scale time-frequency transform is carried out to pollutant candidate signal to identify pollutant type and estimate concentration;Through distributed intelligent agent cooperation, pollution traceability and hierarchical early warning are carried out;Cross-scene adaptive calibration is realized using meta-learning framework.The application realizes the real-time decoupling of pollutant signal and matrix change signal in food processing process.

Provided is a method of evaluating an object to be chewed, the method including: performing an iterative compression process on the object to be chewed; and performing a regression analysis through use of, as explanatory variables, one or more process condition parameters based on one or more process conditions of the iterative compression process and, as a response variable, a measurement parameter based on one or more measurement values selected from the group consisting of a measurement value obtained from the object to be chewed that is being subjected to the iterative compression process and a measurement value obtained from the object to be chewed that has been subjected to the iterative compression process.

The present application relates to the field of environmental monitoring, and more particularly to a dehydration onion drying environment real-time monitoring method based on multi-sensor fusion, the method comprising: obtaining multi-dimensional environment data of a sub-region in a drying chamber; calculating spatial dispersion index, state change vector and dynamic consistency index at the current time; calculating an adaptive adjustment coefficient based on the environmental entropy change index, using the adaptive adjustment coefficient to modify the parameters of the Kalman filter, filtering and denoising the normalized state vector to obtain a denoised state vector; determining an operation deviation vector and calculating a local sensitivity enhancement eigenvalue; splicing the denoised state vector and the local sensitivity enhancement eigenvalue to construct an augmented vector, inputting the augmented vector into an anomaly detection model to obtain an anomaly score, and if the anomaly score exceeds a preset threshold and lasts for a preset period, an alarm is triggered. The present application improves the accuracy of early anomaly detection in the drying process.

The application relates to a device for measuring a property of a gas found in an item of food packaging. The device comprises a sensor for measuring the property of the gas, wherein the sensor is designed to measure the property of the gas through the food packaging without damaging the food packaging. The device also comprises a movement unit in order to move the sensor relative to the food packaging and / or a stationary base. The application also relates to a method for measuring a property of a gas found in an item of food packaging by means of a sensor, said method comprising the steps of: providing the food packaging in a food processing line, moving the sensor relative to the food packaging and / or a stationary base into a measuring position, measuring the property of the gas through the food packaging without damaging the food packaging.