46 results about "Sensory analysis" patented technology

Provided is a consumer to industrial scale renewable energy based quintuple-generation systems and energy storage facility. The present invention has both mobile and stationary embodiments. The present invention includes energy recovery, energy production, energy processing, pyrolysis, byproduct process utilization systems, separation process systems and handling and storage systems, as well as an open architecture for integration and development of additional processes, systems and applications. The system of the present invention primarily uses adaptive metrics, biometrics and thermal imaging sensory analysis (including additional input sensors for analysis) for monitoring and control with the utilization of an integrated artificial intelligence and automation control system, thus providing a balanced, environmentally-friendly ecosystem.

Systems and methods for a sensor hub system that accurately and efficiently performs sensory analysis across a broad range of users and sensors and is capable of recognizing a broad set of sensor-based events of interest using flexible and modifiable neural networks are disclosed. The disclosed solution consumes orders of magnitude less power than typical application processors. In one embodiment, a scalable sensor hub system for detecting sensory events of interest comprises a neural network and one or more sensors. The neural network comprises one or more dedicated low-power processors and memory storing one or more neural network programs for execution by the one or more processors. The output of the one or more sensors is converted into a spike signal, and the neural network takes the spike signal as input and determines whether a sensory event of interest has occurred.

The invention discloses a classified identification method for fish sauce, belonging to the technical field of condiments analysis and identification methods. The method comprises the following steps: respectively determining volatile organic compounds in different types of fish sauce samples by an electronic nose analysis method to obtain the response intensity data of the different types of the fish sauce samples in an electronic nose sensor matrix; performing statistic classification on the response intensity data of the fish sauce samples, and establishing a fish sauce classified identification model; obtaining the response intensity data of a fish sauce sample in the electronic nose sensor matrix, substituting the response intensity data into the fish sauce classified identification model for analysis, and judging to obtain the classification of the fish sauce sample. By the adoption of the method, the quality of odor can be quantized and standardized, and the fish sauce classified identification model is established, so that the fish sauce can be evaluated objectively, quickly and accurately; the standardization of the quality of the fish sauce can be effectively guaranteed; the quality and the market competitiveness of the product are improved; the blank that the precision and the standardization cannot be realized by conventional sensory analysis is filled.

The invention relates to a method for evaluating the shelf life of cooling pork at fluctuating temperature. The method comprises the following steps of: (1) sample microorganism and sensory analysis; (2) microorganism growth prediction models; and (3) application and verification of the prediction models at the fluctuating temperature. The method has the advantages that a predictive microbiology method is applied to analyze the growth situations of aerobic bacteria in the cooling pork at different time points under different temperature conditions and establish the microorganism prediction models of the cooling pork at different storage temperatures so as to evaluate the edible safety of the cooling pork; the established prediction microorganism dynamical-models can effectively predict the shelf life of the cooling pork at the temperature of 4-15 DEG C; and a strong technical support is provided for monitoring and tracking the shelf life of the cooling pork under the environment condition with the fluctuating temperature in real time.

The invention discloses a quick classification and identification method for Ganpu tea (orange pu-erh tea). The method comprises the following steps of measuring characteristic volatile organic compounds in different standard samples by using a gas-phase ion migration analysis method, to acquire response strength data of flavor compounds of different types of standard samples; clustering the response strength data of the standard samples by using a statistical analysis method, and building a classification and identification model; measuring the characteristic volatile organic compound in an unknown sample by using the gas-phase ion migration analysis method having the same parameter with the previous step, thus acquiring a sample fingerprint spectrum, and putting the sample fingerprint spectrum into the classification and identification model acquired in the previous step for analysis, so as to judge the category and authenticity of the sample. According to the method provided by theinvention, the flavor quality is quantified and standardized, and the classification and identification model is built, so that the Ganpu tea can be quickly, objectively and accurately assessed, the standardization of the quality of the Ganpu tea can be effectively ensured, the product quality and market competitiveness can be improved, and the blank that sensory analysis cannot be accurate and standard is filled.

The invention discloses an intelligent pre-cooling treatment and sectioned controlled atmosphere storage combined system for controlling low-temperature cold damage of cold-sensitive fruit vegetable type vegetables and belongs to the technical field of intelligent control on food quality. The system comprises a sensor detection module, a data acquisition module, a wireless communication module, a terminal and a control system, wherein the sensor detection module detects carbon dioxide, ethylene as well temperature and humidity in a preservation chamber, then the data acquisition module connected with the sensor detection module acquires data, and the wireless communication module connected with the data acquisition module sends the data to the terminal; the sensor detection module is also connected with the control system, and the control system controls environmental parameters when the terminal reads the sensor detected data. Compared with existing physical and chemical analysis methods and artificial sensory analysis, the system has the advantages that to-be-tested samples cannot be damaged, the task load is small, and the objectivity and efficiency are higher.

An integrated intelligent server based system includes at least one autonomous system containing one or more analytical server for unified multiple sensory data mapped multi-modal or multi-sensory imagery analysis, generating analysis result and streaming of the sensory data with the generated analysis result to the receiver module. A fail safe and fault tolerant technique to generate, store and stream the multi-sensory images to the receiver module is also proposed. Once received, the receiver module extracts the sensory data and the results of the sensory data analysis from the image and video using a suitable decoder. The integrated intelligent server based system would enable embedding the results of the sensory data analysis within the image itself and streaming the multi-sensory image embedded with the results of said sensory data analysis to a receiver module. This results in adopting this new concept in Internet of Things scheme of activities as well.

The invention discloses a method for analyzing and discriminating odorous substances in drinking water. The method comprises the following steps: (1) extracting volatile substances in the drinking water by a solid phase microextraction technology; (2) performing gas chromatography-olfaction-mass spectrometry (GC-O-MS) analysis on the volatile substances in the drinking water, and qualitatively and quantitatively discriminating the odorous substances; (3) preparing simulated water sample from the discriminated odorous substances and ultrapure water by stimulating the drinking water, performing sensory analysis on the simulated water sample and the drinking water, evaluating the simulated water sample and the drinking water, and determining the accuracy of the odorous substances discriminated by the gas chromatography-olfaction-mass spectrometry. Through solid phase microextraction, GC-O-MS and sensory evaluation on the odorous substances in the drinking water, the odorous substances in the drinking water are analyzed and discriminated, and the accuracy for discriminating the odorous substances in the drinking water is high.

The invention provides a screening method and system of an electronic nose sensor in tea grade identification, which can improve the recognition rate of tea grades. The method includes: detecting the aroma components used to characterize tea leaves of different grades in the tea samples to be tested through the electronic nose; according to the detection results, obtaining the sample intra-class dispersion and the sample inter-class dispersion corresponding to each sensor in the electronic nose. degree; according to the sample class dispersion degree and sample class dispersion degree corresponding to each sensor obtained, determine the distinguishing performance value of each sensor to the tea grade; judge the effect of each sensor in the electronic nose on the tea grade Whether the distinguishing performance value of the electronic nose meets the predetermined distinguishing standard, and the sensors in the electronic nose meeting the predetermined distinguishing standard are screened out. The invention is applicable to the technical field of food intelligent sensory analysis.

The invention belongs to the technical field of food detection, and relates to a detection method of food sweetness degree. The method comprises the following steps: (1) preparing a sweetness degree sensor; (2) soaking the sweetness degree sensor in a potassium hydroxide solution, carrying out detection under a certain voltage, and taking the current value at the 120th second as the (I) standard; (3) preparing sweetener solutions with different sweetness degrees, and then mixing the sweetener solutions with a potassium hydroxide solution individually; (4) soaking the sweetness degree sensor in the mixed solution of sweetener and potassium hydroxide, carrying out detection under a certain voltage, taking the current value at the 60th second as the (I) sample, and taking the ratio of (I) standard to (I) sample as the sample characteristic signal value (S) sample; (5) taking the (S) sample and the actual sample sweetness degree (T) sample as the horizontal ordinate and vertical ordinate respectively to obtain a standard curve; (6) detecting a sample by the sweetness degree sensor, and substituting the measured value into the standard curve to obtain the sweetness degree of the sample. The provided detection method overcome the shortages of conventional sweetness degree detection methods; the sweetness degree sensory analysis and instrument analysis are unified, if the primary standard curve is established, the post detection becomes easier, the provided detection method can be used to detect the sweetness degrees of various sugar-containing beverages and fruits, the detection precision is high, and the application range is wide.

The invention discloses a method for evaluating citrus chewiness. The method comprises the following steps: putting a citrus on a test platform of a texture analyzer, performing a compression test twice to obtain TPA texture characteristic information, analyzing the obtained texture characteristic information to find texture characteristic information data related to citrus chewiness, and obtaining the chewiness characteristic of the tested citrus through a correction model. The method can determine citrus chewiness, is rapid and convenient in operation, avoids interference of human factors during sensory analysis, and is objective and accurate in results.

A rapid identification method of the aroma quality of minced mutton comprises the following steps: 1, extracting volatile components in the minced mutton through headspace solid-phase microextraction;2, performing chromatography and mass spectrometry; 3, scoring by using different characteristic aromas as sensory attributes; 4, comparing the chromatographic peak value with an NIST spectrum library and a Wiley spectrum library, and calculating the KI value of a test object when SI is greater than 800 and smaller than 1000 by using a normal alkane mixture of C8-C24 as a standard; 5, comparing the chromatographic peak area with the chromatographic peak area of 1,2-dichlorobenzene, and calculating the relative content; 6, identifying characteristic aroma components by a partial least square regression method. By the rapid identification method, through combination of a solid-phase microextraction technology, a GC-MS technology, a GC-O technology and sensory analysis, the aroma componentsin the minced mutton can be rapidly identified, and thus the aroma quality thereof is identified so as to avoid mutton adulteration.

The invention provides a method for fusing characteristic parameters of electron nose response signals in tea leaf grade identification. The method allows characteristic information of the electron nose response signals to be comprehensively characterized in order to improve the tea leaf grade recognition rate. The method comprises the following steps: acquiring electron nose response signals of tea leaves to be measured and used for characterizing the fragrance characteristics of tea leaves with different grades; acquiring the time domain characteristics and the frequency domain characteristics of the electron nose response signals according to the acquired electron nose response signals; and fusing the acquired time domain characteristics and the frequency domain characteristics, and using the fused characteristics as the characteristic information of the electron nose response signals. The method is suitable for the technical field of intelligent sensory analysis of foods.

The invention provides a favorite emotion automatic identification method and system, which can improve the rapidness and convenience of sensory favorite degree measurement and improve the identification effect of favorite emotion. The method comprises the steps of acquiring facial expression videos of a testee under stimulation of different flavors and sensory preference of the testee to the flavors; aligning facial expression images in the facial expression video by utilizing the facial feature points; dividing a facial region in the aligned facial expression image into a plurality of regionblocks, extracting dense optical flow from each region block, and performing main direction optimization based on the extracted dense optical flow to obtain an optical flow main direction of each region block; determining a region block combination for emotion level classification according to the obtained optical flow main direction of each region block; and training a classifier for identifyingthe sensory preference degree according to the main direction of the optical flow in the determined regional block combination and the sensory preference degree of the testee to the flavor. The invention relates to the fields of sensory analysis, consumption behavior analysis and artificial intelligence.

A microwave-still air combined thawing process for frozen tuna bars is to thaw frozen bigeye tuna bars by microwave thawing and still-air thawing. The combined thawing process is optimized under the power of 170-300w, the optimized process is determined by physicochemical and sensory analysis, and chewing performance, redness value and sensory indexes of the thawed tuna are compared. The combined thawing method for frozen tuna bars, which is high in thawing quality and fast in thawing, is provided so as to quicken popularization of tuna in China.

The present invention describes the process of producing wine using flowers of Castanea sativa Mill as preservatives properties, in alternative to the use of sulphites. A preferred embodiment refers to the production of vinho verde (green wine).Widely described for its antioxidant and antimicrobial activities, the flowers of Castanea sativa were added directly to the wine during its production process. Based on the physicochemical and sensorial analysis required for this type of drinks, the addition of flowers of C. sativa conferred to the wine preservative properties, without altering its physicochemical and sensorial parameters. The greatest advantage of this process is the complete elimination of the use of synthetic preservatives, namely sulphites, allowing the consumer to enjoy a highly appreciated product with quality and more importantly, safer, and that can also provide to the consumers other benefits from other beneficial bioactive compounds present in the flowers incorporated in the wine.

The invention discloses a consumer preference evaluation method using facial expressions and sensory analysis and an application thereof, aiming at the preference evaluation of consumers on food products. Aiming at evaluating the preference degree of the product by mostly depending on a direct research method (questionnaire) in the current consumer research, the invention discloses a method for evaluating the preference degree of a product by adopting an indirect consumer emotion research method and a direct sensory measurement method, namely a method of combining facial expressions and questionnaires. The method includes building a Multiple linear regression model, and predicting the preference of the consumer to the food. The invention fills the gap of an evaluation method combining a direct method and an indirect method, meanwhile, the evaluation method for predicting the preference degree of the consumer more comprehensively and accurately is provided by applying a facial expression emotion analysis method, and the invention can be widely applied to the field of foods such as beverage wine and dairy products.

The present invention relates to a real-time automatic analysis device for an organic contaminant in water, the device having: an analysis apparatus comprising a solid phase micro-extraction device and a gas chromatography / mass spectrometry analysis device that have been traditionally used; a heating block; a sample bottle; a discharge unit; and a control unit. While using an analysis apparatus, being traditionally used, as it is, the real-time automatic analysis device for an organic contaminant in water accurately and quickly identifies a point of generation of a high-concentration organic contaminant by supplying a sample consecutively and in real time, takes follow-up measures, and easily performs a sensory analysis as well as a chemical analysis.

The invention discloses a meixiang fish fermentation degree multi-dimensional fusion identification method based on smell visualization, which integrates an electronic nose system, gas phase-ion migration mass spectrometry and multi-dimensional data fusion analysis to establish an effective multi-dimensional fermentation degree identification model. According to the method, a rapid identification model for the fermentation degree of the Meixiang fish is established by fusing a neural network algorithm, PCA analysis and other data analysis methods, the method is suitable for quality evaluation and fermentation degree distinguishing of the Meixiang fish, the identification cost is low, and the result visualization degree is high. The method is based on a multi-dimensional fusion identification and prediction strategy, and compared with traditional sensory analysis and single flavor analysis, the method has the advantages of high sensitivity, short analysis time, convenience in operation, high predictability and the like, and meets the requirements of rapid detection and analysis of modern aquatic food.

The invention discloses a method for detecting and identifying volatile substances in Maotai-flavor base liquor. The method comprises the following steps: determining volatile flavor substances; detecting volatile substances of the Maotai-flavor base liquor; constructing a Maotai-flavor base liquor identification model; verifying the Maotai-flavor base liquor identification model; and determining different substances of the Maotai-flavor base liquor. The invention provides a method for rapidly identifying Maotai-flavor type breakstone base liquor and broken sand base liquor by combining a gas chromatographic method with chemometrics analysis, and key difference substances causing difference are screened from the Maotai-flavor type breakstone base liquor and the broken sand base liquor. According to the method, the identification model of the Maotai-flavor Baijiu and the broken Baijiu is constructed for the first time, the identification ability is good, the subjectivity problem of sensory evaluation identification is solved, the identification model and sensory analysis can be combined to be used for identification of Maotai-flavor Baijiu of different processes, the identification method is more efficient and accurate, and the credibility of the identification result is improved.

The invention discloses a wine sample grading method based on comprehensive sensory analysis, which comprises the following steps: establishing a wine sample sensory evaluation index hierarchical model which comprises a first-level index, a second-level index and a third-level index, and designing an evaluation table; evaluating a to-be-graded wine sample by experts and a common evaluation group,filling in an evaluation table and sorting; calculating first-level and second-level index weights and a third-level index contribution index; calculating a sample fitting coefficient to obtain a three-level index scoring result; calculating the capability scores of the common evaluation group for each index of the wine sample, and calculating the total score of all indexes of each wine sample; calculating a wine sample quality sorting rank sum in each round of evaluation, and converting the wine sample quality sorting rank sum into an evaluation score; calculating an average value together with the total score to obtain a final score; and grading wine samples. Details and the overall wine samples are subjected to composite analysis in a multi-model combination mode, and the integrity andthe characteristic analysis are considered to improve the accuracy of the system; personal evaluation ability analysis of common evaluation group members is added, and analysis errors caused by personnel changes are reduced.

The invention discloses a yellow wine taste evaluation method based on the combination of artificial sensory and electronic tongue technology, which comprises the following steps: screening taste descriptors and establishing a reference system, obtaining the static taste profile of a yellow wine sample by quantitative descriptive sensory analysis, and exploring the change trend of each taste attribute within 60 seconds after the yellow wine sample is drunk by utilizing TCATA test; utilizing a dynamic dominant attribute test to determine the change rule of dominant taste attributes within 60 seconds after a yellow wine sample is drunk, utilizing a time intensity test to capture the dynamic change of a certain important taste attribute perception intensity of the yellow wine sample along with time, utilizing an electronic tongue to evaluate and obtain objective response values of each taste attribute of the yellow wine sample, and establishing an electronic tongue response curve of a certain important taste attribute of the yellow wine sample. The taste characteristics of the yellow rice wine are comprehensively revealed by combining artificial sensory and electronic tongue technologies, the result is visual and reliable, the applicability is wide, and a theoretical basis is provided for improving the quality stability and flavor regulation of the yellow rice wine.

The invention discloses a food sensory real-time dynamic evaluation and chewing behavior analysis device and method, and belongs to the technical field of food sensory analysis. In the device, a sliding potentiometer and a direct-current stabilized power supply form a voltage division circuit, and a voltage detection module is used for detecting a voltage value between a movable contact and a fixed contact of the sliding potentiometer in real time; a visual sensor is used for shooting chewing behaviors of evaluation personnel; a voltage detection module and a visual sensor are electrically connected with the lower computer to form a data feedback and control system. A lower computer is in communication connection with an upper computer. The device can obtain dynamic sensory analysis data in real time, the sensory data can be directly and statistically related to quantitative analysis data of flavor substances, and besides, the device can also combine chewing behaviors with sensory evaluation data to perform binary and multivariate analysis. The device has the advantages of being high in operability, good in stability and low in cost.

A polymeric composition suitable for blown film applications comprising a) 80 to 99.5 percent by weight of a continuous polymeric phase comprising a polyolefin, and b) 0.5 to 20 percent by weight of polymeric particles having i) an average particle diameter of 0.85 to 20 μm; ii) a refractive index from 1.46 to 1.61; iii) an average particle hardness from 1.2367E+10 N / m2 to 8.4617E+10 N / m2; and iv) at least 60% polymerized acrylic monomer units, is disclosed. The polymeric composition can be used to form blown film characterized by having a thickness in the range of from 5 to 350 μm, a modulus of elasticity in the range of from 5 to 133 MPa, a melt strength in the range of from 4 to 40 cN, an elongation at break in the range of from 100 to 1000%, a 45 degree gloss in the range of from 7 to 136 and a softness measured by human panel handfeel-ranking methodology, measured by ISO 8587 Sensory analysis that is higher than a film which does not contain the polymeric composition.

The invention discloses a method for discriminating the browning degree of aged tobacco leaves, which is characterized in that a mechanism for discriminating the browning degree of the tobacco leaves is established on the basis of apparent colors, specifically, the grade of the browning degree is preset, and the aged tobacco leaf samples are used for carrying out measurement statistics and comparative analysis on color related indexes, therefore, relatively stable target index data with relatively small mutual influence is obtained, abstract models corresponding to browning degree grades are constructed by using the target index data, and finally, the quantitative browning degree of the tobacco leaves to be detected represented by color values or browning area ratios can be judged in combination with the target indexes of the tobacco leaves to be detected and the abstract models. Compared with sensory analysis, the method has the advantage that the browning degree of the aged tobacco leaves can be quantitatively judged more visually, quickly and accurately.

The invention discloses a classified identification method for fish sauce, belonging to the technical field of condiments analysis and identification methods. The method comprises the following steps: respectively determining volatile organic compounds in different types of fish sauce samples by an electronic nose analysis method to obtain the response intensity data of the different types of the fish sauce samples in an electronic nose sensor matrix; performing statistic classification on the response intensity data of the fish sauce samples, and establishing a fish sauce classified identification model; obtaining the response intensity data of a fish sauce sample in the electronic nose sensor matrix, substituting the response intensity data into the fish sauce classified identification model for analysis, and judging to obtain the classification of the fish sauce sample. By the adoption of the method, the quality of odor can be quantized and standardized, and the fish sauce classified identification model is established, so that the fish sauce can be evaluated objectively, quickly and accurately; the standardization of the quality of the fish sauce can be effectively guaranteed; the quality and the market competitiveness of the product are improved; the blank that the precision and the standardization cannot be realized by conventional sensory analysis is filled.

A method, a program, and a device for evaluating food preference of pets that do not require humans to eat a pet food itself. The preference of pets can be evaluated by conducting sensory analysis on selected palatants contained in a pet food by humans. Accordingly, highly precise prediction of the preference can be made by a simple and intuitive method based on sensory attributes for human. Further, humans are not required to eat a pet food itself because the humans may conduct sensory analysis on selected palatants contained in the pet food.